Countering Local Data Manipulation in China

• In Event: Chinese Politics Mini-Conference: New Frontiers and Perspectives on Chinese Politics

Abstract

The manipulation of economic data has long been a concern in many authoritarian or developing countries. Using the case of China, this paper examines the effectiveness of different ways of countering local GDP manipulation: public shaming and power centralization. We adopt two complementary measurements of data report accuracy, and conduct difference-in-difference estimations that exploit the publication of data manipulation and a pilot that centralized the power of statistics reporting. We find public shaming to strongly reduce overreport of local GDP, although the effect seems to be temporary. However, no effect is detected for power centralization. We further explored the mechanisms of public shaming.

Authors

• Handi Li, University College London

• Shengqiao Lin, Harvard University

• Minh Duc Trinh, Purdue University