Poverty In Pakistan And Impact Of Socioeconomic Variables Economics Essay


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This thesis contains no material, which has been accepted for the reward to the candidate of any other degree or diploma, in any university or other institution. To the best of my knowledge the thesis contains no material previously published or written by another person, except where due reference is made in the text of the thesis.

Haider Ali Khan

Research Completion Certificate

Certified that Haider Ali Khan, I.D No. 07U0446 Session 2007 to 2011 Certified that Haider Ali Khan, id No. 07U0446 Session 2007 to 2011 has carried out and completed the research project entitled "Incidence of Poverty in Pakistan and impact of Socioeconomic variables " under my supervision for requirement for the award of Degree of Bachelor of business Administration Honors (Finance & Marketing) by Lahore School of Economics.

Research supervisor

(Zehra Raza) Lahore School of Economics

Table of Contents


The research reported in this thesis was on "Incidence of Poverty in Pakistan and impact of Socio economic variables". The purpose of research was to study the Poverty situation in Pakistan and the impact of different socioeconomic variables on poverty. The secondary data was collected by consultation of literature in the libraries and Internet and also from the material printed by different governmental organizations. SPSS software was applied to analyze data for frequencies regression parameters. The findings suggested that poverty is at its peak in Pakistan and socioeconomic variables such as unemployment, GDP per capita, literacy rate, male/female ratio and demographic age bracket has significant impact on poverty. Furthermore the efforts made by the government have failed to control the rising level of poverty in Pakistan.



Poverty, defined comprehensively as absence of options to shape one's life according to one's own preferences, comes closer to the concept of human development as presented in UNDP's Human Development Reports. Poverty is further divided into two elements, income poverty and human poverty.

Income poverty is defined as the lack of availability of basic necessities required for minimum material wellbeing determined by the national poverty line. Human poverty means the absence of choices and opportunities for a tolerable life in all economic and social aspects.

There are three poverty measures use to gauge the level of poverty in any country which are head count ratio, poverty gap ratio and severity of poverty measure. Over the past half century, poverty remains widespread in the developing world, More than 1.2 billion people live on less than $1 per day at purchasing power parity, and more than 2.8 billion which is almost the half of the world's population live on less than $2 a day.

According to the United Nations development survey more than 80 percent of the world's population lives in countries in which high level of income gap persists. The poorest 40 percent of the world's population account for only 5 percent of global income. Whereas, the richest 20 percent account for 75 percent of world income.

Poverty is a root cause for a number of other issues in a country which include crime, lawlessness, illiteracy, health issues and other unethical practices. There are number of micro as well as macro economic variables which play a significant role in poverty. If we look at macroeconomic factor, they include foreign direct investment, external debt, remittances, political stability, geo politics, international market conditions unemployment, GDP per capita, inflation etc. all these macroeconomic variables play a critical role in increase or decrease of poverty in a country. Along with these macroeconomic variables, the micro economic variables also play important role in poverty are education, health, education, mental or physical inability. A number of policies were made to control the problem of poverty but so far all policies were failed to eradicate poverty in the country.

The basic aim of the research is to evaluate the impact of 6 macroeconomic variables which include GDP per capita, unemployment, demographic age, primary education attainment, male/female ratio and inflation on poverty in Pakistan.


Poverty is a significant problem that is prevailing in most of the developing and under developed countries of the world.

Pakistan is a developing country with a total population of approximately 17 billion. Since independence, the problem of mass poverty in Pakistan has been substantial and its level is increasing on everyday basis. It is observed that the problem of poverty in Pakistan is now looks to be beyond control. The vast masses of the people, particularly those living in the rural areas are adversely affected by poverty. The government and the authorities have failed to control the increasing poverty in the country. The policies formulated to eradicate it have failed to achieve their objectives. Poverty is not just about providing food, shelter and water to people. The issue of poverty in Pakistan has its significance for sustainable development. Long run development is not possible without protecting the rights of the vulnerable groups and the participation of the entire population in the development process. Although Pakistan has achieved a respectable economic growth since the independence but still the problem of poverty is persisting in the country. One of the major reason for poverty is that the growth and developments were not distributed among all groups equally, as a result of which country is face a significant income gap between different segments. Therefore the income gap between different classes is very high. The major reason behind this income gap is the lack of justice. Because of which only the top 10% of the nation is getting richer day by day whereas the low income class is getting poorer day by day. As a result of this the middle income class which is the backbone of any country is eradicating.

