The Econometrics Journal published its third and final issue of 2020. Stanley Cho’s lead article applies synthetic control methods to quantify the impact of Sweden’s early COVID-19 response on infections and mortality. He find that stricter initial containment measures could have reduced the number of infections by 75 percent and the excess mortality rate by 25 percentage points. This article nicely exemplifies that the Journal’s scope extends beyond the development of new econometric theory and methods, to novel applications of such methods to important and current empirical problems. Like all earlier Editors’ Choices of lead article, it is freely available from OUP.
The issue contains three further regular articles, each illustrating its novel contributions to econometrics with an empirical application.
Shenglong Liu, Ismael Mourifié, and Yuanyuan Wan study the identification and estimation of meaningful treatment effects in cases where candidate instruments do not satisfy the usual exogeneity and monotonicity conditions, but particular two-way exclusion restrictions on variables affecting treatment and outcomes hold. They use their approach to determine the variation in the return to schooling with regional development levels in China.
The issue also contains the long awaited Special Issue on the Methodology and Applications of Structural Dynamic Models and Machine Learning, edited by former Co-editor John Rust and guest editors Fedor Iskhakov and Bertel Schjerning.