When a country becomes richer (prosperous), it tends to revise its poverty line higher, with the exception of the United States, which is that the poverty line has remained essentially unchanged for almost four decades. For example, the European Union generally defines poor people as those who have per capita income below 50 percent of the median (average) income. As the median / average income increases, the relative poverty line also increases. In terms of identifying and targeting poor people, the poverty line is relatively sufficient to be used, and needs to be adjusted to the level of overall development of the country.
Low inflation makes it easy for the poor to manage economic risks due to the limited access and knowledge of the poor to protection institutions such as insurance and credit. As a result, for poor household groups, the impact of inflation has caused uncertainty which has caused them to be reluctant to invest both in the form of investment in human resources and business investment. Poor households are generally classified as having a high level of risk averseness, because they do not have access to adequate financial resources or limited assets. As a result, they generally have a higher cash ratio as part of the motive just in case. They are also reluctant to carry out new investment activities that contain risks. In this connection, inflation will increase the higher risk and cause poor households to become not involved in the process of economic growth. This risk averness also affects investment decisions of poor households. They are more concerned with investments that have a current and short-term impact compared to long-term investments such as education. Since the rate of return on the labor market is positively correlated with the level of education, the reluctance of poor households to make long-term investments not only causes their failure to participate in the wave of economic growth but also exacerbates income distribution which in turn affects the level of absolute poverty. The development of the level of income distribution in Latin American countries is evidence of the link between education investment and poverty levels and income distribution.
Further we present national poverty rates by religions groups. The poverty rates at Lakdwala lines are shown of rural and urban India and the country as a whole. There observations follow. First at the percentage level poverty rates shows a decline in case of Hindus, Muslims, Christians, Jains and Sikhs. Poverty among the Buddhists also declines. According to poverty rates in rural and urban areas combined Jains have the lowest poverty rates followed by Sikhs, Christians, Hindus, Muslims, and Buddhists. The prosperity among Jain and Sikhs is well known but lower level of the poverty among Christians relative to Hindus is less well known.
Economic problems such as poverty and inequality are found in all contemporary societies, although they are more visible and manifest in some societies than in other countries. Poverty can be said to be the most widespread and serious problem that faced the modern world conditions such as hunger, homelessness, preventable diseases, unemployment, and illiteracy as an element of poverty . There is a widespread assumption that poverty and inequality are two sides of the same coin . The evolution of the concept of poverty reflects changes in the theory and practice of development in general, and the analysis of causes of poverty in particular. As a result, measures of measurement, description and povertyanalysis have been widespread . 2.4 Relation of Fuel Price Increases and Basic Electricity
This paper aims to evaluate the impact of a microlending program on ameliorating measured poverty within its client population, with the aim of improving that impact. We analyze over 18,000 women micro-finance clients of the Negros Women for Tomorrow Foundation (NWTF), a database using the Progress out of Poverty (PPI) Scorecard as a measure of poverty. Analysis using both OLS and quantile multivariate regression models shows how observable borrower attributes affect the ability of clients to reduce their measured poverty. Loan size, duration, and the economic activity supported all have strongly identifiable effects. Moreover, estimates suggest which among the poor are receiving the greatest effective help by the program. Results offer specific advice to the NWTF and other micro-lenders: impact is greatest with fewer, larger loans in particular economic sectors (sari-sari, service and trade) but require patience as each additional year increases the client‟s average change in poverty score.
This chapter focused on analytical techniques to measure and understand the income or consumption dimension of poverty, inequality, and vulnerability. The techniques described ranged from developing a simple poverty profile to conducting panel regressions to examine vulnerability, and from using transition matrixes to examine the stability of welfare rankings to a decomposition of inequality measures. However, the range of tools that can be applied to better understand poverty will depend crucially on data availability. The richest understanding of income poverty can be gained if several rounds of multitopic household surveys are present, especially if they contain a panel component of identical households being visited at different points in time. The analysis of income poverty presented here should ideally be complemented with an examination of other dimensions of poverty and how the dimensions are related to each other. Determinants of different dimensions of poverty can then be compared and common factors singled out for policy interventions. For example, health povertyanalysis of the determinants of malnutrition often reveals that a mother's education is a key determinant of the nutritional status of her children. Income poverty can also be closely associated with the same variable so that policies that aim to improve female education can have important synergistic effects on both malnutrition and income poverty. However, analyzing the determinants of various aspects of poverty can also reveal important differences in the determinants, which would then imply that policymakers would have to make important choices as to which dimension of poverty they would want to tackle first.
