CHAPTER ONE

1.0. INTRODUCTION:

The dream of every nation is to evolve into that stage in which it could finally be termed

“developed”. The Nigerian economy for one is definitely not an exception. The problem of

development has continually occupied the attention of scholars, activists, politicians,

development workers, as well as, local and international organizations for many years, with

an increased tempo in the last decade. Although there are different perspectives to

development, there is a general consensus that development will lead to good change

manifested in increased capacity of people to have control over material assets, intellectual

resources and ideology; and obtain physical necessities of life-food, clothing & shelter,

employment, equality, participation in government, political and economic independence,

adequate education, gender equality, sustainable development and peace.

Human development plays a fundamental role and remains the most important factor in

economic growth and development in countries of the world. Human Development is a

development paradigm that is of more significance than the rise or fall of national incomes. It

is about creating an environment in which people can develop their full potential and lead

productive and creative lives in accord with their needs and interests. People are the real

wealth of nations. The Human Development Index (HDI) is a composite statistic used to rank

countries by level of “human development” and to separate countries into developed (high

development), developing (middle development), and underdevelopment (low development)

categories. . The Human Development Index (HDI) is a comparative measure of life

expectancy, literacy, education and standards of living for countries worldwide. It is a

standard means of measuring well-being, especially child welfare. It is used to distinguish

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whether the country is a developed, a developing or an under-developed country, and also to

measure the impact of economic policies on quality of life.

In year 2000, a treaty christened the Millennium Development Goals (MDGs) was adopted

by Presidents of 189 Countries of the World at the end of the 55th session of the United

Nations General Assembly. The Millennium Development Goals (MDGs) are the world’s

time-bound and quantified targets for addressing extreme poverty in its many dimensions.

They embody the deep aspirations and commitment of the global community for significant

improvements in the quality of human life (UNDP, 2009).

The closing decade of the 20th century witnessed an increase in the practice of global

development agenda setting. During this period, several international summits and

conferences were held around the world on the need for countries to evolve strategies to

achieve certain benchmarks on various aspects of development. These international

conferences and summits included the children summit held in New York in 1990, the

Education summit held in Jomiten, Thailand, the summit of the earth held in Rio de Janeiro in

1992, the international population conference held in Egypt, the women’s conference held in

Beijing, china in 1995.

These conferences prompted and climaxed with the United Nations Millennium summit held

in September 2000 by 189 member states including Nigeria, in which the Millennium

Development Goals (MDGs) were set. The eight time-bound goals that were set relate to

poverty alleviation, education, gender equality, environmental protection, maternal health

care, child health care and global partnership. The goals and targets that are to be achieved by

the year 2015 were set on the basis of the global situation in the last decade of the 20th

century. In particular, this decade for Nigeria was low, volatile and turbulent.

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The MDGs, set to be achieved by 2015, provide concrete, numerical benchmarks for tackling

extreme poverty in its many dimensions. The MDGs also provide a framework for the entire

international community to work together towards a common end thus making sure that

human development reaches everyone, everywhere. If according to the agreement, these

goals were achieved, poverty globally will be cut by half, tens of millions of lives will be

saved, and billions of people will have the opportunity to benefit from the global economy.

The eight MDGs are broken down into quantifiable targets that are measured by indicators.

The millennium development goals and their target are outlined as follows:

Goal 1. Eradicate extreme poverty and hunger

o Target 1. Halve, between 1990 and 2015, the proportion of people whose

income is less than one dollar a day

o Target 2. Halve, between 1990 and 2015, the proportion of people who suffer

from Hunger

Goal 2. Achieve universal primary education

o Target 3. Ensure that, by 2015, children everywhere, boys and girls alike, will

be able to complete a full course of primary schooling

Goal 3. Promote gender equality and empower women

o Target 4. Eliminate gender disparity in primary and secondary education,

preferably by 2005, and to all levels of education no later than 2015

Goal 4. Reduce child mortality

o Target 5. Reduce by two thirds, between 1990 and 2015, the under-five

mortality rate

Goal 5. Improve maternal health

o Target 6. Reduce by three quarters, between 1990 and 2015, the maternal

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mortality ratio

Goal 6. Combat HIV/AIDS, malaria and other diseases

o Target 7. Have halted by 2015 and begun to reverse the spread of HIV/AIDS

o Target 8. Have halted by 2015 and begun to reverse the incidence of malaria

and other major diseases.

Goal 7. Ensure environmental sustainability

o Target 9. Integrate the principles of sustainable development into country

policies and programmes and reverse the loss of environmental resources

o Target 10. Halve by 2015 the proportion of people without sustainable access

to safe drinking water

o Target 11. By 2020 to have achieved a significant improvement in the lives of

at least 100 million slum dwellers

Goal 8. Develop a global partnership for development

o Target 12. Develop further, an open rule-based, predictable, non-

discriminatory trading and financial system.

o Target 13. Address the special needs of the Least Developed Countries.

o Target 14. Address the special needs of landlocked developing countries and

small island developing states.

o Target 15. Deal comprehensively with the debt problems of developing

countries through national and international measures in order to make debt

sustainable in the long term.

o Target 16. In cooperation with developing countries, develop and implement

strategies for decent and productive work for youth.

o Target 17. In cooperation with pharmaceutical companies, provide access to

affordable essential drugs in developing countries.

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o Target 18. In cooperation with the private sector, make available the benefits

of new technologies, especially information and communication.

However, for the purpose of this research, attention will be focused on the MDGs in relation

to human development.

1.1. BACKGROUND TO STUDY

About 11 Years ago, leaders from every country agreed on a vision for the future, a world

with less poverty, hunger and diseases, greater survival prospects for mothers and their

infants, better educated children, equal opportunities, for women and a healthier environment,

a world in which developed and developing countries worked in partnership for the

betterment of all.

This vision took the form and shape of eight millennium development goals, which are

providing countries around the world with a frame work for development and time bound

targets by which progress can be measured. The goals were based on the rational assumption

that all persons desire basic human rights and living standards.

However, with only about four years to 2015, many countries are still far from achieving the

MDGs. But speaking at the last United Nations Summit, the United Nations Secretary-

General, Ban Ki-Moon stated that although many countries were still very far from achieving

the MDGs he was optimistic that they had set up recoverable frameworks for achieving these

goals. In fact, President Barrack Obama clearly stated that United States would promote

incentives for economic growth over food or financial aid, and encourage countries to come

up with practical policies for achieving the MDGs. Similarly, other countries are strategizing,

building blocs and galvanizing support to achieve the MDGs.

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The pertinent question in the light of the above is: how far has Nigeria gone towards attaining

the MDGs knowing fully well that Nigeria became a signatory to the Millennium Declaration

in a bid to tackle poverty in the land?

Unfortunately, looking at many indicators for measuring progress towards the MDGs,

Nigeria is not anywhere near achieving the MDGs. A recent United Nations report confirms

Nigeria as having the second highest number of maternal deaths in the world after India. One

of the targets of the MDGs is to improve maternal health and reduce maternal deaths by 75%

by the year 2015. Unfortunately the Maternal Mortality Ratio (MMR) in Nigeria is still

scandalously high. Nigeria still occupies an unenviable position in the "league table" of the

countries with those living with HIV/AIDS (PLWHA). The various Human Development

Index (HDI) reports continue to place Nigeria on the last rung of the global development

ladder. Life expectancy in Nigeria has drastically reduced to 45; real income of most families

has woefully reduced; unemployment has gone overboard. Nigeria is topping the list of

countries with malnourished children; Nigeria's literacy rate is still low. Nigeria is ranked as

the 20th hungriest country on the Global Hunger Index (GHI); Nigeria is pitiably named

among the countries with the highest number of illiterates. Human development is the

epicentre of all developments. Human beings are the wealth of a nation. Therefore, if the

citizens of Nigeria lack access to the basic necessities of life in the 21st century; if they are

denied electricity supply or denied access to primary healthcare in the 21st century, if citizens

are still dying of common cholera. If women still die at child birth in the 21st century

essentially due to lack of access to qualitative health care, then it is a very big shame to the

government and an indication that there is still a bulk of work to be done if we must meet our

2015 MDG target.

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1.2. STATEMENT OF THE PROBLEM.

It is expected that with about three years to the end of the target period (2015), Nigeria would

be on course towards attaining the Millennium development goals (MDGS). Unfortunately,

this is not the case as assessments have shown. According to the recently-concluded United

Nations Summit, many countries, Nigeria inclusive are far from achieving the Millennium

Development Goals (MDGs) by the year 2015. Can we really meet these goals? Can we

reduce poverty and hunger by at least 50%? Can we ensure that, by 2015, children

everywhere, boys and girls alike, will be able to complete a full course of primary schooling?

Can we promote gender equality and empower women? Can we reduce child mortality and

improve maternal health? Combat HIV/AIDS, malaria and other diseases? Ensure

environmental sustainability? Can we develop a global partnership and deal comprehensively

with the problem of debts? And most importantly, will the attainment of these goals have a

significant impact on human development in the Nigerian economy? These are the underlying

problems which the study seeks to tackle.

1.3. OBJECTIVES OF THE STUDY.

The objectives of carrying out this research study include the following:

1. To determine the impact of the MDGs on human development.

2. To examine the relationship between the MDGs and human development.

3. To analyse the current status of Nigeria as regards her meeting the Millennium

Development Goals.

4. To seek and recommend various methods by which these goals can be met.

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1.4 RESEARCH QUESTIONS.

1. How far has Nigeria progressed towards the attainment of the Millennium

Development Goals?

2. Are there factors hindering the attainment of these goals? If yes, how can these

factors be eliminated?

3. Would Nigeria be able to meet these goals by 2015? What steps could be taken in

order to accelerate the attainment of these goals?

4. Do the MDGs have any significant impact on human development in the Nigerian

economy?

1.5. HYPOTHESIS OF THE STUDY.

H0: The MDGs have no significant impact on human development in the Nigerian economy.

H1: The MDGs have a significant impact on human development in the Nigerian economy.

1.6. JUSTIFICATION OF THE STUDY.

The greatest constraints to development in Nigeria are deeply entrenched poverty,

unemployment and the accumulation of debt. The purpose of this study therefore, is to

examine the prospects of the attainment of the United Nations millennium development

goals, by 2015 and at the same time, sensitize the country and other relevant organisations on

the need to brace up to the challenge of meeting the Millennium Development Goals as it is

imperative for human development in the economy. Constructive critique braces, while praise

dulls the recipient. No individual and no nation must be denied the opportunity to benefit

from development.

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1.7. SCOPE AND LIMITATIONS OF STUDY.

The study is centred on the Nigeria economy. It considers the situation of the country before

the millennium when the MDGS were set, and also looks at the post millennium years during

which various steps are being taken to attain these goals. That is, the period of study spans

from 2000-2009.

The limitations to the study are:

1. Time constraint.

2. Financial constraint.

3. Non-availability of comprehensive, verifiable and up-to-date data.

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REFERENCES.

Az-Zubair A, (2010), Nigeria millennium development goals report. Government of the Federal republic of Nigeria.

Igbuzor O, (2006), The millennium development goals: Can Nigeria meet the goals in 2015? A paper presented at a symposium on millennium development goals and Nigeria: issues, challenges and prospects. Institute of chartered accountants (ICAN), Abuja.

Mutasa C, (2005): The politics of the MDGs and Nigeria: A critical appraisal of the globalpartnership for development, African forum and network on debt and development.(AFRODAD)

National economic empowerment and development strategy (NEEDS) (2004). Abuja,National planning commission.

Shetty, Salil (2005), Millennium declaration and development goals: Opportunities for human rights in international journal on human rights, year 2, number 2.

The Nigerian journal of development studies (2009) vol. 7. no. 1, institute of development studies, university of Nigeria, Enugu campus Nigeria.

UNDP (2003), Human development report 2003-millenium development goals: A compact among nations to end human poverty. New York, oxford university press.

World bank (2001), World development report 2000/2001: Attacking poverty. N.Y., oxford university press inc.

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CHAPTER TWO.

2.0. LITERATURE REVIEW AND THEORETICAL FRAMEWORK.

The principal objective of Nigeria's economic development has been to achieve stability,

material prosperity, peace and social progress. Nevertheless, a variety of problems have

persisted, slowing the country's growth and attainment of development objectives. These

include inadequate human development, inefficient agricultural systems, weak infrastructure,

lacklustre growth in the manufacturing sector, a poor policy and regulatory environment, and

mismanagement and misuse of resources. While growth has improved significantly in the last

seven years, on average by about 6 per cent, this growth has often not improved everyday

livelihoods. Furthermore, the country is among those with the highest levels of inequality in

the world. This inequality reflects widening gaps in income and gender access to economic

and social opportunities; growing inequality between and within rural and urban populations;

and widening gaps between economies in different parts of the federation. Az-Zubair (2010).

Building on the United Nations global conferences of the 1990s, the United Nations

Millennium Declaration of 2000 marked a global partnership for creating an environment

conducive, at the national and global level, to the elimination of poverty and the promotion of

sustainable human development. The aims of this work are encapsulated in the Millennium

Development Goals (MDGs). The MDGs are the world's time bound and quantified targets

for addressing extreme poverty in its many dimensions – income poverty, hunger, disease,

inadequate housing – while promoting gender equality, education and environmental

sustainability. The MDGs share common notions with Nigeria's own development vision, as

enshrined in the 1999 Constitution of the Federal Republic of Nigeria. Under the section

'Fundamental Objectives and Directive Principles of State Policy', the Constitution stipulates

that the security and welfare of the people shall be the primary purpose of government. It

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goes on to say that the state shall ensure that suitable and adequate shelter and food, a

reasonable national minimum living wage, old-age care and pensions, and unemployment

benefits are provided for the citizens. Economic development plans, policies and programmes

are designed and implemented by national and state governments with the aim of achieving

these development goals. While the MDGs are country-level targets for sustainable human

development, state governments play a pivotal role in achieving them. In Nigeria, state and

local governments have considerable autonomy in economic policy and fiscal matters. The

three levels of government (federal, state and local) share responsibility for public policies

and services crucial to the achievement of the MDGs. In principle, Nigeria's state and local

governments are closer to the grassroots in providing basic services, so their actions or

inactions impact directly upon the MDGs. So Nigeria's 2015 MDG targets cannot be

achieved unless state and local governments take on their development responsibilities in a

proactive, coordinated, effective and sustained way. Az-Zubair (2010).

Nigeria has a lot of potentials, which are enough for it to compete favourably with the

countries of the G-7, namely; France, Germany, Italy, Japan, United Kingdom, United States

and Canada. This view has been strongly supported by reports of the Goldman Sachs (2007),

Soludo (2007), NEEDS, (2004), Vision Report (1997) and a host of others. In a study,

NEEDS (2004) noted that, Nigeria has the potential to become Africa’s largest economy and

a major player in the global economy by virtue of its rich human and material resource

endowment, while Goldman Sachs (2007) argues that in the whole of African continent only

two countries have the potentials to be among the G-20 by 2020 and these countries are

Egypt and Nigeria. (United Nations, 2009).

The situation of MDG in Nigeria can be seen from two main sources: the Nigeria MDG

report 2004 and the Nigeria MDG report 2005. We can also assess the situation from MDG

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office especially the Debt Relief Gains as provided in the 2006 annual budget. The 2004

report which was Nigeria’s first report on the MDGs states that “based on available

information it is unlikely that the country will be able to meet most of the goals by 2015

especially the goals related to eradicating extreme poverty and hunger, reducing child and

maternal mortality and combating HIV/AIDS, malaria and other diseases” Millennium

Development Goals Report (2004). The Nigeria Millennium Development Goals 2005 report

is the second in the series of annual reports on the MDGs in Nigeria. The report which

addressed the eight MDGs highlights the current status and trends of each of the MDGs, the

challenges and opportunities in attaining the goal, the promising initiatives that are creating a

supportive environment and priorities for development assistance. The report concludes that:

There is high potential to attain some of the Millennium Development Targets namely,

Achieving universal primary education

Ensuring environmental stability

Developing a global partnership for development

Given the current policy environment and strong political will, there is also the likelihood of

eradicating extreme poverty and hunger. The conclusion of the MDG 2005 report is very

remarkable and gives hope that there is possibility for achieving all the MDGs in Nigeria

with sustained effort. This conclusion is quite different from the conclusions reached by the

first report in 2004. It is intriguing that without providing the basis and reason for the

dramatic change, the 2005 states that there is high potential to achieve 3 of the goals (Goals

2,7 and 8) likelihood to achieve one with strong political will(Goal 1) and the need for

sustained efforts to ensure that the country meets the remaining four goals(Goals 3,4,5, and 6)

Igbuzor (2006).

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Three global developments have potentially critical implications for Nigeria's prospects for

achieving the MDGs: The global financial crisis, climatic change and food price inflation.

The global financial crisis has had an effect on Nigeria, mainly through lower oil revenues,

the drying-up of credit and weaker flows of private capital. The crisis has underlined the need

to accelerate diversification of the economy and strengthen fiscal management. The global

economic crisis has slowed the pace of poverty reduction in developing countries, and is

hampering progress toward the other Millennium Development Goals (MDGs).

Nigeria is acutely vulnerable to climate change. The impacts in each ecological zone will be

different. The effects of climate change threaten progress on all the MDGs. However, if well

managed, measures to deal with the effects of climate change provide important opportunities

for ensuring more sustainable progress.

At its peak in 2008, food price inflation was over 20 per cent creating difficulties for many

Nigerians. However, this was not the first such episode and a number of factors cushioned the

impact, such as the diversity of staple crops grown in the country. Agricultural development

remains the best protection against future food price crises. Igbuzor (2006)

The crisis is having an impact in several key areas of the MDGs, including those related to

hunger, child and maternal health, gender equality, access to clean water, and disease control

and will continue to affect development prospects well beyond 2015. As a result of the crisis,

53 million more people will remain in extreme poverty by 2015 than otherwise would have.

Even so, the report projects that the number of extreme poor could total around 920 million

five years from now, marking a significant decline from the 1.8 billion people living in

extreme poverty in 1990. Global Monitoring Report (2010).

It is important to point out that there are limitations of utilizing the MDGs as a framework for

delivering or measuring development. ( Abani, C., Igbuzor, O. and Moru, J. 2005). First, they

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risk simplifying what development is about, by restricting the goals to what is measurable.

