IMPACT OF FOREIGN REMITTANCES ON GROWTH AND INCOME...

IMPACT OF FOREIGN REMITTANCES ON GROWTH

AND INCOME DISTRIBUTION IN PAKISTAN

FOUZIA JAMSHAID

09- arid- 1823

Department of Economics

Faculty of Social Sciences

Pir Mehr Ali Shah

Arid Agricultural University, Rawalpindi

Pakistan

2016

ii

IMPACT OF FOREIGN REMITTANCES ON GROWTH

AND INCOME DISTRIBUTION IN PAKISTAN

by

FOUZIA JAMSHAID

(09- arid- 1823)

A thesis submitted in the partial fulfillment of

the requirements for the degree of

Doctor of Philosophy

in

Economics

Department of Economics

Faculty of Social Sciences

Pir Mehr Ali Shah

Arid Agricultural University, Rawalpindi

Pakistan

2016

iii

CERTIFICATION

I hereby undertake that this research is an original one and no part of this thesis fall under plagiarism, if found otherwise, at any stage, I will be responsible for the consequences.

Student Name: Fouzia Jamshaid Signature:

Registration No. 09-arid-1823 Date:

Certified that the contents and form of thesis entitles “Impact of Foreign

Remittances on Growth and Income Distribution in Pakistan” submitted by Ms.

Fouzia Jamshaid have been found satisfactory for the requirement of the degree.

Supervisor: _____________________________

(Dr. A.Q. Mohsin)

Co-Supervisor: _____________________________ (Dr. Muhammad Ilyas)

Member: _____________________________ (Dr. Ikram Ali)

Member: _____________________________ (Dr. Aneela Afzal)

Chairperson:

Dean:

Director, Advanced Studies:

iv

DEDICATION

I DEDICATE THIS HUMBLE EFFORT TO

MY LOVING HUSBAND.

WHO HAS ALWAYS SUPPORTED AND HELPED IN

MY RESEARCH WORK

v

CONTENTS

Page List of Tables ix

List of Figures xi

List of Appendices xii

List of Abbreviations xiii

Acknowledgements xiv

Abstract xvi

1. INTRODUCTION 1

1.1 BACKGROUND 1

1.2 FOREIGN REMITTANCES AND PAKISTAN ECONOMY 5

1.3 RESERCH QUESTIONS OF THE STUDY 8

1.4 OBJECTIVES OF THE STUDY 12

1.5 HYPOTHESES OF THE STUDY 13

1.6 SIGNIFICANCE OF THE STUDY 13

1.7 ORGANIZATION OF THE STUDY 16

2. REVIEW OF LITERATURE 17

2.1 INTRODUCTION 17

2.2 THEORETICAL FRAMEWORK: LINKING FOREIGN

REMITTANCES TO ECONOMIC GROWTH AND INCOME

DISTRIBUTION

18

2.3 REVIEWING THE STUDIES OF EMPIRICAL NATURE

32

2.4 CONCLUSIONS 56

3. MATERIALS AND METHODS 62

3.1 INTRODUCTION 62

vi

3.2

3.2.1

ANALYTICAL APPROACH AND DATA SET FOR FOREIGN

REMITTANCES AND GROWTH

Justification and Implication of Variables

62

63

3.2.2 Analytical Framework 65

3.2.3 Data Description and Source 70

3.3

3.3.1

ANALYTICAL APPROACH AND DATA SET FOR

DISTRIBUTION OF INCOME VERSUS FOREIGN

REMITTANCES.

Income Distribution Indices (Measures)

71

72

3.3.2 Common Income Distribution Indices 72

3.3.3 Weighting System for Household, Income and Foreign Remittances 73

3.3.4 Model and Analytical Approach 74

3.3.5 Lorenz Curve and Gini Coefficient Analyses 77

3.3.6 Pre-Post Remittances Lorenz Curve 77

3.3.7 Gini Ratio by Ordinary Least Square (OLS) Method 78

3.3.8 Chow Breakpoint Test for Structural Stability 80

3.3.9 Data Description: Household Integrated and Economic Surveys

(HIESs)

80

3.4 STATISTICAL PACKAGES USED 82

4. RESULTS AND DISCUSSION 85

4.1 INTRODUCTION 85

4.2 RELATIONSHIP BETWEEN FOREIGN REMITTANCES AND

GROWTH

85

4.2.1 Unit Root Test 85

vii

4.2.2 Co-Integration Analysis 86

4.2.3 Error Correction Mechanism (ECM) 93

4.2.4 Diagnostic Tests 95


DISTRIBUTION OF INCOME

96

4.3.1 Percentage Distribution of Household Income and Foreign

Remittances

96

4.3.2 Gini Ratios and Lorenz Curves 106

4.3.3 Pre and Post Remittances Incidence (Keeping in view total

households)

107

4.3.3.1 Pre and post remittances incidences in Pakistan 107

4.3.3.2 Pre and post remittances lorenz curves in Pakistan 109

4.3.3.3 Pre and post remittances incidences in urban areas of Pakistan 109

4.3.3.4 Pre and post remittances lorenz curves in urban areas of Pakistan 113

4.3.3.5 Pre and post remittances incidences in rural areas of Pakistan 113

4.3.3.6 Pre and post remittances lorenz curves in rural areas of Pakistan 115

4.3.3.7 Rural versus urban pre and post remittances incidence 115

4.3.3.8 Gini ratios by OLS method. (Keeping in view total households) 123

4.3.3.9 Chow Breakpoint test for structural stability 123

4.3.4 Pre and Post Remittances Incidence (Remittances receiving

households)

127

4.3.4.1 Pre and post remittances incidences in Pakistan 127

4.3.4.2 Pre and post remittances lorenz curves in Pakistan 129

4.3.4.3 Pre and post remittances incidences in urban areas of Pakistan 129

viii

4.3.4.4 Pre and post remittances lorenz curves in urban areas of Pakistan 131

4.3.4.5 Pre and post remittances incidences in rural areas of Pakistan 131

4.3.4.6 Pre and post remittances lorenz curves in rural areas of Pakistan 136

4.3.4.7 Rural versus urban, pre and post remittances incidence 140

4.3.4.8 Gini ratios by OLS method. (Remittances receiving households) 144

4.3.4.9 Chow Breakpoint test for structural stability 146

4.3.5 Analysis of Total Households Versus Remittances Receiving

Households

146

SUMMARY 153

CONCLUSION 159

POLICY IMPLICATIONS 161

FUTURISTIC VISION 165

LITERATURE CITED 167

APPENDICES 185

ix

LIST OF TABLES

Table No. Page

1. Sample Size HIES, 2001- 02 83



4. Households Receiving Foreign Remittances 84

5. ADF Statistics at Level 87

6. ADF Statistics at 1st Difference 87

7. Optimal Lag Selection 89

8. Trace Test 91

9. Maximum Eigen Value Test 91

10. Long Run Coefficients of the Model 94

11. Short Run Coefficients of the Model 94

12. Distribution of Household’s Migrants among Income Quintiles Ranked by Predicted Average Household Income, with and without Foreign Remittances (HIES. 2001-2)

99

13. Distribution of Household’s Migrants among Income Quintiles Ranked by Predicted Average Household Income, with and without Foreign Remittances. (HIES. 2005-06)

101

14. Distribution of Household’s Migrants among Income Quintiles Ranked by Predicted Average Household Income, with and without Foreign Remittances. (HIES. 2010-11)

104

15. Pre and Post Gini Coefficients (Pakistan) 108

16. Pre and Post Gini Coefficients (Urban) 114

17. Pre and Post Gini Coefficients (Rural) 114

x

18. Pre and Post Gin Coefficients (Urban- Rural) 2001-02, 2005-06, 2010-11

124

19. Results for Lorenz Estimation (Urban- Rural) 125

20. Results for Lorenz Estimation in Pakistan 126

21. Chow Breakpoint Tests for Significant Differences in β Coefficients

128

22. Pre and Post Gini Coefficients (Pakistan) 130

23. Pre and Post Gini Coefficients (Urban) 135

24. Pre and Post Gini Coefficients (Rural) 135

25. Pre and Post Gini Coefficients (Urban- Rural) 2001-02, 2005-06, 2010-11

145

26. Results for Lorenz Estimation (Urban- Rural) 147

27. Result for Lorenz Estimation (Pakistan) 148

28. Chow Breakpoint Tests for Significant Differences in β Coefficients

150

29. Comparison for the Analyses of Total Households Versus Remittances Receiving Households.

152

xi

LIST OF FIGURES

Figure No Page

1 Relationship Between Variables 64

2 Graphical Representation Gini Coefficient and Lorenz Curves 79

3 Cumulative Sums 97

4 Cumulative Sums Square 97

5 Pre-Post Remittances Lorenz Curves, 2001.02 (Pakistan) 110



8 Pre-Post Remittances Lorenz Curves, 2001-02 (Urban) 116



11 Pre-Post Remittances Lorenz Curves, 2001-02 (Rural) 120



14 Pre-Post Remittances Lorenz Curves, 2001-02 (Pakistan) 132









LIST OF APPENDICES

xii

Appendix No. Page

A Some Concepts and Terminologies 185

B Unit Root Test 200

C. Johansen Co- integration Results 210

D. Error Correction Mechanism 213

E. Diagnostic Test 214

xiii

LIST OF ABBREVIATIONS

ADF Augmented Dickey Fuller

CONs

DSP

ECM

Consumption

Difference Stationary Process

Error Correction Mechanism

FBS Federal Bureau of Statistics

FIML Full Information Maximum Likelihood

FR Foreign Remittances

GDP Gross Domestic Product

GNP Gross National Product

HIES Household Integrated Economic Survey

INV Investment

LDC’s Less Developed Countries

IMP Imports

OLS Ordinary Least Square

OPF Overseas Pakistani Foundation

PSLM Pakistan Social Living Standards Measurement

SBP State Bank of Pakistan

SD Standard Deviation

SUR Seeming Unrelated Regression

VAR Vector Auto Regression

USA United Sates of America

ACKNOWLEDGEMENTS

First of all, I thank to Almighty Allah who bestowed me with determination to

complete this research successfully and durood- o- salaam on holy prophet Hazrat

Muhammad (Salala Ho Alihe Wasalam), who declared seeking knowledge obligatory

on every Muslim.

I am deeply indebted to my supervisor Dr. Abdual Qayyum Mohsin, Assistant

Professor, Department of Economics for his detailed and constructive comments and

for his valuable support throughout the research.

I am extremely grateful to my co-supervisor Assistant Professor Dr.

Muhammad Ilyas, who has lit my way to success. I am warmly thankful for his

valuable advice and friendly help. His extensive guidance around my work is

remarkable for his detailed and constructive comments and for his important support

throughout this work.

My humble submissions of gratitude to Dr. Abdual Saboor, Dean Faculty of

Social Sciences and Chairman, Department of Economics for his cooperation and

encouragement to start and complete this degree program. His wide knowledge and

logical way of thinking have been a great value for me. His help, stimulating

suggestions and encouragement facilitated me, in all the time of research process and

thesis writing.

I would like to express my deep and sincere gratitude to the members of my

Supervisory committee, Associate Professor Dr. Ikram Ali and Dr. Aneela Afzal

Assistant professor. Moreover, the keen observations of Quality Enhancement Cell and

Directorates of Advanced Studies are highly appreciable to improve the quality and

format of this thesis in line with the international standard.

My deepest feelings of gratitude for my father Atta Ullah Shaheen and my

mother Mrs. Safia Shaheen who are my first teacher and source of aspiration and

xv

guidance for me. I also want to express my gratitude to my mother-in-law Irshad

Begum for her prayers for my success. Their love, prayers and warm wishes endowed

me with the energy and vitality that was very much needed for the accomplishment of

this lengthy and extremely complex endeavour.

The acknowledgement and whole effort are meaningless if I do not mention the

worthy contribution and support of my husband, Jamshaid Ahmed Cheema. He

facilitated my work in diverse ways, at times through emotional support and other

times, keeping silent when he needed my attention, love and time. His praise and

guidance has been of great value for me in the study. Without his boost, help and

cooperation I could never achieve this success.

I owe all my gratitude to my daughters Nawal, Manal and Meshal for

understanding and forgiving me for not providing them care and quality time during

these years when I was so pressed for time for myself.

My special gratitude is also extended to my sisters Dr. Naheed Atta and Dr.

Noshaba Nadeem for sharing with me their academic experiences and engorging me

during difficult time.

Deserving my special thanks is my friend Dr. Gulnaz Hameed who facilitated

my work in one way or other. I am also thankful to Mr. Sajjad for helping and

resolving my computer related issues. My humble thanks to all those whom I could not

name but their prayer and love holds me in my difficult times.

(Fouzia Jamshaid)

xvi

ABSTRACT

A good chunk of factors affect the economic growth and distribution of income

of the economy. Inflow of foreign remittance to developing economies is of prime

importance. The purpose of the present dissertation is to evaluate the impact of foreign

remittances on economic growth and distribution of income over time in Pakistan.

Viewed in this context, this research was conducted in two steps. In a first step, the

study intended to test the hypothesis whether; there exist long-run relationship between

foreign remittances and economic growth in Pakistan during the period 1972-73 to

2012-13.

In the 2nd step, the study tested the hypotheses that the effect of foreign

remittances on the distribution of income has been in favour of high income groups by

comparing the HIESs 2001-02, 2005-06 and 2010-11. In order to quantify and

compare the impacts, this study employed various techniques in line with the

Johansen’s Co-integration, Error Correction Model, Two Stage Least Square, Gini

coefficient, Lorenz curve Ordinary Least Square and formal statistical Chow test. The

empirical results supported the hypothesis that foreign remittances appeared to be an

important source for long and short term sustainable economic growth. The estimated

results of the study also tend to support the other hypotheses that foreign remittances

deteriorated the distribution of income in overall Pakistan and its urban-rural areas.

Keeping in view the findings of the dissertation, the study suggests that it is

imperative for Pakistan to maximize the benefits of labor migration and its resultant

foreign remittances. The study also recommends that appropriate measures are deemed

xvii

necessary to attract maximum remittances to utilize their positive effects on economic

growth. For improving the distribution of income, government should take a

systematic approach to equip the lower and lowest income groups in order to enhance

migration opportunities for them. Moreover, to reduce the migrants cost and risk, the

government may establish migrants' network in the host countries by providing

financial assistance and guiding support to lower and lower income groups. A holistic

policy approach would be required both for short term adjustments and long term

planning keeping the changing dimensions of international labour markets.

1

Chapter 1

INTRODUCTION

1.1 BACKGROUND

People move to another country because of the differences of the real income at

home and abroad. They expect that, by migrating, there will be brighter prospects of

income and better living opportunities abroad as compared with the conditions inside

the country (advocated by traditional neoclassical approach). There is no question

about the importance of substantial real income dissimilarity as a movement of

international labor migration. In association with the costs of migration, according to

neoclassical theorists, large number of emigration that will have a constructive

influence on the part of origin because of their large involvement in economic well-

being of their home country. Not only of the individual migrants, but for the

community as a whole migration has enhanced the standard of living in the history.

One of the most important impacts of migration on source country is that of

money flows from the overseas employees to their home country, which are

considered as foreign remittances. Foreign remittances are that part of the payment of

labor, if we consider that labors are an exportable commodity. According to Galani et

al. (1981 a) “remittances may be defined as the part of earnings of workers while

abroad, sent back to home country from the host country”. Foreign remittances are

very important because they contribute a pivotal role in the economic uplift of

households and overall economic stability in the poor countries. The studies conducted

in the past show that most of the workers save and remit a large amount of their

2

income to their home country during their stay abroad (Stahl and Arnold, 1986 and

Athukorala, 1990). According to Arif (1999), “remittances are the most attractive

aspect of masses working abroad for the government of labor exporting countries and

to the individual migrants and their families.” According to Guinigundo (2007) “the

impacts of remittances can be observed at the macro and micro levels. At the macro

level, such as to strengthen the balance of payment position, raise international

reserves, increase domestic consumption, and contribute to financial sector

development. At the micro level, such as to alleviate poverty, income distribution,

higher human capital investment, and improving living conditions”.

The importance of foreign remittances to home country can be understood by

taking into account their major advantages and disadvantages. As far as advantages are

concerned, remittances play an important role in development strategies, poverty

alleviation, reducing inequality, improve the standard of living such as attainment of

necessities and luxuries, better health and education standards, reducing

unemployment, moderating the foreign exchange constraints and improving the

balance of payment position, increasing savings, investment and capital development

for economic growth. They can also significantly contribute in the fiscal and monetary

management for the labor exporting country.

At the same time, in contrast to these advantages, remittances are not cost free

as their flow has not been without socioeconomic problems, particularly for the large

segment of the population in developing countries. Foreign remittances are an

unreliable source of foreign exchange earnings because it is subject to immigration

policies and regulatory steps of the labor importing countries. Besides that, there is

3

hardly any impact of foreign remittances on investment and growth, due to their poor

planning and ill utilization. Moreover, increase in consumption due to demonstration

effect fuel up inflation at home. On the whole, foreign remittances create income

discrepancies and worsen the distribution of income at local level. Large home

remittances have also resulted as high flow of brain drain in many less developing

countries and these countries have always been deprived of the best talent to be needed

for their country’s development and prosperity. It has also been observed that foreign

remittances do not use for productive purposes and generally go into buyer goods

luxury items, construction activities, real estate, and share markets etc.

The present study undertakes an attempt to evaluate and analyze the impact of

foreign remittances on economic growth and on the trends of distribution of income in

Pakistan. The remittances may be classified as local remittances and foreign

remittances. However, the domain of this dissertation compels us to focus only on the

impacts of foreign remittances. Moreover, this study focuses on the direct (first order)

impacts of foreign remittances and ignores the indirect ( 2nd and 3rd order impacts of

foreign remittances on production and employment wages)

The term economic growth usually applies to less developed countries,

referring to “the steady process by which the productive capacity of the economy is

increased over time to bring about rising levels of national income”. National income

accounts of any country include foreign remittances as a component of Gross National

Product (GNP). As mentioned by Kazi (1989) “inclusion of remittances in GNP

underlines their importance among total resources in the economy”. The foreign

remittances have macroeconomic impact on output growth in which consumption,

4

investment, imports and GDP growth are affected. The foreign remittances are an

internal part of national income with GDP.

Review of literature shows that through a number of channels, foreign

remittances can positively influence economic growth. First of all, foreign remittances

might ease the credit limitation of household revenue thus the entrepreneurial

movement and personal investment can raise. Over and above physical investment,

remittances could also help to finance education and health, which are also key

variables in promoting (long-term) economic growth (Yang, 2004; Woodruff and

Zenteno, 2006). Secondly, the credit worthiness of a country could be improved by

the remittances and hence increase its admittance to global investment markets. World

Bank (2006) mentioned that the estimation of nation credit ratings by global as well

depends on its size of foreign remittance flows; this is a different mode to raise

equally material and human assets investment, thus, attracting economic growth.

Thirdly, remittance inflows through multiplier-effect mechanisms could

produce positive impacts on economic growth. On the other hand, the term “income

distribution” is generally coined to “picture who receives how much income within

a specific society”. In economics, distribution of income is how a nation’s entire GDP

be circulated among its populations. Distribution of income plays a vital role in

economic theory and financial strategy of any country. In the literature, economists

generally discuss two main concepts of income distribution, the functional and

personal or size distribution of income. Classical economists were mainly involved in

factors of income distribution, which is, circulation of earnings among the main factors

of production, (land, labor and capita). However, generally, economists are mainly

5

concerned with a size distribution of income across households and individuals. This

study also works with the range allocation of income to estimate effects of foreign

remittances in the country.

In terms of distribution of income, foreign remittances can directly impact on

poverty by increasing and improving the income of the households. Consumption of

the poor can be enhanced by the addition of that income. Not only its impact on

economic growth, but can also lift up the poor households’ standard of living and

reducing the poverty level. Foreign remittances also play a role in poverty alleviation

by increasing money supply to encourage the demand and increase consumption

expenditures which would finally assist households. Furthermore, foreign remittances

might resolve the investment constraints, thus the both substantial and human capital

savings of the country natives might be improved. The importance of the effects of

foreign remittances at different levels is realized. At the local level, remittances leads

to worsening the income distribution while at the national level, these may improve the

income distribution and help to reduce income inequality.

1.2 FOREIGN REMITTANCES AND PAKISTAN ECONOMY

In the beginning of 1970-71, as the trend of migration started, many workers

migrated to the Middle East and Gulf states because of the oil price boom. These

workers’ remitted, a significant amount of income to their home countries during their

overseas employment which created a boom in construction, personal consumption

and also reduced poverty. As a result, Pakistan received money remitted by migrated

workers about $ 50 million in 1970-71. In early 1980, remittances reached at peak in

Pakistan and considered to be golden period when around half of the remittance inflow

6

of South Asia were received. But in late 1980’s, the trend in remittances started

fluctuating over the time due to cheap oil prices with the deteriorating Arab economies

(up till 1990’s). The Gulf war also has influenced in the flow of remittances.

According to official channel, the flow of remittances has declined from $ 1467

million to $1086 million in 2000-01. The tremendous increase in remittances appeared

due to the 11th September event in 2001, when remittances reached to more than

double in Pakistan. The rapid expansion in the flow of remittances occurred due to

shift from the unauthorized to authorize or banking channels after the said incident. In

the financial year 2014-15, foreign remittance flow has been increased beyond $18

billion (State Bank of Pakistan, 2015).

According to official data, there are more than six million Pakistani living

abroad, most of them residing in the Middle East, Europe and North America. Pakistan

ranks 10th in the world for remittances sent home in 2012 with an amount of 13 billion

dollars. Pakistan receives remittances from the United State, the United Kingdom,

Australia, Canada, United Arab Emirates, Saudi Arabia, and the Gulf State of Qatar,

Oman, Kuwait and Bahrain. Still Middle East is the major contributor (Government of

Pakistan, 2012-13).

In Pakistan, like other developing countries, foreign remittances have become

an increasingly the prominent source of external funding. Foreign remittances emerged

as a main source of foreign exchange in Pakistan since export has been remained

stagnant for years. Remittances contribute over 4 to 5 percent of Pakistan’s Gross

Domestic Product (GDP) and equal to about twenty two percent of annual export and

goods (Economic Survey of Pakistan, 2012-13).Therefore, the foreign remittances

7

significantly influenced the Gross National Product (GNP) growth throughout the mid-

seventies, early eighties and first half decade of twenty first century.

These remittances flows in history have been important factors of Pakistan’s

balance of expenditure and have also shared to the increase the value of Pakistani

rupee value. Accordingly, remittances have been playing an central function in the

country’s exterior position and in conducting the exchange rate and monetary policies.

Qazi (2005) narrated, “In Pakistan foreign’ remittances also play a significant role in

alleviating poverty, reducing inequality, giving impetus to economic growth,

development and reduce current account deficit since long”. In the context of Pakistan,

Hyder and Mahboob (2006) estimated that an increase in foreign remittances as a share

of one percentage of gross domestic products is related to an appreciation of Pakistan’s

exchange rate by 0.16 percent. In the same way, Ahmed (2006) found that a 1 percent

increase in foreign remittances as a share of GDP appreciates Pakistan’s exchange rate

by about 2.5 percent.

In Pakistan, incomes inequalities have increased sharply in the 1990s and HIES

data also show that the trend is still continuing even in this decade. According to

annual plan (2005-06) of Pakistan “ household income or consumption by percentage

share that the lowest 10 percent of household’s receive 3.9 percent of total income and

the highest 10 percent households receive 39.3 percent of total income”. A report of

the US (2006) indicates that the Gini Coefficient for Pakistan is 0.68 and it is in the

range of 0.33 to 0.43 from 1987 to 1999. Income inequalities largely reflect

inequalities in the distribution of resources in case of Pakistan. Distribution of Income

in Pakistan is skewed as the poor have almost no assets and the lower middle-class

8

owns very few assets. There is uneven distribution of state, land, houses, plots and

other resources for the common people because they are not within their means. The

income inequality has increased severely in the last ten to 12 years in Pakistan and still

have upward trend.

The persistent strong rise in foreign remittances is mainly attributed to a rising

number of Pakistani workers going abroad for work. Foreign remittances have

contributed much to the Pakistan’s GNP and foreign exchange. Despite the strong rise

in foreign remittances since 9/11 in Pakistan has not translated into an improvement in

the economic growth and the distribution of income. In spite of the obvious and

significant benefits of foreign remittances for the economy of Pakistan, however, it is

important to evaluate their net impacts on domestic economy.

1.3 RESERCH QUESTIONS OF THE STUDY

Foreign remittances are primarily essential and secure cause of personal

inflows to developing countries as well as in Pakistan. Foreign remittances to

developing economies have been growing at a rather fast pace in current years. In 2013

foreign remittances remained appreciably higher than foreign direct investmentin

developing nations (apart from China). Officially recorded foreign remittances are $

430 billion in October, 2014. Foreign remittances grew by five percent to developing

countries in the period 2014. No doubt, for many developing countries they are the

main source of external funding. Still, no interest has been taken to evaluate the

economic effects of foreign remittances, particularly on the economic growth and the

distribution of income. Studies reveal that these foreign remittances can have

significant effects on the various factors in the developing economies, including

9

economic growth and the distribution of income. Foreign remittances are found to

promote economic growth (Stark and Lucas, 1998). These inflows have also led to

lower poverty and economic disparity in the country (Mughal and Anwer, 2012)

The literature for the effects of foreign remittances on economic growth of

beneficiary countries is contradictory. Some researchers believe that foreign

remittances may impact positively on the economic growth in beneficiary economies

(Zafar and Sattar, 2005; Pradhan, Upadhyay and Upadhyaya; 2008, Fayissa and Nsiah,

2010b). While other researcher emphasizes that foreign remittances may impact

negatively on the economic growth. Chami, Fullenkamp and Jahjah, (2003), Karagoz,

(2009), Siddique, (2010). Adding up to the argument, there are also researcher who

asserts that foreign remittances have no impact on economic growth of recipient

countries of developing economies (Barajas, Chami, Fullenkamp, Gapen and Montiel,

2009; Rao and Hassan, 2011)

There are different paradigms in both the empirical and theoretical literature

regarding the impacts of foreign remittances on economic growth. The theoretical

literature on the effects of foreign remittances can be divided into two major schools of

thought. These schools of thought consist of the “migration optimists” and the

“migration pessimists”. Migration optimists advocate for positive growth effects of

foreign remittances. They demonstrate the positive indirect growth effects of

remittances through economic channels such as increased savings, investment capital,

human capital investments, extra employment and the overall multiplier effects of

consumption on aggregate demand and output (Adenutsi, 2010, Nishat and Bilgrami,

1991). On the other hand, both the school of thoughts argue against the positive

10

growth impacts of foreign remittances. Migration pessimists believe that foreign

remittances may have either negative growth effects or zero impact on economic

growth. They oppose that foreign remittances are usually used for consumption as a

substitute of investments as said by the migration optimists (de Haas, 2007).

The literature for the impact of foreign remittances on the distribution of

income of beneficiary countries is also contradictory. The majority of research studies

find that foreign remittances lead to increase in income disparity and strengthen

existing inequalities since foreign migrants in general come from the upper ends of the

income classes. “Foreign remittances are found to increase income inequality,

especially for the rural dwellers” (Ravanilla and Robleza, 2003; Capistrano and Sta

Maria, 2007 and Adams, 2006). They believe that in the early stage of the migration,

migrants approach from the more well-off families who are more capable to get risks.

Further, according to the Migration Cumulative Theory “only the upper end of the

income distribution can afford migration costs and risks. Countries like Pakistan,

Bangladess and Thailand, migrants were found to have approached from a more

prosperous background, while those from poor classes could not manage to pay for

the preliminary expenses of migration. This implies that migration benefits the higher-

income classes and widen the income gap. This may not be true as most of the migrant

are blue collar workers. Perhaps, regulation to remit money also makes a difference.

In some countries migrants are not allowed to remit in cash. Most of the skiled

migrants prefer to invests in the destination country if rules allow them to do so and

hence not much is remitted to the country of origin. Literature shows that most of the

migrants come from only definite income groups. Usually migrants come from richer

11

families and from urban areas, implying that these migrants can afford the costs and

risks of migration. (Rodriguez and Horton, 1995). This implies that only people from

certain income classes go abroad and take benefits of migration and consequential

their earnings may not be distributed equally. Rather, income inequality may also

increase in the home country due to these remittances. Because migrants face both

monetary and psychological costs, and lower income group has already been

unacceptable and avoids to be considered for migration. Moreover, the opportunities

for migration may not always be equally available among different income groups. In

other words, foreign remittances are not always equally distributed among the

population. At the same time, other researchers find that remittances improve income

distribution. However, some research studies recommended that the harmful impact of

foreign remittances on the distribution of income cannot be expected, and may be

scattered over time if migration opportunities are attained to all income classes.

Due to the contrasting literature, it is not easy for one to conclude on the

effects of foreign remittances in a developing country such as Pakistan. Moreover,

emphasizing the growing importance of foreign remittances for the economy of

Pakistan, their effects on the domestic economy are relatively unknown. In fact, there

are few studies in Pakistan that examine the effects of foreign remittances on growth

and the distribution of income. However, it is critical to assess their net impacts on

domestic economy. In one direction by doing this to evaluate the impacts of foreign

remittances on both “economic growth and the distribution of income”. Due to

significant increase in the amount of foreign remittances in the economy over the

time, there is a need to examine its impacts as of the high level of inequality in the

12

Pakistan. Thus, the current dissertation is an attempt to answer the following questions

of the great interest.

