The study will be conducted from most of the world’s poorest countries which will mostly include Africa, Asia and Latin America. Most of the worlds most affected regions come from sub-Saharan Africa and most of the research will be centred on these regions. Major studies have been conducted on finding out various mechanisms that can be used to eradicate poverty in Africa and they will be used as case studies for comparison purposes. The most common studies are in health care and this can not be isolated as a case study since lack of proper health facilities is attributed to poverty and this prevails mostly in the third-world countries. The research method used will be a Qualitative study which will help us in understanding the depth and nuances of processes that produce and also reproduce poverty in the third world countries. Advanced qualitative techniques will be used to discover processes and interdependencies related to non-quantifiable dimensions of poverty such as vulnerability and powerlessness.
During this research, there will be no human interaction as a source of data. Direct information from the affected people will not be obtained due to the high number of people that are poor and also it might be very expensive to conduct a worldwide research especially when more than half of the human race is below the poverty line. Data samples will be obtained from many regions which are considered to be underdeveloped and provide microloans to the people. Areas which do not give out microloans to its people or those which financial services are limited will also be analysed and this will be used as a comparison basis. This will help in accessing the regions that are developing as a result of the micro loans and those that are not.
The women population will also of importance in determining the selection of the study area. Third world countries with most women will be considered and also those in which the population of women is not great as compared to the men’s population. The financial institutions data on the number of recipients of the microloans will be used.
Determination of the sample size can not be a definite figure since of the large scope of research involved. The number of countries in to be studied will be not less than 20 with major emphasis being on the worst hit areas with poverty. Due to the high population growth of the world, new areas will be studied to help build a comprehensive report on the effect of microlending in the third world countries. This is because as the population increases the number of people living below the poverty line also increases.
The major sources of data will be gathered statistics and figures of countries primarily from the World Bank Development Indicators. Books and journals will be used to assist in getting detailed information about the third-world countries economic status. Financial reports from banks preferably banks which provide financial resources to the third world countries will be used. These will include the number of people applying for loans and also the loan defaulters. Data will be collected on the major activities the loanees mostly engage in after being given the loan. The nation’s economic reports from the economists who mostly calculate the economic growth of the country will be of vital importance.
African Development Indicators will be used which are drawn from the World Bank Africa Database which is a publication that provides the most detailed collection of development data on Africa in one volume. Africa will be a key region of study since most of the people living there are poor based on the fact that they live by less than one US $ a day. Investment climate surveys which contain data on the investment climate in more than 71 countries based on surveys by 40,000 firms. These enterprise surveys measure business perceptions of the investment climate and can be used to analyze the link to job creation and productivity growth. This is due to the fact that the microloans tend to provide a source of capital to the people in starting up businesses which create job opportunities leading to growth in production and improving the living conditions of the people. This in result leads to economic growth. The Private Participation Infrastructure (PPI) Project Database which contains data on 3000 projects in 150 low-and middle income countries. This will help in viewing the changes in the economic activities of the third world countries.
Sub-Saharan Africa being one of the main focus of poverty, the Sub-Saharan Africa data profile will assist us by providing data such as population, life expectancy, GDP and more. The Millennium Development Goals will aid us in reviewing the changes put in place to help countries which have poor economic growth improve the main focus being on microlending activities and mechanisms that have been put in place in those regions. The knowledge Economy Benchmarking which is an interactive database that provides more than 80 structural and qualitative variables to measure countries’ performance on the four knowledge Economy (KE) pillars: Economic Incentive and Institutional Regime, Education, Innovation, and Information and Communications Technologies. This will be used together with the Global Development Finance which includes detailed information of a country’s’ financial activities and reports.
For small areas the indirect estimation techniques will be used and it typically combines two sources of socioeconomic data, namely, household surveys and censuses. More recently, with advances in computing technology and the proliferation of geographic information systems, innovative efforts have been made to link satellite data with socioeconomic data such as those found in household surveys. The basic method used to construct these data sets is the same as those used for consumption-based small area poverty and inequality methods. The richness of household surveys is combined with the depth in coverage of censuses to generate food security/welfare estimates for sub national areas in the following countries: Mexico, Ecuador, Kenya, Malawi, Bangladesh, Sri Lanka, and Vietnam. These studies illustrate spatial analysis approaches to poverty assessments examining the impact of environment and geographic location on rural poverty and agricultural development.
Though spatial information may be used in the process of generating these estimates, the spatial data is generally separated prior to the analysis, reporting and dissemination of the poverty estimates. Thus, CIESIN’s database of sub-national small area estimates contains poverty and inequality data with reconstructed boundary information, using basic geographic information system (GIS) tools.
This concerns many issues which include:
This pertains to the person who has legal rights to the data, who retains the data after the project is completed including the PI’s to right be to able to transfer data between institutions.
This pertains to collecting project data in a consistent, systematic manner (i.e., reliability) and establishing an ongoing system for evaluating and recording changes to the project protocol (i.e. validity).
This concerns the amount of data that should be stored enough so that project results can be
This relates to protecting written and electronic data from physical damage and protecting data integrity, including damage from tampering or theft.
This refers to the length of time one needs to keep the project data according to the sponsor’s or
founder’s guidelines. It also includes secure destruction of data.
This pertains to how raw data are chosen, evaluated, and interpreted into meaningful and
significant conclusions that other researchers and the public can understand and use.
This concerns how project data and research results are disseminated to other researchers and the general public, and when data should not be shared.
This pertains to the publication of conclusive findings, both positive and negative, after the project is completed.
There are various methods used for data analysis. The following methods will be used:
After the research findings a code will be used to label the data to be used during data analysis. A good code should include:
Definitions of what each theme concerns (ie, the characteristics or issues constituting each theme)
Descriptions of how to know when each theme occurs (ie, how to “flag” themes)
Descriptions of any qualifications or exclusions to identifying themes
Examples, both positive and negative, to eliminate possible confusion when looking for themes
These are the software programs that assist with coding, management and analysis. There are two types of qualitative data management software programs that are available. One is a coding and retrieval program that facilitates a more complex coding schema than the researcher may be able to perform manually. This allows the researcher to retrieve text segments throughout the data set. The second is a theory-generating program that facilitates exploring relationships between coded categories in one file and theoretical explanations in another file.
Reporting the findings
After the investigation has been conducted the data will be represented in a form of a report. This will include a detailed report which might include schematic drawings or using a conceptual framework.
Information should be protected from unauthorised observation. The participants should be notified on any unforeseen changes in the investigation and the findings obtained.