Now if we look at the poverty from the historical perspective, right after the independence Pakistan face a significant problem of poverty because of lack of resources and infrastructure. Since the independence the level of poverty is increasing every year. The poverty head count index was 24.47 in 1985 whereas it was 40.91 in 2009. It shows that it is almost doubled from the figure of 1985. Both internal as well external factors are responsible for this increase in poverty. Numerous plans were implemented by the government as well as international organizations to eradicate poverty but still the conditions are indeed alarming. One of the major step was millennium development goals. The major goal of millennium development goal is to decrease the level of poverty. So far the target of decreasing poverty to a certain level is not fulfilled and it has a very slight chances of achieving the target in future.

Importance of the study with respect to the world

Poverty has plagued many underdeveloped countries to affect their socio economic conditions very adversely. Pakistan is a developing nation and the prime hindrance to its growth is high levels of poverty and large income gaps as a result of extreme poverty.

Elimination of poverty would ultimately lead to the elimination of a number of core problems for the country, however, in order to eliminate poverty the various range of factors that are interdependently working together towards high levels of poverty need to be examined.

Organizations like the World Bank, IMF and WHO are all concerned about the deteriorating state of Pakistan. Analysis of statistics shows that in the past decade poverty is rather on the rise after experiencing a decline. The World Bank has extended numerous loans to Pakistan but with little results in place. After giving out billions of dollars to Pakistan, these organizations are very concerned about the root cause of poverty in Pakistan that is halting the growth of the economy. Thus, this study is of great significance as it unravels the various reasons for poverty.

In the world that we are living in today, the concept of altruism in its true sense in barely present. Any loan, aid or help that comes your way comes with a price. There is an ulterior motive that is almost always involved and therefore, whenever any country in the world extends a hand for relationship to Pakistan it inevitably evaluates the economic conditions and level of poverty within the country. The reasons that are eventually leading to this condition are also important to understand as ultimately the reasons are the ones leading to the current situation.

Also, it is important to understand that the world is in transition from being international to global. Now it's not about a particular state but the level of interconnectedness between different countries. Many countries are aligned with Pakistan for trade and political purposes. When such alignment takes place, automatically issues of Pakistan becomes issues of all those related, hence, the rest of the world. These countries can largely be affected by the poverty in Pakistan and in order to function at an interconnected level even they need to be concerned about the state of affairs in Pakistan, the level of poverty and the reasons which are leading to poverty.

The economists of the world are working towards elimination of poverty in the underdeveloped economies Pakistan being one of them. In order to alleviate poverty what's important to understand is that what is causing or what are the factors leading to this state. Thus, the reasons defined in this research are of importance.

Therefore, poverty in Pakistan may be directly affecting Pakistan but at an indirect level there are many other stakeholders affected by the condition in Pakistan due to which this study is of extreme significance. Understanding poverty is of no value until or unless the factors leading to it and the degree of its seriousness are not understood.

Although this study is specific to Pakistan, in reality, there are many global players concerned about the level of poverty, state of affairs and reasons for it.

Importance of the study with respect to Pakistan

This research is primarily evaluating the condition within Pakistan because of the biggest problem in the economy which is poverty thus in every which way this research is of significance to all Pakistanis whether a layman or a policy maker.

The Pakistani economists, policy makers and leaders are all concerned about what to do and how to eliminate poverty. Poverty itself cannot be eliminated without a thorough understanding of the factors leading up to it and it is these factors that need to be defined and studied to come to a productive point where something can be done to generate results. Thus, this study is of value to all those directly involved in Pakistan in the development of economic and public policy.

This analysis is of a lot of significance for NGO's and nonprofit organizations that are trying to make a Pakistan a more balanced economy and trying to alleviate the hunger and poverty that prevails at every nook and corner. The factors leading to poverty are understood and then targeted to come to the final point of poverty elimination. The social welfare organizations of Pakistan therefore might be working towards provision of education and improving literacy rate but what is in due course being targeted is poverty and improvement of poverty.

Furthermore, this study is a fairly simple analysis of the variables affecting poverty and reasons for poverty and it can be used for analysis and as a provision of information by the masses to be better informed and be socially more responsible to change the state of affairs within the country. Poverty is the biggest issue faced by Pakistan and with the level of corruption in place, only if the masses become socially responsible and concerned about what causes poverty and what can be done to change this state can the position within Pakistan be improved.

At a micro level or macro, direct level or indirect all Pakistani's are affected by the level of poverty in Pakistan. The reasons leading up to this are the ones that first need to be understood and then targeted to improve the deteriorating condition of the economy. This study is an eye opener for everyone in the country as it brinks down to conclusions after statistical analysis and regression analysis of the various variables illustrating the adverse condition that we are in.

