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9 Assessing Studies Based on Multiple Regression

The majority of Chapter 9 of the book is of a theoretical nature. Therefore this section briefly reviews the concepts of internal and external validity in general and discusses examples of threats to internal and external validity of multiple regression models. We discuss consequences of

  • misspecification of the functional form of the regression function
  • measurement errors
  • missing data and sample selection
  • simultaneous causality

as well as sources of inconsistency of OLS standard errors. We also review concerns regarding internal validity and external validity in the context of forecasting using regression models.

The chapter closes with an application in R where we assess whether results found by multiple regression using the CASchools data can be generalized to school districts of another federal state of the United States.

For a more detailed treatment of these topics we encourage you to work through Chapter 9 of the book.

The following packages and their dependencies are needed for reproduction of the code chunks presented throughout this chapter:

  • AER
  • mvtnorm
  • stargazer