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A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years

Author

Listed:
  • Mauricio Villamizar-Villegas

    (Banco de la República de Colombia)

  • Freddy A. Pinzón-Puerto
  • María Alejandra Ruiz-Sánchez
Abstract
In this paper we detail the entire Regression Discontinuity Design (RDD) history, including its origins in the 1960’s, and its two main waves of formalization in the 1970’s and 2000’s, 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 employed. 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. **** RESUMEN: En este artículo detallamos toda la historia sobre el Diseño de Regresiones Discontinuas (RDD), incluyendo sus orígenes en los 60s, y sus dos olas principales de formalización en los años 70s y 00s, las cuales rara vez son reconocidas en la literatura. Además, diferenciamos el trabajo empírico en diseños difusos y nítidos, y proporcionamos cierta intuición de por qué algunos criterios basados en reglas producen asignación imperfecta. Finalmente, desglosamos la literatura por campo económico, destacando los principales resultados, tratamientos y variables de asignación empleadas. En general, vemos algunos temas en economía que cobran importancia a través del tiempo, como los casos de: salud, finanzas, crimen, medio ambiente y política económica. En particular, destacamos las aplicaciones en finanzas como las más novedosas. No obstante, reconocemos que el campo de la educación se destaca como el campeón indiscutible de RDD a través del tiempo, con el mayor número de aplicaciones empíricas.

Suggested Citation

  • Mauricio Villamizar-Villegas & Freddy A. Pinzón-Puerto & María Alejandra Ruiz-Sánchez, 2020. "A Comprehensive History of Regression Discontinuity Designs: An Empirical Survey of the last 60 Years," Borradores de Economia 1112, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:1112
    DOI: https://doi.org/10.32468/be.1112
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    3. Agarwal, Natasha & Chan, Jackie M.L. & Lodefalk, Magnus & Tang, Aili & Tano, Sofia & Wang, Zheng, 2023. "Mitigating information frictions in trade: Evidence from export credit guarantees," Journal of International Economics, Elsevier, vol. 145(C).
    4. Wilmar Cabrera & Santiago Gamba & Camilo Gómez & Mauricio Villamizar-Villegas, 2022. "Examining Macroprudential Policy through a Microprudential Lens," Borradores de Economia 1212, Banco de la Republica de Colombia.
    5. Huang, Bin & Li, Bo & Walker, Ian & Zhu, Yu, 2022. "Does It Pay to Attend More Selective High Schools? Regression Discontinuity Evidence from China," IZA Discussion Papers 15756, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Regression Discontinuity Design; Fuzzy and Sharp Designs; Empirical Survey; RDD Formalization; Regresión Discontinua; Diseño Nítido y Borroso; Formalización de RDD;
    All these keywords.

    JEL classification:

    • 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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