Methods to Estimate Causal Effects - An Overview on IV, DiD and RDD and a Guide on How to Apply them in Practice

Collischon M (2021)


Publication Type: Other publication type

Publication year: 2021

DOI: 10.31235/osf.io/usvta

Abstract

The identification of causal effects has gained increasing attention in social sciences over the last years and this trend also has found its way into sociology, albeit on a relatively small scale. This article provides an overview of three methods to identify causal effects that are rarely used in sociology: instrumental variable (IV) regression, difference-in-differences (DiD), and regression discontinuity design (RDD). I provide intuitive introductions to these methods, discuss identifying assumptions, limitations of the methods, promising extension, and present an exemplary study for each estimation method that can serve as a benchmark when applying these estimation techniques. Furthermore, the online appendix to this article contains Stata syntax that simulates data and shows how to apply these techniques in practice.

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How to cite

APA:

Collischon, M. (2021). Methods to Estimate Causal Effects - An Overview on IV, DiD and RDD and a Guide on How to Apply them in Practice.

MLA:

Collischon, Matthias. Methods to Estimate Causal Effects - An Overview on IV, DiD and RDD and a Guide on How to Apply them in Practice. 2021.

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