correlated. In order to understand the threat that the problem of poverty poses, it is necessary to know its dimension and the process through which it seems to be deepened. The measurement of correlated multiple domains with respect to poverty, fabricates the new concept i.e. Multidimensional Poverty. Now theoretical and analytical evidence is ample, while remaining insoluble issues in povertyanalysis are related directly or indirectly to the multidimensional nature and dynamics of poverty (Thorbecke, 2005). Analysis on multidimensional poverty has occupied much attention of economists and policymakers, particularly since the writing of (Sen, 1976) and the rising of data availability for relevant research purpose. The justification behind this multidimensional measurement of poverty is based on the idea that income indicator is incomplete and its deficit leads to vague estimations of poverty (Diaz, 2003). Having said that, alternative dimensions such as health, educational attainment, social exclusion, and insecurity are often weakly correlated with income or expenditure (Appleton and Song, 1999). These poor correlations highlight the fact that measuring these additional dimensions enriches and provides additional information to the poverty picture (Calvo and Dercon, 2005). However, the strength of measurement lies in the construction of indices that capture the relative importance of each indicator in the total poverty picture. The weighting of each indicator is meant to reflect the strength of the relationship with ‘wealth factor’ for asset -based measurement as proposed by (Sahn and Stifel, 2000). While the most important component in poverty measures is identification, there are two main approaches in identifying the poor in a multidimensional setting (Alkire and Foster, 2007) i.e. “ union ” and “ intersection ” approach.
Poverty continues to remain a major challenge during the whole period of transition, since the collapse of communism and which is continuing even today. In this article, the macroeconomic trends in the Balkan region are treated in synthesized way, with a special emphasis on Kosovo for the years of transition. In addition, the paper is focused on some economic indicators that have direct or indirect impact on labour market policies and employment policies. The trend of these indicators is analyzed in terms of nominal and real convergence, aiming at the progress of the Kosovo economy during the years of transition in the process of integration into the current level where it is located, as well as the challenges that has faces in meeting other standards in political and economic system. The focus of this analysis are the employment policies as well as the structural reforms, institutional reforms of the labour market, policies for the reduction of the unemployment rates, generating of new work places, taking into account the fact that in Kosovo the unemployment especially at young people is very high. The purpose of this study is to identify the current state of poverty, considering that the state should take some measures to reduce its level by being based on market instruments of labour and employment policies, migration, remittances and their impact on the labour market, its structuring and their components in the Balkan region, but with particular focus on Kosovo. Poverty is a cycle that is repeated constantly and has negative impacts not only on the economy of a country but also on the lives of its citizens. Its causes are as complex as poverty itself. On the other hand, poverty reduction is as a result of economic growth. In the reduction of poverty, government plays a very important role. So, the government with its policies can cause an increase in the economic growth and then reduce the poverty level. The situation, instead of being relaxed, nowadays, it is experiencing difficult times. This is happing because the world today is undergoing through a global financial crisis which had started in the United States in 2008 and which has spread all around the globe. It can be said that this global financial crisis has been the longest that this world has recognized. For this reason, to the government of a country is added one more task, which is even more difficult, that through its policies to do the impossible in order to overcome this crisis and to send the respective country towards economic development, and thus to reduce poverty.
The remaining portions of Tables 7a and 7b report estimates beyond the scope of those reported by Acosta et al. (2008). The effects of remittances on poverty rates vary widely across state groupings and poverty lines. At the $2 per day poverty threshold, the Traditional region’s results closely resemble the national results, with a 1.66 percentage point reduction in the poverty rate, which results in a 15% reduction in the number of households living below the poverty line. The largest reductions in poverty across geographic regions occur in the Central region, where it is estimated that the poverty rate falls from 9.18% to 7.19%, or 1.99 percentage points. The Northern region’s 1.67 percentage point drop is the next largest reduction in poverty. Notably, the reductions in poverty are smallest in the most impoverished of the four regions, the SSE region, where the observed poverty rate is just over 15%. When broken down by migration intensity, the states in the Very High category fare the best at the $2 poverty line, with
employment generation. Thus effective utilization of agriculture sector in Pakistan will lead to increase in employment of the country which in turn reduces the poverty in a greater number. The result of negative impact of FDI on poverty can be justified in several ways. The inflow of FDI fills the gap between desired investment and domestically mobilized saving. It also improves the technology, management and labor skills in the host countries. The vicious cycle of poverty can also be broke out with the help of FDI. Further the benefits from FDI may consists of generation of employment, acquisition of new technology, development of human capital, increasing domestic investment, enhancing tax revenue and also cause to integration of international trade in the host countries. All these advantages of FDI contribute significantly to economic growth and high employment growth in the host countries and which ultimately causes the poverty to reduce. However, it is pertinent to note that the impact of FDI on poverty reduction depends on many factors. These factors include the quality of institution, the government policies, the quality of labor market and the economic environment in the host countries. The study further shows that education enrollment has significant negative impact on poverty in Pakistan. Education is o considered a major remedy for many problems faced by developed and developing countries and the role of education enrollment in the process of human development is well recognized. Providing better education to people is not only a goal itself for a better quality of life but also it has positive impact on the economic growth of a country (Rebelo, 1991). Education plays a great role in the economic development of a nation, thus educational enrollments are found to constitute a form of nation’s prosperity. It increases individual’s chances of employment in the labor market, and allows them to reap financial and no financial returns and gives them opportunities for job mobility which ultimately reduce the poverty from the country.