Many aspects of development cannot be easily measured. Secondly, some of the goals are

very modest e.g. the goal to half the proportion of people living on less than $1 a day by 2015

and the target to achieve a significant improvement in the lives of at least 100 million slum

dwellers by 2020. Finally, some of the targets do not address the problems holistically. For

instance, the MDG on education talks only of a full course of primary schooling with no

reference to secondary and tertiary education.

Despite the limitations mentioned above, it is necessary for us to engage the MDGs for many

reasons. First, the MDGs draw together in a single agenda, issues that require priority to

address the development question. Secondly, the MDGs have received tremendous

endorsement and backing by world’s governments. Thirdly, the MDGs have the advantage

being more or less measurable, few in number, concentrated on human development and

focused almost on a single date-2015. Another advantage of the MDGs is that it adds urgency

and transparency to international development. Finally, explicit resource commitments have

been made to achieve the MDGs.

2.1 CONCEPT OF HUMAN DEVELOPMENT.

Human Development is a development paradigm that is of more significance than the rise or

fall of national incomes. It is about creating an environment in which people can develop

their full potential and lead productive and creative lives in accord with their needs and

interests. People are the real wealth of nations. Development is thus about expanding the

choices people have to lead lives that they value. Therefore, much more than economic

growth which is only means of enlarging people’s choices. Human development is related to

economics and standards of living. Adediran (2007).

The origins of the HDI are found in the annual Human Development Reports of the United

Nations Development Programme (UNDP). These were devised and launched by Pakistani

15

economist Mahbub ul Haq in 1990 and had the explicit purpose "to shift the focus of

development economics from national income accounting to people centred policies". To

produce the Human Development Reports, Mahbub ul Haq brought together a group of well-

known development economists including: Paul Streeten, Frances Stewart, Gustav Ranis,

Keith Griffin, Sudhir Anand and Meghnad Desai. But it was Nobel laureate Amartya Sen’s

work on capabilities and functionings that provided the underlying conceptual framework.

Haq was sure that a simple composite measure of human development was needed in order to

convince the public, academics, and policy-makers that they can and should evaluate

development not only by economic advances but also improvements in human well-being.

Sen initially opposed this idea, but he went on to help Haq develop the Human Development

Index (HDI). Sen was worried that it was difficult to capture the full complexity of human

capabilities in a single index but Haq persuaded him that only a single number would shift the

attention of policy-makers from concentration on economic to human well-being. Sakiko

(2003), United Nations Development Programme (1999).

Human capital refers to the stock of competences, knowledge and personality attributes

embodied in the ability to perform labour so as to produce economic value. It is the attribute

gained by a worker through education and experience. Many early economic theories refer to

it simply as workforce, one of three factors of production, and consider it to be a fungible

resource – homogeneous and easily interchangeable. Other conceptions of labour dispense

with these assumptions. Human capital theory predicts that more educated individuals are

more productive. According to the theory, productivity of labour is high with educated

individuals and consequently they contribute far more to the level of national income and also

earn higher income than their uneducated counterparts. Furthermore, education is a good

measure of human development and the relationship between human development and

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poverty level has a significant effect on economic growth and developme b nt in some

selected countries of the world. Adediran (2007).

Human Development (HD) and Human Development Index (HDI) are powerful concepts.

The former refers to the process of empowerment in the possession of the capacity to build up

oneself so as to be able to live a long life, be able to read and write and so participate in the

societal affairs effectively and above all be gainfully employed to earn a living. The latter

merely establishes how far a country has been able to achieve this for its citizens in numerical

qualitative evidence represented by a real number. The fact is that earlier indices of

development such as per capita income and its various derivatives have not been able to

establish this effectively, especially for comparative purposes. HDI is an index fashioned out

of education, life expectancy and income in purchasing power parity.

The first Human Development Report in 1990 opened with the simply stated premise that has

guided all subsequent Reports: “People are the real wealth of a nation.” By backing up this

assertion with an abundance of empirical data and a new way of thinking about and

measuring development, the Human Development Report has had a profound impact on

development policies around the world. The 2010 Report continues the tradition of pushing

the frontiers of development thinking. For the first time since 1990, the Report looks back

rigorously at the past several decades and identifies often surprising trends and patterns with

important lessons for the future. These varied pathways to human development show that

there is no single formula for sustainable progress. In other words, no single index could ever

completely capture such a complex concept—and that impressive long-term gains can and

have been achieved even without consistent economic growth. Looking beyond 2010, this

Report surveys critical aspects of human development, from political freedom and

empowerment to sustainability and human security, and outlines a broader agenda for

research and policies to respond to these challenges.

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The new 20th Anniversary Edition of the Report revisits that original analytical exercise,

using new methodologies and international data sources, also looking back to 1970. The HDI

2010 report combines three dimensions: Longevity (a long and healthy life): measured by

Life expectancy at birth; Knowledge (access to knowledge): measured by Mean years of

schooling and Expected years of schooling; and Standard of living (decent standard of

living): measured by purchasing power based on GNI per capita (PPP US$).

Human Development Index (HDI) 2010 ranks Nigeria 142nd position out of 169th listed low

human development. Human Development (HD) concept takes into account all the products

of development including education, health etc. Hence, Policy makers and government must

be reoriented and tutored to know the enormity of the combination of HDI concept as a guide

to development effort to achieve the concept itself. Adediran (2007).

2.2. OVERVIEW OF NIGERIAN MILLENNIUM DEVELOPMENT GOALS

The aftermath of Millennium Development Goals (MDGs) declaration by the world leaders

in September 2000 at the United Nations Millennium Summit, pave the way for the creation

of MDG office in Nigeria. It was established as a secretariat charged with the responsibility

of executing MDGs affairs in the country, headed by Senior Special Assistant to the President

on MDGs (SSAP-MDGs). Since then it is commonly known as the MDG office,

subsequently, other offices were opened in all 36 states and they have been operating on

projects and programs down the ladder to local government. In order to intensify effort and

demonstrate government commitment, virtual poverty fund (VPF) was established to house

debt relief gains. In the year 2007, two innovative mechanisms for achieving the MDGs were

put in place; first, conditional grants scheme (CGS) to states and subsequently to local

governments to execute projects and programs. Second, social safety nets scheme. This

scheme provides cash or in-kind transfer to the poorest in the society. MDG Office (2008).

In short, MDGs refers to series of eight time bound development goals consisting of eighteen

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targets and forty-eight indicators that seek to address issues of poverty, education, gender

equality, health, environment and global partnership for development, endorsed by the

international community to be achieved by the year 2015.

In recent years, Nigeria's macroeconomic environment has improved considerably. This is in

marked contrast to the 1990s when Nigeria was considered to be among the most volatile

economies in the world. In particular, macroeconomic performance over the last five years

has been buoyed by better fiscal and debt sustainability levels and improvements in growth.

During the 1990s, growth barely reached 1 per cent, but it has now increased to, and

stabilised at, about 6 per cent since the return to democracy. The ratio of external debt to

GDP went from over 100 per cent to below 10 per cent. The situation has benefited from

higher crude oil prices, and better fiscal and macroeconomic management. MDG Report

(2010). The question of whether Nigeria can or cannot meet the MDGs is a crucial one that

should agitate the minds of politicians, government bureaucrats, civil society activists and

development workers. In our view, there is no straightforward answer. It can be answered

either in the negative or the affirmative. The NEEDS document clearly states that “if present

trend continues, the country is not likely to meet the Millennium Development Goals.” On

the other hand, the 2005 report gives the conditions for meeting the goals: strong political

will and sustained efforts. Perhaps, a better way to frame the question is what can Nigeria do

to meet the MDGs in 2015? In our view, Nigeria has sufficient resources to meet the MDGs

in 2015. But for this to happen, as argued above, the country will have to change course in

the conceptualization and implementation of policies and programmes to achieve the MDGs.

NEEDS (2004). Unfortunately, looking at many indicators for measuring progress towards

the MDGs, The various Human Development Index (HDI) reports continue to place Nigeria

on the last rung of the global development ladder. Life expectancy in Nigeria has drastically

reduced to 45; real income of most families has woefully reduced; unemployment is gone

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overboard. Nigeria is topping the list of countries with malnourished children; Nigeria's

literacy rate is still low. Nigeria is ranked as the 20th hungriest country on the Global Hunger

Index (GHI); Nigeria is pitiably named among the countries with the highest number of

illiterates. Therefore, the greatest challenge facing our government is to improve the

appalling human conditions and the standard of living in Nigeria. Human development is the

epicentre of all developments. Human beings are the wealth of a nation. Consequently, in the

coming months, the government should initiate, fine-tune or galvanize concrete recoverable

programs and projects aimed at putting Nigeria on the track to achieving the MDGs. Men of

character should be entrusted with the disbursement and utilization of development funds to

ensure accountability. (This day, 2010).

One good initiative in Nigeria designed to meet the MDGs is the Oversight of Public

Expenditure in Nigeria (OPEN) set up to monitor the Debt Relief Gain (DRG). Two issues

make this initiative unique. The first is the leadership of the process which has been

participatory, open, transparent and all inclusive with participation of private sector and civil

society. The second and perhaps most important is that systems have been put in place to

track resources. This is perhaps the model that should become the norm in every ministry,

department and agency at all levels of government. It must be however be recognized that

development is a complex issue and goes beyond allocation of Debt Relief Gains to some

MDG Ministries. A scholar once argued that development requires growth and structural

change, some measure of distributive equity, modernization in social and cultural attitudes, a

degree of political transformation and stability, an improvement in health and education so

that population growth stabilizes, and an increase in urban living and employment.

Kambhampati (2004).

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2.3 POVERTY AND HUNGER ERADICATION

Poverty and hunger are common characteristics of underdeveloped world, particularly in

Africa. They are social vices accounting for the degrading and pitiable standard of living

among the under privileged. The results are that people feel neglected, they are downhearted,

disillusioned, demoralized and often more susceptible to medical problems. ‘what would the

next few years bring for an average Nigerian in terms of poverty and hunger eradication

amidst the unprecedented age of terrorism, precarious and hostile economic and political

climates, starling and dramatic breakthrough in technology and the fast pace of globalization?

Can anything be done to stem the tide of poverty and hunger by 2015? These questions are

among the pivotal issues encapsulated in the 2015 Millennium Development Goals agenda.

Eromafuru (2009).

Poverty and deprivation are almost as old as mankind. Poverty is a threat to the growth and

development of any country. It is inimical to individual well-being, personal growth and

development. Apart from humiliating and demoralizing its victims, extreme poverty creates a

society with a pool of mediocrity, nuisance, and an unwholesome industrial climate notorious

for unprecedented wave of unemployment, indecency, crime, hunger, heartache, infidelity,

suffering, deprivations and disillusionment. It is paradoxical to note that despite the

abundance of material and human resources, millions of people particularly in developing

and transition countries, still live in abject poverty. Poverty is a serious challenge to the

Nigerian government. Ukpong as cited in Obadan(1996), has succinctly argued; ‘poverty has

earned recognition to some extent of its ravaging society and the affairs of humanity at the

international, national and local levels. The need exists for urgent actions towards its

eradication and control. Indeed, poverty is a snare. It is dehumanizing, it must be eradicated.

21

The British magazine, ‘The Economist’ commented: ‘the human race has never been richer or

better armed with the medical knowledge, technological prowess, and intellectual firepower

needed to beat poverty, many though have benefitted from this know-how. The streets of the

big cities in a number of developing countries are packed with glaring new cars, shopping

malls are full of the latest gadgets, and there is no lack of people to buy them, still vast

number of people do not benefit from the wealth that some enjoy’.

Poverty continues to undermine progress in many areas. The concepts of poverty and hunger

can be akin to human identical twins having the same physical qualities. In other words when

we say poverty and hunger, one is expressing the symptoms and manifestations of the other

by extension underdevelopment. (Central Bank of Nigeria / World Bank 1991:1). In Africa,

the post military dictatorship, political instability, mismanagement and corruption

characterized colonial periods. These periods of military rule entrenched poverty and hunger

into the country as a way of life thereby making the people inaccessible to adequate health

facilities, low quality of education, low life expectancy, high infant mortality, low income,

unemployment, poor storage facilities, which further exacerbated hunger. Food production in

Africa is unstable particularly on basic foods such as cassava, rice, yam, maize, poor storage

facilities, losses in post-harvest goods, inadequate market system, poor incentives to farmers,

poor budgetary allocation to Agriculture are the ban of poverty and hunger. (Onah 2006:67-

68). African nations of which Nigeria is one are typically poor and fall towards the bottom of

any list measuring small size economy activity, such as income per capita, despite a wealth of

natural resources. Land degradation, a consequence of extensive Agriculture, deforestation

and overgrazing, has reached alarming levels and further threatens livelihoods. The poorest

people live in the isolated zones deprived of the social safety nets and poverty reduction

programmes available in semi-urban areas. (UNICEF, 5:6). The poor are those deprived,

unable and lack resources to acquire basic needs of life. They are structurally placed to be

22

dependent. Poverty denies its victims the basic needs of survival and they are unable to meet

their social, economic and political obligation in the society.

The World Bank Report (1996) shows that sub-Saharan Africa including Nigeria is among

the world’s poorest class of people in terms of Gross National Product (GNP) and access to

social and political life. Social statistics shows that Nigeria is the worst in terms of hunger

and poverty in sub-Sahara Africa despite the abundance of natural resources. Adding that

greater percentages of Nigerians are living below the universal poverty line of US$1 per day.

World Bank’s chief economist and senior vice president for development economics,

Richards Stern, recommend that economic growth is necessary to accelerate progress in

human development, but it is not enough. Poor countries including Nigeria are poor largely

because they have underdeveloped infrastructures and facilities health, education, agriculture,

governance at a large scale and law enforcement. They remain poor because they lack the

relevant resources and mental preparedness to overcome their development deficiencies.

The dominant characteristic of Nigeria’s human development profile is the gap in wealth

between the north and south of the country. A 2009 visit by a UK House of Commons

committee concluded that “some of the States in northern Nigeria have the worst human

development indicators of any region in the world which is not affected by conflict.”

The impact on the poor of recent years of high food and fuel prices, a squeeze on foreign aid

and falling expatriate remittances remains conjecture. The World Bank observes that “growth

has been resilient during the recent global financial crisis.” But it also estimates that there are

50 million underemployed youth in Nigeria, conceding that “strong economic growth has not

translated into higher employment rates.” (One world, 2011).

The situation of poverty in Nigeria could be linked to the theory of imperialism which

deprives its concepts from Marxists sources. In a nutshell, the wealth and poverty of nations

23

resulted from the process of exploitation of the international capitalist system and its special

imperialist agents, both domestic and alien. (Galtung, 1973:6). Consequently, hunger and

poverty in Nigeria emanate from the structural imbalance of the economy, inappropriate

development agents and debt burden imposed by dependency and the global exploitation of

our resources for the development of their metropolitan countries. (Offiong, 1980:14-15). The

alarming rate of environmental degradation and its effects on employment and food

production is also traceable to these imperialist agents; particularly the domestic bourgeoisies

whose interests are programmes launched in Nigeria. Furthermore, high unemployment rate,

unaffordable basic education, inequality, insecurity, deprivation of fundamental human

rights, freedom, liberation and basic needs for human survival and crisis for constant

agitation for the resource control in the case of Niger Delta are evidence of poverty and

hunger in the land. However, as a means to eradicate poverty and hunger in Nigeria, Nigerian

government had at different times established different poverty alleviation programmes

which include: National Acceleration Food Programmes in 1972, Operation Feed the Nation

in 1976, National Directorate of Employment in 1986, National Poverty Eradication

Programme in 2000, and the National Economic Empowerment and Development Strategies

initiated by Obasanjo on his assumption of office in May 1999 and his second term policy in

2003.

2.3.1. CAUSES OF POVERTY AND HUNGER IN NIGERIA.

The economic malaise driving poverty in Nigeria is the failure to distribute the country’s vast

oil revenues more equitably. Inability to diversify into non-oil sectors is such that, in 2010,

oil revenues contributed 89% of exports and 65% of the national budget.

With over 200 tribal identities, Nigeria’s vast ethnic diversity demands a decentralised

structure of government administration. The challenge of efficient delivery has been

undermined by a pervasive culture of corruption. Dysfunctional government agencies at

24

federal, state and local levels therefore impede poverty reduction strategies.

Demographic pressures place additional demands on both household and government

budgets. Between 2000 and 2008, population growth was 3.2% per annum, far above the

global average. Urban migration is projected to bring 60% of the total population into the

cities by 2025, fuelling the unplanned slum settlements where poverty is rife. One World

(2011).

Some other causes of poverty in Nigeria are as follows:

Colonialism: in most African countries, the years of colonialism brought some

setback to them. The colonial masters for instance, built and structured African

economy to facilitate the expropriation of their resources for British economic

growth and development. In the process Nigeria was penetrated, dominated,

raped, exploited, distorted, and disarticulated, thereby leaving the country in

hunger, poverty and dependency. (Claude 1989:xi).

Corruption: according to (Lipset and Lenz 2000:112), corruption is ‘effort to

secure wealth and power through illegal means’. In Nigeria, corruption has

contributed immensely to poverty and misery of a large segment of the

population, exemplified on Nigeria’s horrifying faces of despair and deprivation.

Many native groups in Nigeria believe family relationships are more important

than national identity and people in authority often used nepotism and bribery for

the benefit of their extended family group at the expense of the nation.

Poor Leadership and Misuse of Funds: the issue of poor leadership revolves

around both military and civilian governments. Various regimes in Nigeria have

overburdened the country by borrowing substantial sums of money from

International Monetary Funds (IMF), World bank, Paris Club, etc. it is of note that

25

these foreign loans are invested on weapons and the rest on personal consumption

which does not alleviate poverty. (Wikipedia, 2008)

Flood, War and Natural Disasters: in Africa, the destruction caused by war and

natural disasters such as drought and flood often have devastating effect on the

communities. In many parts of Nigeria, the production of food depends upon the

intense manual labour of each family. The religious and ethnic conflicts that have

ravaged the country such as Oodua Peoples’ Congress (OPC)/Hausa and

Modakeke conflicts in the South-West, the Ijaw/Urhobo/Itsekiri conflicts in the

Niger Delta, and the Umuleri/Aguleri conflicts in the south East and the numerous

religious conflicts sweeping through the Northern part of the country, have made

per capita food production plummeted (UNICEF, 2000:5). In addition, in the

Northern part of Nigeria, farmers suffer drought from time to time while their

counterparts in the South experience flooding and erosion. These problems have

in many occasions led to massive deaths, loss of crops and animals, property, etc.