- Do foreign remittances affect economic growth in the short- run and long-run

in Pakistan?

- Do foreign remittances serve to improve or worsen the distribution of income

among the households in Pakistan across urban- rural areas?

1.4 OBJECTIVES OF THE STUDY

The objectives of this study are specifically aligned with the stream of research

examining the effectiveness of foreign remittances for economic growth and income

distribution. In the light of previous research suggesting controversial impacts on

economic growth and controversial for the trend in the distribution of income. The

objectives of the dissertation are as follows.

- To analyze the short- run as well as the long-run relationship among foreign

remittances, gross national product, private consumption, private investment

and imports in Pakistan.

- To observe and compare the patterns of pre remittances distribution of income

of households with that of post remittances distribution of income in overall

Pakistan in three selected years, i.e. 2001-02, 2005-06, and 2010-11.

- To observe and compare the trends of the pre remittances distribution of

income of households with that of post remittances distribution of income in

urban- rural areas of Pakistan in three selected years.

- To suggest some policy measures for the effective management and utilization

of foreign remittances in order to enhance the pace of economic growth and

13

improve overall distribution of income.

1.5 HYPOTHESES OF THE STUDY

Beside the above mentioned objectives moreover, this dissertation also

attempts to examine the following hypotheses.

- There exists short-run as well as long-run relationship between foreign

remittances and economic growth.

- The effect of foreign remittances on the distribution of income in Pakistan is in

favour of high income groups i.e. pro-rich.

- The effect of foreign remittances is more pro-poorer in urban areas than that of

the rural areas in Pakistan.

1.6 SIGNIFICANCE OF THE STUDY

As the main purpose of economic development is the improvement in living

standards of a common man. Just to achieve the goal, economic growth would not be

sufficient because economic growth and distribution of income jointly determine the

development in the living standards of an ordinary man. As a matter of fact, with an

enhance in poverty in Pakistan during 1990s, the focus of research has been shifted to

evaluate the percentage of the poor rather than the on the whole distribution of income.

Policy makers are also engaged to reduce the proportion of the poor in the form of

poverty alleviation programs rather than taking appropriate measures to improve the

distribution of income as a whole. There has been an increase in the number of studies

based on the subject of foreign remittances in the past years. Nearly all of the studies

focused fully on the effects of remittances in developing economies in general. The

effecet of foreign remittances on economic growth and distribution of income has been

14

one of the important issues in economic literature. Even though foreign remittances are

quite large, there is no agreement in the literature about the effects of these monetary

transfers on the economic growth and the distribution of income. There has been a

difference of opinion among researchers about the positive and negative association

and its impacts on economic growth and distribution of income.

Moreover, very few numbers of research studies have been conducted

regarding the impact of foreign remittances with reference to Pakistan context. Most of

the available literature on foreign remittances in Pakistan concentrated only on the

impact of foreign remittances on growth and poverty. Existing work to estimate the

impact of remittances on the distribution of income shows that a few attempts have

been made. With the exceptions of Gillani and Iqbal (1981) Adams (1992) and Mughal

and Diawara (2012), no study has examined the impact of remittances on the

distribution of income. Gillani and Iqbal (1981) argue that on the whole remittances

caused worsening of the distribution of income. Adams (1992) uses samples of four

districts and establishes that there is no considerable effect of remittances on the rural

distribution of income.

There is a dire need for the study that assesses the impact of foreign

remittances on economic growth and the distribution of income which distinguishes

Pakistan from the rest of the developing world. However, this study is set out in two

steps to analyze its impacts on domestic economy by taking into account GNP growth

and trends or pattern in the distribution of income in Pakistan, which has been a

largely neglected area in this context. This study comes into complement the few-

available research studies on the growth effects and income distributional effects of

15

remittances in Pakistan. However, for the impact of foreign remittances on economic

growth this study in first step employs a macro-economic approach and uses large time

series data of forty years. This study employs a Co- integration approach in order to

see short-run as well as the long - run relationship among the variables. By using large

time series data and Co-integration approach differentiates it from earlier studies and

come up with justified and unbiased results on the growth effects of remittances in

Pakistan. Previously, no study has used this approach and analyzed the relationship for

a longer period.

In literature poverty, income distribution and economic growth are closely

associated. The more unequal distribution of income, the larger proportion of the

population living in poverty. Therefore, incomes at the top and middle of the

distribution are as equally important to us as the income of those at the bottom. In this

dissertation, it is, therefore, worthwhile to analyze the impact of remittances on the

entire distribution of income rather than considering just the base of distribution in the

domestic economy of Pakistan. Consequently the impacts of remittances appear to be

substantial and thus looking attractive for further research.

In the existing research, there is no consensus on how remittances impact

income distribution. These studies use different methodologies, surveys, data sets and

areas. Few studies focused only on the short-term effects of foreign remittances on the

distribution of income covering primary data or specific survey.In this regard, this

dissertation in its second component recognizes the importance of analyzing the

impact of remittances on the income distribution over a much longer time. Moreover,

this study observes the trends in the distribution of income by using three latest

16

household surveys for urban-rural areas and in overall Pakistan. Previously, no study is

available for employing the pre-post remittances analysis of the distribution of income.

Hence, by looking at a longer time span in the urban- rural area and in overall

Pakistan, the study helps in observing the trends and the patterns in the distribution of

income. Hence, this dissertation is of great scholarly help in preparing policy

recommendations for policy experts in Pakistan. Furthermore, this dissertation hopes

to add the accessible literature on foreign remittances, economic growth and

distribution of income in Pakistan.

1.7 ORGANIZATION OF THE STUDY

This research study presents four chapters. Chapter one focuses on the rational

and the background of the study, including the hypotheses, objectives and significance.

Relevant literature review related to foreign remittances, growth and distribution of

income are discussed in chapter 2. Chapter 3 dwelt upon the methodological issues,

specification of the models and explanation of the data used in this study. Chapter 4

offers the results and discussion regarding the foreign remittances versus economic

growth and the foreign remittances versus income distribution analysis. Finally, this

chapter also summarizes and concludes the study with policy recommendations for the

economy of Pakistan. Moreover, appendixes having different important related

concepts and data used in this study are also given. The references used in the study

are listed at the end.

17

Chapter 2

REVIEW OF LITERATURE

2.1 INTRODUCTION:

Review of the related literature has a benchmark importance in any research

work. This chapter deals with the review of almost all available previous theoretical as

well as empirical studies on a national level. On the issue of foreign remittances,

growth and distribution of income, a good number of international studies have also

been taken into consideration. It would make to understand the topic in depth. The

rationale of this chapter is to discover and ascertain the previous works in this field

which will enable us to point out that where the flaws and imperfections exist

generally in this study. It also gives answers to the questions such as what has been

carried out done and what would still to be conducted in this particular area of study.

According to Gail (1989), the review of literature in any field forms the foundation

upon which all future work must be built.

The literature review presented in this chapter provides a foundation on the

basis of which one can develop arguments in support of the methodologies proposed in

this dissertation. The chapter is separated into three key sections as follows. The first

section put forward the discussion of the theoretical literature and provides the

theoretical framework for linking foreign remittances, economic growth and

distribution of income for this dissertation. The second section reviews the empirical

research literature on the time-series, cross section and survey based analyses. The

third and last concluding section highlights gaps in existing literature and justifies the

18

contribution of this study to bridge these gaps. This section also highlights the

importance of defined arguments in the context of Pakistan economy.

2.2 THEORETICAL FRAMEWORK: LINKING FOREIGN EMITTANCES

TO ECONOMIC GROWTH AND INCOME DISTRIBUTION

Foreign remittances, economic growth and distribution of income are three

main concepts involve in the discussion and present in the dissertation. In the absence

of a theoretical framework the analysis of foreign remittances may not clarify the flow

or give guidance on the factors which would influence continuous inflows obligatory

for development and economic growth. This section helps to understand the theoretical

framework for analysis of the foreign remittances and their implications on the

economy and society. It also identifies some of the variables determining sustained

inflows for growth purposes. The section invites to categorize the determinants of the

level of migrants ‘remittance flows. The section of the thesis presents the theories

which are explaining for the unusual behavioral model of foreign remittances. This

conversation then followed by another discussion related to the brief theoretical outline

of the growth effects of foreign remittances. At the end, it’s followed by theoretical

discussion regarding income distribution effects of foreign remittances.

The issue of foreign remittances arises only because there has been an earlier

decision to migrate, thus the analysis of remittances cannot be separated from an

analysis of the factors which stimulate migration. These are different motives, such as

Motive for Self- Interest, Motives of Altruistic, Motive of Coinsurance and Motive of

Loan Repayment. There are two important factors for determining the level of

remittance flows. The OECD (2006) highlights the significant factors in the level of

19

remittances flows. Income and savings of the migrants is the first factor, which

manipulate the quantity of wealth they may be able to send to support the family. The

2nd factor which is responsible is the residence class of the migrants and their

intentions whether they stay permanently in the host country. The OECD (2006)

mentiones some of the significant factors for the intensity of foreign remittances are

network and the welfare effects of the migrant’s relatives.

The main issue is what are the motivators at the backside of the migrants to

remit, on the whole when they evaluate that how foreign remittances impact. In order

to counter the research question on the link among economic growth and foreign

remittances, it is essential that one carefully looks at the related objectives of the

migrants. Chami et al. (2003) pointed, “that there is a need to recognize the behavioral

patterns of foreign remittances to see how can foreign remittances really impact on

financial and economic growth. These motives and behavioural patterns have been

twisted into theories of macroeconomic to understand the trend in the flow of foreign

remittances”.

The most recent studies claim that self-interesting motives exist for remitting.

Migrants will engage their family members for investment in the home country as their

agents. Stark (1991) as well as Agarwal and Horowitz (2002) and Gubert (2002) argue

“that the family can do something as an insurance company that protects its members

against income shocks by verifying the sources of income”. Apart from of the motives,

the volume of foreign remittances also play important role in the determination of the

income. If higher the income, the larger would be the foreign remittances into the

20

home country. Even if foreign remittances at first sight emerge to be really self-

interested, the system may be an altruistic one.

With regard to the effects of foreign remittances on the economy of the labour

sending country in the literature, there are two special viewes: the optimistic view and

the pessimistic view. The first one aspects foreign remittances as mechanisms for

development and economic growth, it comes as of the neoclassical migration theory

the development optimistic view dominated throughout the 1950s and 1960s. “The

common hypothesis the supporters of this theory generate is that flows of foreign

remittances as well as experiences, aptitude and consciousness that migrants attain in a

foreign country will improve development in the recipient countries” (Adenutsi, 2010,

Anaynwu and Erhijakpor, 2010).

The Neoclassical economists also situate, migration into an optimistic light. In

the Neoclassical model of balanced growth, migration is method contributing to the

optimal distribution of factors of production, which help all uniformly both countries

of origin and the recipients. Especially the take-off in the economic sense is expected

to thrive because migrants would be expected to invest great capital into enterprises in

the countries of origin (de Hass, 2007).

In the late 1960s, a new point of view on the subject of foreign remittances,

migration and development come out. “The theory arises from a conversion in social

sciences in the direction of more structural views” (de Hass, 2007). “This theory

suggests that the net effect of migration and foreign remittances does not promote

sustainable development” (Adenutsi, 2010). In addition, this theory implies that the

deprived do not have sufficient money to move abroad because of the expenses

21

associated to migration, such as travelling costs. Adenutsi, 2010, Chami et al, 2008, de

Hass, 2007). This would imply that foreign remittances might increase the income gap

in developing countries even further. Moreover, it argued that foreign remittances

would not be used upon attracting investment, as optimistic view would imply.

Also, Nishat and Bilgrami, (1991) have concluded that remittances indicate

strong positive impact on economic growth, the larger impact on private consumption

and smaller on private investment. Ratha (2003) has recommended “that foreign

remittances that raise the consumption levels of rural households might have large

multiplier effects because they are more likely to be used up on locally produced

goods”. However, as for countries with low gross domestic products foreign

remittance receipts can alter the functions of recognized capital markets and also

undermine exchange rate regimes through the establishment of equivalent money

markets.

Foreign remittances used for as the core resource of foreign exchange income

and stand for in surplus of ten percent of Gross National Product for a lot of countries

(Juthathip and Jongwanich, 2007). At the macro level, Adam, Page and Elasaka(2003,

2004, 2005) show the poverty reduction impact of foreign remittances and also show

that a 10 percent increase in foreign remittances in a developing economy decrease

the poverty by 3.5 percent in that country. Policymakers can take help from such

impacts for future policies to generate more flow of remittances.

The uses of foreign remittances are widespread and not simple to grip.

According to Lucas (2004), “foreign remittances can directly affect poverty through

the rise of the income of the recipient, which in turn smoothen the consumption of the

22

poor and alleviates poverty”. The foreign remittances can control the poverty in some

direction through their impact on economic growth, in addition to, on the distribution

of income and human capital growth. Lipton (1980) points out that income distribution

worsens due to foreign remittances. Milanovic (1987), Adams (1989) and Talor (1992)

explain in their empirical work that foreign remittances made the income distribution

worsened. On the other hand, Anyanwu (2011), Barham (1992), Ahlburg (1996) and

Handa and King, (1997) view that foreign remittances largely reduce income

inequality.

Foreign remittances raise the family incomes at the family level, Hence raising

savings and private consumption of durable and nondurable products. Definitely,

foreign remittances are division of a personal wellbeing system that transfers resources

from comparatively wealthy to comparatively poorer houshods of a family. “They

reduce poverty, smooth consumption, affect labour supply, provide working capital,

and have multiplier effects through increased household spending. For the most part,

foreign remittances seem to be used to finance consumption or investment in human

capital, such as education, health, and better nutrition” (Lopez-Cordova, 2004;

Hildebrant and McKenzie, 2005; Adams, Cuecuecha and Page, 2008).

Hence, the outcomes are gained as of these foreign remittances are depended

upon the way how the leftbehinds are used up them. Chami et al (2005) “argues that

migration and associated remittances may create a moral hazard problem, inducing

disincentives to work among migrant household members” (Azam and Gubert, 2006).

Along the societal side, Rodriguez (2000) argues “that remittances have, quite apart

23

from increased family tensions within families but also with migrants. It also

associated with moral hazard problem”.

2.2.1 Foreign Remittances and Economic Growth

In many circles it has been discussed that the impacts of foreign remittances on

economic growth of the country and be inclined to disagree with every one. “The

biggest and the most contested issue whether foreign remittances are saved or

consumed. Migration optimists believe that remittances are saved and generate

important capital for development in an economy. Migration pessimists counter such

thinking and argue that foreign remittances are mainly used to consuming thereby

having limited or no bearing on economic growth” (de Haas, 2007).

According to one school of thought which perceives foreign remittances as an

main cause of development capital discuss “that foreign remittances used for

consumption can still result in increased economic growth as a result of multiplier

effects on aggregate demand, which have a positive bearing on total output” (Brown,

2006, Gupta et al., 2008, Pradhanet al., 2008, Ratha, 2003).

Moral hazard problem of foreign remittances that negatively affect labour

supply pointed by the school of thought related to remittance pessimists. “In this

situation, foreign remittances are thought to be a disincentive to work” (Chami et al.,

2003). One more conflicted question regarding the issue of that the extra demand

created by foreign remittances increase or lower consumption.

Those in favour of remittances believe that such additional demand can

generate more employment (OECD, 2006): Whereas, those in opposition to

24

remittances argue that the additional demand causes inflationary pressures in the long

run that may have negative employment effects (Catrinescuet al., 2009).

2.2.2 Foreign Remittances and Distribution of Income

Having reviewed the effects of foreign remittances on economic growth, it

is now essential for the researcer to concentrate on income distribution effects of

foreign remittances as these have been discussed in the literature. Economists have

shown interest in income distribution from the beginning of economics as a separate

discipline, although their interests vary over time and space, and from person to

person. Classical economists’ claim that the distribution of income has primary

importance and it is the distribution of income between the main factors of production.

Some other economists concern with the size distribution of income which indicates

the distribution of income across households and individuals.

There are only three groups in society according to theories based on functional

distribution. There are some other concepts of income distribution also used for the

study of income inequality. That makes help in the distinction between urban groups

and rural areas. Up till now the theoretical argument regarding income inequality

related to the two main ideas of functional and size distribution of income.

Moreover, income classes of the migrants have impact on amount of foreign

remittances and the distribution of income. If migrants, generally related to relatively

well-off, then their foreign remittances may have worsen impact on income inequality.

On the other hand, if migrants are belonged to the lower classes, then foreign

remittances may add to larger income equality.

25

Therefore, “the effect of foreign remittances on the distribution of income over

the time depends on how information and factors that make possible migration become

diffused through the population. If access to these factors easily extend across

households, then migration and hence the receipt of remittances by those at the lower

ends of the income distribution is likely to occur, possibly reducing the initially

unfavorable effect of remittances on income inequality” (Stark, Taylor and Yitzhaki

1986).

Furthermore, the types of labour or skills demanded abroad may change with

the passage of time, depending on the developments in the labour markets of the

receiving economies. These shifts in demand for migrant labour may in turn determine

the income distribution in the sending nations. For instance, if the demand for labor

abroad shifts towards those occupations that require lower skill and education levels,

then migration opportunities are opened up, especially for those in the lower income

brackets, who may be constrained from acquiring higher skill levels. In this case,

migrants’ remittances may contribute to greater income equality.

A large part of theoretical literature has been erected around the concept of

functional distribution of income. The functional distribution shows how much income

is received by each factor of production. This is how total income is distributed

between land, labor and capital. Theories based on functional distribution consider the

existence of only three groups (or classes) in society: laborers, capitalists, and

landowners, assuming within group homogeneity. It elaborates the share of total

national income that each factor of production receives. Process of functional income

distribution requires the comparison the percentage that labor receives as a whole with

26

the percentage of total income distributed in the form of rent, interest and profit. The

actual process can be illustrated by the firm-individual relationship. At first the flow

from the firm to individuals, who are the owners of the factors employed. The landlord

receives his rent, the worker his wages, the investor his interest and profits.

The war of tug between entrepreneurs and workers springs from the conflict of

interests present among them. As, it is well known, the profit is the residual balance of

the activities of the firm or, saying more precisely, is the share of entrepreneurs. So,

the quantum of this residual depends upon the payments made to other factors, that is,

if wage, rent and interest rates are decreased (increased), the profit will be increased

(decreased). Remember that the profit also varies with the prices of commodities and

services produces by the firm, but it is not poining to be concentrated in our present

discussion.

It is obvious from the interdependent nature of profit with other rewards that

the willingness of entrepreneur to hire factors of production in such proportion, which

gives him a larger share in the enterprise, plays a major role in the distribution of

rewards. The theory that explains the extent of the willingness of entrepreneur in

hiring factors of production is termed as “marginal productivity theory of factor

prices.” This theory elaborates that factor will be rewarded well or ill according to its

contribution to the total product or revenue of the firm.Formally, marginal productivity

theory can be defined as the increase in total revenue or total output of the firm

resulting from the employment of an additional (last) unit of the factor. The

specification of the term additional unit with the ‘last unit’ necessitate that the

27

marginal unit of the factor is the unit the entrepreneur has just hired, in an expanding

industry; or is about to discard in a contracting industry.

It is clear that the demand for factors is created by entrepreneurs in the factors

market and this demand is a derived demand, which arises not due to the factors are

demanded for themselves, but for what they can create: goods and services. This

process bestows the entrepreneur maximum profit through the channel of last cost

combination of the factors and the greater revenue from the sale of these goods and

services. So, if demand for final goods and services. So, if demand for final goods and

services produced by a firm is higher (lower) than the demand for the factors

producing those goods and services by the firm will be higher.

There are many criticisms of the marginal productivity theory; but we explore

those, which serve our purpose of shifting the discussion from functional to the size

distribution of income. To judge a country’s performance, empirical verification by

using facts and figures is unavoidable, marginal productivity theory of distribution on

the other had possessed mostly theorizing style and very little bother for empirical

verification.

Hence, functional distribution is less helpful in an empirical work of our type,

especially, where horizontal and vertical equity are the objectives of a national

government. Furthermore, grouping of factors with different incomes is also difficult.

For example, groups of workers with identical skills, who are paid alike, difficult to

construct practically due to the difficulty of identifying better and worse workers with

common skill. So some workers in that skill will be paid more; some will be paid less

28

than their actual individual marginal products. Similar difficulties can be seen in the

grouping of workers of a given sex, age and educational qualification in a particular

industry, where firms may pay these groups same wages. Especially, in the beginning

due to the problem of accurately measuring the marginal products of individuals.

All the above problems can be avoided by adopting the idea of size

distribution, particularly, when one wants to judge empirically the effect of

government programme upon different income groups of the society as a whole.

Concept of size distribution of income also bestows the researchers different tools;

like, Lorenz curve and Gini concentration ratio, for examining the degree of fair of

worse distribution of income. Needless to say, the above outcomes of the concept of

size of distribution of income have made easy to examine the poverty conditions of a

country at an aggregate level.

Playing the final round against functional distribution of income, a person may

be the employee of a firm but, at the same time, he is earning interest from his

investment or he may have inherited property that can comprise many forms. For

example, fertile land, commercial land, residence building given on rent etc. so it will

be difficult to categories him rightly.

The only solution is to divide all individuals not on the basis of their sources of

earning but on their earning. This above notion leads us to a precise definition of

personal or size distribution of income, which can be defined as, “It is a measure that

solely deals with individual person or households and the total earning they receive,

while ignoring their sources of income”. It means that no matter the incomes in the

29

pockets of persons or households are derived from employment only or from other

different sources like profits, rents, interest, inheritance, gifts and so forth, they are

grouped according to their quantum of incomes and not according to the different

channels by which their earnings move into their pockets.

Also, the occupational sources of earning like trade, manufacturing,

agriculture, services and the spatial consideration or location are shrugged off.

Moreover, number of working hours, sex, age, educational qualification, skill,

experience, status and other items of these types deserve no attention. For example, if a

person A is more qualified than a person B, but they possess same quantum of earning,

then they will be adjusted in the same group irrespective of the difference in their

qualification. Same is the case with other items.

The procedure of constructing a size distribution of income for a country is

very simple. Firstly, different income groups, each having some particular income

ranges, are ordered in ascending fashion. And then, according to their personal

incomes, all individuals or households are adjusted in different income groups, having

definite income ranges.

This process gives a column of income groups in ascending order. The second

column is of personal income, which is usually taken in percentage; this column

determines what proportion of total national income each income group receives. “At

the beginning of a country’s migration history, when few households have just started

establishing contacts at the receiving economy, the distribution of remittances is

necessarily unequal” (Stark, Taylor and Yitzhaki 1986). There are many observable

30

facts. One is that, during this time, information about the working conditions abroad is

scarce and costly; because of the uncertainty that this creates, migration, in a sense,

becomes a high-return yet high-risk investment. Therefore, the first households that

will vest in a migration decision are likely to occur from the upper rungs of the income

distribution, since they are more financially able to take on its costs and perils.

In addition, to mention here that migration is demand-driven, any inequality in

the distribution of income puts those in the lower-income classes at an even greater

disadvantage. Working abroad may require specific skills, a certain level of education

or experience, and even English proficiency, depending on which foreign labour

market or occupation opens its doors to migrant labour. Thus, unless the low-income

classes can afford to acquire the skills and levels of education demanded by overseas

workers, then migration may remain to be a valid option only for those in the high-

income classes.

The impact of foreign remittances in the overall household distribution of

income at this early stage, therefore, depends firstly upon the amount of foreign

remittances in relation to income from other sources. If remittance-receiving

households depend significantly on foreign remittances to boost their income, then the

distribution of foreign remittances is expected to greatly contribute to the distribution

of income. If, on the other hand, foreign remittances represent only a small part of

household income, then remittances will have a minimal effect on income distribution.

Ahluwalia and Chenery (1983) associate the variations in income at the lower

levels with the lack of human skills, physical capital and access to them. Attansasio

and Sekely (1999) document that income inequality in Latin America is, to a large

31

extent, a reflection of a very skewed distribution of income generating assets.

Therefore, asset distribution cannot be disregarded when assessing the effects of

economic growth on income inequality.

Finally, successful migrants make available important information to those left

behind, and this may raise the latter’s tendency to migrate. These would-be migrants

now are feeling more relatively deprived of, will also want to migrate in order to shift

the distribution of returns to migration in their favour. Moreover, the early migrant

makes migration a much more worthwhile undertaking because the information they

bring reduces the risks and uncertainty associated with it. In some instances, too, early

migrants provide direct assistance to new migrants by financing the costs of migration,

especially for family and friends. In other words, migration flows tend to create a

“migration chain” that generates opportunities for later migration (Tan 2000)

Therefore, the effect of foreign remittances on the distribution of income over

the time depends on how information and factors that make possible migration become

diffused through the population. If access to these factors easily extend across

households, then migration and hence the receipt of remittances by those at the lower

ends of the income distribution is likely to occur, possibly reducing the initially

unfavorable effect of remittances on income inequality (Stark, Taylor and Yitzhaki

1986).

Furthermore, the types of labour or skills demanded abroad may change with

the passage of time, depending on the developments in the labour markets of the

receiving economies. These shifts in demand for migrant labour may in turn determine

the income distribution in the sending nations. For instance, if the demand for labor

32

abroad shifts towards those occupations that require lower skill and education levels,

then migration opportunities are opened up, especially for those in the lower income

brackets, who may be constrained from acquiring higher skill levels. In this case,

migrants’ remittances may contribute to greater income equality.

This should partly explain the divergence of views about the effect of foreign

remittances on income inequality, because the empirical studies did not temper their

conclusions with the fact that the observations were made in distinct and specific

stages of the migration process. Moreover, because the impact of foreign remittances

and income inequality is state-specific, looking at longer span of time logically

suggests that this impact may also change over time. More explicitly white remittances

do seem to worsen income inequality at the start of the migration chain, they may be

expected to gradually reduce inequality, as more people from the lower ranks of the

distribution are enticed and are able to migrate.

REVIEWING THE STUDIES OF EMPIRICAL NATURE

For the relationship among foreign remittances, growth and distribution of

income, the is lot of empirical literature is accessible. The performance shown so far in

Pakistan on the issue of remittances, growth and income distribution is restricted in

range as compared to other labor exporting countries. It would be helpful to evaluate

some of the previous national and international, academic as well as experimental

studies, which would make us to understand the subject in detail. This will also enable

us to investigate the restrictions of the preceding work in this area. For a more

comprehensive study, the literature is divided into two parts. The first part is related to

time series analysis about the foreign remittances and economic growth, relationship,

33

second part is related with cross sectional and survey based analysis on the remittances

and trends in income distribution.

2.3.1 Foreign Remittances versus Economic Growth (Time Series Analysis)

Gilani et al. (1981) widely discussed the issues related to the topic of migration

and foreign remittances in the economy of Pakistan. Their study used primary data and

based on the cost-benefit analysis of labor immigration. They took a sample of 15,000

migrants and their kings. For this purpose they included a sub-sample covering 250

villages, 50 towns and cities. They used simple methodology for determining the entire

number of migrants. These total migrants were urban as well as rural. They classified

the flow of remittances into three categories and uses of remittances into five

categories. They used only direct costs and benefits for each item and they concluded

that the net effect is constructive. Based on study findings, they concluded and

recommended that policy makers should handle the bottlenecks for the labors. They

also concluded that consumption takes a big share, but savings are also subjective,

mostly when retained funds of workers are incorporated.

Rashid (1986) for the impact, in his study used the survey data from Pakistan

(ILO/ARTEP Phase-II Migration Study). He proved to link up the uses of remittances

by the migrant household with the overall growth of the state. The uses of remittances

were carefully analyzed by the author in detail. It was observed that foreign remittance

financed major part of cumulative consumption, housing and other investments. He

also observed that growth standards in construction, small scale manufacturing,

communication and transport. The flow of foreign remittances also positively

34

influenced the retail trade and wholesale trade. The empirical result of his study

support the results of other studies.

Burney (1987) studied the macro economic impact of foreign remittances by

using the time series data for the period 1969-70 to 1985-86 for the economy of

Pakistan. His work focused on the effects of foreign remittances on some

macroeconomic variables. At the same time, by the estimation of magnitudes of these

remittances, he has originated, that in short-period exchange rate policy has major

positive pressure on the flow of foreign remittances, whereas in the long-period,

economic activities in the Middle East mostly determine foreign remittances. The

author considered the real remittances, which include both authorized and

unauthorized. To maintain a reasonable economic growth, the inflow of foreign

remittances has helped the Pakistan’s economy. The author found in his study that

foreign remittance inflow and Gross National Product and economic growth are

extremely associated.

He also found that the average annual growth rate (GNP) during period under

consideration was the maximum i.e. (eight percent). Conversely, during 1982-83 to

1985-86 due to quickly turn down in foreign remittances the average growth rate of

Gross National Product (GNP) also decreased from 8.0to 6.0 percent. He concluded

that saving and investment must have a positive relationship with remittances. But

after estimating regression equation, the author found that there did not appear to be

any systematic relationship between remittances, saving and total fixed private

investment because the economy as a whole is not utilizing the remittances to enhance

the capital stock in the economy. At the end, he also concluded that there may happen

35

simultaneity problems while estimating the magnitudes by ordinary least squares

(OLS) method. Therefore, in his study, he used a simultaneous equation system for

estimating different variables.

