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ECO601 : Business Econometrics

Course Overview

Course Synopsis

The course aims at enhancing the knowledge and skill related to use of econometrics in business research. It covers problems like regression analysis, regression diagnostics, simultaneous and structural equation systems, and categorical dependent variable models. The course may cover topics in analyzing cross sectional data, time series and panel data. The course focuses on learning the theory of econometrics but may have both the theoretical and practical aspect using software like Microsoft Excel, SPSS and/or ‘Stata’where necessary.

Course Learning Outcomes

After studing this course;

  • The students may be able to apply econometric techniques to research in business.
  • The course shall result in developing good skills in applying econometric modeling to business studies.
  • It will lead to enabling the students to be independent researchers, who can analyze, estimate and forecast business outcomes.
  • It develops the skills related to analyze a research question, apply an appropriate model, estimate models and forecast results.

Course Calendar

What is Econometrics About?1Handouts2
Why should we study Econometrics?1Handouts4
Methodology of Econometrics.1Handouts5
Structure of Data1Handouts6
Sources of Data1Handouts8
Types of Data files1Handouts8
Summation Operators2Handouts9
Some functions & their properties. (Linear, quadratic, Natural Logarithm, exponential functions etc.)2Handouts16
Higher order derivatives3Handouts32
Partial derivatives4Handouts33
Multivariate Optimization5Handouts40
Basics of Probability distributions5Handouts46
Normal and related distributions5Handouts49
Definition of The Simple Regression Model - I6Handouts54
Deriving the ordinary least square (OLS) estimates and their formula6Handouts62
Properties of OLS6Handouts65
Quiz No 01
Estimation and Testing in Regression Analysis7Handouts67
Examples Using Microsoft Excel8Handouts79
Effects of changing Units of Measurement8Handouts84
Incorporating nonlinearities in simple regression8Handouts85
Multiple Regression9Handouts89
Deriving the estimates and their formula with 2 independent variables9Handouts89
Diagnostic Tests9Handouts98
Analysis ToolPak: DATA ANALYSIS Add-In in Microsoft Excel100
Understanding the Regression Results10Handouts107
Assignment No 01
Transformation for Regression11Handouts111
Exponential and Logarithmic Function11Handouts112
Dynamic Models: Models with lagged independent Variable11Handouts115
Models with interaction terms11Handouts115
Regression on standardized variables12Handouts117
Summary Statistics, Correlation Matrix, Graphs12Handouts118
Regression with qualitative explanatory variables13Handouts125
Dummy Variables and their use13Handouts125
Using logs in regression analysis14Handouts132
Regression with growth rates, ratios and percentages14Handouts133
Treatment of missing data14Handouts134
What is Multicollinearity?15Handouts139
Theoretical Consequences of Multicollinearity15Handouts142
Practical consequences of Multicollinearity15Handouts143
How to detect for Multicollinearity?15Handouts143
Remedial Measures for Multicollinearity16Handouts146
Some practical examples17Handouts147
What is Heteroskedasticity?17Handouts152
Consequences of Heteroskedasticity?17Handouts155
Tests for Heteroskedasticity: Visual Inspection17Handouts155
Detection of Heteroskedasticity18Handouts158
Formal Tests18Handouts158
Quiz No 02
Detection of Heteroskedasticity: Examples of Formal Tests19Handouts163
Dealing with Heteroskedasticity problem19Handouts167
What is Serial Correlation?20Handouts171
Nature of Serial Correlation20Handouts171
Causes and examples20Handouts172
Detection of Autocorrelation21Handouts176
Graphic method, AR(1) test with strictly exogenous regressors, AR(1) test without strictly exogenous regressors, Durbin Watson d Test, Durbin h Test, LM Test21Handouts
Treatment of Autocorrelation22Handouts184
Removal: Generalized differencing (GLS22Handouts184
Generalized Differencing : Special Cases22Handouts185
Estimating Non-Linear equation by OLS23Handouts193
Transforming models and estimating by OLS23Handouts196
Introduction to Stata24Handouts200
Introduction to Stata25Handouts210
Quiz No 03
Data Management in Stata26Handouts218
Practice session of Stata27Handouts228
Graphs in Stata28Handouts228
Regression with Stata29Handouts241
Post Regression analysis29Handouts245
Graded Discusion Board
Simultaneous Equation Models30Handouts254
Exogenous and Endogenous Variables30Handouts255
Identification Problem30Handouts256
Simultaneous Equation Models-II31Handouts259
Indirect Least Square (ILS): EXAMPLE II)32Handouts266
Examples of Identification and applying ILS32Handouts271
Two Stage Least Square33Handouts273
Examples of Identification & applying 2SLS33Handouts274
Using Stata for Two Stage Least Square (2SLS)33Handouts278
Two Stage Least Square: continued34Handouts282
Three stage least square34Handouts285
Three Stage Least Square: Select independent variables34Handouts286
Panel Data Methods35Handouts291
Pooled Regression35Handouts294
Least Square Dummy Variable model35Handouts294
Error component: one way and two way36Handouts295
Fixed Effect Model36Handouts297
Fixed Effect Model Estimation: First Difference36Handouts298
Random Effect Model36Handouts299
Panel Data Models using Stata36Handouts300
Panel Data Methods & Post Estimation Tests37Handouts307
Quiz No 04
Qualitative and limited dependent variable38Handouts321
Logistic Regression38Handouts321
Logistic Regression using Stata38Handouts322
Example of Logistic Regression using Stata38Handouts323
Ordinal Logistic Regression38Handouts324
Qualitative and limited dependent variable39Handouts328
Probit Regression39Handouts329
Example of probit Regression using Stata39Handouts330
Ordinal Probit Regression39Handouts331
Qualitative and limited dependent variable40Handouts334
Post regression tests after logit/probit models40Handouts336
Censored Data Regression Models40Handouts337
Tobit Model using Stata40Handouts338
Types of Forecasts41Handouts344
Time Series Models for forecasting41Handouts346
Examples of Forecasting Techniques41Handouts347
Forecasting( Count-)42Handouts352
Seasonal Variation and forecasting42Handouts352
Calculating Seasonal Index42Handouts352
Measuring Forecast Performance42Handouts354
Variance of Forecast Error42Handouts361
Stationary & Non-Stationary data43Handouts364
Unit Root Test43Handouts366
Cointegration & Error Correction Model Using Stata44Handouts373
Cointegration & Error Correction Model Example44Handouts375
Time Series Revisited45Handouts379
ARMA processes45Handouts384
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