ESTIMATING SPATIAL CONSUMER PRICE INDICES THROUGH ENGEL CURVE ANALYSIS

In this paper we propose a method of estimating spatial multilateral price index numbers from cross‐section consumer expenditure data on different items using Engel curve analysis. The novelty of the procedure is that it overcomes the problem of data inadequacy, a problem that is shared by most of the developing countries. The procedure does not require item‐specific price/unit value data and price index numbers can be calculated from consumer expenditure data grouped by per capita income/total consumer expenditure class in a situation where unit level data are not available. To illustrate the method, we use published state‐specific data of the 50th round (1993–94) and 55th round (1999–2000) consumer expenditure surveys of India's National Sample Survey Organization (NSSO) and calculate the spatial consumer price index numbers for 15 major states of India, with All‐India taken as base, separately for the rural and the urban sector for each round.     

URBAN POVERTY IN CHINA AND ITS CONTRIBUTING FACTORS, 1986–2000

Food price increases and the introduction of radical social welfare and enterprise reforms during the 1990s generated significant changes in the lives of urban households in China. During this period urban poverty increased considerably. This paper uses household level data from 1986 to 2000 to examine what determines whether households fall below the poverty line over this period and investigates how the impact of these determinants has changed through time. We find that large households and households with more nonworking members are more likely to be poor, suggesting that perhaps the change from the old implicit price subsidies, based on household size, to an explicit income subsidy, based on employment, has worsened the position of large families. Further investigation into regional poverty variation indicates that over the 1986–93 period food price increases were also a major contributing factor. Between 1994 and 2000 the worsening of the economic situation of state sector employees contributed to the poverty increase.     

中国城镇家庭能源贫困评估*——基于微观调查数据的研究

我国扶贫工作重点已进入新阶段,从消除绝对贫困向缓解发展不平衡、不充分的相对贫困转变,从解决收入贫困向解决多维贫困转变,从重点解决农村贫困问题向统筹城乡扶贫转变。能源是人民生活质量的重要指标,能有效反映福利水平。了解我国城镇家庭能源消费的基本特征、准确测度能源贫困水平与分布,有助于为今后扶贫工作提供资料基础和科学管理依据。本文构建消费者能源消费决策分析框架,并运用第一次中国家庭能源消费调查数据,考察居民收入与能源消费之间的关系,并对中国城镇家庭能源贫困状况进行测度。研究发现,居民收入与能源消费之间存在S型非线性关系,能源价格、家庭特征、地域特征等因素在能源消费决策中都发挥重要影响。我国城镇家庭相对能源贫困较为严重,主要表现为能源可支付性问题。能源贫困率在20%左右,其中电力贫困程度更为严重,超过25%。家庭收入增长、户主受教育程度提高、城市电力基础设施的普及、城市环境规制水平的提升会显著降低城镇家庭陷入能源贫困的可能性,而电力价格上涨会显著增加城镇家庭陷入能源贫困的概率。     

Who Faces Higher Prices? An Empirical Analysis Based on Japanese Homescan Data

On the basis of household‐level scanner data (called homescan data) for Japan, we construct a household‐level price index and investigate the causes of price differences across households. We observe large price differentials across households, a result that is consistent with the previous research based on the data in the USA. However, the differences across age and income groups are small. In addition, we find that elderly people face higher prices than the younger ones, which is contrary to the results of the previous research. The most important determinant of the price level is the extent to which households rely on bargain sales; doubling purchases of goods at bargain sales decreases the price level by about 2%, while shopping frequency only has a limited effect on the price level.     

