Andrii Babii

Andrii Babii Andrii Babii


Economics Department
Associate Professor

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Working Papers

  1. Regularized estimation of semiparametric mixtures, with Marine Carrasco and Xiaohong Chen, 2024 (in progress).

  2. Functional partial least-squares: adaptive estimation and inference, with Marine Carrasco, and Idriss Tsafack, 2025, reject and resubmit at Journal of the American Statistical Association.

  3. Tensor PCA for factor models, with Eric Ghysels, and Junsu Pan, 2025, revise and resubmit at Journal of Econometrics. [Python package]

  4. Binary choice with asymmetric loss in a data-rich environment: theory and an application to racial justice, with Xi Chen, Eric Ghysels, and Rohit Kumar, 2024, revise and resubmit at Quantitative Economics. [slides], [IAAE Webinar]

  5. Nowcasting and aggregation: why small Euro area countries matter, with Luca Barbaglia, Eric Ghysels, and Jonas Striaukas, 2024, reject and resubmit at Journal of Business & Economic Statistics.

Publications

  1. Are unobservables separable?, with Jean-Pierre Florens, Econometric Theory, 2025 (forthcoming). [slides]

  2. Is completeness necessary? Estimation in nonidentified linear models, with Jean-Pierre Florens, Econometric Theory, 2025 (forthcoming).

  3. Econometrics of machine learning methods in economic forecasting, with Eric Ghysels, and Jonas Striaukas, Handbook of Research Methods and Applications on Macroeconomic Forecasting, 2024.

  4. Panel data nowcasting in a data-rich environment: the case of price-earnings ratios, with Ryan T. Ball, Eric Ghysels and Jonas Striaukas, Journal of Applied Econometrics 2024, 39(2).

  5. High-dimensional Granger causality tests with an application to VIX and news, with Eric Ghysels and Jonas Striaukas, Journal of Financial Econometrics (2024), 22(3). [slides]

  6. Isotonic regression discontinuity designs, with Rohit Kumar, Journal of Econometrics (2023), 234(2). [slides]

  7. Machine learning panel data regressions with heavy-tailed dependent data: theory and application, with Ryan T. Ball, Eric Ghysels and Jonas Striaukas, Journal of Econometrics (2023), 237(2). [R package]

  8. High-dimensional mixed-frequency IV regression, Journal of Business & Economic Statistics (2022), 40(4).

  9. Machine learning time series regressions with an application to nowcasting, with Eric Ghysels and Jonas Striaukas, Journal of Business & Economic Statistics, (2022), 40(3). [slides], [R package], [Julia package]

  10. Honest confidence sets in nonparametric IV regression and other ill-posed models, Econometric Theory (2020), 36(4). [slides]

  11. ET interview: Jean-Pierre Florens, with Eric Ghysels, Econometric Theory (2020), 36(3).

  12. Commercial and residential mortgage defaults: spatial dependence with frailty, with Xi Chen and Eric Ghysels, Journal of Econometrics (2019), 212(1).

Academic Genealogy: Jean-Pierre Florens (1980) - Jean-Pierre Raoult (1969) - Daniel Dugué (1937) - Georges Darmois (1921) - Édouard Goursat (1881) - Gaston Darboux (1866) - Michel Chasles (1814) - Siméon Denis Poisson (1800) - Pierre-Simon Laplace (1769) and Joseph Louis Lagrange (1754) - Leonhard Euler (1726) - Johann Bernoulli (1694) - Jacob Bernoulli (1676)