Staff profile

Hugo Kruiniger has studied econometrics at the Econometric Institute of Erasmus University Rotterdam (EUR) and graduated from EUR with a Doctorandus degree (this is equivalent to an MSc degree) in Econometrics and Operations Research. He has obtained his Doctor's degree (PhD degree) in Economics from Maastricht University. He has been a Postdoctoral Research Fellow at University College London (UCL), a Visiting Professor at CREST-INSEE (in Malakoff/Paris) and a Fulbright Scholar at Harvard University. He has published his research in journals such as Journal of Econometrics, the Econometrics Journal, Econometric Theory, Econometric Reviews and Journal of Economic Dynamics and Control (JEDC). 

Journal Article

• Kruiniger, H. (2022). Estimation of dynamic panel data models with a lot of heterogeneity. Econometric Reviews, 41(2), 117-146. https://doi.org/10.1080/07474938.2021.1899507
• Kruiniger, H. (2021). Identification without assuming mean-stationarity: Quasi ML estimation of dynamic panel models with endogenous regressors. The Econometrics Journal, 24(3), 417-441. https://doi.org/10.1093/ectj/utaa036
• Kruiniger, H. (2013). Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions. Journal of Econometrics, 173(2), https://doi.org/10.1016/j.jeconom.2012.11.004
• Kruiniger, H. (2009). GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data. Econometric Theory, 25(5), 1348-1391. https://doi.org/10.1017/s0266466608090531
• Kruiniger, H. (2008). Maximum Likelihood Estimation and Inference Methods for the Covariance Stationary Panel AR(1)/Unit Root Model. Journal of Econometrics, 144(2), 447-464. https://doi.org/10.1016/j.jeconom.2008.03.001
• Kruiniger, H. (2007). An efficient linear GMM estimator for the covariance stationary AR (1)/unit root model for panel data. Econometric Theory, 23(3), 519-535. https://doi.org/10.1017/s0266466607070235
• Kruiniger, H. (2000). On the solution of the linear rational expectations model with multiple lags. Journal of Economic Dynamics and Control, 24(4), 535-559. https://doi.org/10.1016/S0165-1889%2899%2900006-8

Working Paper

• Kruiniger, H. (2022). Large sample properties of GMM estimators under second-order identification
• Kruiniger, H. (2020). Further results on the estimation of dynamic panel logit models with fixed effects
• Kruiniger, H. (2018). A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions