全球智库信息集成服务系统(G2TT): A New Control Function Approach for Non-Parametric Regressions with Endogenous Variables

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w16679
来源ID	Working Paper 16679
	A New Control Function Approach for Non-Parametric Regressions with Endogenous Variables
	Kyoo il Kim; Amil Petrin
发表日期	2011-01-13
出版年	2011
语种	英语
摘要	When the endogenous variable enters the structural equation non-parametrically the linear Instrumental Variable (IV) estimator is no longer consistent. Non-parametric IV (NPIV) can be used but it requires one to impose restrictions during estimation to make the problem well-posed. The non-parametric control function estimator of Newey, Powell, and Vella (1999) (NPV-CF) is an alternative approach that uses the residuals from the conditional mean decomposition of the endogenous variable as controls in the structural equation. While computationally simple identification relies upon independence between the instruments and the expected value of the structural error conditional on the controls, which is hard to motivate in many economic settings including estimation of returns to education, production functions, and demand or supply elasticities. We develop an estimator for non-linear and non-parametric regressions that maintains the simplicity of the NPV-CF estimator but allows the conditional expectation of the structural error to depend on both the control variables and the instruments. Our approach combines the conditional moment restrictions (CMRs) from NPIV with the controls from NPV-CF setting. We show that the CMRs place shape restrictions on the conditional expectation of the error given instruments and controls that are sufficient for identification. When sieves are used to approximate both the structural function and the control function our estimator reduces to a series of Least Squares regressions. Our monte carlos are based on the economic settings suggested above and illustrate that our new estimator performs well when the NPV-CF estimator is biased. Our empirical example replicates NPV-CF and we reject the maintained assumption of the independence of the instruments and the expected value of the structural error conditional on the controls in their setting.
主题	Econometrics ; Estimation Methods
URL	https://www.nber.org/papers/w16679
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/574354
推荐引用方式 GB/T 7714	Kyoo il Kim,Amil Petrin. A New Control Function Approach for Non-Parametric Regressions with Endogenous Variables. 2011.

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w16679.pdf（377KB）	智库出版物		限制开放	CC BY-NC-SA	浏览