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Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 101
ASSESSING THE RELATIONSHIP BETWEEN INVESTMENT CLIMATE AND
DOMESTIC SAVINGS IN INDIA
Dr. Manjari Agarwal
Assistant Professor
School of Management Studies and Commerce
Uttarakhand Open University, Haldwani, Uttarakhand
ABSTRACT
Growth in an economy depends upon the savings and investments along with capital-output ratio which
determines level of income. Savings reflects long term economic viability of a country and investment climate
reflects the health of a nation's business environment in totality. Further, there are broad and interrelated factors
that affect the buoyancy of savings and investments in the country. These can be macro factors at the economy
level concerning economy and political stability and the level of policies adopted towards investments. Hence, the
present study assesses the relationship between savings and investment climate. It tries to assess that how the
savings of the Country is important for shaping the investment climate in the country. It tries to explore the impact
of Gross Domestic Savings on the investment climate of the country.
The study used Correlation and Johansen Co-integration Method for identifying relationship and on the basis of
correlation and co-integration analysis, it was found that savings in the country is an important factor that have
significant impact on the investment climate. This means that Gross Domestic Savings should be accelerated in the
economy for developing healthy investment climate in the country.
Key Words: Investment Climate, Investments, Savings, Granger Causality
1. Introduction
Investment is the sacrifice of certain present value for the uncertain future profits. It includes deciding on various
aspects like type, amount timing, grade etc. of investments. Broadly speaking an investment decision is a trade-off
between risk and return. Accordingly, investment means the engagements of funds with an objective of realizing
additional income or growth in investment value at a future date. Investment has been an activity attributable to the
rich and business class in the past, but today we find that investment is a word commonly used in households and
is quite familiar with people at each cadre. It is an activity by which resources are actually committed to
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 102
production. Investments generally promote larger consumption in future as they lead to more income and larger
capital appreciation. Moreover, Government policies, technology, state of industry and stock of capital also
influence expected future earnings. Further, the amount of investments depends upon surplus funds generated by
individuals and organizations, which in turn get, invested in various investment options. Therefore, investment is
lifeblood of an economy, which flows in all sectors and without which a country is difficult to prosper.
However, on the other hand, savings are the excess of income over expenditure for any economic unit. Saving is
abstaining from present consumption for a future use. Saving refers to the activity by which claims to resources,
which might be put to current consumption, are set aside and are made available for other purpose in future. The
total volume of savings in an economy therefore depends mainly upon the size of its material income and its
average propensity to consume, which in turn, is broadly determined by the level and distribution of the income of
the people. Further, savings in an economy is composed of public and private savings. Public saving comprises of
the saving of the Government through budgetary channels and retained earnings of public enterprises. They are
greatly influenced by economic and fiscal policies, tax rates and investment policies. Private saving includes
household sector savings and business savings. Business saving is also in the form of retained savings, surplus,
provisions etc. They are also called as corporate savings and are greatly influenced by the state of economy and
industry, the fiscal policies etc.
Additionally, finance is a link between savings and investment by which saving are consolidated and put into the
hands of those who are able and willing to invest. It is an activity by which claims are assembled from the savings
either from domestic avenues or from abroad and then placed in the hands of the investors. Therefore, financial
system is significant for capital formation and this capital formation is yet again necessary for the development of
an economy. Thus, the function of financial system is to establish a bridge between savers and investors and
thereby help in removing gaps in the investment process. Hence, the financial system has an important role to play
in the mobilization of savings and their distribution among the various productive activities.
Accordingly, growth in an economy depends upon the savings and investments along with capital-output ratio
which determines level of income. Further, by investing in physical assets capital formation rises, which in turn
returns into increase in output. Thus, the total capital -output ratio for the economy, speaking in macro terms and
the total volume of investments in the economy would determine the growth of output and income.
Particularly in India, the net savers are the household sector whose savings are higher than their investment,
leading to their positive contribution of saving in the economy. On the other hand, business and Government
sectors are negative savers as investments are higher than the savings leading to a net negative contribution. The
foreign sector also contributes to net savings due to larger inflow of funds through commercial borrowings and
other forms of capital inflows. The flow of funds in the form of saving and investment comes from the financial
system and promote production of goods and service in the real sector, leading to increase in output and incomes
of the people. Thus, overall, the importance of financial system is to increase savings and investment in the
economy and to increase these resources flowing into financial assets, which are more productive than physical
assets.
