Issue 6/2023
Special Issue in Honor of Professor Peter Schmidt
Content (26 Articles)
Robust dynamic space–time panel data models using -contamination: an application to crop yields and climate change
Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
Open Access
Unbiased estimation of the OLS covariance matrix when the errors are clustered
Tom Boot, Gianmaria Niccodemi, Tom Wansbeek
Refined GMM estimators for simultaneous equations models with network interactions
Peter H. Egger, Ingmar R. Prucha
Open Access
Identification and estimation of categorical random coefficient models
Zhan Gao, M. Hashem Pesaran
Open Access
Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects
George Kapetanios, Laura Serlenga, Yongcheol Shin
Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices
Hongjun Li, Zheng Li, Cheng Hsiao
A simple, robust test for choosing the level of fixed effects in linear panel data models
Leslie E. Papke, Jeffrey M. Wooldridge
Internal adjustment costs of firm-specific factors and the neoclassical theory of the firm
V. K. Chetty, James J. Heckman
Proportional incremental cost probability functions and their frontiers
Frédérique Fève, Jean-Pierre Florens, Léopold Simar
Indirect inference estimation of stochastic production frontier models with skew-normal noise
Hung-pin Lai, Subal C. Kumbhakar
An alternative corrected ordinary least squares estimator for the stochastic frontier model
Christopher F. Parmeter, Shirong Zhao
Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility
Richard T. Baillie, Dooyeon Cho, Seunghwa Rho
Multivariate models of commodity futures markets: a dynamic copula approach
Sihong Chen, Qi Li, Qiaoyu Wang, Yu Yvette Zhang
Open Access
Generalized kernel regularized least squares estimator with parametric error covariance
Justin Dang, Aman Ullah
Public subsidies and innovation: a doubly robust machine learning approach leveraging deep neural networks
Kerda Varaku, Robin Sickles
Open Access
DS-HECK: double-lasso estimation of Heckman selection model
Masayuki Hirukawa, Di Liu, Irina Murtazashvili, Artem Prokhorov
Open Access
Simultaneity in binary outcome models with an application to employment for couples
Bo E. Honoré, Luojia Hu, Ekaterini Kyriazidou, Martin Weidner