Diseases: The greatest mortality in Nigeria arises from preventable water-borne

disease. Malaria, tuberculosis, tapeworm and dysentery often claim lives. Report

shows that HIV/AIDS contribute to the worsening poverty situation at household

level in African countries. For instance, between 12 and 14 million African adults

have died of HIV/AIDS. (World Bank/UNICEF) cited in (UNICEF, ibid).

Culture Values: these have also helped to explain the intractability of the problems

of hunger, poverty and injustice in part of the third world.(Harrison,2000)cited by

(Dike, 2005:5). For instance the culture of polygamy in Nigeria is one of the

causes of poverty.

26

2.3.2 Assessment of some previous and present poverty alleviation programmes in

Nigeria.

S/N Year launched. Names of programmes project or

institution.

Nature of activity.

1. 1975 Agriculture Development

Projects (ADPs)

Provision of decentralized

opportunities and resources in

agriculture to smallholder

farmers.

2. 1975 Universal Primary Education. To provide free primary

education.

3. 1976 River Basics Development

Authority

To undertake comprehensive

development of both surface

and underground water

resource for various purposes.

4. 1976 Operation Feed the Nation

(OFN)

To provide sufficient food for

all Nigerians. To facilitate

agricultural credit from

commercial banks to farmers.

5. 1979 Green Revolution To provide sufficient food for

all Nigerians.

6. 1986 Directorate of Food, Roads and

Rural Infrastructure.

To coordinate and streamline

all rural development

activities in the country and to

accelerate the pace of

27

integrated rural development.

7. 1986 National Directorate of

Employment.

To provide skill development

to secondary school leavers

and graduates from tertiary

institutions.

8. 1987. Nigerian Agriculture insurance

cooperation

Provision of insurance cover

for business engaged in

agricultural production.

9. 1987 Better Life Programme

(BLP)

Training finance and

Guidance

10. 1989 Peoples’ Bank of Nigeria Encouraging saving

and credit facilities

11. 1990 Community Banks Credit facilities

12. 1994 Family Support

Programme (FSP)

Health care delivery,

child welfares, youth

development etc

13. 1997 Family Economic

Advancement Programme

(FEAP)

Credit facilities to

support the

establishment of

cottage industries

14. 2001 National Poverty

Eradication Programme

(NAPEP)

Employ generation in

rural sector and

societal welfare

15. 2004 National Economic Human and Economic

28

Empowerment and

Development Strategy

(NEEDS

Empowerment

16. 2007 Millennium Development

Goals (MDGs)

Human development

as a means of nation /

national development

Source: Adediran (2007), NEEDS

The Nigeria government’s poverty reduction framework is named the National Economic

Empowerment and Development Strategy (NEEDS), the state level framework is the State

Economic Empowerment and Development Strategy (SEEDS), the local government is the

Local Economic Empowerment and Development Strategy (LEEDS), the community level is

the Community Economic Empowerment and Development Strategy (CEEDS), while at the

household level is the Personal Economic Empowerment and Development Strategy

(PEEDS). NEEDS has four pillars; empowering people and improving social service

delivery; improving the private sector and focusing on non-oil growth; changing the way

government works and improving governance; and value reorientation at all level (World

Bank, 2007)

The government has gone to considerable lengths to integrate the MDGs into its economic

planning and to create greater accountability for poverty reduction. The task of improving

project delivery through empowerment of state and local government entities has been

pursued through the Conditional Grants Scheme. This makes grants available subject to

reform of local institutions, with very encouraging results. A reduced federal budget for the

scheme in 2011 nevertheless amounts to about $300 million. The dire record of social data

29

collection is being addressed through a National Strategy for the Development of Statistics

2010-2014.

From all indications, more than 70% of the population exist below the poverty line. The

various programmes as we have seen above initiated towards poverty and hunger alleviation

have invariably spread poverty. In other words, the more these programmes, the more poverty

spreads. The situation is more painful considering the fact that Nigeria has lots of resources

including oil which she exports on a daily basis. Again these programmes ordinarily meant to

alleviate poverty are now like Frankenstein monster that was made to serve the people but the

people are in turn serving the monster. What this means is that these programmes that were

made to alleviate poverty ended up pauperizing the less privileged people with more poverty

and hunger. This is because the programmes are apparently hijacked by the politicians and

bureaucrats to perpetuate poverty with reckless abandon resulting in alleviating their own

poverty and increasing their security.

The reality is that Nigeria’s effort towards sustainable development would be a dream if

government does not create a forum of projects-recipients reconciliation to ascertain the level

to which these programmes have actually better their lot, just as a customer and the bank

reconcile their accounts to know their financial statement. By so doing, the people will be

able to gather and testify the level of their involvement, their benefits and their next

expectations. The idea of creating more and more institutions to be managed by the same

people, to further their interests is an ill-conceived idea of putting an old wine in a new wine

skin. Rather there should be continuity of programmes and periodic changes of the personnel

in order to enhance efficient programmes delivery. ‘Abujanization’ of programmes without

decentralization to reach or get to the grass roots is an aberration. The local people should be

asked to identify their needs for implementation. Those charged with the responsibility of

distributing programme funds should be honest with utmost good faith to ensure the success

30

of programmes and their implementation. Agriculture should be encouraged at the rural level.

Because vast number of people are rural dwellers that can productively make use of

agricultural loan facility,etc. to improve their living conditions. Aisedon, Gaiani & Silvia

(2009).

2.4 ACHIEVING UNIVERSAL PRIMARY EDUCATION.

Education offers the people alternative options pertaining to the kind of lives they want to

lead. It enables the people to interact and relate meaningfully in the community. It also helps

to foster in the members of the community values such as hard work, integrity, honesty,

selflessness and tolerance.

The National Policy on Education adopted in 1981 and revised in 1995 and 1998 provides for

nine years of basic education. The Universal Basic Education (UBE) Programme established

in 1999, aims to provide access to all children at least the first nine years of schooling.

Nigeria also endorsed the Jomiten Conference on Education For All (EFA) by the year 2000

that set out targets for early childhood care and development, primary education, junior

secondary school, and adult literacy. The trend in Gross Enrolment Ratio (GER) indicates

considerable fluctuation in enrolment between 1991 and 2000. Enrolment increased steadily

between 1991 and 1994, rising from 68%. Subsequently, enrolment declined to 81% in 1995

and 70% in 1996. Nigeria, therefore did not achieve the Jomiten EFA goals of 2000. Literacy

rates were higher in urban areas compared to rural areas, and more males were literate

compared to females. Recent survey reveal that the overall literacy rates have declined from

58% in 1990 to 49% in 2001, while literacy rate among women and girls have declined from

44% over the same period. Enojo (2009)

Though significant progress has been made, so much needs to be done to enhance Universal

education. Several Nigerian children still have no formal education. It is claimed that over

90% of children employed as domestic servants have never attended a formal education.

31

According to the UNICEF, nearly 800million adults in Nigeria are still illiterate. (Chukwuike

2005). Even the quality of those who had formal education is egregiously low.

In Nigeria, reports on the MDGs indicate that a reasonable degree of success has been

recorded in the area of Universal primary education as manifested in increased primary

schools pupil enrolment and training of teachers. MDGs Report (2006).

2.5 PROMOTING GENDER EQUALITY AND WOMEN EMPOWERMENT.

Gender equality is essential for socio economic development, poverty reduction and disease

prevention. Quite unfortunately, the commitment to the implementation of this goal has not

been very impressive. Women still suffer so many inequalities in political participation and

control of household resources. Girl child education compared to the male child education is

yet unparalleled. Poverty is yet largely feminized. Several culture norms are manipulated to

ensure subordination of women to men. Genital mutilation, harmful widowhood practices and

other human rights violations against women are still practiced.

The reports highlights gender disparity in access to primary, secondary and tertiary education

leading to unequal access to employment. It was found that the trend in gender ratios show a

reduction of inequality at the primary and secondary levels, although the disparity is still

pronounced at the tertiary levels. The ratio of literate females to males in the 15 to 24 years

age group increased from 0.89 in 1996 to 0.93 in 2000. However, National literacy rate

remained low, declining from 58% in 1990 to 49% in 2001. During the same period, literacy

rates for women and girls declined from 44% to 41%. Enojo (2009)

2.6 REDUCE CHILD MORTALITY.

Reduction of child mortality is of central concern. High child mortality is a huge loss and a

serious threat to the nation. It is an acknowledged fact that children are the future of any

32

nation. Any nation therefore which suffers high child mortality has its future endangered.

According to the MDGs report in 2006, as against the global target of 30/1000 live births in

2015, Nigeria had 110/1000 live births.

Recent estimates from 2008 National Demographical and Health Survey put under five

mortality rates as 217 per 1,000 with large regional variations. Urban and rural areas had

under-five mortality rates of 243 per 1000 and 153 per 1000 respectively. With regard to geo-

political zones, the highest under-five mortality rates were found in the North West and North

East and the lowest in the South East and South West. Enojo (2009)

Indeed with high child mortality and morbidity, the nation will be drained off of the human

capital needed in the future. There are indicators that the government have shown signs of

appreciation of the danger of high child mortality for national development. They have

through collaborations provided health services such as immunization and enlightenment on

sound health tips.

2.7 REDUCING MATERNAL MORTALITY.

The moment of childbirth should be a period of happiness. This has not been the case for

several women who have lost their lives during pregnancy and childbirth due to

complications. According to UN Reports, Nigeria has the second highest number of maternal

deaths in the world after India. (Ogbu, 2008). Also, the Centre for Reproductive Rights, a

New York based international non-governmental organization stated that over 59,000

Nigerian women die annually during child birth. The CRR further stated that a woman in

Nigeria has a 1-in-18 risk of dying in childbirth or from pregnancy related cause during her

lifetime. The risk differs for women in rural, low income and non-formal education groups.

Majority of these maternal deaths are said to be preventable but for the actions or inactions of

governments. (Nwankwo, 2009). Increased maternal deaths deplete the nation of human

capital, increase the ranks of orphan, economic fugitives and poverty-stricken children and

33

increase the risk that more of Nigeria’s youth will be at the mercy of charitable organizations

and others will be forced to learn new strategies such as prostitution, street begging, hawking,

and pickpocket for survival.

2.8 COMBATTING HIV/AIDS, MALARIA, TUBERCULOSIS AND OTHER

DEADLY DISEASES.

Combating HIV/AIDS, malaria, tuberculosis and other deadly diseases, which is at the heart

of the MDGs, has been one of the major challenges of Nigeria. According to the United

Nations Report, Nigeria ranks third in the League of Nations with people living with

HIV/AIDS pandemic. (Ogbu, 2008). Though there are no exact statistical figures on the

number of deaths arising from these deadly diseases, the number is no doubt considerably

large. The number of orphans due to these diseases is also on the increase. More so, a large

population of the population is suffering from the killer diseases and many more are at the

risk of being victims. As Price Smith contended, there is link between AIDS-related deaths

among the youth, the most infested and productive segment of the population, the

commensurate loss of human capital, and resultant falling of GDP levels in Africa. He stated

that as AIDS skims off the doctors, teachers, parents, lawyers, entrepreneurs, judges, and

policymakers; it leads to institutional and societal fragility. USIP (2001). According to the

macroeconomic costs of AIDS and other associated infectious diseases posed an extra burden

on societies. As the sickness strikes at the labour force, it takes a toll on productivity,

profitability, and foreign investment in the future. USIP (2001).

The Nigerian government through collaboration with local and international non-

governmental organizations is addressing the problem of stigma and discrimination against

people living HIV/AIDS. Also there has been continuous public education on malaria and

tuberculosis management and control. Federal Republic of Nigeria. (2006). These efforts

should be sustained while seeking lasting solutions.

34

2.9 ENVIRONMENTAL SUSTAINABILITY.

Environmental Sustainability is the prudent use of natural resources and protection of the

ecosystem, which sustain lives from the despoliation and degradation. Nigeria’s rich

environmental base is currently undermined by unsustainable practices such as unrestrained

deforestation encouraged by the use of fuel wood for cooking, climate change and pollution

arising from industrial waste, gas flaring, and oil spillages. In particular, the Niger Delta has

suffered severe depletion of the environment. On account of severe ecological despoliations

and pollution arising from oil production in the Niger Delta, about 10 million of the people

are destitute, with 14 million struggling to eke out a living. Only about 30% of the population

of the region has access to safe drinking water while the rest of the people depend on water

from often contaminated lakes, streams, stagnant ponds and hand dug wells. Emuedo (2006),

Osumah (2009). In other parts of the country, the consumption of fossil fuels oil, coal and

natural gas results in carbon dioxide, emissions that are contributing to gradual global

warming of the atmospheric conditions. The expected repercussion is climate change. Also,

there has been severe depletion of the environment in some parts of the country due to coastal

erosion and flooding. In particular, many parts of the country such as Lagos, Anambra, Imo,

Benue, Edo, and Akwa Ibom states erosion and flooding have ruined farmlands, residential

quarters, and highways thus imposing adverse economic calamities and many environmental

refugees. Many of the environmental refugees who are not fortunate to benefit from

rehabilitation end up as destitute. Even those who are rehabilitated end up having to contend

with violation if their rights, which usually come in the form of loss of property and violence

of armed conflict from hostile hosts. Fagbohun (2008).

Nigeria has not shown so much commitment to environmental pollution. The repeated shift in

the terminal date for gas flaring indicates this. Poor environmental management has

engendered environmental scarcities that have led into violence in various parts of the

35

country. The recurring conflicts in the Niger Delta are linked to poor environmental

management.

2.10 DEVELOPING A GLOBAL PARTNERSHIP.

Nigeria’s overall economic performance since Independence in 1960 has been decidedly

unimpressive. According to World Bank data, the average annual growth rate of Gross

Domestic Product (GDP) between 1960 and 2000 was less than 4 percent. Thus, despite the

availability and expenditure of colossal amounts of foreign exchange obtained mainly from

its oil and gas resources, Nigeria’s economic growth has been weak and the incidence of

poverty has increased. It is estimated that Nigeria received over US$228 billion from oil

export receipts between 1981 and 1999 (Udeh, 2000). Yet the number of Nigerians living in

abject poverty- that is, on less than US$1 a day – more than doubled between 1970 and 2000,

and the proportion of the population living in poverty rose from 36% in 1970 to 70% in 2000.

Nigeria’s per capita income of US$260 in 2000 is much less than, indeed it is only one-third

of its level, US$780, in 1980. (See World Bank (2003). Meanwhile, the external debt stock

has continued to mount and the debt service burden has become unbearable. Obviously, the

colossal oil revenues have been tragically misspent and misused. Corruption has been

pervasive and there has been a lack of transparency, accountability and good governance.

Above all, there have been serious mistakes made in macroeconomic and debt management

policies.

Goal Eight relates to issues of – debt cancellation, trade justice, equitable governance in

global institutions, and political, social and economic rights for the poor – as an indispensable

foundation for a politics that will enable sustained progress to end poverty in the South. It is

an important goal for holding developed countries accountable in advancing the MDGs. This

goal is particularly significant, as it requires richer countries to reform their policies and

actions to contribute to the fight against poverty. The lack of basic rights in poor countries

36

stems from and reinforces highly unequal power, within and between countries, which

marginalize poor people’s needs and priorities. Mutasa (2005). Specifically, goal 8 has as

targets the following: Develop further an open, rule-based, predictable, non-discriminatory

trading system; Address the special needs of LDCs. Includes: tariff and quota free access for

LDC exports; Address the special needs of land-locked Countries and small island

developing states through The Programme of Action for the Sustainable Development of

Small Island Developing States and 22nd General Assembly provisions; Deal

comprehensively with the debt problems of developing countries through national and

international measures in order to make debt sustainable in the long term; In cooperation with

developing countries, develop and implement strategies for decent and productive work for

youth, In cooperation with pharmaceutical companies, provide access to affordable essential

drugs in developing countries, and In cooperation with the private sector, make available the

benefits of new technologies, especially information and communication.

Four decades after Independence in 1960, Nigeria remains a poor country with a per capita

income of US$260 in 2000. At the dawn of the Third Millennium, approximately 70% of the

population still lived on less than US$1 a day, an indication of extreme poverty. Real GDP

growth has remained sluggish, averaging 3.5% per annum since 2000. Nigeria is also a highly

indebted country with total external debt exceeding US$32 billion in 2003. The debt service

burden remains crushing. Foreign Aid in the form of Official Development Assistance

(ODA) has been low and declining during the past decade. In 2002, ODA per capita was less

than US$2 and total ODA was only 0 .4% of GNP. Clearly, Nigeria would find it difficult to

attain the Millennium Development Goals without massive assistance from Development

Partners in the areas of Aid, Trade and Debt relief. (ibid. p 11)

Debt relief negotiated by Nigeria in 2005 provided new opportunities for investment in the

social sector. Debt servicing fell from 15.2 per cent of exports in 2005 to 0.5 per cent in 2008.

37

To build on these positive developments there is a need to take action to forestall a relapse

into unsustainable levels of debt that could prevent the country from achieving the MDGs.

The outlook for the broader partnership for development is not as bright. Trade agreements,

continue to be inequitable and constrain exports and economic growth. Development

assistance has grown although, when debt relief is excluded, it is still very low on a per capita

basis. Improving the quality of human and capital resources available is critical to attracting

the foreign direct investment that is needed to contribute to development. As a result of the

deregulation of the telecommunications sector in 2001, the proportion of the population with

access to mobile telephones increased from 2 per cent to 42 per cent between 2000 and 2008.

However, this has yet to bridge the digital divide and only 15.8 per cent of the population

currently has access to the internet. (Mutasa, 2005).

The flow of ODA (including debt relief gains) from developed countries to Nigeria has

increased dramatically since 2004, rising from US$4.49 per person in 2004 to US$81.67 per

person in 2006 and 2007). However, these figures include the large volume of debt relief

negotiated by Nigeria, which was received in tranches spanning both 2005 and 2006. This

does not reflect a large or sustained increase in the volume of additional ODA provided by

international development partners in line with their commitments.

