Academic literature on the topic 'Headcount index'

AbstractThis study examines the impacts of fiscal capacity on the acceleration of poverty alleviation through a dynamic simultaneous equations model using empirical data of 23 provinces and conducting historical simulation. The increasing of fiscal capacity from local taxes and tax-revenue sharing have signicant impact on poverty reduction, particularly in agricultural household, which has the largest share in number of poor in Indonesia indicated by larger decline of agricultural headcount index than industrial and trade headcount index. However, the increasing of General Allocator Fund/Dana Alokasi Umum (DAU) has negative impact on agricultural headcount index. The policy implication is to increase revenue from taxation by local governments as the impact is more effective in accelerating poverty reduction.Keywords: Fiscal Capacity, Poverty Reduction, Policy Simulation AbstrakStudi ini menganalisis dampak kapasitas fiskal dalam mempercepat pengentasan kemiskinan di Indonesia melalui jalur pertumbuhan pro-poor melalui model persamaan simultan dinamis atas data empiris 23 provinsi dan simulasi historis. Peningkatan kapasitas fiskal dari pajak daerah dan bagi hasil pajak berdampak paling besar dalam menurunkan kemiskinan terutama di rumah tangga pertanian yang mendominasi jumlah penduduk miskin di Indonesia di mana headcount index pertanian turun lebih besar dibandingkan headcount index industri dan perdagangan. Sebaliknya, peningkatan Dana Alokasi Umum (DAU) berdampak negatif pada kemiskinan pertanian. Implikasinya adalah pemerintah daerah perlu meningkatkan penerimaan dari perpajakan karena dampaknya lebih efektif mempercepat pengentasan kemiskinan.Kata kunci: Kapasitas Fiskal, Penurunan Kemiskinan, Simulasi Kebijakan

The analysis and the comparison of poverty between regions and countries are important topics in social sciences, which have relevant demands of many national (Cáritas, Intermón Oxfam, Cruz Roja, etc) and international (UN, World Bank, OECD, Eurostat, IMF, etc) agencies and organizations. One of the most common poverty indicators in practice is the headcount index, which analyzes the proportion of individuals considered as poor in a population. In this paper, we first analyze the impact on the headcount index when different sampling designs are considered. Note that this study is based on real data sets taken from different countries of the European Union, and the empirical measures for comparisons are based on different Monte Carlo simulation studies. For instance, we observe that stratified sampling has the best performance in comparison to alternative sampling designs. Post-stratification performs similar to simple random sampling without replacement, and the use of auxiliary information provides similar results to ones derived from stratified sampling. Second, we also analyze the empirical performance of different variance estimators under the commented sampling designs. We conclude that they have a similar empirical performance, and they provide, in general, confidence intervals with desirable coverage rates.

The aim of this article is to investigate the claim that tourism development can be the engine for poverty reduction in Kenya using a dynamic, microsimulation computable general equilibrium model. The article improves on the common practice in the literature by using the more comprehensive Foster-Greer-Thorbecke (FGT) index to measure poverty instead of headcount ratios only. Simulations results from previous studies confirm that expansion of the tourism industry will benefit different sectors unevenly and will only marginally improve poverty headcount. This is mainly due to the contraction of the agricultural sector caused the appreciation of the real exchange rates. This article demonstrates that the effect on poverty gap and poverty severity is, nevertheless, significant for both rural and urban areas with higher impact in the urban areas. Tourism expansion enables poorer households to move closer to the poverty line. It is concluded that the tourism industry is pro-poor.

The purpose of this research is to assess the role played by Baitul Maal Wattamwil (BMT) in increasing welfare of its member. This research adopts a quantitative approach through empirical analysis using Pahlawan Baitul Maal Wattamwil (BMT) located in Tulungagung as the subject of research.Several tools of analysis used in this research are: The Headcount Ratio, The Poverty Discrepancy Ratio, The Income Discrepancy Ratio, The Fooster, Greer and Thorbeck (FGT) index and the Threshold of Trade.

