Advances in Applied Econometrics

Edited by Subal C. Kumbhakar (), Robin C. Sickles () and Hung-Jen Wang ()

in Advanced Studies in Theoretical and Applied Econometrics from Springer, currently edited by Badi Baltagi, Yongmiao Hong, Gary Koop and Walter Krämer

Date: 2024
ISBN: 978-3-031-48385-1
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Chapters in this book:

Introduction

Subal C. Kumbhakar, Robin C. Sickles and Hung-Jen Wang

Robust dynamic space–time panel data models using ε $$ \varepsilon $$ -contamination: an application to crop yields and climate change

Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi and Guy Lacroix

Unbiased estimation of the OLS covariance matrix when the errors are clustered

Tom Boot, Gianmaria Niccodemi and Tom Wansbeek

Refined GMM estimators for simultaneous equations models with network interactions

Peter Egger and Ingmar R. Prucha

Identification and estimation of categorical random coefficient models

Zhan Gao and M. Hashem Pesaran

Dynamic panel GMM estimators with improved finite sample properties using parametric restrictions for dimension reduction

Chirok Han and Hyoungjong Kim

Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects

George Kapetanios, Laura Serlenga and Yongcheol Shin

Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices

Hongjun Li, Zheng Li and Cheng Hsiao

A simple, robust test for choosing the level of fixed effects in linear panel data models

Leslie E. Papke and Jeffrey M. Wooldridge

Internal adjustment costs of firm-specific factors and the neoclassical theory of the firm

V. K. Chetty and James J. Heckman

Proportional incremental cost probability functions and their frontiers

Frédérique Fève, Jean-Pierre Florens and Leopold Simar

Hotelling tubes, confidence bands and conformal inference

Roger Koenker

Indirect inference estimation of stochastic production frontier models with skew-normal noise

Hung-pin Lai and Subal C. Kumbhakar

The noise error component in stochastic frontier analysis

Alecos Papadopoulos

An alternative corrected ordinary least squares estimator for the stochastic frontier model

Christopher F. Parmeter and Shirong Zhao

Likelihood-based inference for dynamic panel data models

Seung C. Ahn and Gareth M. Thomas

Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility

Richard T. Baillie, Dooyeon Cho and Seunghwa Rho

Does climate change affect economic data?

In Choi

Information loss in volatility measurement with flat price trading

Peter Phillips and Jun Yu

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

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DOI: 10.1007/978-3-031-48385-1

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