Poverty Gap Index Research Articles

Poverty Situation in Tribal and Non-tribal Area of Gujarat, India

The present investigation undertook to study the extent of poverty in the tribal and non-tribal areas applying the FGT index. Results showed that overall poverty was higher in the tribal area as compared to non-tribal areas. Among farm sectors in the tribal and non-tribal area, the highest poverty in marginal farm households was followed by landless agricultural labors and small farm households. The overall poverty gap index revealed, on average, 11 percent and 4 percent of the poverty line cash transfer needed to lift each poor person out of poverty in tribal and non-tribal areas, respectively. The value of the squared poverty gap index showed poverty was less severe in non-tribal areas. The poverty line’s average expenditure gap shows poor of tribal areas were more flawed than the poor of non-tribal regions in Central Gujarat. Overall expenditure of poor households on food items constituted maximum share followed by non-food items, medical and education in the tribal and non-tribal area. In tribal regions, both poor and non-poor people were spending more on intoxicant and tobacco products than non-tribal areas. The government should give regular employment to inadequate household programs like MGNREGA. There is a dire need to make an awareness program to control the use of intoxicants and tobacco in general for both the area and particularly in tribal areas because they were spending more on these items.

Determinants of Urban Poverty in Ethiopia: The Case of Jimma Town, South West Ethiopia

The objective of this study is to identify determinants of urban poverty in Jimma town. In order to meet the objectives of the study, cross sectional, descriptive and explanatory, research design applied. The sampling technique of the study used stratified and simple random sampling was employed to select households. Information has gathered a sample of 397 household heads were through primary and secondary data. A Logit model was employed and estimated based on the primary data, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. By Considering total household consumption and dividing it by the household adult equivalent size, from sample of 397 surveyed household heads, the head count, poverty gap, and severity index of the survey obtained as 66%, 17.8% and 3.16 respectively. The finding revealed that variables that are positively correlated with the probability of being poor are gender, family size, employment/occupation and health/disease incidence of the household. Variables negatively correlated with probability of being poor are: income, educational level, and marital status, age of house hold, housing, house hold residence and saving. The major significance which affected significantly the incidences of poverty in the town are: education, income, age, saving, housing, gender, occupation, family size, previous residence, health and employment. The study concluded that most important determinants of urban poverty in the study area that plays a significant role in affecting incidence poverty are income, education and saving are the major implication to incidence of poverty. Study recommended that strong negative relationship between income, education, saving, housing, and residence with the probability of being poor point out that a need to consider government and non-government organization in designing strategy and policies targeted to curb urban poverty. Keywords: Urban poverty, Jimma Town, House hold-level, analysis DOI: 10.7176/CER/13-4-01 Publication date: June 30 th 2021

Assessing the household economic burden of non-communicable diseases in India: evidence from repeated cross-sectional surveys

BackgroundFinancing for NCDs is encumbered by out-of-pocket expenditure (OOPE) assuming catastrophic proportions. Therefore, it is imperative to investigate the extent of catastrophic health expenditure (CHE) on NCDs, which are burgeoning in India. Thus, our paper aims to examine the extent of CHE and impoverishment in India, in conjunction with socio-economic determinants impacting the CHE.MethodsWe used cross-sectional data from nationwide healthcare surveys conducted in 2014 and 2017–18. OOPE on both outpatient and inpatient treatment was coalesced to estimate CHE on NCDs. Incidence of CHE was defined as proportion of households with OOPE exceeding 10% of household expenditure. Intensity of catastrophe was ascertained by the measure of Overshoot and Mean Positive Overshoot Indices. Further, impoverishing effects of OOPE were assessed by computing Poverty Headcount Ratio and Poverty Gap Index using India’s official poverty line. Concomitantly, we estimated the inequality in incidence and intensity of catastrophic payments using Concentration Indices. Additionally, we delineated the factors associated with catastrophic expenditure using Multinomial Logistic Regression.ResultsResults indicated enormous incidence of CHE with around two-third households with NCDs facing CHE. Incidence of CHE was concentrated amongst poor that further extended from 2014(CI = − 0.027) to 2017–18(CI = − 0.065). Intensity of CHE was colossal as households spent 42.8 and 34.9% beyond threshold in 2014 and 2017-18 respectively with poor enduring greater overshoot vis-à-vis rich (CI = − 0.18 in 2014 and CI = − 0.23 in 2017–18). Significant immiserating impact of NCDs was unraveled as one-twelfth in 2014 and one-eighth households in 2017–18 with NCD burden were pushed to poverty with poverty deepening effect to the magnitude of 27.7 and 30.1% among those already below poverty on account of NCDs in 2014 and 2017–18 respectively. Further, large inter-state heterogeneities in extent of CHE and impoverishment were found and multivariate analysis indicated absence of insurance cover, visiting private providers, residing in rural areas and belonging to poorest expenditure quintile were associated with increased likelihood of incurring CHE.ConclusionSubstantial proportion of households face CHE and subsequent impoverishment due to NCD related expenses. Concerted efforts are required to augment the financial risk protection to the households, especially in regions with higher burden of NCDs.

