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The rank-based measures of intergenerational mobility have become increasingly popular in economics literature. Recent evidence shows that rank-based measures are less affected by measurement error and life-cycle bias compared with other standard measures such as intergenerational regression coefficient and intergenerational correlation. However, most of the available household surveys suffer from sample truncation, because coresidency is used to define household membership. There is no evidence on how sample truncation affects the rank-based mobility estimates relative to intergenerational regression coefficient and intergenerational correlation. This paper provides evidence on this in the context of intergenerational schooling persistence, using two exceptional surveys from India and Bangladesh that include all children irrespective of residency status. The analysis shows that the measures of relative mobility (slopes) are biased downward in coresident samples, but the average bias in rank correlation is less than half of that in intergenerational regression coefficient, and comparable to that in intergenerational correlation in magnitude. The intercept estimates are biased upward, with the largest bias found in the intercept of the regression used for intergenerational correlation. Truncation bias in rank-based absolute mobility estimates is the lowest in most cases. The results strengthen the case for rank-based measures of intergenerational mobility when working with the standard household surveys.

Household income surveys often fail to capture top incomes which leads to an underestimation of income inequality. A popular solution is to combine the household survey with data from income tax records, which has been found to result in significant upward corrections of inequality estimates. Unfortunately, tax records are unavailable in many countries, including most of the developing world. In the absence of data from tax records, this study explores the feasibility of using data on house prices to estimate the top tail of the income distribution. In an application to Egypt, where estimates of inequality based on household surveys alone are low by international standards, the study finds strong evidence that inequality is indeed being underestimated by a considerable margin. The Gini index for urban Egypt is found to increase from 36 to 47 after correcting for the missing top tail.

The subject of which firms are the key employers—and which of these create or destroy jobs at a faster rate—is eminently important for academics and policy makers. The relative importance of small versus large firms and old versus young firms has in particular been extensively debated and studied. Nevertheless, the results often hinge on the questions that are asked. Moreover, the categorical definitions used to define firm size and age, and the nature and coverage of the data used have important effects. This paper lays out the relevant definitions and metrics that are central to the debate, reviewing the main findings to date on the subject (with particular emphasis on results in developing economies). The paper adds updated results for 117 developing economies using the World Bank’s Enterprise Survey Data, finding that (i) small and medium enterprises and older establishments are the dominant employers in the nonagricultural private sector labor force in developing economies, and (ii) net job creation is negatively correlated with establishment age and, although the effect of size is also negative, its significance is sensitive to the definition and methods used.

This paper provides empirical evidence for the Keynesian demand-driven propagation: initial rounds of job losses lead to additional rounds of job losses. The paper shows that U.S. counties with higher pre-existing exposure to tradable industries experienced larger job losses in non-tradable sectors during the Great Recession. This was arguably because laid-off tradable workers cut their consumption, which hurts local non-tradable firms. The finding is not driven by exposure to the construction sector, by the collapse in house prices, or by credit supply problems. In addition, the spillover is stronger when the focus is on the job losses of more income-elastic non-tradable sectors.

This study analyzes the extent of downward bias in the calculation of inequality of opportunity for continuous outcomes such as income. A typically recognized source of bias is the unobserved circumstances as there is a limited set of variables available in household and labor force surveys. Another previously overlooked source is the likely unobservable nature of top incomes. Using Monte Carlo simulations where the underlying inequality of opportunity is predetermined at various levels, the study presents three key findings. First, the omission of a relevant circumstance can bias the inequality of opportunity estimate by as much as 80 percent, depending on how much variation of the outcome such circumstance explains. Second, not observing the top 5 percent of the income distribution can lead to downward biases of anywhere between 12 and 35 percent, and the combination of missing the most favored population and even one relevant circumstance exacerbates the bias of the empirical estimates. The third key result is that the estimated inequality of opportunity is strongly correlated with the amount of variation in the outcome variable explained by the combination of circumstances (measured by the R2). This result suggests that in empirical applications, the inequality of opportunity estimate can be roughly (and quickly) approximated using simple econometric techniques.

When measuring inequality of opportunity, researchers usually opt to eliminate within-type variation. Provided that in practice it is impossible to observe all circumstances, this implies that the researcher estimates a lower bound of the true level of inequality of opportunity. By using data drawn from 27 Demographic Household Surveys (circa 2008), it is found that lower bound estimates can have substantial measurement error, and that measurement error can vary considerably across countries. As a consequence, lower bound estimates of inequality of opportunity can demand too little redistribution to equalize inequalities due to circumstances and can make the “traditional” cross-country comparisons misleading.

Drawing on a new set of nationally representative, internationally comparable household surveys, this paper provides an overview of key features of structural transformation—labor allocation and labor productivity—in four African economies. New, micro-based measures of sector labor allocation and cross-sector productivity differentials describe the incentives households face when allocating their labor. These measures are similar to national accounts-based measures that are typically used to characterize structural changes in African economies. However, because agricultural workers supply far fewer hours of labor per year than do workers in other sectors, productivity gaps disappear almost entirely when expressed on a per-hour basis. What look like large productivity gaps in national accounts data could really be employment gaps, calling into question the prospective gains that laborers can achieve through structural transformation. These employment gaps, along with the strong linkages observed between rural non-farm activities and primary agricultural production, highlight agricultures continued relevance to structural change in Sub-Saharan Africa.

High labor tax wedges and slow formal employment growth have combined to make labor tax reform an important economic policy issue in Turkey. This synthesis report presents the results of a series of empirical studies of the impact of a labor tax reform. The analysis was undertaken before the social contribution reforms that were introduced as part of the 2008 employment package. Using data from firms, households, and social insurance files, the research finds that employment does respond to changes in labor costs at levels that are comparable to those found in other middle-income and Organization for Economic Co-operation and Development (OECD) countries. The results show that reducing labor costs could significantly boost registered employment. However, the actual effect of lower taxes on employment would be diluted because a significant portion of the reduced tax will be captured by workers through higher wages rather than by employers through lower labor costs. As a result, tax cuts targeted towards low-wage labor would be more cost-effective than across-the-board reductions. To achieve overall fiscal neutrality, compensating additional revenues from other sources or reduced expenditures will be needed to accompany lower contribution rates.

Export diversification can lead to higher growth. Developing countries should diversify their exports since this can, for example, help them to overcome export instability or the negative impact of terms of trade in primary products. The process of economic development is typically a process of structural transformation where countries move from producing "poor-country goods" to "rich-country goods." Export diversification does play an important role in this process. The author also provides robust empirical evidence of a positive effect of export diversification on per capita income growth. This effect is potentially nonlinear with developing countries benefiting from diversifying their exports in contrast to the most advanced countries that perform better with export specialization.