book

Panel Data Econometrics with R

by Yves Croissant, Giovanni Millo

November 2018

Beginner to intermediate

328 pages

11h 12m

English

Wiley

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1.1 Panel Data Econometrics: A Gentle Introduction1.2 R for Econometric Computing1.3 plm for the Casual R User1.4 plm for the Proficient R User1.5 plm for the R Developer1.6 Notations
2.1 Notations and Hypotheses2.2 Ordinary Least Squares Estimators2.3 The Generalized Least Squares Estimator2.4 Comparison of the Estimators2.5 The Two‐ways Error Components Model2.6 Estimation of a Wage Equation
3.1 Unbalanced Panels3.2 Seemingly Unrelated Regression3.3 The Maximum Likelihood Estimator3.4 The Nested Error Components Model
4.1 Tests on Individual and/or Time Effects4.2 Tests for Correlated Effects4.3 Tests for Serial Correlation4.4 Tests for Cross‐sectional Dependence
5.1 Robust Inference5.2 Unrestricted Generalized Least Squares

6.1 Introduction6.2 The Instrumental Variables Estimator6.3 Error Components Instrumental Variables Estimator6.4 Estimation of a System of Equations6.5 More Empirical Examples
7.1 Dynamic Model and Endogeneity7.2 GMM Estimation of the Differenced Model7.3 Generalized Method of Moments Estimator in Differences and Levels7.4 Inference7.5 More Empirical Examples
8.1 Introduction8.2 Heterogeneous Coefficients8.3 Cross‐sectional Dependence and Common Factors8.4 Nonstationarity and Cointegration
9.1 Binomial and Ordinal Models9.2 Censored or Truncated Dependent Variable9.3 Count Data9.4 More Empirical Examples
10.1 Spatial Correlation10.2 Spatial Lags10.3 Individual Heterogeneity in Spatial Panels10.4 Serial and Spatial Correlation

Overview

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.