This textbook makes learning the basic principles of econometrics easy for all undergraduate and graduate students of economics. It specifically caters to the syllabus of the Introductory Econometrics course taught in the third year of the Bachelor of Economics program in many universities.

It takes the readers step-by-step from introduction to understanding, first introducing the basic statistical tools like concepts of probability, statistical distributions, and hypothesis tests, and then going on to explain the two variable linear regression models along with certain additional tools like use of dummy variables, various data transformations amongst others.

The most innovative feature of this textbook is that it familiarizes students with the role of R, which is a flexible and popular programming language. With its help, the student will be able to implement a linear regression model and deal with the associated problems with substantial confidence.

Point Estimation and the Method of Ordinary Least Squares

Point Estimation and the Method of Ordinary Least Squares

Point estimation and the method of ordinary least squares


In this chapter, we will learn about estimation of parameters. This chapter will cover the following:

  • The idea of an estimator as a random variable.
  • Some desirable properties of estimators: Unbiasedness, Efficiency, Consistency.
  • The Ordinary Least Squares (OLS) estimator for a two variable regression model: Estimating the parameters using the method of least squares and properties of OLS estimator.
  • Properties of the OLS estimators, and that they are BLUE under certain assumptions.
  • Goodness of fit measures and model selection criteria for the two-variable linear regression model.
  • The use of the F statistic in the context of the two-variable linear regression model.
  • Using dummy variables to model qualitative explanatory ...
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