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The purpose of this paper is to apply a poverty level decomposition approach to decompose the poverty by income sources and investigate the impact of government transfers on income inequality and rural poverty.

This paper uses the decomposition method of inequality and the decomposition method of poverty level by resource endowments to decompose the overall inequality and the overall poverty by income sources.

It is found that unequal income distribution rather than income endowments is mainly responsible for the existence of poverty. Government transfers and relief income, aiming at the poor, help alleviate inequality and poverty, but are not targeting the poorest. Unequal distribution of production subsidies actually lead to higher poverty incidence.

This paper has revealed that the poverty issue cannot be resolved with economic development alone if the issues including the inequality in income distribution are not solved. It is important to make government transfers/subsidies pro-poor.

A poverty level decomposition approach is first used to decompose the poverty by income sources in China.

The purpose of this paper is to provide insight to policy-makers into a framework for action, which is needed to effectively reduce poverty in its monetary and non-monetary dimensions.

Specifically, an exact decomposition analysis is conducted that is based on the Shapley value method, and investigated the growth and redistribution effects as well as changes due to mobility and sector-specific effects of the variation in both income/expenditure and non-income poverty dimensions.

Growth in mean consumption and household assets accounted for the bulk of the improvement in poverty reduction and the results complement the evidence obtained from the “sectoral decomposition” of poverty in Cameroon which may indeed have a strong bearing on the sectoral shares of poverty. The temptation is resisted, however, not to deny that redistribution also has an important role to play, yet there must be severe limits to what can be achieved by growth neutral redistribution. The redistribution effect had an ameliorating tendency in household asset deprivation among farming households.

This paper is a well-written piece using quite rigorous and interesting methodological approach. To obtain a measure of non-income dimensions of well-being, the authors constructed composite indices on household assets reflecting household access to a range of physical assets and services including human capital by polychoric principal component analysis method.

This paper aims to address the thesis that poverty is best alleviated by a policy emphasising the growth of per capita average income, a strategy that affords little room for direct pro-poor interventions or a movement towards a more equal distribution of incomes. This policy prescription is based on the empirical finding that cross-country variations in poverty are largely explained by variations in growth rates of average income.

The paper contends, as has been done in other commentaries on the subject, that inferring the dictum that “growth is [virtually the only thing] good for poverty” from cross-country evidence on poverty, growth and inequality is neither logically plausible nor normatively compelling. This is sought to be established both through conceptual reasoning and (secondary) data-based analysis. In particular, the thesis under review implicitly rejects the value of counter-factual analysis. Such a hypothetical illustrative analysis is attempted here, using evidence relating to urban poverty, growth and inequality in India.

The paper concludes, without undermining the salience of growth, that there is little basis for the pre-eminence accorded to it as the instrument for poverty redress.

This paper has not been published elsewhere. A collaborative paper by one of the present authors with another scholar, on a similar theme is, however, under preparation for publication.

The purpose of this paper is to decompose inequality in Sri Lanka by population subgroups and income sources.

The study is based on the latest Sri Lankan Household Income and Expenditure Survey. The study firstly sketches an inequality profile for Sri Lanka and then investigates the principle components of inequality by applying several decomposition techniques. Essentially a decomposable class of inequality measures were computed by considering households characteristics such as geographic location/sector, gender, education and type of employment. Inequality within and between population subgroups/sectors in the distribution of expenditure was done by employing the Theil's entropy index, mean logarithmic deviation, and the half the squared coefficient of variation. Concentration curves and indices were utilized to decompose inequality by expenditure components.

The empirical findings are broadly encouraging. Decomposition analysis results reveal that in all groups used, the between‐group inequality accounts only for a very small part of the overall inequality. Thus, reducing inequality between the household groups would have only limited effect on reducing the overall inequality. Results confirm the fact that inequality in Sri Lanka was driven by relatively higher levels of expenditure inequalities of those at the top of the expenditure distribution. Decomposition estimates of the Gini index by expenditure sources via Rao's method revealed that the distribution of non‐food expenditure was more asymmetric as compared to food expenditure. Findings in general point to the wisdom of considering the redistribution of economic resources within‐sectors and sub‐groups rather than between‐sectors and sub‐groups if the intention is to cost effectively reduce overall inequalities in Sri Lanka. However, in practice an optimal‐mix of within and between‐group policies would be required in addressing overall inequality.

