Econometrics - Multiple Variable Regression - Chapter 4 - Gujarati - 2020

This video is based on Chapter 4 (Multi-Variable Regression) of D.N. Gujarati & Porter's, Essentials of Econometrics. This chapter further extends our discussion to include more explanatory variables in regression process and the implications on our analysis.

I have covered the following topics in this video:

1. Three Variable Regression: Interpretation of Partial Regression Coefficients, Assumptions (addition of Multi-Co-linearity), Estimation of parameters & Standard Errors, Hypothesis Testing (Individual Parameters)

2. Concept of Overall Significance of Model: Joint Hypothesis & Use of ANOVA Table for its analysis.

3. Relation between F & R square & Utility of Adjusted R Square to Compare Models across different explanatory variables.

4. When to add an Explanatory Variable: Use of Restricted vs Unrestricted Regression.

Overall, this chapter does not always give direct questions, yet at a fundamental level the concepts discussed are key in the overall framework of regression analysis.

I welcome all students of Delhi University (Economics Hons. Sem IV, BBE Sem IV) as well other students preparing for IES, UGC-NET & Masters to go through the video and review it.

My Best Wishes & Happy Learning :)

The Pink Professor
(Siddharth Rathore)
Department of Economics
Gargi College
University of Delhi