Quibria (1987) highlighted the issues on the subject of foreign remittances and

economic development. Due to the oil boom of 1973, the Middle East (ME) emerged

as a “growth pole” within the developing world. It was also followed by a construction

explosion in these countries for which their own labor force was scarce. Many Asian

countries took advantage of this, especially after 1975. Foreign remittances and its best

use for economic development purposes will continue to be a main policy thought for

many Asian labor exporting countries. Many factors and policy packages influenced

on foreign remittances. The crux of this study gave some insights into the

responsibility of migrants and the foreign remittances in the economic development of

the developing labor excessive Asian economies. The author recommended some

policy directions to all Asian economies that labor market handling must be made

accordingly. He further added the employment policy should accomplish the

prerequisites of the migrating economy and also exchange rate policy and financial

services to migrants for capturing high rate of foreign remittances is needed.

Kandi and Metwally, (1990-91) they studied the impact of migration and

foreign remittances on the economy of Egypt. With the help of annual data from 1970

to 1984, they estimated the Keynesian macroeconomic simultaneous model by using

Three Stage Least Square (3SLS) assessment techniques. The authors anticipated the

reduced from the equation of the Seemingly Unrelated Regression (SUR) and

Structural model techniques in their study. This study related to the multiplier analysis

36

of foreign remittances to Gross National Product and through its main components. It

was also concluded that foreign remittances have a positive impact on Gross National

Product but the impact of rise in foreign remittances diverse across the different

variables of Gross National Product (GNP). Remittances have more positive impact on

consumption and minimum impact on private investment. This study is mostly

concerned with the positive aspects and left out the negative

Nishat and Bilgrami (1991) tried to determine the impact on Pakistan’s

economy. The authors used the annual data for the time period of 1959-60 to 1987-88

and analyzed the impact of foreign remittances for the economy of Pakistan. They

practiced a simple Keynesian Structural Model for estimation of the remittances

multipliers in Pakistan. They estimated the structural equation using 3SLS techniques.

The authors used the results of a model to estimate the magnitude of marginal

propensities to consume, investment and imports. They used these magnitudes to

estimate the impact of a rupee increase in remittances on national income of Pakistan.

They concluded that the results indicate strong positive impact on GNP. They also

showed that remittances indicate that larger impact on private consumption and

smaller on private investment. Their study originated a multiplier of the magnitude 2.4

which operated on, mainly from side of consumption.

Nawab and Javed (1997) evaluated the impact of remittances on the economy

of the home country and its macroeconomic variables e.g. private consumption, private

investment and imports. For this purpose they utilized Keynesian macroeconomic

model developed by Kandil and Matwally (1990) and modified the model by

incorporating some explanatory variables in it. They used annual data from 1971-72 to

37

1993-94 and estimated model by Three Stage Least Square Technique. They

concluded that remittances had a strong positive impact on GNP in Pakistan. They

added that remittances also had a positive impact on the private consumption, private

investment and imports. The results were further clarified by estimating the reduced

form equation and the structural model with Jointly Seemingly Unrelated Regression

Method, where coefficients were found statistically significant at a reasonably high

level. They suggested that the government should take measures to attract the

remittances and build firm promises to enhance the saving rate. They indicated that the

government should not close the eyes for the rural expanses of Pakistan as the larger

proportion of migrants is from rural surroundings.

Arif (1999) examined that foreign remittances and investment at the household

level using survey data on homecoming migrants. His study showed that propensity of

Pakistani migrants to remit was extremely high 78 percent. The bulk of the workers,

even if their period of stay out of the country were long remitted about three quarters

of their earnings. In this research, the author analyzed that workers and their families

did direct a significant amount of foreign remittances into saving and investment when

migrant had been out of the country for long periods. This study also showed that the

investment and saving of the migrants were determined by different factors.

About remittances, he concluded that the proportion of remittances saved was

substantially greater among rural households than among urban households. He also

found that factors that were responsible for directing remittances to investment were:

the procedure of employment, including the price of migration and sources of its

financing, pre migration family’s economic position, the human capital of the migrants

38

and marital status. It appeared that education provided them with better contact with

the information and knowledge essential for coping us with the new demands placed

on them by migration. It was concluded by the author that the higher the education, the

greater the prospect of using remittances productively. He suggested that investment

related information should be provided to the migrants’ families. Some attractive

schemes should be launched for the migrant workers. Migrants and their families

should be educated in a way that they can learn how to utilize the resources in a better

constructive way.

Glytsos (2002) examined the dynamic effects of foreign remittances on

economic growth of Mediterranean countries, including Egypt, Jordan, Morocco,

Greece and Portugal using simultaneous equations Keynesian macro econometric

model for the time period of 1969-1998. The impact and dynamic multipliers were

calculated from reduced form equations of income, investment, imports and

consumption functions. The results specified that the effects of foreign remittances

were differentiated in sizes, but not in nature in different countries. Therefore,

remittances are signs of country specific conditions. The study also highlighted that

remittances bad effect more when decreasing, but good effect is less when increasing.

Sattar and Zafar (2005) in their studies, attempted to give an answer to the

main economic issue whether foreign remittances impact on economic growth of the

economy of Pakistan. They used the latest time series data for the years 1972-73 to

2002-03. The multiple regression framework was used to see the effects of foreign

remittances on some macroeconomic factors on actual GDP growth. The results of

their analysis are spokesperson of current research for the determinants of growth. The

39

quantitative evidence showed that real GDP was positively related to worker

remittances during 1972-73 to 2002-2003. It was found that worker remittances

ppeared to be the third important source of Capital for economic growth in Pakistan. In

the regression result, it was found, that there were only some factors which negatively

affected economic growth of a country during 1972-73 to 2002-2003. For example,

inflation and external depths were also negatively related to economic growth. Their

studies focused out macroeconomic effects of remittances flows on economic growth.

They analyzed the effect of remittances on the real GDP previously there is no such

type of micro economic study or analysis.

Jacques, Bouhga - Hagbe (2006) showed in the cross country study that

foreign remittances are equal to about twenty two percent with the share of exports of

commodities and services in Pakistan. Moreover, these flows are very significant part

for Pakistan’s balance of expenditure and also strengthening the currency of Pakistan.

As a result, foreign remittances participating a significant function in the country’s

exterior situation and manipulate the conduct of economic and exchange rate strategy

in the country. The study showed the direct link between the observed variables.

Karagoz (2009) examined in his study the connection between foreign

remittances and economic growth in Turkey. This study used panel data for the period

1970-2005. The time series regression results revealed that foreign remittances flow to

Turkey have statistically important, but negative impact on the economic growth but

exports and domestic investment positively affect the economic growth. The study

used the Model developed by Chami et al (2003). The study used per capita GDP,

Gross Capital information (Gross Domestic Investment) and Net Capital inflows as

40

variables. This study used the level, rather than growth, of foreign remittances to GDP.

The Ordinary Least Square applied and originated the results. The results discovered

that per Capita GDP and the foreign remittances ratio to Gross Domestic Product were

negatively interrelated in Turkey. The result is as that of same like Chami et al (2003)

which points out moral hazard problems can strict to decline economic activities.

Muhammad and Ahmed (2009) examined as case study for the effects of

foreign remittances on economic growth, of Pakistan. They utilized time series data

from 1973 to 2007. They collected the data from annual reports of the State Bank of

Pakistan and Federal Bureau of Statistics of Pakistan. This study used level of income

of GDP and foreign remittances. The study used level of income (GDP plus

remittances), consumption, investment and imports as variables. The study used

Keynesian type simultaneous econometric model with a dynamic perspective. They

used impact multipliers for short run relationship and dynamic multipliers for long urn

effect. The results showed that investment is highly significant positive coefficient of

income. The consumption and imports are also positively affected by income. In long

run results showed that foreign remittances affect output growth positively through

multiplier process.

Siddique (2010) in the study of foreign remittances and economic growth;

Empirical evidence from Bangladesh, India and Srilanka examined the causal link

between international remittance and economic growth. This study utilized time series

data from 1976 to 2006. The data were taken from World Bank publication. The study

used remittances per capita and GDP per capita for all three countries. The authors

employed Granger causality test under a Vector Auto Regressive method (VAR)

41

framework (Granger 1988), Unit root Test and Co-integration. The analysis reveals

that both time series, remittance and economic growth are I (1) and are not co-

integrated. They found that growth in foreign remittances did lead to economic growth

in Bangladesh and it is only a one way causal relationship. In India there is no causal

relationship between growth in remittances and economic growth. But in Srilanka a

two way directional causality is found. It means in Sri Lanka economic growth is

being influenced by growth in foreign remittances.

Sami (2013) investigated the role of remittances, banking sector development

and economic growth in Fiji. The study used time series annual data from 1979 to

2010. The data were obtained from World Development indicators (2011). The author

used Bound Testing Procedure developed by for examining co-integration relationship

between remittances and banking sector development. He also used the Vector Error

Correction Model (VECM) and Toda Yamamoto Granger Non Causality test for

causality analysis. The study established long urn relationship between foreign

remittances, economic growth and banking sector development. This study suggested

that there is causality from economic growth and remittances to banking sector

development. The economic growth is measured by real GDP per capita. Banking

sector development is measured as a ratio of domestic credit to the private sector as a

percent of GDP, which shows the quantity of investment from the banking sector. In

this study foreign remittance and economic growth are long run, forcing variables and

banking sector is controlled variable. The study revealed that foreign remittances are

imperative for economic growth and banking sector development.

42

In addition, similar to the academic literature, empirical literature is as well

very contested. In the observed literature there are unusual and contradicting results

about the impacts of foreign remittances on growth coming out of the studies. This

makes it hard for the researcher to draw any results on the basis for how foreign

remittances impact on the economic development of beneficiary countries.

2.3.2 Foreign Remittances versus Distribution of Income (Cross Section and

Survey Based Analysis)

A vast variety of empirical research studies on the topic of foreign remittances

and distribution of income have been conducted in the developing world, this link

study, investigate the mentioned nationwide and worldwide studies to observe their

capacity and deficiencies for achieving their main objectives. “The empirical literature

has shown that the foreign remittances have mixed impact on the distribution of

income in the home country”. (Rapoport and Docquier, 2005).

Stark et al. (1986) analyzed household data studied the effect of foreign

remittances on the distribution of income in two rural Mexican villages with different

migration histories. One village had a long migration background, and the other village

had a short one. They established that the impact of foreign remittances on disparity

related to migration history and the extent to which opportunities to traveler were

circulated among households in the society. The results were contrasted. Remittances

were found to reduce inequality in the villages that had a long history of migration to

the United States and hence a more ready access to United States labour markets. Only

the richest households in the area can meet the expenses of the high migration costs

43

and risks due to lack of information on the initial stages of migration. Due to this fact,

inter-household inequality has been raised.

Based on these facts, the authors concluded that the effects of foreign

remittances on the distribution of income depended on how migration eased the

information flowed and how the contacts were disseminated within the area.

According to the authors, this would invalidate any harmful effect on the distribution

of income in the early stages of migration. On the other hand, remittances increased

inequality in the village that had only a few households that had experienced migration

to the United States. Meanwhile, the study by Stark and Taylor (1991) further argued

that the propensity of households to participate in international migration from Mexico

to the United States was directly related to the households’ initial relative deprivation.

This disguised that comparatively poor households were more likely to connect in

worldwide migration than were households more satisfactorily located in their

village’s distribution of income.

Djajic (1986) also extended the hard works and efforts of Rivera Batiz (1982)

to see the impact of foreign remittances on the welfare for the left-behinds in a country

producing evenly traded and non-traded commodities. In theory the studies showed

that if in any economy the flow of foreign remittances go above a specific major

amount. The households which left-behinds are benefied by movement of the head of

the household still if they do not carry out and believe some of the foreign

remittances themselves. Moreover, the consequences of this study were against the

results of the studyof Rivera Batiz (1982) model. Non-migrant interests were not

considered in their model. The instigator, accomplished that his findings are suitable,

44

but if the migrant’s family do not transfer earnings to their families. Additionally, he

also accomplished that its significance is there while foreign remittances are

mentioned as the level of expenditure and consumption of migrants. In abroad what

they saved they consumped when they have returned back in the source nation.

Aaccordingly, the decision cannot be overlooked as the migration improves the

welfare of the household left-behinds

Irfan (1986) stressed that when an economy develops, there is the shifting of

dynamic resources from one area to the other area. He further stressed that where

sufficient opportunities are existing usually factors move in those directions. This

proves to be an equilibrating and growth promoting method leading to decline in return

differentials, unbiased distribution and removal of surpluses and shortages. The

researcher added that the migration may entail a worsening impact on the distribution

of income and have un-equilibrating influences on the economy as the accumulated

evidence witnessed in 1960’s and 1970s. Along with numerous impacts of migration

and foreign remittances in the country, the author considered only some of the

interrelationships among migration and development, focusing particularly on labor

coming from the rural areas of Pakistan. He concluded that there is a positive impact

of large scale migration on the economy. For Pakistan some limited facts suggested

that removal of young skilled workers may negative influence on the productivity level

in agriculture, industrial and other sectors. In the same way, low rate of profits on

investment has been observed in the rural areas which promote a cumulative impact on

worsening the distribution of income. The rural area of Pakistan was only covered in

45

this study. Migration entails distribution and redistribution modification. As a result, it

desires careful treatment.

Rivera-Batiz (1986) extended the work of Djajic (1986) and Kirwan and

Holden (1986) and developed his own model by comparing the results. The author

stressed upon that how the emigration impacts on the home country when a part of

foreign remittances is invested. He considered the wellbeing aspects, impact on the

distribution of income and household prices. He drew some common findings by

developing a complete model of twenty five equations. He found that due to migration,

the domestic prices of goods had increased and foreign remittances also strengthen this

impact. This also turned the distribution of income in support of labor and against

capital. In addition, foreign remittances offer a net increase to migrants and their

families, but their actual impact is diminished by the increase of the prices of domestic

goods. He concluded that the actual impact on the non-migrants welfare is positive,

because of speeding up of domestic trade and raise in the relative prices of non-traded

goods, which redistributes the actual income from migrants to non-migrants.

Amjad (1989) presented a complete account of the main conclusions of the

cross country studies. A series of investigative studies organized by the International

Labour Organization in the mid-eighties examined the economic impact of overseas

migration of labor-sending Asian countries. As far as testing the relationship between

income inequality and international remittances was concerned, however, these studies

were mainly descriptive, since they did not use regression equations or decomposition

analyses to test the said relationship. The study on South Korea, for instance, merely

reported a highly positive correlation between migration and the income disparity of

46

urban households: The Gini ratio in the 1970s, when migration prevailed was higher

than in the 1960s, implying a worsening of income distribution (Hyun 1989).

However, mere correlation does not necessarily mean that migration cannot improve

income distribution at all or will automatically aggravate it, since overseas

employment does allow some of those in the lower-income brackets to earn more than

otherwise possible.

Mahmud (1989) used survey data and suggested that the income-distributional

consequences of migration and remittances depended on the relative income classes

from which migrants’ families originally came. In Bangladesh and Thailand, migrants

were found to have come from a more affluent background, since those from the

poorer classes could not afford the initial costs of migration. This implies that

migration benefits the higher-income classes and only serves to extend the income gap

between them and the lower-income classes. In contrast, most of Sri Lankan migrants

came from the lower-income and low-skilled groups, and this was seen to have

moderated income disparities in Sri Lanka.

Russell (1990) in his study concluded that foreign remittances have a

significant and positive effect for their recipient countries. These countries improve the

stability of expenditures and ease overseas trade constraints; they sanction imports of

investment goods and assets for industrial expansion; they are many possible sources

of savings and investment capital for development; they help to cushion the effects of

external fluctuations and shocks in the country (e.g. Oil price changes or increases);

Moreover, they are a addition to the resources; they increase the income and raise the

47

recipient's instant standard of living; and they enhance and improve the income

distribution in the area (while poorer and less experienced workers migrate).

Adams (1991) investigated in Rural Egypt, the effects of foreign remittances

for the decrease of poor quality of th households and the allocation of income. He

observed that when household’s incomes included foreign remittances and that

remittance income accounted for 14.7% of total income of poor segments. He also

concluded that due to the inclusion of remittances that the number of poor households

declined by 9.8 percent. The author conducted a different study, focusing on the

effects of foreign remittances on the distribution of income, poverty and development

in rural Egypt. His study used to predict income equations to estimate the changes that

would take place among two contrasting situations: excluding foreign remittances,

where the remittances of the correspondents with a still-abroad migrant were excluded,

and including foreign remittances, where the remittances of these still-abroad migrants

were included. The study found that while international remittances helped alleviate

poverty, they nevertheless had a negative, worsening effect on income distribution.

Ahlburg (1991) attempted to properly measure the impact of foreign

remittances on the distribution of income in the South Pacific. He concluded that the

poorest households received six percent non remittances income and eighteen percent

of remittance income. While the richest household received forty three percent of non-

remittance income and twenty nine percent of remittance income and concluded that

remittances improve income distribution. The study found that remittances more

unequally distributed than any other sources. The author critically analyzed and

explained that the primary use of foreign remittances is consumed with the rest are for

48

the construction of houses, financing of potential migration and for debt repayments.

According to his point of view, remittances have been raising the consumption level

exclusive of creating a firm source within the home economy. Although remittances

could enhance investment, insurance provided by remote migrants tends to permit

households to keep in risk investment activities for generating income.

Adams and Alderman (1992, 1995) in their studies in rural Pakistan provided a

good foundation in the decomposition analysis of the sources of income inequality.

The decomposition analyses of these studies determined exactly what sources of

income contributed to the total income inequality, as well as how much these income

sources actually contributed to the observed inequality. The main objective of these

two studies was only to analyze the determinants of rural poverty in Pakistan and not

to focus on and assess the impact of foreign remittances on the distribution of income,

as evident in both the data set and the methodology used. The study by Adams and

Alderman, for instance, used a 1986 - 1989 survey which, as the authors noted, “Was

not designed to be representative of the rural population as a whole in Pakistan”

(1992). Furthermore, in the decomposition of the Gini coefficient, all transfers

international remittances, domestic or internal remittances, pensions, and payments of

the government to the poor were lumped together as one source of income. On the

basis of these studies, it can be concluded that the effect of foreign remittances on the

distribution of income was thus not isolated.

Taylor (1992) utilized technique for the estimation of direct, indirect and inter-

temporal special effects of foreign remittances on the income distribution and

confirmed that remittances did not have indirect short-run and long run asset buildup

49

impacts on the level and distribution of household-farm income. Foreign remittances

may finance the accumulation of income generating assets on household forms in the

long run.

Adam (1998) used panel data for five years and found that remittances are

primarily used for consumption. Data for the analysis, the study was composed of a

sequence of fourteen interviews with four hundred and sixty nine households more

than five years (1986-87 to 1990-91) for rural Pakistan. Data was collected of different

variables like income, expenditure, employment, education, migration and household

possessions. . He concluded “although poverty may well have been reduced by the

process of emigration and remittances, the poorest appears to have been bypassed, at

least directly”. Along with the sample of rural families, the richest twenty percent of

households took almost fourteen percent of their income from foreign remittances

whereas; they were sources of only one per cent of income for the poorest twenty

percent of their families. Results showed that external and internal foreign remittances

add a little in the total household income and findings of others study also supported

these observations. To see the effects of remittances on the asset accumulation, he

considered four types of rural assets. These were all physical assets: irrigated land

owned, ruined land owned, livestock assets and non-firm assets.

He established that in spite of high cost of irrigated land in Punjab province,

foreign remittances can and do direct to rural asset accumulation. Since internal

migrants in this sample received not as much of remittance income than external

migrants, they lack the resources to buy more of this asset. However the households

50

receiving foreign remittances had both the resources and the incentive to invest in

irrigated land. Overall the study concluded that;

1- Most households did not own physical assets in any year, i.e. people were

Impatient to forgo current consumption for the sake of expected asset

accumulation.

2- The availability of remittances helped to increase investment in rural areas by

raising the marginal propensity to invest from migrant households.

3- External remittances had much more positive and significant impact those

internal remittances on the accumulation of physical assets in rural Pakistan.

The author concluded that remittances have a positive effect on the accumulation of

rural assets like irrigated land owned, rained land owned, livestock assets and non-

formal assets.

Barham and Boucher, (1998) found in their study that when foreign

remittances were integrated in household income, the Gini coefficient rose by between

12 and 15 percent. The study concluded that this is due to higher costs since global

migration tends to be costly. Therefore, global migrants tend to come from middle- to

upper-income groups.

Ravanila (2003) determined that foreign remittances from overseas Filipino

workers worsened income inequality by using decomposition equations, the

researcher, and separated total inequality into its four components, namely wages,

entrepreneurial incomes, other income, and remittances from migrants. The

decomposition exercise revealed that the role of foreign remittances to overall income

51

inequality depended on their contribution to total income, their distribution among the

population, and their correlation with total income. Foreign remittances were found to

accumulate mostly to higher income classes, but they were found to be slowly

becoming less inequality increasing over time. Consequently, policies that would

intend to reduce income inequality should consider making migration-facilitating

factors more available to those in the lower ends of the distribution, because

remittances would only tend to contribute less to less to income disparity if the lower-

income classes were also able to migrate.

Rozelle and Brauw, (2004) in their article attempted to observe how

involvement in migration affects household’s investment in rural china. For this

purpose they saw the investment pattern across the break and among households that

took part in the migration and those did not. They developed a heuristic model to

describe that how a household decision to send out migrants could make possible to

involve in investment. They examined the conditions that lead to increase in household

products or consumptive investment. Data was collected in a randomly selected from

sixty villages and from six provinces of rural China.

They concluded that migrants and return migrant households have had higher

investment level than non-migrant households. However, rural households prefer to

invest more in consumption goods rather than creative ones. In deprived areas, they

found no relationship between investment and migration, while migration has a

stronger effect on consumptive assets in non-deprived villages. They provide evidence

that migrant households invest more in housing and consumer durables, especially in

non-well off places. They suggested that the financial system of china should be more

52

developed, so that the credit could be easily accessible, that would increase the

efficiency in rural economies.

McKenzie and Rapoport, (2004) used two survey data sets from Mexico argued

that the outcomes of immigration and foreign remittances on the distribution of income

cannot be clearly determined, because they depend upon the primary income

distribution and on the location of prospective migrants in that allocation. They also

stated “the first migrants will be those located on higher steps of the income

distribution, because they have both the means and the incentives to migrate”. They

used inverted U-shaped effect in their model which first time described by Stark,

Taylor and Yitzhaki, (1986). According to them “migration channels are formed after

the settlement of migrant networks in the foreign country, this will tend to lower

migration costs, making migration affordable for lower-income households”. The

observed proof of their theoretical model provided for Mexico supports.

Lucas (2005) argued in his study that foreign remittances increase the income

of households which can directly effect on the distribution of income and poverty

level, which as a result smoothens the consumption of poor and reduce the poverty

level. According to their study foreign remittances also helped to beat the working

capital constraints by depriving households, this means facilitating the recipients for

investment in human and physical capital.

The results of their study showed that foreign remittances perhaps contributed

in an important way to poverty reduction method because a lot of migrants were

comparatively poor, possessing modest or no education and belonging tremendously

from rural backgrounds. Their findings were to some degree dependable upon the

53

findings of the study by Jafarey and Ilahi, (1999) thus demonstrated that the payback

of foreign remittances for economy of Pakistan has been disseminating away from the

direct family members.

Taylor et al (2005) used available data of National Household Survey, from the

the Mexico economy to see the impacts on rural inequality and poverty by using the

foreign remittances. Their results were different then prvious studies that their impacts

are not equalizing or not as much of unequalzing, as the frequency of immigration

increases. But some of the results were very supportive and matched with the results of

few more available studies.

Rapoport and Shen, (2006) For foreign remittances impact they used a

energetic immigration model to consider the relationship with income distribution.

Their findings advocate that assets discrimination is exposed to be monotonically

condensed with the long the past history of movement. Special results of in different

period have short and long run impact with contradictory signs signifying vibrant

affiliation between foreign remittances for the distribution of income and may be

comprise on an inverted U- shaped pattern of inequity. Some other researchers

including Lermann and Feldman, (1998) accomplished that foreign remittance income

sharing additional to Gini- Coefficient than it’s add to in total income shows and it

increase disparity by using the Gini-Coefficient decomposition method in the area.

Yang and Martinez (2006) In the Philippines they also studied the impacts of

foreign remittances related with the distribution of income and poverty measurement.

Linked household surveys were used for the sample of available 26,121 households.

During the Asian crises, they demoralized a special experiment related with exchange

54

rate shocks in the economy. They got an instrument for the isolation of net effect of

foreign remittances on the resulting variables. Their study concluded there is no

statistically significant impact on the said variables.

Esquivel and Huerta-Pineda, (2006) in their research study, utilized the

Propensity Score Matching Method to consider the impact of foreign remittances on

the distribution of income and poverty reduction among the households of the Mexican

economy. The authors conclude that the households receiving foreign remittances

reduce possibility of being in food-based and in capabilities-based poverty in 8 percent

points, 6 percent points, respectively.

If the foreign remittance senders look like the Mexican population, this effect is

alike to a decrease of about 50 and 30 percent in equivalent poverty rates for foreign

remittance receiving households’ vis-à-vis non remittances receiving households. On

the other hand, receiving foreign remittances does not appear to affect the possibility

of being in asset-based poverty and foreign remittances help to shrink the level and

strength of poverty up to definite level.

Brown and Councell, (2006) claimed remittances improve income distribution.

They first estimated and compared the effects of remittances on income distribution

(Gini coefficient) in Fiji and Tonga by using household survey data. They found that

remittances improve income distribution from 0.43 to 0.38 in Tonga. International

remittances in Mexico have an egalitarian effect on income distribution they also

calculated Gini ratios Stark and Taylor, (1986). In India, foreign remittances aggravate

rural inequality because these are earned mostly by upper-income cluster villagers

(Lipton, 1980).

55

Acosta et. al. (2007) in the Latin America and Caribbean, they conducted a

cross country analysis and explored that foreign remittance are contributing to

inequality and poverty. Their study used a different econometric techniques which

allowed them to estimate the separate effects of foreign remittances on two

determinants of poverty. The determinants were the average income growth and the

degree of inequality. Their findings suggested that foreign remittances exert a positive

and significant effect on income growth and cause a slight reduction in inequality.

Adams (2008) used the counterfactual approach for imputing incomes in

Ghana, and found that when foreign remittances were added in household income,

the Gini coefficient increased approximately 3 percent: from 0.40 to 0.41.

Wouterse (2009) analyzed data from four villages to compare the effects of

foreign remittances from intercontinental and intra-African migrants on inequality,

poverty and social welfare and found that intra-African remittances reduce inequality

while intercontinental remittances have the opposite effect.

Moghal and Diawara, (2010) they studied the impact of foreign remittances on

both the distribution of income and poverty in Pakistan. They studied the differential

impacts of domestic and external foreign remittances on these variables. Additionally

to the sources of foreign remittances in term of the region such as the Middle East and

North America are also examined. The conclusions of their research study

recommended that the foreign remittances reduce poverty plus discrimination both at

micro and macro level. In terms of regional origin, remittances from the Middle East

are negatively related to poverty and inequality. According to their analysis, household

56

savings emerged to be the major channel through which the foreign remittances

control poverty in Pakistan.

Mughal and Anwar, (2012) explored micro and the macro impact of

remittances on poverty, inequality and growth for Pakistan economy. They used

income data of Household Integrated Economic survey data for the years 2005-06 and

2007-08. They explore the impact on the poverty and inequality by using the Variable

General Method of Moments (IV GMM) technique.They calculated poverty head

count ratios and found that foreign remittances substantially lower the poverty

headcount, as well as the depth and severity of poverty. They did not find significant

impact of remittances on inequality in macro analysis but found beneficial by using

micro data. They also found that contribution of foreign remittances to poverty

alleviation and inequality reduction is much stronger than of internal remittances. They

used time series analysis for the period 1979-2007 and suggested that among the three

main remittances-sending regions remittances from North America have the strongest

equalizing effect in Pakistan. They suggested that Pakistan maximizes the benefits of

remittances by giving importance to its human capital development, by improving the

access and quality of banking services.

2.4 CONCLUSION

The rationale of this chapter is to review a number of issues related to foreign

remittances, economic growth and the distribution of income. This yields a theoretical

foundation for the research and helps us to find out the nature and scope of the work.

Generally, research studies enclose the theoretical and methodological aspect of the

field. Few research studies are related to cross countries investigations. The broad

57

rationale of the review of the literature is to help us to develop a hypothetical

understanding and approaching towards the previous works and the trends that have

developed. The purpose of review of literature is also to find the gap and flaws in the

existing literature or previous research works, Moreover, it highlights the contribution

of this research work to bridge the gap. Further, it emphasizes the importance of this

research work in the context of the economy of Pakistan.

Mostly, reviewed literature on foreign remittances consists on motivation to

remit and uses of remittances. The only drawback here is the unconvincing literature

on the economic growth and income distribution effects of foreign remittances in

developing countries which make it difficult to answer the research question. This

occurs as a consequence of the conflicting theoretical and empirical literature on how

remittances impact economic growth and the distribution of income of recipient

nations. Such contradictory findings may be due to use of different data sets, due to

use of different bases in the analysis measure of equality, income, consumption or

expenditure, due to differences in the community, due to difference in areas i.e. urban

rural overall country. Some study basses on deciles data and some on quintile data.