Provisional data for 2008 from the OECD show per capita ODA of US$8.53, which is an

increase on previous years but is still far short of the volume of funds required to make

appreciable progress on the MDGs. The coordination and management of ODA from

different donors and countries is a complex challenge and the government will need to

allocate more resources to this activity. Nigeria's economy was over-burdened by the

country's huge external debt for many years. In 1990, for example, servicing the country's

external debt consumed 22.3 per cent of the value of the country's exports of goods and

services. Nigeria obtained debt relief in 2005, when the Paris Club wrote off US$18 billion of

38

its debt on condition that the country pay off the balance of approximately US$12.4 billion

owing to the Paris Club creditors. Nigeria paid off its debt to the Paris Club in 2006. It

subsequently paid off its debt to the London Club of creditors through par bonds worth

US$1.486 billion and promissory notes worth US$476 million. In addition, in 2007 Nigeria

repurchased about 21 per cent of outstanding oil warrants issued under a debt-restructuring

deal in 1991. All Paris Club debt relief gains were dedicated to additional spending on pro-

poor projects and programmes towards achieving the MDGs in Nigeria.

In 1990 there were only 0.3 telephone lines per 100 people in Nigeria. This increased to 0.54

in 2002 and to 0.86 in 2008. If this trend continues, only about 2 of every 100 people in

Nigeria will have access to telephone lines by 2015. However, many more people have access

to cellular phones. As a result of the deregulation of the telecommunications sector in 2001,

foreign investment in Nigeria's telecommunications sector increased from US$2.1 billion in

2002 to US$8.1 billion in 2006. This has significantly expanded infrastructure and activity in

the sector. The number of GSM (Global System for Mobile Communications) lines increased

from 0.27 million in 2001 to more than 1.57 million lines in 2002. The number of lines

doubled again in 2003 to 3.1 million lines and tripled in 2004, reaching 9.2 million. In 2006,

the number of lines almost doubled the 2005 figure of 18 million to reach 32 million. Thus,

access to cellular phones increased from only two out of every 100 people in Nigeria in 2000

to nearly 42 per 100 in 2008. If this trend were to continue, 56.10 per cent of the population

would have access to a cellular phone by 2015.

The number of Nigerians using the internet increased from 0.6 in every 100 people in 2000 to

15.86 in 2008. Projections for 2010 to 2015 show an average of 11.35 users for every 100

persons, rising to 13.90 by 2015. Thus, although access to the internet increased between

2000 and 2008, access rates are still very low in Nigeria. Overall, the involvement of private

sector operators in the telecommunications sector has brought competition, innovation and

39

wider coverage, mobilised new financing for the industry and increased its contribution to

GDP. Az-Zubair (2010).

Although the cost of servicing Nigeria's debts is currently within sustainable limits, there is a

need to ensure that the country does not revert to unsustainable levels of debt. A major

challenge facing policy-makers and implementers is the need to integrate the management of

external and domestic debt in such a way that debt can be used effectively to fund

development projects at the federal, state and local government levels, in addition to its

traditional objective of financing fiscal gaps. This is particularly important in view of the

unprecedentedly high level of Nigeria's domestic debt. The need to develop approaches to

public debt management that reflect changing funding realities, such as the growing

importance of public-private partnerships, is a critical challenge for policy-makers and

implementers. In the telecommunications sector, although the numbers of telephone lines and

teledensity have increased, Nigerians generally consider the pricing of telecommunication

services to be exploitative. The quality of services rendered by service providers is

considered inadequate, both by the government and by citizens. More efforts need to be made

to address issues like dropped calls, inaccurate billing and poor call quality.

In the area of foreign direct investment (FDI), there are two major challenges. The first is to

attract FDI and the second is to maximise its contribution to development. Whether foreign

companies invest in Nigeria depends on a number of factors. These include the cost of doing

business, such as the quality of human resources, adequate provision of infrastructure and the

efficiency and credibility of business regulatory institutions. Az-Zubair (2010).

The problem of development is a global challenge and the MDGs are a response by world

leaders. There are limitations to utilizing the MDGs as a framework for delivering or

measuring development. But they provide a platform to engage the development process. The

40

situation in Nigeria indicates that there are challenges in meeting the goals by 2015. For

Nigeria to meet the goals in 2015, there is the need to formulate and implement policies that

will promote transparency and accountability; overcome institutional constraints; promote

pro-poor growth; bring about structural change; enhance distributive equity; engender social

and cultural re-orientation; engineer political transformation; promote human development;

practice inclusive urban development; generate employment and transform power relations.

Nigeria is making real progress. If the supportive environment continues to improve, as it has

over the last ten years, the nation has a real chance of achieving the MDGs.

REFERENCES.

Abani, C., Igbuzor, O. and Moru, J. ( 2005), Attaining the millenium development goals in Nigeria: Indicative progress and a call for action. In Moru, J. (Ed), another Nigeria

41

is possible: Proceedings of the first Nigeria social forum. Abuja, Nigeria socialforum.

Adediran, O.E. (2007), An assessment of human development index and poverty parameters in the millennium development goals : Evidence from Nigeria.

Aisedon, Gaiani & Silvia(2009), Eradication of poverty and hunger in Nigeria MDGs: Issues on gender, women, poverty and development.

Az-Zubair A, (2010), Nigeria millennium development goals report. Government of theFederal republic of Nigeria.

Central bank of Nigeria and world bank, (1999), Nigeria’s development projects: Poverty assessment and alleviation study & march.

Claude, A. (1989), The political economy of crisis and underdevelopment in Africa. Lagos JAD publishers.

Emuedo, C. (2006); Nigeria oil, environment, poverty and cyclic insecurity to the niger delta being a seminar paper presented at the department of political science and public administration, university of Benin, Benin city.

Enojo, K. (2009), Millennium development goals and political stability in Nigeria, millennium development goals; integrated issues, vol. 4.

Eromafuru E, (2009), Unravelling the keys to maximizing the dividends of millennium development goals through poverty and hunger eradication programme, millennium development goals; integrated issues, vol. 4.

Fagbohun, L. (2008); ‘Coastal erosion, pushing the frontiers of remedies’, The nation, Tuesday, August 19.

Fukuda-Parr, Sakiko (2003). "The human development paradigm: operationalizing Sen’s ideas on capabilities". Feminist economics 9 (2–3): 301–317.

Galtung (1973), The Europeans community: A superpower in the making. (London: George Alien & Unwin).

Global monitoring report 2010 : The MDGs after the crisis.The world bank group.

Goldman Sachs (2007). BRICs and beyond, Goldman Sachs global economic research, the Goldman Sachs Group, inc. July 25, 2007, p. 158.

Harrison, E. (2000) cited by Dike, V. (2005), ‘The global economy and poverty in Nigeria’.

Igbuzor O, (2006), The millennium development goals: Can Nigeria meet the goals in 2015? A paper presented at a symposium on millennium development goals and Nigeria: issues, challenges and prospects. Institute of chartered accountants (ICAN), Abuja.

Kambhampati, U. S. (2004), Development and the developing world. USA, blackwell publishing Inc.

Lipset, S.M. and Lenz, G.S. (2000) ‘Computation, culture and markets’ in E.I, Harrison, and S.P. Huntington, 9eds) culture matters. (New York: Basic Books).

42

MDG Office (2008), MDGs Nigeria: Information kit (January) [brochure]. Abuja, Nigerian capital territory: published by office of the senior special assistant to the president on millennium development goals, Nigeria. p. 2-16.

Millenium development goals report 2004 p. v

Mutasa C, (2005) : The politics of the MDGs and Nigeria: A critical appraisal of the global partnership for development, African forum and network on debt and development. (AFRODAD).

National economic empowerment and development strategy (NEEDS) (2004). Abuja, National planning commission.

NEEDS (2004). NIGERIA: National economic empowerment and development strategy, (March) [brochure]. Abuja, Nigerian capital territory: Published by national planning commission. p. 19.

Nwankwo, J. (2009), ’59,000 Nigerian women die annually during childbirth’, daily independent, Friday, November 14.

Obadan, M.I (1996) Poverty in Nigeria characteristics alleviation strategies and programmes, NCEMA policy analysis series, vol 2, no. 2.

Office of the senior special assistant to the president on the MDGs. (2008). Mid-point assessment of the millennium development goals in Nigeria. Abuja: OSSAP-MDGs.

Ogbu, M. (2008), Tackling poverty in Gombe via cooperatives, daily independent, Tuesday, July 22.

Onah O. Fab. (2006), Managing public programmes and projects (Nsukka: Great AP express publishers).

One world poverty global guide (2011): Poverty reduction in Nigeria briefing.

Osumah, O. Pedro, O. (2009). Implementations of millennium development goals (MDGs) and National security in Nigeria: A strategic thinking.

Soludo, C. (2007). Nigeria’s financial system strategy 2020 plan: Our dream. FSS 2020 international conference, Abuja, Nigeria. Pp.1- 45.

This day (2010) Nigeria : Nation and millennium development goals.

Udeh, J. 2000. “Petroleum revenue management: The Nigerian perspective.” Paper presented at world bank/IFC petroleum revenue management workshop, Washington, D.C., U.S.A., Oct. 23 – 24.

UNDP (2003), Human development report 2003-Millenium development goals: A compact among nations to end human poverty. New York, oxford university press

UNICEF (2000) ‘Poverty in africahunger, HIV/AIDS and deaths in Africa’ file:|///192.168.1.2/Document/JV.htm 2/16/2000, 6:45pm

United Nations (2009). Country data, retrieved July 31, 2009, fromhttp://mdgs.un.org/unsd/mdg/Data.aspx.

43

United Nations Development Programme (1999). Human development report 1999. New York: Oxford university press.

United States Institute of Peace (USIP) (2001), ‘AIDS and violent conflicts in Africa’, October 15, Washington D.C.

Vision Report (1997). Report of the vision 2020 committee: Main report (September) [Brochure]. Abuja, Nigerian capital territory: Published by economic affairs office, Federal secretariat, the presidency.

Wikipedia (2008) ‘Poverty in Africa’ file.////192.168.1.2/Document/omo.htm2/16/2009, 5.56pm

CHAPTER THREE.

RESEARCH METHODOLOGY.

44

3.0. INTRODUCTION.

This chapter is concerned with the overall design of the study. This is necessary in order to

review and state the method of analysis used in the course of this research work. It explains

the layout and design of the research work, and also states the method, types and sources of

data collection.

This chapter deals with the procedure used in gathering data and analysing data to produce

information, which becomes a basis of drawing conclusions on the ‘The impact of the

Millennium Development Goals on human development’.

3.1. RESEARCH DESIGN.

A research design is the plan, structure and strategy of investigation concerned, so as to

obtain answers to research questions. The plan is the overall scheme of the research that

contains an outline of what the research prepares to do. The structure on the other side is the

outline or model of how variables are interrelated, how objectives will be achieved and how

problems encountered in the research will be solved.

This design shows a clear presentation of the subject matter in a five-chapter format as

follows:

Chapter One: This is the introduction to the study. It consists of the background of the study,

the statement of the problem, objectives of the study, justification of the study, research

questions and hypotheses, scope and limitations of the study.

Chapter Two: This contains the literature review which consists of the theoretical literature

of the study on the impact of the Millennium Development Goals (MDGs) on human

development index, and how their achievement would facilitate economic development.

45

Chapter Three: This consists of the research methodology and design. The model

specification, sources of data, method of the data analysis, and the decision making criteria.

Chapter Four: In this chapter, the treatment of data presentation was done in addition to

analysing and interpreting the data.

Chapter Five: This embodies the summary of findings, conclusions and recommendations

of the study.

3.2 SOURCES OF DATA.

The sources of data for this research are basically secondary. Data will be obtained from the

United Nations Statistic Department, National Bureau of Statistics, National Planning

Commission, UNICEF, Central Bank of Nigeria annual reports and Millennium Development

Goals reports.

3.3. MODEL SPECIFICATION.

There is need to capture and present the impact which the millennium development goals

have on the human development in the Nigerian economy. This is done by the model

specification. It is a mathematical relationship showing the interrelationship between

economic variables; dependent and independent. It specifies the model to be tested in order to

determine the impact of the MDGs on human development. This is functionally expressed as:

Y= f(X1 X2)

The specified form of the model is

HDI= f (MDG1 MDG2 MDG3 MDG4 MDG5 MDG6 MDG7 MDG8).

Economic model is expressed as:

46

HDI=a0+ a1MDG1+ a2MDG2+ a3MDG3 +a4MDG4 +a5MDG5 +a6MDG6 + a7MDG7

+a8MDG8.

The econometrics model is expressed as:

HDI=a0+ a1MDG1+ a2MDG2+ a3MDG3 +a4MDG4 +a5MDG5 +a6MDG6 + a7MDG7

+a8MDG8 + U.

Where;

HDI- Human Development Index, which is the selected macro-economic variable for

measuring development.

MDG1-Prevalence of underweight children under five years of age (%), an indicator for the

measurement of the first millennium development goal.

MDG2- Net enrolment ratio in primary education (%), an indicator for the measurement of the

second millennium development goal.

MDG3-Ratio of girls to boys in tertiary education (girls per 100 boys), an indicator for the

measurement of the third millennium development goal.

MDG4-Infant mortality rate (per 1,000 live births), an indicator for the measurement of the fourth

millennium development goal.

MDG5- Maternal mortality rate (per 100,000 live births), an indicator for the measurement of the

fifth millennium development goal.

MDG6- HIV prevalence among pregnant young women aged 15-24 (%), an indicator for the

measurement of the sixth millennium development goal.

47

MDG7-Proportion of population using an improved sanitation facility (%), an indicator for the

measurement of the seventh millennium development goal.

MDG8- Teledensity, an indicator for the measurement of the eight millennium development

goal.

The eight independent variables above are used in order to encapsulate the eight millennium

development goals.

a0-intercept

a1, a2, a3, a4, a5, a6, a7 & a8-measure of the slope/regression coefficients.

U= Error term/ Stochastic term/ Random variable.

This shows that there exists a functional relationship between the millennium development

goals and human development.

APRIORI EXPECTATION.

HDI=a0+ a1MDG1+ a2MDG2+ a3MDG3 +a4MDG4 +a5MDG5 +a6MDG6 + a7MDG7

+a8MDG8

Where

a1<0, a2>0, a3>0, a4<0, a5 <0, a6<0, a7>0, and a8>0.

This implies that the prevalence of underweight children under five years of age (%), Infant

mortality rate (per 1,000 live births), Maternal mortality rate (per 100,000 live births)and HIV

prevalence among pregnant young women aged 15-24 (%) have negative signs and thus denoting

a negative relationship with human development in the Nigerian economy. On the other hand,

Net enrolment ratio in primary education (%), Ratio of girls to boys in tertiary education (girls per

48

100 boys), Proportion of population using an improved sanitation facility (%) and Teledensity have

positive signs, thus denoting a positive relationship with human development in the Nigerian

economy.

RESTATEMENT OF RESEARCH HYPOTHESIS.

H0: The MDGs have no significant impact on human development in the Nigerian economy.

H1: The MDGs have a significant impact on human development in the Nigerian economy.

Decision Rule for Accepting and Rejecting H0 and H1.

If t calculated < t tabulated

Accept H0 and reject H1.

If t calculated > t tabulated

Accept H1 and reject H0.

3.4. MODEL ESTIMATION TECHNIQUE.

This refers to the method used in analysing the data that has been gathered for the purpose of

this research study. The technique used for analysing the model would be the Ordinary Least

Square method (OLS). The computational software that is used for the specified model is E-

views.

3.5. MODEL EVALUATION TECHNIQUE AND TEST OF RESEARCH

HYPOTHESIS.

49

This deals with the reliability of the results obtained from using the OLS. The evaluation

concerns itself with deciding whether or not the estimates of the parameters are theoretically

meaningful and statistically satisfactory. The student T test, Standard Error, R2, Adjusted R2,

and the F test will be used in evaluating the model.

The student T test will measure the statistical significance of the coefficient in the model at

5% level of significance. The standard error will measure the dispersion of the estimates

around the true parameters. The larger the standard error of the parameter, the less reliable it

is. The reverse holds true. The overall fitness of the model is measured using the coefficient

of determination. R2 and the hypothesis will be jointly testing the F test. R2 will be

operationally useful if it is equal or greater than 0.5. A higher level of R2 denotes a strong

explanatory power of the model and shows the level of the relationship that exists between

the MDGs and human development.

50

REFERENCES

Afolabi G.K, G.N. Okezie (2005). Project writing and supervision. Gold fish publishers.

Asika N. (2000). Research methodology in behaviour sciences. Lagos: Longman Nigeria Plc.

Gujarati, D.N. (2009). Basic econometrics, McGraw hill. 5th Edition.

CHAPTER FOUR

51

DATA PRESENTATION AND ANALYSIS.

4.0 INTRODUCTION

This chapter contains the presentation, analysis and discussions of data obtained from

secondary sources. It seeks to establish the extent to which the MDGs have an impact on

human development.

4.1 DATA PRESENTATION.

Below are the data of all Human Development Index, Prevalence of underweight children

under five years of age(%), Net enrolment ratio in primary education (%), Ratio of girls to

boys in tertiary education (girls per 100 boys), Under-five mortality rate (per live 1,000

births), Maternal mortality rate (per 100,000 live births), HIV prevalence among pregnant

young women aged 15-24 (%),Proportion of population using an improved sanitation facility

(%) and teledensity, all indicators for measurement of the eight MDGs respectively, in

Nigeria, from the millennium-2000 to 2009.

Year Human

Development

Index

Prevalence of

underweight

children under

Net

enrolment

ratio in

Ratio of

girls to

boys in

Under-

five

mortality

Maternal

mortality

rate (per

HIV

prevalence

among

Proportion

of

population

Teledensity

52

five years of

age(%)

primary

education

(%)

tertiary

education

(girls per

100 boys)

rate (per

live

1,000

births)

100,000

live

births)

pregnant

young

women

aged 15-24

(%)

using a

n improved

sanitation

facility (%)

2000 0.468 31 95.0 66 183.75 704 5.4 42.9 0.68

2001 0.468 28.7 95.0 68 183.75 704 5.8 42.9 0.73

2002 0.469 28.7 93.0 87 183.75 704 5.8 49.4 1.89

2003 0.470 28.7 90.0 72 201 800 5.0 49.8 3.35

2004 0.468 30 81.1 75.5 201 800 5.0 38 8.50

2005 0.422 30 84.6 70.1 201 800 4.3 33 16.27

2006 0.43 28 87.9 69.0 201 800 4.3 33 24.18

2007 0.437 25 89.6 66.4 138 800 4.3 42.9 29.98

2008 0.443 23.1 88.8 66.8 157 545 4.2 53.8 45.93

2009 0.448 24 89.1 68.1 160 545 4.2 51.6 45.93

Source:

Human Development index: Trends 2005 – Present UNDP 2004/2005 report UNDP MDG Report 2010.

DISCUSSION OF TABLE 1.

53

The above table shows the values for the dependent and independent variables for a given

period of 10 years.

