Description
R is a powerful programming language that is especially well-suited for statistical analyses and the creation of graphics. In many areas of applied statistics, R is the most widely used software package. In other areas, such as econometrics, it is quickly catching up to commercial software packages. R is constantly adjusted and extended by a large user community so that many state-of-the-art econometric methods are available very quickly. R is powerful and versatile for the advanced user and is also quite easy for a beginner to learn and use.
The software package R is completely free and available for most operating systems. When using it in econometrics courses, students can easily download a copy to their own computers and use it at home (or their favorite cafรฉs) to replicate examples and work on take-home assignments. This hands-on experience is essential for the understanding of the econometric models and methods. It also prepares students to conduct their own empirical analyses for their theses, research projects, and professional work.
Several excellent books introduce R and its application to statistics; for example, Dalgaard (2008); Field, Miles, and Field (2012); Hothorn and Everitt (2014); and Verzani (2014). The books of Kleiber and Zeileis (2008) and Fox and Weisberg (2011) not only introduce applied econometrics with R but also provide their own extensions to R, which we will make use of here. A problem I encountered when teaching introductory econometrics classes is that the textbooks that also introduce R do not discuss econometrics in the breadth and depth required to be used as the main text. Conversely, my favorite introductory econometrics textbooks do not cover R. Although it is possible to combine a good econometrics textbook with an unrelated introduction to R, this creates substantial hurdles because the topics and order of presentation are different, and the terminology and notation are inconsistent.
This book does not attempt to provide a self-contained discussion of econometric models and methods. It also does not give an independent general introduction to R. Instead, it builds on the excellent and popular textbook "Introductory Econometrics" by Wooldridge (2016). It is compatible in terms of topics, organization, terminology, and notation, and is designed for a seamless transition from theory to practice.
ISBN:9781523285136