Caste, Inequality, and Poverty in India

This paper analyses inequality and poverty in India within the context of caste‐based discrimination. It does so by decomposing the difference between (caste) Hindu and Scheduled Caste (SC) and Scheduled Tribe (ST) households in: their average household incomes; their probabilities of being in different income percentiles; their probabilities of being at different levels of poverty into: a “discrimination effect”, which stems from the fact that a household's income level, into which its (income‐generating) profile translates, depends on whether it is SC/ST; an “attributes (or residual) effect” which stems from the fact that there are systematic differences between SC/ST and Hindu households in their (income‐generating) profiles. The results, based on unit record data for 28,922 households, showed that at least one‐third of the average income/probability differences between Hindu and SC/ST households was due to the “unequal treatment” of the latter.     

Impact of Socio-Economic factors on Consumption Expenditure through Public Distribution System in rural India

Impact of public distribution system (PDS) on poverty in rural India is established; however, how the households from different socio-economic backgrounds are procuring through PDS, relatively, needs study. With this objective, influence of factors like poverty status, family size, social group, religion, gender and occupation on probability of household incurring consumption expenditure through PDS has been studied by using unit level data of consumer expenditure survey of National Sample Survey Office (NSSO) and multinomial logistic regression technique. The study is restricted to food grains rice and wheat and reveals that probability of consumption, through PDS, of minorities, economically and socially backward classes are higher, in general.

     

Violence exposure and poverty: Evidence from the Burundi civil war

We investigate the relationship between exposure to the Burundi Civil War and household (food) poverty, using a three-wave household-level panel matched with data on local-level violence. We find that households living in localities exposed to the war have been subsequently more likely to be poor than non-exposed households. Within-household estimations, controlling for time-varying heterogeneity at the province level, confirm the positive impact of violence exposure on household poverty. We investigate some of the potential mechanisms at play in the violence – poverty nexus, and the role of violence exposure in household poverty dynamics over time. Our results notably suggest that the destruction of physical capital, as well as a shift of exposed households out of non-farm activities, shape poverty dynamics and lower their chances of durably remaining out of poverty.     

Poverty Dynamics,Violent Conflict,and Convergence in Rwanda

This paper analyzes the poverty impact of the violent events that affected Rwanda in the 1990s. The main objective of the paper is to identify systematically potential mechanisms linking violent conflict with changes in poverty across provinces and households in Rwanda before and after a decade of violence. In accordance with emerging literature on the long‐term economic effects of violent conflict, we find empirical evidence for economic convergence between richer and poorer Rwandan provinces and households following the conflict shocks. Using a small but unique panel of households surveyed before and after the conflict period, we find that households whose house was destroyed or who lost land ran a higher risk of falling into poverty. We do not find much evidence for an economic effect of violent deaths at the household level due to substitution effects of labor within the household. Non‐violent deaths however seem to increase income per adult equivalent for the survivors. Results are shown to be robust to sample selection and IV models.     

Assessment of the effects of targeted poverty alleviation policy on differently poverty-stricken households: A multi-propensity score weighting model

Eliminating poverty is a multifaceted global challenge and a focal point of global development governance. With the implementation of targeted poverty alleviation (TPA), China's poverty alleviation efforts have had significant achievements. This study provides a new perspective by classifying poverty-stricken households based on poverty root causes at the household level, a multi-propensity score weighting model based on counterfactual inference is employed to examine the poverty reduction effect and policy precision on six non-equivalent poverty-stricken household groups in a Chinese county. The results reveal that the poverty reduction effects differed among poverty-stricken households with different root causes of poverty. Specifically, households impoverished due to disability have the lowest income of the six groups. The assistance policy effects also vary significantly and are found to be poorly suited to poverty-stricken households a lack of labor force and funds. A robustness test confirms this conclusion and a more nuanced analysis reveals that these differences are reflected in the wage and transfer incomes. Therefore, to ensure the stability of poverty reduction and the sustainability of income for poverty-stricken households, relevant associated aid policies need to place different emphases based on their household characteristics.     