Poverty is one of the main problems facing Indonesia to date, as the capital of Central Java City Semarang also can not be separated from this poverty problem. Although the number of poor people from year to year decline, but in terms of proportion to the total population of Semarang City, the number of poor people reached 20%. One instrument that can help reduce poverty is zakat. This study aims to analyze the impact of zakat as poverty reduction with zakat approach and with zakat. The analytical tool used in this research is poverty indicator consisting of headcount ratio, poverty gap index, income index gap, Sen index and FGT (Foster, Greer, Thorbecke) index and CIBEST Index. The find show that zakat can reduce the poverty rate and also can improve the level of welfare of a family, both material and spiritual.

Background: Poverty has been in existence for many years and continues to exist in a large number of countries. Poverty is “pronounced in wellbeing” where wellbeing (and poverty) in broader term, focuses on the capability of the individual to function in society and poor people often lack key capabilities, they may have not adequate income, education, or be in poor health or feel powerless or lack of political freedoms. In Nepal, despite the decreasing trend in poverty incidence, still the current prevalence is very high with the comparison of other countries. Objective: To identify, compare and decomposition of different poverty measures by rural urban area and ecological belt in Nepal. Materials and Methods: Data set of Nepal Living Standard Survey (NLSS) conducted by Central Bureau of Statistics in 2011 consisting of various variables related to food, non-food consumption, income, demographic, socioeconomics, etc., have been used for analysis. In order to measure the poverty, different measures such as head count ratio, poverty gap, poverty severity, Watts index and Sen-Shorrocks-Thon index were used. The comparisons of different poverty measures across different variables were attempted including use of appropriate poverty curves. The decomposition of poverty indices by consumption components using the Shapley value along with Lump-Sum Targeting approach has been applied. Results: Average per capita consumption is 34186.5, the head count index, poverty gap and poverty severity of Nepal are 0.2518, 0.0545 and 0.0182, respectively. The poverty measures of rural area are higher than the urban area, and the incidence of poverty is highest in mountain ecological belt. Food and non-food component allows to 46.39% & 28.42% of the total population to be non-poor of headcount index, 60.19% & 34.34% for poverty gap index and 59.96% & 38.20% for poverty severity, respectively. Conclusion: For both within and overall population, rural area has the higher impact than urban area and each measure of poverty in mountain is significantly higher than hill and terai. To reduce within group headcount index and poverty gap, policymakers should give more focus to rural area and mountain region.

Although Vietnam’s economic growth and poverty reduction for almost three decades have been remarkable, growth for poverty reduction is unequally distributed across the nation. The paper examines the cause of poverty and the impact of provincial economic growth on poverty alleviation, using the data of 63 provinces in Vietnam. The elasticity of poverty with respect to provincial economic growth is employed (the elasticities of headcount index, poverty gap index, and squared poverty index with respect to provincial economic growth) to identify the provinces where pro-poor growth has occurred. The elasticity of poverty with respect to provincial Gini coefficient is examined to identify the impact of expenditure inequality on poverty. The simultaneous equation system is estimated to analyze not only direct and indirect effects of the related variables, but also the causality effect between economic growth and the poverty elasticity with respect to both growth and the Gini coefficient.

<p>Poverty is a fundamental problem faced by the people of Indonesia. This thesis discusses the empirical the charity if charity has mustahiq poverty rate using poverty indices and income mustahiq Determination program at Tegal village and the village of Kampung Anyar Babakan Sabrang, Ciseeng district, Bogor regency. Determination Program is a poverty reduction and empowerment of the poor by the Institute Amil Zakat Wallet Dhuafa Republika, Foundation for Community Empowerment, and Governmental Cooperative Self Determination. This study used FGT index consisting of headcount index (H), the depth of poverty (P1) and severity of poverty (P2). The findings of this study indicate that the poverty index mustahiq measured using FGT index, the poverty rate mustahiq will increasingly come down once they join the program endeavor. It can be concluded that the income per capita mustahiq significantly affected by income from a job / business which uses funds from the Program Determination, activity mustahiq work, and the number of families mustahiq the load.<br />Keywords: Poverty, Zakat, FGT index</p>

