A model based approach for predicting annual poverty rates without expenditure data

The primus inter pares of the UN-approved Millennium Development Goals is to reduce poverty. The only internationally accepted method of estimating poverty requires a measurement of total consumption based on a time-consuming and resource-demanding measure of household expenditure in an integrated survey over 12 months. Rather than measuring poverty, say, only every fifth year, a model is presented to predict poverty based on a small set of household variables to be collected annually between two 12-monthly household surveys. Information obtained from these “light” surveys might then be used to predict poverty rates. The key question is whether the inaccuracy in these predictions is acceptable. It is recommended that these models be tested at a country level and if the test results are similar to those found here, that this approach be adopted.      

Improving the measurement of child welfare in the context of intra-household inequality

This study aims to illustrate how to improve the evaluation of child economic well-being and child poverty using the collective approach. International organisations such as the World Bank, OECD and UNICEF have made important efforts in recent years to produce reliable data and to measure poverty according to the most relevant items of household consumption baskets. However, when measuring poverty, it is common practice to assume either that resources are distributed equally within the household or that there are fixed equivalence scales (for example, a child can be counted as 0.5 adults). The methodology based on collective models of consumption overcomes this rigidity by allowing inequality within each household to be taken into account. The method assumes that each household devotes a fraction of resources to children, which can be estimated using the observed expenditure on child-exclusive goods. An example of how child poverty measures can be inaccurately estimated is illustrated through the case of young children in Albania.     

Modeling Family Economic Conditions and Young Children’s Development in Rural United States: Implications for Poverty Research

In this study we examined the additive and multiplicative relations between poverty status, material hardship, liquid assets, non-liquid assets, and children’s cognitive skills and social problems at 36?months. The data were from a representative sample of 1,292 children in six rural counties in the United States. Findings indicated that income, material hardship, and non-liquid assets explained unique variation in young children’s development. Material hardship was associated with more social problems for children. Poverty status was associated with lower cognitive skills, and non-liquid assets were associated with higher cognitive skills at 36?months. We concluded that models that estimate the relation between poverty and child outcomes without including measures of hardship and assets could be underspecified.     

The impacts of the food,fuel and financial crises on poor and vulnerable households in Nigeria: A retrospective approach to research inquiry

This article examines the impacts of the financial, food and fuel crises on poor and vulnerable households in two states of Nigeria: Lagos and Kano. It uses retrospective household‐level data to analyze the impacts of induced price variability on household welfare. The results indicate that aggregate shocks have significant adverse effects on household consumption, schooling and child labour decisions, with a degree of impact heterogeneity across regions and rural and urban areas of the country. We find that the coping strategies adopted by the poor to deal with the short‐term effects of the crises can lock households in a low‐income equilibrium or poverty trap. Provided that covariate shocks exacerbate these effects, they become central for policy design.     

From Soviets to oligarchs: inequality and property in Russia 1905-2016

This paper combines national accounts, survey, wealth and fiscal data (including recently released tax data on high-income taxpayers) in order to provide consistent series on the accumulation and distribution of income and wealth in Russia from the Soviet period until the present day. We find that official survey-based measures vastly under-estimate the rise of inequality since 1990. According to our benchmark estimates, top income shares are now similar to (or higher than) the levels observed in the United States. We also find that inequality has increased substantially more in Russia than in China and other ex-communist countries in Eastern Europe. We relate this finding to the specific transition strategy followed in Russia. According to our benchmark estimates, the wealth held offshore by rich Russians is about three times larger than official net foreign reserves, and is comparable in magnitude to total household financial assets held in Russia.     

The possibilities for global inequality and poverty reduction using revenues from global carbon pricing

Global carbon pricing can yield revenues which are large enough to create significant global pro-poor redistributive opportunities. We analyze alternative multidecade growth trajectories from 2015 to 2105 for major global economies with carbon tax rates designed to stabilize emissions in the presence of both continued country growth and autonomous energy use efficiency improvement. In our central case analysis, revenues from globally internalizing carbon pricing rise to 8 % and then fall to 6 % of gross world product. High growth in India and China reduces global inequality and poverty strongly over time, but important incremental redistributive effects can be achieved using global carbon pricing revenues. Taking into account both between-country effects and previous literature estimates of within-country effects, a global carbon tax alone tends to be regressive in its global incidence. However, if its revenues are redistributed globally via equal per capita transfers, in our central case the Gini coefficient for world income falls by about 3 % and the share of the bottom decile rises by 81 % on average from 2015 to 2105. The population living in poverty falls by 16 % in 2015. Going further, global poverty could be eliminated entirely by 2015 according to our calculations if one third of global carbon tax revenues were redistributed directly to the poorest individuals.     