Research Question

What is the impact of Economic variables like unemployment, lack of education, inflation, male/female ratio, demographic age and GDP (LCU) on poverty?

Literature Review

R.Amjad and A. R.Kemal(1997) wrote the case Macroeconomic Policies and their Impact on Poverty Alleviation in Pakistan. The main aim of this study is to identify those economic policies, especially at the macro level, which can play an important part in ensuring that the process of economic growth and development translates itself into real improvements in peoples' lives-not just in reducing poverty as measured in meeting the minimum nutritional needs but also in ensuring adequate access to education and health services so as to combat early mortality, high rate of disease, and very high levels of illiteracy.

According to the case study for those seeking to explore the relationship between economic growth and poverty alleviation, Pakistan makes a fascinating case-study. The slow progress in improvements in education levels, especially of women, and the high infant and child mortality rates, reflected in the very high rate of population growth, has hindered the achievement of a higher sustained rate of growth of per capita income and of a much faster reduction in nutritional poverty levels. Pakistan's economic performance in fighting poverty cannot, therefore, be divorced from its meager efforts, so far, at improving the overall human development indicators, even though a more concerted attempt is now being made to improve the situation.

There are severe data limitations; also the correlates themselves are not always open to easy and clear-cut interpretation. It is important, therefore, to emphasize the exploratory and, Indeed, tentative nature of the study, and to exercise extreme caution in interpreting some of its main findings.

M.Shaukat Ali(1995) wrote the case Poverty Assesment: Pakistan's Case. The study focuses on the incidence of poverty in Pakistan and the reason for poverty in Pakistan. The methodology used in this case is of "BASIC NEEDS", which defines the poverty line in terms of minimum expenditure on all the basic needs. The findings from the case are that incidence of poverty is quite significant in Pakistan and there is a need to redefine the poverty on the basisof needs. Moreover the shortfall is more pronounced in non food items. The major limitation that the writer faced during he was writing this case was that there wasn't any relevant price indices available.

S.MALIK(1996) wrote a case study named Determinants of Rural Poverty in Pakistan: A Micro Study. The study was conducted to investigate the reasons as to how some of the landless households managed to escape poverty whereas some cultivating households failed to do so. According to the case the main factors responsible for this outcome were found to be favorable/unfavorable distribution by size of landholding, household size, educational attainment, dependency ratio, participation rates, female-male ratio, and age of the household head. The study is based on a village survey conducted in Pakistani Punjab containing 100 households. Per capita rural income is considered to be an important measure of the level of living and, hence, is used as the key dependent variable here.

Ehtasham. A and Steven.L (1989) conducted a research "Poverty, inequality and Growth in Pakistan". The major aim of the study was to find out the impact of growth on poverty and inequality. According to article there are number of factor which play a significant role in increasing poverty and inequality. For Pakistan as a whole, the author found that the Gini coefficient for both income and expenditure has deteriorated over time. What this study shows is that both income inequality and poverty have worsened over time and growth has failed to distribute income equally. The writer used Lorenz curve and Gini coefficient to measure the impact of growth on poverty and in equality.

SALMAN.S.A and S.TAHIR (1999) conducted a study "Dynamics of growth, poverty and inequality in Pakistan". According to the article growth is considered central or the best course to reduce poverty (e.g. World Development Report 1990) with the preconditions that access to

education, health, and social services are available to all by means of other policies. On the other hand, there is a realization that growth, inequality, and poverty relations are non-linear, complex, and path dependent in their dynamics. Institutional factors do not change in a few years while they matter in the reduction of poverty as well as in sustaining it at low levels. Hence these

Relationships are likely to be non-linearity and path dependent, i.e., history matters in the determination of the impact of growth on poverty, of growth on inequality, of inequality on poverty. This paper relies on the consistent data series on household count index and head count

index developed in Tahir and Ali (1999). The poverty estimates in this study are based on both food and non-food poverty.

T.ANWAR and SARFRAZ K.Q conducted a research on trends in absolute poverty in Pakistan. The focus of the study was to examine changes in poverty, the extent of poverty in 1990-91, 1998-99 and 2001.The primary data of Household Income and Expenditure Survey (HIES) for the year 1990-91 and Pakistan Integrated Household Survey (PIHS) for the year 1998-99 and 2001 have been used to examine the poverty trends in Pakistan. These surveys provide complete information on quantity and expenditure of all food and non-food items.5 To provide consistent poverty estimates, HIES 1990-91 has been used to estimate the 'base year poverty line'. To measure the poverty, the Foster, Greer and Thorbecke (1984) class of poverty measures Pα , have been used. According to case the absolute poverty has increased during the time between 1990 to 2001.

