Search results
Results: 22
Number of items: 22
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Boot, T., & Juodis, A. (2025). Uniform inference in linear error-in-variables models: Divide-and-conquer. Econometric Reviews, 44(3), 335-355. https://doi.org/10.1080/07474938.2024.2417166 -
de Brabander, E., Juodis, A., & Miyazato Szini, G. (2025). On the use of synthetic difference-in-differences approach with (-out) covariates: The case study of Brexit referendum. Econometric Reviews, 44(10), 1617-1646. https://doi.org/10.1080/07474938.2025.2530649
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Juodis, A., & Kučinskas, S. (2023). Quantifying noise in survey expectations. Quantitative Economics, 14(2), 609-650. https://doi.org/10.3982/QE1633
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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
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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
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Juodis, A., & Sarafidis, V. (2022). An incidental parameters free inference approach for panels with common shocks. Journal of Econometrics, 229(1), 19-54. https://doi.org/10.1016/j.jeconom.2021.03.011
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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
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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. https://doi.org/10.1080/07350015.2021.1906687
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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
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