Out-of-Pocket Health Expenditure and Poverty: Evidence from a Dynamic Panel Threshold Analysis.

The current study investigated the association between out-of-pocket health expenditure and poverty using macroeconomic data from a sample of 145 countries from 2000 to 2017. In particular, it was examined whether the relationship between out-of-pocket health expenditure and poverty was contingent on a certain threshold level of out-of-pocket health spending. The dynamic panel threshold method, which allows for the endogeneity of the threshold regressor (out-of-pocket health expenditure), was used. Three indicators were adopted as poverty measures, namely the poverty headcount ratio, the poverty gap index, and the poverty gap squared index. At the same time, out-of-pocket health expenditure was measured as a percentage of total health expenditure. The results showed the validity of the estimated threshold models, indicating that only beyond the turning point, which was about 29 percent, that out-of-pocket health spending led to increased poverty. When heterogeneity was controlled for in the sample, using the World Bank income classification, the findings showed variations in the estimated threshold, with higher values for the low- and lower-middle-income groups, as compared to the high-income group. For the lower-income groups, below the threshold for out-of-pocket health expenditure, it had a positive or insignificant effect on poverty reduction, while it led to higher poverty above the threshold. Further, the sampled countries were divided into regions, according to the World Health Organization. Generally, improving health care systems through tolerable levels of out-of-pocket health expenditure is an inevitable step toward better health coverage and poverty reduction in many developing countries.

Rural and urban poverty models on Sumatra Island

This study aims to analyze rural and urban poverty on Sumatra Island, Indonesia, and its determinants. The variables tested in the model are HDI (Human Development Index), GRDP (Gross Regional Domestic Product), and per capita expenditure. The data used is panel data for the provinces on Sumatra Island in the period 2011 - 2019. The analysis tool uses a panel data regression model. The study results found that during the 2011 - 2019 period, the rural poverty rate on Sumatra Island was 11.68 percent, relatively higher than in urban areas, 9.22 percent. The poverty gap index and poverty severity index in rural areas are also relatively higher than in urban areas. The research results also found that the poverty level in rural areas is significantly affected by HDI, while the GRDP and per capita expenditure does not significantly affect.

THE PERFORMANCE OF MICROFINANCE PROVIDERS ON POVERTY ALLEVIATION AMONG YAM FARM HOUSEHOLDS IN SELECTED LOCAL GOVERNMENT AREAS OF NIGER STATE, NIGERIA

The study examined the performance of microfinance providers on poverty alleviation among yam farm household in some selected Local Government Areas of Niger State, Nigeria. Multi-stage sampling technique was used to draw up respondents for the survey. Data were collected from 120 respondents using structured questionnaire and were analyzed using descriptive statistics, poverty gap index, Foster-Greer-Thorbeck index, head count ratio, severity index, farm budget technique, and Gini coefficient. The results revealed that most (89.17%) yam farm household were males and married (87.50%). The average age of the respondents was 37.83 years; 75% were into poultry farming; 44.17% and 30.83% obtained credit from commercial and microfinance banks, respectively. Also, average income of the respondents before and after the loan was N38, 401.04 and N83, 329.21, respectively. The results also revealed even though credit had positive impact on the livelihood of the respondents in the area, the result of the Gini coefficient (0.6631) showed that there was inequality in income distribution among the respondents in the area. The study therefore, recommended that additional microcredit providers be established in the study area to increase its impact among the respondents especially in poverty alleviation. Also, integrated community development effort should be encouraged to provide rural infrastructures in the study area.

