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Testing missing at random using instrumental variables
Breunig, Christoph - 2015
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...
Persistent link: https://www.econbiz.de/10010503886
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Testing missing at random using instrumental variables
Breunig, Christoph - 2017
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic's...
Persistent link: https://www.econbiz.de/10011894725
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Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models
Baltagi, Badi H.; Pirotte, Alain; Yang, Zhenlin - 2020
We propose an Adjusted Quasi-Score (AQS) method for constructing tests for homoskedasticity in spatial econometric models. We first obtain an AQS function by adjusting the score-type function from the given model to achieve unbiasedness, and then develop an Outer-Product-of-Martingale-Difference...
Persistent link: https://www.econbiz.de/10012305035
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Time-varying instrumental variable estimation
Giraitis, Liudas; Kapetanios, George; Marcellino, … - 2020
We develop non-parametric instrumental variable estimation and inferential theory for econometric models with possibly endogenous regressors whose coefficients can vary over time either deterministically or stochastically, and the time-varying and uniform versions of the standard Hausman...
Persistent link: https://www.econbiz.de/10012262677
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Breaking ties : regression discontinuity design meets market design
Abdulkadiroğlu, Atila; Angrist, Joshua D.; Narita, Yusuke - 2019
Centralized school assignment algorithms must distinguish between applicants with the same preferences and priorities. This is done with randomly assigned lottery numbers, nonlottery tie-breakers like test scores, or both. The New York City public high school match illustrates the latter, using...
Persistent link: https://www.econbiz.de/10011989205
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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 econometric techniques aimed at addressing endogeneity problems, including …
Persistent link: https://www.econbiz.de/10014025557
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Dummy Endogenous Treatment Effect Estimation Using High-Dimensional Instrumental Variables
Zhong, Wei - 2020
Dummy endogenous variables are commonly encountered in program evaluations using observational data. Motivated by the increasing availability of rich micro data, we develop a two-stage approach to estimate the dummy endogenous treatment effect using high-dimensional instrumental variables (IV)....
Persistent link: https://www.econbiz.de/10012833601
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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
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Testing missing at random using instrumental variables
Breunig, Christoph - 2017
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...
Persistent link: https://www.econbiz.de/10011619523
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Testing missing at random using instrumental variables
Breunig, Christoph - In: Journal of business & economic statistics : JBES ; a … 37 (2019) 2, pp. 223-234
Persistent link: https://www.econbiz.de/10012176614