Tem-se falado demasiadamente sobre a distribuição espacial do pobre. Quanto mais desagregado o mapa, mais perfeita é a sua visualização, maior a evidência da heterogeneidade da pobreza e melhor o entendimento da maneira com que ela é formada e como pode ser combatida a partir de políticas públicas localmente específicas. O Rio Grande do Sul apresenta a pobreza distribuída de forma heterogênea por todo o território gaúcho (medida pela proporção de pobres - PP - e pelo índice de pobreza humana municipal - IPH-M), o que é corroborado a partir dos mapas de pobreza apresentados. A hipótese de que há aglomeração ('clusterização') da pobreza e não-pobreza no Rio Grande do Sul é confirmada para os dados fornecidos pelo IPEAdata para o ano 2000. Para tanto se buscou apresentar as definições de pobreza e as formas mais usadas para a sua mensuração e as dificuldades e os benefícios do mapeamento da pobreza, chamando a devida atenção ao fato que as dimensões e características da pobreza se manifestam de forma diferente quando o espaço é considerado.
There has been a lot of debate about the space distribution of the poor. The more disaggregated the map, the more perfect the evidence of poverty; aggregated national-level poverty data may obscure considerable regional variation and can bias public policies to fight poverty. Rio Grande do Sul State has its poverty (measured by the headcount index and by the human poverty index) distributed in a heterogeneous way throughout the 'gaucho' territory, what is corroborated by the presented maps of poverty displayed in this study. The hypotheses that there is a cluster of poverty and non-poverty in Rio Grande do Sul is confirmed when using the data supplied by IPEAdata for the year 2000. The confirmation was possible thanks to the use of spatial econometrics tools. To achieve this goal we presented the definitions of poverty and the most used ways to measure it and also the difficulties and the benefits of poverty mapping, giving proper attention to the fact that the dimensions and the characteristics of poverty occur in a different way when space is considered.

This paper analyses rural poverty in Ethiopia using the 1997 round of household survey data from the Ethiopian Rural Household Survey. Poverty measurements are estimated using a consumption based two-step procedure through the implementation of the Foster-Greer-Thorbecke model. The results indicate that the incidence of rural poverty is high for villages that have lower conditions for agriculture. These findings imply that poverty reduction can be possible through effective policies toward improving the conditions for agriculture in the rural areas. Moreover, examination of the connection between different socioeconomic characteristics and poverty indicates that households consisting of household heads with a higher age and availability of farmland are relatively less poor. However, households where the household head has completed at least primary school suffer from most incidence of poverty. Furthermore, this study use three different definitions of poverty in connection to well-being to determine poverty. It is possible to state that these measurements are different modifications of each other with common variables and follow the same trend. The results of the paper may increase our understanding of the nature of rural poverty in Ethiopia and help in providing different poverty reducing policies, for the specific survey round.