In 2000, the estimated value of the human development index was 0.468. The value for

Prevalence of underweight children under five years of age(%) was 33 , Net enrolment ratio

in primary education (%) was 95, Ratio of girls to boys in tertiary education (girls per 100

boys) was 66, Under-five mortality rate (per live 1,000 births) was 183.75, Maternal

mortality rate (per 100,000 live births) was 704, HIV prevalence among pregnant young

women aged 15-24 (%) was 5.4, Proportion of population using an improved sanitation

facility (%) was 42.9 and teledensity was 0.68. However, through the years 2001-2004, the

value of the HDI revolved around the same figure until 2005 when it fell drastically to 0.422.

Prevalence of underweight children under five years of age(%) fell to 28.7 and then rose to

30 in 2004. Net enrolment ratio in primary education (%) fell to 81.1 in 2004. Ratio of girls

to boys in tertiary education (girls per 100 boys) rose to 75.5 in 2004. Under-five mortality

rate (per live 1,000 births) was constant through 2001 and 2002 and then rose to 2001 until

2006.

In 2009, HDI was estimated to have increased to 0.448, Prevalence of underweight children

under five years of age(%) fell to 24, Net enrolment ratio in primary education (%) 89.1,

Ratio of girls to boys in tertiary education (girls per 100 boys) was 68.1, Under-five mortality

rate (per live 1,000 births) fell to 160, Maternal mortality rate (per 100,000 live births)

reduced to 545, HIV prevalence among pregnant young women aged 15-24 (%) fell to 4.2,

Proportion of population using an improved sanitation facility (%) increased to 51.6 and there

was a tremendous increase in teledensity to 45.93.

We can see from the trend that there has been remarkable improvement in attempts to meet

the targets. However, more work still needs to be done if we are to achieve these goals by

2015.

54

4.2. DATA ANALYSIS.

Using Econometric Views (E-Views), computer software for empirical statistical analysis, we

estimate the specified model of the functional relationship between the explained variable on

the one hand, and the explanatory variables on the other hand, via the Ordinary Least Squares

(OLS) technique to obtain the result below.

Table 4.2: Regression Analysis Result.

Variable Coefficient Std. Error t-Statistic Prob.

C -0.922739 0.119024 -7.752542 0.0817

MDG1 0.016819 0.001470 11.43844 0.0555

MDG2 -0.001010 0.000195 -5.166817 0.1217

MDG3 -0.001934 0.000132 -14.64776 0.0434

MDG4 0.000370 4.79E-05 7.717613 0.0820

MDG5 0.000373 3.12E-05 11.97269 0.0530

MDG6 0.104166 0.006712 15.51868 0.0410

MDG7 0.004580 0.000261 17.51859 0.0363

MDG8 0.005479 0.000479 11.44288 0.0555

R-squared 0.999444

Adjusted R-squared 0.994993

Durbin-Watson stat 2.969553Prob(F-statistic) 0.05156

where C= a0

From the hypothesis within the model,

HDI=a0+ a1MDG1+ a2MDG2+ a3MDG3 +a4MDG4 +a5MDG5 +a6MDG6 + a7MDG7

+a8MDG8 + U.

55

Where;

HDI- Human Development Index, which is the selected macro-economic variable for human

development.

a0= slope of the regression.

MDG1- Prevalence of underweight children under five years of age (%).

a1= coefficient of the prevalence of underweight children under five years of age (%).

MDG2- Net enrolment ratio in primary education (%)

a2= coefficient of Net enrolment ratio in primary education (%)

MDG3-Ratio of girls to boys in tertiary education (girls per 100 boys).

a3= coefficient of Ratio of girls to boys in tertiary education (girls per 100 boys).

MDG4- Under-five mortality rate (per live 1,000 births).

a4= coefficient of under-five mortality rate (per live 1,000 births).

MDG5- Maternal mortality rate (per 100,000 live births).

a5= coefficient of Maternal mortality rate (per 100,000 live births).

MDG6- HIV prevalence among pregnant young women aged 15-24 (%).

a6= coefficient of HIV prevalence among pregnant young women aged 15-24 (%).

MDG7-Proportion of population using an improved sanitation facility (%).

a7= coefficient of Proportion of population using an improved sanitation facility (%).

MDG8- Teledensity

56

a8= coefficient of teledensity.

U= Random variable.

From the regression analysis carried out on EViews 6

a0= -0.922739

a1= 0.016819

a2= -0.001010

a3= -0.001934

a4= 0.000370

a5=0.000373

a6= 0.104166

a7= 0.004580

a8= 0.005479

Therefore the model can now be written as:

HD1= -0.922739 + 0.016819MDG1- 0.001010MDG2 -0.001934MDG3 + 0.000370MDG4 +

0.000373MDG5 + 0.104166MDG6 + 0.004580MDG7 + 0.005479MDG8 + e

DISCUSSION OF TABLE 4.2.

From the derived model for the hypothesis, the slope is -0.922739.

57

The coefficient a1 (a1=0.016819) shows a positive relationship between the prevalence of

underweight children under five years of age (%) and Human Development Index, implying

that a unit increase in the prevalence of underweight children would induce an infinitesimal

increase of about 0.017units in the value of the Human Development Index, and vice-versa.

However, this positive relationship is not consistent with our a priori expectation as earlier

stated.

The coefficient a2 ( a2= -0.001010) shows a negative relationship between the net enrolment

ratio in primary education (%) and the Human Development Index. This implies that a unit

increase in the percentage of net enrolment ratio in primary education would cause a

corresponding decrease in the Human Development Index by about 0.001 units and vice-

versa. This relationship is not consistent with the earlier stated a priori expectation.

The coefficient a3 (a3= -0.001934) shows a negative relationship between the Human

Development Index and the ratio of girls to boys in tertiary education (girls per 100 boys).

This implies that a unit increase in the ratio of girls per 100 boys in tertiary education would

lead to a decrease in Human Development Index by about 0.002 units, and vice-versa. This

negative relationship is inconsistent with the a priori expectation.

The coefficient a4 (a4= 0.000370) shows a positive relationship between Infant mortality rate

(per 1,000 live births) and human development. That is, as the rate of infant mortality

increases, human development increases. This too, is inconsistent with the a priori

expectation.

The coefficient a5 (a5=0.000373) shows a positive relationship between maternal mortality

rate (per 100,000 live births) and human development index. A unit increase in maternal

mortality rate will cause a corresponding increase in human development index by about

0.0004 units, and vice-versa. This relationship is not consistent with the a priori expectation.

58

The coefficient a6 (a6= 0.104166) shows a positive relationship between HIV prevalence

among pregnant young women aged 15-24 (%) and human development index. This implies

that a unit increase in the prevalence of HIV among pregnant young woman would lead to a

corresponding increase in human development index by about 0.104%. This relationship as

well, is inconsistent with the a priori expectation.

The coefficient a7 (a7=0.004580) indicates a positive relationship between proportion of

population using an improved sanitation facility (%) and human development index. This

implies that an increase in the number of people who use an improved sanitation facility will

lead to a corresponding increase in the human development index. This relationship is

consistent with the a priori expectation.

The coefficient a8 (a8=0.005479) indicates a positive relationship between teledensity and

human development index. This implies that an increase in the number of people who have

access to telephones will lead to a corresponding increase in the human development index.

This relationship follows from the a priori expectation.

GRAPHS SHOWING CORELLATION BETWEEN HUMAN DEVELOPMENT AND THE

MDGs.

HDI Positive Correlation

59

0

MDG1 MDG4 MDG5 MDG6 MDG 7 MDG8

Negative Correlation

HDI

0 MDG2 MDG3

4.3 DATA INTERPRETATION.

The data was analysed, estimated and interpreted with the aid of the multiple regression

technique, and the Econometrics views (E-views) statistical tool.

In the model, the intercept a0 shows the value of the HDI when the values of the independent

variables are indeterminate or when they are zero.

The R2 measures the changes in the dependent variables that occur as a result of the variations

in the independent variables. The coefficient of determination R is such that 0≤R≤1and

denotes the strength of the linear relationship between the variables.

60

From the generated result, R2 =0.999444. This means that 99.9% of the variations in HDI can

be explained by MDG1, MDG2, MDG3, MDG4, MDG6, MDG7 and MDG8. More

specifically, it implies that, in Nigeria, from the year 2000 to 2009, changes in the values of

Human Development Index is accounted for by changes in Prevalence of underweight

children under five years of age (%), Net enrolment ratio in primary education (%),Ratio of

girls to boys in tertiary education (girls per 100 boys) Under-five mortality rate (per live

1,000 births). Maternal mortality rate (per 100,000 live births), HIV prevalence among

pregnant young women aged 15-24 (%), Proportion of population using an improved

sanitation facility (%), and Teledensity, 99.9% of the time. The remaining 0.1% is explained

by the other variables which are not included in the model and are covered by the stochastic

error term U.

The adjusted R2 is often used because the R2 tends to give an overtly optimistic picture of the

fit of regression especially when the number of explanatory variables is large compared with

the number of observations. From the regression results, Adjusted R2 is given as 0.994993

which is a reaffirmation that a significant percentage of about 99.4% of the variation in HDI

is as a result of changes in Prevalence of underweight children under five years of age (%),

Net enrolment ratio in primary education (%),Ratio of girls to boys in tertiary education (girls

per 100 boys) Under-five mortality rate (per live 1,000 births). Maternal mortality rate (per

100,000 live births), HIV prevalence among pregnant young women aged 15-24 (%),

Proportion of population using an improved sanitation facility (%), and Teledensity.

The student t test method is used in testing the hypothesis of the research work.

Decision Rule

If t cal (tc) > t tab (tb) : Accept H1 and Reject H0

61

If t cal (tc) < t tab (tb) : Accept H0 and Reject H1

Using the t distribution table to test the result at 5% significance level and degree of freedom

df=n-k.

Where n= number of observations.

K= number of parameters.

Therefore, df=10-9=1

From the t distribution table, t tab =4.303.

Coefficient tcal < or > ttab Probability.

a1 -7.752542 Less than 12.706 0.0817

a2 11.43844 Less than 12.706 0.0555

a3 -5.166817 Less than 12.706 0.1217

a4 -14.64776 Less than 12.706 0.0434

a5 7.717613 Less than 12.706 0.0820

a6 11.97269 Less than 12.706 0.0530

a7 15.51868 Greater than 12.706 0.0410

a8 17.51859 Greater than 12.706 0.0363

Note: it was tested at 5% level of significance, with df=n-k.

From the above table, it can be seen that tcal < ttab value for a1, a2, a3, a4, a5,and a6 but tcal > ttab for

values of a7 and a8. Based on the decision rule, we can infer that the independent variables

MDG1, MDG2, MDG3, MDG4, MDG5 and MDG6 have no statistically significant impact

on human development in Nigeria, whereas MDG7 and MDG8 have a statistically significant

impact on human development in Nigeria.

62

Based on the above t statistics; we accept the null hypothesis H0 and reject the alternative

hypothesis H1, for MDGs 1-6 ascertaining that the MDGs have no significant impact on

human development in the Nigerian economy and we accept the alternative hypothesis for

MDGs 7 and 8.

DETERMINATION OF STATISTICAL SIGNIFICANCE

To determine if in the model a relationship exists between of MDG1 MDG2 MDG3 MDG4

MDG5 MDG6 MDG7 and MDG8 and Human Development in the Nigerian economy from

2000 to 2009, the standard error test will be utilized. The standard error is used to provide the

reliability of the result.

Decision Rule:

If the standard error of an explanatory variable in the model is less than half the value of its

coefficient in absolute terms, then we reject H0 and accept H1.

H0: The MDGs have no significant impact on human development in the Nigerian economy.

H1: The MDGs have a significant impact on human development in the Nigerian economy.

SE(a1 ) < a1/2 ; Accept H1 and Reject H0.

SE(a2 ) < a2/2 ; Accept H1 and Reject H0.

SE(a3 ) < a3/2 ; Accept H1 and Reject H0.

SE(a4 ) < a4/2 ; Accept H1 and Reject H0.

SE(a5 ) < a5/2 ; Accept H1 and Reject H0.

SE(a6 ) < a6/2 ; Accept H1 and Reject H0.

SE(a7 ) < a8/2 ; Accept H1 and Reject H0.

63

SE(a8 ) < a8/2 ; Accept H1 and Reject H0.

Coefficient Standard Error < or > Coefficient/2

a1 0.001470 Less than 0.016819/2=0.0084095

a2 0.000195 Less than -0.001010/2=0.000505

a3 0.000132 Less than -0.001934/2=0.000967

a4 4.79E-05 Greater than 0.000370/2=0.000185

a5 3.12E-05 Greater than 0.000373/2=0.0001865

a6 0.006712 Less than 0.104166/2=0.052083

a7 0.000261 Less than 0.004580/2=0.00229

a8 0.000479 Less than 0.005479/2=0.0027395

From the table above, the standard error of MDG1 is 0.001470 is less than half of its

coefficient (i.e. 0.016819/2=0.0084095), therefore, the effect of the prevalence of

underweight children under five years of age (%) has a significant impact on human

development in the Nigeria economy from 2000 to 2009.

Also, the standard error of MDG2 is 0.000195 is less than half of its coefficient (i.e. -

0.001010/2=0.000505), therefore, Net enrolment ratio in primary education (%) has a

significant impact on human development in the Nigerian economy from 2000 to 2009.

The standard error of MDG3 is 0.000132 which is less than half of its coefficient (-

0.001934/2=0.000967), therefore, Ratio of girls to boys in tertiary education (girls per 100

boys) has a significant impact on human development in the Nigerian economy from 2000 to

2009.

64

The standard error of MDG4 is 4.79E-05 which is greater than half of its coefficient (i.e.

0.000370/2=0.000185), therefore Under-five mortality rate (per live 1,000 births) has no

significant impact on human development in the Nigerian economy from 2000 to 2009.

Also, the standard error of MDG5 is 3.12E-05 which is greater than half of its coefficient

(0.000373/2=0.0001865), therefore, maternal mortality rate (per 100,000 live births) has no

significant impact on human development in the Nigerian economy from 2000 to 2009.

Also, the standard error of MDG6 is 0.006712 which is less than half of its coefficient

0.104166/2=0.052083), therefore, HIV prevalence among pregnant young women aged 15-

24 (%) has a significant impact on human development in the Nigerian economy from 2000

to 2009.

The standard error of MDG7 is 0.000261 which is less than half of its coefficient (i.e.

0.004580/2=0.00229), therefore, Proportion of population using an improved sanitation

facility (%) has a significant impact on human development in the Nigerian economy from

2000 to 2009.

Lastly, the standard error of MDG8 is 0.000479 which is less than half of its coefficient (i.e.

0.005479/2=0.0027395), therefore, teledensity has a significant impact on human

development in the Nigerian economy from 2000 to 2009.

DETERMINATION OF JOINT STATISTICAL SIGNIFICANCE

F-statistics will be used to determine if the effects of MDG1, MDG2, MDG3, MDG4,

MDG5, MDG6, MDG7 and MDG8 have a joint statistical significance on Human

Development Index from 2000 to 2009.

Decision Rule:

65

If the value of Fcalculated is greater than the value of Ftabulated, then the effect of MDG1, MDG2,

MDG3, MDG4, MDG5, MDG6, MDG7 and MDG8 on Human Development Index has joint

statistical significance otherwise, their overall effect is statistically insignificant.

H0: The MDGs have no significant impact on human development in the Nigerian economy.

H1: The MDGs have a significant impact on human development in the Nigerian economy.

Degree of freedom for the numerator = K – 1, where, K = number of parameters.

K – 1 = 9 – 1= 8

Degree of freedom for the denominator = N – K, where, N = number of observations.

N – K= 10 – 9 = 1

Therefore, Ftabulated = 239 (at 5% level of significance).

Ftabulated = 59.4 (at 10% level of significance)

From the Eviews 6 regression results, the value of Fcalculated is 224.5697 and it is less than the

value of Ftabulated at 5% level of significance and K – 1, N – K degree of freedom. However,

the value of Fcalculated is 224.5697 and it is greater than the value of Ftabulated which is 59.4 at

10% level of significance and K – 1, N – K degree of freedom. Therefore, we accept H1, that

is, The MDGs have a joint or overall statistical significance on human development index in

Nigeria for the period of 2000- 2009.

Also, because the Fcal is greater than 100, we conclude that the F value is highly statistically

significant, suggesting that, not only individually, but also collectively, all the explanatory

variables have a significant impact on human development index.

AUGMENTED DICKEY – FULLER UNIT ROOT TEST

66

The result of the unit root test in the time series variables using the Augmented Dickey-Fuller

test developed by Dickey and Fuller in 1979 is presented in the table below:

Level 1st Difference 2nd Difference

Tcalculated Tcalculated Tcalculated

Variable Intercept

Trend and Intercept Intercept

Trend and Intercept Intercept

Trend and Intercept

HDI-

1.434813 -1.601690-

2.665921 -2.533282-

3.738123 -3.445005

MDG1-

1.239602 -4.311711-

2.355082 -1.311563-

1.465013 -0.821566

MDG2-

1.671901 -1.246626-

2.188293 -2.400252-

3.165844 -2.829456

MDG3-

2.529205 -7.612141-

4.168896 -4.192716-

7.648552 -21.25075

MDG4-

1.441230 -1.944311-

3.215685 -2.813724-

2.898362 -2.117129

MDG5-

0.794232 -0.970602-

2.560922 -3.722332-

4.474348 -2.707246

MDG6-

0.732617 -2.369252-

3.590570 -3.347784-

4.476372 -4.698574

MDG7-

3.673911 -3.805631-

2.950309 -3.182150-

1.886968 -1.060399

MDG8 1.358477 -1.397566-

0.683138 -6.045963-

7.074970 -5.842659

Decision Rule:

67

If the Tcalculated > Ttabulated in absolute terms for any variable at any specified level of

significance (1%, 5% or 10%), then the time series values of that particular variable is non-

stationary, otherwise, the time series variable is stationary.

From the Eviews 6 Augmented Dickey-Fuller test, the unit root test results reveals:

Human Development Index is stationary at intercept at level, trend and intercept at

level, intercept at first difference, trend and intercept at first difference and trend at

intercept at second difference at 1%, 5% and 10% levels of significance.

MDG1 is stationary at intercept at level, at intercept at first difference, trend and

intercept at first difference, intercept at second difference, trend at intercept at second

difference, at all levels of significance of 1%, 5% and 10% and at trend at intercept at

level at 1% and 5% levels of significance.

