Economic health and education aspects of poverty

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Whenever there is a research on poverty, it is likely to take into consideration the economic aspect, education and health aspect of poverty into consideration. There is no doubt the aforementioned are today's leading indicators in poverty however we have not been able to achieve much with the economic approach. Under no circumstances I am negating the fact that Health and Education are not significant indicators of poverty however in this research paper I have tried to divert attention towards the role of civil society towards poverty alleviation. This is surely not a new approach but it is imperative that with the changing dynamics of the Middle East, it is evident now that even today collective action by the society can bring about a change in society and hence should focus on the role of society in alleviating poverty. I have chosen 6 independent variables and one dependent variable as shown in the above table. Instead of taking the conventional independent variables such as GDP per capita, provision of health services and expenditure on education, I have tried to integrate a few socio-political variables in my model. In the following paragraphs I will be justifying my selection of the variables.

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Theoretical Justification

Political Imprisonment Rating refers to the incarceration of people by government officials because of: their speech; their non-violent religious practices including proselytizing; or Their membership in a group, including an ethnic or racial group (CIRI Variables List & Short Descriptions, 2011). This variable will measure the degree of suppression by the government towards non-violent opposition. Under Civil Liberties and the Role of Civil Society in Poverty Alleviation initiative heading of the Literature Review, the articles that were referred to put forth the idea of an active civil society against the inefficiencies of the government, and demand a fair and an efficient policy implementation to alleviate poverty from society. One of the reasons why developing countries take a lot of time to break free from the poverty trap is because of the lack of voice and accountability in the society. We could have taken Voice and Accountability variable to assess the freedom of speech but the Political Imprisonment Rating gives a better and a more accurate angle to analyze how many people exercising the right to voice their opinion against the government or political leaders were suppressed. More the people are allowed to voice their opinion and concerns more will be the pressure on the government to take their issues into consideration. And the issue in Pakistan at the moment that requires immense attention is the increasing rate of poverty and inequality in society. Therefore it is imperative that the poor have the right to question the decisions of the government or the educated/civil society class intervene on their behalf. One of the reasons why developing countries such as Pakistan have drastic changes very often is because people are afraid of being silenced by the inhumane law enforcement agencies. Therefore more you listen to people or allow people to be expressive, the better the government will know as to what people want and how they want it; improving accountability and achieving the end result; accommodating the poor.

Dummy for Political Regime

Pakistan has been a victim of numerous dictators and democratically elected governments. It is widely believed that democratically elected governments are better able to alleviate poverty is because they are the representatives of the people and they have been elected by the people of Pakistan, however statistics show otherwise. Pakistan has seen economic growth and improvement in the provision of education, health and other development projects during a dictator rule. For that matter, I have decided to take Dummy for Political Regime as an independent variable. By taking this variable against poverty headcount ratio in the model estimation into consideration we will be able to analyze whether or not there is a significant relationship between the type of political regime in place and the poverty headcount ratio.

Unemployment Rate

The lack of employment opportunities for the poor is considered to be one of the causes of increase in poverty headcount ratio. Therefore, in order to determine whether unemployment rate has a significant relationship with poverty headcount ratio or not I have included the inverse of unemployment rate in the model. The inclusion of this variable is also justified by Hossain, N., et. al., (1999) as even in the article highlights the fact that employment opportunities is one of the reason why the poor stay poor and furthermore, the civil society is also to be blamed for this as they are not large employers.

GINI Index

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GINI Index is a very important variable and has been relied upon by many researchers to investigate the prevailing level of inequality in a country. However, by including GINI Index in our model estimation we tend to analyze the relationship between income inequality and poverty headcount ratio.

Empowerment Rights Index

We have mentioned Freedom of speech in the political imprisonment rating but to analyze the freedom to movement (Foreign and Domestic), Freedom of Speech, Freedom of Assembly and Association I have included the Empowerment Rights Index in our model in order to determine the relationship with poverty headcount ratio. This will show us whether the freedom of speech and other rights do actually reduce poverty or not. (CIRI Variables List & Short Descriptions, 2011)

Freedom of Assembly and Association

To assess specifically the Freedom of Assembly and Association we include the Freedom of Assembly and Association variable in our model estimation. This variable will help us analyze the freedom of people to assemble and freedom to associate with political parties and other organizations such as trade unions to fight for their rights. Furthermore, by including the variable in our model we will be able to pass our analysis as to whether or not actually freedom of speech affects poverty headcount ratio (CIRI Variables List & Short Descriptions, 2011).

Poverty Headcount Ratio

There are numerous proxies that are used while measuring proxies, for instance, GDP per capita, aid per capita or other rural related variables, but model estimation using Poverty Headcount ratio along with variables measuring civil society's role is far more efficient.

