Closed-form estimation of nonparametric models with non-classical measurement errors

Yingyao Hu and Yuya Sasaki

Journal of Econometrics, 2015, vol. 185, issue 2, 392-408

Abstract: This paper proposes closed-form estimators for nonparametric regressions using two measurements with non-classical errors. One (administrative) measurement has location-/scale-normalized errors, but the other (survey) measurement has endogenous errors with arbitrary location and scale. For this setting of data combination, we derive closed-form identification of nonparametric regressions, and practical closed-form estimators that perform well with small samples. Applying this method to NHANES III, we study how obesity explains health care usage. Clinical measurements and self reports of BMI are used as two measurements with normalized errors and endogenous errors, respectively. We robustly find that health care usage increases with obesity.

Keywords: Closed form; Non-classical measurement errors; Nonparametric regressions (search for similar items in EconPapers)
JEL-codes: C14 C21 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:185:y:2015:i:2:p:392-408

DOI: 10.1016/j.jeconom.2014.11.004

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