MDG2 is stationary at intercept at level, trend at intercept at level, intercept at first

difference, trend and intercept at first difference, trend at intercept at second

difference at all three levels of significance of 1%, 5% and 10%.

MDG3 is stationary at intercept at level, intercept at second difference, at all three

levels of significance of 1%, 5% and 10%. trend and intercept at first difference at 1%

level of significance, trend at intercept at 1% and 5% levels of significance.

MDG4 is stationary at intercept at level, trend at intercept at level, trend and intercept

at first difference, intercept at second difference, trend and intercept at second

difference at all three levels of significance of 1%, 5% and 10%, at intercept at first

difference at 1% level of significance.

MDG5 is stationary at intercept at level, trend at intercept at level, intercept at first

difference, , trend at intercept at second difference at all three levels of significance of

68

1%, 5% and 10%, trend and intercept at first difference at 1% and 5% level of

significance, intercept at second difference at 1% level of significance.

MDG6 is stationary at intercept at level, trend at intercept at level, intercept at first

difference, levels of significance of 1%, 5% and 10%, trend and intercept at first

difference at 1% level of significance, intercept at second difference at 1% level of

significance, trend at intercept at second difference at 1% and 10% levels of

significance.

MDG7 is stationary at intercept at level at 1% level of significance, trend at intercept

at level at 1% and 10% levels of significance, intercept at first difference at 1% and

10% levels of significance, trend and intercept at first difference, intercept at second

difference, trend at intercept at second difference, at all three levels of significance of

1%, 5% and 10%.

MDG8 is stationary at intercept at level, trend at intercept at level, intercept at first

difference, at all three levels of significance of 1%, 5% and 10% and trend at intercept

at second difference at 1% level of significance.

69

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS.

5.0 INTRODUCTION

This chapter deals with the summary, conclusions and recommendations of this research

work. This study was an attempt to identify the relationship that exists between the

millennium development goals and human development in the Nigerian economy from 2000

to 2009. The main objective was to establish the degree of impact which the MDGs have on

the Nigerian Human Development Index. Hence, a model was formulated to link the human

development index and the eight millennium development goals viz: Prevalence of

underweight children under five years of age, Net enrolment ratio in primary education (%),

Ratio of girls to boys in tertiary education (girls per 100 boys), Under-five mortality rate (per

70

live 1,000 births), Maternal mortality rate (per 100,000 live births), HIV prevalence among

pregnant young women aged 15-24 (%), Proportion of population using an improved

sanitation facility (%) and teledensity. The data collected for these variables were subjected

to regression analysis with the ordinary least squares technique. The software employed was

Eviews 6.

5.1 SUMMARY OF FINDINGS

From the relevant data collected through secondary sources, the following findings emerged:

Looking at many indicators for measuring progress towards the MDGs, Nigeria is not

anywhere near achieving the MDGs. The Maternal Mortality Ratio (MMR) in Nigeria

is still scandalously high. Nigeria still occupies an unenviable position in the "league

table" of the countries with those living with HIV/AIDS (PLWHA). Life expectancy

in Nigeria has drastically reduced to 45; real income of most families has woefully

reduced; unemployment is gone overboard. Nigeria is topping the list of countries

with malnourished children; Nigeria's literacy rate is still low. Nigeria is ranked as the

20th hungriest country on the Global Hunger Index (GHI); Nigeria is pitiably named

among the countries with the highest number of illiterates. The various Human

Development Index (HDI) reports continue to place Nigeria on the last rung of the

global development ladder.

There indeed exists a positive relationship between the millennium development goals

and the human development index. Achieving these goals by 2015 will help Nigeria

to increase her development index and invariably lift her up the HDI ladder in

comparison with other countries.

Some of the MDG indicators exhibit outright insignificance, and unless

allowance is given to a low probability of significance as we did they would not have

71

been included. For example, the prevalence of underweight children, indicator for the

goal of eradicating poverty and extreme hunger. HDI takes into consideration life

expectancy. An underweight person is more likely to be fit and so live longer than an

obese or overweight person. This explains the existence of a positive relationship,

inconsistent with our a priori expectations.

The model revealed that 99% of the variations in HDI are explained by the linear

relationship.

One can argue that HDI is only a statistical calculation but it is equally true that there

is an underlying relationship of true human development identified that must be

encouraged by policy and practice.

5.2. CONCLUSION.

The Millennium Development Goals are crucial to Nigeria’s social, economic and human

development, especially at this time when we have about three years to 2015. It is clear that

Nigeria will not achieve the MDGs by 2015. Even though, the MDGs are not going to be met,

that is not without progress as there have been tremendous improvements in the economy.

This work is limited to eight MDG indicators that stand as the surrogate of the eight goals

and eighteen targets. Further research direction should focus on exploring the entire forty-

eight indicators of the country. HDI is too important to be under-rated in government policies

and consensus must be sought to bring the development system to reason together on it.

Multiple variable indices provide a better guide to development policies and decisions.

Government cannot just look at HDI yearly and endorse it, it must do so with concern, asking

itself and the agencies how it can do better. The greatest challenge facing our government is

72

to improve the appalling human conditions and the standard of living in Nigeria. Human

development is the epicentre of all developments. Human beings are the wealth of a nation.

5.3 RECOMMENDATIONS.

Having analysed the impact of the Millennium Development Goals on Human development

in the Nigerian economy, the following recommendations have been proffered:

There exists the need for governments and civil society to intensify efforts in

achieving these goals, as 2015 is now just a few years away and as some of these

goals will bring about human development. The administration should initiate, fine-

tune or galvanize concrete recoverable programs and projects aimed at putting Nigeria

on the track to achieving the MDGs. Adjustments in respect of official development

assistances, funding from governments, non-governmental organizations, private

sector and international organizations is tremendously needed to follow up the MDG

targets. Again, strategic planning and effective implementation to the latter is needed.

The situation in Nigeria indicates that there are challenges in meeting the goals by

2015. For Nigeria to meet the goals in 2015, there is the need to formulate and

implement policies that will promote transparency and accountability; overcome

institutional constraints; promote pro-poor growth; bring about structural change;

enhance distributive equity; engender social and cultural re-orientation; engineer

political transformation; practice inclusive urban development; generate employment

and transform power relations.

Government will need to convince itself that single issue parameters like GDP and its

derivatives as a basis for decision making will lead a nation nowhere as evidence

continue to show.

73

Nigeria cannot sustainably establish stability and economic growth while its people

lack fundamental health services. The government should provide increased access to

quality family planning and reproductive health services. Maternal and child health

efforts should focus on routine immunization, polio eradication, birth preparedness,

maternity services, and obstetric fistula repairs. With regards to the increase in the

number of people that die from malaria, the government should increase access to

proven preventive and curative interventions-insecticide-treated bed nets, net re-

treatment kits, and malaria treatment for children and pregnant women. There should

be increased awareness of HIV/AIDS and available treatments for those who already

have it.

In education, government should support equitable access to quality basic education

through teacher training, support for girls' learning, infrastructure improvement, and

community involvement, focusing on public schools, as well as schools, which

provide both secular and religious education. Higher education partnerships between

Nigerian universities and other foreign universities should also be developed.

The Nigerian economy has the tendency to be a green economy and structurally

transformed if MDGs are given serious considerations. The government should look

into this and formulate policies and also ensure a transparent implementation. They

should also formulate policies that comply with international safety, health and

environmental standards as they relate to specific industries and sectors of the

economy.

Telecommunications should be made available to Nigerians regardless of where they

live. Telephone density should be increased with a fewer number of people assigned

to one. Internet facilities should also be made available.

74

Should these strategies be put in place and the various problems earlier stated in this

research study be solved, Nigeria would be a country with high human development in

the not so distant future.

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APPENDIX

Year Human

Development

Index

Prevalence of

underweight

children under

five years of

age(%)

Net

enrolment

ratio in

primary

education

(%)

Ratio of

girls to

boys in

tertiary

education

(girls per

100 boys)

Under-

five

mortality

rate (per

live

1,000

births)

Maternal

mortality

rate (per

100,000

live

births)

HIV

prevalence

among

pregnant

young

women

aged 15-24

(%)

Proportion

of

population

using a

n improved

sanitation

facility (%)

Teledensity

2000 0.468 31 95.0 66 183.75 704 5.4 42.9 0.68

2001 0.468 28.7 95.0 68 183.75 704 5.8 42.9 0.73

2002 0.469 28.7 93.0 87 183.75 704 5.8 49.4 1.89

78

2003 0.470 28.7 90.0 72 201 800 5.0 49.8 3.35

2004 0.468 30 81.1 75.5 201 800 5.0 38 8.50

2005 0.422 30 84.6 70.1 201 800 4.3 33 16.27

2006 0.43 28 87.9 69.0 201 800 4.3 33 24.18

2007 0.437 25 89.6 66.4 138 800 4.3 42.9 29.98

2008 0.443 23.1 88.8 66.8 157 545 4.2 53.8 45.93

2009 0.448 24 89.1 68.1 160 545 4.2 51.6 45.93

Sources: Human Development index: Trends 2005-Present UNDP2004/2005 report UNDPMDG Report 2010.REGRESSION ANALYSIS RESULT.

Dependent Variable: HDI

Method: Least Squares

Date: 03/20/12 Time: 18:11

Sample: 2000 2010

Included observations: 11

Variable Coefficient Std. Error t-Statistic Prob.

C -0.970040 0.737048 -1.316115 0.3187

MDG1 0.012809 0.006263 2.045315 0.1775

MDG2 0.001713 0.002184 0.784163 0.5151

MDG3 -0.000813 0.000593 -1.371457 0.3038

MDG4 0.001013 0.000985 1.028747 0.4117

79

MDG5 0.000336 0.000171 1.969773 0.1877

MDG6 0.101689 0.040646 2.501835 0.1295

MDG7 0.001286 0.000600 2.144312 0.1652

MDG8 0.005452 0.002823 1.931463 0.1932

R-squared 0.961903    Mean dependent var 0.452364

Adjusted R-squared 0.809517    S.D. dependent var 0.017569

S.E. of regression 0.007668    Akaike info criterion -6.971987

Sum squared resid 0.000118    Schwarz criterion -6.646437

Log likelihood 47.34593    Hannan-Quinn criter. -7.177202

F-statistic 6.312265    Durbin-Watson stat 2.969553

Prob(F-statistic) 0.143897

UNIT ROOT TEST FOR HDI

INTERCEPT AT LEVEL

Null Hypothesis: HDI has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.434813  0.5181Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test Equation

80

Dependent Variable: D(HDI)Method: Least SquaresDate: 03/26/12 Time: 16:31Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

HDI(-1) -0.408554 0.284744 -1.434813 0.1945C 0.182762 0.129033 1.416400 0.1996

R-squared 0.227261    Mean dependent var -0.002222Adjusted R-squared 0.116870    S.D. dependent var 0.016776S.E. of regression 0.015766    Akaike info criterion -5.268851Sum squared resid 0.001740    Schwarz criterion -5.225023Log likelihood 25.70983    Hannan-Quinn criter. -5.363431F-statistic 2.058687    Durbin-Watson stat 1.877541Prob(F-statistic) 0.194470

TREND AND INTERCEPT AT LEVEL

Null Hypothesis: HDI has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.601690  0.7108Test critical values: 1% level -5.521860

5% level -4.10783310% level -3.515047

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(HDI)Method: Least SquaresDate: 03/26/12 Time: 16:32Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

HDI(-1) -0.693222 0.432807 -1.601690 0.1603C 0.325331 0.207797 1.565624 0.1685

@TREND(2000) -0.002736 0.003094 -0.884269 0.4106

R-squared 0.316355    Mean dependent var -0.002222Adjusted R-squared 0.088473    S.D. dependent var 0.016776S.E. of regression 0.016017    Akaike info criterion -5.169131Sum squared resid 0.001539    Schwarz criterion -5.103390Log likelihood 26.26109    Hannan-Quinn criter. -5.311001F-statistic 1.388243    Durbin-Watson stat 1.684932Prob(F-statistic) 0.319515

81

INTERCEPT AT 1ST DIFFERENCE

Null Hypothesis: D(HDI) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.665921  0.1200Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(HDI,2)Method: Least SquaresDate: 03/26/12 Time: 16:33Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(HDI(-1)) -1.096449 0.411283 -2.665921 0.0372C -0.002801 0.006930 -0.404269 0.7000

R-squared 0.542234    Mean dependent var 0.000625Adjusted R-squared 0.465940    S.D. dependent var 0.026354S.E. of regression 0.019260    Akaike info criterion -4.849293Sum squared resid 0.002226    Schwarz criterion -4.829432Log likelihood 21.39717    Hannan-Quinn criter. -4.983243F-statistic 7.107133    Durbin-Watson stat 2.006808Prob(F-statistic) 0.037229

TREND AND INTERCEPT AT 1ST DIFFERENCE

Null Hypothesis: D(HDI) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.533282  0.3135Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

82

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(HDI,2)Method: Least SquaresDate: 03/26/12 Time: 16:34Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(HDI(-1)) -1.115021 0.440149 -2.533282 0.0523C -0.012002 0.019092 -0.628649 0.5572

@TREND(2000) 0.001662 0.003180 0.522680 0.6235

R-squared 0.565950    Mean dependent var 0.000625Adjusted R-squared 0.392330    S.D. dependent var 0.026354S.E. of regression 0.020544    Akaike info criterion -4.652491Sum squared resid 0.002110    Schwarz criterion -4.622701Log likelihood 21.60996    Hannan-Quinn criter. -4.853417F-statistic 3.259706    Durbin-Watson stat 2.086874Prob(F-statistic) 0.124122

INTERCEPT AT 2ND DIFFERENCE

Null Hypothesis: D(HDI,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.738123  0.0335Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(HDI,3)Method: Least SquaresDate: 03/26/12 Time: 16:35Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(HDI(-1),2) -1.473245 0.394114 -3.738123 0.0135C 0.000977 0.010389 0.094049 0.9287

R-squared 0.736475    Mean dependent var -0.000286Adjusted R-squared 0.683770    S.D. dependent var 0.048853S.E. of regression 0.027472    Akaike info criterion -4.116351

83

Sum squared resid 0.003774    Schwarz criterion -4.131805Log likelihood 16.40723    Hannan-Quinn criter. -4.307363F-statistic 13.97356    Durbin-Watson stat 2.316351Prob(F-statistic) 0.013458

TREND AND INTERCEPT AT 2ND DIFFERENCE

Null Hypothesis: D(HDI,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.445005  0.1317Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(HDI,3)Method: Least SquaresDate: 03/26/12 Time: 16:36Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(HDI(-1),2) -1.497879 0.434797 -3.445005 0.0262C -0.013658 0.036148 -0.377843 0.7247

@TREND(2000) 0.002443 0.005728 0.426480 0.6917

R-squared 0.747937    Mean dependent var -0.000286Adjusted R-squared 0.621905    S.D. dependent var 0.048853S.E. of regression 0.030039    Akaike info criterion -3.875104Sum squared resid 0.003609    Schwarz criterion -3.898286Log likelihood 16.56287    Hannan-Quinn criter. -4.161622F-statistic 5.934524    Durbin-Watson stat 2.402511Prob(F-statistic) 0.063536

UNIT ROOT TEST FOR MDG1

INTERCEPT AT LEVEL

Null Hypothesis: MDG1 has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.239602  0.5999Test critical values: 1% level -4.582648

5% level -3.320969

84

10% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1)Method: Least SquaresDate: 03/26/12 Time: 16:37Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG1(-1) -0.388609 0.313495 -1.239602 0.2701D(MDG1(-1)) 0.770052 0.511763 1.504704 0.1927

C 10.96655 9.073812 1.208593 0.2809

R-squared 0.319857    Mean dependent var -0.587500Adjusted R-squared 0.047800    S.D. dependent var 1.528246S.E. of regression 1.491274    Akaike info criterion 3.917134Sum squared resid 11.11948    Schwarz criterion 3.946925Log likelihood -12.66854    Hannan-Quinn criter. 3.716209F-statistic 1.175699    Durbin-Watson stat 0.996204Prob(F-statistic) 0.381505

TREND AND INTERCEPT AT LEVEL

Null Hypothesis: MDG1 has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.311711  0.0474Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1)Method: Least SquaresDate: 03/26/12 Time: 16:38Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG1(-1) -0.946478 0.219513 -4.311711 0.0125D(MDG1(-1)) 0.980598 0.272147 3.603193 0.0227

C 30.30827 6.943857 4.364761 0.0120@TREND(2000) -0.661639 0.174085 -3.800661 0.0191

85

R-squared 0.852504    Mean dependent var -0.587500Adjusted R-squared 0.741882    S.D. dependent var 1.528246S.E. of regression 0.776431    Akaike info criterion 2.638634Sum squared resid 2.411379    Schwarz criterion 2.678355Log likelihood -6.554538    Hannan-Quinn criter. 2.370734F-statistic 7.706445    Durbin-Watson stat 3.020026Prob(F-statistic) 0.038726

INTERCEPT AT 1ST DIFFERENCE

Null Hypothesis: D(MDG1) has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.355082  0.1818Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1,2)Method: Least SquaresDate: 03/26/12 Time: 16:38Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG1(-1)) -0.928921 0.394432 -2.355082 0.0781D(MDG1(-1),2) 0.758336 0.380416 1.993437 0.1170

C -0.657899 0.584966 -1.124678 0.3236

R-squared 0.619129    Mean dependent var 0.128571Adjusted R-squared 0.428693    S.D. dependent var 1.698739S.E. of regression 1.283990    Akaike info criterion 3.635348Sum squared resid 6.594516    Schwarz criterion 3.612167Log likelihood -9.723719    Hannan-Quinn criter. 3.348831F-statistic 3.251116    Durbin-Watson stat 2.499007Prob(F-statistic) 0.145063

TREND AND INTERCEPT AT 1ST DIFFERENCE

Null Hypothesis: D(MDG1) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.311563  0.7941

86

Test critical values: 1% level -6.2920575% level -4.450425

10% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1,2)Method: Least SquaresDate: 03/26/12 Time: 16:39Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG1(-1)) -0.830001 0.632833 -1.311563 0.2810D(MDG1(-1),2) 0.770111 0.438848 1.754849 0.1776

