Selected working papers:  

• Beyhum, J., & Mugnier, M. (2024). Inference after discretizing time-varying unobserved heterogeneity. arXiv preprint arXiv:2412.07352.

• Willems, I., Beyhum, J., & Van Keilegom, I. (2025). Bounds for the regression parameters in dependently censored survival models. arXiv preprint arXiv:2503.11210. 

• Crommen, G., Beyhum, J., & Van Keilegom, I. (2025). Estimation of the complier causal hazard ratio under dependent censoring. arXiv preprint arXiv:2504.02096. (R & R at the Journal of Business & Economic Statistics)

• Miao, W., Beyhum, J., Striaukas, J., & Van Keilegom, I. (2025). High-dimensional censored MIDAS logistic regression for corporate survival forecasting arXiv preprint arXiv:2502.09740. (R & R at the Journal of Econometrics)

• Beyhum, J., & Striaukas, J. (2024). Factor-augmented sparse MIDAS regressions with an application to nowcasting. arXiv preprint arXiv:2306.13362. (R & R at the Journal of Business & Economic Statistics)

• Bruneel-Zupanc, C. & Beyhum, J. (2024). Identification with possibly invalid IVs. arXiv preprint arXiv:2401.03990.

• Beyhum J. (2024). The potential outcomes factor model. Available at SSRN 4684405. (Undergoing major revision)

• Beyhum, J., & Gautier, E. (2019). Square-root nuclear norm penalized estimator for panel data models with approximately low-rank unobserved heterogeneity. arXiv preprint arXiv:1904.09192. (Permanent Working Paper)