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A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years

Author

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  • Mauricio Villamizar‐Villegas
  • Freddy A. Pinzon‐Puerto
  • Maria Alejandra Ruiz‐Sanchez

Abstract

In this paper we detail the entire Regression Discontinuity Design (RDD) history, including its origins in the 1960s, and its two main waves of formalization in the 1970s and 2000s, both of which are rarely acknowledged in the literature. Also, we dissect the empirical work into fuzzy and sharp designs and provide some intuition as to why some rule‐based criteria produce imperfect compliance. Finally, we break the literature down by economic field, highlighting the main outcomes, treatments, and running variables. Overall, we see some topics in economics gaining importance through time, like the cases of health, finance, crime, environment, and political economy. In particular, we highlight applications in finance as the most novel. Nonetheless, we recognize that the field of education stands out as the uncontested RDD champion through time, with the greatest number of empirical applications.

Suggested Citation

  • Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
  • Handle: RePEc:bla:jecsur:v:36:y:2022:i:4:p:1130-1178
    DOI: 10.1111/joes.12461
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    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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