C -1.158860 2.342372 -0.494738 0.6547@TREND(2000) 0.096571 0.432680 0.223192 0.8377

R-squared 0.625350    Mean dependent var 0.128571Adjusted R-squared 0.250699    S.D. dependent var 1.698739S.E. of regression 1.470465    Akaike info criterion 3.904594Sum squared resid 6.486804    Schwarz criterion 3.873685Log likelihood -9.666079    Hannan-Quinn criter. 3.522571F-statistic 1.669155    Durbin-Watson stat 2.580778Prob(F-statistic) 0.342088

INTERCEPT AT 2ND DIFFERENCE

Null Hypothesis: D(MDG1,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.465013  0.4910Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1,3)Method: Least SquaresDate: 03/26/12 Time: 16:40Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG1(-1),2) -0.674327 0.460287 -1.465013 0.2028

87

C 0.109962 0.671091 0.163855 0.8763

R-squared 0.300334    Mean dependent var 0.071429Adjusted R-squared 0.160400    S.D. dependent var 1.936246S.E. of regression 1.774175    Akaike info criterion 4.219505Sum squared resid 15.73849    Schwarz criterion 4.204051Log likelihood -12.76827    Hannan-Quinn criter. 4.028493F-statistic 2.146264    Durbin-Watson stat 1.210377Prob(F-statistic) 0.202808

TREND AND INTERCEPT AT 2ND DIFFERENCE

Null Hypothesis: D(MDG1,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -0.821566  0.8952Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG1,3)Method: Least SquaresDate: 03/26/12 Time: 16:41Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG1(-1),2) -0.378396 0.460579 -0.821566 0.4575C -2.871008 2.112727 -1.358911 0.2458

@TREND(2000) 0.494010 0.335500 1.472457 0.2149

R-squared 0.546270    Mean dependent var 0.071429Adjusted R-squared 0.319405    S.D. dependent var 1.936246S.E. of regression 1.597367    Akaike info criterion 4.072118Sum squared resid 10.20633    Schwarz criterion 4.048936Log likelihood -11.25241    Hannan-Quinn criter. 3.785600F-statistic 2.407909    Durbin-Watson stat 2.181726Prob(F-statistic) 0.205871

UNIT ROOT TEST FOR MDG2

INTERCEPT AT LEVEL

Null Hypothesis: MDG2 has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

88

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.671901  0.4111Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2)Method: Least SquaresDate: 03/26/12 Time: 16:48Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG2(-1) -0.438785 0.262447 -1.671901 0.1385C 38.59137 23.50222 1.642031 0.1446

R-squared 0.285368    Mean dependent var -0.655556Adjusted R-squared 0.183278    S.D. dependent var 3.793122S.E. of regression 3.427946    Akaike info criterion 5.494930Sum squared resid 82.25572    Schwarz criterion 5.538758Log likelihood -22.72718    Hannan-Quinn criter. 5.400350F-statistic 2.795253    Durbin-Watson stat 1.668065Prob(F-statistic) 0.138465

TREND AND INTERCEPT AT LEVEL

Null Hypothesis: MDG2 has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.246626  0.8301Test critical values: 1% level -5.521860

5% level -4.10783310% level -3.515047

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2)Method: Least SquaresDate: 03/26/12 Time: 16:49Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

89

MDG2(-1) -0.426192 0.341876 -1.246626 0.2590C 37.27516 32.30356 1.153902 0.2924

@TREND(2000) 0.037959 0.576482 0.065846 0.9496

R-squared 0.285884    Mean dependent var -0.655556Adjusted R-squared 0.047846    S.D. dependent var 3.793122S.E. of regression 3.701268    Akaike info criterion 5.716430Sum squared resid 82.19632    Schwarz criterion 5.782171Log likelihood -22.72393    Hannan-Quinn criter. 5.574560F-statistic 1.200999    Durbin-Watson stat 1.687004Prob(F-statistic) 0.364172

INTERCEPT AT 1ST DIFF

Null Hypothesis: D(MDG2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.188293  0.2223Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2,2)Method: Least SquaresDate: 03/26/12 Time: 16:50Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG2(-1)) -0.890094 0.406753 -2.188293 0.0712C -0.652323 1.567978 -0.416028 0.6919

R-squared 0.443859    Mean dependent var 0.037500Adjusted R-squared 0.351168    S.D. dependent var 5.393366S.E. of regression 4.344360    Akaike info criterion 5.987952Sum squared resid 113.2408    Schwarz criterion 6.007812Log likelihood -21.95181    Hannan-Quinn criter. 5.854002F-statistic 4.788624    Durbin-Watson stat 1.912915Prob(F-statistic) 0.071242

TREND AND INTERCEPT AT 1ST DIFFERENCE

Null Hypothesis: D(MDG2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

90

Augmented Dickey-Fuller test statistic -2.400252  0.3552Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2,2)Method: Least SquaresDate: 03/26/12 Time: 16:51Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG2(-1)) -1.028368 0.428442 -2.400252 0.0616C -4.685036 4.285558 -1.093215 0.3241

@TREND(2000) 0.713736 0.706094 1.010824 0.3585

R-squared 0.538224    Mean dependent var 0.037500Adjusted R-squared 0.353514    S.D. dependent var 5.393366S.E. of regression 4.336502    Akaike info criterion 6.052009Sum squared resid 94.02625    Schwarz criterion 6.081800Log likelihood -21.20804    Hannan-Quinn criter. 5.851084F-statistic 2.913881    Durbin-Watson stat 2.088287Prob(F-statistic) 0.144903

INTERCEPT AT 2ND DIFF

Null Hypothesis: D(MDG2,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.165844  0.0669Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2,3)Method: Least SquaresDate: 03/26/12 Time: 16:52Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

91

D(MDG2(-1),2) -1.325743 0.418765 -3.165844 0.0249C 0.291344 2.251892 0.129377 0.9021

R-squared 0.667167    Mean dependent var 0.442857Adjusted R-squared 0.600601    S.D. dependent var 9.425295S.E. of regression 5.956601    Akaike info criterion 6.641833Sum squared resid 177.4055    Schwarz criterion 6.626379Log likelihood -21.24642    Hannan-Quinn criter. 6.450822F-statistic 10.02257    Durbin-Watson stat 2.181949Prob(F-statistic) 0.024931

TREND AND INTERCEPT AT 2ND DIFF

Null Hypothesis: D(MDG2,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.829456  0.2450Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG2,3)Method: Least SquaresDate: 03/26/12 Time: 16:53Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG2(-1),2) -1.325784 0.468565 -2.829456 0.0474C 0.274763 7.967740 0.034484 0.9741

@TREND(2000) 0.002763 1.259562 0.002193 0.9984

R-squared 0.667168    Mean dependent var 0.442857Adjusted R-squared 0.500752    S.D. dependent var 9.425295S.E. of regression 6.659679    Akaike info criterion 6.927547Sum squared resid 177.4053    Schwarz criterion 6.904365Log likelihood -21.24641    Hannan-Quinn criter. 6.641029F-statistic 4.009034    Durbin-Watson stat 2.181827Prob(F-statistic) 0.110777

UNIT ROOT UNIT TEST FOR MDG3

INT AT LEVEL

Null Hypothesis: MDG3 has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

92

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.529205  0.1400Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG3)Method: Least SquaresDate: 03/26/12 Time: 16:54Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG3(-1) -0.928999 0.367308 -2.529205 0.0393C 66.37803 26.25377 2.528324 0.0393

R-squared 0.477490    Mean dependent var 0.233333Adjusted R-squared 0.402846    S.D. dependent var 8.949441S.E. of regression 6.915747    Akaike info criterion 6.898609Sum squared resid 334.7929    Schwarz criterion 6.942437Log likelihood -29.04374    Hannan-Quinn criter. 6.804029F-statistic 6.396879    Durbin-Watson stat 2.044524Prob(F-statistic) 0.039279

TREND AND INT AT LEVEL

Null Hypothesis: MDG3 has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -7.612141  0.0023Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test Equation

93

Dependent Variable: D(MDG3)Method: Least SquaresDate: 03/26/12 Time: 16:55Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG3(-1) -1.776593 0.233389 -7.612141 0.0016D(MDG3(-1)) 0.174723 0.145065 1.204445 0.2948

C 145.2760 18.29271 7.941739 0.0014@TREND(2000) -3.205945 0.484622 -6.615356 0.0027

R-squared 0.957519    Mean dependent var 0.012500Adjusted R-squared 0.925658    S.D. dependent var 9.541105S.E. of regression 2.601454    Akaike info criterion 5.056871Sum squared resid 27.07025    Schwarz criterion 5.096592Log likelihood -16.22748    Hannan-Quinn criter. 4.788970F-statistic 30.05309    Durbin-Watson stat 1.162038Prob(F-statistic) 0.003335

INT AT 1ST DIFF

Null Hypothesis: D(MDG3) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.168896  0.0167Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG3,2)Method: Least SquaresDate: 03/26/12 Time: 16:55Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG3(-1)) -1.484987 0.356206 -4.168896 0.0059C 0.060999 3.184862 0.019153 0.9853

R-squared 0.743367    Mean dependent var -0.087500Adjusted R-squared 0.700595    S.D. dependent var 16.46186S.E. of regression 9.007586    Akaike info criterion 7.446329Sum squared resid 486.8196    Schwarz criterion 7.466190Log likelihood -27.78532    Hannan-Quinn criter. 7.312379F-statistic 17.37969    Durbin-Watson stat 1.393599Prob(F-statistic) 0.005886

94

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG3) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.192716  0.0538Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG3,2)Method: Least SquaresDate: 03/26/12 Time: 16:56Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG3(-1)) -1.573841 0.375375 -4.192716 0.0085C 7.303683 8.691233 0.840351 0.4390

@TREND(2000) -1.315236 1.464696 -0.897959 0.4104

R-squared 0.779006    Mean dependent var -0.087500Adjusted R-squared 0.690608    S.D. dependent var 16.46186S.E. of regression 9.156578    Akaike info criterion 7.546818Sum squared resid 419.2146    Schwarz criterion 7.576609Log likelihood -27.18727    Hannan-Quinn criter. 7.345893F-statistic 8.812517    Durbin-Watson stat 1.354778Prob(F-statistic) 0.022959

INT AT 2ND DIFF

Null Hypothesis: D(MDG3,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -7.648552  0.0007Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

95

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG3,3)Method: Least SquaresDate: 03/26/12 Time: 16:56Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG3(-1),2) -1.750179 0.228825 -7.648552 0.0006C -2.700041 3.766139 -0.716925 0.5055

R-squared 0.921260    Mean dependent var -2.300000Adjusted R-squared 0.905512    S.D. dependent var 32.41275S.E. of regression 9.963307    Akaike info criterion 7.670652Sum squared resid 496.3374    Schwarz criterion 7.655197Log likelihood -24.84728    Hannan-Quinn criter. 7.479640F-statistic 58.50035    Durbin-Watson stat 0.844188Prob(F-statistic) 0.000608

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG3,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -21.25075  0.0001Test critical values: 1% level -7.006336

5% level -4.77319410% level -3.877714

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 6

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG3,3)Method: Least SquaresDate: 03/26/12 Time: 16:56Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG3(-1),2) -1.699422 0.079970 -21.25075 0.0022D(MDG3(-1),3) 0.080688 0.036856 2.189236 0.1600

C -4.278614 1.633551 -2.619212 0.1201@TREND(2000) 0.771591 0.228563 3.375834 0.0777

R-squared 0.999776    Mean dependent var 5.816667Adjusted R-squared 0.999439    S.D. dependent var 26.59529S.E. of regression 0.630025    Akaike info criterion 2.148606Sum squared resid 0.793863    Schwarz criterion 2.009779Log likelihood -2.445818    Hannan-Quinn criter. 1.592870F-statistic 2969.241    Durbin-Watson stat 2.847483Prob(F-statistic) 0.000337

96

UNIT ROOT TEST FOR MDG4

INT AT LEVEL

Null Hypothesis: MDG4 has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.441230  0.5151Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4)Method: Least SquaresDate: 03/26/12 Time: 16:57Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG4(-1) -0.511690 0.355037 -1.441230 0.1927C 91.18508 65.52852 1.391533 0.2067

R-squared 0.228832    Mean dependent var -2.638889Adjusted R-squared 0.118666    S.D. dependent var 23.91100S.E. of regression 22.44751    Akaike info criterion 9.253366Sum squared resid 3527.235    Schwarz criterion 9.297194Log likelihood -39.64015    Hannan-Quinn criter. 9.158786F-statistic 2.077145    Durbin-Watson stat 1.942978Prob(F-statistic) 0.192716

TREND AND INT AT LEVL

Null Hypothesis: MDG4 has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.944311  0.5535Test critical values: 1% level -5.521860

5% level -4.10783310% level -3.515047

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

97

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4)Method: Least SquaresDate: 03/26/12 Time: 16:57Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG4(-1) -0.724621 0.372688 -1.944311 0.0998C 150.5193 76.43250 1.969310 0.0964

@TREND(2000) -4.058156 3.042039 -1.334025 0.2306

R-squared 0.405240    Mean dependent var -2.638889Adjusted R-squared 0.206987    S.D. dependent var 23.91100S.E. of regression 21.29305    Akaike info criterion 9.215840Sum squared resid 2720.365    Schwarz criterion 9.281582Log likelihood -38.47128    Hannan-Quinn criter. 9.073970F-statistic 2.044054    Durbin-Watson stat 2.063739Prob(F-statistic) 0.210390

INT AT 1ST DIFF

Null Hypothesis: D(MDG4) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.215685  0.0575Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4,2)Method: Least SquaresDate: 03/26/12 Time: 16:58Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG4(-1)) -1.268705 0.394536 -3.215685 0.0182C -3.867232 9.488952 -0.407551 0.6977

R-squared 0.632817    Mean dependent var 0.375000Adjusted R-squared 0.571620    S.D. dependent var 40.60788S.E. of regression 26.57816    Akaike info criterion 9.610375Sum squared resid 4238.392    Schwarz criterion 9.630235Log likelihood -36.44150    Hannan-Quinn criter. 9.476424F-statistic 10.34063    Durbin-Watson stat 2.056889

98

Prob(F-statistic) 0.018236

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG4) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.813724  0.2482Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4,2)Method: Least SquaresDate: 03/26/12 Time: 16:59Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG4(-1)) -3.161985 1.123772 -2.813724 0.0671D(MDG4(-1),2) 1.190922 0.694094 1.715793 0.1847

C 73.80190 45.28495 1.629723 0.2017@TREND(2000) -14.78152 8.170291 -1.809179 0.1681

R-squared 0.831112    Mean dependent var 0.428571Adjusted R-squared 0.662224    S.D. dependent var 43.86122S.E. of regression 25.49148    Akaike info criterion 9.610125Sum squared resid 1949.447    Schwarz criterion 9.579217Log likelihood -29.63544    Hannan-Quinn criter. 9.228102F-statistic 4.921084    Durbin-Watson stat 2.147438Prob(F-statistic) 0.111665

INT AT 2ND DIFF

Null Hypothesis: D(MDG4,2) has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.898362  0.1000Test critical values: 1% level -5.119808

5% level -3.51959510% level -2.898418

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations

99

        and may not be accurate for a sample size of 6

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4,3)Method: Least SquaresDate: 03/26/12 Time: 16:59Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG4(-1),2) -3.951267 1.363276 -2.898362 0.0626D(MDG4(-1),3) 1.601154 0.901814 1.775482 0.1739

C -14.91176 16.17407 -0.921955 0.4245

R-squared 0.902504    Mean dependent var -5.541667Adjusted R-squared 0.837507    S.D. dependent var 84.73671S.E. of regression 34.15776    Akaike info criterion 10.20671Sum squared resid 3500.258    Schwarz criterion 10.10259Log likelihood -27.62013    Hannan-Quinn criter. 9.789908F-statistic 13.88525    Durbin-Watson stat 1.679389Prob(F-statistic) 0.030442

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG4,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.117129  0.4487Test critical values: 1% level -7.006336

5% level -4.77319410% level -3.877714

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 6

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG4,3)Method: Least SquaresDate: 03/26/12 Time: 17:00Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG4(-1),2) -5.519169 2.606912 -2.117129 0.1685D(MDG4(-1),3) 2.739044 1.839412 1.489087 0.2749

C 55.48331 97.85213 0.567012 0.6279@TREND(2000) -12.45865 17.03576 -0.731323 0.5407

R-squared 0.923075    Mean dependent var -5.541667Adjusted R-squared 0.807688    S.D. dependent var 84.73671S.E. of regression 37.15996    Akaike info criterion 10.30306

100

Sum squared resid 2761.725    Schwarz criterion 10.16423Log likelihood -26.90919    Hannan-Quinn criter. 9.747326F-statistic 7.999788    Durbin-Watson stat 1.788876Prob(F-statistic) 0.113139

UNIT ROOT TEST FOR MDG5

INT AT LEVEL

Null Hypothesis: MDG5 has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -0.794232  0.7704Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5)Method: Least SquaresDate: 03/26/12 Time: 17:01Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG5(-1) -0.313944 0.395280 -0.794232 0.4531C 214.5471 294.1484 0.729384 0.4894

R-squared 0.082666    Mean dependent var -17.66667Adjusted R-squared -0.048382    S.D. dependent var 94.49339S.E. of regression 96.75228    Akaike info criterion 12.17531Sum squared resid 65527.03    Schwarz criterion 12.21914Log likelihood -52.78892    Hannan-Quinn criter. 12.08073F-statistic 0.630805    Durbin-Watson stat 1.666247Prob(F-statistic) 0.453140

TREND AND INT AT LEVEL

Null Hypothesis: MDG5 has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -0.970602  0.8904Test critical values: 1% level -5.521860

5% level -4.10783310% level -3.515047

101

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5)Method: Least SquaresDate: 03/26/12 Time: 17:02Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG5(-1) -0.357898 0.368738 -0.970602 0.3692C 331.4610 285.1259 1.162507 0.2892

@TREND(2000) -16.88053 11.65196 -1.448729 0.1976

R-squared 0.320394    Mean dependent var -17.66667Adjusted R-squared 0.093858    S.D. dependent var 94.49339S.E. of regression 89.94965    Akaike info criterion 12.09758Sum squared resid 48545.63    Schwarz criterion 12.16332Log likelihood -51.43910    Hannan-Quinn criter. 11.95571F-statistic 1.414321    Durbin-Watson stat 2.167211Prob(F-statistic) 0.313886

INT AT 1ST DIFF

Null Hypothesis: D(MDG5) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.560922  0.1376Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5,2)Method: Least SquaresDate: 03/26/12 Time: 17:02Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG5(-1)) -1.044458 0.407845 -2.560922 0.0429C -20.75861 39.28906 -0.528356 0.6162

R-squared 0.522229    Mean dependent var 0.000000Adjusted R-squared 0.442601    S.D. dependent var 145.6424

