Course Co-ordinated by IIT Kharagpur
 Coordinators IIT Kharagpur

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The objective of this course is to present a comprehensive tools and techniques for managerial decision making including problem of cost estimation, market size determination, sales projection, stock price prediction, etc.

It has two parts. First part deals with regression-based modeling, which captures the behavior of variable through a structural model based on theory.

The second part deals with time series modeling, which concentrates on the dynamic characteristics of economic and financial data. The tentative subject outline is described below.

Contents

What is Econometrics? Difference between Econometrics, Mathematics and Statistics, Basics of Model Building, Basics of Business Forecasting, Univariate Statistics, Bivariate Statistics, Probability and Hypothesis Testing.

Bivariate Econometric Modelling, Trivariate Econometric Modelling, Multivariate Econometric Modelling, Multicolinearity, Serial Correlation, Heteroskedasticity, DG Test, Dummy Variable Econometric Modelling.

Panel Data Modelling, Lag Modelling, Identification Problem, Structural Equation Modelling, Basics of Time Series, Box- Jenkins Methods, Error Measurements, Univariate Time Series Modelling.

Unit Root Test, Cointegration Test, Causality Test, VECM, ARM, MAM, ARIMA, ARCH, GARCH, EGARCH, TGARCH.

 Module Lecture Learning Topic Total Hours Module 1 1 INTRODUCTION TO ECONOMETRIC MODELLING 1 Module 2 2 STRUCTURE OF ECONOMETRIC MODELLING 1 Module 3 3 UNIVARIATE ECONOMETRIC MODELLING 1 Module 4 4 PROBABILTY THEORY 1 Module 5 5 HYPOTHESIS TESTING 1 Module 6 6 INTRODUCTION TO BIVARIATE ECONOMETRIC MODELLING 1 Module 7 7 RELIABILITY OF BIVARIATE ECONOMETRIC MODELLING 1 Module 8 8 INTRODUCTION TO TRIVARIATE ECONOMETRIC MODELLING 1 Module 9 9 INTRODUCTION TO MULTIVARIATE ECONOMETRIC MODELLING 1 Module 10 10 MATRIX APPROACH  TO ECONOMETRIC MODELLING 1 Module 11 11 CONSTRAINTS OF OLS ESTIMATIONS 1 Module 12 12,13 MULTICOLLINEARITY PROBLEM 2 Module 13 14,15 AUTOCORRELATION PROBLEM 2 Module 14 16,17 HETEROSCEDASTICITY PROBLEM 2 Module 15 18,19 DUMMY REGRESSION MODELLING 2 Module 16 20,21 QUALITATIVE RESPONSE REGRESSION MODELLING 2 Module 17 22,23 PANEL DATA MODELING 2 Module 18 24,25 SIMULTANEOUS EQUATION MODELING 2 Module 19 26,27,28 STRUCTURAL EQUATION MODELING 3 Module 20 29,30 BASICS OF TIME SERIES MODELING 2 Module 21 31,32 UNIT ROOTS TEST 2 Module 22 33,34 COINTEGRATION TEST 2 Module 23 35,36 GRANGER CAUSALITY TEST 2 Module 24 37,38 VOLATILITY TIMESERIES MODELS 2 Module 25 39,40 VECTOR AUTOREGRESSIVE MODEL 2 Total Lec-40 Total hours - 40

Stat and Math courses in undergraduate (B Tech) program.

Preferred Background.

2. Some probability and statistics.

3. 2 years Work experience is recommended.

1. Pindyck, R. S. and Daniel, L. R., "Econometric Models and Business Forecasts", McGraw Hill, New York.

2. Brooks, C., "Introductory Econometrics for Finance", Addison Wesley Longman, New York.

3. Campbell, J. Y., Andrew, W. L. and Mackinley, A. L., "The Econometrics of Financial Markets", Princeton University Press, Princeton.

4. Granger, C. W., "Forecasting in Economics and Business", Academic Press, New York.

5. Gujarati, D. N., "Basic Econometrics", McGraw Hill, New York.

6. Douglas, C. Montgomery, Elizabeth A. Peck and G. Geoffrey Vining, "Introduction to Linear Regression Analysis", Wiley Publications, New York.

7. Norman R. Draper and Harry Smith, "Applied Regression Analysis", Wiley Publications, New York.