Dynamic Spatial Durbin Modeling (Case: Percentage of Poor Population in Indonesia 2010-2019)

The dynamic panel model assumes that each observation unit is independent of each other. But sometimes this assumption is violated, so there are spatial effects in the model. This study aimed to make percentage modeling of poverty in Indonesia using the Dynamic Spatial Durbin Model (DSDM). The data used in this study were secondary data obtained from the Statistics Indonesia in the period 2010-2019. The parameter estimation method used in this model was the Maximum Likelihood (ML). According to Moral-Benito, Allison and Williams the ML method has the best performance when used on panel data that has small cross-section data dimensions. The results of this study indicated that spatial dependence, time lag, variables of Poverty Gap Index, Poverty Severity Index and Logarithm of Expenditures per Capita affect poverty in Indonesia significantly. Other results showed that DSDM was able to explain the diversity in models at 95.6 %. This seemed higher when it’s compared to the Spatial Durbin Model (SDM). Thus, the result of the study proved that DSDM is the best model for modelling dynamic poverty data panel in Indonesia during 2010-2019.

Analisis Pengaruh Zakat dan Infak Terhadap Tingkat Kedalaman Kemiskinan, Keparahan Kemiskinan dan Gini Rasio di Indonesia Tahun 2007-2018

Poverty in Indonesia has decreased in recent years, though slowing. Besides that, zakat and infaq have increased from year to year. Based on this phenomenon, this study aims to determine the effect of zakat and infaq on poverty and income disparities in Indonesia. The method used is a quantitative approach with descriptive and inferential analysis (multiple linear regression analysis). The data used are secondary data with zakat, infaq, poverty gap index, poverty severity index, and gini coefficient (gini ratio). The results of T test and F test shows the value of sig. 0,00 less than 0,05. Overall, zakat and infaq have a significant effect on the poverty gap, poverty severity and gini ratio. While partially, zakat and infaq also have a significant effect on the poverty gap, poverty severity and gini ratio. Zakat has a negative relationship to the poverty gap and poverty severity, while infaq has a negative relationship to the gini ratio.

Rwanda: Lessons from Applied Intergovernmental Fiscal Equalization Formula

It is a well-known fact that budgetary allocations need to be based on a just formula for balanced service delivery in the modern world. This paper describes the intergovernmental formula designed for Rwanda in 2003 to allocate grants from the central to local governments (LGs). First, the previous criterion, the Local Authority Budget Support Fund, was reviewed. This was followed by a literature review and field visits. Finally, the specifications of the mathematical model are described, followed by the proxy selection, data analysis, econometric evaluation, and estimations used in the study. In 2003, data analysis revealed that LGs had low fiscal capacities and ubiquitous fiscal needs. These were proxied by mean own source revenues and expenditure needs, respectively, in the proposed formula. The difference between the two was taken as the mean fiscal gap. This formula corrected the inherent weaknesses in the previous transfer system. It proposed weighting parameters to determine subnational transfer entitlements. Additionally, it constructed and applied welfare poverty and fiscal gap indices that captured the behavior of LGs in terms of wellbeing, fiscal needs, and revenue capacity for the first time in Rwanda. The study recommendations were entirely adopted by the government. The formula was used to allocate unconditional grants from the central government to LGs to improve service delivery and reduce poverty. The study also highlights that any successful transfer formula design depends on how the following are determined—the transfer pool, weights, proposed variables, and proxy indices—and how they enter the model.

Measures, Distribution and Decomposition of Poverty: An Empirical Analysis in Nepal

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.

English

This article assesses the link between the four pillars of gender equality and extreme poverty in sub-Saharan Africa. Accordingly, the objective of the paper is to empirically examine whether the four pillars of gender equality, namely women’s health, women education, political participation of women and economic participation facilitate extreme poverty alleviation in sub-Saharan Africa. Data were collected from the World Bank development indicators and World Economic Forum Global Gender Gap Index for 25 sub-Saharan African countries whose data appear on both indexes for three years into the SDGs era. Th e paper applied a quantitative approach with secondary data on poverty gap index drawn from the World Economic Forum Poverty Gap Index for sub-Saharan Africa. Data for twenty-fi ve sub-Saharan African countries were analysed using the fi xed-eff ect panel data regression approach using the Hauseman model selection test. Findings from the analysis indicate that, ceteris paribus, an increase in the threegender equity variables namely economic participation of women, education of women and political participation and leadership of women in sub-Saharan Africa has a signifi cant potential to reduce extreme poverty in sub-Saharan Africa within the sample of study. Since the fi ndings of this study have shown that extreme poverty can be reduced through increased women participation in economic activity, education and leadership, the SDG of poverty alleviation can be improved in sub-Saharan Africa through better government provision of economic, educational and leadership opportunities for women such as providing women with free-interest small business start-up funds, free education for women and supporting women to ascend and survive in political and leadership positions in sub-Saharan Africa through a balanced quota for female leadership positions. Given that the women’s health variable did not prove to be signifi cant on extreme poverty, further research is recommended to separate the health variable into rural health and urban health variables in order to examine the possibility that either of the health clusters might contribute signifi cantly to reducing extreme poverty. Th is paper contributes to existing literature by providing an empirical evidence to show that gender equality in sub-Saharan Africa is a viable policy strategy for achieving the SDGs 2030 Agenda of extreme poverty eradication in sub-Saharan Africa; the paper also provides empirical model for future study.

