Course Contents

Linear and Non-Linear Regression Models Introduction, Estimation and Hypothesis Testing of Linear and Non-Linear Regression Models, Problems of Multicollinearity, Heteroscedasticity and Autocorrelation, Assumptions of Generalize Regression Models; Generalized Least Squares (GLS) and Feasible GLS methods and its Application Simultaneous Equations Models Simultaneous equations and applications in microeconomics and macroeconomics: Indirect Least Squares (ILS), Two-Stage Least Squares (2SLS), Three-Stage Least (3SLS) and Instrumental Variables Technique (IV), Vector Autoregressive Model (VAR): Likelihood Ratio. Lagrange Multiplier and Wald tests; Model Selection: Choice of Variables and Choice of Functional Form, Hausman test Nested and Non-Nested Models Testing Between Nested and Non-Nested Models; Qualitative Response Models; Dummy variables, Structural Shifts, Seasonality, Tests of Structural Shifts and Model Stability, Spline functions; Structure Estimation Techniques of pooled Time Series and Cross Section Data Assumption and Estimation Techniques of pooled Time Series and Cross Section Data: Dynamic Models Involving Pooled Data and GMM Estimation; Seemingly Unrelated Regression Models, Limited Dependent Variables: Linear and Non-Linear Probability Models for Bivariate and Multivariate Models.

Course Synopsis

The Course ‘Econometric Theory and Methods’ plays a significant role in learning econometrics techniques and resolving the economic problems of an economy. The objective of the course is to make the student understand an advanced treatment of econometric theory and methods for cross-sectional, panel (or longitudinal), and time-series data sets. The Course will focus on modern econometric techniques and its practical applications.

Course Learning Outcomes

The course will enable the student to understand:  linear and Non-linear regression models, their estimation and inference  stationary and Non-stationary time Series models and their main features  estimation of simultaneous equations and their applications in microeconomics and macroeconomics  estimation techniques of Pooled time series and Cross section data and their application  econometric model for estimating an economic model under certain specific situation