The aim of this dissertation was to analyse the effect of socio-economic factors on poverty in Nyakallong. Nyakallong is a former Black township in the Free State Province of South Africa. The effect of the socio economic factors on poverty was analysed using an econometric model. The analysis was based on data collected by the researcher and three fieldworkers who conducted a survey of 412 households in Nyakallong in 2009. To calculate poverty rates and the effect of socio-economic factors, data relating to the area was used. Poverty was defined and then measured for the township, and the profile of both the whole and the poor population was determined. The following poverty lines are used in South Africa – PDL, MSL, MLL, SLL, HSL and HEL. The HSL, which is defined as an estimate of the theoretical income needed by an individual household to maintain a defined minimum level of health and decency in the short term, was used as a measure of poverty in the area. The headcount index, poverty gap ratio and the dependency ratio were also used to measure poverty. The headcount index was found to be 0.472 for Nyakallong, meaning that 47.2% of all household’s income is below their respective poverty line. Poverty rate in Nyakallong was found to be 48.5% which is almost similar to the poverty rate of 49.1% for the Free State province, while poverty rate in Kwakwatsi was found to be 62.1%. The analysis of the sources of income of the poor showed that government grants constitute 64% of household income, with the old state pension grant alone contributing 16% to household income for a poor family. In Kwakwatsi, government grants contributed 38.4% of poor household’s income, with the old state pension grant having contributed 40.6%. On average, the whole population has a monthly income of R2 938, 35 compared to R1 140 which is received by the poor population; while in Kwakwatsi, the poor population received a monthly income of R688 and the whole population received an average of R1401.01. The expenditure patterns for the whole sampled population show that 39.7% of household income goes to buying food, compared to 44.3% for the poor sampled population of Nyakallong. In Kwakwatsi, poor population spent 49.2% of income on food and the whole population spent 33.4%. In Nyakallong, 50% of the whole population and 53% of the poor population was found to be economically inactive. In Kwakwatsi, 44% of the whole population and 56% of the poor population was found to be economically inactive. The unemployment rate of the poor in Nyakallong is 95.6% compared to 69.9% of the whole population. In Kwakwatsi 86.9% of the poor population and 79% of the whole population were unemployed. The dependency ratio was found to be 6 among the poor population and 2 for the whole population of Nyakallong, while in Kwakwatsi it was found to be 7 among the poor population and 4 among the whole population. The study analysed the socio-economic determinants of poverty in the area. The data was evaluated using hypothesis testing for statistical significance of the parameters. It was established that there is a positive relationship between education and the poverty gap ratio although it is statistically insignificant. It was also found that there is an inverse relationship between employment and poverty ratio. This complies with theory. The results also showed a positive relationship between household expenditure and the poverty gap – this is what was expected, because expenditure is the reduction of resources. On gender, the results confirm the generally held hypothesis that female headed households are poorer compared to their male counterparts. The results show that poverty is high among female headed households compared to male headed households. Household size was measured by the number of people staying in a given house. The household size was found to range from one to eleven members per household. The average household size was found to be 4.2 in Nyakallong, 3.9% in Kwakwatsi and 3.4% in the Free State. Household size is an important variable in determining poverty – increasing the household size by 10% is likely to increase the poverty gap of the household by about 1%. This might seem not significant, but this is a result that must be noted and handled with caution. More people in households also mean more expenditure on food items, medical expenses, clothing and education. In order to reduce the level of poverty in Nyakallong, job creation and employment opportunities should be targeted. The nearby university of technology and FET College should inform learners at secondary schools about funds (NFSAS) available to help them in furthering their studies. Educators should also engage learners to realise the disadvantages of large household size. Large organisations such as ESCOM and Harmony Gold could help by means of skills development, especially among youth and females, in order to make them employable. Unemployment can also be reduced by putting back into operation the closed mine shaft and Allanridge Sanatorium hospital. A food garden community programme should be established in order to reduce the level of poverty. People who are involved should be trained on how to manage and develop the programme.
MCom, Economics, North-West University, Vaal Triangle Campus, 2012