Testing Prediction Performance of Poverty Models: Empirical Evidence from Uganda

This paper examines the performance of a method of predicting poverty rates. Because most developing countries cannot justify the expense of frequent household budget surveys, additional low‐cost methods have been developed and used. The prediction method is based on a model linking the proportion of poor households to suitable explanatory variables (consumption proxies). These consumption proxies are variables that can be collected at much lower cost through smaller annual surveys. Several applications have shown that such models can produce poverty estimates with confidence intervals of a similar magnitude to the poverty estimates from the household budget surveys. There is, however, limited evidence of how well the methods perform out‐of‐sample. A series of seven household budget surveys conducted in Uganda in the period 1993–2005 allows us to test the prediction performance of the model. We test the poverty models by using data from one survey to predict the proportion of poor households in other surveys, and vice versa. The results are encouraging, as all models predict similar poverty trends. Although in most cases the predictions are precise, sometimes they differ significantly from the poverty level estimated from the survey directly.     

Non-monetary poverty in Togo: a multidimensional approach

The monetary approach is not sufficient to understand the multiple dimension of poverty. The purpose of this research is therefore to measure and analyze multidimensional poverty reduced to a single non-monetary dimension and according to the characteristics of household heads. Based on the non-monetary variables provided by the most recent country survey (QUIBB 2006), we use Multidimensional Correspondence Analysis techniques to construct a Composite Poverty Indicator. The results of the non-poverty index suggest that the poorest are large families and households in rural areas. The deprivation is also more serious in households whose heads are male, aged between 51 and 99 and less educated. The findings are the same for the monetary approach at the poverty line, leading to the conclusion that both types of poverty are quite strongly and positively correlated. Finally, we propose some recommendations for socioeconomic policies.     

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.     

POVERTY IN RURAL INDIA: CASTE AND TRIBE

This paper analyzes the determinants of rural poverty in India, contrasting the situation of scheduled caste (SC) and scheduled tribe (ST) households with the non-scheduled population. The incidence of poverty in SC and ST households is much higher than among non-scheduled households. By combining regression estimates for the ratio of per capita expenditure to the poverty line and an Oaxaca-type decomposition analysis, we study how these differences in the incidence of poverty arise. We find that for SC households, differences in characteristics explain the gaps in poverty incidence more than differences in transformed regression coefficients. In contrast, for ST households, differences in the transformed regression coefficients play the more important role.     

Poverty Mapping with Aggregate Census Data: What is the Loss in Precision?

Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some countries (notably China and India), national statistics agencies are reluctant, for reasons of confidentiality, to release household‐level census data, but they are generally more willing to release aggregated census data, such as village‐ or district‐level means. This paper examines the loss in precision associated with using aggregated census data instead of household‐level data to generate poverty estimates. The authors show analytically that using aggregated census data will result in poverty rates that are biased downward (upward) if the rate is below (above) 50%, and that the bias approaches zero as the poverty rate approaches zero, 50%, and 100%. Using data from Vietnam, it is found that the mean absolute error in estimating district‐level poverty rates is 2.5 percentage points if the census data are aggregated to the enumeration‐area level means, and 3–4 percentage points if the data are aggregated to commune or district level. Finally, the authors propose a method for reducing the error using variances calculated from the census. When this approach is applied to the Vietnam data, this method can cut the size of the aggregation errors by around 75%.     

Adding value through the mechanization of post-harvest cassava processing,and its impact on household poverty in north-eastern Zambia

This article investigates the impact of adopting a mechanized cassava processing system on household poverty levels in Zambia. An Foster, Greer and Thorbecke (FGT) poverty measure was used to compare poverty levels among households using a mechanized cassava processing system against those households using a nonmechanized process. Based on the FGT poverty measure’s specifications, a significantly lower poverty status of 49% was found among households using the mechanized process when compared to the 58% found among households using the nonmechanized process. The significant factors contributing to these differences in poverty levels include whether households are using a mechanized process or not, the number of years’ schooling among household members, the number of years’ farming experience, household income and membership of associations. The study concludes that the mechanization of cassava processing, particularly if done on the right scale, can transform primary production activities, in turn leading to higher incomes and reduced poverty levels in rural villages. Thus, policies should be introduced aimed at encouraging the promotion of mechanized post-harvest cassava processing technologies among rural households, so as to enhance crop productivity and household income levels, as well as reduce poverty among rural households.     

