Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference.
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Springer, 2009. — 262 p. — ISBN 978-0-387-88697-8 This book gives you a step-by-step introduction to analysing time series using the open source software R. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence confirms understanding of both the model and the R...
Second Edition. — Springer, 2008. — (501 + 305) p. — ISBN 0387759586. The book was developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. Basic applied statistics through multiple linear regression is assumed. Calculus is assumed only to the extent of minimizing sums of squares, but a...
Springer, 2008. — 232 p. — ISBN: 978-0-387-77316-2, e-ISBN: 978-0-387-77318-6.
This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of...
Institute of Transportation Engineers, 2010. — 145 p. The R statistical package can best be thought of, in terms of user interface, as falling some-where in-between SAS and Limdep. Like SAS, R accomplishes different tasks using different procedures. Instead of the procedures being self-contained (like PROC REG in SAS), commands are issued one at a time, like Limdep. However,...
2nd ed. — Springer, 2008. — 189 p. ISBN: 0387759662. Analysis of Integrated and Cointegrated Time Series with R (2nd Edition) by Bernhard Pfaff offers a rigorous introduction to unit roots and cointegration, along with numerous examples in R to illustrate the various methods. The book, now in its second edition, provides an overview of this active area of research in time...
Wiley, 2013. — 520 p. — ISBN: 1118617908, 9781118617908 An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of...