Even the available empirical evidence is highly conflicted, some studies

conclude on positive growth effects of remittances Straubhaar (1985), Swamy (1981)

and Iqbal and Sattar, (2005) (Fayissa and Nsiah, 2010a, Fayissa &Nsiah, 2010b,

Pradhan et al., 2008), These studies also conclude that foreign remittances may have a

positive impact on economy by improving its growth rate, income distribution and

reduced dependence on external borrowing. Remittances through their multiplier

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effects may influence the main macro-economic variables such as investment,

consumption, imports and so the economic growth (Nishat and Bilgram, 1991).Some

studies mention the negative effects of foreign remittances on economic growth.

(Singh et al., 2010, Chamiet al., 2003) while some maintain that foreign remittances

have no impact on economic growth (Barajas et al., 2009, Rao and Hassan, 2011).

For impact of foreign remittances on economic growth, mostly the studies use

time series data. The majority of the authors of the impact of economic growth

analysis in their research studies anticipate the magnitudes by simple arithmetic’s of

percentages and ratios with the exemption of Burney (1987) and Zafar and Iqbal

(2005) where separate regressions have been estimated. OLS regression

underestimates the coefficients and leads to prejudiced results due to spurious

regression. Previous literature shows that none of the study has established long run

relationship among the economic variable by using time series data for the relationship

between foreign remittances and economic growth analysis.

There are also contradictory views about the effect of foreign remittances on

the distribution of income in the literature Adams (1989) uses a sample of rural

communities in Egypt and originates that remittances worsens income distribution in

the home area. On the other hand, by using a similar approach in rural Pakistan,

Adams (1992) establishes that there is no considerable effect of foreign remittances on

income inequality. Alternatively Barham and Boucher (1998) use a sample of three

coastal communities in Nicaragua and find the foreign remittances have an inequality-

reducing effect. Adam and Page (2005), Jongawanich (2007) evidence that foreign

59

remittances reduce the level and strength of poverty. According to Taylor (1992) and

Faini (2002) “remittances, admittedly, can positively affect the growth through a

number of channels”. According to Taylor and Wyatt (1996) rather than the direct

effect of foreign remittances on the distribution of income, remittances also settle

down the credit constraints with liquidity limitations for the people. Adam and Page,

(2005), Jongawanich (2007) evidence that foreign remittances reduce the level and

strength of poverty.

In a nutshell, there is a need for further empirical research on this subject. This

research work is different from all above mentioned studies in the following respects.

1. This research study may be considered as a first study that addresses the impact

of foreign remittances on economic growth by using time series data of 40

years i.e. 1972-73 to 2012-13. Hence, this study is carried out by analyzing the

foreign remittances and economic growth relationship over a much longer

period of time (forty years from 1972-73 to 2012-13). This requires co-

integration analysis to evaluate the existence of the long run relationship

among the variables.

2. As the present study utilizes large time series data having usually high R2 lead

in spurious regression. This study would cover the deficiencies of preceding

studies by utilizing an advance and accurate method of assessment. None of the

researcher in the previous studies has used this technique. Additionally, the

results of this study would facilitate the policy makers to accomplish some

60

suitable policy recommendation to the government of Pakistan for accelerating

economic growth.

3. Adam (1998) explores per-post remittances era for some selected rural areas in

Pakistan but he uses primary data. On the other hand, this study compares the

distribution of income with and without foreign remittances era for a relatively

huge data. Moreover, this study uses Reynolds and Smolensky (1977), model

to calculate pre-post Gini ratios and to construct Lorenz curves for the three

selected years. There is almost no study in this area which have used this

methodology and compared the trends in the distribution by using three HIES

data sets in Pakistan.

4. While there has been much research work on the issue of poverty in Pakistan,

however, the studies related to economic growth and the distribution of income

are limited. Moreover, foreign remittances are increasing rapidly in the recent

years in Pakistan ultimately affect many economic variables including

economic growth and distribution of income. According to facts and figures,

the remittances contribute 4 to 5 percent of GDP and thus significantly

influence the economy of Pakistan. On the other side, the income inequality

has increased severely in the last 10 to 13 years in Pakistan and will have an

upward trend. The gap between the low and high income classes has been

increasing and reaching to the alarming situation in Pakistan. So this

dissertation also suggests making changes in the pattern of remittances to curb

ever increasing inequality trends in Pakistan.

5. Many studies have been conducted to calculate income and expenditure Gini

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by using HIES data. However, no study calculates pre-post remittances

analysis for urban – rural and overall Pakistan by comparing trends in three

HIES data.

6. The current dissertation also contributes to the existing empirical literature by

taking the case of Pakistan to investigate the impact of foreign remittances on

economic growth and distribution of income distribution.

Lastly, the results of this study would facilitate the policy makers to

accomplish some feasible policy recommendation to the government of Pakistan for

accelerating economic growth and improving the distribution of income. Having

looked at both the theoretical and empirical literature on economic growth and income

distributional effects of foreign remittances, the next chapter 3, provides the

methodological issues of this dissertation.

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Chapter 3

MATERIALS AND METHODS

3.1 INTRODUCTION

This chapter outlines the economic model and methodology and all other

relevant information pertaining to how the present dissertation is planned and

conducted. It gives some background information on the research design and model

specified in the study. It provides the methodological framework that makes it possible

to answer the research question of the impact of foreign remittances on economic

growth and the distribution of income in Pakistan. This research study accomplishes in

two phases and thereby establishes the separate relationships for foreign remittances,

firstly, with economic growth and then income distribution. In section 3.2, the first

phase examines the short run and the long run impact of foreign remittances on

economic growth in Pakistan and uses annual data for the period 1972-73 to 2012-13.

The second phase, section 3.3 explains the study of the impact of foreign remittances

on the distribution of income among the households in Pakistan and in urban-rural

areas by using three latest Household Integrated Economic Surveys (HIESs) for the

years, 2001-02, 2005-06 and 2010-11.

3.2 ANALYTICAL APPROACH AND DATA SET FOR FOREIGN

REMITTANCES AND GROWTH.

This section analyzes the association of foreign remittances with economic

growth on the basis of time series data ranging from 1972-73 to 2012-13. This part of

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the study is an effort to examine the long run and short run relationships among

foreign remittances, economic growth, private investment, private consumption and

imports. This part of the chapter develops the understanding of economics and

economic methodology. This methodology is employed due to certain reasons. To

find the short run as well as long run relationship. Empirical investigation related to

this methodology will be given in the first step, of the next chapter 4.

First part of the section dealing with the justification and implication of

variables, second section argues the analytical framework comprising Augmented

Dicky Fuller (ADF) Unit Root tests, co-integration methodology by Johansen and

Juselius (1990) and error correction mechanism. Data description and their sources are

reported in the last section. This research study these uses variables for the analysis:

(1) Foreign Remittances (FR), (2) Gross National Product (GNP) as a proxy of GDP

(3) Private Consumption (CONs) (4) Private Investment (INV) (5) Imports (IMP).

3.2.1 Justification and Implication of Variables

This study mainly designed in step 1, to examine the impact of foreign

remittances on GNP growth over time. However, it is customary to examine the

behavior of the different ingredients of GNP as well. Figure: 1 shows the relationship

among the main macroeconomic variables. In the following discussion, the

justification of variables used in the time series analysis beside given GNP.

3.2.1.1 Consumption (CONs)

Consumption is generally the largest GNP component. The economic

performance of any country is mainly judged in terms of consumption level. In

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Figure: 1 Relationship between Variables

65

macroeconomic perspective the consumption is the function of income. The

enhancement in income will be followed by an increase in consumption. It means a

positive feedback loop is triggered among consumption and income. While specifying

the consumption and foreign remittances in this methodology are being used as an

explanatory variable. It is assumed that the consumption is positively related to GNP.

3.2.1.2 Investment (INV)

Private Investments are referred to as the engine of economic growth. The

strong relationship between investment and growth in GNP has been well recognized

empirically which indicates that higher rate of investments-savings lead to

enhancement in economic activities. Here, investment is a function of GNP. It is

assumed that investment is positively related to GNP. It means that the higher the

investment, higher will be GNP in accounting.

3.2.1.3 Imports (IMP)

The import function in this methodology is described in a way that import is a

function of GNP. It is assumed that the imports are negatively related to GNP.

3.2.2 Analytical Framework

This part of the chapter develops the understanding related to econometric

tools and econometric methodology. This methodology is employed due to certain

reasons. To find the short run as well as the long run relationship among the variables.

Empirical investigation related to this methodology is given in the next chapter 4.

When time series data is used for analysis in econometric, several statistical steps are

needed to be undertaken. First of all, the unit root test is applied to each series

individually in order to determine information about the data being stationary.

66

Stationary data contain no unit root. The existence of unit root makes hypothesis

testing results unpredictable. Augmented Dickey Fuller (ADF) test is applied to infer

the order of integration. ADF test is necessitated as the variables having the same order

of integration, may be Co integrated. In this study of growth and foreign remittances

analysis, “Johansen Co-integration Technique” is implied to study the long run

connection among the variables. Further, to check the short-run dynamic relationship

of the variables Error Correction Mechanism (VECM) is applied. Before testing for

co- integration, it is necessary to examine whether the time series is stationary or non-

stationary through the ADF test.

3.2.2.1 Unit root test

Unit root test explains the order of integration of the variables. There are two

types of unit root tests. One is Augmented Dickey-Fuller (ADF) test and another is the

Phillips- Perron test. This research study uses Augmented Dickey-Fuller (ADF) test.

3.2.2.2 Augmented Dickey-Fuller (ADF) test

This test is presented by Dickey and Fuller (1984).In this test they extended the

test procedure of the Augmented by including extra lagged terms of dependent

variables to eliminate the problem of auto-correlation.

Consider a simple AR (1) process:

Yt = ao + a1t + φYt-1 + ut (3.2.1)

Where, ao anda1t are exogenous regressor (a constant and trend). φ is a

parameter to be estimated, and the ut is assumed to be white noise. If | φ| = 1, Yt is a

67

non-stationary series and the variance of Yt increases with time and approaches

infinity. If | φ| <1, Yt is a stationary series.

ADF first is tested for a unit root in the levels of the series Yt. If the hypothesis

of the presence of a unit root is not rejected, we test the first difference for the

presence of a second unit root and so on. This testing procedure from lower to higher

orders of integration continues until the null hypothesis of a unit root is rejected.

3.2.2.3 Co-integration analysis

The Long run relationship between the variables can be explained by the co-

integration analysis. The Co- integration test shows that either there exist is a long run

relationship or not between the variables. To test for Co- integration, there are three

approaches. The first idea of Co- integration was presented by Granger in 1981. After

that Engle and Granger (1987) extended the idea, but there was a limitation in Engle

and Granger (1987) residual based on the Co-integration approach. It fails to

differentiate between dependent and independent variables and give single long run

equilibrium link. Thus, this method becomes inappropriate and only suitable for two

variables. To overcome this issue Johanson & Juselius (JJ) (1990) and further

Johanson (1995) introduced famous technique of Co-integration. This technique

differentiates between dependent and explanatory variables. It is also called multiple

equation approach because it offers more than one Co-integrates vectors when model

consist of more than one variable. The restriction of this technique is that it can only

apply when all the variables have the same order of integration. To resolve the

problem of different orders of integration there is another technique like auto

Regressive Distributed Lag (ARDL) model.

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3.2.2.4 Johansen Co-integration technique (Long Run Relationship)

When all the variables have the same order of integration, then we can proceed

for the Johanson Co- integration approach. In time series data, when the series is non-

stationary, then the maximum likelihood method is used to check, if there is any Co-

integrating vector Johanson & Juseliusco integration test is done on Vector

autoregressive (VAR).

In this study Johansen Co- integration is being used. Unlike the Engle Granger

static procedure, the Johansen VAR based procedure allows the simultaneous

evaluation of multiple relationships and imposes no prior restriction on the co-

integration space. To inference about the Co-integration, relation between variables,

two statistics are critical to use. One is trace statistics and other is a maximum Eigen

value.

The Johansen’s FIML approach for multivariate co-integration is based on the

following Vector Auto Regression (VAR) model of order P.

Yt = A1Yt-1 + … + ApYt-p + Bxt + µt (3.2.2)

Where Yt is an (n x 1) vector of endogenous I (1) variables (GNP, CONs, IMP,

INV and FR), Ai are an (n x n) matrix of parameters, xt is a d-vector of deterministic

variables, µt (n x n) is a vector of innovations.

To inference about the co-integration, relation between variables, two statistics are

critical to use. One is trace statistics and other maximum Eigen Value.

The Long Run Coefficients of the Model.

The long run coefficients of the variables can be estimated by 2SLS.

69

3.2.2.5 Error Correction Model (ECM)

The error correction mechanism integrates the short run dynamics with the long

run equilibrium without losing long run information. This term grasps the short run

relationship. Whenever variables are non-stationary and co-integrated, then we use the

VECM. This is equivalent to VAR at the 1st difference.

Association between Yt and Xt with an error correction specification as;

ΔYt = β1ΔXt - πēt-1 +µt (3.2.3)

β1 will have the short run effect, that measure the immediate impact that a change in Xt

will have to change with Yt.

The short run coefficients of ECM.

The next step is to estimate the short run coefficient of the model. The ECM

coefficient should be negative and statistically significant. The coefficients of ECM

show the speed of adjustment towards long run equilibrium in the current year from

the disequilibrium of the previous year. ECM can determine short run parameters as

follows.

ΔLN(GNP) =β1 ΔLN(CONs) +β2 ΔLN(INV)+β3 ΔLN(IMP)+ β4 ΔLN(FR)– φECM(-1)+ (3.2.4)

Where is the difference operator and ECM (-1) is an error correction term. The

expected signs of the parameters , should be negative, which measure the speed of

adjustment towards long run equilibrium.

3.2.2.6 Stability test

The existence of co-integration is proving the reliability of regression

coefficients. If the parameters are unstable then co--integration estimation are not

70

reliable. CUSUM and CUSNMS, O test is introduced by Brownetal (1975) to avert the

problem of unstable coefficients. The diagnostic test is taken to confirm the goodness

of fit of the model. In this respect, there are various test are like as ARCH, LM test of

Hetroscdasticity, Lagrange Multiplier test of residual Serial Correlation and Ramsey’s

Reset test of error specification. Furthermore the normality test is checked by

skewness. Knotosis test CUMUM and CUMUM are applied for the stability of the

parameters which indicates that the model is correctly specified or not.

3.2.3 Data Description and Source

It is a fact that researchers face usually with the problem of inadequate and

non-consistent data. Precise and enough data set is important for advanced empirical

research. Generally, in developing countries and mostly in Pakistan, one would

confront serious deficiencies in the quality of economic data. With the passage of time

data collection has got importance and it is expected that its quality would improve.

This part of the research study is mainly relying on time series data 1972-73 up to

2012-13.

The study is based on secondary source of data Gross Domestic Product

(GNP), Private Consumption (CONs), Imports (IMP), Private Investment (INV) and

Foreign Remittances (FR) are taken from various issues of “Pakistan Economic

Survey” and annual reports of the State Bank of Pakistan (SBP). The Gross National

Product (GNP) deflator with 2005-2006 as base year has been computed by taking the

ratio of Gross National Product (GNP) at current prices and Gross National Product

(GNP) at constant prices. All the data carry the same base year, i.e. 2005-2006.

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3.3 ANALYTICAL APPROACH AND DATA SET FOR DISTRIBUTION OF

INCOME VERSUS FOREIGN REMITTANCES.

Foreign remittances contribute towards increasing the income of households

which have a direct implication on the welfare of households and distribution of

income. It is therefore proposed to carry out a statistical study on the dynamic impact

of foreign remittances on the income of households and on the distribution of income

(Gini coefficient) by using HIESs in the years i.e. 2001-02, 2005-06 and 2010-11. This

section of the thesis explains analytical tools and informs about the methodology of the

second step that can be applied.

This study comes under the technical type of distribution of income studies. This

research work explores the distributive effects of foreign remittances on the size of

distribution in Pakistan and its urban-rural areas. The study makes use of information

contained in the three HIES surveys conducted by the Federal Bureau of Statistics of

Pakistan (FBSP). The HIES data provide data on household income and expenditures.

This study uses here household income as a unit of analysis for income distribution. In

addition, this research as said earlier, falls among the technical studies and uses a more

comprehensive definition of households’ pre-remittances income and then ads to

remittances and gives rise to post remittance incomes. The analysis of this research

work based on different related statistical facts and figures to see the impact of foreign

remittances on the income distribution in Pakistan.

Most the mentioned studies in the literature review in case of Pakistan explore

the distribution and redistribution effects of remittances by using only one year. This

study traces the changes in the trend and in the size distribution of income in the years

72

2001-02, 2005-06 and 2010-11. The problems can be raised that whether we take the

data at the individual or household level; whether it considered to income or

expenditures. It is better to only consider the data that are delegated at the national

level, based on income data and subjective to the individual level.

3.3.1 Income Distribution Indices (Measures)

Social scientists use the term income distribution metrics or income inequality

metrics to quantify the income distribution and economic disparity among the

participants of a particular economy. Different theories such as functional distribution

of income and size distribution of income attempt to make clear how income disparity

arises. It can be said that metrics of income inequality such as Gini index, Hoover

Index and Thiel Index provide a method to determine the spreading of incomes. (see

appendix A-1) for different theories of income distribution). For inequality four

properties should be satisfied as a measure of inequality (see appendix A-2).

3.3.2 Common Income Distribution Indices.

Different metrics are used to measure disparity in the income distribution,

wealth and expenditure distribution, etc. are the i) Thiel index, ii) Hoover index and

iii) Gini index iv) Palma ratio and v) 20:20 ratio. But the most common index is Gini

index or Gini coefficient. Gini index is very popular because it satisfies the four

properties of inequality, easy to understand and compute the Gini index as a ratio of

two areas in the Lorenz curve diagram. At the same time it has disadvantages, the Gini

index only a number of the properties of a diagram, but the diagram itself is not based

on any model of distribution (see appendix A-3 for common income inequality

metrics).

73

This dissertation in the second part of the study uses Gini coefficient for

measuring the distribution of income along income groups in the urban – rural areas in

Pakistan. There are different measures of inequality, but the main advantage of the

Gini coefficient is that it is a measure of inequality by means of a ratio analysis, rather

than a variable unrepresentative of most population, such as per capita income and

gross domestic product. As it satisfies four important principles, it does not matter who

the high and low earners are, it does not consider the size of the economy. However,

use of Gini ratios is not free from objections. The measure will give different results,

when it is applied to individuals instead of households when different population is not

measured with consistent definitions, comparison is not meaningful. As a result of

above criticism Gini coefficient entropy measures are frequently used.

3.3.3 Weighting System for Household, Income and Foreign Remittances

In Household Integrated and Economic Surveys (HIESs) of three selected

years, the distribution of the average yearly income of households by income groups

for all Pakistan and its urban-rural areas have been given. These distributions of

income by income group have been developed through questioner based household

income and expenditure survey. Household income is a materials return in cash or in

kind in exchange for goods and services, etc., by household earners other than

boarders, lodgers and servants. This study uses the household income as the income

base or the pre- remittances distribution in Pakistan and its urban- rural areas. This

study takes into account the average yearly income of ten household groups in each

period in overall Pakistan and its urban - rural areas. For these groups study calculates

the income Gini index have been calculated for the household groups excluding

74

foreign remittances or pre-remittances distribution of income. Similarly, this study

takes into account the average yearly income of ten household groups, those are

receiving foreign remittances in each period in overall Pakistan and its rural urban

areas. Then income of these household groups has been added to the income of those

ten income groups without remittances.

As the number of those households who are receiving foreign remittances are

very less as compared to those who are not receiving remittances, their average income

is more than that of the latter-without remittances households. For symmetrical

distribution a weighting system has been used, in which each income group is

multiplied by its average income. Similarly, the number of households along income

groups have been used as weights for average income along the different income

groups.

The data, which need weighting, are not weighted the resultant estimates

usually will be influenced. After assigning the different weights to income groups the

Gini index for household groups have been calculated for pre and post income

remittances income distributing for Pakistan and its urban-rural areas in all three

selected year for HIES data.

3.3.4 Model and Analytical Approach

To pursue the objectives, the study estimates the distribution of final income

using the percentage distribution of remittances for each period, but with new amounts

of pre- remittances incomes. To construct a post-remittances distribution of income in

any year the study use the model of Reynolds and Smolensky (1977)1 and Ilyas

(2004)2 with some modification.

75

As they constructed post-physical distribution of income, but this study uses

post- remittances distribution of income instead. Reynolds and Smolensky (1977) and

Lambert (1989) have not segregated their analysis in urban-rural areas. Thepthna

(1979) and Ilyas (2004) did their analysis by taking into account rural urban areas.

Ilyas has mentioned weight system to divide government expenditures and taxes in

urban- rural areas. This study carries out the analysis s for all Pakistan and its urban-

rural areas.

Our focus is income as a resource in this study. This study relies on household

income data for constructing our inequality indicators. The HIES data provides data on

household income and expenditure. The study use here household income for income

distribution analysis. To construct pre- remittances income along the income groups

the average income of households in each income group has been calculated by using

HIES data in three selected years. Post- remittance incomes for the income groups

have been constructed by adding remittances received by each income group to their

average incomes imputed to respective income groups.

The procedure is as follows:-

- Constructing an income base or pre-remittances distribution of

income.

- Adding remittances by income group for the pre-remittances

distribution of income. __________________________

1Reynolds, Morgan and Smolensky, Eugene. 1977: Public expenditure, Taxes and the

Distribution of income: The United States, 1950, 1961, 1970. New Academic Press,

Inc. 111 Fith Avenue, New Yourk 10003.

2Unpublished PhD Thesis (2004)

76

All procedure can be compactly given in matrix form as below.

Ry =yWh + rWy (3.3.1)

In expanded form,

Where

Ry = the post-remittances or final average income vector of the households, order

1 x k. An element, Ryi denotes the amount of income in income interval i,

i= 1,……., k.

y = the pre-remittances or initial average income of the households vector, order

1 x k.

r = a vector of remittances of order 1 x m.

Wy = A matrix of percentage average income used as a weight for remittances of

order

1 x m.

Wh= A matrix of percentage households used as a weight for average income of

order

1 x m.

(3.3.2)

77

3.3.5 Lorenz Curve and Gini- Coefficient Analyses

This study works out a Lorenz curve and Gini coefficient analyses by using

pre- and post- remittances distributions of incomes for Pakistan and also for its urban-

rural areas in the years 2001-02, 2005-06 and 2010-11. The following equation is

being used to calculate Gini coefficients of Pakistan and its urban-rural areas in three

selected years.

G = 1 – (hi+1 – hi) (yi + yi+1) (3.3.3)

Where,

G = Gini ratio

hi = Cumulative per unit, number of households in the ith income group

yi = Cumulative per unit share of income of ith income group.

The Lorenz curves are drawn by using a percentage cumulative distribution of

households in the pre and post-remittances era respectively. To see the impact of

remittances on the distribution of income, this research study plot both pre-remittances

and post –remittances income shares against number of households belonging to each

income group. Figure: 2 graphically presents Gini coefficient and Lorenz curve.

3.3.6 Pre-Post Remittances Lorenz Curves

Lorenz curve can be used as a criterion for ranking income distribution. But the

ranking provided by it is only partial. Because partial in the sense that when the

Lorenz curve of one distribution is strictly inside another distribution, it can be said

confidently that first distribution is more equal than the second one. If two Lorenz

curves intersect, neither distribution can be said to be more equal than another. But it

http://www3.nccu.edu.tw/~jthuang/Gini.pdf#page=2


78

does not mean that partial ranking is a drawback of Lorenz curve. As Sen (1973)

criticized complete ranking by saying that “the concept of inequality has different facts

which may point in different directions and sometimes a total ranking cannot expect to

emerge”. The concept of inequality is therefore essentially a question of partial ranking

and, the Lorenz curve is consistent with such a notion of inequality. In the dissertation

pre-post remittances Lorenz curves are drawn on the basis of the three selected years

i.e. 2001-02, 2005-06 and 2010-11.

3.3.7 Gini Ratios by Ordinary Least Square (OLS) Method.

Gini Ratios also calculated in this study by Ordinary Least Square (OLS)

Method. The OLS method has also been applied for calculating the Gini ratios. The

slope coefficient β calculates by regressing the average income with and without

remittances on the number of households in all three selected year. The rationale of

this test is to show that, if structural relationships are altered, the Gini-ratios should

Differ considerably. For this purpose, the data are fitted to the following functional

form (See Reynolds and Smolensky, 1977).

(3.3.4)

Where

is the cumulative proportion of income

is the cumulative proportion of households

79

Source: Kakwani (1986)

Figure: 2 Graphical Representation of Gini Coefficient and Lorenz Curves

http://en.wikipedia.org/wiki/File:Economics_Gini_coefficient2.svg



80

In case of β > 0 the Lorenz curve lies below the 45o line, and if β = 0 the curve

coincides with the income equality (45o) line, and if β = ∞ the curve lies along the x-

axis and y-axis under 45o line. The Gini ratios have been calculated by the given

expression.

3.3.8 Chow Breakpoint Test for Structural Stability

A formal statistical test called Chow test is used for knowing that two

distributions under examination are statistically significantly different from each other

or not. As an alternative for stability test that coefficient is stable or not different

(Chow, 1960). This test breaks the sample into two or more structures, estimates the

equation for each of them. The null hypothesis of Chow test asserts that there is no

significant difference between two distributions in question. This test is an F test, and

shows the equality of the regression coefficient, if fecal >Ftab, the hypothesis that β1 =

β2 = βis rejected and it is accomplished that there is proof of structural instability. The

study conducts Chow test for pre- post remittances distributions having same years in

Pakistan and in its urban-rural areas for testing equality of = β coefficients.

(3.3.5)

81

3.3.9 Data Description: Household Integrated and Economic Surveys (HIESs)

For the impact of foreign remittances on the distribution of income impact, the

study uses cross sectional data, this part of the research is mainly based on data on

three (HIESs) for the years 2001-02, 2005-06 and 2010-11. Table 1, 2, and 3 present

the sample size of three data sets and Table 4 presents households receiving the

foreign remittances. During the mentioned period (HIESs) was conducted by the

Federal Bureau (FBS) of Statistics previously it was conducted by the Central

Statistical Office. The Household, Income and Expenditure Surveys have been

conducted on a national basis in overall Pakistan and in its urban and rural areas. (See

appendix A- 4 for HIESs) In present study HIES data for three periods 2001-02, 2005-

06 and 2010-11 have been used to compare the changes in the trend and size

distribution of income and distributional impact of household income. Therefore, three

surveys with four year gap for the comparison of the distributional impact of foreign

remittances have been selected. The aim of HIES to provide data on household income

and expenditure ascertain the pattern and level of consumption, variation in

expenditure, household saving, investment and liabilities by different income groups

and by urban- rural areas. For this research study, primary data files have been

obtained from FBS then households and their income with and without remittances

were sorted at the urban-rural level of analysis.

This research work for distribution analysis falls among the technical studies. It

is data based and records observed facts through certain measurement procedures

explained in the subsequent chapters. These procedures are described in the main

sources of income and expenditure data, for example, Economic Survey, Population

82

Censuses and Household Integrated Survey (HIES). It shows a comprehensive

measure of income inequality by including the benefits and burden at all levels. In the

analysis of the distribution of income the student pursues the practice, more or less, of

a line of studies by Reynolds and Smolensky (1977) and Thepthana (1979) Lamert

(1989) and Ilyas (2004). The study uses the Gini coefficient, which is a measure of

income inequality, is directly linked with Lorenz curve.

3.4 STATISTICAL PACKAGES USED

This research work is based on many statistical techniques and packages for its

completion. Microsoft Excel, SPSS and E Views 6 have been utilized for its analysis. .

E Views has been used for Co-integration, analysis, statistical and econometric

significance tests. These are well known packages and need no explanation. SPSS has

been used for sorting out different distributions along the income groups from data of

Households Integrated Economic Survey and Excel has been used for computation and

Lorenz curve tests.

83

Table: 1 Sample size HIES, (2001-02)

Sample PSUs Sample SSUs

Urban Rural Total Urban Rural Total

Punjab 206 230 436 2432 3668 6100

Sind 128 136 264 1534 2174 3708

KPK 72 116 188 857 1842 2699

Baluchistan 52 88 140 623 1406 2029

Total 458 570 1028 5446 9090 14536

Source: Report of HIES (2001-02)


Sample PSUs Sample SSUs


Punjab 240 244 484 2790 3892 6662

Sind 140 132 272 1666 2107 3773

KPK 88 119 207 1049 1901 2950

Baluchistan 63 83 146 735 1313 2048

Total 531 578 1109 6240 9214 15453

Source: Report of HIES (2005-06)

84


Sample PSUs Sample SSSUs


Punjab 256 256 512 2935 4019 6954

Sind 152 144 296 1802 2296 4098

KPK 88 120 208 1041 1913 2954

Baluchistan 68 96 164 811 1524 2335

Total 564 616 1180 6589 9752 16341

Source: Report of HIES 2010-11

Table: 4 Households Receiving Foreign Remittances

HIES Data 2001-02 HIES Data 2005-06 HIES Data 2010-11

No of H.H

Total Urban Rural Total Urban Rural Total Urban Rural

14050 5348 8702 15450 6240 9210 16317 6574 9743

No of H.H

Receiving

Remittances

786 344 442 852 316 536 868 304 564

Percentage of

H.H Receiving

Remittances

5.6 6.4 5.0 5.5 5.0 5.8 5.3 4.6 5.8

Source: Calculated by Author from (HIESs) data

85

Chapter 4

RESULTS AND DISCUSSION

4.1 INTRODUCTION

This research study has been accomplished in two steps. This chapter in section

4.2 provides the estimation of the results and discussion of the first part, of the study

related to foreign remittances and economic growth. The discussion of this part of the

study analyzes the results on the basis of 1st research question and hypothesis that uses

time series data from 1972-73 to 2012-13. Later on, in the section 4.3, the estimation

and discussions of the results about the impacts of foreign remittances on the

distribution of income in Pakistan and its urban-rural areas will be presented.


