Difference-in-differences with as few as two cross-sectional units -- A new perspective to the democracy-growth debate

Abstract

Pooled panel analyses tend to mask heterogeneity in unit-specific treatment effects. For example, existing studies on the impact of democracy on economic growth do not reach a consensus as empirical findings are substantially heterogeneous in the country composition of the panel. In contrast to pooled panel analyses, this paper proposes a Difference-in-Differences (DiD) estimator that exploits the temporal dimension in the data and estimates unit-specific average treatment effects on the treated (ATT) with as few as two cross-sectional units. Under weak identification and temporal dependence conditions, the DiD estimator is asymptotically normal. The estimator is further complemented with a test of identification granted at least two candidate control units. Empirical results using the DiD estimator suggest Benin's economy would have been 6.3% smaller on average over the 1993-2018 period had she not democratised.