Accordingly, the flow of funds promotes production of goods and service in the real sector, leading to a rise in
output and income of the people. But sometimes it is also said that increase in capital without suitable social,
economic, political conditions cannot cause growth. On the other hand favorable development in the conditions
can achieve much greater growth with minimum of capital. Thus, there are broad and interrelated factors that
affect the buoyancy of savings and investments in the country. These can be macro factors at the economy level
concerning economy and political stability and the level of policies adopted towards investments. Further, these
can be macro economic factors such as fiscal, monetary, exchange rate policies and political stability which affect
growth in investments. There can be other factors like governance and regulatory framework both in the financial
and legal systems and it may also include factors like infrastructural facilities such as transportation, electricity and
communication that are necessary for productive investment in the country. These factors in totality may lead into
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 103
determining investment climate of a country. Thus, the investment climate presents the reasoned expectations
about the competitiveness, growth, prosperity and profitability. As per the definition given by the World Bank in
the World Development Report, 2005 as “The investment climate reflects the many location-specific factors that
shape the opportunities and incentives for firms to invest productively, create jobs, and expand.” Phillips (2006)
divided investment climate into governance and infrastructure components while stating that healthy investment
climate includes economic and political stability, rule of law, adequate infrastructure, tax and regulations
conducive to doing business, labor policies, and access to finance. Stern (2002) notes that it is the “The policy,
institutional, and behavioral environment, both present and expected, that influences the returns and risks
associated with investment. The notion of investment climate focuses on questions of institutions, governance,
policies, stability, and infrastructure that affect not just the level of capital investment but also the productivity of
existing investments indeed, of all factors of production and the willingness to make productive investments for
the longer term.” This conveys that besides the various macroeconomic variables that may affects investment
climate in the county, even savings also plays a predominant role in explaining the investment climate in the
Country.
Further, before 1991 i.e. before liberalization, investment in the prime areas of the economy was under the hands
of public sector, private investments were discouraged. The Government owned and controlled almost all banking
system and prevented foreign and domestic institutions from entering it. The insurance and pension fund industry
was Government owned and had to invest most of its assets in low yielding Government securities. The
Government set nearly all interest rates and financial institutions were directed on how they should allocate some
of their investments. Capital Markets were constrained by few companies and corporate houses. Private companies
in capital markets were small and needed Government approval (including Government determination of price and
terms) on new capital issues. But after the reforms of 1991, there has been a substantial and steady liberalisation of
the economy, which impedes the importance of market forces. Permission is granted for the foreign investment to
enter into debt and equity market. Mutual funds territory is opened for private sector. Government control of the
prices of initial public offering has ended. Finally, better regulation, disclosures and investor protection have
greatly changed the savings and investment patterns of the individuals in the country.
Thus on the basis of the above background the present study assesses the relationship between savings and
investment climate. It tries to assess that how the savings of the Country is important for shaping the investment
climate in the country. It tries to explore the impact of Gross Domestic Savings on the investment climate of the
country. For the purpose of the study, operationally Investment climate is explained as Trade, investments,
industrial and manufacturing conditions in an economy that influences national and international individuals and
institutions for investing money and acquiring stake.
Savings reflects long term economic viability of a country and investment climate reflects the health of a nation's
business environment in totality.
2. Review of Literature The relationship between savings and the investment has been incessant study not only in developing countries but
also in developed countries across the globe. Emmanuel Anorou in the year 2001 conducted a study to explore
relationship between savings and investments in context to ASEAN Countries. The study found long run
equilibrium association between the savings and investments. The study was conducted using Johansen Juselius
Co-integration method, Granger Causality Test and VECM. The study explored that investment causes saving in
the cases of Indonesia and Singapore. For the Philippines, causality runs from saving to investment. However, in
case of Malaysia and Thailand, the study resulted into bi-directional causality between saving and investment.
Jangili Ramesh in the year 2011 investigated the relationship between savings, investments and economic growth
for India. The study found unidirectional causality between savings and investments. It was that higher savings and
investments contribute into higher economic growth. It was also found that saving and investment led growth has
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 104
been contributed by the household sector. The study also found that savings and investments of private sector
endogenously contributed in the growth of economic growth. Further the study also found that economic growth is
possible due to investments in public sector but the economic growth does not contribute in the increase of public
sector investments.
