Michael Kevane and William Sundstrom
Department Of Economics, Santa Clara University, 500 El Camino Real, Santa
Clara, 95053, CA, USA
This book, entitled A Short Introduction to Econometrics with R, is an introductory textbook for courses in basic quantitative data analysis. The analysis is appropriate for students in Economics, Development Studies, Political Science, and Sociology. The emphasis is on regression analysis, where the analyst seeks to estimate the parameters that describe a causal relationship.
An example is used consistently throughout the book: the relationship between educational attainment and adult wages later in life. The book introduces the student to R and RStudio, statistical computing software that is commonly used in academic, government, civil society, and corporate settings. R is an open source programming language and software environment for statistical computing and graphics. The R computing environment provides the data management, data wrangling, analysis, and visualization tools needed for virtually all analysis.
Online bookdown.org draft of the book (Version Sept 2025): https://bookdown.org/mkevane/Intro_Metrics_MKWS/
PDF of each chapter (Version Sept 2025):
- Getting ready for econometrics
- Basic inferential statistics
- Single variable regression analysis
- Assumptions and confidence in estimated coefficient
- Binary variables and randomized controlled trials (RCT)
- Log specifications
- Multiple regression analysis
- Understanding omitted variable bias
- Polynomial functions and interaction terms
- Recapitulation of and practical tips for regression analysis
- Assuring that estimation of causal effects are credible
- Appendix A: Installing R and RStudio and writing a script
- Appendix B: Using R Markdown to create reports
- Appendix C: The Kenya DHS data
Michael Kevane 