Improving Estimates of Inequality and Poverty from Urban China's Household Income and Expenditure Survey

In urban China the Household Income and Expenditure Survey requires respondents to keep a daily expenditure diary for a full 12-month period. This onerous reporting task makes it difficult to recruit respondents, compromising the sample. This article uses monthly expenditure data from two urban areas of China to see if data collection short-cuts, such as extrapolating to annual totals from expenditure reports in only some months of the year, would harm the accuracy of annual expenditure, inequality and poverty estimates. Replacing 12-month diaries with simple extrapolations from either one, two, four or six months would cause a sharp increase in estimates of annual inequality and poverty. This undermines international comparisons of inequality statistics because no country other than China uses such comprehensive 12-month expenditure records. But a corrected form of extrapolation, based on correlations between the same household's expenditures in different months of the year, gives much smaller errors in estimates of inequality and poverty.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.     

The impact of work and non‐work migration on household welfare,poverty and inequality

This article estimates the impact of work migration and non‐work migration on per capita income, per capita expenditures, poverty and inequality in Vietnam using data from the two most recent Vietnam Household and Living Standard Surveys. We find that both work migration and non‐work migration have a positive impact on per capita expenditures of migrant‐sending households. Non‐work migration significantly decreases the incidence, depth and severity of national poverty. The effect of work migration on poverty is much smaller. Still, while work migration does not lift people out of poverty, it makes their poverty less severe. In addition, both work migration and non‐work migration decrease inequality, albeit only very slightly.     

Poverty and inequality under income and price dispersions

Abstract.  We introduce an analytical framework for welfare analysis that accounts for changes in the joint distribution of prices and incomes by using parametric formulae of poverty and inequality measures. We propose statistical indicators for the levels, variabilities and a statistical link of price indices and nominal living standards, which are consistent with a bivariate lognormal model. Our analysis provides intuitive insight about the social welfare impact of economic shocks affecting levels, variabilities, and correlation of prices and incomes. The roles of price and income variabilities for poverty and inequality are exhibited, with the possibility of several variation regimes. JEL classification: I32, O15, D31     

CHINESE POVERTY: ASSESSING THE IMPACT OF ALTERNATIVE ASSUMPTIONS

This paper investigates how estimates of the extent and trend of consumption poverty in China between 1990 and 2004 vary as a result of alternative plausible assumptions concerning the poverty line and estimated levels of consumption. Our methodology focuses on the following sources of variation: purchasing power exchange rates (used to convert an international poverty line), alternative levels and distributions of private incomes, alternative estimates of the propensity to consume of different income groups, and alternative spatial and temporal price indices. We report national, urban and rural poverty estimates corresponding to distinct assumptions. It is widely believed that substantial poverty reduction took place in China in the 1990s, and we find this conclusion to be largely robust to the choice of assumptions, although estimates of the extent of Chinese poverty, and therefore of world poverty, in any year are greatly influenced by this choice.     

The impact of natural disasters on household income,expenditure, poverty and inequality: evidence from Vietnam

Natural disasters are expected exacerbate poverty and inequality, but little evidence exists to support the impact at household level. This article examines the effect of natural disasters on household income, expenditure, poverty and inequality using the Vietnam Household Living Standard Survey in 2008. The effects of a natural disaster on household income and expenditure, corrected for fixed effects and potential endogeneity bias, are estimated at 6.9% and 7.1% declines in Vietnamese household per capita income and expenditure, respectively. Natural disasters demonstrably worsen expenditure poverty and inequality in Vietnam, and thus should be considered as a factor in designing poverty alleviation policies.     

Upper and Lower Bound Estimates of Inequality of Opportunity: A Cross-National Comparison for Europe

I provide lower and upper bound estimates of inequality of opportunity (IOp) for 32 European countries, between 2005 and 2019. Lower bound estimates use machine learning methods to address sampling variability. Upper bound estimates use longitudinal data to capture all-time invariant factors. Across all years and countries, lower bound estimates of IOp account from 6 percent to 60 percent of total income inequality, while upper bound estimates account from 20 percent to almost all income inequality. On average, upper bound IOp saw a slight decrease in the aftermath of the Great Recession, recovering and stabilizing at around 80 percent of total inequality in the second half of the 2010s. Lower bound estimates for 2005, 2011, and 2019 show a similar pattern. My findings suggest that lower and upper bound estimates complement each other, corroborating information and compensating each other's weaknesses, highlighting the relevance of a bounded estimate of IOp.     

Poverty-Reducing Tax Reforms with Heterogeneous Agents

The poverty impact of indirect tax reforms is analyzed using sequential stochastic dominance methods. This allows agents to differ in dimensions that cannot always be precisely captured within the usual money‐metric indicators of living standards. Examples of such dimensions include household size and composition, temporal or spatial variation in price indices, and individual needs and “merits.”     