G. M. ARIF(2000) conducted a study on Rise in Poverty and Its Implications for Poor Households in Pakistan. This paper examines recent trends in poverty and their impact on primary school enrolment, health status and housing conditions in Pakistan. The study has used data sets generated by the Pakistan Integrated Households Surveys (PIHS) carried out in 1991, 1995-96, 1996-97, and 1998-99 by the Federal Bureau of Statistics. The 1998-99 Pakistan Socioeconomic Survey (PSES), carried out by the Pakistan Institute of Development Economic, has also been used extensively. According to case the rise in poverty in the 1990s has adversely affected the poor families of the country. Primary school enrolment has declined; health and housing conditions have also deteriorated. There is a large gap in these indicators between the poor and non poor households as well as between rural and urban areas.

S.K. Qureshi and G. M. Arif(1999) conducted a study on profile of poverty in Pakistan. The main aim of this project is to analyze the impact of structural adjustment policies on income distribution and poverty in Pakistan. The author used the calorie intake and consumption expenditure method to measure the trends of poverty in Paksitan. According to the article macro-level factors such as demographic dynamics that affect the labor force and dependency ratio, employment levels, real wage rates, workers' remittances, assets ownership and access, and

Inflationary impact on food availability. The factors which have significant impact on poverty are Age of the Head of Households, Sex of the Head of Household, Education of the Head of Household, Farm Status of Households, Place of Residence and Number of Earners in a Household.

T. Anwar, S.K..Qureshi, and H. Ali(2004) conducted a research on landlessness and poverty. The paper examined the landlessness and rural poverty in Pakistan. The results indicate that prevalence of rural poverty based on official poverty line is far greater than the urban poverty-42.9 percent of rural population compared to 26 percent of urban population was poor in 2001-02. The results showed that poverty is strongly correlated with lack of land which is the principal asset in the rural economy of Pakistan. Prevalence of poverty was found to be the highest among landless at 54.89 percent across rural areas in the country. Not only the poverty gap but also the

degree of inequality among the landless household was substantially high. A highly unequal landownership pattern is reflected by the fact that merely 1.0 percent households own greater than 35 acres and above land in Pakistan. This result is also supported by the Gini Coefficient of land holding which was considerably high at 0.6151 in 2001-02. It thus appears that highly unequal land distribution is the main manifestations of poverty in rural Pakistan.

Sohail.J.Malik(2003) conducted a research on agricultural growth and rural poverty in Pakistan. This paper explores the apparently "paradoxical" relationship between the reasonably high reported agricultural growth and increasing rural poverty in Pakistan since 1990. The relationship between agricultural growth and poverty reduction is generally assumed to be much more clear-cut. Study indicates that because of highly skewed distribution of land ownership the incidence of sharecropping has increased in recent years. The incidence of poverty among sharecroppers has been found to be considerably higher. Also the exploitation of tenants also leads to unequal terms of trade between the tenants and the non-tenants and contributes to the higher poverty faced by the tenants. Secondary data is used in case study to highlight the relation between agricultural growth and poverty.


Research type

The research is based on quantitative secondary data. The main aim of the research is to analyze and study the variables which have caused poverty to increase in Pakistan. The variables which are incorporated for carrying out research are unemployment, lack of education, inflation, male/female ratio, demographic age and number of dependents on household. The primary aim in this situation is to scrutinize that these variables have caused poverty to increase. The research will be conducted by analyzing secondary data.

Data type and research period

Secondary data will be used to analyze the reason for poverty in Pakistan. In secondary data time series method is used to observe the trends and understand the core reasons for poverty in Pakistan. The selected time period for time series analysis is 2000 to 2010. The data collected will be quantitative because this data collection technique is more helpful in understanding the overall trends of poverty.

Population, Working population and planned sample

Poverty is a nationwide issue which needs to be dealt. So the research is going to be held on total population of Pakistan. Since I am measuring the impact of different factors on poverty therefore the sample for this research will be the total population of Pakistan. Similarly the working population is also going to be the total population of Pakistan.

