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IV Quantile Regression for Group-Level Treatments, with an Application to the Effects of Trade on the Distribution of Wages
Chetverikov, Denis - 2013
We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group-level unobservables, a quantile extension of Hausman and Taylor (1981). Standard quantile regression techniques are inconsistent in this setting, even...
Persistent link: https://www.econbiz.de/10013071528
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Estimating causal effects with observational data guidelines for agricultural and applied economists
Henningsen, Arne; Low, Guy; Wuepper, David; Dalhaus, Tobias - 2024
observational data requires appropriate research designs and convincing identification strategies, which are usually very difficult … that results are interpreted as causal despite lacking a robust identification strategy, which has contributed to a … discuss the chosen identification strategies in their publications. …
Persistent link: https://www.econbiz.de/10015162983
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Bounding program benefits when participation is misreported
Tommasi, Denni; Zhang, Lina - 2020
In empirical research, measuring correctly the benefits of welfare interventions is incredibly relevant for policymakers as well as academic researchers. Unfortunately, the endogenous program participation is often misreported in survey data and standard instrumental variable techniques are not...
Persistent link: https://www.econbiz.de/10012243324
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Historical Econometrics : Instrumental Variables and Regression Discontinuity Designs
Valencia Caicedo, Felipe - 2020
, acknowledging that there are other useful sources of identification available to tackle potential endogeneity issues …
Persistent link: https://www.econbiz.de/10012824629
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Instrumental Variables with Unobserved Heterogeneity in Treatment Effects
Mogstad, Magne; Torgovitsky, Alexander - National Bureau of Economic Research - 2024
This chapter synthesizes and critically reviews the modern instrumental variables (IV) literature that allows for unobserved heterogeneity in treatment effects (UHTE). We start by discussing why UHTE is often an essential aspect of IV applications in economics and we explain the conceptual...
Persistent link: https://www.econbiz.de/10015072869
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Outlier Robust Inference in the Instrumental Variable Model With Applications to Causal Effects
Klooster, Jens; Zhelonkin, Mikhail - 2021
The instrumental variable model is one of the central tools for the analysis of causal relationships in observational data. The Anderson and Rubin (1949) test is an important method that allows for reliable inference in the instrumental variable model when the instruments are weak. Yet, the...
Persistent link: https://www.econbiz.de/10013210938
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Causal inference with endogenous price response
Jeziorski, Przemyslaw; Leng, Dingzhe; Seiler, Stephan - 2025 - This draft: May 10, 2025
We study the estimation of causal treatment effects on demand when treatment is randomly assigned but prices adjust in response to treatment. We show that regressions of demand on treatment or on treatment and price lead to biased estimates of the direct treatment effect. The bias in both cases...
Persistent link: https://www.econbiz.de/10015404498
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Instrumental Variables and the Sign of the Average Treatment Effect
Machado, Cecilia - 2019
This paper considers identification and inference about the sign of the average effect of a binary endogenous regressor …
Persistent link: https://www.econbiz.de/10012892857
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Chapter 7. Endogeneity in Empirical Corporate Finance 1
Roberts, Michael R.; Whited, Toni M. - 2013
This chapter discusses how applied researchers in corporate finance can address endogeneity concerns. We begin by reviewing the sources of endogeneity—omitted variables, simultaneity, and measurement error—and their implications for inference. We then discuss in detail a number of...
Persistent link: https://www.econbiz.de/10014025557
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A comparison of two qantile models with endogeneity
Wüthrich, Kaspar - 2014
This paper analyzes estimators based on the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2004, 2005, 2006) under the local quantile treatment effects (LQTE) framework (Abadie et al., 2002). I show that the quantile treatment effect (QTE) estimators in the IVQR...
Persistent link: https://www.econbiz.de/10010437770