GROWTH.

In this section, the findings and the results are presented that address the

relationship among foreign remittances, economic growth and some main macro-

economic variables like consumption, investment and import. In estimating time

series data, unit root test is applied usually to check the stationary of the data. After

using the unit root test, the Co-integration, analysis is used to find out whether Co-

integration exists between the variables or not. Appendix B, C, and D are based on

these results of said estimations.

4.2.1 Unit Root Test

The unit root test is applied to observe the stationary level of the variables. In

application of this, Augmented Dickey-Fuller carries out for each variable by

introducing the intercept and trend. Moreover, unit root tests are applied on the

86

logarithmic values of Gross National Product (LNGNP), Consumption (LNCONs),

Foreign Remittances (LNFR), Private Investment (LNINV) and Imports (LNIMP).

4.2.1.1 ADF test at level

Table 5 depicts the results for all the series for unit root using the ADF test at

level with constant and linear trend and with a lag. In the given Table 5the results of

the unit root show that all the variables have unit roots.

4.2.1.2 ADF test at first difference

All the series are tested (in first difference form) for unit roots, the results are

presented in Table6. Thus, it is concluded that these series are stationary at first

difference with the constant and linear trend. This shows that they are integrated of

order one. It means that we can proceed with the co-integrating technique for these

variables.

4.2.2 Co-Integration Analysis.

The result of the unit root tests indicates that all variables are stationary at I(1).

To verify this long run relationship, exist between foreign remittances, growth,

consumption, investment and imports Co-integration test is applied.

4.2.2.1 Model specipication and optimal lag selection in VAR

After analyzing the result of unit root test next step is to find out the lag order

for Co- integration.Co- integrating analysis is sensitive to the specification of the trend

and the number of lags used in the VAR. Therefore, a greater attention is given to deal

this problem.

87

Table: 5 ADF Statistics at Level

Variables ADF (Statistics) Critical Value

1% Level

No. of Lags K

LN GNP -2.608663 -3.608663 0

LNCON -2.766545 -4.234972 0

LNIMP -2.634082 -4.234972 0

LNINV -1.785534 -4.234972 0

LNFR -2.331246 -4.234972 0

Source: Based on computer software E-Views.

Table: 6 ADF Statistics at 1st Difference

Variables ADF (Statistics)

Critical Value

1% Level

No. of Lags K

LN GNP -5.065880 -3.510453 0

LNCON -5.244529 -4.243644 0

LNIMP -9.407273 -4.243644 0

LNINV -5.717836 -4.243644 0

LNFR -3.642137 -3.544284* 0

Source: Based on computer software E-Views.

88

Outcome of different criterions for optimal lag selections are given in Table 7.

According to the criterion, the model four is selected for Co- integration. Schwarz

Criterion suggests that optimal lag is one.

4.2.2.2 Results from Johansen Co-Integration analysis

It is established that all the variables are integrated of order 1 i.e. I (1). While,

SC statistics suggested one lag as optimal lag. The next step is to test the existence of

long run relationship among the variables. So, we can proceed to test for co-integration

among the variables. Johanson and Juselius approach is used for the co-integration

relationship among the variables. Johansen (1988), co-integration test is examined

whether there are one or more than one co-integration relationships. If the number of

co-integrating vector is zero, it would entail that, there is no long run relationship

among the variables. Conversely, if there are co-integrating vectors it recommends that

there are common stochastic trends among the variables that connect them together.

This test is based on Maximum Eigen Statistics and the Trace Test Statistics.

4.2.2.2.1 Trace test statistics

Table 8 illustrates the results on the basis Trace Test for testing the number of

co-integrating relations. In the co-integration test, the null hypothesis, there is no co-

integration among the variables and alternative hypothesis is that co-integration exists

among the variables. The result of Trace Statistics reveals that the trace statistics is

(100.61) greater than the critical values at 05 percent (88.80) level of significance.

Thus, it is possible to reject the null hypothesis of no co-integration vector, in support

of general alternative hypothesis that co-integration exist or long-run relationship

between the variables. Consequently, there is one co-integrating relationship involving

89

Table: 7 Optimal Lag Selections

Lag LogL LR FPE AIC SC HQ

0 54.75136 NA 5.02e-08 -2.618493 -2.403021 -2.541829

1 255.1902 337.5812 4.97e-12 -11.85211 -10.55928* -11.39214*

2 277.8933 32.26227 6.02e-12 -11.73122 -9.361034 -10.88793

3 312.8682 40.49732* 4.33e-12* -12.25622* -8.808672 -11.02961

Source: Calculations are based on computer software E-views.

Indicates lag order selected by the criterion

LR: sequential modified LR test statistic (each test at 5% level)

FPE: Final prediction error

AIC: Akaike information criterion

SC: Schwarz information criterion

HQ: Hannan-Quinn information criterion

SC statistics suggested one lag as optimal lag.

90

the variables. The presence of co-integrating vector predicts that, there exists a stable,

long run relationship between gross national product, consumption, imports,

investment and foreign remittances. This means that while the five series variables

may diverge from each other in the short run, but they will stay near to each other and

not drift far away in the long run.

4.2.2.2.2 Maximum eigen value test

The results on the basis of Maximum-Eigen Statistics are given in the Table 9

reveal that the null hypothesis of no co-integration is at the 5 percent level of

significance. Thus, the alternative hypothesis that at least one co-integrating vector has

been accepted by the test at the 5 percent level of significance. Consequently, it is

deduced that there is precisely one co-integrating relationship involving the variables.

The presence of co-integrating vector confirms that, there exists a stable, long run

relationship between the gross national product, consumption, imports, investment and

foreign remittances. This piece of evidence supports the hypothesis that there is strong,

long run relationship among the variables.

Because of the above discussion and empirical results, there is clear and long-

run relationship among variables, the gross national product, foreign remittances,

private consumption, private investment and imports. The literature for the impact of

foreign remittances on economic growth also support this positive and long run

relationship among the said variables.

4.2.2.2.3 The long run coefficients of the model

The existence of long run relationship between the variables leads to examine

Table: 8 Trace Test

91

Trend assumption: Linear deterministic trend (restricted)

Series: LNCON LNIMP LNINV LNFR

Lags interval (in first differences): 1 to 1

Hypothesized

No. of CE(s)

Eigen value Trace

Statistic

0.05

Critical Value Prob.**

None * 0.636482 100.6099 88.80380 0.0054

At most 1 0.470613 61.14478 63.87610 0.0831

At most 2 0.420212 36.33938 42.91525 0.1942

At most 3 0.202860 15.08078 25.87211 0.5678

At most 4 0.147824 6.238509 12.51798 0.4306

Source: Calculations are based on computer software Eviews-6

Trace test indicates 1 co-integrating equation (s) at the 0.05 level *denotes rejection of the hypothesis at the

0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Table: 9 Maximum Eigen Value Test

Hypothesized

No. of CE(s) Eigen value

Max-Eigen

Statistic

0.05

Critical Value

Prob.**

None * 0.636482 39.46515 38.33101 0.0369

At most 1 0.470613 24.80539 32.11832 0.2978

At most 2 0.420212 21.25861 25.82321 0.1788

At most 3 0.202860 8.842267 19.38704 0.7406

At most 4 0.147824 6.238509 12.51798 0.4306


Trace test indicates 1 co-integrating equation (s) at the 0.05 level *denotes rejection of the hypothesis at the

0.05 level **MacKinnon-Haug-Michelis (1999) p-values

92

long run impact of independent variables on dependent variable. Table 10 presents the

empirical results. The long run values are given by the co- integrating regression. The

analysis of the results of 2 SLS indicates that variables which determine the economic

growth have expected signs. Hence foreign remittances, consumption and investment

positively affect the economic growth, whereas imports affects negatively. Empirical

findings indicate that foreign remittances have a positive effect on economic growth

and the 3rd most substantial effect on GNP i.e. 1.07. This means, that 1 percent

increase in foreign remittances causes a 1.07 percent increase in GNP at the 1 percent

level of significance.

The analysis of the results of 2SLS indicates that variables which determine the

economic growth have expected signs. Hence foreign remittances, consumption and

investment positively affect the economic growth, whereas imports affects negatively.

Empirical findings indicate that foreign remittances have a positive effect on economic

growth and the 3rd most substantial effect on GNP i.e. 1.07. This means that 1 percent



This analysis provides empirical support and also indicates positive long run

relationships between economic growth, consumption and investment. This is in line

with the general assertion that consumption and investments are the key components

of economic growth. On this estimation 1 percent increase in consumption leads to

increase in GNP by 1.10 percent at the 1 percent level of significance. Similarly, a

percent increase in investment leads to increase in GNP by 1.34 percent at the 1

percent level of significance. These relationships are inconsistent with economic

93

theory. Results are reported in the table 10 indicate that imports have the negative long

run relationship with the economic growth, i.e. an increase 1 percent of imports leads

to decline in GNP by 0.17 percent. However, this relationship is insignificant. This

means that rising in imports deters economic growth. Empirical evidence for a number

of researchers also confirms these relationships. The findings are consistent with the

literature with Mugal (2012), Ahmad (2006) and Gilani, (1981).

4.2.3 Error Correction Mechanism (ECM)

To examine the short run dynamic among the variables foreign remittances,

gross national product, private consumption, private investment and imports, the study

uses error correction mechanism (ECM). The short run dynamic equation has two

important objectives in this research. Firstly, it is being used to investigate whether the

impact of foreign remittances is stable or temporary. If the responses are significant

both in the short and long run, it can be said that the changes are permanent as well as

transitory. Secondly, the error correction term (ECT) provides information about the

speed of adjustment in response to a deviation from the long run equilibrium. Table 11

presents the short run results of the model which are calculated by using software

Eviews. To compare different results the study uses R2, Durbon –Watson, F- statistics,

Mean Dependence Variance and Probability (F-statistic). Moreover, GNP is used as a

dependent variable.

The results are reported in the table 11indicate that the short run results of first

difference or log-level variables are similar to long run. The short run dynamics

indicate that the short run impact of remittances, consumption and investment is

positive and statistically significant. Imports exert negative statistically significant

94

Table: 10 Long Run Coefficients of the Model (Dependent Variable GNP)

(These results are based on 2SLS)

Variable Coefficient Std. Error t-Statistic Prob.

C -110609.5 86362.94 -1.280752 0.2085

FR 1.073790 0.356145 3.015032 0.0047

CONs 1.101631 0.053260 20.68411 0.0000

INV 1.345236 0.279825 4.807420 0.0000

IMP -0.175931 0.131305 -1.339869 0.1887

Source: Calculations are based on computer software Eviews- 6

R-squared 0.996561 Mean dependent var 4938669.

F-statistic 2617.315 Durbin-Watson stat 1.273099

Prob (F-statistic) 0.000000 Prob(F-statistic) 0.000000

Table: 11 Short Run Coefficients of the Model (Dependent Variable GNP)


IMP -0.006980 0.012742 -0.547769 0.5875

INV 0.121995 0.043917 2.777828 0.0090

FR 0.042479 0.012396 3.426909 0.0017

CONs 0.255756 0.076546 3.341221 0.0021

ECMt-1 -0.215003 0.101182 -2.124910 0.0412

C 0.027223 0.005500 4.949565 0.0000


R-squared 0.480886 Mean dependent var 0.048718

F-statistic 6.113969 Durbin-Watson stat 1.94716

Prob(F-statistic) 0.000412

95

effects on economic growth in the short run and the size of negative effect on

economic growth is weaker than long runs. GNP increases 0.25, 0.12 and 0.04percent

as a result of 1 percent increase in consumption, investment and remittances

respectively. The short run coefficients of all variables are smaller than long run

estimates. This confirms that results of research studies are reliable and efficient.

After determining of the existing co-integrating relationship, disequilibrium

may take place in the short run. If, there is a long run connection between the different

variable exist, then an error correction process is also taking place. The coefficient of

the error correction term (ECT) provides information about the speed of adjustment

towards the long run equilibrium after a short run shock. If the speed of adjustment

higher than greater would be corrected in deviations from short run towards long run

Banerjee, et al. (1993).The estimate of the error correction term, i.e. ECMt-1 bears a

negative sign and statistically significant at the 1percent level of significance. The

coefficient of ECMt-1 is -0.21, significantly different from zero, indicating the existing

of error correction mechanism and implying that the D (LNGNP) D (LNCONs),

D (LNINV), D (LNIMP) and D (LNFR) converge to long run equilibrium. The speed

of adjustment of the equilibrium suggests that if a shock inserted into the model 21

percent deviation is rather corrected within the first year. This speed of adjustment is

relatively slow. This confirms our long run established relationship among the

variables.

4.2.4 Diagnostic Tests

The diagnostic tests depict that the model is well built-in, whilst as evident

from LM test, no serial correlation exists. Ramsey’s RESET proves that the functional

96

form is in order. The normal distribution is authenticated by the Normality test. There

is no heteroscedasticity. The graphs of cumulative sum and cumulative sum square

tests are presented in Figure 3 and Figure 4 Both graphs lie within 5 percent

significance boundaries, which specify that short-run and long-run parameters are

stable.


DISTRIBUTION OF INCOME

This section provides the results of estimation and discusses about the 2second

step, of the study for the impacts of foreign remittances on the distribution of income

among the households in Pakistan and across urban-rural areas. The discussion of this

section depends on the research questions related to second and third hypotheses.

These results are the outcomes of the estimation of Gini coefficient of pre-post

remittances accompanied by their respective Lorenz curves.

4.3.1. Percentage Distribution of Household Income and Foreign

Remittances.

Analysis of the impact of foreign remittances on the distribution of income

here deals with the answers to some important questions. (i) What is the magnitude of

foreign remittances related to total income? (ii) Which income groups of households

produce migrants? (iii) How much different income groups of migrants remit? And

(iv) how much unequal distribution of remittances contributes to inequality?

Tables 12, 13 and 14 analyze the three HIESs data sets, 2001-02, 2005-06 and

2010-11 and present the trends in the distribution of household’s migrants abroad

97

-15

-10

-5

0

5

10

15

88 90 92 94 96 98 00 02 04 06 08 10 12

CUSUM 5% Significance

Figure: 3 Cumulative Sums

-0.4

0.0

0.4

0.8

1.2

1.6

88 90 92 94 96 98 00 02 04 06 08 10 12

CUSUM of Squares 5% Significance

98

among income quintile through the income order ranked by predicting income

without and with foreign remittances. Column (1) of given table 12 ranks all migrant

households of Pakistan belong to urban-rural areas by income quintile on the basis of

their average annual income. Column (2) presents the percentage of their average

annual income (without remittances) and column (3) presents the percentage of their

average annual income (with remittances). Column (4) shows the percentage change

between column (2) and (3). In order to see which income groups produce more

migrants, it can be observed in the column (1) of Table 12. It presents the percentage

of migrant along the income groups. It shows that the lowest income quintiles actually

produce one of the highest shares of total migrants in overall Pakistan and its rural

areas, but however, in an urban area it is not the lowest. On the other hand, it can also

be observed that the highest income quintiles in urban area produced one of the highest

shares of migrants and the highest income quintile in rural area produced the lowest

share of migrant. Table 12 also provides the information that migrants are not

distributed fairly equal among the income order and poorer groups tend to receive a

smaller share of foreign remittances. Table 12 presents that foreign remittances may

have no positive effect on income distribution, when foreign remittances excluded

with when they have been included in Pakistan and its urban-rural areas in 2001-02.

This shows that the uneven share of abroad migrants produced by the different

income groups may have a negative effect on income distribution. To evaluate this

effect, it is necessary to compare the change in income distribution that occurs when

remittances are included and excluded from the analysis. Table 12 also analyses the

impact of foreign remittances on income distribution in two cases when remittances

99

Table 12: Distribution of Households’ Migrants among Income Quintiles Ranked by

Predicted average Household Income, with and without Foreign

Remittances (HIES 2001-02)

Rank

Percent of

Household

Along the

Income Groups

(1)

Percent of

Average

Income Without

Remittances

(2)

Percent of

Average

Income With

Remittances

(3)

Percent of

Change

Between

(2)&(3)

(4)

Pakistan 2001-02

Lowest 20 25.38 6.00 2.38 -3.68

Second 20 14.62 5.90 3.95 -1.95

Third 20 20.67 13.75 8.68 -5.07

Fourth 20 19.83 20.61 15.43 -5.18

Highest 20 19.50 53.74 69.57 15.83

100.00 100.00 100.00

Urban 2001-02

Lowest 20 17.63 3.20 1.76 -1.44

Second 20 12.23 4.40 3.74 -0.66

Third 20 19.06 10.26 7.75 -2.51

Fourth 20 22.30 18.39 14.69 -3.7

Highest 20 28.78 63.76 72.07 8.31

100.00 100.00 100.00

Rural 2001-02

Lowest 20 32.08 10.46 3.32 -7.32

Second 20 16.67 8.27 4.65 -3.62

Third 20 22.01 19.26 10.72 -8.54

Fourth 20 17.61 23.97 17.92 -6.05

Highest 20 11.64 38.04 63.38 25.34

100 100 100

Source: Calculated by Author

100

are included and excluded from the analysis. As the column (2) shows the percentage

share of average income going to each income quintile group excluding remittances.

Column (3) shows the percentage share of average income going to the each income

quintile group including remittances. Column (4) shows the percent of change

between columns (2) and (3). By analyzing the table, we can see when remittances are

included, the households from the lower-middle income quintiles benefit less than the

household of the upper class for Pakistan and in its urban-rural areas. The share of

average income going to households in second, third and fourth income quintile

declines by 2.9, 7.65 and 14.43 percent respectively. In contrast, the percentage of

average income going to household in the upper highest income quintile increases by

68 percent for Pakistan when remittances are included. However, for other income

quintile these percentage decrease. Similar trend can be observed in urban rural areas.

Column (4) shows large changes in income for different quintile groups, when foreign

remittances are included which show that foreign remittances have a negative effect on

income distribution.

Table 13 is based on the HIES 2005-06 and put forwards the distribution of

households migrants abroad among income quintile through the income order ranked

by predicted income without and with foreign remittances. Column (1) of given

Table 13 ranks all migrant households of Pakistan belong to urban-rural areas by

income quintile on the basis of their average annual income. Column (2) put forward

the percentage of their average annual income (without remittances) and column (3)

presents the percentage of their average annual income (with remittances). Column

(4) shows the percentage change between column (2) and (3). Table 13 presents the

101

Table: 13 Distribution of Household’s Migrants among Income Quintiles

Ranked by Predicted Average Household Income, with and without

Foreign Remittances. (HIES, 2005-06)

Rank

Household

Along the

Income Groups

(Percent)

(1)

Average Income

Without

Remittances

(Percent)

(2)

Average Income

With

Remittances

(Percent)

(3)

Percentage

Change

Column(2) &

(3)

(4)

Pakistan 2005-06

Lowest 20 20.77 7.14 4.71 -2.43

Second 20 19.13 10.64 7.89 -2.75

Third 20 20.07 15.42 11.93 -3.49

Fourth 20 20.19 21.68 18.52 -3.16

Highest 20 19.84 45.12 56.96 11.84

100.00 100.00 100.00

Urban 2005-06

Lowest 20 12.97 3.97 3.35 -0.62

Second 20 16.46 8.00 6.97 -1.03

Third 20 19.62 13.10 11.87 -1.2

Fourth 20 24.05 22.29 20.49 -1.8

Highest 20 26.90 52.63 57.33 4.7

100.00 100.00 100.00

Rural 2005-06

Lowest 20 25.37 9.51 5.53 -3.98

Second 20 20.71 12.61 8.43 -4.18

Third 20 20.34 17.15 11.87 -5.22

Fourth 20 17.91 21.22 17.09 -4.13

Highest 20 15.67 39.50 57.08 17.58

100 100 100


102

percentage of migrants along the income groups. It can be seen the lowest income

quintiles actually produce one of the highest shares of total migrants in overall

Pakistan and its rural area but in urban areas are not the lowest.On the other hand, it

can also observe that the highest income quintiles in urban area produce one of the

highest shares of migrant and the highest income quintile in rural area produced lowest

share of migrant.

Table 13 shows that migrants are not distributed fairly equally among the

income quintiles, and poorer groups tend to receive a smaller share of foreign

remittances. Table 13 also presents that remittances may have no positive effect on

income distribution when foreign remittances excluded with when foreign included in

Pakistan and its Urban-Rural areas in 2005-06. The uneven share of abroad migrants

produce by the different income groups may have a negative effect on income

distribution. To evaluate this effect, it is necessary to compare the change in income

distribution that occurs when remittances are included and excluded from the analysis.

Table 13 also shows the impact of foreign remittances on income distribution

in the cases, when remittances are included and excluded from the analysis. As the

column (2) shows the percentage share of average income going to each income

quintile group excluding remittances. Column (3) shows the percentage share of

average income going to each income quintile group including remittances. Column

(4) shows the percent of change between column (2) and (3). By analyzing the table, it

can be seen when remittances are included, the household from the lower-middle

income quintiles benefit less than the household of the upper class for Pakistan across

its urban-rural areas. The share of average income going to households in second, third

103

and fourth income quintile declines by 6.8, 10.9 and 17.5 percent respectively. In

contrast, the percentage of average income going to household in the upper highest

income quintile increases by 55.96 percent for Pakistan when remittances are included.

The largest percentage increases for the highest quintile, while, for other income

quintile these percentage decrease, similar trend can be observed in urban rural areas.

Column (4) shows large changes in income for different quintile groups when foreign

remittances are included which show that foreign remittances have a negative effect on

income distribution.

Table 14 is based on the HIES 2010-11 presents the distribution of migrant

households and income without and with foreign remittances. Column (1) of given

Table 14 ranks all migrant households of Pakistan belong to urban-rural areas by

income quintile on the basis of their average annual income. Column (2) presents the

percentage of their average annual income (without remittances) and column (3)

present the percentage of their average annual income (with remittances). Column (4)

shows the percentage of change between column (2) and (3). It can be observed in the

column (1) of Table 14 in order to see which income roups produce more migrants.

Table 14 presents the percentage of migrant along the income groups. It can be

seen that the lowest income quintiles actually produced one of the highest shares of

total migrants in overall Pakistan and across its rural areas but in urban areas are not

the lowest. Moreover, it can also be observed that the highest income quintiles in

urban area produce one of the highest shares of migrants and the highest income

104

Table: 14 Distribution of Household’s Migrants among Income Quintiles Ranked by

Predicted Average Household Income, with and without Foreign Remittances.

(HIES. 2010-11)

Rank

Percent of

Household

Along the

income

Groups

(1)

Percent of

Average Income

Without

Remittances

(2)

Percent of

Average Income

With Remittances

(3)

Percent of

Change

Between

(2)&(3)

(4)

Pakistan 2010-11

Lowest 20 20.05 7.52 5.37 -2.15

Second 20 19.93 11.56 8.81 -2.75

Third 20 20.16 15.65 13.03 -2.62

Fourth 20 19.82 20.74 19.02 -1.7

Highest 20 20.05 44.53 53.77 9.24

100.00 100.00 100.00

Urban 2010-11

Lowest 20 10.86 3.65 3.49 -0.16

Second 20 13.49 6.59 6.44 -0.15

Third 20 23.03 15.07 13.12 -1.95

Fourth 20 22.70 20.16 19.50 -0.66

Highest 20 29.93 54.53 57.45 2.92

100.00 100.00 100.00

Rural 2010-11

Lowest 20 25.00 10.28 6.43 -3.85

Second 20 23.40 15.09 10.07 -5.02

Third 20 18.62 16.06 12.63 -3.43

Fourth 20 18.26 21.15 18.12 -3.03

Highest 20 14.72 37.42 52.74 15.32

100.00 100.00 100.00


105

quintile in rural area produced the lowest share of migrant. Table 14 indicates that

migrants are not distributed fairly equal among the income classes and poorer groups

tend to receive a smaller share of foreign remittances.

Table 14 presents that the effects of remittances may have no positive effect on

income distribution after the inclusion of the pre- remittances income in urban-rural

areas of Pakistan in 2010-11. The uneven share of abroad migrants produced by the

different income groups may have a negative effect on income distribution. To

evaluate this effect, it is necessary to compare the trends in changing in income

distribution that occurs when remittances are included and excluded from the analysis.

Table 14 also analyses the impact of foreign remittances on income distribution

in two cases when remittances are included and excluded from the analysis. As the

column (2) reveals the percentage share of average income going to each income

quintile group excluding remittances. Column (3) shows the percent share of average

income going to each income quintile group including remittances. Column (4)

presents the percentage of change between column (2) and (3). By analyzing the table,

it can be seen when remittances are included, the households from the lower-middle

income quintiles benefit less than the household of the upper class for Pakistan and its

urban-rural areas. The share of average income going to households in second, third

and fourth income quintile declines by 7.8, 12.8 and 18.5 percent respectively.

In contrast, the percentage of average income going to household in the upper

highest income quintile increases by 52.77 percent for Pakistan when remittances

include the largest percentage increases for the highest quintile for other income

106

quintile these percentage decrease, similarly it can observe for urban rural areas.

Column (4) shows large changes in income for different quintile groups when foreign

remittances are included which show that foreign remittances have negative effect on

income distribution. This section of the study may conclude by the analysis of three

HIES data sets that remittances have a negative effect on income distribution because

they are not distributed fairly equals through the income order in Pakistan and in its

urban-rural areas. Lower and middle income quintile groups of household’s decreases

their percentage after inclusion of foreign remittances and upper income class

increases their percentage share.

4.3.2 Gini Ratios and Lorenz Curves

Changes in income distribution before and after the foreign remittances are

measured by standard indices of inequality, the Gini coefficient in this analysis. The

graphical presentation of Lorenz curves is also used in this connection. In this section,

distribution of income of initial group is being compared with the distribution of

income of the post remittances group. The Gini coefficients are presented along the

Lorenz curves for making, among overall Pakistan and across its urban-rural areas

during 2001-02, 2005-06 and 2010-11.

The purpose of this study is to calculate Gini coefficients for group data

through trapezoidal approximation and OLS method. However, these summary

statistics are not error free because their values are sensitive to the pattern of

distribution in low, middle and high income groups. The main purpose of this study is

to compare the trend in the distribution of income in Pakistan and its urban- rural areas

over the time. Here, the trend in pre- remittances income for the income groups is

107

compared with that of the trend in post- remittances distribution of incomes. The Gini

coefficients are also presented along the Lorenz curves for comparing distributions in

Pakistan and across the urban-rural areas in 2001-02, 2005-06 and 2010-11.

The analysis has been carried out keeping in view total households with and

without remittances in the following section 4.3.3. The study has also conducted

analysis in the section 4.3.4. keeping in view only those households which have

received remittances in the three selected years.

4.3.3 Pre and Post Remittances Incidence (Keeping in view total households)

This section provides the trends in the distribution of income keeping in view

total households belonging to different income groups. Pre-post Gini coefficients are

based on Lorenz curves without and with foreign remittances.

4.3.3.1 Pre and post remittances incidence in Pakistan.

The Gini ratios in Pakistan for pre and post- remittances incidence are given,

in table 15, it can be evidenced from given table that Gini ratios for pre remittance

distribution are smaller than the Gini ratios for post remittance distribution in all three

selected years 2001-02, 2005-06 and 2010-11. It can be seen that in the period 2001-02

pre remittances Gini ratio is 0.41, while the post-remittances Gini ratio for the same

year is equal is 0.42. In percentage terms, there is an increase of 2.44 percent in pre-

remittances Gini ratio after the remittances incidence has been observed. Hence, due to

the inclusion of remittance distribution of income, it has become more discouraging

for the lower income groups. In the same way, in 2005-06 pre-remittances Gini ratio is

0.42, while it has been increased to 0.55 after the inclusion of remittances in the same

108

Table: 15 Pre and Post Gini Coefficients (Pakistan)

Years 2001-02 2005-06 2010-11

Pre-remittances Gini

ratio

0.41 0.42 0.38

Post remittances

Gini ratios

0.42 0.55 0.56

Percentage variation

in Gini ratios

2.44 30.95 47.37


109

period in overall Pakistan.

In percentage terms, there is an increase of 30.95 in pre-remittances Gini ratio

after the inclusion of remittances. Finally, in 2010-11 pre remittances Gini ratio is

0.38, while the post-remittances Gini ratio is equal to 0.56, which is 47.37 percent

greater than its pre-remittances Gini ratio as shown in Table 15 (column 4, row 4).

It can be concluded that there is disparity between distributions of income in

different time periods. In all three selected periods (2001-02, 2005-06 and 2010-11)

the Gini ratios are increased. It may also be observed that the disparity between initial

distribution of income and post-remittances is greater in 2010-11 than in 2005-06 and

very small in 2001-02. The trend between above mentioned years may be interpreted

to mean that the distributional impacts of remittances in Pakistan are the largest in

2010-11 and the smallest in 2001-02.

4.3.3.2 Pre and post lorenz curves in Pakistan

The pre and post Lorenz curves are s hown in figures 5, 6 and 7 respectively.

From these figures, it can be concluded that the shapes and their positions are quite

consistent with the Pre and Post Gini ratios in Pakistan in all three selected time

periods.

