Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/334159 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
I4R Discussion Paper Series No. 278
Verlag: 
Institute for Replication (I4R), s.l.
Zusammenfassung: 
Exploiting exogenous natural variation to study the impact of hard-to-randomize policies based on instrumental variables (IVs) is a widespread research design in economics. The key identification assumption underlying this design is the exclusion restriction, requiring the IV to affect the outcome variable only through the instrumented treatment variable. We review the literature using topography as an IV to show that systematic violations of this assumption are likely because of topography's ubiquity in socio-economic relationships. Furthermore, as topography often lacks first-stage strength, even subtle violations of the exclusion restriction undermine any causal inference. Instead of the vindication that often accompanies IV applications, we advocate a falsificationist approach to the use of topographic IVs, grounded in precaution and skepticism. We apply this approach to a seminal example of a topographic IV, Dinkelman (2011).
Schlagwörter: 
Causal inference
collider bias
topography
exclusion restriction
JEL: 
C26
C36
C52
O13
O18
Dokumentart: 
Working Paper

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