areas, while the distribution of public investments by region in 2012/13 shows an opposite case, in which investment was higher in Upper Egypt especially in the southern areas (Ministry of Planning, 2012). Actually, this trend of investment can explain the situation of poverty by region in Egypt over years. Over the period 1995/96-1999/2000, poverty has declined in the Metropolitan cities and increased in Upper Egypt and was at intermediate levels in Lower Egypt. The incidence of poverty increased substantially from 10.82% to 19.27% in urban Upper Egypt and from 29.32% to 34.15% in rural Upper Egypt. On the contrary, over the period 2010/11-2012/13, the urban governorates have seen the biggest rise in the poverty indicators (becoming more deteriorated). Moreover, the poverty rate has fallen in Upper Egypt, whether in urban or rural areas, and the difference was statistically significant. One of the main findings of the micro analysis is that improving educational levels in all regions will reduce the probability of being poor because of the positive relationship between the number of years of schooling and the earnings of an individual. Accordingly, it is important to present a general outlook on the public expenditure on education in Egypt. The percentage of public expenditure on education to the total public expenditure was 11.7% in 2010/11 and 2013/14. However, the percentage of public expenditure on pre-university education to the total expenditure on education has increased from 66.4% in 2010/11 to 68.1% in 2013/14, while the percentage of public expenditure on university education to the total expenditure on education has remained constant in 2011/12-2012/13 (21.4%) and reached 22.4% in 2013/14. As a percentage of GDP, the public expenditure on education was 3.4% in 2010/11 and 4.1% in 2013/14 (CAPMAS, Egypt in Figures, 2012, 2013, 2014 and 2015).
To do an effective Gender Analysis, both traditional and non-traditional methods can be used to collect data. Traditional methods include formal interviews and surveys, mapping, and statistical research through libraries and organizations. Non-traditional methods can include household interviews and focus-group sessions, informal conversations, walking tours observing community or organizational practices and other methods where there is participation by a diverse group of people.
private schemes will generate less antipoverty effects than public programs. We perform a cross-county analysis of the relationship between public and private social expenditures and poverty rates at one point in time. The material presented is only descriptive and does not explain poverty levels and poverty structure. Such an analysis should ideally be based on a theory, which would have to address at least the following cross-national differences: differences in labor markets that affect earnings of individual household members; demographic differences, such as the aging of the population and growth of single parent households, which affect both family needs and labor market decisions; and differences across countries in tax and transfers policies that not only affect family income directly, but also may affect work and investment decisions. 25 Two recent seminal books edited by Kakwani and Silber in 2007 and 2008 present the panorama of the many dimensions of poverty from various disciplines. A fully- fledged model should be developed to assess the relative performance of social factors and the economic development. Such a comprehensive approach is far beyond the scope of this paper. We simply employ bi-variate regressions on the relationship between social expenditures and poverty rates, so one could argue that omitted (macroeconomic) variables cause bias. Differences in social effort across countries at one point in time can be the result of cyclical factors.
Studies relating to household poverty and household vulnerability to poverty in the context of post- conflict districts of Teso-sub-region are mostly retrospective in nature. To the best of our knowledge, none of the studies so far have attempted to link social protection ex-ante measures in reducing household poverty and the relative impacts of social protection ex-post measures in addressing the household idiosyncratic and covariate sources of vulnerability. This distinction is important for policy and decision makers in designing anti-poverty policies and programmes, particularly policies relating to poverty prevention and promotion of those who are structurally poor by protecting and transforming their socioeconomic status. However, there are a number of studies that explored social protection measures in addressing household poverty dynamics in Uganda, that fall into this category of ex-post dynamic analysis. But also seems shorts in estimating the impact of social protection ex-ante poverty measures in reducing households idiosyncratic and covariate shocks in the dynamics related to the causes of poverty and vulnerability in rural Uganda especially among conflict affected households. Base on the foregoing we recommend that, to reduce household poverty in Katakwi and other post-conflict districts in Teso sub-region and others, state, multi-bilateral, national, regional and international social protection actors, need to build a concerted efforts that should be aimed at encouraging free, compulsory and quality education at least up to the basic level, easily accessible and quality healthcare social protection services, a population policy that would encourage a married couple to have at most four children or at most with a household size of 6, and the enabling environment that encourages hard-work
This study investigated the effect of poverty on health status in Kenya. According to findings from the Control Function Approach, increase in wealth index increases the probability of reporting own health as being very good and reduces that of reporting own health as being very poor, other factors held constant. The finding confirms that a decrease in poverty minimizes the probability of reporting poor health and increases that of reporting very good health. This may be due to higher purchasing power of the wealthy. Hence, wealthier people can afford balanced meals, clean drinking water, and good shelter. Thus, they are less likely to suffer from nutrition and water related diseases. They are also able to afford health care in case of illness/injury. The importance of poverty reduction in influencing the level of