On an different dimension, Bahmani-Oskooee and Chakrabarti (2005) found that there was a significant and
positive relationship between the ratio of Gross Domestic Investments to GDP and the ratio of Gross Domestic
Savings to GDP. They found that a systematic effect of „„country-size‟‟ and „„openness‟‟ on the saving–investment
relationship was robust for Higher- Income Countries. The study was conducted on 126 economies over the period
of 1960 to 2000. The study was concentrated on the exploring the saving-investments relationship for the Higher-
Income, Low Income and Closed economies.
Narayan Paresh Kumar (2005) found that savings and investments are co-integrated for Japan. Further he explored
that bidirectional causality exists between savings and investments. The direction of causation between saving and
investment was explored using the bootstrap approach. Though moderate rate of correlation between the variables.
Further, the study found that shocks to saving and investment have a permanent effect in case of Japan.
Ramesh Mohan (2006) investigated the relationship between the domestic savings and economic growth for
various economies. The study seeks to determine whether the direction of causality in these economies is different
based on their income class: namely low−income, low−middle income, upper−middle income, and high−income
countries. Granger causality tests conducted by the researcher revealed that economic growth rate Granger causes
growth rate of savings in 13 countries.
Komain Jiranyakul and Tantatape Brahmasrene (2008) tested the relationship between savings and investments in
Indonesia, Philippines and Thailand. The study also applied Bound Testing Procedure for co-integration, the
results does not found positive correlation between savings and investments in the Indonesia, Philippines and
Thailand.
Kaya Huseyin (2010) found the relationship between domestic saving –investment relationship in Turkey. The
researcher applied ARDL Bound testing Procedure and Bai and Perron Procedure for founding structural breaks.
The study found strong long-run relationship between total investments and savings. However, the study didn‟t
found any long run relationship between private savings and investments. The study was conducted over the
period to 1984Q1-2007Q3.
Francesca and Fachin (2011) investigated long-run savings-investments relationship in OECD economies over the
period 1970 to 2007. The study concluded that the there is long run savings investments in 18 OECD economies
over the period 1970-2007. The study was undertaken by using new bootstrap test for panel co integration in terms
of short-run and long-run dependence across units.
Nwogwugwu, & Odulukwe (2012) explored the factors that affects the investments in Nigeria. The study used
Johansen and Juselius Method to find co-integration among the variables. They found that long run relationship
exists among the variables. The study found that market size and incremental capital ratios are key drivers of
investments in case of Nigeria. The paper suggested that Nigeria have to improve it Investment Climate and
infrastructure to attract investments in the Country.
Christopher K.U (2013) examined that how Nigerian investment climate can be improved for fostering economic
growth in the Country. The study explored that decline in investment rates is one of the factor for the reduced
economic performance. Accordingly, the study recommended that Nigerian economy should foster investments by
providing favorable fiscal regime and by providing stable macroeconomic framework.
Ogbokor and Musilika (2014) found that there is a unidirectional causality between savings and investments in
Namibia . The study found one way causality between the variables and it was inferred that Savings causes into
Investments in Namibia but not vice versa. The study suggested that there is no co-integration between savings and
investments in the Country. Thus, no long-run equilibrium relationship was derived between Savings and
Investments.
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 105
On exploring in the dimension of FDI, Dollar et. al (2005) analysed the importance of investment climate on
exports and FDI for Latin American and Asian Countries using firm level data. The study concluded that better
investment climate in general encourages FDI. All explanatory variables were considered for the study including
physical and financial infrastructure without giving specific effect of a particular variable.
Similar results were found by Kinda Tidiane (2010) investigated the constraints posed by investment climate in
restricting FDI in seventy seven developing Countries using firm level data. The study suggested that physical and
financial infrastructure magnifies the possibility of attracting FDI.
Thus, from the review of literature, it was found that many studies have been conducted on exploring the
relationship between savings and investments. Further, studies have also been undertaken for finding the
relationship of investment climate on exports and FDI. However, any study of exploring the specific relationship
between savings and investment climate has not yet been traced in context to India. In light of this, the study tried
to fill this gap in some ways by attempting to investigate the relationship between savings and investment climate
in India using relevant econometric techniques.
3. Objectives of the Study
The objective of the study is to find out the correlation and co integration between relationship between savings
and investment climate in India during the period from 1980 to 2013.
