This study examines the relationship between capital account liberalisation and income inequality. Adopting a novel identification strategy, namely a difference-in-difference estimation combined with propensity score matching between the liberalised and closed countries, we provide robust evidence that opening the capital account is associated with an adverse impact on income inequality in developing countries. The main findings are threefold. First, fully liberalising the capital account is associated with a small rise of 0.07-0.30 standard deviations in the Gini coefficient in the short-run and a rise as large as 0.32-0.62 standard deviations in the ten years after liberalisation, on average. Second, widening income inequality is the outcome of the growing income share of the rich at the cost of the poor. The long-term effect of capital account liberalisation includes a reduction in the income share of the poorest half by 2.66-3.79 percentage points and an increase in the income share of the richest 10% by 5.19-8.76 percentage points. Third, the directions and categories of capital account liberalisation matter. Inward capital account liberalisation is more detrimental to income equality than outward capital account liberalisation, and free access to the international equity market exacerbates income inequality the most, while foreign direct investment has an insignificant impact on inequality.

We show, theoretically and empirically, that the effects of technological change associated with automation and offshoring on the labor market can substantially deviate from standard neoclassical conclusions when search frictions hinder efficient assortative matching between firms with heterogeneous tasks and workers with heterogeneous skills. Our key hypothesis is that better matches enjoy a comparative advantage in exploiting automation and a comparative disadvantage in exploiting offshoring. It implies that automation (offshoring) may reduce (raise) employment by lengthening (shortening) unemployment duration due to higher (lower) match selectivity. We find empirical support for this implication in a dataset covering 92 occupations and 16 sectors in 13 European countries from 1995 to 2010.

Using country-level panel data over 1995–2013 on within-country income inequality and foreign bank presence, this paper establishes a positive relation between the two, running from higher foreign bank presence to income inequality. Given that foreign bank participation increased by 62% over the period 1995 to 2013, our baseline results imply a 5.8% increase in the Gini coefficient on average over this period, ceteris paribus. These results are robust to the inclusion of country and year fixed effects and to the use of restrictions on foreign bank entry in the host countries as an instrumental variable. We show that this positive effect is channelled through the lack of greenfield entry and the associated lower levels of competition.

The German government provides discretionary investment grants to structurally weak regions in order to reduce regional inequality. We use a regression discontinuity design that exploits an exogenous discrete jump in the probability of regional actors to receive investment grants to identify the causal effects of the policy. We find positive effects of the programme on district-level gross value-added and productivity growth, but no effects on employment and gross wage growth.

The dispersion of individual returns to experience, often referred to as heterogeneity of income profiles (HIP), is a key parameter in empirical human capital models, in studies of life‐cycle income inequality, and in heterogeneous agent models of life‐cycle labor market dynamics. It is commonly estimated from age variation in the covariance structure of earnings. In this study, I show that this approach is invalid and tends to deliver estimates of HIP that are biased upward. The reason is that any age variation in covariance structures can be rationalized by age‐dependent heteroscedasticity in the distribution of earnings shocks. Once one models such age effects flexibly the remaining identifying variation for HIP is the shape of the tails of lag profiles. Credible estimation of HIP thus imposes strong demands on the data since one requires many earnings observations per individual and a low rate of sample attrition. To investigate empirically whether the bias in estimates of HIP from omitting age effects is quantitatively important, I thus rely on administrative data from Germany on quarterly earnings that follow workers from labor market entry until 27 years into their career. To strengthen external validity, I focus my analysis on an education group that displays a covariance structure with qualitatively similar properties like its North American counterpart. I find that a HIP model with age effects in transitory, persistent and permanent shocks fits the covariance structure almost perfectly and delivers small and insignificant estimates for the HIP component. In sharp contrast, once I estimate a standard HIP model without age‐effects the estimated slope heterogeneity increases by a factor of thirteen and becomes highly significant, with a dramatic deterioration of model fit. I reach the same conclusions from estimating the two models on a different covariance structure and from conducting a Monte Carlo analysis, suggesting that my quantitative results are not an artifact of one particular sample.

Die Berliner Mauer als das Symbol der deutschen Teilung ist mittlerweile länger verschwunden als sie gestanden hat, doch die Unterschiede innerhalb des Landes sind auch nach drei Jahrzehnten noch sichtbar. Jüngste Forschungsergebnisse zeigen jedoch, dass die Bruchkante der wirtschaftlichen Entwicklung nicht immer ausschließlich entlang der ehemaligen innerdeutschen Grenze verläuft, sondern neben dem West-Ost-Gefälle auch Süd-Nord- oder Stadt-Land-Unterschiede zutage treten.

In labor markets, some individuals have, or believe to have, less data on the determinants of success than others, e.g., due to differential access to technology or role models. We provide experimental evidence on when and how informational differences translate into performance differences. In a laboratory tournament setting, we varied the degree to which individuals were informed about the effort-reward relationship, and whether their competitor received the same or a different amount of information. We find performance is adversely affected only by worse relative, but not absolute, informedness. This suggests that inequity aversion applies not only to outcomes but also to information that helps achieve them, and stresses the importance of inequality in initial information conditions for performance-dependent outcomes.

In this article, we use cross-state panel and cross-U.S. commuting-zone data to look at the relationship between innovation, top income inequality and social mobility. We find positive correlations between measures of innovation and top income inequality. We also show that the correlations between innovation and broad measures of inequality are not significant. Next, using instrumental variable analysis, we argue that these correlations at least partly reflect a causality from innovation to top income shares. Finally, we show that innovation, particularly by new entrants, is positively associated with social mobility, but less so in local areas with more intense lobbying activities.