South Africa, like international countries, has been experiencing an increase in the levels of poverty over the years. Poverty affects vulnerable groups of society more intensely and these groups include children, the old, disabled people and women, especially those who are single parents. This dissertation studies the role social grants have on the level of poverty in households of Sharpeville. This study focuses on two areas namely the theoretical background of poverty and social grants; and what the impact is of income from social grants. The South African government provides its citizens with eight different social grants to help those in need and/or vulnerable. From these social grants only six are investigated for the purpose of this study. These grants include the old age grant, child dependency grant, foster care grant, child support grant, disability grant and the war veteran grant. Poverty is defined as the inability to attain a minimal material standard of living by the World Bank. The different indicators used in this study to profile poor households in Sharpeville include the Household Subsistence Level (HSL) as the poverty line, the poverty gap ratio, the headcount index and the dependency ratio. This dissertation shows that poverty within the township has increased over the five years. And to do this the results from the data survey conducted in 2009 are compared to the results from Sekatane‘s 2004 data. The poverty gap ratio and the headcount index for the township in 2009 were estimated at 0.86 and 0.654 respectively. In the year 2004 the headcount index was estimated at 0.431 indicating a 22.3 percent increase in the number of people living in poverty. This means that an estimated 5 477 households in Sharpeville, in 2009, were regarded to be poor When government grants are excluded from the household‘s income within the township both the poverty gap ratio and the headcount index decrease to 0.93 and 0.705 respectively. This means that when government grants are excluded from households‘ income within Sharpeville, the depth of poverty within household‘s increases. The income from government grants might be regarded as minimal, however it assists in moving households further from the poverty line. This study recommends that activities within the informal sector should be encouraged as this will increase employment opportunities for those unemployed in the township. As the vast majority of the unemployed people have skills from trading/retail sector; employment creation should be focused in this sector. Lastly, the income threshold used in the means test equation to check affordability of social grant applicant should be decreased as people meeting the current criteria are already living in dire poverty.
Thesis (M.Com. (Economics))--North-West University, Vaal Triangle Campus, 2011

All over the world, the level of poverty is increasing. In South Africa it is mainly concentrated in rural areas and differs significantly from whether considering race, sex, provinces or community areas. This dissertation studies the relationship between poverty and inflation in Sharpeville by determining the impact of rising prices on the poor households in Sharpeville. The study focuses on three areas, namely the theoretical background of poverty and inflation, the impact of rising prices in expenditure patterns and the relationship to poverty. There are different approaches in defining poverty. Poverty can either be absolute or relative. For the purpose of this study, poverty is defined as absolute. Thus the study defines individuals as poor due to their inability to attain a minimum material standard of living. This minimal standard of living is normally referred to as the poverty line. Inflation may be defined in different ways. For the purpose of this dissertation, inflation is defined as the rise in the general price levels over a specific period of time. Changes in expenditure patterns are caused by an increase in inflation. This study uses the regression model to determine the impact of inflation on poverty in Sharpeville. According to the macroeconomic theory’s implication, the same level of inflation on the same basket of commodities has a different level of effect on each household. Accordingly, in this study, all households are assumed to be faced with the same inflation rate. Household size is positively related to poverty gap squared. This means that the more members there were in a household in Sharpeville the poorer they were. Households with the highest number of members were poorer than those with few members. Statistically, the null hypothesis that there is no relationship between household size and poverty gap is rejected, even at the 1% level of significance. EXPINFL is negatively related to poverty gap. The correlation matrix confirms the results in the regression analysis. The correlation coefficient between The relationship between poverty and inflation in Sharpeville Page EXPINFL and PGAP is -0.34467. Although it is relatively weak, the fact that there is a negative correlation confirms that inflation negatively affects poverty. Finally, the study recommends that government provides more job opportunities for the individuals without any source of income in Sharpeville. The government could also provide business funding to the unemployed individuals to enable them to start their own businesses. This would enable those individuals to create additional employment. In addition, measures should be introduced to determine the effect of inflation on those households who are not employed (that is, not receiving any form of income, not even through any form of grant), but do benefit from some form of feeding scheme administered by either government or non-profit organisations.
MCom, Economics, North-West University, Vaal Triangle Campus, 2012

We measure multidimensional poverty in India using National Sample Survey Organization data from 2014–15 to 2017–18. We use income, health, education, and standard of living to measure the multidimensional poverty index (MPI). The MPI headcount declined from 26.9 to 13.75 per cent over the study period. The all-India estimates indicate that 144 million people were lifted from poverty during this period. We include different health dimensions, factoring in insurance, institutional coverage, antenatal care, and chronic conditions. Income is the dominant instrument with the highest contribution to the MPI, followed by insurance. Cooking, sanitation, and education also have significant weights. The decline in deprivation is steeper in rural areas than urban areas. Our state-level estimates reveal that 20 states report less than 10 per cent headcount poverty, up from six states. COVID-19 may lead to reversals of these gains, with poverty rising to pre-2014–15 levels, rising more steeply in rural areas.