Sources of data

The data used for analysis would be taken from world development indicator, economic survey of Pakistan and World Fact Book. Data for all the variables would be time series data of last 10 years starting from 2000 till 2009. The inflation data used in the research is based on consumer price index. The unemployment rate used in the research is gathered from world development indicator. The values for literacy rate in Pakistan is taken from World Fact book. The data on unemployment is gathered from economic survey of Pakistan. Lastly the data on poverty in Pakistan is also gathered from a chapter from economic survey of Pakistan of 2009.

Research hypothesis

Ho: There is a significant impact of inflation on poverty.

H1: There is no relationship between inflation and poverty

Ho: Unemployment has a significant impact on poverty.

H1: Unemployment has no impact on poverty.

Ho: Literacy rate has a significant impact on poverty.

H1: Literacy rate has no impact on poverty.

Ho: Male/Female ratio has a significant impact on poverty.

H1: Male/Female ratio has no impact on poverty.

Ho: the demographic age has a significant impact on poverty.

H1: The demographic age has no impact on poverty.

Ho: GDP per capita has significant impact on poverty.

H1:GDP per capita has no impact on poverty


The data collected will be quantitative because this data collection technique is more helpful in understanding the overall trends of poverty. So keeping in view this factor, the data will be analyzed from software such as Minitab and regression will be done through Statgraphics.

Data analysis

Since the research is based on quantitative data. There for regression analysis will be used to find the impact of different independent variables on poverty. For achieving a more accurate result of regression analysis, two softwares Mini and Statsgraphic will be used.

Data interpretation

One's the data will be collected and analyzed, it will be interpreted from different angles. The data will be interpreted both in the form of equations as well as in detailed analysis of equations, tables and graphs.

Theoretical framework and variables under consideration

Dependent Variable: Poverty

Independent Variables


Lack of education


Male/female ratio

Demographic age


Operational Definitions

Literacy Rate

Percentage of the population of 15 years and older that is able to read, write and thus fully participate in the wider society.


The state of having no job; joblessness; The phenomenon of joblessness in an economy; The level of joblessness in an economy, often measured as a percentage of the workforce; A type of joblessness due to a particular economic mechanism; An instance or period of joblessness


Inflation is persistent increase in the price level of goods and services. Consumer Price Index. An inflationary indicator that measures the change in the cost of a fixed basket of products and services, including housing, electricity, food, and transportation.

Male/Female ratio

The male-female ratio is the ratio between male and female in total population. It is measured by dividing total number of male population in a country with the female population of that country.

Demographic age

Aging of population (also known as demographic aging, and population aging) is a summary term for shifts in the age distribution (i.e., age structure) of a population toward older ages. Demographic ageing designates an increase in the proportion of old people in a population.

GDP per capita

GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current local currency.

Statistical Analysis

Multiple Regression Analysis

Dependent variable: poverty head count


Standard T

Parameter Estimate Error Statistic P-Value


CONSTANT 1.95789E9 4.54508E7 43.0771 0.0148

gdp per capita -1089.24 240.297 -4.5329 0.1382

inflation 515079.0 30895.7 16.6715 0.0381

male ratio -103.555 2.34155 -44.2251 0.0144

primary -3.39274 0.277366 -12.232 0.0519

unemployment 100.727 2.7215 37.0116 0.0172

working age popul 72.2375 1.64988 43.7835 0.0145

Analysis of Variance

Source Sum of Squares Df Mean Square F-Ratio P-Value


Model 1.52982E15 6 2.5497E14 4333.44 0.0115

Residual 5.88378E10 1 5.88378E10


Total (Corr.) 1.52988E15 7

R-squared = 99.9962 percent

R-squared (adjusted for d.f.) = 99.9731 percent

Durbin-Watson statistic = 2.86828

Lag 1 residual autocorrelation = -0.451829


The output shows the results of fitting a multiple linear regression model to describe the relationship between poverty head count and 6 independent variables. The equation of the fitted model is

poverty head count = 1.95789E9 - 1089.24*gdp per capita +515079.0*inflation - 103.555*male ratio - 3.39274*primary +100.727*unemployment + 72.2375*working age population

Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant relationship between the variables at the 95% confidence level.

The R-Squared statistic indicates that the model as fitted explains 99.9962% of the variability in poverty head count. The adjusted R-squared statistic, which is more suitable for comparing models with different numbers of independent variables, is 99.9731%.

The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file.

In determining whether the model can be simplified, notice that the highest P-value on the independent variables is 0.1382, belonging to gdp per capita. Since the P-value is greater or equal to 0.10, that term is not statistically significant at the 90% or higher confidence level.