4.3.3.3 Pre and post remittances incidence in urban areas of Pakistan.

The pre-post Gini ratios in urban area of Pakistan for pre and post remittances

incidence are given in Table 16, it can be evidenced from given table that

concentration ratios for pre - remittances distribution are greater than the Gini ratios

for post - remittances distribution in all selected periods. For example, in 2001 – 02

pre-remittances Gini ratio is 0.7181, while post - remittances Gini ratio for the same

110

Source: Drawn by using HIES Data by the Author

Figure 5: Pre- Post Remittances Lorenz Curve, 2001-02 (Pakistan)

111


Figure 6: Pre- Post Remittances Lorenz Curves, 2005-06 (Pakistan)

112


Figure 7: Pre and Post Remittances Lorenz Curves 2010-11 (Pakistan)

113

the same period is equal to 0.7182. In percentage terms, impact is almost same 0.014

percent increase in the pre-remittances Gini ratio after the remittances incidence has

been realized. Hence, due to the effects of remittances, distribution of income is almost

same for low income groups of urban areas. Similarly, it can be seen, in 2005-06 pre-

remittances Gini ratio is 0.2487, while it has increased to 0.2739 after the inclusion of

remittances in the different income groups in the urban areas. However, this time the

boost in Gini coefficient is 10.11 percent as can be seen in Table 16 Lastly, in 2010-

11, pre-remittances Gini ratio is 0.2211, while post-remittances Gini ratio is 0.2443,

which is 10.50 percent more than its pre-remittances Gini ratio as shown in Table 16

(row4, column 4)

It can be accomplished that discrepancy between initial distribution of income

and the post-remittances distribution is the largest in 2010-11, larger in 2005-06 and

almost the smallest in 2001- 02. This disparity may be interpreted to mean that the

remittances addition impact in urban areas is worsening in 2010-11, 2005-06 and small

in 2001-02.

4.3.3.4 Pre and post lorenz curves in urban areas of Pakistan

The pre-post Lorenz curves in urban areas of Pakistan which show,

correspondingly are depicted in figures 8, 9 and 10 respectively.

4.3.3.5 Pre and post remittances incidence in rural areas of Pakistan

The Gini ratios in rural areas of Pakistan for pre and post-remittances incidence

are given in Table 17. It can be evidenced from given table, that post Gini ratios for

post-remittances distribution are greater than the Gini ratios in pre-remittances

distribution in 2005-06 and 2010-11 but small in 2001-02 in rural areas. On the other

114

Table 16 Pre and Post Gini Coefficients (Urban)

Years 2001-02 2005-06 2010-11

Pre remittances Gini ratios 0.46 0.41 0.37

Post remittances Gini ratios 0.48 0.50 0.47

Percentage variation in Gini

ratios

4.35 21.95 27.58


Table: 17 Pre and Post Gini Coefficients (Rural)

Years 2001-02 2005-06 2010-11

Pre Gini ratio 0.36 0.38 0.35

Post Gini ratios 0.39 0.55 0.47


ratios

5.87 44.82 34.29


115

hand, these result are quite related as in case of Pakistan and urban areas in the same

period 2001-02. Looking at Table 17 in 2001-02, the Gini ratio is 0.36 in a pre-

remittances era, while its counterpart Gini ratio is 0.39 in a post remittances era. The

percentage increases in Gini ratio is 5.87 very small. Whereas, in 2005-06, the Gini

ratio of pre-remittances are 0.38, while in the same years post remittances Gini ratio

becomes equal to 0.55 which shows 44.74 percent increase in Gini ratio.

Finally, in 2010-11 the value of the pre remittances Gini ratio is 0.35 and that

of the post Gini ratio is 0.47 in a post remittances era. While, percentage increases in

Gini ratio are only 34.29 percent, which is smaller than Gini ratio in 2005-06 in rural

areas. In summary, the difference between initial distribution of income and post

distribution is the largest in 2005-06, larger in 2010-11 and smaller in 2001-02 in rural

in 2005-06 and 2010-11 the value of Gini coefficient increased after the addition of

remittances.

4.3.3.6 Pre and post lorenz curves in rural areas of Pakistan

The Pre and Post Lorenz curves in rural areas of Pakistan which show,

correspondingly are depicted in figures 11, 12 and 13 respectively.

4.3.3.7 Rural versus urban pre and post remittances Incidence

Table 18 shows pre and post- remittances Gini ratios and their comparisons for

urban-rural areas, in three selected years. The comparison of pre and post- remittances

Gini ratios for urban-rural areas, in three selected years is presented in the given Table

18.It can be seen that rural pre-remittances Gini ratios are smaller than urban pre-

remittances Gini ratios in the years 2001-02, 2005-06 and 2010-11. In other words, the

pre remittances income distribution in rural areas (Having relatively smaller Gini ratio)

116


Figure: 8: Pre- Post Remittances Lorenz Curves, 2001-02 (Urban)

117

.


Figure 9: Pre- Post Remittances Lorenz Curves, 2005-06 (Urban)

118


Figure 10: Pre- Post Remittances Lorenz Curve, 2010-11 (Urban)

119

are more equal distribution than their counterpart urban areas in all selected years

(compare row- column).

However, in 2001-02 the rural pre-remittances ratio is smaller than urban pre-

remittances Gini ratio (compare row and column). The urban Gini ratio is 0.46 and the

rural Gini ratio is 0.36 it means that pre-remittances income distribution is more equal

in rural than urban areas in 2001-02. However, the post Gini ratio of urban and rural

areas produced by post-remittances is 0.48 and 0.39, which is greater than the pre-

remittances ratio. It means that due the addition of remittances the distribution of

income in rural and urban areas have become more unequal than in the pre-remittances

era. Let us explain these facts and figures from another point of view, in Table 18 pre-

remittances Gini ratio in 2001- 02 is 0.46 in urban areas, while post-remittances

Gini ratio is 0.48 which is increasing by 4.35 percent. In 2005-06 pre-remittances Gini

ratio is 0.41 and post-remittances Gini ratio is 0.50, the percentage increase in the

urban Gini ratio in 2005-06 is 21.95 percent.

Similarly, in 2010-11 Gini ratio is 0.37 and post-remittances urban Gini ratio is

0.47. The percentage increase in the urban Gini ratio is 27.03 percent. Turning to

values of pre-post Gini ratios in rural areas and their percentage increase, in 2001-02

pre remittances Gini ratio is 0.36 and post remittances rural concentration ratio is

0.39. Thus percentage change is a 5.87 percent increase. In 2005-06 Gini ratios are a

0.38 and post-remittance Gini ratio is 0.55. The percentage increase is 44.74, in 2010-

11 pre-remittances Gini ratio is 0.35 and post remittances is 0.47. The percentage

increases in the rural Gini ratio is 34.29. Obviously, percentage increases in rural Gini

120


Figure 11: Pre- Post Remittances Lorenz Curves, 2001-02 (Rural)

121


Figure 12: Pre-Post Remittances Lorenz Curve, 2005-06 (Rural)

122


Figure 13: Pre-Post Remittances Lorenz Curves, 2010-11 (Rural)

123

ratio due to remittances addition in all selected periods. In other words, after induction

of remittances to each income group of urban-rural households, income distribution is

worsening in all periods for urban-rural income households. But income distribution is

relatively less worsened for urban and rural households in 2001-02 and income

distribution is more worsen for rural and urban areas in 2005-06. Now it can also be

compared in terms of the percentage given in rows.

4.3.3.8 Gini ratios by OLS method. (Keeping in view total households)

The results for fitting the data in Lorenz function , equation (3.3.4), by OLS

method are shown in the given Tables 19 and 20 for urban-rural areas and overall

Pakistan. The resulting OLS Gini ratios are also given in the same table for testing the

equality of β coefficients and thus a test for equality of distribution of income.

4.3.3.9 Chow Breakpoint test for structural stability

Chow test is used, as alternative for stability test that coefficient is stable, are

not different. (Chow, 1960). This test breaks the sample into two or more structures,

estimates the equation for each of them. Chow test is carried out for significant

difference in β coefficient. The null hypothesis of the Chow test asserts that no breaks

at specified break points, β1= β2. This test is an F test checking F statistics if over 5

percent we can accept the null hypothesis of no break and shows the equality of the

regression coefficient, if Fcal > Ftab, the hypothesis HO that parameters are stable

β1=β2=β is rejected and can be accomplished that there is proof of structural instability.

In Table 21, three types of test of experiments are shown by applying the Chow test. In

all three experiments, pre- post regression coefficients are statistically not significantly

different from overall Pakistan. So H0 cannot be rejected and coefficients are not

124

Table: 18 Pre and Post Gin Coefficients (Urban- Rural) 2001-02, 2005-06, 2010-11.

Years 2001-2002 2005-2006 2010-2011

Urban

Pre remittances

Gini coefficient

0.46 0.41 0.37

Post remittances

Gini coefficient

0.48 0.50 0.47

Rural

Pre remittances

Gini coefficient

0.36 0.38 0.35

Post remittances

Gini coefficient

0.39 0.55 0.47


coefficient (urban)

4.35 21.95 27.03


coefficient (rural)

5.87 44.74 34.29

Percentage difference in urban-

rural percentage variation in Gini

ratios

34.94 103.83 26.85


125

Table: 19 Results for Lorenz Estimation (Urban- Rural)

OLS

Experiment

2001-02 2005-06 2010-11

Pre- Remittances

Urban Rural Urban Rural Urban Rural

β 2.20 1.51 1.91 1.71 1.63 1.48

t- ratios 13.2 15.65 14.17 11.6 15.7 13.27

0.93 0.99 0.99 0.98 0.99 0.98

Gini- ratios 0.46 0.36 0.42 0.39 0.38 0.35

Post-Remittances


β 2.30 1.69 2.81 3.59 2.43 2.45

t-ratios 13.0 15.5 12.55 6.45 13.00 9.49

R2

0.99 0.99 0.98 0.90 0.98 0.96

Gini- ratios 0.48 0.39 0.53 0.59 0.49 0.49


126

Table: 20 Result for Lorenz Estimation in Pakistan

OLS estimation 2001-02 2005-06 2010-11

Pre- Remittances

β 1.74 1.97 1.65

t- ratios 16.28 12.03 13.7

R2

0.99 0.98 0.98

Gini-ratios 0.40 0.43 0.38

Post-Remittances

β 1.95 3.52 3.51

t- ratios 15.33 8.60 9.2

R2

0.98 0.95 0.96

Gini-ratios 0.43 0.59 0.59


127

statistically different and stable. But for urban areas in all three experiments the

regression coefficients for pre-post remittance distribution are statistically significantly

different at5 percent. However, for rural areas in all three experiments, the regression

coefficients for pre-post remittance distribution are statistically significantly different

at 1 percent in 2005-06 and at 5 percent in 2001- 02 and 2010-11at 5 percent

respectively. Here in all results p value is < 1 this mean Ho got rejected, it can be said

that the coefficients are different and not stable so there is a structural break in the data.

4.3.4 Pre and Post Remittances Incidence: (Remittances receiving households)

4.3.4.1 Pre and post remittances incidence in Pakistan

This section of the study presents the trends in the distribution of income by isolating

only those households which receive foreign remittances. Gini coefficients based on

Lorenz curves of income of households are measured and compared with the absence

of migration without foreign remittances and then with actual households income with

foreign remittances.

The pre-post Gini ratios in Pakistan for pre and post remittances incidence are

given in Table 22. It can be evidenced from the table that Gini ratios for pre-remittance

distribution are smaller than the Gini ratios for post-remittance distribution in all three

selected years 2001-02, 2005-06 and 2010-11. It can be seen, that in the period 2001-

02 pre-remittances Gini ratio is 0.47, and while the post-remittances Gini ratio for the

same year is equal is 0.63. In percentage terms, there is increase of 34.04 percent in

pre-remittances Gini ratio after the remittances incidence has been observed. Hence,

due to the inclusion of remittance distribution of income has become more

discouraging for lower income groups. In the same way, in 2005-06 pre-remittances

128

Table: 21 Chow Breakpoint Tests for Significant Differences in β Coefficients

Distributive Experiment F-statistical Probability

2001-02 Pre-post-Remittances( Pakistan) 1.24 0.31

2001-02 Pre-post-Remittances ( Urban) 3.37 0.05

2001-02 Pre-post-Remittances ( Rural) 2.86 0.08

2005-06 Pre-post-Remittances (Pakistan) 1.05 0.36


2005-06 Pre-post-Remittances (Rural) 4.09 0.03


2010-11 Pre-post-Remittances (Urban) 3.60 0.05



129

Gini ratio is 0.37, while it has been increased to 0.49 after the inclusion of remittances

in the same period in overall Pakistan. In percentage terms, there is an increase of

32.43 percent in the pre remittances Gini ratio after the inclusion of remittances.

Finally, in 2010-11 pre- remittances Gini ratio is 0.36, while the post-remittances Gini

ratio is equal to 0.46, which is 27.78 percent greater than its pre-remittances Gini ratio

as shown in Table 22 (column 4, row 4).

It may be concluded that there is disparity between distributions of income between

different time periods. In all three selected periods (2001-02, 2005-06 and 2010-11),

the Gini ratios have increased. It may also be observed that the disparity between

initial distribution of income and post-remittances is greater in 2001-02 than in 2005-

06 and 2010-11. The disparity between them may be interpreted to mean that the

distributional impacts of remittances in Pakistan was the largest in 2001-02.

4.3.4.2 Pre and post lorenz curves in Pakistan

The pre-post Lorenz curves are shown in figures 14, 15 and 16 respectively.

From these figures, it can be concluded that the shapes and their positions are quite

consistent with the pre-post Gini ratios in Pakistan in all three selected periods.

4.3.4.3 Pre and post remittances incidence in urban areas of Pakistan

The pre-post Gini ratios in urban area of Pakistan for pre and post-remittances

incidence are given in Table 23. It can be evidenced from Table 23 that Gini ratios for

pre-remittance distribution are lesser than the Gini ratios for post-remittance

distribution in all three selected periods. For example, in 2001-02 pre-remittances Gini

ratio is 0.45, while post-remittances concentration ratio for the same period is equal to

0.54. In percentage term impact is almost 20 percent increase in the pre-remittances

130

Table: 22 Pre-Post Gini Coefficients (Pakistan)

Year

2001-02

2005-06

2010-11

Pre-remittances

Gini ratio

0.47 0.37 0.36

Post remittances

concentration ratios

0.63 0.49 0.46

Percentage

variation in Gini

ratios

34.04 32.43 27.78


131

Gini ratio after the remittances incidence has been realized. Hence, due to the effects

of remittances, distribution of income is almost worsening for low income groups of

urban areas. Similarly, it can be seen in, 2005-06 pre-remittances Gini ratio is 0.35,

while it has increased to 0.41 after inclusion of remittances to the different income

groups in the urban areas.

However, this time the boost in Gini coefficient is 17.14 percent as can be seen

in Table 23. Lastly, in 2010-11, pre-remittances Gini ratio is 0.33, while post-

remittances Gini ratio is 0.36, which is 9.09 percent more than its pre-remittances Gini

ratio as shown in Table23 ( row4, column 4). It can be accomplished that discrepancy

between initial distribution of income and the post-remittances distribution is the

largest in 2010-11, larger in 2001-02 and smaller in 2005-06. This disparity may be

interpreted to mean that the remittances addition impact in urban areas is worsening in

all three selected time periods.

4.3.4.4 Pre and post lorenz curves in urban areas of Pakistan

The pre-post Lorenz curves which show, correspondingly in urban areas are

depicted in figures 17, 18 and 19 respectively. From these figures, it can be concluded

that shapes and their positions are quite reliable with Gini coefficient ratios in urban

areas of Pakistan in all three selected periods.

4.3.4.5 Pre and post remittances incidence in rural areas of Pakistan

The pre-post Gini ratios in rural area of Pakistan for pre and post remittances

incidence are given in Table 24. It can be evidenced from Table 24, that Gini ratios for

pre - remittances distribution are lesser than the Gini ratios for the post - remittances

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Figure 14: Pre-Post Remittances Lorenz Curves, 2001-02 (Pakistan)

133



134



135

Table: 23 Pre and Post Gini Coefficients (Urban)

Years

2001-02

2005-06

2010-11


ratio

0.45 0.35 0.33

Post remittances


0.54 0.41 0.36


in Gini ratios

20.00 17.14 9.09

Source: Calculated by author

Table: 24 Pre and Post Gini Coefficients (Rural)

Years

2001-02

2005-06

2010-11


ratio

0.447 0.38 0.36

Post remittances

Gini ratios

0.68 0.55 0.52


in Gini ratios

52.12 44.74 44.45


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distribution in all three selected periods. The Gini ratios in rural areas of Pakistan for

pre and post-remittances incidence are given in Table 24. It can be evidenced from

table that post Gini ratios for post- remittances distribution are greater than the Gini

ratios for pre- remittances distribution in 2001-02, 2005-06 and 2010-11 in rural areas.

On the other hand, these results are quite related as in case of Pakistan and

urban areas in the same periods. Looking at Table 24, in 2001-02, the Gini ratio is

0.447 in pre-remittances era, while its pre-remittances Gini ratio is 0.68 in a post-

remittances era. The percentage increase in Gini ratio is very large. Whereas, in 2005-

06 the Gini ratio of pre-remittances are 0.38, while in the same years post-remittances

in Gini ratio. Finally, in 2010-11 the value of the pre-remittances Gini ratio is 0.36 and

that of Gini ratio is 0.52 in a post-remittances era. While, percentage increases in Gini

ratio are only 44.45 percent, which is smaller than Gini ratio in 2005-06 in rural areas.

On the basis of results it can be concluded that the difference between initial

distribution of income and post distribution is larger in all time periods in rural areas.

It means that income distribution worsened in rural areas after inclusion of

remittances.

4.3.4.6 Pre and post lorenz curves in rural areas of Pakistan

The pre-post Lorenz curves which show, correspondingly in rural areas are

depicted in figures 20, 21 and 22 respectively. From these figures it can be concluded

that shapes and their positions are quite reliable with Gini coefficient ratios in rural

areas of Pakistan in all three selected periods.

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Figure 17: Pre-Post Remittances Lorenz Curves, 2001-02 (Urban)

138



139



140

4.3.4.7 Rural versus urban, pre and post remittances incidence

Table 25 shows pre and post-remittances Gini ratios keeping in view

remittances receiving households and their comparisons for urban-rural areas, in three

selected years. The comparison of pre and post- remittances Gini ratios for urban-rural

areas, in three selected years is presented in the Table 25.This show pre and post-

remittances Gini ratios and their comparisons for urban-rural areas, in three selected

years. The comparison of pre and post-remittances Gini ratios for urban-rural areas, in

three selected years is presented in the given table. It can be seen that rural pre-

remittances Gini ratios are greater than urban pre- remittances Gini ratios in years

2005-06 and 2010-11 and almost same in year 2001-02.

In other words, it can be said that pre-remittance income distribution in urban

areas (having relatively smaller Gini ratios) is more equal distribution than their

counterpart rural areas in years 2005-06 and 2010-11. (Compare row, column).

However, in 2001-02 the rural pre-remittances ratio is almost same with urban pre-

remittances Gini ratio (compare row and column) but variation in Gini ratio is very

small. The urban Gini ratio is 0.448 and the rural Gini ratio is 0.447 values are same, it

means that pre-remittances income distribution is almost equal in both rural and urban

areas in 2001-02. However, the post Gini ratio of urban and rural areas produced by

post-remittances is 0.54 and 0.68, which is for rural areas is greater than post-

remittances ratio of urban areas. It means that due to remittances addition, the

distribution of income in rural is worse than urban areas. Let us explain these facts and

figures from another point of view, in Table 25 pre-remittances Gini ratio in 2001-02

is 0.448 in urban areas, while post-remittances Gini ratio is almost same which 0.54

141



142



143



144

that increases in 20.54 percent. In 2005-06 pre remittances Gini ratio is 0.35 and post-

remittances Gini ratio is 0.41. The percentage increase in the urban Gini ratio in 2005-

06 is 17.14 percent. Similarly, in 2010-11 Gini ratio is 0.33 and post remittances urban

Gini ratio is 0.36. The increase in the urban Gini ratio is 9 percent.

Turning to values of pre-post Gini ratios in rural areas and their percentage

increase, in 2001-02 pre-remittances Gini ratio is 0.447 and post-remittances rural Gini

ratio is 0.68. Thus percentage change is a 52.12 percent increase. In 2005-06 Gini ratio

is 0.38 and post- remittances Gini ratio is 0.55. The percentage increase is 44.78

percent, in 2010-11 pre-remittances Gini ratio is 0.36 and post-remittances is 0.52. The

percentage increase in the rural Gini ratio is 44.45 percent.Obviously, percentage

increases in rural Gini ratio due to remittances addition to all selected n periods. In

other words, after induction of remittances to each income group of urban-rural

households, income distribution is worsening in all periods for rural urban income

households. But income distribution is relatively less worsen for urban and rural

households in 2010-11 (row, column) and income distribution is more equal for rural

and urban areas in 2001-02.

4.3.4.8 Gini ratios by OLS method. (Remittances receiving households)

The results for fitting the data, keeping in view the households receiving

remittances to Lorenz function, equation (3.3.4), by ordinary least method are shown

in the given Tables 26 and 27. The resulting OLS Gini ratios are also given in the same

table. This test shows that if structural relationships are altered the Gini-ratios should

differ considerably pre-remittances to post-remittances era.

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Table: 25. Pre and Post Gini Coefficients (Urban- Rural) 2001-02, 2005-06, 2010-11

Years

2001-2002

2005-2006

2010-2011

Urban Pre remittances

Gini coefficient

0.448 0.35 0.33

Post remittances

Gini coefficient

0.54 0.41 0.36

Rural Pre remittances

Gini coefficient

0.447 0.38 0.36

Post remittances

Gini coefficient

0.68 0.55 0.52


coefficient (urban)

20.54 17.14 9.09


coefficient (rural)

52.12 44.741 44.45

Percentage difference in urban

rural percentage variation in Gini


153 161 389


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4.3.4.9 Chow Breakpoint test for structural stability

Chow test is also used to keep in view the households receiving remittances to

see, that the coefficient is stable are not different. In Table 28, three types of tests have

been shown by applying Chow test keeping in view the household receiving

remittances. In first three tests, for Pakistan, the regression coefficients for the pre-

remittances distribution are statistically not significantly different from their Pakistan

counterpart for the post-remittances distributions. These results are same as in case of

total households receiving remittances. So it cannot be rejected Ho that difference in

post-remittances inequality is merely due to chance variation. So it can be said that

coefficients are not statistically different and stable. Similarly for urban-rural areas in

first two test regression coefficients for the pre-remittances distribution is statistically

not significantly different from their counterparts in the post-remittances distributions.

Third test for urban-rural areas in the same type of test, the regression

coefficients for pre remittance distribution are statistically significant different at 1

percent and 5 percent of post remittance distribution for their counterparts. This shows

that post-remittances Gini ratios in urban-rural areas possess significantly more

inequality in the distributions than that the pre-remittances Gini ratios in these areas in

each time period. Hence, remittances significantly increase the final (post-

remittances) income inequalities in urban and rural areas.

4.3.5 Analyses of Total Households Versus Remittances Rreceiving Households.

This section 4.3.5 of the chapter presents the comparison of section 4.3.3

keeping in view total households, and section 4.3.4 keeping in view household

receiving remittances in Table 29 for Pakistan and its urban - rural areas for three

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Table: 26 Results for Lorenz Estimation (Urban- Rural)

OLS

Estimation 2001-02 2005-06 2010-11

Pre- Remittances


2.19 2.18 1.49 1.63 1.34 1.52

t- ratios 21.42 15.3 15.7 14.8 19.2 11.32

R2 0.99 0.98 0.99 0.98 0.99 0.98

Gini- ratios 0.46 0.46 0.36 0.38 0.33 0.36

Post-Remittances


3.16 6.39 1.88 3.40 1.54 3.06

t-ratios 14.56 8.4 12.5 8.6 16.27 7.22

R2 0.98 0.95 0.98 0.95 0.99 0.93

Gini-ratios 0.56 0.74 0.42 0.58 0.36 0.59


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Table: 27 Result for Lorenz Estimation (Pakistan)

OLS Estimation 2001-02 2005-06 2010-11

Pre- Remittances

2.40 1.60 1.49

t- ratios 17.4 15.3 13.8

R2 0.99 0.99 0.98

Gini-ratios 0.48 0.37 0.36

Post-Remittances

4.66 2.68 2.31

t- ratios 11.4 10.08 10.59

R2 0.97 0.97 0.97

Gini-ratios 0.66 0.51 0.47


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Selected time periods 2001-02, 2005-06 and 2010-11. In case of overall Pakistan in

2001-02 changes in income distribution between excluding and including foreign

remittances measure Gini coefficient. The pre-Gini ratio keeping in view total

households is 0.41 and post-Gini ratio is 0.42, while the pre-Gini ratio keeping in view

households receiving remittances is 0.47and the post Gini ratio is 0.63.Gini coefficient

raises in percentage term 2.44 keeping in view total households and 34.04 percent,

while keeping only household receiving remittances.

It means that after inclusion of foreign remittances inequality increase and

income distribution is more worsen households receiving remittances. Similarly, it can

be seen that inequality of income raises more for households receiving remittances in

2005-06 and 2010-11 years. It can be concluded by comparing percentage variation in

HIES three data sets, that income distribution worsen due to the addition of

remittances in Pakistan. This study may conclude that foreign remittances have a

negative effect on the distribution of income.

Similarly, pre-post Gini ratios can be compared to urban areas in three selected

time periods. In case of urban areas in 2001-02, the pre-Gini ratio keeping in view total

households is 0.46 and post-Gini ratio is 0.48, while the pre-Gini ratio keeping in view

households receiving remittances is 0.45and post Gini ratio is 0.54.Gini coefficient

raises in percentage term 4.35 keeping in view total households and 20 percent, while

keeping only household receiving remittances. It means that after inclusion of foreign

remittances inequality increase and income distribution is more worsen households

receiving remittances. Similarly, it can be seen that the inequality of income raises

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Table: 28 Chow Breakpoint Tests for Significant Differences in β Coefficients

Distributive Experiment F-statistical Probability

2001-02 Pre-post-Remittances( Pakistan) 1.16 0.33


2001-02 Pre-post-Remittances ( Rural) 2.49 0.11





2010-11 Pre-post-Remittances (Urban) 4.68 0.02



151

more for urban households receiving remittances in 2005-06 and 2010-11 years.

Moreover, study can also compare pre-post Gini ratios in rural areas in three

selected time periods. In case of in 2001-02 year, the pre-Gini ratio keeping in view

total households is 0.36 and post-Gini ratio is 0.39 while the pre-Gini ratio keeping in

view households receiving remittances is 0.44and the post Gini ratio is 0.68.Gini

coefficient raises in percentage term 5.87 keeping in view total households and 54.54

percent, while keeping only household receiving remittances. It means that after

inclusion of foreign remittances inequality increase and income distribution is more

worsen households receiving remittances. Similarly, it can be observed that inequality

of income raises more for rural households receiving remittances in 2005-06 and 2010-

11 years.

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Table: 29 Comparisons for the Analyses of Total Households versus Remittances

Receiving Households.

Years HIES 2001-02 HIES 2005-06 HIES 2010-11

Pakistan

Keeping

in view

total

household

Keeping

in view household receiving remittances

Keeping

in view

total household

Keeping in

view

household

receiving

remittances

Keeping

in view

total household

Keeping

in view

household

receiving remittances

Pre Remittances Gini

0.41 0.47 0.42 0.37 0.38 0.36

Post Remittances Gini

0.42 0.63 0.55 0.49 0.56 0.46

Percentage

Variation

Gini ratio

2.44 34.04 3.95 32.43 47.37 27.78

Urban


0.46 0.45 0.41 0.35 0.37 0.33


0.48 0.54 0.50 0.41 0.47 0.36

Percentage

Variation

Gini ratio

4.35 20 21.9 17.14 27.58 9.09

Rural


0.36 0.44 0.38 0.38 0.35 0.36


0.39 0.68 0.55 0.55 0.47 0.52

Percentage

Variation

Gini ratio

5.87 54.54 44.82 44.74 34.29 44.45


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SUMMARY

This section of the chapter presents the summary of the dissertation related to

foreign remittances, economic growth and distribution of income. This part concludes

the discussion of the results regarding the research hypotheses presented in chapter 1.

This discussion surrounds with particular attention that finding related to hypothesis 3

is not supported. This chapter provides few policy implications related to the findings

of this dissertation. This part also illustrates the limitations of this dissertation and

provides recommendations for the directions of future research in this area.

The present dissertation is an attempt to contribute to explore the answer of an

important economic issue that whether the increase in foreign remittance inflow in

Pakistan contributes to its economic growth and somehow affect the income

distribution or not. For this purpose, this dissertation is built in two steps. To this end,

in the first step, this dissertation intends to test the first hypothesis that there exist

long-run relationship between foreign remittances and economic growth by using time

series data from 1972-73to 2012-13. In second step, the impact of foreign remittances

on income distribution has been assessed and compared by using three HIES surveys

for the years, 2001-02, 2005-06 and 2010-11 in case of Pakistan. The findings of the

study illustrate that foreign remittance inflows have a distinctive importance of

economy of Pakistan and vividly contribute to the economic growth and affect the


Review of related literature has shown that no attempt has been yet explored on

the same nature of this study. However, some relevant studies have been reviewed,

154

which explored the impact of foreign remittances on growth. Similarly, few studies

have been reviewed on the impact of foreign remittances and the distribution of

income. While, most of the reviewed studies are related to the impact of remittances

on poverty alleviation. According to Quiz (2005), “in Pakistan foreign remittances

play a significant role in alleviating poverty, reducing inequality, giving impetus to

economic growth, development and reduce current account deficit since long”.

