Econometrics of machine learning methods in economic forecasting, with Eric Ghysels, and Jonas Striaukas, 2023, R&R.
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, 2022, R&R. [slides], [IAAE Webinar]
Is completeness necessary? Estimation in nonidentified linear models, with Jean-Pierre Florens, 2021, R&R.
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 2023 (forthcoming).
High-dimensional Granger causality tests with an application to VIX and news, with Eric Ghysels and Jonas Striaukas, Journal of Financial Econometrics (2022), forthcoming. [slides]
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]
High-dimensional mixed-frequency IV regression, Journal of Business & Economic Statistics (2022), 40(4).
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]
Honest confidence sets in nonparametric IV regression and other ill-posed models, Econometric Theory (2020), 36(4). [slides]
ET interview: Jean-Pierre Florens, with Eric Ghysels, Econometric Theory (2020), 36(3).
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)