Analysis of poverty, income inequality and their effects on food insecurity in southern Ethiopia

BackgroundReduction of poverty and income inequality, and ensuring food security is the main goal of the Ethiopian government. In response, declines of national poverty were observed over time, but it is still a worrying concern as a significant proportion of the population remains poor. However, the trends of income inequality are rising substantially over time and thereby might exacerbate the food insecurity status in the country. This study aims to measure, identify determinants, and analyze the effects of poverty and income inequality on food insecurity status of households in Sawla town of southern Ethiopia.MethodologyA two-stage sampling technique was used to select 227 sampled households’ heads. This study applied descriptive statistics, Foster Greer Thorbecke approach, binary logistic, and quantile regression models to analyze the data.ResultsThe finds of this study reveals that 34% of households are living below the poverty line with a poverty gap index of 11% and severity index of 5.6%. The average income inequality with Gini coefficient index is found to be 0.447. Both poverty and income inequality result is quite larger than the national average of the country. The sample households are food insecure with 20.7% depth and 13% severity indexes of food insecurity. The levels of poverty and income inequality are more worrisome among the food-insecure households. Moreover, the logistic regression model shows that levels of education, family size, being divorced, the main occupation, savings, and house ownership negatively and significantly affected the household level of poverty. Quantile regression model result shows that age, level of education, income, family size, health, savings, remittances, electric, credit, and house ownership affected households’ level of income of the study area.ConclusionThe study suggests strengthening the existing welfare-oriented strategies by undertaking intra-household resource allocations for women, encouraging participation of diversified business activities, promoting the use of family planning methods, strengthening formal education, microfinance institution and housing program by targeting impoverished households in the town.

Public family spending, labour productivity, income inequality and poverty gap in the group of seven countries

Purpose. Comparable data on distribution of family income provide reference point for determining economic performance of any country, opportunity to assess effects of income inequality and poverty drivers that are either country- or region-specific. This study analysed the effectiveness of composite indices of public spending on family benefits, labour productivity, macroeconomic performance indicators and moderating factors in reducing income inequality and poverty gap in the Group of Seven (G7) countries from 1980 to 2019. Methodology. The study employed fixed effects Least Squares regression model in panel environment within the framework of empirical econometric methodologies. The composite indices comprised public spending on family benefits in cash and kind, unemployment allowance payments, tax on personal income, labour productivity, harmonised unemployment rate, consumer price index, real GDP growth rate, GDP per capita and per hour worked, fertility rate and trade. After graphical analysis of the data, order of integration was via unit root tests. Hausman test was carried out to choose between fixed and random effects models. Subsequently, parameters of the models were estimated and evaluated for significance at the 0.05 critical level. Findings. The results showed that percentage changes in income inequality and poverty gap indices differed for same percentage change in components of the composite indices. Some variable-specific percentage changes in income inequality and poverty gap were statistically significant, while others were not. However, the overall percentage changes was statistically significant. The paper concluded that while some specific effectiveness of the explanatory variables in reducing income inequality and poverty gap was not significant, their joint effectiveness significantly reduced poverty. Therefore, it is pertinent that family-oriented fiscal policy thrusts should be strengthened and sustained so as to continually reduce income inequality and, ultimately, narrow poverty gap in the countries. Limitations. The study considered the G7 countries for a period of 40 years. The limitations were that the variables considered to influence income inequality and poverty gap in the countries were both exhaustive. Also, the results were conditioned to the method used, and different methods can alternatively be used by other researchers and the results compared with this. Originality. The study is original research paper. It has neither been published in any other peer-reviewed journal not under consideration for publication by any other journal.