4. Hypotheses of the Study
H1: There is a positive correlation between savings and investment climate in India.
H2: The variables savings and investment climate in India are co-integrated.
5. Research Methodology
The present study is based on secondary data on Gross Domestic Savings and Investment climate (proxies) which
have been taken from the database of the World Bank (World Development Indicators). Annual data has been used
in the study over the period of 1980 to 2013. The stated period witnessed significant economic and financial
reforms and hence this period would be able to comprehend about the relationship between the variables.
5.1 Variables of the Study
5.1.1 Gross Domestic Savings: This variable represents the Gross Domestic Product minus final consumption
expenditure/ total consumption in India in a particular year. The data is depicted as current U.S. dollars. This
variable is considered as a proxy of the savings of a country.
Variables for Investigating Investment Climate
As per the literature reviewed various factors has been taken for explaining the investment climate in the country
like macro stability, investments, access to finance, tax regulations, trade regulations, infrastructure, production
capacity, corruption, political stability and the likes. However, for this study the following variables have been
taken to reflect investment climate in the country.
5.1.2 Investments: Investments refers to the total investments in the country. This ratio between the investments
and GDP portrays economic health [in terms of gross capital formation]. As per World Bank, it is measured by the
total value of the gross fixed capital formation and changes in inventories and acquisitions less disposals of
valuables for a unit or sector. Thus, this variable is taken majorily for assessing Investment Climate in India.
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 106
5.1.3 Trade Openness: This variable Trade is the proxy for Trade Openness. It depicts the sum of exports and
imports of goods and services measured as a share of gross domestic product.
5.1.4 Industrial Climate/Contribution: This is variable for depicting the industrial climate of an economy which
in turns affects Investment Climate in the Country. This is an economic indicator that measures changes in output
for the industrial sector of the economy. The industrial sector includes manufacturing, mining, and utilities. Data is
in constant US$, and not seasonally adjusted. The base year is 2005.
5.1.5 Value Addition by Manufacturing Sector: It is the proxy for manufacturing contribution in the overall
investment climate of the country. Thus, it depicts the total valued added by the Manufacturing units in
intensifying Investment Climate of India. As per the World Bank, Value added is the net output of a sector after
adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for
depreciation of fabricated assets or depletion and degradation of natural resources. The data is depicted as current
U.S. dollars.
5.2 Method used
5.2.1 Correlation
The correlation assess the relationship between two variables and for studying the same various methods and tools
are used. This statistical tool is widely used for inferring the relationship between the variables of the study. Two
variables are termed to be correlated when increment or decrement in one variable result into corresponding
increment or decrement in the other. Thus, it explains that change in one variable leads to subsequent change in the
other variable. It assesses the degree and direction of the relationship between the variables. However, correlation
does not depict co-integration of the variables.
A mathematical formula for measuring the intensity or the magnitude of linear relationship between two variables
series was suggested by Karl Pearson. The method is;
𝑟 = 𝑑𝑥 𝑑𝑦
𝑑𝑥 2𝑑𝑦 2 or
𝑐𝑜𝑣 (𝑥 ,𝑦)
𝜎𝑥𝜎𝑦
5.2.2Co-integration
Variables are said to be co integrated if long run equilibrium relationship is found among them. If the two series of
Integrated of order one, then the partial difference between them might be stable around a fixed mean. This
narrates that the series are drifting together almost at the same rate. Such series are said to be co-integrated and the
resultant vectors (1,-𝛽0,𝛽1,𝛽2) are called as co integrating vectors. Engle and Granger (1987) defined co-integration as the components of the vector 𝑥𝑡 = (𝑥1𝑡 , 𝑥2𝑡 ……… . . 𝑥𝑛𝑡 ) are
said to be co integrated of order d, b, denoted by 𝑥𝑡~𝐶𝑇(𝑑, 𝑏) explained by if, all components of 𝑥𝑡 are integrated
of order d. and there exists co integrating vector 𝛽 = 𝛽1 , 𝛽2, ……… . such that the linear combination 𝛽𝑥𝑡 =
𝛽1𝑥1𝑡 + 𝛽2𝑥2𝑡 …… . +𝛽𝑛𝑥𝑛𝑡 is integrated of order (d-b) where b>0.
Johansen (1995) developed a maximum likelihood estimation procedure based on reduced rank regression method.
