We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Online ordering is currently unavailable due to technical issues. We apologise for any delays responding to customers while we resolve this. For further updates please visit our website: https://www.cambridge.org/news-and-insights/technical-incident
Yiqing Xu (Massachusetts Institute of Technology)
Causal Inference with Time-Series Cross-Section Data with Applications to Chinese Political Economy
Citation:
The first chapter and main methodological contribution of Xu's dissertation is the development of a new method for causal inference in time-series cross-sectional data, which he refers to as the "Generalized Synthetic Control Method." As the name implies, the method generalizes the synthetic control method (Abadie et al. 2010) to multiple treatment units and to variable treatment periods. It also unifies linear fixed effects models and difference-in-differences estimators as special cases. Compared to those existing methods, Xu's method often improves both robustness and efficiency, which he demonstrates analytically and via simulations. Subsequent chapters of Xu's dissertation apply this new method to empirical questions in Chinese political economy.