Handling Spillover Effects in Empirical Research: An Application using Credit Supply Shocks

Tobias Berg, Daniel Streitz

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

Despite their importance, the discussion of spillover effects in empirical research misses the rigor dedicated to endogeneity concerns. We show that i) even with random treatment, spillovers lead to an intricate bias in estimating treatment effects, ii) there is a trade-off between endogeneity and spillover concerns, iii) the practice of using individual level regressions to identify direct effects and aggregate level regressions to learn about spillover effects can lead to misleading conclusions. We develop a simple guidance for empirical researchers, apply it to a credit supply shock, and highlight differences in the results compared to current empirical practice.
Original languageEnglish
Publication date2019
Number of pages52
Publication statusPublished - 2019
EventSFS Cavalcade North America 2019 - Carnegie Mellon University, Pittsburgh, United States
Duration: 20 May 201923 May 2019
https://www.conftool.com/sfs-cavalcade-2019/sessions.php

Conference

ConferenceSFS Cavalcade North America 2019
LocationCarnegie Mellon University
CountryUnited States
CityPittsburgh
Period20/05/201923/05/2019
Internet address

Bibliographical note

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Keywords

  • Spillovers
  • Credit supply
  • Direct vs. indirect effects
  • Aggregate effects

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