ZAKAT AND POVERTY ALLEVIATION IN INDONESIA: A PANEL ANALYSIS AT PROVINCIAL LEVEL

As a pillar of Islam and an instrument for poverty alleviation, zakat is perceived as aneffective tool for tackling the problem of poverty in the Muslim world. However,whether zakat is effective in improving indicators of both quantity and quality ofpoverty is still a question requiring empirical investigation. This study is aims toempirically investigate the role of impactful zakat in poverty alleviation as indicated bythe BAZNAS prosperity index (Indeks Kesejahteraan BAZNAS or IKB), at provinciallevel in Indonesia. This study covers annual data from 28 provinces in Indonesia forthe years 2017 and 2018. Data analysis uses a panel-data approach, with threeindicators of poverty – the poverty headcount ratio (P0), poverty gap index (P1), andpoverty severity index (P2) – as dependent variables. The study finds that higherBAZNAS IKB, used as a sign of impactful zakat, significantly reduces P0 but hasinsignificant effect on P1 and P2. The results of this study imply that zakat managersshould put emphasis on the poorest section of the poor population to enableimprovements in poverty indicators through zakat utilization.

Effects of Off-farm Income on Poverty and Food Security Status of Farmers in Paikoro Area of Niger State, Nigeria

This study determined the effects of off-farm income on poverty and food security status of farmers in Paikoro Local Government area of Niger state, Nigeria. A total of 150 farmers were selected randomly from six wards across the Local Government Area. Structured questionnaire and interview schedule were used to elicit primary data from the farmers for the study. Descriptive statistics, Foster-Greer-Thorbeck (FGT) model, Logit regression and Tobit regression models were used for data analysis. Results showed that the mean age of the farmers was 42 years, majority (89.33%) were male while 90.67% were married and 63% had no formal education. The most prevailing off-farm enterprise was trading (74%). The poverty status of the respondents were classified under poor and non-poor with poverty incidence of 41.33% for the poor, poverty gap and severity indices were 37.63% and 14.16% respectively. Logit regression showed membership of association, household size, gender, food expenses, years in formal education, and off-farm income were significant at p=0.01, p=0.01, p=0.05, p=0.05, p=0.05, p=0.05 respectively. The food security status analysis revealed that 67% of the farmers were food secure while 33% were food insecure. Tobit regression results showed household size, farming experience, size of farm and off-farm income at p=0.01 respectively were significant determinants of food security. It was concluded that off-farm income had significant positive effect on the poverty and food security status of the farmers. However, poverty and food insecurity still remain major issues in the area that cannot be over-looked, and as such, efforts should be made to ensure that farmers are encouraged and empowered to engage in profitable off-farm activities while the government should also make policies that will favour their off-farm enterprises.

Changes in Income Distribution for Different Family Types in Poland

This paper compares income distributions for the family types distinguished by the number of children. The primary contribution to the literature of the current paper was to provide evidence that between 2015 and 2016, when the child benefit Family 500+ program was implemented, there was a reduction in income inequality and poverty, especially for families with many children. The basis for the calculations was microdata from the Household Budget Survey conducted by Statistics Poland. It is the basic source of information on the revenues, expenditures, quantitative food consumption and other aspects of the living conditions of particular groups of the population. The data obtained from this survey allow for the analysis of different factors influencing income distribution and its inequality by means of selected income inequality measures: Gini index and the quintile and decile share ratios. To conduct poverty analysis, the head-count ratio, poverty gap and squared poverty gap indices were applied. The results of the analysis revealed noticeable changes in the income distribution of Polish households, which resulted in poverty reduction, especially for families with many children. In total, mean equivalent income increased by 127 PLN and poverty decreased by 1.2 percentage points. Approximately 160,000 households came out of poverty. The two-sample parametric tests for differences in means and proportions showed that in 2016, the means were significantly larger and poverty rates significantly smaller for all family types but the differences were larger for large families.

Mapping Poverty of Latin American and Caribbean Countries from Heaven Through Night-Light Satellite Images

The adoption of the Sustainable Development Goals in September 2015 by the United Nations General Assembly is calling National Statistics Offices worldwide to underpin a data revolution. Indeed, these organizations should extend both the scope and disaggregation of the data traditionally produced, and measure new economic, social and environmental phenomena, leaving none behind. There is a growing consensus that, in the digital era, earth observation might strengthen traditional data sources and statistics in monitoring sustainable well-being, facilitating the transformative agenda that official statisticians should implement in the forthcoming years. This research analyses how earth observation, under the form of observable nightlights, might help in mapping poverty data, thus filling in existing gaps of official statistics for a core sustainable development indicator. The empirical analyses show that there are indeed considerable advantages from the use of satellite remote sensing information, the so-called ‘views from the above’, in facing the increasing demand from policy makers and the public at large. The analysis shows that publicly and freely available information from the space might be a key source of information to derive—through an unbalanced fractional panel-data model—spatially disaggregated and continuous-time estimations of poverty gap, headcount, and Gini indices for 20 Latin American and Caribbean countries.