However, this research contributes to the existing literature by broadenings the scope

of this study and investigates the impacts of foreign remittances on both economic

growth and the distribution of income.

In the 1st step of this research study, in order to see the long run relationship

between the variables, along with main macro-economic variables like GNP, private

consumption, private investment and imports are included in the model. To this end,

available time series data for the period 1972-73 to 2012-13 is used. To conduct this

analysis, the ADF test for stationary of the variables has been applied. Johansen’s Co-

integration, of long run relationship and error correction model for short run

relationship among the above mentioned macro variables have been used.

The investigating test of the study shows that the model is well fitted and there

is no serial correlation. Ramsey’s RESET shows that the functional form is accurate.

Normality test also confirms that the data is normally distributed and the

heteroscedasticity test also supports and shows that there is no heteroscedasticity.

In this study ADF test is used to check the stationary of the main

macroeconomic variables which shows that all variables are stationary at first

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difference with the constant and linear trend. This show that variables are integrated of

order I (1). So the study has been preceded with the Johansen’s co-integration

techniques and error correction model.

The test statistics of the Trace test and Max-Eigen value reveal that the null

hypotheses of no co-integration has been rejected, while, the other hypothesis that

there is at least one co-integrating vector has been accepted by the test at the 5 percent

level of significance. Accordingly, it is concluded that there is one co-integrating

relationship involving the variables LNGNP, LNCONs, LNIMP, LNINV and LNFR.

The presence of co-integrating vector shows that there exists a stable, long run

relationship between gross domestic production, consumption, imports, investment and

foreign remittances.

The analysis of the results of 2SLS indicates that variables which determine the

economic growth have expected signs. Hence foreign remittances, consumption and

investment positively affect the economic growth, whereas imports affects negatively.

Empirical findings indicate that foreign remittances have a positive effect on economic

growth and the 3rd most substantial effect on GNP i.e. 1.07. This means that 1 percent



This analysis provides empirical support and also indicates positive long run

relationships between economic growth, consumption and investment. This is in line

with the general assertion that consumption and investments are the key components

of economic growth. On this estimation 1 percent increase in consumption leads to

increase in GNP by 1.10 percent at the 1 percent level of significance. Similarly, a

156

percent increase in investment leads to increase in GNP by 1.34 percent at the 1

percent level of significance. These relationships are inconsistent with economic

theory. Results indicate that imports have the negative long run relationship with the

economic growth, i.e. a percent of imports leads to decline in GNP by 0.17 percent.

However, this relationship is insignificant. This means that rising in imports deters

economic growth. Empirical evidence for a number of researchers also confirm these

relationships. The findings are consistent with the narrative of Mugal (2012), Ahmad

(2006) and Gilani, (1981).

Short run dynamics also contribute to the long-run relationship and indicate the

stability of the model. The short run dynamics indicate that the short run impact of

remittances, consumption and investment is positive and statistically significant.

Imports exert negative statistically significant effects on economic growth in the short

run and the size of negative effect on economic growth is weaker than long runs. GNP

increase 0.25, 0.12 and 0.04 percent as a result of 1 percent increase in consumption,

investment and remittances respectively. The short run coefficients of all variables are

smaller than long run estimates. This confirms that results of research studies are

reliable and efficient.

The coefficient of the Error Correction Term (ECT) provides information about

the speed of adjustment towards the long run equilibrium after a short run shock. The

estimate of the Error Correction Term, i.e. ECMt-1 bears the negative sign and

statistically significant at the 1 percent level of significance. The coefficient of ECMt-1

is -0.21, significantly different from zero, indicating the existing of error correction

mechanism and implying that the GNP, CONs, INV, IMP and FR converge to long run

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equilibrium. The speed of adjustment of the equilibrium suggests that if a shock

inserted into the model 21 percent deviation is rather corrected within the first year.

This speed of adjustment is relatively slow. This confirms the long run established

relationship among the variables.

To understand the relationship among foreign remittances and the distribution

of income, two more hypotheses are tested in the 2nd step of this dissertation. For this

purpose, primary data HIES files were obtained from the Federal Bureau of Statistics

(FBS) than households and their income with and without remittances are sorted at

overall and the urban-rural level of analysis. Three HIES data are analyzed and

compared to SPSS and MS Excel by using different statistical techniques, like average,

percentage, Ordinary Least Square (OLS), Gini coefficient, Lorenz curves. Chow test

for structural stability has been applied to examine the data. The findings on the basis

of the above mentioned techniques are as under.

By analyzing and comparing the trend in the percentage distribution share of

household’s income and remittances, the study finds that migrants are not fairly

distributed among the quintile having income groups. The lowest income quintiles

actually produce one of the highest shares of total migrants in overall Pakistan and its

rural area, but however, in urban areas it is not the lowest. Findings of the 2nd step, of

the chapter No: 4 also show that foreign remittances may have no positive effect on

income distribution in Pakistan and in its Urban-Rural areas in the years 2001-02,

2005-06 and 2010-11. This study calculates and compares Gini ratios accompanied by

Lorenz curves for pre-post remittances incidence by using HIES data for the years

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2001-02, 2005-06 and 2010-11, keeping in view remittances income imputed to the

total households belonging to different groups and keeping in view remittances

receiving households only. This research study finds that foreign remittances have

worsened the effect on income distribution in Pakistan and in its urban-rural areas in

all three selected time periods for both groups of households. This result is in favour of

the hypothesis: 2 of the study.

The study also shows when foreign remittances are included in income (while

keeping in view remittances income imputed to the total households belonging to

different groups) and the rise in Gini co-efficient, ranges between 4.35 to 44.74

percent in urban rural areas of Pakistan. On the other hand, the rise in Gini co-

efficient, ranges between 9.09 to 52.12 percent in urban rural areas of Pakistan in case

of analyzing the remittances receiving households only. However, the increase in Gini

ratios after incorporating foreign remittances in the analysis for both groups of

households in all three selected year have been larger in rural areas than that of urban

areas. This means that post-remittances income distribution has been more worsened

for rural areas comparatively. This result is against hypothesis: 3 of the study.

Gini ratios have also been calculated again by Ordinary Least Square method

(OLS) for Pakistan and its urban-rural areas for three selected time periods. These

ratios have also been increased in all cases, which support the results that income

distribution has been worsened in case of Pakistan.

The study also applies Chow breakpoint test for structural stability for both

groups of households. This test is used for knowing that two distributions under

examination are statistically significantly different from each other or not. The results

159

of the study show that most of the distributions are statistically significantly different.

However, some of the distributions are not statistically significantly different.

CONCLUSION

The findings of the first part of the dissertation enable us to have a good

appreciative of the impact study of foreign remittances on economic growth. The

quantitative evidences have shown that growth is positively related to foreign

remittances and there is a long run relationship among the variables during 1972-73 to

2012-13. The findings of the 1st part, of the chapter: 4 also support the first hypothesis

of the study there is relationship between economic growth, foreign remittances,

private consumption, private investment and imports in Pakistan. It is concluded in this

dissertation that the foreign remittances may impact positively on the economic growth

but is not fairly distributed among the income groups. So the remittances may improve

the economic growth and may not always improve the distribution of income and even

may contribute to income disparity in the country.

On the basis of the findings of the first part of the study, it may conclude that

foreign remittances appear to be a main source of short and long term sustainable

economic growth in case of Pakistan. Similarly, foreign remittances appeared to be an

significant cause of capital formation for economic growth presenting considerable

positive effect on components of growth. The findings of the study are also supported

by Mughal, (2012), Ahmad (2006), Sattar (2005) and Gilani, (1981).

Further on the basis of the findings of the 2nd part of the dissertation, the study

may conclude that foreign remittances have worsening effect on income distribution

because during data analysis, it has been observed that foreign remittances are not

160

distributed fairly, equally through the income groups. The numbers of the households

in the the different lowest income groups are very few in all three data sets as

compared to middle and upper class income groups. It may be concluded that it is due

to variation in the quantity of migrants formed by different income classes in the home

country and not differences in whichever migrant income abroad or marginal

propensity to remit that cause foreign remittances may have a negative effect on the

distribution of income. It may also be concluded on the basis of the results of the study

that due to high migration cost and risk lower income groups cannot afford to migrate

as compared to high income groups. These results are aligned with the migration

cumulative theory related to upper end classes and which is also applicable in

countries like Pakistan.

During the last decade, the economy witnesses’ remarkable growth rate due to

high capital inflow in the form of workers’ remittances which increase real wages.

However increase in wages and workers’ remittances is not spread evenly among

households belonging to lower and the lowest groups which seems to increase income

inequality. However, the income class from which migrants come appears to be the

most significant element in explaining that remittances increase income inequality

over time. Findings for distribution of income are contradictory with the findings of

some previous studies Adam, (1998) Richard and Brown, (2006) and Mughal and

Anwer, (2012).

The analysis of the results of the chapter five indicates that the distribution of

income is worsening, perhaps due to the distribution pattern of remittances among

different income groups lowest, lower. Moreover the findings of the study indicate that

161

foreign remittances are appeared to increase income inequality and more so in urban

areas than rural areas. The study also shows that the size or volume of foreign

remittances contributes to growing more rapidly in overall income inequality in

Pakistan. The findings of this dissertation consistent with the previous work of Lipton,

(1980), Adam, and Gilani, (1981).

At the end on the basis of the findings of this dissertation in chapter 4,

remittances versus economic growth analysis and in chapter 5, remittances verses

income distribution analysis, the study may conclude that foreign remittances have a

long run relationship with economic growth during 1972-73 to 2012-13. Whereas

foreign remittances have a negative effect on income distribution in Pakistan and its

urban-rural areas in three selected time periods. Perhaps, it may conclude that this is

due to increase in foreign remittances that economic growth has increased, which in

result increase national income as a whole, but the distributing it among the

households in Pakistan more or less in a pro-rich manner.

POLICY IMPLICATIONS

Keeping in view the findings of the dissertation, the study advocates that it is

imperative for Pakistan to maximize the benefits of labor migration and its resultant

foreign remittances. The empirical findings of the study are important for policy

makers and few policy recommendations are highlighted for their considerations.

Foreign remittances are an important source of external capital inflow that can

help in enhancing both economic and social development in Pakistan. Since evidence

from some component of the study also reveals that there is strong connection among

foreign remittances, economic growth, private consumption, private investments and

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imports in the country. The analysis related economic growth is helpful for taking the

initiative and incentives for policy makers to support and stimulate migration in a way

to attract as much remittances as possible so as to maximize the benefit of foreign

remittances. During the financial year 2015-16, the growth rate target up to 5.5 percent

has been set by the experts. To achieve this target, the role of remittances is also

remarkable.

An important and relevant question arises, how Pakistan can attract and

maximize the benefit of foreign remittances? Firstly, the country needs to think about

adopting the institutions that facilitate in amplifying the positive economic growth

impacts of foreign remittances for sustainable development. The important tip is to

first to make the policies that formulate the entire implementation cheap, safe and

easy to collect foreign remittances. Encouraging impacts of foreign remittances on

economic growth are additionaly possible to take place when foreign remittances are

transmitted in proper channels. Pakistan must establish well-organized and helpful

proper channels for receiving foreign remittances.

Secondly, if Pakistan wants to enhance economic growth through investment,

financial sector policies may be taken care by policy makers. The financial sector may

be arranged independent authority to control the official transmission of foreign

remittances. Favorable cost structures for remitting money through financial sector

regulation can be considered. Government needs to devise its policy measures making

the system and channels of the remittances more convenient, expedient and productive.

The country may modify its immigration standards by exploring some of reciprocal visa

arrangements with neighboring countries. Moreover, the government may provide

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incentives that make remitting money using official channels cheaper as compared to

the unofficial ones. It could be done by improving the banking services, quality and

accessibility of the remittances receiving households. Moreover, all migrants must be

properly and technically guided regarding the money transfer process such as opening

of bank accounts and sending money at home. Virtual and on-line arrangements would

be a hall mark in the process of facilitation.

Thirdly, by promoting the confidence of the immigrants and by providing more

lucrative investment opportunities to attract and forcing them to remit their earnings

into their home country. This will lead to an increase in the level of private investment

in the country leading to increase in output, employment opportunities and reducing

the import bills.

Fourthly, to encourage the use of foreign remittances in productive

investments, financial sector policies need also to be complemented with other policies

favouring for the increased use of foreign remittances in funding entrepreneurial

activities in the economy. There is a need of a policy for an effective and efficient

distribution system, that is, a vibrant financial system that can mobilize remittances.

Recipient households may be influenced to save their earnings so that the foreign

remittances can be disseminated to investment activities of the economy.

Fifthly, there is a dire need for policies that protect home industries even when

foreign remittances are used for consumption goods. Foreign remittances are possible

to have a positive growth effect for a home country when they are used to purchase

locally produced goods.

164

The findings of the second part of this dissertation are to focus on policy to

improve the distribution of income and reduce income inequality in Pakistan well as

in its urban-rural areas. For improving the distributional impacts of foreign

remittances, steps require to be used to facilitate poorer groups of the households to

have contact for employment opportunities in abroad. One measure as gauged from the

findings of the study is to focus on the income classes from which migrants came

would contribute to overall worsening the distribution of income.

Moreover, policies should emphasize and access lower and the lowest income

groups to enhance migration opportunities for them. Foreign remittances can improve

the distribution of income if the less privileged classes are also able to migrate. It

could be done by establishing migrants' network and migration centers” in urban- rural

areas to process visas, work contracts, and loan arrangements for prospective external

migrants. This would reduce the migrants, cost and risks by providing financial and in

kind assistance to lower and the lowest income groups migrants, as well as helping

them in arranging jobs for them abroad. So it is suggested that the system of migration

needs to be continued and regularized in Pakistan to improve its distributional effects

over time. The government may come into agreements such as the agreement signed

with Malaysia. The overseas missions should not only assist in getting jobs, but they

should also in touch with the issues like the exploitation of Pakistani workforce out of

the country. However, if migrants are from higher income classes, it might ultimately

aggravate income disparity.

Ministry of Labour and Manpower along with respective departments in

various provinces should chalk out some integrated policies for making our potential

165

and aspirant labour productive, efficient and effective for international markets

keeping the emerging domains of skills and capabilities in view. The focus on virtual

jobs should also be made to reap benefits of highly paid online-line jobs particularly in

services sector which is leading in the world.

FUTURISTIC VISION

This study highlights the importance of foreign remittances for the economy of

Pakistan and helps in understanding its role in accelerating economic growth and

affecting income inequality in Pakistan. Moreover, the foreign remittances have

significantly increased over the years since 2001. Further, since the mid- nineties

Household Income and Expenditures (HIES) Survey has been available and may be

utilized for determining the impact of remittances on the distribution of income and

growth. So further researches which may be required in this area are being

recommended for the future. Finally the2nd part of the dissertation has limited itself to

the impact of remittances on the distribution of income, but the analysis can be

extended a few steps further. The mixed findings of the 2nd part of the dissertation

invoke a question for future research that to see the role of remittances in the trends in

the distribution of income. Some sort of general equilibrium analysis can also be

employed.

This study has been conducted to see the long-run relationship among foreign

remittances on economic growth of Pakistan by using the interaction of five

macroeconomic variables. Replication of this study by including more variables may

be undertaken to extend the analysis. A great deal of research work is required to

166

explore such pattern of foreign remittances, which can acquire fairer distribution of

income in the country like Pakistan.

Present study opens the door for other researchers to conduct their research in

this field by using governmental huge data sources that is available with Federal

Bureau of Statistics. Moreover, they may also extend their study to see the impact of

foreign remittances on education, health and agriculture, etc. Following the

methodology of this study, the researchers intend to do work in this area may segregate

the analysis at provincial levels.

167

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APPENDICES

APPENDIX-A Some Concepts and Terminologies

Defining Income

Income often stands for the taxed income per individual or per household. Here

income inequality measures also can be used to compare the income distributions before and

after remittances in order to measure the effects of remittance income. (HIES 2010-11)

The Household

A household can be defined as a single person or a group of people who live together

as a single unit in the sense that they have common housekeeping arrangements; that is, they

have common provision for food and other essentials of living. Persons living in the same

dwelling, but having separate catering arrangements constitute a separate household. The

individual and the family are the subsets of a household. A household may consist of an

individual or a family or families or plus other persons, or contain only unrelated persons. A

ledger that usually lives in a household, but takes meals at a hotel, restaurant, etc, will

constitute a separate household. Whereas, a group of people living separately, but taken their

meals together will constitute a distinct household. (HIES 20010-11)

Household Income

It means material returns in cash or in kind in exchange for goods and services, etc.,

by household earners other than boarders, loaders and servants. The income of a household

may be classified into monthly and annual income in cash or in kind and imputed income.

Monthly income shall relate to wages, salaries, persons, contribution made by boarders and

lodgers and professional’s fees, etc. whereas yearly income shall refer to interest and

dividends, earning from agriculture actives, business commercial and industrial undertakings

land and property rents gifts and assistance (zakah) and relief in cash or in kind, bonus, social

and insurance benefits, etc. it also includes the remittance from other household remembers

who are permanently absent. (HIES 20010-11)

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Income in Cash

It means money receipts such as wages, salaries, rent from land and property, income

from self-employment, gifts (nazaran) assistance (zakah) etc. (HIES 20010-11).

Imputed Income

It is the estimated value of current market prices of the goods received by the

household for which no cash payment is made. Imputed income may comprise the estimated

value of home produced goods consumed by the household rent free dwellings, gifts and

assistance received in kind and provision of free meals by an employer. (HIES 20010-11)

Household Expenditure (HIES 20010-11)

It means the total expenses incurred in the survey year, whether or not payment was

made during the years. Similarly, payment made in the survey year on the purchases prior to

the survey year is not recorded as expenditure.

Income Distribution

The term "income distribution" is usually coined to "picture" who receives how much

income within a specific society.

Functional and Size Distribution of Income

To deal with the distribution problem analytically one to be very clear about these two

basic concepts. There are two principal concepts of income distribution encountered in the

literature: the functional and the personal or size distribution of income. The distinction

between the two has been elaborated below.

Functional Distribution of Income

A large part of theoretical literature has been erected around the concept of functional

distribution of income. The functional distribution shows how much income is received by

each factor of production. This is how total income is distributed between land, labor and

capital. Theories based on functional distribution consider the existence of only three groups

(or classes) in society: laborers, capitalists, and landowners, assuming within group

homogeneity. It elaborates the share of total national income that each factor of production

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receives. Process of functional income distribution requires the comparison the percentage that

labor receives as a whole with the percentage of total income distributed in the form of rent,

interest and profit. The actual process can be illustrated by the firm-individual relationship. At

first the flow from the firm to individuals, who are the owners of the factors employed. The

landlord receives his rent, the worker his wages, the investor his interest and profits.

The war of tug between entrepreneurs and workers springs from the conflict of

interests present among them. As, it is well known, the profit is the residual balance of the

activities of the firm or, saying more precisely, is the share of entrepreneurs. So, the quantum

of this residual depends upon the payments made to other factors, that is, if wage, rent and

interest rates are decreased (increased), the profit will be increased (decreased). Remember

that the profit also varies with the prices of commodities and services produces by the firm, but

it is not poining to be concentrated in our present discussion.

It is obvious from the interdependent nature of profit with other rewards that the

willingness of entrepreneur to hire factors of production in such proportion, which gives him a

larger share in the enterprise, plays a major role in the distribution of rewards. The theory that

explains the extent of the willingness of entrepreneur in hiring factors of production is termed

as “marginal productivity theory of factor prices.” This theory elaborates that factor will be

rewarded well or ill according to its contribution to the total product or revenue of the firm.

Formally, marginal productivity theory can be defined as the increase in total revenue

or total output of the firm resulting from the employment of an additional (last) unit of the

factor. The specification of the term additional unit with the ‘last unit’ necessitate that the

marginal unit of the factor is the unit the entrepreneur has just hired, in an expanding industry;

or is about to discard in a contracting industry.

It is clear that the demand for factors is created by entrepreneurs in the factors market

and this demand is a derived demand, which arises not due to the factors are demanded for

themselves, but for what they can create: goods and services. This process bestows the

entrepreneur maximum profit through the channel of last cost combination of the factors and

the greater revenue from the sale of these goods and services. So, if demand for final goods

and services. So, if demand for final goods and services produced by a firm is higher (lower)

than the demand for the factors producing those goods and services by the firm will be higher .

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Size Distribution of Income

On the other hand, the size distribution of income shows how many individuals

(or households) receive how much income. This is how total income, from all sources, is

distributed among individuals or households. Other concepts of income distribution sometimes

used in the analysis of income inequality are those which make a distinction between urban

and rural areas as well as interregional or interstate differentials. However, the theoretical

debate about income inequality has been focused on the concepts of functional and size


There are many criticisms of the marginal productivity theory; but we explore those,

which serve our purpose of shifting the discussion from functional to the size distribution of

income. To judge a country’s performance, empirical verification by using facts and figures is

unavoidable, marginal productivity theory of distribution on the other had possessed mostly

theorizing style and very little bother for empirical verification.

Hence, functional distribution is less helpful in an empirical work of our type,

especially, where horizontal and vertical equity are the objectives of a national government.

Furthermore, grouping of factors with different incomes is also difficult. For example, groups

of workers with identical skills, who are paid alike, difficult to construct practically due to the

difficulty of identifying better and worse workers with common skill. So some workers in that

skill will be paid more; some will be paid less than their actual individual marginal products.

Similar difficulties can be seen in the grouping of workers of a given sex, age and educational

qualification in a particular industry, where firms may pay these groups same wages.

Especially, in the beginning due to the problem of accurately measuring the marginal products

of individuals.

All the above problems can be avoided by adopting the idea of size distribution,

particularly, when one wants to judge empirically the effect of government programme upon

different income groups of the society as a whole. Concept of size distribution of income also

bestows the researchers different tools; like, Lorenz curve and Gini concentration ratio, for

examining the degree of fair of worse distribution of income. Needless to say, the above

outcomes of the concept of size of distribution of income have made easy to examine the

poverty conditions of a country at an aggregate level.

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Playing the final round against functional distribution of income, a person may be the

employee of a firm but, at the same time, he is earning interest from his investment or he may

have inherited property that can comprise many forms. For example, fertile land, commercial

land, residence building given on rent etc. so it will be difficult to categories him rightly.

The only solution is to divide all individuals not on the basis of their sources of

earning but on their earning. This above notion leads us to a precise definition of personal or

size distribution of income, which can be defined as, “It is a measure that solely deals with

individual person or households and the total earning they receive, while ignoring their sources

of income”. It means that no matter the incomes in the pockets of persons or households are

derived from employment only or from other different sources like profits, rents, interest,

inheritance, gifts and so forth, they are grouped according to their quantum of incomes and not

according to the different channels by which their earnings move into their pockets.

Also, the occupational sources of earning like trade, manufacturing, agriculture,

services and the spatial consideration or location are shrugged off. Moreover, number of

working hours, sex, age, educational qualification, skill, experience, status and other items of

these types deserve no attention. For example, if a person A is more qualified than a person B,

but they possess same quantum of earning, then they will be adjusted in the same group

irrespective of the difference in their qualification. Same is the case with other items.

The procedure of constructing a size distribution of income for a country is very

simple. Firstly, different income groups, each having some particular income ranges, are

ordered in ascending fashion. And then, according to their personal incomes, all individuals or

households are adjusted in different income groups, having definite income ranges. This

process gives a column of income groups in ascending order. The second column is of

personal income, which is usually taken in percentage; this column determines what

proportion of total national income each income group receives.

A-1 Theories of Income Distribution

General Theories of Income Distribution

If some agreement arises from all the debates about distribution of income along the

history of economic thought this is that there is no agreement among economists about which

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are the determinants of income distribution. The main reason is that the distribution of income

is the final result of the entire economic process (Bigsten, 1983), and it is well known that

there is a lack of unanimity of views even on general economic issues of that process, which

makes it logical to expect no agreement on a topic that has been the source of ideological wars

and political revolutions (Sahota, 1978). A theory of income distribution needs a theory which

explains the prices of factor of production and factor shares that would explain the factorial

distribution of income. "Most theories conceive the central problem of income distribution

as the determination of the level of employment and remuneration of the factors of production,

usual y grouped into capital and labor. They differ mainly in their assumptions about market

behavior and the way in which wages and product prices are determined" (Ahluwalia and

Chenery, 1983, p. 43). But a theory of size, income distribution needs to explain also the

distribution of the ownership of factors among households (Knight, 1976). Some theories fail

in going further than the functional distribution of incomes. The classical period

was characterized by focusing only on the functional distribution. Adam Smith devoted his

work to the causes of wealth and discussed the division of what was produced between wages,

rent, and profit, but he did not develop a theory about the determinants of such distribution.

David Ricardo was the one who placed the distribution of income at the center of his thought.

According to Ricardo, the Political Economy was aimed at determining the laws that rule the

distribution of income (Bigsten, 1983; Ferrán, 1997). "He was the first economist to derive a

meaningful income distribution, theory" (Bigsten, 1983, p. 4). The productive factors are land,

capital and labor, and total income is distributed according to rent, profits and wages. The

basic idea in Ricardian thought is that a differential rent is produced only when less fertile

lands are exploited requiring more capital and/or labour leading to a rise in the price of

agricultural products. As a consequence, the owners of the most fertile lands receive an

increased rent. This is why Ricardo insisted that the increase in rent is not a cause but a

consequence of wealth (Ferrán, 1997). In the Ricardian system, distribution is prior to

exchange, thus income distribution does not depend on demand for final products (Bigsten,

1983).The distribution of total income works as follows: the surplus over the production costs

(output value) constitutes the rent and the rest is distributed between profits and wages. "The

Ricardian system accepts a Malthusian unlimited supply of labor at the subsistence wage in the

long-run; it assigns to 'profits' the residual between the marginal product of labor at a14 point

in time and the subsistence (or institutional) wage, and at ributes to landlord rent the remaining

residual in total output value" (Cline 1975, p. 360). Since land is not unlimited and not

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equally fertile, in the long-run, according to this theory, the share of profits tends to fall while

rent and wage shares tend to rise (more labor is required), although the real wage is kept at

subsistence level. According to Ricardo, this distribution in favour of the landlords prevents

economic growth acceleration and the economy would tend to stagnate, since he regarded

landlords as spendthrifts and thought that economic growth was financed by the savings of the

capitalists. Moreover, he proposed reducing restrictions on imports and introducing

technological innovations without increasing the proportion of labor and keeping wages at

subsistence level in order to achieve rapid economic growth (Gil is, Perkins, Roemer,

Snodgrass, 1987). This proposition reveals his view that economic growth requires not

only redistribution from landlords to the capitalists, but also stressing inequality between

profits and wages. The Ricardian theory focuses on the conflict between rent and profits. Later

on, this focus shifts to the conflict between profits and wages especially with Marx's view.

Since Karl Marx regarded the main class conflict to be between capitalists and workers, he

only considered two sources of income: profits and wages. Although Marx recognized that

rent, benefits and interests were also sources of income, he assumed that these types of income

were received only by one class: the capitalists (Ferrán, 1997). Marx uses the Ricardian

"labor theory of value" to diagnose exploitation of workers (Cline, 1975). Like Ricardo, he

assumed an unlimited labor supply which al owed the capitalists to hold down the wages at a

subsistence level. But the labor surplus was possible through the existence of a "reserve

army of labor" that capitalists were stimulated to maintain through labor displacing

innovations in order to achieve the profit rate level that capital accumulation requires.

Marx refused to accept the Malthusian theory that demographic forces created the

labor surplus (Gil is, Perkins, Roemer, Snodgrass, 1987). In the Marxian theory, the structure

of the distribution of incomes is strongly linked to the structure of the production relations.

Therefore, a change in the structure of distribution can only happen as a result of a change in

the production conditions. According to Marx, capitalism constantly reproduces its production

relations and therefore the laws that rule the corresponding distribution of income. For this

reason, the economic position of the working class can only improve when capitalism itself col

apses. He saw the industrial concentration as the result of the tendency for the profit rate to

fall, leading to cyclical crisis until a final apocalyptic crisis. (Cline, 1975; Bigsten, 1983). "In

the Marxian long-run the system col apses due to declining wages (whether declining

absolutely or only relatively to capitalist income is unclear) and intolerable worker poverty in

the face of capitalistic accumulation" (Cline, 1975, p. 361). Opposite to the Marxian theory in

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many aspects, the neo-classical or marginal productivity theory postulates that all factors of

production are in scarce supply and all of them creating value vi. This refutes the Marxian

view that only labour creates value. The product value is explained by the marginal

utility which also explains the remuneration of factors. They generalized the marginal

productivity as the basis for payment of all factors, eliminating the attribution of residual

income to any one factor. This view is based on the principle that the producers maximize their

benefits, and this point is only reached when al factor payments equalize their corresponding

marginal productivity. Thus, the distribution of income is regarded as part of the general

pricing process in the economy. In this way, the demand of factors depends on product

demand, this is, and the demand of factors is derived from product demand. The prices of

factors and goods are assumed to be determined by market forces. Also,

factor substitutability is assumed so that the rise in one factor supply decreases its relative

price. Therefore, the neo-classical theory of distribution is based on production functions and

elasticity’s of substitution (Cline, 1975; Bigsten 1983; Ferran, 1997). Explaining the functional

distribution, the neo-classical view helps to explain the size distribution of income. "The

sum of payments to the factors of production possessed by an individual determines his

income" (Bigsten, 1983, p. 5). Thus, the changes in the functional 15 distribution and, as a

consequence, in the size distribution of income over time can be explained by changes in

relative factor supplies, elasticity of substitution between factors, changes in product demand,

and the capital or labor saving bias in technological change (Cline, 1975). While the

neo-classical theory uses the marginal productivity of factors to explain income distribution,

the Keynesian economics, base its view on marginal propensities to save. According to Ferrán

(1997), Nicholas Kaldor establishes this view, stating that the profit share of total income is

determined by macroeconomic forces which assure that capitalist’s expenditures on

consumption produce benefits to finance those expenditures. This is, as quoted

by Kurz (1994), assuming that only capitalists are net savers, a given amount of profits can

only materialize if there is a corresponding amount of net investment and capitalists'

consumption. Kaldor's model assumes that there are only two classes: capitalists and workers.

