Publications/Working Papers

"The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies" (with Anna Baiardi) accepted at The Econometrics Journal 

"The Benefits of Forecasting Inflation with Machine Learning: New Evidence" (with Eoghan O'Neill and Martina Zaharieva) accepted at  Journal of Applied Econometrics

"The Effect of Plough Agriculture on Gender Roles: A Machine Learning Approach"  (with Anna Baiardi) accepted at Journal of Applied Econometrics

"Robust Estimation of Probit Models with Endogeneity" (with Máté Váradi and Mikhail Zhelonkin),  Econometrics and Statistics (2022)

"Statistical tests for linear and nonlinear dependence and long-memory" (with Dorina Lazar and Andrada Filip), Carpathian Journal of Mathematics Vol. 25, No. 1 (2009), pp. 92-103 (pre-PhD publication)

"Heterogeneity in Lung Cancer Screening: a Causal Machine Learning Approach" (with Andreas Alfons, Kevin ten Haaf and Max Welz), submitted

"Finite Sample Performance of Causal Machine Learning Methods for Average and Heterogeneous Treatment Effects" (with Christian Wirths), submitted       

Work in Progress

"Robust Estimation of Probit Models with Endogeneity in R: a Vignette" (with André Bik and Mikhail Zhelonkin)

"Outlier Robust Inference in the Instrumental Variable Model in Stata (with Jens Klooster, Matthias Hofstede and Mikhail Zhelonkin)

"Robust Estimation and Inference for Treatment Effects in Sample Selection Models" (with Máté Váradi and Mikhail Zhelonkin)

"Estimation and Inference under Weak Identification in MIDAS Models"  (with Onno Kleen and Michel van der Wel)

"Identification Robust Predictive Ability Testing"

"Assessing Global Identification in DSGE Models"

"Testing Forecast Rationality under Asymmetric and Unknown Loss"