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1. The Nature of Econometrics and Economic Data
   Econometrics and models
   Steps in econometric modelling
   Types of economic data, time series, cross-sectional, panel
   Causality in econometric analysis
   Specification and Data Issues
   Functional form
   Proxy variables
   Measurement error in variables
   Missing data, outliers, influential observations
   Regression Analysis
   Estimation
   Ordinary least squares (OLS) estimators
   Classical OLS assumptions,
   Gauss Markov-Theorem
   Best Linear Unbiased Estimators
   Inference
   Testing statistical significance of parameters t-test(single, group)
   Confidence intervals
   Testing multiple linear restrictions, F-test
   Goodness of fit
   Testing functional form
   Missing variables
   Binary variables
   Testing for violation of assumptions and their implications:
   Heteroscedasticity
   Autocorrelation
   Multicolinearity
   Endogeneity
   Other Estimation techniques
   Instrumental Variables Estimation
   Generalised Least Squares
   Maximum Likelihood
   Generalised Method of Moments
   Models for Binary Response Variables
   Linear Probability Model
   Probit Model
   Logit Model
   Estimation
   Interpretation of parameters, Marginal Effects
   Goodness of Fit
   Limited Dependent Variables
   Tobit Model
   Truncated Normal Distribution
   Interpretation of Tobit Model
   Specification and Estimation Issues
   Time Series Models
   Characteristics of Time Series
   Decomposition of Time Series
   Exponential Smoothing
   Stationarity
   ARIMA models
   Co-Integration
   ECM model
   Predictive Analysis
   Forecasting, Planning and Goals
   Steps in Forecasting
   Evaluating Forecast Accuracy
   Redisual Diagnostics
   Prediction Intervals