Bounding Omitted Variable Bias Using Auxiliary Data with an Application to Estimate Neighborhood Effects

68 Pages Posted: 16 Jun 2021 Last revised: 8 Aug 2022

Date Written: August 8, 2022

Abstract

This paper proposes a new estimator that bounds omitted variable bias using proxies for omitted variables with an asymptotically valid bootstrap procedure. The proxies do not need to appear in the same dataset as the outcome variable and the estimator is robust to measurement errors in proxies. I provide the open-source software to implement the estimator and its confidence interval. Next, I illustrate the application in the context of estimating neighborhood effect on intergenerational cultural transmission and find that growing up in an ethnic enclave could change some adulthood outcomes for second-generation immigrants that reflect their extent of cultural assimilation.

Keywords: Omitted Variable Bias, Two-Sample Least Squares, Data Combination, Data Fusion, Auxiliary Data, Proxy Variable, Intergenerational Cultural Transmission, Cultural Assimilation, Neighborhood Effect

JEL Classification: C01, C80, J01, J15, J16, J61, Z10, Z13

Suggested Citation

Hwang, Yujung, Bounding Omitted Variable Bias Using Auxiliary Data with an Application to Estimate Neighborhood Effects (August 8, 2022). Available at SSRN: https://ssrn.com/abstract=3866876 or http://dx.doi.org/10.2139/ssrn.3866876

Yujung Hwang (Contact Author)

Johns Hopkins University ( email )

3400 N. Charles Street, Wyman Bldg.
Baltimore, MD Maryland 21218
United States

HOME PAGE: http://https://sites.google.com/view/yujunghwang/home?authuser=0

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