Naghi, AndreaA., O'Neill, E. and Danielova Zaharieva, M. (2024). The benefits of forecasting inflation with machine learning: New evidence Journal of Applied Econometrics, :.
9 Key Publications
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De Vos, I. and Stauskas, O. (2024). Cross-section bootstrap for CCE regressions Journal of Econometrics, 240(1):1--20. -
Kleen, O. (2024). Scaling and measurement error sensitivity of scoring rules for distribution forecasts Journal of Applied Econometrics, 39(5):833--849. -
Frazier, DavidT., Renault, E., Zhang, L. and Zhao, X. (2024). Weak Identification in Discrete Choice Models Journal of Econometrics, :. -
Tommasi, D. and Zhang, L. (2024). Identifying program benefits when participation is misreported Journal of Applied Econometrics, :1123--1148. -
Tommasi, D. and Zhang, L. (2024). Bounding Program Benefits When Participation Is Misreported Journal of Econometrics, 238(1):. -
Cahuc, P., Carcillo, S., Patault, B. and Moreau, F. (2024). Judge bias in labor courts and firm performance Journal of the European Economic Association, 22(3):1319–1366. -
Friedrich, M. and Lin, Y. (2024). Sieve bootstrap inference for linear time-varying coefficient models Journal of Econometrics, 239(1):1--29. -
Creal, D., Koopman, S.J., Lucas, A. and Zamojski, M. (2024). Observation-driven filtering of time-varying parameters using moment conditions Journal of Econometrics, 238(2):.