Andrii Babii
Personal Details
| First Name: | Andrii |
| Middle Name: | |
| Last Name: | Babii |
| Suffix: | |
| In ASCII letters: | |
| RePEc Short-ID: | pba1689 |
| [This author has chosen not to make the email address public] | |
| http://ababii.github.io/ | |
| Twitter: | @babii_andrii |
| Terminal Degree: | 2017 Toulouse School of Economics (TSE) (from RePEc Genealogy) |
Affiliation
Department of Economics
University of North Carolina-Chapel-Hill
Chapel Hill, North Carolina (United States)http://www.unc.edu/depts/econ/
RePEc:edi:deuncus (more details at EDIRC)
Research output
Jump to: Working papers Articles ChaptersWorking papers
- Andrii Babii & Luca Barbaglia & Eric Ghysels & Jonas Striaukas, 2025. "Nowcasting and aggregation: Why small Euro area countries matter," Papers 2509.24780, arXiv.org.
- Andrii Babii & Marine Carrasco & Idriss Tsafack, 2024.
"Functional Partial Least-Squares: Adaptive Estimation and Inference,"
Papers
2402.11134, arXiv.org, revised May 2025.
- Andrii Babii & Marine Carrasco & Idriss Tsafack, 2026. "Functional Partial Least-Squares: Adaptive Estimation and Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 121(554), pages 1424-1434, April.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2023.
"Panel Data Nowcasting: The Case of Price-Earnings Ratios,"
Papers
2307.02673, arXiv.org.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2024. "Panel data nowcasting: The case of price–earnings ratios," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 292-307, March.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023.
"Econometrics of Machine Learning Methods in Economic Forecasting,"
Papers
2308.10993, arXiv.org.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "Econometrics of machine learning methods in economic forecasting," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 10, pages 246-273, Edward Elgar Publishing.
- Andrii Babii & Eric Ghysels & Junsu Pan, 2022. "Tensor PCA for Factor Models," Papers 2212.12981, arXiv.org, revised Mar 2025.
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021.
"Machine Learning Time Series Regressions With an Application to Nowcasting,"
LIDAM Discussion Papers LFIN
2021004, Université catholique de Louvain, Louvain Finance (LFIN).
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Reprints LFIN 2021010, Université catholique de Louvain, Louvain Finance (LFIN).
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Time Series Regressions with an Application to Nowcasting," Papers 2005.14057, arXiv.org, revised Dec 2020.
- Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice under Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Algorithmic Fairness," Papers 2010.08463, arXiv.org, revised Nov 2025.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020.
"Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application,"
Papers
2008.03600, arXiv.org, revised Nov 2021.
- Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
- Babii, Andrii & Chen, Xi & Ghysels, Eric & Kumar, Rohit, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," CEPR Discussion Papers 15418, Centre for Economic Policy Research.
- Andrii Babii, 2020.
"High-dimensional mixed-frequency IV regression,"
Papers
2003.13478, arXiv.org.
- Andrii Babii, 2022. "High-Dimensional Mixed-Frequency IV Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019.
"High-Dimensional Granger Causality Tests with an Application to VIX and News,"
Papers
1912.06307, arXiv.org, revised Feb 2021.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
- Andrii Babii & Rohit Kumar, 2019.
"Isotonic Regression Discontinuity Designs,"
Papers
1908.05752, arXiv.org, revised Dec 2020.
- Babii, Andrii & Kumar, Rohit, 2023. "Isotonic regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 234(2), pages 371-393.
- Andrii Babii & Jean-Pierre Florens, 2017.
"Are Unobservables Separable?,"
Papers
1705.01654, arXiv.org, revised Apr 2021.
- Babii, Andrii & Florens, Jean-Pierre, 2025. "Are Unobservables Separable?," Econometric Theory, Cambridge University Press, vol. 41(3), pages 551-583, June.
- Andrii Babii & Jean-Pierre Florens, 2020. "Are unobservables separable?," Working Papers hal-02532383, HAL.
- Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
- Andrii Babii & Jean-Pierre Florens, 2017.
"Is completeness necessary? Estimation in nonidentified linear models,"
Papers
1709.03473, arXiv.org, revised Jan 2025.
- Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
- Andrii Babii, 2016.
"Honest Confidence Sets in Nonparametric IV Regression and Other Ill-Posed Models,"
Papers
1611.03015, arXiv.org, revised Dec 2020.
- Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
- Babii, Andrii, 2017. "Honest confidence sets in nonparametric IV regression and other ill-posed models," TSE Working Papers 17-803, Toulouse School of Economics (TSE).
Articles
- Babii, Andrii & Florens, Jean-Pierre, 2025.
"Are Unobservables Separable?,"
Econometric Theory, Cambridge University Press, vol. 41(3), pages 551-583, June.
- Andrii Babii & Jean-Pierre Florens, 2020. "Are unobservables separable?," Working Papers hal-02532383, HAL.
- Babii, Andrii & Florens, Jean-Pierre, 2017. "Are unobservables separable?," TSE Working Papers 17-802, Toulouse School of Economics (TSE).
- Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Apr 2021.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2024.
"Panel data nowcasting: The case of price–earnings ratios,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 292-307, March.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2023. "Panel Data Nowcasting: The Case of Price-Earnings Ratios," Papers 2307.02673, arXiv.org.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024.
"High-Dimensional Granger Causality Tests with an Application to VIX and News,"
Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Papers 1912.06307, arXiv.org, revised Feb 2021.
- Babii, Andrii & Kumar, Rohit, 2023.
"Isotonic regression discontinuity designs,"
Journal of Econometrics, Elsevier, vol. 234(2), pages 371-393.
- Andrii Babii & Rohit Kumar, 2019. "Isotonic Regression Discontinuity Designs," Papers 1908.05752, arXiv.org, revised Dec 2020.
- Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023.
"Machine learning panel data regressions with heavy-tailed dependent data: Theory and application,"
Journal of Econometrics, Elsevier, vol. 237(2).
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application," Papers 2008.03600, arXiv.org, revised Nov 2021.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022.
"Machine Learning Time Series Regressions With an Application to Nowcasting,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Reprints LFIN 2021010, Université catholique de Louvain, Louvain Finance (LFIN).
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Time Series Regressions with an Application to Nowcasting," Papers 2005.14057, arXiv.org, revised Dec 2020.
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Discussion Papers LFIN 2021004, Université catholique de Louvain, Louvain Finance (LFIN).
- Andrii Babii, 2022.
"High-Dimensional Mixed-Frequency IV Regression,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
- Andrii Babii, 2020. "High-dimensional mixed-frequency IV regression," Papers 2003.13478, arXiv.org.
- Babii, Andrii, 2020.
"Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models,"
Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
- Andrii Babii, 2016. "Honest Confidence Sets in Nonparametric IV Regression and Other Ill-Posed Models," Papers 1611.03015, arXiv.org, revised Dec 2020.
- Babii, Andrii, 2017. "Honest confidence sets in nonparametric IV regression and other ill-posed models," TSE Working Papers 17-803, Toulouse School of Economics (TSE).
- Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
Chapters
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024.
"Econometrics of machine learning methods in economic forecasting,"
Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 10, pages 246-273,
Edward Elgar Publishing.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
More information
Research fields, statistics, top rankings, if available.Statistics
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Co-authorship network on CollEc
NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 16 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-ECM: Econometrics (13) 2017-05-21 2017-05-21 2019-09-02 2020-01-13 2020-04-13 2020-05-04 2020-06-15 2020-08-31 2020-11-02 2023-01-16 2023-08-21 2023-10-02 2024-04-01. Author is listed
- NEP-BIG: Big Data (8) 2020-01-13 2020-06-15 2020-08-31 2020-11-02 2021-05-24 2022-02-28 2023-08-21 2023-10-02. Author is listed
- NEP-CMP: Computational Economics (6) 2020-06-15 2020-08-31 2021-05-24 2022-02-28 2023-08-21 2023-10-02. Author is listed
- NEP-ETS: Econometric Time Series (5) 2020-01-13 2020-04-13 2020-06-15 2023-01-16 2023-10-02. Author is listed
- NEP-ORE: Operations Research (3) 2017-05-21 2017-05-21 2020-05-04
- NEP-DCM: Discrete Choice Models (2) 2020-11-02 2021-05-24
- NEP-MAC: Macroeconomics (2) 2020-06-15 2022-02-28
- NEP-EEC: European Economics (1) 2025-10-20
- NEP-FDG: Financial Development and Growth (1) 2022-02-28
- NEP-FOR: Forecasting (1) 2025-10-20
- NEP-MST: Market Microstructure (1) 2020-04-13
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