Why Did Semiconductor Price Indexes Fall So Fast in the 1990s? A Decomposition

Price deflators for semiconductors fell rapidly over the 1990s, pulled down by steep declines in the deflator for the microprocessor (MPU) segment that accelerated around 1995. A decomposition of a price index for Intel's MPUs suggests that virtually all of the declines in the price index—and the acceleration—can be attributed to quality increases associated with product innovation, rather than declines in the cost per chip. The sizable decline in Intel's margins from 1993–99 only accounted for about 6 percentage points of the average 24% decline per quarter in the price index and cannot explain the acceleration. (JEL D42, L63, O47)     

Politics by numbers: poverty reduction discourse,contestations and regime legitimacy in Ethiopia

There are contradictory statistics about the number of poor people and changes in number of poor people in Ethiopia with statistics ranging from 26 to 86% of the total population in 2013. This paper analyzed how such contradictory statistics feed into national politics focusing on who uses which statistics and based on what justifications of authoritativeness. Drawing from data collected from print newspapers, blogs, websites, published articles, party publications, and interviews with four key informants and combining an actor’s centered discourse analysis (ACDA) with Van Dick’s (1997) approach of identifying and analyzing political discourses, the paper deconstructed the poverty statistics debate in Ethiopia to understand the basic contestations. Synthesis of the data shows that poverty numbers are being used as tools for, and manifestations of, ongoing power struggles in Ethiopia whereby different actors selectively use poverty statistics that promote their political agenda. While doing so, the underlying rationale of actors for choosing one statistics over another was not based on the merit of their preferred set of statistics over the others but on the suitability of the data for their political purpose. As such, the government disregards statistics except its own which portray rapid poverty decline in the country while opposition groups actively use and promote statistics coming from international organizations that depict increasing poverty or a slow rate of reduction of poverty. The paper argues that the underlying cause of such politicization of numbers is linked with the developmental statism ideology of the ruling party in Ethiopia and how it tries to justify its rule in Ethiopia – claiming that it is reducing poverty and bringing development in Ethiopia and therefore should be allowed to continue in power. Therefore, in debating poverty numbers what is being debated is not just the statistics but the legitimacy of the government, hence politics by numbers.     

The concept and measurement of asset poverty: Levels, trends and composition for the U.S., 1983–2001

American prosperity in the second half of the 1980s together with the booming economy of the 1990s created the impression that American households have done well, particularly in terms of wealth acquisition. In this paper, we develop the concept of “asset poverty” as a measure of economic hardship, distinct from and complementary to the more commonly used concept of “income poverty.” We define a household with insufficient assets to enable it to meet basic needs (as measured by the income poverty line) for a period of three months to be asset poor. The results reveal that in the face of the large growth in overall assets in the U.S. and a fall in standard income poverty over the period from 1983 to 2001, the level of asset poverty increased from 22.4 to 24.5 percent. We also find that asset poverty rates for blacks and Hispanics are over twice those for whites; that asset poverty rates fall monotonically with both age and education; that they are much higher for renters than homeowners; and that by family type they range from a low of 5 percent for elderly couples to 71 percent for female single parents.     

Measuring the impact of price changes on poverty

This paper develops a methodology to measure the impact of price changes on poverty measured by an entire class of additive separable poverty measures. This impact is captured by means of the price elasticity of poverty. The total effect of changes in price on poverty is explained in terms of two components, income and distribution effects. The income effect measures the change in poverty when all prices increase uniformly, whereas the distribution effect captures the change in poverty because of changes in relative prices. Using this decomposition, the paper derives an empirically operational index, which reveals whether the price changes have been pro-poor or anti-poor. The paper also derives a new price index for the poor. While this index can be computed for any poverty measures, our empirical analysis applied to Brazil is based on three poverty measures, the head-count ratio, the poverty gap ratio and the severity of poverty. The empirical analysis shows that price changes in Brazil during the 1999–2006 periods have been anti-poor. Nevertheless, during the last 2 to 3 years, the price changes have affected the poor less adversely than the non-poor.     

