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Regression Discontinuity Designs with a Continuous Treatment

Yingying Dong, Ying-Ying Lee and Michael Gou

Discussion papers from Research Institute of Economy, Trade and Industry (RIETI)

Abstract: Many empirical applications of regression discontinuity (RD) designs involve a continuous treatment. This paper establishes identification and bias-corrected robust inference for such RD designs. Causal identification is achieved by utilizing changes in the distribution of the continuous treatment at the RD threshold (including the usual mean change as a special case). Applying the proposed approach, we estimate the impacts of capital holdings on bank failure in the pre-Great Depression era. Our RD design takes advantage of the minimum capital requirements which change discontinuously with town size. We find that increased capital has no impacts on the long-run failure rates of banks.

New Economics Papers: this item is included in nep-ecm and nep-his
Date: 2019-08
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