Variable References

Statement of Research Hypothesis

Hypothesis 1

H0: There is an insignificant relationship between POLPRIS and Poverty Headcount Ratio

H0: B=0

HA: There is a significant relationship between POLPRIS and Poverty Headcount Ratio

HA: B≠0

Hypothesis 2

H0: There is an insignificant relationship between Empowerment Right Index and Poverty Headcount Ratio

H0: B=0

HA: There is significant relationship between Empowerment Right Index and Poverty Headcount Ratio

HA: B≠0

Hypothesis 3

H0: There is an insignificant relationship between ASSN and Poverty Headcount Ratio

H0: B=0

HA: There is significant relationship between ASSN and Poverty Headcount Ratio

HA: B≠0

Hypothesis 4

H0: There is an insignificant relationship between Dummy for Political Regime and Poverty Headcount Ratio

H0: B=0

HA: There is a significant relationship between Dummy for Political Regime and Poverty Headcount Ratio

HA: B≠0

Hypothesis 5

H0: There is an insignificant relationship between Unemployment rate and Poverty Headcount Ratio

H0: B=0

HA: There is significant relationship between Unemployment rate and Poverty Headcount Ratio

HA: B≠0

Hypothesis 6

H0: There is an insignificant relationship between GINI Index and Poverty Headcount Ratio

H0: B=0

HA: There is a significant relationship between GINI Index and Poverty Headcount Ratio

HA: B≠0

Elements of Research Design

Type of Research

Applied Research

Study Setting

Natural Study Setting

Nature of Data

Time Series

Unit of Analysis

Participation of civil society in poverty alleviation initiatives

Reference Period

1981 - 2009

Research

Secondary Research

Data Collection Preferences

Poverty has always attracted controversial debate where ever it is discussed all over the world. To obtain facts and figures on poverty is not a difficult task as most of the governments have their data published in yearly statistical publications. Therefore to obtain data on poverty headcount ratio our preference was to obtain data from a government publication such as the Economic Survey of Pakistan or Pakistan's Handbook of Statistics. Variables concerning the characteristics of the civil society are widely available however my aim was to acquire the required data from WDI but then I wanted a more reliable and purpose built source in order to improve the results and accuracy of my model. Therefore, my preference was to gain data from an international source which was credible, therefore I gathered data from Economic Intelligence Unit, World Resource Institute and POLCON database. Unemployment data could not be authenticated from any government publication therefore I opted for World Bank databases for the required data.

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Data Collection and Related Procedure

I started off by going through the World Development Indicator and Global Development Finance Index to search for the required data on my selected variables. After going through the WDI and GDF database I realized the fact that these respective databases were not reliable as far as referring to civil society characteristics such as voice and accountability, and participation of the civil society were concerned. Therefore, before moving to an alternative source for obtaining the aforementioned variables, I decided to search for the poverty headcount ratio. Once again I made an unsuccessful attempt to gain the data from WDI and GDF. Data availability for Pakistan was becoming a cause of concern, but with the guidance of my supervisor, I referred to Pakistan's own statistical publications. Therefore, I managed to obtain poverty headcount ratio figures from the hard copies of Pakistan's Economic Survey available at our institution's library. There was a lot of data missing but I opted for interpolation of data to predict the missing data. Furthermore, with regard to civil society factors/variables I gained access to World Research Institute's database, Freedom House database, POLCON database and World Governance Indicator. The data obtained from the aforementioned sources were overlapping; confirming that they were accurate however, many individuals in my batch were using the aforementioned databases, and therefore I decided to find alternative sources to gather data on my variables. I searched on Google "Human Rights Data Project", the first search result was from a Harvard database; which was not possible to access therefore when I randomly checked the second result which was CIRI Human Rights Data Project. I came across the variables that I wanted and they were obtained with a more thorough and comprehensive methodology. Therefore, Freedom of Assembly and Association, Political Imprisonment and Empowerment Rights Index were obtained from CIRI Human Right Data Project.

Statement of Analytical Approach and Methodology

In this portion I will be highlighting as to how I will be going about estimating my model. Estimating a model using civil society variables is a very tricky task. In order to avoid any sort biases or overlapping of results I decided to estimate 3 models with the same dependent variable; poverty headcount ratio. As economic factors are given priority when tackling poverty, but as we are using variables that assess the role of the civil society, we need to take cautious and analyze the relationship of Empowerment Right Index, Freedom of Assembly and Association and Political Imprisonment with the dependent variable along with the other independent variables; dummy for political regime, unemployment rate and GINI Index. In other words, dummy for political regime, unemployment rate and GINI index were used in all the three models. The variables were used in their existing mathematical form to estimate the model besides unemployment rate. Theoretically speaking unemployment has a direct relationship with poverty headcount ratio; if unemployment goes up poverty headcount increases, however for mathematical purposes and to get the hypothesized signs I estimated all three models with the inverse of unemployment rate. Therefore here onwards I will be referring to the variable measuring unemployment as 1/unemployment. The first model would be estimated with POLPRIS, Dummy for Political Regime, 1/unemployment rate, GINI Index as independent variables and Poverty Headcount Ratio as a dependent variable. The second model was estimated using the same variables; however instead of POLPRIS I have used NEW_EMPINX and ASSN in place of POLPRIS. Civil liberty indexes do not fluctuate as often as other economic or any other variables; therefore I did anticipate p-values of a few variables to be insignificant and R-squared to be less than the respectable benchmark of 90% and above. In case we yield the aforementioned results, I have referred to sufficient literature to support the inclusion of the aforementioned variables if the need arises.