CALCULATING A PRICE INDEX FOR FAMILIES WITH CHILDREN: IMPLICATIONS FOR MEASURING TRENDS IN CHILD POVERTY RATES

This paper investigates the effects of varying consumption patterns for families with and without children on measured trends in child poverty. We first use data from consumer expenditure surveys to calculate price indices by family type. We next examine the effect of using these group-specific price indices on measured trends in child poverty. Although we find that, all else equal, children increase the cost of living, our calculations indicate that on average families with children experienced relatively lower inflation rates than families without children during the 1968 to 1987 period. While this result suggests that estimates of child poverty rates calculated using an average price index may have over-stated secular increases in child poverty, we find that child poverty rates calculated using a price index specific lo families with children are not substantively different from those calculated using an average index for all families.     

Inequality at Low Levels of Aggregation in Chile

Despite success in poverty reduction, inequality in Chile has remained virtually unchanged over the last 20 years. High levels of inequality have been shown to hamper further reductions in poverty as well as economic growth, and local inequality has been shown to affect such outcomes as violence and health. The study of inequality at the local level is thus crucial for understanding the economic wellbeing of a country. Local measures of inequality have been difficult to obtain, but recent theoretical advances have enabled the combination of survey and census data to generate estimates of inequality that are robust at disaggregated geographic levels. We employ this methodology to produce consistent and precise estimates of inequality for every county in Chile. We find considerable heterogeneity in county‐level estimates of inequality, with Gini coefficients ranging from 0.41 to 0.64.     

Spatial differences in poverty: The case of Peru

This paper examines the implications of spatial differences in living costs for measures of poverty. Taking Peru as a case study, spatial price indices are used to calculate location-specific poverty lines, based on the local cost of a basket of basic needs. Applied to income distribution data, these poverty lines yield measures of the extent and location of poverty. The paper shows that these measures are significantly different from, and much more accurate than those obtained using a single countrywide poverty line; the latter can give a misleading picture of poverty by over- stating spatial differences, in general overestimating rural and underestimating urban poverty.     

A Proposal to Compare Consistently the Inequality Among the Poor

A poverty index should be sensitive to the number of poor people, the extent of the shortfall of the poor, and the inequality among the poor. A difficulty arises when inequality among the poor needs to be assessed. The inequality may be analyzed in terms of either incomes or gaps. Depending on what side we focus on, the inequality level comparisons may be contradictory. This paper proposes a reinterpretation of the inequality component involved in the decompositions of well‐known poverty indices. The alternative indices we introduce measure equally the income and gap inequality among the poor. The comparisons in inequality as measured by these indices are then independent of the viewpoint. An empirical application illustrates the proposal.     

SPACE AND TIME COMPARISONS OF PURCHASING POWER PARITIES AND REAL VALUES

The calculation of purchasing power parities and quantity comparisons for a given year provides interesting information about the relative importance of countries. However, it is necessary to make these estimates annually in order to enable users to apply these parities for international comparison of annual data expressed in national currency. The paper deals with the problems related to merging spatial comparisons and temporal volume and price movements for the countries of the European Community. For these countries full information was collected in 1975 and in 1980, whereas in the intermediate years some price data were collected and price indices at a detailed level have also been collected. First the theoretical problems of consistency between the spatial results and temporal indices are discussed. Because no immediate consistency can be obtained, several methods are proposed to achieve consistency, by estimating one unique set of spatial and temporal indices. The available information for the period 1975-80 has been used in order to test the numerical differences between two sets of parities and price indices over time. Besides theoretical reasons for inconsistency, it is also necessary to take into account errors in the price observations or in the price indices. The results presented in the paper should be considered as provisional and further work will be undertaken to obtain better insights into the inconsistency between these sets of data.     

A Decomposition Analysis of Regional Poverty in Russia

The paper applies a new decomposition technique to the study of variations in poverty across the regions of Russia. The procedure, which is based on the Shapley value in cooperative game theory, allows the deviation in regional poverty levels from the all‐Russia average to be attributed to three proximate sources: per capita income, inequality, and local prices. Contrary to expectation, regional poverty variations turn out to be due more to differences in inequality across regions than to differences in real income per capita. However, when real income per capita is split into nominal income and price components, differences in nominal incomes emerge as more important than either inequality or price effects for the majority of regions.     

Living Decently

One of the reasons why poverty lines became popular at the turn of the century was their promise of a scientific technique that would dispense with moralising about poverty. We argue that a price paid in this quest has been an impoverishment of the richness of the notion of 'a decent life', the moral concept underlying poverty. In addition, poverty lines have in practice been more to do with inequality at the bottom end of the income distribution than with poverty. The purpose of this article is to rehabilitate the measurement of poverty, and to make it credible. We set out our preferred method of poverty measurement, and illustrate it using data from the Australian Standard of Living Study. A feature of our approach is to distinguish clearly between issues of inequality and issues of poverty. Questions such as who is on the bottom of the income distribution, whether this has changed over time, and how income levels of the worst off compare with the mean, are questions of inequality. As such, the answers tell us nothing at all about how the worst off are actually living. To answer that question, we require direct measures of consumption and of social participation. These measures are not as simple, but they provide us with knowledge about poverty that poverty lines have promised, but have not delivered in a credible fashion.     