102

S.E. of regression 108.7354    Akaike info criterion 12.42803Sum squared resid 70940.38    Schwarz criterion 12.44789Log likelihood -47.71212    Hannan-Quinn criter. 12.29408F-statistic 6.558320    Durbin-Watson stat 2.002325Prob(F-statistic) 0.042855

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG5) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.722332  0.0880Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5,2)Method: Least SquaresDate: 03/26/12 Time: 17:03Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG5(-1)) -1.545379 0.415164 -3.722332 0.0137C 158.2217 94.56497 1.673154 0.1552

@TREND(2000) -34.35203 17.07936 -2.011318 0.1005

R-squared 0.735904    Mean dependent var 0.000000Adjusted R-squared 0.630266    S.D. dependent var 145.6424S.E. of regression 88.55903    Akaike info criterion 12.08521Sum squared resid 39213.51    Schwarz criterion 12.11500Log likelihood -45.34085    Hannan-Quinn criter. 11.88429F-statistic 6.966254    Durbin-Watson stat 2.321445Prob(F-statistic) 0.035843

INT AT 2ND DIFF

Null Hypothesis: D(MDG5,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.474348  0.0144Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

103

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5,3)Method: Least SquaresDate: 03/26/12 Time: 17:03Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG5(-1),2) -2.000988 0.447213 -4.474348 0.0066C -36.46457 48.83117 -0.746748 0.4888

R-squared 0.800158    Mean dependent var 36.42857Adjusted R-squared 0.760190    S.D. dependent var 248.7072S.E. of regression 121.7930    Akaike info criterion 12.67748Sum squared resid 74167.64    Schwarz criterion 12.66202Log likelihood -42.37118    Hannan-Quinn criter. 12.48647F-statistic 20.01979    Durbin-Watson stat 2.124997Prob(F-statistic) 0.006553

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG5,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.707246  0.2867Test critical values: 1% level -7.006336

5% level -4.77319410% level -3.877714

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 6

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG5,3)Method: Least SquaresDate: 03/26/12 Time: 17:04Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG5(-1),2) -3.860686 1.426057 -2.707246 0.1136D(MDG5(-1),3) 1.128889 0.993598 1.136163 0.3737

C 238.6102 252.2901 0.945777 0.4441@TREND(2000) -50.49410 41.09507 -1.228714 0.3441

R-squared 0.926188    Mean dependent var 26.50000

104

Adjusted R-squared 0.815469    S.D. dependent var 270.9212S.E. of regression 116.3797    Akaike info criterion 12.58631Sum squared resid 27088.48    Schwarz criterion 12.44749Log likelihood -33.75894    Hannan-Quinn criter. 12.03058F-statistic 8.365255    Durbin-Watson stat 3.219928Prob(F-statistic) 0.108649

UNIT ROOT TEST FOR MDG6

INT AT LEVEL

Null Hypothesis: MDG6 has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -0.732617  0.7883Test critical values: 1% level -4.420595

5% level -3.25980810% level -2.771129

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6)Method: Least SquaresDate: 03/26/12 Time: 17:04Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG6(-1) -0.153179 0.209085 -0.732617 0.4876C 0.617245 1.032686 0.597708 0.5689

R-squared 0.071215    Mean dependent var -0.133333Adjusted R-squared -0.061469    S.D. dependent var 0.377492S.E. of regression 0.388921    Akaike info criterion 1.142247Sum squared resid 1.058815    Schwarz criterion 1.186075Log likelihood -3.140113    Hannan-Quinn criter. 1.047667F-statistic 0.536727    Durbin-Watson stat 1.957129Prob(F-statistic) 0.487593

TREND AND INT AT LEVEL

Null Hypothesis: MDG6 has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.369252  0.3674Test critical values: 1% level -5.521860

105

5% level -4.10783310% level -3.515047

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 9

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6)Method: Least SquaresDate: 03/26/12 Time: 17:05Sample (adjusted): 2001 2009Included observations: 9 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG6(-1) -0.924870 0.390364 -2.369252 0.0556C 5.425475 2.346727 2.311933 0.0601

@TREND(2000) -0.205389 0.093742 -2.191010 0.0710

R-squared 0.484033    Mean dependent var -0.133333Adjusted R-squared 0.312044    S.D. dependent var 0.377492S.E. of regression 0.313103    Akaike info criterion 0.776634Sum squared resid 0.588202    Schwarz criterion 0.842376Log likelihood -0.494855    Hannan-Quinn criter. 0.634764F-statistic 2.814328    Durbin-Watson stat 1.469910Prob(F-statistic) 0.137362

INT AT 1ST DIFF

Null Hypothesis: D(MDG6) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.590570  0.0351Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6,2)Method: Least SquaresDate: 03/26/12 Time: 17:05Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG6(-1)) -1.214286 0.338187 -3.590570 0.0115C -0.232143 0.136328 -1.702829 0.1395

106

R-squared 0.682409    Mean dependent var -0.050000Adjusted R-squared 0.629477    S.D. dependent var 0.587975S.E. of regression 0.357904    Akaike info criterion 0.995214Sum squared resid 0.768571    Schwarz criterion 1.015074Log likelihood -1.980855    Hannan-Quinn criter. 0.861263F-statistic 12.89219    Durbin-Watson stat 2.342207Prob(F-statistic) 0.011496

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG6) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.347784  0.1325Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6,2)Method: Least SquaresDate: 03/26/12 Time: 17:06Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG6(-1)) -1.177158 0.351623 -3.347784 0.0204C -0.480694 0.339348 -1.416524 0.2158

@TREND(2000) 0.046204 0.057420 0.804666 0.4576

R-squared 0.718821    Mean dependent var -0.050000Adjusted R-squared 0.606349    S.D. dependent var 0.587975S.E. of regression 0.368905    Akaike info criterion 1.123441Sum squared resid 0.680454    Schwarz criterion 1.153231Log likelihood -1.493763    Hannan-Quinn criter. 0.922515F-statistic 6.391119    Durbin-Watson stat 2.778201Prob(F-statistic) 0.041924

INT AT 2ND DIFF

Null Hypothesis: D(MDG6,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.476372  0.0143Test critical values: 1% level -4.803492

107

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6,3)Method: Least SquaresDate: 03/26/12 Time: 17:07Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG6(-1),2) -1.576372 0.352154 -4.476372 0.0065C -0.041169 0.207485 -0.198421 0.8505

R-squared 0.800303    Mean dependent var 0.071429Adjusted R-squared 0.760363    S.D. dependent var 1.113125S.E. of regression 0.544905    Akaike info criterion 1.858545Sum squared resid 1.484606    Schwarz criterion 1.843091Log likelihood -4.504908    Hannan-Quinn criter. 1.667534F-statistic 20.03790    Durbin-Watson stat 1.873307Prob(F-statistic) 0.006541

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG6,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -4.698574  0.0403Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG6,3)Method: Least SquaresDate: 03/26/12 Time: 17:07Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG6(-1),2) -1.693211 0.360367 -4.698574 0.0093C -0.748881 0.671250 -1.115651 0.3271

@TREND(2000) 0.116561 0.105379 1.106112 0.3307

108

R-squared 0.847077    Mean dependent var 0.071429Adjusted R-squared 0.770616    S.D. dependent var 1.113125S.E. of regression 0.533121    Akaike info criterion 1.877389Sum squared resid 1.136871    Schwarz criterion 1.854208Log likelihood -3.570862    Hannan-Quinn criter. 1.590872F-statistic 11.07851    Durbin-Watson stat 2.012603Prob(F-statistic) 0.023385

UNIT ROOT TEST FOR MDG7

INT AT LEVEL

Null Hypothesis: MDG7 has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.673911  0.0315Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7)Method: Least SquaresDate: 03/26/12 Time: 17:08Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG7(-1) -1.054733 0.287087 -3.673911 0.0144D(MDG7(-1)) 1.016868 0.294050 3.458146 0.0181

C 44.89731 12.15107 3.694925 0.0141

R-squared 0.755959    Mean dependent var 1.087500Adjusted R-squared 0.658343    S.D. dependent var 7.735343S.E. of regression 4.521420    Akaike info criterion 6.135526Sum squared resid 102.2162    Schwarz criterion 6.165316Log likelihood -21.54210    Hannan-Quinn criter. 5.934600F-statistic 7.744186    Durbin-Watson stat 1.904463Prob(F-statistic) 0.029421

TREND AND INT AT LEVEL

Null Hypothesis: MDG7 has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

109

Augmented Dickey-Fuller test statistic -3.805631  0.0804Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7)Method: Least SquaresDate: 03/26/12 Time: 17:09Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG7(-1) -1.187617 0.312068 -3.805631 0.0190D(MDG7(-1)) 1.208347 0.344850 3.503984 0.0248

C 55.01740 15.48667 3.552566 0.0237@TREND(2000) -0.852166 0.818964 -1.040541 0.3568

R-squared 0.807945    Mean dependent var 1.087500Adjusted R-squared 0.663904    S.D. dependent var 7.735343S.E. of regression 4.484475    Akaike info criterion 6.145973Sum squared resid 80.44205    Schwarz criterion 6.185693Log likelihood -20.58389    Hannan-Quinn criter. 5.878072F-statistic 5.609118    Durbin-Watson stat 2.555357Prob(F-statistic) 0.064559

INT AT 1ST DIFF

Null Hypothesis: D(MDG7) has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -2.950309  0.0870Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

110

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7,2)Method: Least SquaresDate: 03/26/12 Time: 17:10Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG7(-1)) -1.176189 0.398666 -2.950309 0.0420D(MDG7(-1),2) 0.864702 0.411479 2.101450 0.1035

C -0.757827 2.461888 -0.307824 0.7736

R-squared 0.688473    Mean dependent var -1.242857Adjusted R-squared 0.532709    S.D. dependent var 9.283472S.E. of regression 6.346057    Akaike info criterion 6.831072Sum squared resid 161.0898    Schwarz criterion 6.807890Log likelihood -20.90875    Hannan-Quinn criter. 6.544554F-statistic 4.419987    Durbin-Watson stat 2.424867Prob(F-statistic) 0.097049

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG7) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -3.182150  0.1722Test critical values: 1% level -6.292057

5% level -4.45042510% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7,2)Method: Least SquaresDate: 03/26/12 Time: 17:11Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG7(-1)) -1.303636 0.409671 -3.182150 0.0500D(MDG7(-1),2) 0.826587 0.406056 2.035647 0.1346

C -8.820865 7.931440 -1.112139 0.3472@TREND(2000) 1.386807 1.299121 1.067496 0.3640

R-squared 0.774231    Mean dependent var -1.242857Adjusted R-squared 0.548462    S.D. dependent var 9.283472S.E. of regression 6.238174    Akaike info criterion 6.794811Sum squared resid 116.7444    Schwarz criterion 6.763903Log likelihood -19.78184    Hannan-Quinn criter. 6.412788F-statistic 3.429308    Durbin-Watson stat 3.021167

111

Prob(F-statistic) 0.169233

INT AT 2ND DIFF

Null Hypothesis: D(MDG7,2) has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.886968  0.3158Test critical values: 1% level -5.119808

5% level -3.51959510% level -2.898418

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 6

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7,3)Method: Least SquaresDate: 03/26/12 Time: 17:11Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG7(-1),2) -1.365905 0.723862 -1.886968 0.1556D(MDG7(-1),3) 0.643741 0.530087 1.214407 0.3115

C 0.425093 4.303152 0.098786 0.9275

R-squared 0.542772    Mean dependent var -1.166667Adjusted R-squared 0.237953    S.D. dependent var 11.79248S.E. of regression 10.29429    Akaike info criterion 7.807908Sum squared resid 317.9169    Schwarz criterion 7.703787Log likelihood -20.42372    Hannan-Quinn criter. 7.391106F-statistic 1.780637    Durbin-Watson stat 2.492925Prob(F-statistic) 0.309172

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG7,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.060399  0.8357Test critical values: 1% level -7.006336

5% level -4.77319410% level -3.877714

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 6

112

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG7,3)Method: Least SquaresDate: 03/26/12 Time: 17:12Sample (adjusted): 2004 2009Included observations: 6 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG7(-1),2) -1.363674 1.286001 -1.060399 0.4001D(MDG7(-1),3) 0.642920 0.734209 0.875663 0.4736

C 0.491467 28.21112 0.017421 0.9877@TREND(2000) -0.010579 4.417222 -0.002395 0.9983

R-squared 0.542773    Mean dependent var -1.166667Adjusted R-squared -0.143067    S.D. dependent var 11.79248S.E. of regression 12.60786    Akaike info criterion 8.141238Sum squared resid 317.9160    Schwarz criterion 8.002411Log likelihood -20.42371    Hannan-Quinn criter. 7.585502F-statistic 0.791398    Durbin-Watson stat 2.494386Prob(F-statistic) 0.600122

UNIT ROOT TEST FOR MDG8

INT AT LEVEL

Null Hypothesis: MDG8 has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic  1.358477  0.9952Test critical values: 1% level -4.582648

5% level -3.32096910% level -2.801384

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8)Method: Least SquaresDate: 03/26/12 Time: 17:12Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG8(-1) 0.439493 0.323519 1.358477 0.2324D(MDG8(-1)) -1.306052 1.010641 -1.292301 0.2528

C 5.850007 2.840245 2.059684 0.0945

R-squared 0.270495    Mean dependent var 5.650000Adjusted R-squared -0.021307    S.D. dependent var 5.149247

113

S.E. of regression 5.203815    Akaike info criterion 6.416657Sum squared resid 135.3985    Schwarz criterion 6.446448Log likelihood -22.66663    Hannan-Quinn criter. 6.215732F-statistic 0.926982    Durbin-Watson stat 1.381223Prob(F-statistic) 0.454538

TREND AND INT AT LEVEL

Null Hypothesis: MDG8 has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -1.397566  0.7770Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8)Method: Least SquaresDate: 03/26/12 Time: 17:13Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

MDG8(-1) -0.359527 0.257252 -1.397566 0.2348D(MDG8(-1)) -1.336410 0.505744 -2.642461 0.0574

C -11.36025 4.534905 -2.505068 0.0664@TREND(2000) 5.536168 1.385299 3.996371 0.0162

R-squared 0.853887    Mean dependent var 5.650000Adjusted R-squared 0.744302    S.D. dependent var 5.149247S.E. of regression 2.603797    Akaike info criterion 5.058671Sum squared resid 27.11903    Schwarz criterion 5.098392Log likelihood -16.23469    Hannan-Quinn criter. 4.790771F-statistic 7.792026    Durbin-Watson stat 2.539395Prob(F-statistic) 0.038023

INT AT 1ST DIFF

Null Hypothesis: D(MDG8) has a unit rootExogenous: ConstantLag Length: 1 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -0.683138  0.7868Test critical values: 1% level -4.803492

5% level -3.403313

114

10% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8,2)Method: Least SquaresDate: 03/26/12 Time: 17:13Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG8(-1)) -0.348117 0.509585 -0.683138 0.5320D(MDG8(-1),2) -1.485816 0.644646 -2.304856 0.0825

C 5.457051 2.836661 1.923759 0.1267

R-squared 0.826726    Mean dependent var -0.165714Adjusted R-squared 0.740089    S.D. dependent var 7.982011S.E. of regression 4.069347    Akaike info criterion 5.942369Sum squared resid 66.23833    Schwarz criterion 5.919188Log likelihood -17.79829    Hannan-Quinn criter. 5.655852F-statistic 9.542410    Durbin-Watson stat 2.465674Prob(F-statistic) 0.030024

TREND AND INT AT 1ST DIFF

Null Hypothesis: D(MDG8) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -6.045963  0.0083Test critical values: 1% level -5.835186

5% level -4.24650310% level -3.590496

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 8

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8,2)Method: Least SquaresDate: 03/26/12 Time: 17:14Sample (adjusted): 2002 2009Included observations: 8 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG8(-1)) -2.739782 0.453159 -6.045963 0.0018C -6.682459 3.338730 -2.001497 0.1017

@TREND(2000) 4.031473 0.951172 4.238425 0.0082

115

R-squared 0.894810    Mean dependent var -0.006250Adjusted R-squared 0.852734    S.D. dependent var 7.403657S.E. of regression 2.841169    Akaike info criterion 5.206304Sum squared resid 40.36120    Schwarz criterion 5.236095Log likelihood -17.82522    Hannan-Quinn criter. 5.005379F-statistic 21.26658    Durbin-Watson stat 1.857536Prob(F-statistic) 0.003589

INT AT 2ND DIFF

Null Hypothesis: D(MDG8,2) has a unit rootExogenous: ConstantLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -7.074970  0.0012Test critical values: 1% level -4.803492

5% level -3.40331310% level -2.841819

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8,3)Method: Least SquaresDate: 03/26/12 Time: 17:14Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG8(-1),2) -2.818984 0.398445 -7.074970 0.0009C 3.965979 1.712431 2.315994 0.0684

R-squared 0.909182    Mean dependent var -2.437143Adjusted R-squared 0.891018    S.D. dependent var 11.65079S.E. of regression 3.846201    Akaike info criterion 5.767005Sum squared resid 73.96631    Schwarz criterion 5.751551Log likelihood -18.18452    Hannan-Quinn criter. 5.575994F-statistic 50.05520    Durbin-Watson stat 2.380673Prob(F-statistic) 0.000873

TREND AND INT AT 2ND DIFF

Null Hypothesis: D(MDG8,2) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=1)

t-Statistic   Prob.*

Augmented Dickey-Fuller test statistic -5.842659  0.0147Test critical values: 1% level -6.292057

5% level -4.450425

116

10% level -3.701534

*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20 observations        and may not be accurate for a sample size of 7

Augmented Dickey-Fuller Test EquationDependent Variable: D(MDG8,3)Method: Least SquaresDate: 03/26/12 Time: 17:15Sample (adjusted): 2003 2009Included observations: 7 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

D(MDG8(-1),2) -2.765380 0.473308 -5.842659 0.0043C 5.442605 5.146431 1.057549 0.3499

@TREND(2000) -0.266398 0.863434 -0.308533 0.7731

R-squared 0.911293    Mean dependent var -2.437143Adjusted R-squared 0.866940    S.D. dependent var 11.65079S.E. of regression 4.249911    Akaike info criterion 6.029200Sum squared resid 72.24697    Schwarz criterion 6.006019Log likelihood -18.10220    Hannan-Quinn criter. 5.742683F-statistic 20.54616    Durbin-Watson stat 2.489175Prob(F-statistic) 0.007869

117