Each class has a specific propensity to save -workers' lower than that of capitalists. In this

model, the ratio of investment to national income is an exogenous variable which does not

depend on changes in the propensities to save. Then, under full employment condition,

equalizing saving and investment yields the only one possible distribution of total income

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between wages and profits (Cline, 1975; Bigsten, 1983). The profit share in total income

is expressed by the equation P/Y = [1/(sp - sw)][(I/Y) - sw] (1)

Where P are profits, I investment, Y total income, sp and sw are the propensities to save of

capitalists and workers respectively, being sw < sp (See Ferran 1997, pp. 248-249). Assuming

that both propensities to save are given, the profit share is determined by the rate of

investment. The coefficient 1/(sp - sw) measures the changes in the distribution of income due

to a unit change in the investment rate. The smaller the difference between sp and sw the

greater the impact of changes in the investment rate on income distribution. Assuming sw very

small, nearly zero,the equation (1) leads to P = (1/sp)I (2)

This last proposition shows clearly Kaldor's view on capitalists' consumption, stated

above . Therefore, according to Kaldor's model, there is a specific distribution between wages

and profits that makes savings equal to investment. An increase in investment forces an

increase in savings to restore equilibrium. Since capitalists are assumed to have a

higher propensity to save, the equilibrium can only be restored by increasing profits through an

increase in the price level (Knight, 1976). This suggests a positive relationship between

economic growth and inequality in the factorial distribution of income. Cline (1975) points out

a couple of basic flaws in Kaldor's model. The assumption that there are only two

class’s makes its application extremely restricted, since it becomes undetermined considering

three or more classes. Also, an exogenously given investment is not well justified While

Kaldor built up his model focusing on profit share; Michal Kalecki proposed a model based on

the Marxian view focused on the wage share in which he uses monopoly analysis. In his

microeconomic analysis Kalecki uses the Lerner definition of the "degree of monopoly": μ =

(p -m)/p, where p is product price and m is the marginal cost. "If marginal cost is equal to

marginal revenue, μ is equal to the inverse of the elasticity of demand for the product of the

enterprise" (Kalecki, 1951, p. 19). In Kalecki's model the components of variable costs are raw

material and labor costs. Aggregating for a closed economy, Kalecki shows that labour share

varies negatively with the "average" degree of monopoly power in the economy (Cline, 19775;

Bigsten, 1983). So, according to the relationship between the degree of monopoly and the

elasticity of product demand stated above, this means that the lower the product demand

elasticity, the lower the share of wages in value added. Thus, this model suggests that

economic growth relied on a growing monopoly power in the economy would lead to an

increasing gap between wage and profit shares in total income. Kalecki's model faces the

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difficulties of building up a macroeconomic theory of distribution based on

microeconomic elements without paying attention to aggregation problems. For example,

Ferran (1997) argues that at microeconomic level it is plausible to16 assume a given factor

supply at a given price, while at macroeconomic level some limitations may arise by factor

availability.

Theories of Size Income Distribution

The foregoing theories are aimed at explaining the functional distribution of income

rather than the size distribution of income. Therefore, they are of limited value in analyzing the

governmental action. According to Ahluwalia and Chenery (1983), because most of the wage

earners belong to the middle-income groups is the reason why policies affecting the

distribution between wages and profits mainly concern the upper end of the size distribution.

Although, the neo-classical theory makes some contribution in understanding the determinants

of the size distribution of incomes, differences in factor endowments seem not to be enough to

explain the large inequalities in developing countries, particularly in Latin America. It would

be necessary to explain also how these differences in endowments were created. A number of

theories of size income distribution have been developed. According to Sahota (1978) the set

of theories of personal income distribution can be classified into two basic groups. One group

ranges from those theories developed by economists who believe that income inequalities are

largely a consequence of voluntary choice to those in which inheritance and institutions

play the main role. The other, which Sahota (1978) calls the "fatalist" group, is constituted

by three schools: a) theories based on the premise that incomes are distributed among

individuals according to abilities which are genetically determined; b) Theories that postulates

that income inequalities are largely determined by chance, luck and stochastic factors; And

c) the life-cycles theories which give high relevance to the age effect on earning capacities.

The theory presented by Milton Friedman is referred to as the individual choice theory

in which stochastic influences are combined with optimizing behavior on behalf of the

individuals (Bigsten, 1983). According to Friedman, being risk-taker is what explains that a

small group in society can receive a large proportion of total income since, as in the lottery, the

amount of money that many can lose is small in comparison with the large amount that a few

individuals can win (Ferran, 1997). The risk adverse individual will take less risky choices. As

a consequence, a society composed of risk averse individuals will generate less inequality than

195

one composed of risk-taking individuals. This theory suggests that the rich are risk-taking

while the poor are risk averse individuals. However, Ferran (1997) refers to the

work by Stanley Lebergot (1959) who tests Friedman's model using data from USA and finds

that the group who takes the most risky investments is not the richest but the small investors

expecting a windfall. Moreover, in most countries (developed or developing), gambling seems

to be supported by the low income groups who expect through a windfall to improve their

economic position. Cline (1975) and Sahota (1978) highlight the

work by Mincer (1958) among those economists who support the human capital approach.

This approach focuses on the explanation of job earning differentials. "Mincer's human capital

model is based on the idea that occupations requiring longer training periods

pay higher earnings to compensate for the foregone income during training. More precisely, all

individuals are assumed to choose among occupations such that the present discounted value

of earnings is equated among all occupations. .al incomes are in reality equal. Observed

differences are merely statistical illusions stemming from the fact that the high income

individual has been on the job a shorter time than his low income cohort" (Cline 1975, pp.

365-366). There are two general objections to this model. First, it focuses only on job earning

differentials as the main source of income inequality, disregarding the effects of other sources

such as holding assets. Second, it over emphasizes the impact of schooling on earning

differentials, but disregards the effects of sex, race and family background on schooling

achievement which could limit the range of real choices that individuals have.

Another interesting approach within the context of the job earning differentials is the "job

competition" model at rebuttable mainly to Thurow (1972, 1975) (Cline, 1975; Bergsten,

1983). According to this model "wages are paid based on the characteristics of the job in

question and workers are distributed across job opportunities based on their relative17 position

in the labour queue" (Cline 1975, p. 367). Bigsten (1983) argues that the position of a

worker in the queue should be dependent on the potential cost of training the worker which

may be determined using some screening device such as education. The job competition

approach refutes the assumption that the labour market determines the wage level. Wages are

not set by the marginal product of the worker associated with his/her previously acquired

education level, but by the marginal product associated with the skills he/she learns on the job.

As a consequence, people with identical levels of education may be paid different wages. This

theory disregards that how rapid workers can learn skills on the job might depend in some

degree on the level of education previously achieved, which in turn depends on several

196

other factors such as family background. So, according to the job competition view, expanding

education would not tend to equalize income distribution. The effect of education expansion

would be only to increase the admission requirements for obtaining jobs, while expanding job

opportunities would have a more effective equalization impact. Abilities and stochastic forces

have also been used as explanations for inequalities in the distribution of income. Differences

in abilities explains differences in worker's productivity and as a consequence differences in

income, while other theories regard stochastic forces as responsible for the skewed shape of

the personal distribution of incomes. However, these views give little help for explaining the

determinants of income inequality and for policy making aimed at changing the distribution of

income. (For details about these theories, see Sahota, 1978, and Bigsten, 1983,).

The theories previously discussed are concerned mainly with the distribution of

earnings. They neglect an important source of income which is property. Sahota (1978) points

out those property incomes are more unequally distributed than earnings and that inheritance is

the major source of property class perpetuation. Hence, a theory of distribution that neglects

property incomes will tell only part of the story. The personal-income-distribution theory of

inheritance takes account of property incomes. Sahota (1978) and Bigsten, (1983) summaries

the view of inheritance, at rebuttable to Meade (1964, 1976), as consisting of a bundle of

four major endowments: genetic make-up, parental level of education and training, social

contacts, and inherited property itself. The mutual interaction of these endowments affects

incomes, savings and accumulation, so inequality in these endowments explains differences in

income.

This brief survey shows that the ideal theory able to explain simultaneously the

determinants of factor prices, functional shares and the size distribution of income does not

exist. Although the theory of inheritance considers the property incomes, the missing element

from all those theories is an explicit treatment of the distribution among households of the

various forms of assets such as land, privately owned capital, access to public goods, and

human capital. Ahluwalia and Chenery (1983) coincide with Sahata’s (1978) view that the

distribution of assets is more unequal than the distribution of earnings. Also, Deininger and

Squire (1997) refer to six developing countries in which inequality in the distribution of land is

greater than that in the distribution of incomes. Ahluwalia and Chenery (1983) associate the

variations in income at the lower levels with the lack of human skills, physical capital and

access to them. Attansasio and Sekely (1999) document that income inequality in Latin

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America is, to a large extent, a reflection of a very skewed distribution of income generating

assets. Therefore, asset distribution cannot be disregarded when assessing the effects of

economic growth on income inequality.

A-2 Properties of Inequality Metrics

In the economic literature on inequality four properties are generally postulated that

any measure of inequality should satisfy.

Anonymity

An inequality metric is a statement about how income is distributed, not about who the

particular people in the economy are or what kind of income they deserve.

Scale Independence

This property says that richer economies should not be automatically considered more

unequal by construction. In other words, if every person’s income in an economy is doubled

(or multiplied by any positive constant) then the overall metric of inequality should not

change, off-course the same thing applies to poorer economies. The inequality income metric

should be independent of the aggregate level of income.

Population Independence

Similarly, the income inequality metric should not depend on whether an economy has

a large or small population. An economy with only a few people should not be automatically

judged by the metric as being more equal than a large economy with lots of people. This

means that the metric should be independent of the level of population.

Transfer Principle

The Pigou-Dalton, or transfer principle, is the assumption that makes an inequality

metric actually a measure of inequality. In its weak form it says that if some income is

transferred from a rich person to a poor person, while still preserving the order of income

ranks, then the measured inequality should not increase. In its strong form, the measured level

of inequality should decrease.

A-3 Common Income Inequality Metrics

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Gini Index

The range of the Gini index is between 0 and 1 (0% and 100 %) where 0 indicates

perfect equality and 1 (100%) indicates maximum inequality.

The Gini index is the most frequently used inequality index. The reason for its popularity is

that it is easy to understand how to compute the Gini index as a ration of two areas in Lorenz

curve diagrams. As a disadvantage, the Gini index only maps a number to the properties of a

diagram, but the diagram itself is not based on any model of a distribution process. The

“meaning” of the Gini index only can be understood empirically. Additionally the Gini does

not capture where in the distribution the inequality occurs. As a result two very different

distributions of income can have the same Gini index.

20:20 Ratio

The 20:20 or 20/20 ratio compares how much richer the top 20% of populations are to

the bottom 20% of a given population, this can be more revealing of the actual impact of

inequality in a population, as it reduces the effect on the statistics of outliers at the top and

bottom and prevents the middle 60% statistically obscuring inequality that is otherwise

obvious in the field. The measure is used for the United Nations Development Programmer

Human Development Indicators. The 20 : 20 ratio for example shows that Japan and Sweden

have a low equality gap, where the richest 20% only earn 4 times the poorest 20% , whereas in

the UK the ratio is 7 times and in the US 8 times. Some believe the 20:20 ratio is a more useful

measure as it correlates well with measure of human development and social stability

including the index of child well-being, index of health and social problems, population in

prisons, physical health, mental health and many others.

Palma Ratio

The Palma ratio is defined as the ratio of the richest 10% of the population’s share of

gross national, income divided by the poorest 40 %’s share. It is based on the work of Chilean

economist Gabriel Palma who found that middle class incomes almost always represent about

half of gross national income while the other half is split between the richest 10% and poorest

40% but the share of those two groups varies considerably across.

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The Plama ratio addresses the Gini index’s over-sensitivity to changes in the middle of

the distribution and insensitivity to changes at the top and bottom, and therefore more

accurately reflects income inequality’s economic impacts on society as a whole. Palma has

suggested that distributional politics pertains mainly to the struggle between the rich and poor,

and who the middle classes side with.

Hoover Index

The Hoover index is a simplest of all inequality measures to calculate: it is the

proportion of all income which would have to be redistributed to achieve a state of perfect

equality. In a perfectly equal world, no resources would need to be redistributed to achieve

equal distribution: a Hoover index of 0. In a world in which all income was received by just

one family, almost 100% of that income would need to be redistributed (i.e., taken a given to

other families) in order to achieve equality. The Hoover index then ranges between 0 and 1

(0& and 100%) where 0 indicate perfect equality and 1 (100%) indicates maximum inequality.

Thiel Index

A Thiel index of 0 indicates perfect equality. A Thiel index of 1 indicates that the

distributional entropy of the system under investigation is almost similar to a system with an

82:18 distribution. This is slightly more unequal than the inequality in a system to which the

“80:20 Pareto principle” applies. The Thiel index can be transformed into an Atkinson index,

which has a range between 0 and 1 (0% and 100%), where 0 indicates perfect equality and 1

(100%) indicates maximum inequality.

A-4 Households Integrated Economic Survey (HIES) DATA

Since 1963, HIES has been conducted with some breaks, In 1990 HIES questionnaire

was revised to reflect the integration of HIES with the Pakistan Integrated Household Survey

(PIHS). After this HIES was conducted as an integrated Survey with PIHS in 1998-99 and

2001-02. Subsequently the survey was renamed in 2004 as Pakistan Social and Living

Standards Measurement (PSLM) Survey and the same module of HIES remain in contact. In

PSLM, (District level) Survey and PSLM/HIES (National/ Provincial level) Survey are

conducted on alternative years. Three rounds of HIES were conducted during 2004-05.2005-

06 and 2007-08. Last round of HIES was conducted in 2007-08 and after the revision of PC-1

which was extended to 2015, The next round was planned to be conducted in year 2009-10,

200

but due to technical as well as administrative reasons the survey could not to be conducted.

During the year 2010-11 the PSLM District level survey was scheduled but considering the

requirement of Government of Pakistan and urgency of HIES data it was decided in

consultation with the Planning and Development Division to carry out the HIES survey along

with the PSLM District level Survey during the financial year 2010-11.

201

APPENDIX-B Unit Root Testing

B1. Private Consumption Series

Table B-1.1

Unit Root Testing at Level

Null Hypothesis: LNCONs has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -2.766545 0.2181Test critical values: 1% level -4.234972

5% level -3.54032810% level -3.202445

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test EquationDependent Variable: D(LNCONs)Method: Least SquaresDate: 04/01/14 Time: 11:37Sample (adjusted): 1977 2012Included observations: 36 after adjustments


CONs(-1) -0.328773 0.118839 -2.766545 0.0092C 4.648955 1.659433 2.801532 0.0084

@TREND(1976) 0.015377 0.005740 2.678830 0.0114

R-squared 0.196660 Mean dependent var 0.050649Adjusted R-squared 0.147973 S.D. dependent var 0.042328S.E. of regression 0.039071 Akaike info criterion -3.567195Sum squared residual 0.050377 Schwarz criterion -3.435235Log likelihood 67.20951 Hannan-Quinn critter. -3.521138F-statistic 4.039249 Durbin-Watson stat 1.660437Prob(F-statistic) 0.026967


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Table B-1.2

Unit Root Testing at 1st difference

Null Hypothesis: D(LNCONs) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.54428410% level -3.204699


Augmented Dickey-Fuller Test EquationDependent Variable: D(CONs,2)

Method: Least SquaresDate: 04/01/14 Time: 11:39Sample (adjusted): 1978 2012Included observations: 35 after adjustments


D(CONs(-1)) -0.923514 0.176091 -5.244529 0.0000C 0.055485 0.018801 2.951136 0.0059

@TREND(1976) -0.000450 0.000736 -0.611520 0.5452

R-squared 0.462457 Mean dependent var -0.000278Adjusted R-squared 0.428860 S.D. dependent var 0.058002S.E. of regression 0.043834 Akaike info criterion -3.334988Sum squared residual 0.061486 Schwarz criterion -3.201673Log likelihood 61.36229 Hannan-Quinn critter. -3.288968F-statistic 13.76504 Durbin-Watson stat 1.867607Prob(F-statistic) 0.000049


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B2. Import Series

Table B-2.2

Unit Root Testing at level

Null Hypothesis: LNIMP has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.54032810% level -3.202445


Augmented Dickey-Fuller Test EquationDependent Variable: D(LNIMP)Method: Least SquaresDate: 04/01/14 Time: 11:43Sample (adjusted): 1977 2012Included observations: 36 after adjustments


LNIMP(-1) -0.619862 0.170569 -3.634082 0.0009C 7.945054 2.175622 3.651854 0.0009

@TREND(1976) 0.025387 0.007595 3.342692 0.0021

R-squared 0.287073 Mean dependent var 0.062277Adjusted R-squared 0.243865 S.D. dependent var 0.255580S.E. of regression 0.222243 Akaike info criterion -0.090440Sum squared residual 1.629928 Schwarz criterion 0.041520Log likelihood 4.627913 Hannan-Quinn critter. -0.044382F-statistic 6.644016 Durbin-Watson stat 2.103245Prob s(F-statistic) 0.003761


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Table B-2.2 Unit Root Testing at 1st Difference Null Hypothesis: D(LNIMP) has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -9.407273 0.0000 Test critical values: 1% level -4.243644

5% level -3.544284 10% level -3.204699


Augmented Dickey-Fuller Test Equation Dependent Variable: D(LNIMP,2) Method: Least Squares Date: 04/01/14 Time: 11:27 Sample (adjusted): 1978 2012 Included observations: 35 after adjustments


D(LNIMP(-1)) -1.480859 0.157416 -9.407273 0.0000 C 0.076597 0.088530 0.865217 0.3934

@TREND(1975) 0.000711 0.003930 0.180930 0.8576

R-squared 0.734544 Mean dependent var 0.008864 Adjusted R-squared 0.717953 S.D. dependent var 0.442197 S.E. of regression 0.234842 Akaike info criterion 0.022011 Sum squared residual 1.764828 Schwarz criterion 0.155327 Log likelihood 2.614806 Hannan-Quinn critter. 0.068032 F-statistic 44.27362 Durbin-Watson stat 2.186781 Prob(F-statistic) 0.000000


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B3. Private Investment Series Unit Root Testing at level

Null Hypothesis: LNINV has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.540328 10% level -3.202445


Augmented Dickey-Fuller Test Equation Dependent Variable: D(LNINV) Method: Least Squares Date: 04/01/14 Time: 11:45 Sample (adjusted): 1977 2012 Included observations: 36 after adjustments


LNINV(-1) -0.136542 0.076471 -1.785534 0.0834 C 1.812554 0.974662 1.859674 0.0719

@TREND(1976) 0.003218 0.003018 1.066141 0.2941

R-squared 0.151817 Mean dependent var 0.039370 Adjusted R-squared 0.100412 S.D. dependent var 0.071926 S.E. of regression 0.068219 Akaike info criterion -2.452520 Sum squared residual 0.153578 Schwarz criterion -2.320560 Log likelihood 47.14536 Hannan-Quinn critter. -2.406462 F-statistic 2.953358 Durbin-Watson stat 1.893015 Prob(F-statistic) 0.066081


206

Table B-3.2

Unit Root Testing at 1st Difference

Null Hypothesis: D(LNINV) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.54428410% level -3.204699


Augmented Dickey-Fuller Test EquationDependent Variable: D(LNINV,2)Method: Least SquaresDate: 04/01/14 Time: 11:46Sample (adjusted): 1978 2012Included observations: 35 after adjustments


D(LNINV(-1)) -1.002886 0.175396 -5.717836 0.0000C 0.080369 0.029128 2.759123 0.0095

@TREND(1976) -0.002110 0.001249 -1.689203 0.1009

R-squared 0.505443 Mean dependent var 0.000887Adjusted R-squared 0.474533 S.D. dependent var 0.098897S.E. of regression 0.071690 Akaike info criterion -2.351124Sum squared residual 0.164461 Schwarz criterion -2.217809Log likelihood 44.14467 Hannan-Quinn critter. -2.305104F-statistic 16.35218 Durbin-Watson stat 1.979193Prob(F-statistic) 0.000013


207

B4. Foreign Remittances Unit Root Testing at level

Null Hypothesis: LNFR has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.540328 10% level -3.202445


Augmented Dickey-Fuller Test Equation Dependent Variable: D(LNFR) Method: Least Squares Date: 04/01/14 Time: 11:49 Sample (adjusted): 1977 2012 Included observations: 36 after adjustments


LNFR(-1) -0.131130 0.056249 -2.331246 0.0260 C 1.558345 0.576635 2.702480 0.0108

@TREND(1976) 0.002427 0.005307 0.457416 0.6504

R-squared 0.190519 Mean dependent var 0.117761 Adjusted R-squared 0.141460 S.D. dependent var 0.262462 S.E. of regression 0.243191 Akaike info criterion 0.089713 Sum squared residual 1.951675 Schwarz criterion 0.221673 Log likelihood 1.385171 Hannan-Quinn critter. 0.135770 F-statistic 3.883430 Durbin-Watson stat 1.191412 Prob(F-statistic) 0.030578


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Table B-4.2 Unit Root Testing at 1st Difference

Null Hypothesis: D(LNFR) has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -3.544284 10% level -3.204699


Augmented Dickey-Fuller Test Equation Dependent Variable: D(LNFR,2) Method: Least Squares Date: 04/01/14 Time: 11:50 Sample (adjusted): 1978 2012 Included observations: 35 after adjustments


D(LNFR (-1)) -0.585278 0.160696 -3.642137 0.0009 C 0.107213 0.095221 1.125940 0.2686

@TREND(1976) -0.002383 0.004174 -0.570850 0.5721

R-squared 0.295319 Mean dependent var -0.006271 Adjusted R-squared 0.251277 S.D. dependent var 0.278502 S.E. of regression 0.240984 Akaike info criterion 0.073645 Sum squared residual 1.858348 Schwarz criterion 0.206961 Log likelihood 1.711208 Hannan-Quinn critter. 0.119666 F-statistic 6.705325 Durbin-Watson stat 1.956576 Prob(F-statistic) 0.003697


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B5. Gross Domestic Product (GNP) B-5.1 Unit Root testing at level

Null Hypothesis: GNP has a unit root(at level) Exogenous: Constant Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -2.936942 10% level -2.606857


Augmented Dickey-Fuller Test Equation Dependent Variable: D(GNP) Method: Least Squares Date: 09/30/15 Time: 13:32 Sample (adjusted): 1973 2012 Included observations: 40 after adjustments


GNP(-1) -0.016876 0.006469 -2.608663 0.0129 C 0.305783 0.098691 3.098400 0.0037


210

B -5.2 Unit Root Testing at 1st Difference Null Hypothesis: D(GNP) has a unit root (1st difference) Exogenous: Constant Lag Length: 0 (Automatic based on SIC, MAXLAG=9)

t-Statistic Prob.*


5% level -2.938987 10% level -2.607932


Augmented Dickey-Fuller Test Equation Dependent Variable: D(GNP,2) Method: Least Squares Date: 09/30/15 Time: 13:34 Sample (adjusted): 1974 2012 Included observations: 39 after adjustments


D(GNP(-1)) -0.810150 0.159923 -5.065880 0.0000 C 0.038700 0.008692 4.452482 0.0001

R-squared 0.409541 Mean dependent var -0.000769 Adjusted R-squared 0.393583 S.D. dependent var 0.030898 S.E. of regression 0.024061 Akaike info criterion -4.566549 Sum squared residual 0.021420 Schwarz criterion -4.481239 Log likelihood 91.04771 Hannan-Quinn critter. -4.535941 F-statistic 25.66314 Durbin-Watson stat 2.056159 Prob(F-statistic) 0.000012

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APPENDIX-C Johansen Co- integration Results

Table C-1.1 VAR Lag Order Selection Criteria

VAR Lag Order Selection Criteria Endogenous variables: GNP CONP INV IMP REM Exogenous variables: C Date: 09/29/15 Time: 15:29 Sample: 1972 2012 Included observations: 38

Lag LogL LR FPE AIC SC HQ

0 54.75136 NA 5.02e-08 -2.618493 -2.403021 -2.541829 1 255.1902 337.5812 4.97e-12 -11.85211 -10.55928* -11.39214* 2 277.8933 32.26227 6.02e-12 -11.73122 -9.361034 -10.88793 3 312.8682 40.49732* 4.33e-12* -12.25622* -8.808672 -11.02961

* indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion Source: Calculations are based on computer software Eviews-6

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Table C-1.2Trace Test Date: 09/30/15 Time: 10:03 Sample (adjusted): 1974 2012 Included observations: 39 after adjustments Trend assumption: Linear deterministic trend (restricted) Series: GNP REM INV IMP CONP Lags interval (in first differences): 1 to 1

Unrestricted Co-integration Rank Test (Trace)

Hypothesized Trace 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.636482 100.6099 88.80380 0.0054 At most 1 0.470613 61.14478 63.87610 0.0831 At most 2 0.420212 36.33938 42.91525 0.1942 At most 3 0.202860 15.08078 25.87211 0.5678 At most 4 0.147824 6.238509 12.51798 0.4306

Trace test indicates 1 integrating eon(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Table C-1.3 Maximum Eigen value Test

Unrestricted Integration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05 No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.636482 39.46515 38.33101 0.0369 At most 1 0.470613 24.80539 32.11832 0.2978 At most 2 0.420212 21.25861 25.82321 0.1788 At most 3 0.202860 8.842267 19.38704 0.7406 At most 4 0.147824 6.238509 12.51798 0.4306

Max-eigenvalue test indicates 1 integrating eon(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Integrating Coefficients (normalized by b'*S11*b=I):

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Table C-1.4 Long run coefficients by 2SLS

Dependent Variable: GNP Method: Two-Stage Least Squares Date: 09/14/15 Time: 15:13 Sample: 1972 2012 Included observations: 41 Instrument list: INV WR IMP GNP


C -110609.5 86362.94 -1.280752 0.2085 FR 1.073790 0.356145 3.015032 0.0047

CONS 1.101631 0.053260 20.68411 0.0000 INV 1.345236 0.279825 4.807420 0.0000 IMP -0.175931 0.131305 -1.339869 0.1887

R-squared 0.996561 Mean dependent var 4938669. Adjusted R-squared 0.996179 S.D. dependent var 2568166. S.E. of regression 158743.2 Sum squared residual 9.07E+11 F-statistic 2617.315 Durbin-Watson stat 1.273099 Prob(F-statistic) 0.000000 Second-Stage SSR 2.37E-15

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APPENDIX-D

Table D-1

Error Correction

ECM RESULTS Dependent Variable: D(GNP) Method: Least Squares Date: 10/14/15 Time: 14:20 Sample (adjusted): 1973 2011 Included observations: 39 after adjustments


D(IMP) -0.006980 0.012742 -0.547769 0.5875 D(INV) 0.121995 0.043917 2.777828 0.0090

D(REM) 0.042479 0.012396 3.426909 0.0017 D(CONP) 0.255756 0.076546 3.341221 0.0021

D(EC) -0.215003 0.101182 -2.124910 0.0412 C 0.027223 0.005500 4.949565 0.0000



215

APPENDIX-E Diagnostic Test

Table E-1.1

VEC Residual Serial Correlation LM Tests

Null Hypothesis: no serial correlation at lag order h

Date: 04/02/14 Time: 14:49

Sample: 1975 2012

Included observations: 35

Lags LM-Stat Prob

1 23.49563 0.1011

2 20.31988 0.2062

3 14.50674 0.5610

4 12.09002 0.7378

5 21.91179 0.1461

6 16.11009 0.4453

7 14.52736 0.5595

8 12.48897 0.7097

9 10.44463 0.8424

10 17.19258 0.3732

11 15.65080 0.4776

12 23.16200 0.1095

Probs from chi-square with 16 df.

Ho = accepted (No Autocorrelation), If P value 0.05 accept Ho


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Figure E-1.1

8

9

10

11

12

13

14

15

16

1975 1980 1985 1990 1995 2000 2005 2010

CONP IMP INV REM

Normality Test Figure E-1.2

0

1

2

3

4

5

6

7

-0.05 0.00 0.05

Series: ResidualsSample 1982 2012Observations 31

Mean -8.95e-18Median 0.004043Maximum 0.075214Minimum -0.073780Std. Dev. 0.031899Skewness -0.026068Kurtosis 3.001898

Jarque-Bera 0.003516Probability 0.998244

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Stability Test Figure E-1.3

-15

-10

-5

0

5

10

15

88 90 92 94 96 98 00 02 04 06 08 10 12

CUSUM 5% Significance

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