The preliminary study of meso data at the district level and panel data of the sampled viI/ages made under the project ViIlage Dynamics Studies in South Asia(VDSA) in the two sampled districts of Orissa reveal interesting pictures with respect to poverty incidence, asset holding pattern, size class-wise land holding pattern, agricultural productivity, livestock owning and natural resource endowment. Poverty in Orissa, an eastern coastal state of India has been a matter of great concern for successive governments and planning authorities at the national and state levels. The eastern state has been under scrutiny by the national planning authorities and a number of poverty alleviation programme launched in the country have focused Orissa as a test case of impact of development initiatives. However, the state has failed to catch up with national poverty reduction efforts due to plethora of socio- economic, historical, political, administrative and natural reasons. It is estimated that during 2004-05, the incidence of rural poverty was 47 and for urban Orissa it was 44 as against the average poverty incidence of 26 for India. The social grouping of people under poverty in the state reflects that the poor scheduled tribes constitute as high as 76 in rural areas and 65 in the in urban areas respective category of population. The region-wise break up of rural and urban poverty in the stare indicates that the southern Orisso suffers from highest incidence of poverty followed by western, northern and eastern Orissa. The districts like Nuapoda, Balangir, Kalahandi, Koraput are grouped under highest poverty incidence region in the state. The two district sampled for study namely Bolangir (48.79 of population below poverty) under Western Orissa and Dhenkanal (47.53 of population below poverty) under north eastern high lands reveal different scenarios of poverty under different social groupings. The analysis of Ginni coefficient and Theil entropy measures in one of the sampled villages in Dhenkanal district under the project were found to be 0.7and 0.9 respectively. There is differential pattern of land holdings which highly skewed in favour of large farmers in all the study villages. The occupational composition of population, sex ratio, the age group distribution of population, farm mechanization, agricultural productivity and migration pattern also reveal diversified pattern under different size class and social groups.
2.1.3. Panel Data Regression Analysis To know the influence of financial inclusion to the other variables, we use panel data regression analysis. Panel data is a combination between time series data and cross section data, which the same cross section unit is measured in different time. Panel data analysis is also used to observe the relationship and influence between the dependent variable (financial inclusion) and one or more independent variables (poverty and income inequality). Generally, there are three techinques that can be used to estimate data panel regression model, they are Common Effect Model (CEM), Fix Effect Model (FEM), and Random Effect Model (REM).
Poverty is both a cause and an effect of environmental degradation, there is a circular link between the two, as with many international development challenges, and is very complex. Issues surrounding the environment, economics and policies are all inter-related through the way human beings interact both with each other and with their immediate environment. Whilst, environmental problems are expressed in largely generic terms such as climate change, these problems are of particular concern where they are localized and are immediate issues, which are not viewed remotely by vulnerable or marginalized groups in many developing countries. These affect the poorer sectors of the population as the problems are directly related to household food security.
An efficient network of SMEs in Pakistan is prerequisite for the establishment of robust industrialization. Government of Pakistan has declared SMEs as one of the four important drivers of growth for the Pakistan economy. SMEs play very important role in value addition and employment generation in Pakistan. SME sector is highly laborintensive and this sector provides employment to the major part of nonagriculture labor force in Pakistan, Economic Survey (2004 05) issued by Ministry of Finance, Government of Pakistan. In Pakistan, SMEs constitute 90 percent of the business constitutes. This sector provides 80 percent of the employment opportunities to nonagriculture labor force, 25 percent of the total exports, 35 percent of the manufacturing value added and contributes more than 30 percent to the GDP of the economy, Economic Survey (2009 10). Onefourth of the export earnings are generated by the output of this sector, Economic Survey (2001 02). SME sector in Pakistan is comprised of cotton weaving, wood and furniture, metal products, art silk, grain milling, jewelry, carpets, sports goods, pottery, dairy and poultry, fisheries, food and catering, and slaughtering. The situation of industrial sector in Pakistan is bleak. The largescale industries are, mostly, urban based where as the most of the SMEs are located in small towns and rural areas. These SME units located in rural localities are of great importance for the provision of employment to poor rural workers, Qureshi and Ghani (1989). SME sector in has got very much importance in Pakistan. A welldeveloped modern SME sector, in a more open economy, is a complement. Many developing counties have been reaping the benefits of the export orientation of this sector, Berry (1998). The present examines the impact of small scale industries performance on poverty levels in Pakistan.