curriculum vitae in PDF
My main research area is theory and methodology in econometrics, statistics and machine learning. Currently, a major focus is high-dimensional models.
Applications of my research include big data analysis, causal inference, economics and finance.
- Small Sample Properties of Likelihood Ratio Tests in Linear State Space Models: An Application to DSGE Model Validation with Ivana Komunjer. Accepted at Journal of Econometrics. (Annals issue on Identification, Inference, and Causality in honor of Jean-Marie Dufour)
- Variable Selection in Panel Models with Breaks with Simon Smith and Allan Timmermann. Accepted by Journal of Econometrics. (Annals issue on Big Data in Predictive Dynamic Econometric Modeling)
- Significance testing in non-sparse high-dimensional linear models with Jelena Bradic. Accepted by Electronic Journal of Statistics.
- Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data with Victor Chernozhukov and Kaspar Wüthrich. Accepted by COLT 2018 (Conference on Learning Theory)
- Linear hypothesis testing in dense high-dimensional linear models with Jelena Bradic. Forthcoming at Journal of the American Statistical Association.
- Comments on 'High-dimensional simultaneous inference with the bootstrap by Dezeure, Buhlmann and Zhang' with Jelena Bradic. Forthcoming at TEST.
Papers under revision
- Monitoring forecasting performance with Allan Timmermann. Revise and resubmit at Journal of Econometrics.
- A simple method for uniform subvector inference of linear instrumental variables models. Revise and resubmit at Journal of Econometrics.
- Testability of high-dimensional linear models with non-sparse structures with Jelena Bradic and Jianqing Fan. Major revision at Annals of Statistics.
- Comparing Forecasting Performance with Panel Data with Allan Timmermann
- Sparsity Double Robust Inference of Average Treatment Effects with Jelena Bradic and Stefan Wager.
- Inference on average treatment effects in aggregate panel data settings with Victor Chernozhukov and Kaspar Wüthrich.
- Inference For Heterogeneous Effects Using Low-Rank Estimations with Victor Chernozhukov, Christian Hansen and Yuan Liao.
- k-step correction mixed integer linear programming: a new approach for instrumental variable quantile regressions and related problems (Matlab code for the old version. Code for the new version coming soon)
- An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls with Victor Chernozhukov and Kaspar Wüthrich.
- High-dimensional panel data with time heterogeneity: estimation and inference
- Testing for common factors in large factor models
- Breaking the curse of dimensionality in regression with Jelena Bradic.
- Two-sample testing in non-sparse high-dimensional linear models with Jelena Bradic.
- A projection pursuit framework for testing general high-dimensional hypothesis with Jelena Bradic.
- Quantile spacings: a simple method for the joint estimation of multiple quantiles without crossing with Lawrence Schmidt.
- Tests of forecasting performance and choice of estimation window with Allan Timmermann.
- “Inference on manifolds”, with Ivana Komunjer.
- “Limit theory of filtered historical simulation in GARCH models”, with Brendan Beare and Lajos Horvath.