Regression equation

The regression equation is

POVERTY = 1.96E+09 - 104 Males + 72.2 population 15-64 + 101 Unemployed- 3.40 primary - 1088 GDP/Capita + 514290 inflation

Statistical Analysis

Dependent Variable: Poverty

Independent Variable: Number of males in total population

The regression equation suggests:

POVERTY = 1.96E+09 - 104 Males + 72.2 population 15-64 + 101 Unemployed- 3.40 primary - 1088 GDP/Capita + 514290 inflation

Keeping all the variables constant, decrease of 104 'Males in the population' increases 1 more person under poverty head count. On the other hand, P-Values of the variable come out to be 0.0144 which is lesser than 0.05. Thus, it rejects H0, and accepts H1. The Hypothesis is:

H1: Number of males in total population has significant impact on Poverty in Pakistan


Dependent Variable: Poverty

Independent Variable: Working population in the age bracket of 15-65 years

The regression equation suggests:

POVERTY = 1.96E+09 - 104 Males + 72.2 population 15-64 + 101 Unemployed- 3.40 primary - 1088 GDP/Capita + 514290 inflation

Keeping all the variables constant, an increase of 72 persons in 'working population in the age bracket of 15-65 years' increases 1 more person under poverty head count. Here, P-Values of the variable is 0.0145 which is lesser than 0.05. Thus, it rejects H0, and accepts H1. The Hypothesis is:

H1: Working population in the age bracket of 15-65 years has significant impact on Poverty in Pakistan


Dependent Variable: Poverty

Independent Variable: Unemployment

The regression equation suggests:

POVERTY = 1.96E+09 - 104 Males + 72.2 population 15-64 + 101 Unemployed- 3.40 primary - 1088 GDP/Capita + 514290 inflation

Keeping all the variables constant, an increase of 101 person getting unemployed out of the total working population increases 1 more person under poverty head count. On the other hand, P-Values of the variable come out to be 0.0172 which is lesser than 0.05. Thus, it rejects H0, and accepts H1. The Hypothesis is:

H1: Unemployment has significant impact on Poverty in Pakistan


Dependent Variable: Poverty

Independent Variable: Number of people with at least primary education

The regression equation suggests:

POVERTY = 1.96E+09 - 104 Males + 72.2 population 15-64 + 101 Unemployed- 3.40 primary - 1088 GDP/Capita + 514290 inflation

Keeping all the variables constant, one more persons gets under the line of poverty if there is a decrease of 4 persons who gets the chance to complete at least primary level of education.

P-Values of the variable come out to be 0.0498 which is lesser than 0.05. Thus, it rejects H0, and accepts H1. The Hypothesis is:

H1: Number of people with at least primary education has significant impact on Poverty in Pakistan


Dependent Variable: Poverty

Independent Variable: Gross Domestic Product per Capita

P-Values of the variable come out to be 0.1382 which is greater than 0.05. Thus, it accepts H0. The Hypothesis is:

H0: Gross Domestic Product per Capital has insignificant impact on Poverty in Pakistan


Dependent Variable: Poverty

Independent Variable: Inflation

P-Values of the variable come out to be 0.382 which is greater than 0.05. Thus, it rejects H0. The Hypothesis is:

H0: Inflation has significant impact on Poverty in Pakistan



The primary purpose of the research was to find out the impact of different economic factors on poverty. The economic factors used for this research were inflation, male/female ratio, primary education, demographic age GDP per capita. It is observed from the research that Pakistan is passing through worst poverty in its history. The reasons for poverty in Pakistan are number of internal as well as external factors both at micro as well as macro level. Different factors impact at different level on poverty in Pakistan. The living conditions in Pakistan are worsened but the facts about the poverty provided by the government are always underestimated. Although the data is available in excess about the poverty and its reason but still it is not accurate because of which its really difficult to gauge the exact level of poverty in Pakistan.

The basic findings of the research shows that there is a significant relationship between the dependent variable which is poverty and the 5 independent variable which are male/female ratio, completion of primary education, inflation, unemployment and demographic age. Whereas the relationship between GDP per capita and Poverty is insignificant. The reason for insignificant relation is multicolliniarity, as GDP per capita has economic relation with all other variables.

So keeping in view all the facts gathered and analyzed. It is quite obvious that Pakistan is facing the problem of extreme poverty and government policies have failed to eradicate it. Therefore in order to improve the poverty conditions in Pakistan a holistic plan is need to be made which address both internal as well external factors to eradicate the poverty in Pakistan.


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