Research Interests:  

           Spatial Econometrics

           Panel Data Models

           Bootstrap methods for Refined Inferences

           Event Time Analysis

 

Editorial Service:

Co-Editor, Regional Science and Urban Economics

 

Papers Recently Accepted:

[1]          Yang, Z. L. (2017). Unified M-estimation of fixed-effects spatial dynamic models with short panels (the supplement, Application with Matlab Codes). Journal of Econometrics, accepted on 1 Aug. 2017. (Version Dec 2015)

[2]          Shen, Y. and Yang, Z. L. (2017). Improved Likelihood Inferences for Weibull Regression Model (Supplementary Material, Early Version). Journal of Statistical Computation and Simulation, forthcoming.

[3]          Yang, Z. L., Yu, J. and Liu, S. F. (2016). Bias Correction and refined inferences for Fixed Effects Spatial Panel Data Models. (Supplementary Material, Matlab Files). Regional Science and Urban Economics, 61, 52-72. (Early Version)

[4]          Desmond, A. F. and Yang, Z. L. (2016). Asymptotically refined score and GOF tests for inverse Gaussian models. Journal of Statistical Computation and Simulation, forthcoming. http://dx.doi.org/10.1080/00949655.2016.1158819

[5]          Su, L. J. and Yang, Z. L. (2016). Asymptotics and bootstrap for random-effects panel data transformation models. Econometric Reviews, forthcoming. http://dx.doi.org/10.1080/07474938.2015.1122235 Early Versions: Ver2008.

[6]          Liu, S. F. and Yang Z. L. (2015). Improved Inferences for Spatial Regression Models. Regional Science and Urban Economics 55, 55-67.

[7]          Liu, S. F. and Yang, Z. L. (2015). Asymptotic distribution and finite-sample bias correction of QML estimators for spatial error dependence model. Econometrics 3, 376-411.

[8]          Liu, S. F. and Yang, Z. L. (2015). Modified QML estimation of spatial autoregressive models with unknown heteroskedasticity and nonnormality. Regional Science and Urban Economics 52, 50-70.

[9]          Yang, Z. L. (2014). LM tests of spatial dependence based on bootstrap critical values. Journal of Econometrics, http://dx.doi.org/10.1016/j.jeconom.2014.10.005 Accepted on 3 Oct. 2014, Sup Appendix. Early Versions: Ver2013May, Ver2011

[10]     Yang, Z. L. (2014). A general method for third-order bias and variance correction on a nonlinear rstimator. Journal of Econometrics, Accepted on 15 July 2014, http://dx.doi.org/10.1016/j.jeconom.2014.07.003, Sup Appendix. Early Versions: VerFeb2014, Ver2013Oct, Ver2013Jul, Ver2012. Initial Version with Title: Bias-corrected estimation for spatial autocorrelation.

[11]     Su, L. J. and Yang, Z. L. (2014). QML estimation of dynamic panel data models with spatial errors. Journal of Econometrics. Accepted on 10 Nov. 2014. Sup Appendix. Early Versions: Ver2012, Ver2007

[12]     Shen, Y. and Yang, Z. L. (2014). Bias-correction for Weibull common shape estimation. Journal of Statistical Computation and Simulation, Accepted on 26/07/2014, DOI: 10.1080/00949655.2014.949714. Early Versions: Ver2013a, Ver2013b

 

Papers in Review Process:

[1]        Yang, Z. L. (2016). Joint tests for dynamic and spatial effects in short panel data models with fixed effects. Under review.

Work in Progress:

[1]        Yang, Z. L. (2014). Initial-condition free estimation of fixed effects dynamic panel data models.

[2]        Desmond, A. F. and Yang, Z. L. (2016). Confidence limits for cure rates in first hitting time regression models.

[3]        Pirotte, A. and Yang Z. L. (2016). Tests for homoscedasticity in spatial linear or panel models.

Unpublished Working Papers:

[1]        Su, L. J. and Yang Z. L. (2007). Instrumental variable quantile estimation of spatial autoregressive models. Version 2011

[2]        Yang, Z. L. and Shen, Y. (2011). A simple and robust method of inference for spatial lag dependence. Version 2014 (Sup Appendix).

[3]        Yang, Z. L. (2008). Tests for Spatial Dependence under Distributional Misspecification.

[4]        Yang, Z. L. (2006). Joint Modeliing and Testing for Local and Global Spatial Externalities.

[5]        Yang, Z. L. (2005). Quasi-Maximum Likelihood Estimation for Spatial Panel Data Regressions.