This is the first study that analyzes the latest Sri Lankan Household Income and Expenditure Survey to decompose inequality by population subgroups and income sources.

Using the latest census data (2010), this paper investigates housing poverty conditions in Shanghai, the largest city in China. The data shows that a large fraction of Shanghai households are still living in excessively over-crowded housing. Meanwhile, the incidence ratio of housing poverty among migrants is more than five times than among natives. In particular, 45% of rural migrant households were living in housing poverty. Poverty decomposition analysis shows that approximately 70% of total housing poverty in Shanghai is attributable to rural migrants. Our finding is supported by estimating the multidimensional poverty index (MPI). The findings in this paper have significant implications to general housing policy making in urban China.

Outlines a method for controlling for compositional factors in the measurement of poverty. Bases the method on “shift‐share analysis” and “direct standardization”, consistent with Sen’s (1976) influential axiomatic approach to poverty measurement. Employs the popular poverty index proposed by Foster et al. (1984), which is one of the few summary poverty measures that can be directly standardized and also meets Sen’s criteria. The method is illustrated by examining the trend in absolute and relative poverty in the UK. Uses data from the “Family Expenditure Survey”, covering the period 1968 to 1986, and places specific empirical focus on the relationship between household structure and poverty.

Inequality is an essential factor for the alleviation of poverty. In Cameroon, most of the households derive their livelihoods from non-wage income and a better understanding of how different variables affect income inequality is a way to reduce those inequalities and improve social welfare. Studies carried out so far barely make out the determinants among non-wage earners. This study sets out to identify these determinants, using the regression-based decomposition technique and data obtained from the 2005 Employment and Informal Sector Survey (EISS) undertaken by the National Statistic Institute (INS) in Cameroon. Results show that the total inequality of an hourly active income ensues from the ratio of age/experience and unobserved individual heterogeneity among non-wage earners.

During the last two decades the share of foreign-born residents in Italy has grown considerably, from just over 1 percent to about 8 percent. This chapter seeks to clarify the status of immigrants in Italy by examining the evolution of their economic situation and, in particular, the presence of economic hardship. Poverty is measured by considering not only the usual income-based indicators but also others that take into account households’ real and financial wealth. The picture that emerges is one of a higher incidence of economic hardship among immigrant households that strongly affects the dynamics of poverty nationwide. The economic gap with respect to natives appears to increase in the years considered, but the condition of poverty is not more persistent for immigrants than for Italians.

This paper aims to assess whether official development assistance (ODA) or foreign aid has been effective in reducing extreme poverty; test whether the type and source of aid matter; and examine whether political or economic freedom enhances aid effectiveness in developing countries.

The study uses recent dynamic panel estimation techniques (system generalised method of moments), including those methods which deal with endogeneity by controlling for simultaneity and unobserved heterogeneity.

The main findings of the study are: firstly, foreign aid does have a statistically significant poverty reduction effect and the results are consistent across all the three extreme poverty proxies. Secondly, the disaggregation of aid by source and type shows that total aid, grant and bilateral aid are more likely to reduce poverty. Thirdly, political freedom might not be an effective channel through which aid impacts extreme poverty, but aid is more effective in an environment where there is respect for freedom of enterprise.

As with most cross-country aid–growth–poverty dynamic panel data studies, the challenges of establishing robust causality and accounting for the unobserved country-specific heterogeneity remain apparent. However, given the data availability constraints, generalised method of moments is, to the best of the authors’ knowledge, the most robust empirical strategy when T < N. Future research could explore possibilities of individual country analysis, disaggregating countries by income and also examining the direction of causality between foreign aid, poverty and democracy.

The policy implications are that the development partners should continue to focus on poverty reduction as the main objective for ODA; aid allocation should be focused on channels which have more poverty-reduction effect, such as per capita income and economic freedom; and aid recipient countries should also focus on reducing inequality.

The main social implications from this study is that it is possible to reduce poverty through ODA. Second, to enhance the effectiveness of foreign aid, ODA allocation should be focussed on channels, which have more poverty-reduction effect, and the host countries should have economic freedom.

This paper makes a further contribution to the aid effectiveness literature, especially the channels through which foreign aid affects poverty.