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.

The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.

In the canonical DMP model of job openings, all job openings stem from new job creation. Jobs denote worker-firm matches, which are destroyed following worker quits. Yet, employers classify 56 percent of vacancies as quit-driven replacement hiring into old jobs, which evidently outlived their previous matches. Accordingly, aggregate and firm-level hiring tightly track quits. We augment the DMP model with longer-lived jobs arising from sunk job creation costs and replacement hiring. Quits trigger vacancies, which beget vacancies through replacement hiring. This vacancy chain can raise total job openings and net employment. The procyclicality of quits can thereby amplify business cycles.

In this paper we analyse how the terms of trade (TOT) – the ratio of export prices to import prices – affect total factor productivity (TFP). We provide empirical macroeconomic evidence for the European Union countries based on the times series SVAR analysis and microeconomic evidence based on industry level data from the Competitiveness Research Network (CompNet) database which shows that the terms of trade improvements are associated with a slowdown in the total factor productivity growth. Next, we build a theoretical model which combines open economy framework with the endogenous growth theory. In the model the terms of trade improvements increase demand for labour employed in exportable goods production at the expense of technology production (research and development – R&D) which leads to a shift of resources from knowledge development towards physical exportable goods. This reallocation has a negative impact on the TFP growth. Under a plausible calibration the model is able to replicate the observed empirical pattern.