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When individual or household incomes are collected for administrative or scientific surveys, the accounting period is sometimes a month, sometimes a quarter, and sometimes a year. The accounting period likely affects the shape of the income distribution and the level of measured inequality. The present study systematically explores the sensitivity of inter-temporal and inter-regional inequality comparisons to the length of the accounting period.

Purpose: The paper analyzes the variability of labor incomes in Argentina from mid-1980s to 2005. The magnitude of income instability and its determinants are evaluated under different macroeconomic contexts. It also analyzes how income fluctuations have influenced income distribution. Finally, the income convergence hypothesis is explored.

Methodology/approach: Different quantitative procedures are employed to measure mobility from dynamic information coming from the regular household survey. Four periods are distinguished that are relatively homogeneous. Dynamic pseudo-panels are also considered.

Findings: The growth in occupational instability registered since the mid-1990s led to a high variability of incomes despite the macroeconomic stability enjoyed throughout the nineties. Moreover, the panorama of growing inequality in the distribution of monthly income (the usual measure employed in Argentina) is also appropriate to describe what happened with the changes in the distribution of more permanent incomes. Finally, long-term income mobility in Argentina is scarce, indicating that the income path does not converge to the general mean.

Research limitations/implications (if applicable): Data refer only to Greater Buenos Aires since microdata are not available for the other areas covered by survey for the entire period under analysis. However, results are reasonably representative of the whole urban areas of the country.

Originality/value of paper: This research identifies the relative importance of labor market and macroeconomic factors in explaining income mobility. Moreover, it is for the first time in Argentina that dynamic information coming from panel data and pseudo-panels are analyzed together.

The economic reality of the 1990s in Europe forced the labor markets to become more flexible. Using a consistent comparative dataset for 14 countries, the European Community Household Panel (ECHP), we explore the degree of earnings mobility and inequality across Europe, and the role of labor market institutions in understanding the cross-national differences in earnings mobility. We study the degree of rank mobility and the degree of mobility as equalizer of long-term earnings. The country ranking in long-term earnings inequality is similar with the country ranking in annual inequality, which is a sign of limited long-term equalizing mobility within countries with higher levels of annual inequality. In long-term earnings inequality, Denmark renders the most mobile earnings distribution with the second highest equalizing effect. The only disequalizing mobility in a lifetime perspective is found in Portugal. With respect to the relationship between earnings mobility and earnings inequality, we find a significant negative association both in the short and the long run. Based on the rankings in long-term Fields mobility and long-term inequality, Denmark is expected to have the lowest lifetime earnings inequality in Europe, followed by Finland, Austria, and Belgium. The Mediterranean countries (Spain and Portugal) are expected to have the highest long-term inequality. With respect to the institutional factors that may be related to earnings mobility, we bring evidence that the deregulation in the labor and product markets, the degree of unionization, the degree of corporatism and the spending on ALMPs are positively associated with earnings mobility.

This paper argues that the assumption of a homogeneous workforce, which is implicitly invoked in the decomposition analysis of changes in welfare indicators, hides the role that schooling and its returns may have on the understanding of these changes. Using Peruvian cross-sectional data for a period of 10 years (2004–2013) and counterfactual simulations, this paper finds that the main factor contributing to poverty reduction has been individuals’ changes in labor earnings, and the role of these changes has been less important in reducing income inequality. The main driving force of reduced income inequality has been the fall in returns to education, which at the same time has been one of the important factors to constraining the period’s remarkable progress in poverty reduction and expansion of the middle class.

We investigate the reasons why income inequality is so high in Spain in the EU context. We first show that the differential in inequality with Germany and other countries is driven by inequality among households who participate in the labor market. Then, we conduct an analysis of different household income aggregates. We also decompose the inter-country gap in inequality into characteristics and coefficients effects using regressions of the Recentered Influence Function for the Gini index. Our results show that the higher inequality observed in Spain is largely associated with lower employment rates, higher incidence of self-employment, lower attained education, as well as the recent increase in the immigration of economically active households. However, the prevalence of extended families in Spain contributes to reducing inequality by diversifying income sources, with retirement pensions playing an important role. Finally, by comparing the situations in 2008 and 2012, we separate the direct effects of the Great Recession on employment and unemployment benefits, from other more permanent factors (such as the weak redistributive effect of taxes and family or housing allowances, or the roles of education and the extended family).

This paper devises a new method for using the information contained in income-generating equations to “account for” or “decompose” the level of income inequality in a country and its change over time. In the levels decomposition, the shares attributed to each explanatory factor are independent of the particular inequality measure used. In the change decomposition, methods are presented to break down the contribution of each explanatory factor into a coefficients effect, a correlation effect, and a standard deviation effect. In an application to rising earnings inequality in the United States, it is found that schooling is the single most explanatory variable, only one other variable (occupation) has any appreciable role to play, and all of schooling’s effect was a coefficients effect.

This study used data from the General Social Survey (2011) to examine the trends in intergenerational educational mobility in Canada for the 1940–1989 birth cohorts. To this end, the purpose of this study is to focus on the relationship between mothers' education and children's education.

The study estimated intergenerational regression and correlation coefficients and several mobility indices, namely, the Prais–Shorrocks index, immobility index, upward mobility index and downward mobility index.

The study found considerable gender differences with respect to the trends in these coefficients and indices. The study found that, over the period of study, the correlation coefficient slightly increased for sons while it decreased for daughters. The Prais–Shorrocks index, immobility index, upward mobility index and downward mobility index show that educational mobility has increased for daughters while that of sons has decreased over time. Finally, the relative educational opportunities indicators also suggest a similar result that educational mobility has increased for the daughters while it fell for the sons.

A number of studies used Canadian data to examine intergenerational educational mobility. However, no study particularly focused on the relationship between mothers' education and children's education. In recent years, women's labor force participation rate and employment rate increased significantly. Thus, it will be interesting to see how mothers' education is related to children's education in Canada.

This chapter provides a detailed analysis of the recent evolution (1993–2007) of Brazilian income inequality. Particularly, we assess the contribution of different income sources to inequality, using three different decomposition techniques: Shorrocks (1982), Lerman and Yitzhaki (1985), and Gini decomposition. We exploit a recent dataset (PNAD, 2004) that allows the identification of different governmental transfer programs (Bolsa-Família, PETI, and BPC) and their impacts into inequality. While informal labor income and self-employment income reduces inequality in almost every measure, the opposite is true for public sector wages. Private formal labor income is becoming less important in explaining Brazilian inequality over time, but its behavior is still important, as it represents more than 40% of the total income. We find that social transfer programs have a limited, but positive impact on equality. On the other hand, dynamics of pensions attenuate the recent path of decreasing inequality in Brazil.