Juodis, A., & Sarafidis, V. (2023). New results on asymptotic properties of likelihood estimators with persistent data for small and large T. SERIEs, 14(3-4), 435-461. https://doi.org/10.1007/s13209-023-00286-y[details]
Xiao, J., Karavias, Y., Juodis, A., Sarafidis, V., & Ditzen, J. (2023). Improved tests for Granger noncausality in panel data. Stata Journal, 23(1), 230-242. https://doi.org/10.1177/1536867X231162034
2022
Juodis, A. (2022). A regularization approach to common correlated effects estimation. Journal of Applied Econometrics, 37(4), 788-810. https://doi.org/10.1002/jae.2899[details]
Juodis, A., & Reese, S. (2022). The Incidental Parameters Problem in Testing for Remaining Cross-Section Correlation. Journal of Business and Economic Statistics, 40(3), 1191-1203. Advance online publication. https://doi.org/10.1080/07350015.2021.1906687[details]
Juodis, A., & Sarafidis, V. (2022). A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors. Journal of Business and Economic Statistics, 22(1), 1-15. Advance online publication. https://doi.org/10.1080/07350015.2020.1766469
Juodis, A., Karavias, Y., & Sarafidis, V. (2021). A homogeneous approach to testing for Granger non-causality in heterogeneous panels. Empirical Economics, 60(1), 93–112. https://doi.org/10.1007/s00181-020-01970-9[details]
Juodis, A., & Westerlund, J. (2019). Optimal panel unit root testing with covariates. Econometrics Journal, 22(1), 57-72. https://doi.org/10.1111/ectj.12118
2018
Juodis, A. (2018). First difference transformation in panel VAR models: Robustness, estimation, and inference. Econometric Reviews, 37(6), 650-693. Advance online publication. https://doi.org/10.1080/07474938.2016.1139559[details]
Juodis, A., & Sarafidis, V. (2018). Fixed T dynamic panel data estimators with multifactor errors. Econometric Reviews, 37(8), 893-929. Advance online publication. https://doi.org/10.1080/00927872.2016.1178875[details]
Bun, M. J. G., Carree, M. A., & Juodis, A. (2017). On Maximum Likelihood Estimation of Dynamic Panel Data Models. Oxford Bulletin of Economics and Statistics, 79(4), 463-494. https://doi.org/10.1111/obes.12156[details]
De UvA gebruikt cookies voor het meten, optimaliseren en goed laten functioneren van de website. Ook worden er cookies geplaatst om inhoud van derden te kunnen tonen en voor marketingdoeleinden. Klik op ‘Accepteer alle cookies’ om akkoord te gaan met het plaatsen van alle cookies. Of kies voor ‘Weigeren’ om alleen functionele en analytische cookies te accepteren. Lees ook het UvA Privacy statement.