Where Are the Children? Extent and Determinants of Preschoolers' Child Care Time

According to the 1988 National Health Interview Child Health Supplement, half of all children under age six attended nonparental child care on a regular basis. Close to a quarter of all children spent 40 or more hours per week in care. Average time in care was 30.5 hours for children in care. Statistical tests indicate that (a) the predictors of whether parents use any child care differ from the predictors of the number of hours care is used, and (b) estimates for children under three years of age differ from estimates for children from three to five years of age. The probability of attending care is related to a child's age, mother's education, race, family type, number and age of siblings, type of adults living in the household, income, poverty status, and region and size of the community in which a family resides. For children from three to five years of age, hours in care are associated with child's age, mother's education, race, family type, siblings, income, poverty status, and region. For children under three years of age, relatively few factors (mother's education, race, siblings, and region) predict the number of hours spent in child care.     

Population growth,inequality and poverty

In this discussion of population growth, inequality, and poverty, the type of relationships that can be observed in intercountry comparisons are explored, reviewing the findings of several other authors, presenting some new estimates using an International Labor Office data bank, considering some basic conceptual problems, and examining some of the theoretical and empirical issues that call for investigation at the national level. Intercountry comparisons, despite their limitations, appear to be the easiest starting point for empirical analysis. The approach adopted by most researchers has been to select 1 or more population indicators and a measure of national income inequality and to explain intercountry differences in 1 or both of these variables in terms of each other and of other indicators of economic and social development. Underlying this methodology is the assumption that there are aspects of demographic and economic change that are common to all countries included in the study, so that differences between countries give some guide to the likely evolution over time within any 1 country. This can be accepted at best with reservations, but given the scarcity of data on the evolution of inequality over time, a working hypothesis of this type appears unavoidable. But, as many of the factors likely to cause population growth and inequality operate over extended periods of time, a dynamic model is indicated. A simpler model, which pays particular attention to lags and variations over time, may generate new insights. A summary of the results of a new international cross-section analysis set up on these lines is presented. Results suggest that contrary to expectations, reducing population growth does not seem to generate longterm benefits for the poor in this model, though some short term gains are found. Increasing equality does appear to generate some decline in population growth, as well as persistent gains in incomes among the poor, but the reductions in population growth look small when set against the substantial reduction in inequality assumed. The central problem is that inequality and poverty are complex variables conceptually and empirically. 3 major sets of issues are particularly relevant: the nature of the unit of analysis; the reference period; and the conceptualization and measurement of welfare in relation to inequality and demographic change. In interpreting empirical findings, it is necessary to be aware of the different aspects of inequality and the correspondingly varied links with demographic change. The issues raised by the effects of inequality on population growth are distinct from those of population growth on the generation of inequality, and these are separated. Future research possibly will be most productive if it concentrates on the multiple roles of population growth in the transformation of systems of production.     

AVERAGE PREDICTIVE COMPARISONS FOR MODELS WITH NONLINEARITY, INTERACTIONS, AND VARIANCE COMPONENTS

In a predictive model, what is the expected difference in the outcome associated with a unit difference in one of the inputs? In a linear regression model without interactions, this average predictive comparison is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive comparison in general depends on the values of the predictors. We consider various definitions based on averages over a population distribution of the predictors, and we compute standard errors based on uncertainty in model parameters. We illustrate with a study of criminal justice data for urban counties in the United States. The outcome of interest measures whether a convicted felon received a prison sentence rather than a jail or non-custodial sentence, with predictors available at both individual and county levels. We fit three models: (1) a hierarchical logistic regression with varying coefficients for the within-county intercepts as well as for each individual predictor; (2) a hierarchical model with varying intercepts only; and (3) a nonhierarchical model that ignores the multilevel nature of the data. The regression coefficients have different interpretations for the different models; in contrast, the models can be compared directly using predictive comparisons. Furthermore, predictive comparisons clarify the interplay between the individual and county predictors for the hierarchical models and also illustrate the relative size of varying county effects.     

Poverty status probability: a new approach to measuring poverty and the progress of the poor

Poverty measurement and the analysis of the progress (or otherwise) of the poor, whether it is societies, families or individuals, is beset with difficulties and controversies surrounding the definition of a poverty line or frontier. Here, borrowing ideas from the mixture model literature, a new approach to assigning poverty-non poverty status is proposed which avoids specifying a frontier, the price is that an agent’s poverty status is only determined to the extent of its chance of being poor. Invoking variants of Gibrat’s law to give structure to the distribution of outcomes for homogeneous subgroups of a population within the context of a finite mixture model of societal outcomes facilitates calculation of an agent’s poverty status probability. From this it is straightforward to calculate all the usual poverty measures as well as other characteristics of the poor and non poor subgroups in a society. These ideas are exemplified in a study of 47 countries in Africa over the recent quarter century which reveals among other things a growing poverty rate and a growing disparity between poor and non poor groups not identified by conventional methods.     

Region-specific versus country-specific poverty lines in analysis of poverty

An analysis of poverty based on a country-specific income poverty line suffers from disregarding regional differences in prices and needs within a country and may, therefore, produce results that give a misleading picture of the extent of poverty as well as the geographic and demographic composition of the poor. To account for differences in prices and needs, this paper introduces an alternative method for identifying the poor based on a set of region-specific poverty lines. Applying Norwegian household register data for 2001 we find that the national level of poverty is only slightly affected by the change in definition of poverty line. However, the geographic as well as the demographic poverty profiles are shown to depend heavily on whether the method for identifying the poor relies on region- or country-specific thresholds. As expected, the results demonstrate that an analysis of poverty based on a country-specific threshold produces downward biased poverty rates in urban areas and upward biased poverty rates in rural areas. Moreover, when region-specific poverty thresholds form the basis of the poverty analysis, we find that the poverty rates among young singles and non-western immigrants are significantly higher than what is suggested by previous empirical evidence based on a joint country-specific poverty line.     

Correlates of perceived effectiveness of the Safe Schools/Healthy Students Initiative

A three-level growth-curve model was applied to estimate perceived impact growth trajectories, using multi-year data from project and school surveys on outcome and program implementation collected from 59 sites and approximately 1165 participating schools in the Safe Schools and Healthy Students Initiative. Primary interest is to determine whether and how project-level and school-level correlates affect schools’ perceptions of the Initiative's effectiveness over time when the effects of the pre-grant environmental conditions, grant operations, and near-term outcomes are considered. Coordination and service integration, comprehensive programs and activities for early childhood development, and change in school involvement were found to be significant predictors of school-perceived overall impact when the effect of poverty was considered. Partnership functioning, perceived importance of school resources, and school involvement were found to be significant predictors of school-perceived impact on substance use prevention when the effect of poverty was considered.     

DURABILITY, MAINTENANCE AND THE PRICE OF USED ASSETS

This paper considers assets whose service flow decays at a rate determined by built-in durability and the level of maintenance. A cost minimization model determines optimal durability and maintenance and shows how these variables respond to changes in interest rates, the price of maintenance, and the cost of new assets. The price of old assets adjusts so that the cost of services from both old and new assets is the same. The model provides a framework for analyzing data on automobile scrapping rates and repair expenditures. Data for postwar United States show that scrapping rates are sensitive to the price of repairs relative to the price of new cars. The amount of repairs per car also responds to the relative repair price .     

Subjective measures of household preferences and financial decisions

In intertemporal models of household consumption or portfolio choice, household behaviour depends on, for example, the household's rate of time preference, the rate of risk aversion, and the household's information set. In this paper we use a survey of Dutch households which contains direct subjective information on risk aversion and time preference and on interest in financial matters. We first describe these data and analyze how they relate to household characteristics and household income. We then investigate whether these variables are related to households' financial decisions on home ownership, mortgages and ownership of risky assets. Our results are broadly in accordance with economic theory.     

Placing Families in Context: Challenges for Cross‐National Family Research

Cross‐national comparisons constitute a valuable strategy to assess how broader cultural, political, and institutional contexts shape family outcomes. One typical approach of cross‐national family research is to use comparable data from a limited number of countries, fit similar regression models for each country, and compare results across country‐specific models. Researchers increasingly are adopting a second approach, which requires merging data from many more societies and testing multilevel models using the pooled sample. Although the second approach has the advantage of allowing direct estimates of the effects of nation‐level characteristics, it is more likely to suffer from the problems of omitted‐variable bias, influential cases, and measurement and construct nonequivalence. The author discusses ways to improve the first approach's ability to infer macro‐level influences as well as how to deal with challenges associated with the second one. She also suggests choosing analytical strategies according to whether the data meet multilevel models' assumptions.     

Growth and Poverty Reduction in Uganda, 1999–2000: Panel Data Evidence

To explore factors underlying growth and poverty reduction in Africa while overcoming some of the limitations of cross‐country analysis, this article uses micro‐level survey and panel‐data evidence from Uganda spanning 1992–2000. The high elasticity of both income growth and poverty reduction with respect to agricultural output (coffee) prices confirms the benefits from Uganda's decisive liberalisation of output markets. It also suggests the importance of product diversification to protect the poor against price shocks and the potential of cotton‐market improvements in tackling persistent poverty in the North. The importance of improving access to basic education and health care emerges more clearly than in cross‐country analysis, but benefits depend on complementary investments in electricity and other infrastructure, and reductions in civil strife.