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Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric...
Persistent link: https://www.econbiz.de/10013124543
Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric...
Persistent link: https://www.econbiz.de/10012461562
Persistent link: https://www.econbiz.de/10009612838
Persistent link: https://www.econbiz.de/10008667541
Persistent link: https://www.econbiz.de/10003035733
In this paper, we employ a partially linear nonparametric additive regression estimator, with recent U.S. Current Population Survey data, to analyze returns to schooling. Similar to previous research, we find that blacks and Hispanics have higher rates of return on average. However, for married...
Persistent link: https://www.econbiz.de/10013039569
In this article we overview nonparametric (spline and kernel) regression methods and illustrate how they may be used in labor economic applications. We focus our attention on issues commonly found in the labor literature such as how to account for endogeneity via instrumental variables in a...
Persistent link: https://www.econbiz.de/10012907832
In this paper we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient and free from the curse of dimensionality. Monte...
Persistent link: https://www.econbiz.de/10013054589
Persistent link: https://www.econbiz.de/10009709125
In this paper we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient and free from the curse of dimensionality. Monte...
Persistent link: https://www.econbiz.de/10010350365