Decomposing poverty changes into vertical and horizontal components

Variations in aggregate poverty indices can be due to differences in average poverty intensity, to changes in the welfare distances between those poor of initially unequal welfare status and/or to emerging disparities in welfare among those poor of initially similar welfare status. This note uses a general cost‐of‐inequality approach that decomposes the total change in poverty into a sum of indices of each of these three components. This decomposition can serve inter alia to integrate horizontal and vertical equity criteria in the poverty alleviation assessment of social and economic programmes. The use of these measures is briefly illustrated using Tunisian data.     

The Political Economy of Austerity in Southern Europe

ABSTRACT

Europe’s response to the sovereign debt crisis in Southern Europe has been premised on the idea that these states can return to growth through internal devaluation and fiscal consolidation. This article explores the distributive consequences of that strategy in Greece, Portugal, Italy, and Spain. We argue that standard measures of poverty do not capture the deterioration in living standards as fully as anchored poverty. Moreover, we show that inequality trends conceal considerable re-ranking within the income distribution: those who were rich in 2012 had got richer in 2009–12, but those who were rich in 2009 lost ground in 2009–12. We find that in all four countries the new poor include significantly fewer pensioners and more unemployed workers, and are considerably poorer than the old poor had been. We demonstrate that there was significant variation in the magnitude and design of austerity, with Italy imposing a far smaller adjustment than Spain, and Portugal achieving less inequality in spite of robust fiscal consolidation. Nevertheless, even when austerity measures were designed to reduce inequality by compressing incomes downward, their second-order macro-economic effects ultimately increased inequality (except in Portugal). In the last section, we explore the political reasons for this variation.     

Poverty,inequality and growth in Albania

This article studies the distribution of well‐being and, specifically, the degree of poverty and deprivation in Albania, in the years 2002 and 2005, using Living Standard Measurement Surveys (LSMS). The distribution analysis is performed by applying both one‐dimensional and multidimensional approaches, in particular to better examine the link between economic growth, inequality and poverty in Albania. Furthermore, by estimating a non‐monetary indicator, as proposed by Bossert et al. ( 2007 ), and a nonlinear principal component model together with a probit model, the paper focuses on the multidimensional measures of poverty to address the relationship between poverty and socio‐economic factors. Our evidence shows that absolute poverty decreased from 2002 to 2005 while national relative poverty increased; economic growth reduced poverty in Albania over the observed period; and living in rural and mountain areas, being female, poorly educated and with a large family increased the probability of suffering from deprivation.     

THE MEASUREMENT OF POVERTY WITH GEOGRAPHICAL AND INTERTEMPORAL PRICE DISPERSION: EVIDENCE FROM RWANDA

It is not known to what extent welfare measures result from seasonal and geographical price differences rather than from differences in living standards across households. Using data from Rwanda in 1983, we show that the change in mean living standard indicators caused by local and seasonal price deflation is moderately significant at every quarter. By contrast, the differences in poverty measures caused by this deflation can be considerable, for chronic as well as transient or seasonal poverty indicators. Thus, poverty monitoring and anti-poverty targeting can be badly affected by inaccurate deflation of living standard data. Moreover, when measuring seasonal poverty, the deflation based on regional prices instead of local prices only partially corrects for spatial price dispersion. Using annual local prices instead of quarterly local prices only yields a partial deflation, which distorts the measure of poverty fluctuations across seasons and biases estimates of annual and chronic poverty.     

A Framework for the Simultaneous Measurement of Spatial Variation and Temporal Movement in Prices in a Heterogeneous Country: The Dynamic Household Regional Product Dummy Model

This paper contributes to the growing literature on spatial prices in large heterogeneous countries. While the literatures on spatial variation and temporal movement in prices have grown in parallel, this study marks a departure by providing a unified treatment and proposing a comprehensive framework that allows both approaches. The proposed model is based on twin extensions of the household version of the “country product dummy model” by allowing for a dynamic stochastic specification and interdependence of spatial prices of geographically adjacent regions. Tests of temporal stability and regional independence of the estimated spatial prices are proposed and applied in this paper. The paper shows that the introduction of an autoregressive error process of order one, AR(1), improves the efficiency of the estimates of parameters, urban‐rural and temporal price indices under certain conditions. The Indian application points to a rich potential for using the proposed framework in cross country comparisons such as the International Comparison Program (ICP) exercises.