Learning Microeconometrics with R

Chris Adams was born and raised in Melbourne Australia and is a lifelong Carlton supporter. Chris received his PhD in economics from the University of Wisconsin - Madison. He has taught at the University of Vermont and in the Johns Hopkins’ Masters of Applied Economics program. He has 17 years experience working in merger regulation and antitrust for the US Federal Trade Commission. He is currently a Principal Analyst at the US Congressional Budget Office. Chris’ work and research focus on econometrics, empirical industrial organization, pharmaceutical innovation and auctions. His work has been published in various academic journals including The Econometrics Journal, Health Affairs, Health Economics, Marketing Science and Economics Letters. Chris is a colon cancer survivor and a research patient advocate with ECOG-ACRIN. Most importantly, he is a father to CJ and husband to Deena.

• I. Experiments.1. Ordinary Least Squares.2. Multiple Regression.3. Instrumental Variables4. Bounds Estimation.II. Structural Estimation.5. Estimating Demand.6. Estimating Selection Models.7. Demand Estimation with IV8. Estimating Games.9. Estimating Auction ModelsIII. Repeated Measurement.10. Panel data.11. Synthetic Controls.12. Mixture Models.IV. Appendices.A. Measuring Uncertainty.B. Statistical Programming in RAcknowledgements Bibliography

'The book offers a great set of statistical and econometric methods useful not only in microeconometrics but in many other fields where the statistical modeling is needed. At the same time, it is a great source of the R programming, particularly, in data simulation and solving complex problems. The whole volume is saturated with R scripts, examples of the language application to numerous aims, and each chapter suggests multiple links to the internet websites related to the topics under consideration. Bibliography of more than eighty sources is also supplied. The book presents an incredibly useful source of information on the modern statistical techniques and their implementations to solving various real-life problems, that makes it very helpful to students and researchers in their projects.'- Stan Lipovetsky, Technometrics, Vol. 63, Issue 3, August 2021