Advanced Studies in Theoretical and Applied Econometrics

From Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Access Statistics for this chapter series.
Is something missing from the series or not right? See the RePEc data check for the archive and series.

On the Estimation of Forecaster Loss Functions Using Density Forecasts: Kajal Lahiri, Fushang Liu and Wuwei Wang
Fairness in Machine Learning and Econometrics: Samuele Centorrino, Jean-Pierre Florens and Jean-Michel Loubes
Local Average Treatment Effect and Regression-Discontinuity-Design: Giovanni Cerulli
A simple, robust test for choosing the level of fixed effects in linear panel data models: Leslie Papke and Jeffrey Wooldridge
Reflections on a Life of Teaching Econometrics: James Davidson
Asymmetric AdaBoost for Maximum Score Estimation of High-Dimensional Binary Choice Regression Models: Jianghao Chu, Tae-Hwy Lee and Aman Ullah
Estimating Dynamic Probit Models with Higher-order Time- and Network-lag Structure and Correlated Random Effects: Peter Egger and Michaela Kesina
Internal adjustment costs of firm-specific factors and the neoclassical theory of the firm: V. K. Chetty and James Heckman
Nonparametric Models with Random Effects: Yiguo Sun, Wei Lin and Qi Li
Graphical Models and their Interactions with Machine Learning in the Context of Economics and Finance: Ekaterina Seregina
Proportional incremental cost probability functions and their frontiers: Frédérique Fève, Jean-Pierre Florens and Leopold Simar
Horizontal Regression or Vertical Regression to Generate Counterfactuals?: Cheng Hsiao, Jing Kong, Yimeng Xie and Qiankun Zhou
Using Replication to Teach and Understand Econometrics: Daniel J. Henderson and Christopher F. Parmeter
Nonparametric Models with Fixed Effects: Daniel Henderson and Alexandra Soberon
Nonparametric Correlated Random-Effects Models: Daniel Henderson, Emma Kate Henry and Alexandra Soberon
Poverty, Inequality and Development Studies with Machine Learning: Walter Sosa-Escudero, Maria Victoria Anauati and Wendy Brau
Reflections of an Applied Econometrician: Walter Enders
Hotelling tubes, confidence bands and conformal inference: Roger Koenker
Imputing Missing Waves for Pseudo Panels: A Generalized Scoring and Matching Method: Zhongjian Lin and Esfandiar Maasoumi
Difference-in-Differences with Many Pre- and Post-Treatment Times: Giovanni Cerulli
Indirect inference estimation of stochastic production frontier models with skew-normal noise: Hung-pin Lai and Subal C. Kumbhakar
The Correlated Random Effects GMM-Level Estimation: Monte Carlo Evidence and Empirical Applications: Maria Bontempi and Jan Ditzen
Quarto the Assassin: Jeffrey S. Racine
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
Teaching Statistical Learning in Econometrics: Mohamad A. Khaled, Alicia N. Rambaldi and Christiern Rose
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
Teaching Mathematics for Economists: Eric Hillebrand
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 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
Modelling Migration: Raul Ramos
Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility: Richard T. Baillie, Dooyeon Cho and Seunghwa Rho
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 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