Micro, small, and medium enterprises (MSMEs) and poverty reduction: empirical evidence from Indonesia

ABSTRACT This study aims to analyze the effect of MSMEs on poverty reduction, both directly and indirectly, through labor absorption from 1997 to 2018. The poverty measurements used in this study comprise Head Count Index (P0), Poverty Gap Index (P1), and Poverty Severity Index (P2), while the MSMEs are classified based on their scales, which are small-medium enterprises (SMEs) and micro-small enterprises (MSEs). Control variables, such as economic growth, openness, government expenditure, and investment, are also covered in this model. In general, the results show that MSMEs statistically affect poverty reduction in Indonesia both directly and indirectly. Nevertheless, different business scales offer various implications for poverty reduction. SMEs play a bigger role in alleviating poverty than MSEs as they reduce not only the percentage of poor people but also the Poverty Gap and Severity Index. Furthermore, of the four control variables, only economic growth has a significant effect on poverty reduction, both direct and indirect. Hence, policymakers should support the market certainty of SMEs products to sustain the production cycle.

Combining Microsimulation and Optimization to Identify Optimal Flexible Tax-Transfer Rules

We use a behavioural microsimulation model embedded in a numerical optimization procedure in order to identify optimal (social welfare maximizing) tax-transfer rules. We consider the class of tax-transfer rules consisting of a universal basic income and a tax defined by a 4th degree polynomial. The rule is applied to total taxable household income. A microeconometric model of household, which simulates household labour supply decisions, is embedded into a numerical routine in order to identify – within the class defined above – the tax-transfer rule that maximizes a social welfare function. We present the results for five European countries: France, Italy, Luxembourg, Spain and United Kingdom. For most values of the inequality aversion parameter, the optimized rules provide a higher social welfare than the current rule, with the exception of Luxembourg. In France, Italy and Luxembourg the optimized rules are significantly different from the current ones and are close to a Negative Income Tax or a Universal basic income with a flat tax rate. In Spain and the UK, the optimized rules are instead close to the current rule. With the exception of Spain, the optimal rules are slightly disequalizing and the social welfare gains are due to efficiency gains. Nonetheless, the poverty gap index tends to be lower under the optimized regime.

Determinates of Urban Poverty at Household Level: The Case of Wolaitta Soddo Town, SNNPRS, Ethiopia

Poverty is daily experience of citizens in Ethiopia and the government has implemented different poverty reducing policies and strategies in the intention to reach middle income countries in the coming 7 years. This Study aimed at analyzing the determinants of urban poverty At household level in terms of demographic, economic and social practices in soddo Town. The study was conducted under cross sectional research design. The approach that was used is a mixed approach which makes the use of both quantitative and qualitative methods. Samples of 227 households were drawn from the target population by adopting systematic random sampling technique and 18 of them were discarded from further consideration due to lack of response. Data collecting instruments like questionnaire, semi-structured interview, document analysis and focus group discussions were used to collect data. .A Logistic regression model was employed and estimated based on the primary data, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. By making use of Food Energy Intake (FEI) approach the surveyed households are identified as the poor and non-poor. Based on this, Birr 3246 was computed as food poverty line per adult equivalent per month and out of the 209 respondent household heads, 94(45%) were found to be poor. The poverty gap index of 8 percent and poverty severity index of 3 percent were estimated. The variables that are positively correlated with the probability of being poor are family size whose number of members are 5 and above, education, age, sex, saving, electricity connection, unemployment and marital status. The variables that are negatively correlated with the probability of being poor are family size whose numbers of members are less than 5, house tenure, water pipe connection, employment status. These calls for urgent interventions aimed at curbing the problems of the people through creating employment opportunities, family planning, provision of market based short term trainings, empowering females and distribution of social service, improving education services, health services, and creating access to credit facilities need to be promoted for poor urban household in the study area. Keywords: - Poverty, poverty line, poverty incidence, poverty gap, poverty severity DOI : 10.7176/JAAS/60-02 Publication date: January 31 st 2020