It is used for testing co-integration by interpreting the independent linear combinations for a set of time series
variables that has stationary roots. The Johansen test is based on 𝜆𝑡𝑟𝑎𝑐𝑒 and 𝜆𝑚𝑎𝑥 test statistics for assessing the
co integration among the variables The test for the number of characteristic roots that are insignificantly different
from unity. The trace and max statistics are depicted by ;
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
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𝜆𝑡𝑟𝑎𝑐𝑒 (𝑟) = −𝑇 ln(1 − 𝜆𝑖 )
𝜆𝑚𝑎𝑥 𝑟, 𝑟 + 1 = −𝑇𝑙𝑛 ln(1 − 𝜆𝑟+1 )
Where
𝜆𝑖 =The estimated values of the characteristics roots obtained from the estimated 𝜋 matrix
T= the number of usable observations.
The trace statistics tests the null hypothesis that the number of co-integrating vectors are less than or equal to r
against a general alternative. Maximum Eigen value statistics tests a null of r co integrating vectors against the
specific alternative of r+1.
6. Results
On the basis of the tests used in e-views, the following results were discerned;
6.1 Correlation:
The Table 1 depicts the findings of Karl Pearson Coefficient of Correlation. The figures of correlation are
duplicated in the matrix. It was found that strong positive correlation existed between the Gross Domestic Savings
and the factors that represented Investment Climate in the Country. It can be interpreted that there is a sound and
positive correlation between Gross Domestic Savings and Industrial Climate. Similarly, there is a positive
relationship between Savings and Investments. Strong Positive relationship was also found between Savings and
Trade Openness. On the similar grounds strong positive correlation was also found between Savings and Valued
addition by Manufacturing Sector.
Thus it can be inferred that higher domestic savings can lead to spur Investment Climate in the Country.
Table: 1 Correlation between Gross Domestic Savings and Proxies for Investment Climate in India.
LNGDS
LNINDUST
RY LNINVST LNTRADE LNMANU
LNGDS 1.000000 0.996952 0.951106 0.962366 0.994841
LNINDUST
RY 0.996952 1.000000 0.940061 0.966709 0.999424
LNINVST 0.951106 0.940061 1.000000 0.924990 0.939161
LNTRADE 0.962366 0.966709 0.924990 1.000000 0.965359
LNMANU 0.994841 0.999424 0.939161 0.965359 1.000000
6.2 Johansen Co-integration Test
To assess the linear combination of integrated variables, Johansen Co-integration was applied to infer the co-
integration between Domestic Savings and Investment Climate. The variable Domestic Savings and proxies for
investment climate were pretested to assess their order of integration. The Augmented Dickey Fuller Test (ADF)
was used in the present study on all the series individually to assess the order of integration. ADF was used in E
views 7 to infer the stationarity of the variables. Accordingly, it was found that all the variables are integrated of
order 1 [I (1)], i.e. they are stationary at first difference (Table 2). Further, a VAR Lag Order Selection Criteria
was used in to assess the lag length criteria. The Johansen test is quite sensitive to the lag length; therefore the lag
length test was used in e views. It was found that t-statistic for two lags is significant at the specified critical value.
Hence, one lag criteria were found appropriate according to these LR (Likelihood Ratio Criterion), AIC (Akaike
Information Criterion), SIC (Schwarz Information Criterion), FPE (Final Prediction Error), HQ (Hannan-Quinn
Information Criterion) criterion. Therefore, lag length 2 has been selected on the basis of multivariate
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
www.apjor.com Page 108
generalizations of the all the criteria. The undifferenced data was used in Johansen Co-integration Test in EViews
to assess the co-integration among the series. Further, the same lag length as obtained from VAR Lag Order
Selection Criteria in E Views has been taken.
As a guideline if the absolute value of the computed Trace and Maximum Eigen Value exceeds the critical value
then the null hypothesis of no co-integration is rejected and at least one way co integration among the variables is
accepted at 5% level of significance. On the basis of the result of the test as depicted in Table No. 2 it was found
that as per Trace statistics 84.266 is greater than the critical value of 64.819 at 5% significance level, therefore, it
is possible to reject the null hypothesis of no co-integrating vectors and accept the alternative one or more co
integrating equations for the two series. Moreover, The Maximum Eigen Value test results that Maximum Eigen
statistic 38.055 exceeds the 33.87 percent critical value of the 𝜆max 𝑒𝑖𝑔𝑒𝑛 and hence it is possible to reject the
null hypothesis of no co-integrating vectors and accept the alternative one or more co-integrating equations for
Domestic Savings and proxies for Investment Climate series. Thus, the null hypothesis of no co-integration is
strictly rejected at 5% level of significance, implying long run relationship among the variables. Thus, it may be
inferred that there exist long run equilibrium relationship between Gross Domestic savings and Investment Climate
in India.