A Behavior‐Based Approach to the Estimation of Poverty in India

Estimates of poverty in India are crucial inputs for the understanding of world poverty, yet there is much disagreement about the numbers and the legitimacy of methods used to derive them. In this paper, we propose and justify an alternative approach to identify the poor, which uses the proportion of income spent on food. Our estimates have weaker data requirements than official methods, and they compare favorably with several validation tests. Most notably, households around our state poverty lines obtain their calories from similar sources, whereas this is not true of official poverty lines. We also find that rates of self‐reported hunger are higher in states that we classify as poor.     

Challenges and Changes in Gendered Poverty: The Feminization,De-Feminization,and Re-Feminization of Poverty in Latin America

Despite reductions in poverty generally, recent trends in Latin American countries show processes of both de-feminization and re-feminization of poverty. A rise in the numbers of women to men living in income-poor households has occurred despite feminized anti-poverty programs, most notably conditional cash transfers (CCTs), which target resources to women. This paper shows that methodological differences in what, how, and who is the focus of measurement may influence patterns of poverty “feminization.” It also suggests that feminized policy interventions might in themselves be playing a role in the re-feminization of poverty, not least because of data and definitional limitations in the way female-headed households and, relatedly, women’s poverty are understood. The somewhat paradoxical interactions between the feminization of household headship, the feminization of poverty, and the feminization of anti-poverty programs present interesting challenges for redressing gender gaps in poverty within the 2030 Agenda for Sustainable Development.     

Household composition,Engel curves and welfare comparisons between households: A duality approach

This paper is about household composition effects in consumer theory. These are important for the specification and estimation of Engel curves and demand functions. The models examined here have important applications in the areas of the measurement of cost of living indices, the study of poverty and inequality and in certain aspects of social policy. The models are based on the approach of Barten (1964). Taste differences between households are parameterized in a way which has been called simple good augmenting or simple repackaging in the literature on quality change. In this theory, changes in household composition play an analogous role to price changes. ‘True household equivalent scales’ are developed which are analogous to true cost of living indices and permit welfare comparisons across households.     

Household poverty and inequality: the implication of migrants’ remittances in Nigeria

This article examines the nature of migrant remittances and the amount by which income poverty and inequality will be reduced given migrants’ remittances. We used the living standard survey (NLSS) data set produced by the government of Nigeria to help track poverty reduction progress. The unit of analysis was the household, upon which information on remittances was analysed. From the results, 94% of households received remittances through internal channels while less than 5% received them through international channels. Remittances alleviated poverty head count by 20% and helped to equalize household income inequality by 25%.     

MEASURING MULTIDIMENSIONAL POVERTY: AN EMPIRICAL COMPARISON OF VARIOUS APPROACHES

This paper makes a systematic comparison of four approaches to multidimensional poverty analysis based respectively on the theory of fuzzy sets, information theory, efficiency analysis and axiomatic derivations of poverty indices. The database was the 1995 Israeli Census that provided information on the ownership of various durable goods. There appears to be a fair degree of agreement between the various multidimensional poverty indices concerning the identification of the poor households. The four approaches have also shown that poverty decreases with the schooling level of the head of the household, first decreases and then increases with his/her age and with the size of the household. Poverty is higher when the head of the household is single and lower when he/she is married, lowest when the head of the household is Jewish and highest when he/she is Muslim. Poverty is also higher among households whose head immigrated in recent years, does not work or lives in Jerusalem. These observations were made on the basis of logit regressions. This impact on poverty of many of the variables is not very different from the one that is observed when poverty measurement is based only on the income or the total expenditures of the households.