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Consistent hypothesis testing in semiparametric and nonparametric models for econometric time series

Chen, Xiaohong; Fan, Yanqin - In: Journal of econometrics 91 (1999) 2, pp. 373-401

Persistent link: https://www.econbiz.de/10001382096

A consistent test for the parametric specification of the hazard function

Fan, Yanqin; Rilstone, Paul - In: Annals of economics and finance 2 (2001) 1, pp. 77-96

Persistent link: https://www.econbiz.de/10001732256

A consistent model specification test based on the kernel sum of squares of residuals

Fan, Yanqin; Li, Qi - In: Econometric reviews 21 (2002) 3, pp. 337-352

Persistent link: https://www.econbiz.de/10001718759

Partial identification of distributional and quantile treatment effects in difference-in-differences models

Fan, Yanqin; Yu, Zhengfei - In: Economics letters 115 (2012) 3, pp. 511-515

Persistent link: https://www.econbiz.de/10009632890

Wald, QLR, and score tests when parameters are subject to linear inequality constraints

Fan, Yanqin; Shi, Xuetao - In: Journal of econometrics 235 (2023) 2, pp. 2005-2026

Persistent link: https://www.econbiz.de/10014471442

Large sample sieve estimation of semi-nonparametric models

Chen, Xiaohong - 2007

Persistent link: https://www.econbiz.de/10003601887

Sieve semiparametric two-step GMM under weak dependence

Chen, Xiaohong; Liao, Zhipeng - In: Journal of econometrics 189 (2015) 1, pp. 163-186

Persistent link: https://www.econbiz.de/10011502514

Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions

Chen, Xiaohong; Christensen, Timothy M. - In: Journal of econometrics 188 (2015) 2, pp. 447-465

Persistent link: https://www.econbiz.de/10011503628

Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions

Chen, Xiaohong; Christensen, Timothy M. - 2014 - Rev.

We show that spline and wavelet series regression estimators for weakly dependent regressors attain the optimal uniform (i.e. sup-norm) convergence rate (n= log n)..p=(2p+d) of Stone (1982), where d is the number of regressors and p is the smoothness of the regression function. The optimal rate...

Persistent link: https://www.econbiz.de/10010458629

Sieve semiparametric two-step GMM under weak dependence

Chen, Xiaohong; Liao, Zhipeng - 2015

Persistent link: https://www.econbiz.de/10011312300