7. Conclusion
On the basis of the results derived by applying the Correlation and Co-integration test, it was found that strong
correlation was found between Domestic Savings and Investment Climate. This means these two influences each
other in the long run.
Thus, on the basis of correlation and co-integration analysis, it was found that null hypothesis of no correlation and
co-integration between Domestic savings and Investment Climate is strictly rejected and the alternate hypothesis
of significant correlation and co-integration among the Domestic Savings and proxies of investment climate has
been accepted. The results denotes that savings in the country is an important factor that have significant impact on
the investment climate. This means that Gross Domestic Savings should be accelerated in the economy for
developing healthy investment climate in the country. Accordingly, this Gross Domestic Savings may intensify
Investment Climate in long run which will eventually results in attracting foreign savings and thereby maintaining
high growth rate in the economy.
Thus in the nutshell, Domestic Savings and Investment Climate are strongly related to each other in India.
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
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Tables: Results of the Test used
Table: 2 Results from Johansen Co-integration Test
VAR Lag Order Selection Criteria
Endogenous variables: LNGDS LNINDUSTRY LNINVST
LNTRADE LNMANU
Exogenous variables: C
Date: 07/01/15 Time: 08:47
Sample: 1975 2013
Included observations: 32
Lag LogL LR FPE AIC SC HQ
0 162.6416 NA 3.62e-11 -9.852598 -9.623576 -9.776683
1 278.5395 188.3341* 1.26e-13* -15.53372* -14.15959* -15.07823*
2 303.3228 32.52809 1.45e-13 -15.52017 -13.00094 -14.68512
* 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
Date: 07/02/15 Time: 07:38
Sample (adjusted): 1982 2013
Included observations: 32 after adjustments
Trend assumption: Linear deterministic trend
Series: LNGDS LNINDUSTRY LNINVST LNTRADE
LNMANU
Lags interval (in first differences): 1 to 1
Unrestricted Cointegration Rank Test (Trace)
Hypothesized Trace 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.695540 84.26690 69.81889 0.0023
At most 1 0.468501 46.21199 47.85613 0.0708
At most 2 0.407922 25.98625 29.79707 0.1291
At most 3 0.213420 9.214491 15.49471 0.3459
At most 4 0.046763 1.532535 3.841466 0.2157
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
Asia Pacific Journal of Research Vol: I. Issue XXXIII, November 2015
ISSN: 2320-5504, E-ISSN-2347-4793
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* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized Max-Eigen 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.695540 38.05491 33.87687 0.0149
At most 1 0.468501 20.22573 27.58434 0.3257
At most 2 0.407922 16.77176 21.13162 0.1830
At most 3 0.213420 7.681956 14.26460 0.4120
At most 4 0.046763 1.532535 3.841466 0.2157
Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegrating Coefficients (normalized by b'*S11*b=I):
LNGDS
LNINDUSTR
Y LNINVST LNTRADE LNMANU
31.42263 -106.6407 -12.83069 2.112042 78.25086
-14.55113 16.94014 -5.813558 -3.027525 3.120172
19.37197 -15.04070 -10.23365 -2.594479 -3.858295
-6.684580 10.75392 16.73250 -7.224706 -3.088693
-4.730101 26.00906 -4.457240 -3.632573 -16.90053
Unrestricted Adjustment Coefficients (alpha):
D(LNGDS) -0.051952 -0.012062 -0.009564 -0.048917 0.001545
D(LNINDUS
TRY) -0.019645 -0.027326 0.002158 -0.034074 -0.003508
D(LNINVST) -0.018777 0.016109 0.013542 -0.031882 0.003026
D(LNTRADE
) -0.009756 -0.012144 0.022788 0.001010 0.010848
D(LNMANU
) -0.027218 -0.031634 0.006818 -0.031422 -0.005796
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