Basic Econometrics

Summary

One of the significant roles of econometrics is to provide the tools for modeling on the basis of given data. The regression modeling technique helps a lot in this task. The regression models can be either linear or non-linear based on which we have linear regression analysis and non-linear regression analysis. We will consider only the tools of linear regression analysis and our main interest will be the fitting of linear regression model to a given set of data.

Most current econometric texts either make no mention of causality, or else contain a brief and superficial discussion. Establishing causality is often a central concern in many papers in applied econometrics. Differentiating between causes and effects of growth, poverty reduction, inflation, etc. is of crucial importance to crafting suitable policy and developing an understanding of the world we live in. Due to lack of appropriate training, many published articles display very poor understanding of the evidence required to support causal claims.

In Basic Econometrics course, we are going to study about the sample and based on that we estimate population parameters. In our basic model, we develop best linear unbiased estimator for the population. These estimators are the best to predict population parameters and it’s based on certain assumption. We will look at what happen when assumptions are violated and what are the possible remedies of it. Also, we will look at qualitative aspect of explanatory variable in the model in the form of Dummy variable.

The task of this workbook is to make interactive foundation for the basic concept of Econometrics, hope this will help students to understand this area.

CBCS Syllabus

1. Introduction

 Concept - Types – theoretical and applied econometrics- importance and role of

Econometrics in economics- Classical Methodology of Econometrics.

2. The Classical Linear Regression Model (Two variable case)

 The Classical Ordinary Least Square Method (CLSM) – Assumptions – estimation of

parameters in two variable case – Properties of least-square estimators – testing of

regression coefficients – BLUE – Goodness of Fit - the Coefficient of determination R2 –

Numerical Problems.

3. The Classical Linear Regression Model (Three variable case)

 The Classical Ordinary Least Square Method (CLSM) – estimation of parameters with

Two independent variables – Violation of the Assumptions of CLSM – Multicollinearity,

Heteroscedasticity and Autocorrelation (Concepts only).

4. Dummy Variable

 Introduction – Dummy independent variable – estimation – dummy variable trap

Chapters

0. Review of Statistical Methods

1. Introduction

2. Simple Linear Regression Model

Online lecture

Lecture 1 - Introduction and development of basic concept, 15 min + 1.18 hrs date 24/03/2020 available at

Video output

https://www.facebook.com/shashi.krshaw.737/videos/143389503861043/

Transcript

https://drive.google.com/open?id=1zWAp_pVfU6mp4Il8v98S043iNj-Hn135

Lecture 2 - 26 March 11 am - Basic econometric; PRF , SRF, Significance of Error term, Method of Ordinary least square. 1.18 hrs, available at

Video output

https://www.facebook.com/shashi.krshaw.737/videos/144100297123297/

Transcript

https://www.facebook.com/shashi.krshaw.737/videos/144100297123297/

Lecture 3 - 29 March 11 am, Revision of concept, Features and proof of OLS method and numerical example. 1.42 hrs + 20 min,available at

Transcript

https://drive.google.com/file/d/1-3dicC3bckreNbnDRwsT1yb5XbguO3eZ/view?usp=drivesdk&fbclid=IwAR0mb4GkUEAVrYcBztpWPqaoNYiHZPu6nB5HgtSHkDyK4NlsC1mGVqlPBGI

Video output

https://www.facebook.com/shashi.krshaw.737/videos/145118743688119/

and Summary

https://youtu.be/usRnX5wFvBM?fbclid=IwAR1zkrECiZndJ_Sj-NFd2sugU9My9U0zTNsi-COS9OmBkZhIcYPK_Aat3n8

Lecture 4 -30 March - 1 hrs, Three time series numerical

Transcript

https://drive.google.com/open?id=1vDtGZXN_DNscLOBvbCi0eMKlxLi6endM

Video output

https://www.facebook.com/shashi.krshaw.737/videos/145479283652065/

Questions based on topics covered for final exam

https://drive.google.com/open?id=14wYwLlCNgLWe8kUstefdhb_cOIw2t5zm