Advanced Studies in Theoretical and Applied Econometrics

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Hotelling tubes, confidence bands and conformal inference: Roger Koenker
Difference-in-Differences with Many Pre- and Post-Treatment Times: Giovanni Cerulli
The Correlated Random Effects GMM-Level Estimation: Monte Carlo Evidence and Empirical Applications: Maria Elena Bontempi and Jan Ditzen
Indirect inference estimation of stochastic production frontier models with skew-normal noise: Hung-pin Lai and Subal C. Kumbhakar
Synthetic Control Method: Giovanni Cerulli
Multi-dimensional Panels in Quantile Regression Models: Antonio Galvao and Gabriel Montes-Rojas
The noise error component in stochastic frontier analysis: Alecos Papadopoulos
Machine Learning for Asset Pricing: Jantje Sönksen
Estimation of Serially Correlated Error Components Models Using Whittle’s Approximate Maximum Likelihood Method: Badi Baltagi, Georges Bresson and Jean-Michel Etienne
Multi-Dimensional Models for Spatial Panels: Julie Le Gallo and Alain Pirotte
Dynamic Heterogeneous Linear Models for Three-level Panel Data with Short Time Dimension and Stratification: Monika Avila Márquez and Jaya Krishnakumar
An alternative corrected ordinary least squares estimator for the stochastic frontier model: Christopher F. Parmeter and Shirong Zhao
The Econometrics of Gravity Models in International Trade: Badi Baltagi, Peter Egger and Katharina Erhardt
The Basics of the Mundlak and Chamberlain Projections: Badi Baltagi and Tom Wansbeek
Likelihood-based inference for dynamic panel data models: Seung C. Ahn and Gareth M. Thomas
Modelling Housing Using Multi-dimensional Panel Data: Badi Baltagi and Georges Bresson
An Algebraic Equivalence between Generalized Fixed Effects and a Generalized Mundlak Regression with Applications to Heterogeneous Trends and Difference-in-Differences: Jeffrey M. Wooldridge
Dimensionality and Exact Bound Tests in Simultaneous Equations: Jean-Marie Dufour and Lynda Khalaf
Dynamic Log-Linear Probability Model with Interactions: Christian Gouriéroux and Nour Meddahi
Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility: Richard T. Baillie, Dooyeon Cho and Seunghwa Rho
Modelling Migration: Raul Ramos
Multi-dimensional Panels in Health Economics with an Application on Antibiotic Consumption: Anikó Bíró, Péter Elek and Nóra Kungl
Does climate change affect economic data?: In Choi
Information loss in volatility measurement with flat price trading: Peter Phillips and Jun Yu
Can Machine Learning Beat Gravity in Flow Prediction?: György Ruzicska, Ramzi Chariag, Olivér Kiss and Miklós Koren
Forecasting in the presence of in-sample and out-of-sample breaks: Jiawen Xu and Pierre Perron
Multivariate models of commodity futures markets: a dynamic copula approach: Sihong Chen, Qi Li, Qiaoyu Wang and Yu Yvette Zhang
Generalized kernel regularized least squares estimator with parametric error covariance: Justin Dang and Aman Ullah
Predicting binary outcomes based on the pair-copula construction: Kajal Lahiri and Liu Yang
Public subsidies and innovation: a doubly robust machine learning approach leveraging deep neural networks: Kerda Varaku and Robin C. Sickles
DS-HECK: double-lasso estimation of Heckman selection model: Masayuki Hirukawa, Di Liu, Irina Murtazashvili and Artem Prokhorov
Simultaneity in binary outcome models with an application to employment for couples: Bo E. Honoré, Luojia Hu, Ekaterini Kyriazidou and Martin Weidner