Course Content

Module 1: Linear Regression Model: (10 Hours)

Two variable model: estimation of parameters, properties of parameters, hypothesis testing and model validation. Extension to multiple linear regression model

Module 2: Failure of classical assumptions: (10 Hours)

Heteroskedasticity, autocorrelation and multicollinearity: implications, corrective measures, Outliers:-implication and detection, non-normality of errors and bootstrapping of confidence intervals

Module 3: Systems of equations: (10 Hours)

Endogeneity and specification issues, Structural form and reduced form models, instrumental variables and two stage least squares

Module 4: Introduction to time series: (10 Hours)

Stationary and non-stationary time series, tests of stationarity, optimal forecasts and methods of forecast evaluation, introduction to ARIMA models