Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest.

Summary: This paper studies the effects of bilateral foreign aid on conflict escalation and deescalation. First, we develop a new ordinal measure capturing the two‐sided and multifaceted nature of conflict. Second, we propose a dynamic ordered probit estimator that allows for unobserved heterogeneity and corrects for endogeneity. Third, we identify the causal effect of foreign aid on conflict by predicting bilateral aid flows based on electoral outcomes of donor countries which are exogenous to recipients. Receiving bilateral aid raises the chances of escalating from small conflict to armed conflict, but we find little evidence that aid ignites conflict in truly peaceful countries.

This paper studies periods of prolonged contractions in output per capita in a sample of 145 countries from 1950 to 2014. Economic slumps are defined as abrupt interruptions of a period of growth by several regime switches. Slumps start with a sharp contraction along with a trend break, which is followed by another switch when growth stabilizes again. The paper then analyzes the correlates of these slumps, focusing on the length and depth of the contraction, from the beginning of the slump to its trough. The results establish three new stylized facts: (i) weak political institutions predate crises whereas political reforms tend to follow them, (ii) the length and depth of economic declines are robustly correlated with executive constraints and ethnic heterogeneity, and (iii) there is a robust interaction between these two variables, suggesting that institutions constraining leaders are important for stabilizing growth. This is particularly relevant for Sub-Saharan Africa, where politics are often ethnic and decision makers are comparatively unconstrained.

Summary: The ‘BCG hypothesis' suggests that the Bacillus Calmette-Guérin (BCG) vaccine against tuberculosis limits the severity of COVID-19. We exploit the differential vaccination practices of East Germany and West Germany prior to reunification to test this hypothesis. Using a difference in regression discontinuities (RD-DD) design centred on the end of universal vaccination in the West, we find that differences in COVID-19 severity across cohorts in the East and West are insignificant or have the wrong sign. We document a sharp cross-sectional discontinuity in the severity of the disease, which we attribute to limited mobility across the long-gone border and which disappears when we control for social connectedness. Case and death data after the end of the first lockdown on 26 April does not display a discontinuity at the former border, suggesting that mobility (as opposed to BCG vaccination) played a major role during the initial outbreak.

This paper analyzes periods of economic stagnation in a panel of countries. We test whether stagnation can be predicted by institutional characteristics and political shocks and compare the impacts of such variables with those of traditional macroeconomic variables. We examine the determinants of stagnation episodes using dynamic linear and nonlinear models. In addition, we analyze whether the effects of the included variables on the onset of stagnation differ from their effects on the continuation of stagnation. We find that inflation, negative regime changes, real exchange rate undervaluation, financial openness, and trade openness have significant effects on both the onset and the continuation of stagnation. Only for trade openness is there robust evidence of a differential impact. Open economies have a significantly lower probability of falling into stagnation, but once in stagnation they do not recover faster.