1. The Nature of Dummy Variables The Nature of Dummy Variables Regression on One Quantitative Variable and One Qualitative Variable with Two Classes, or Categories Regression on One Quantitative Variable and One Qualitative Variable with Two Classes, or Categories Regression on One Quantitative Variable and One Qualitative Variable with More than Two Classes Regression on One Quantitative Variable and One Qualitative Variable with More than Two Classes Regression on One Quantitative Variable and Two Qualitative Variable Regression on One Quantitative Variable and Two Qualitative Variable Example 15.3: The Economics of “ Moonlighting ” Example 15.3: The Economics of “ Moonlighting ” Testing for Structural Stability of Regression Models: Basic Ideas Testing for Structural Stability of Regression Models: Basic Ideas Comparing Two Regression: The Dummy Variable Approach Comparing Two Regression: The Dummy Variable Approach Comparing Two Regressions: Further Illustration Comparing Two Regressions: Further Illustration Interaction Effects Interaction Effects The Use of dummy Variables in Seasonal Analysis The Use of dummy Variables in Seasonal Analysis Some Technical Aspects of Dummy Variable in Technique Some Technical Aspects of Dummy Variable in Technique Topics for Further Study Topics for Further Study Summary and Conclusions Summary and Conclusions Topics in Econometrics 15- Regression on Dummy Variables

2.  Dummy Dependent Variable  The Linear Probability Model (LPM)  Problems in Estimation of LPM  LPM: A Numerical Example  Applications of LPM  Alternatives to LPM  The Logit Model  Estimation of the Logit Model  The Logit Model: A Numerical Example  The Logit Model: Illustrative Example  The Probit Model  The Probit Model: A Numerical Example  The Probit Model: Example 16.5  The Tobit Model  Summary and Conclusions 16- Regression on Dummy Dependent Variable: The LPM, Logit, Probit, and Tobit Models

3. The Role of “ Time ” or “ Lag ” in Economics The Role of “ Time ” or “ Lag ” in Economics The Reasons for Lags The Reasons for Lags Estimation of Distributed-Lag Models Estimation of Distributed-Lag Models The Koyck Approach to Distributed-lag Models The Koyck Approach to Distributed-lag Models Rationalization of the Koyck Model: The Adaptive Expectations Model Rationalization of the Koyck Model: The Adaptive Expectations Model Another Rationalization of the Koyck Model : The Stock Adjustment, or Partial Adjustment, Model Another Rationalization of the Koyck Model : The Stock Adjustment, or Partial Adjustment, Model Combination of Adaptive Expectations and Partial Adjustment Models Combination of Adaptive Expectations and Partial Adjustment Models Estimation of Autoregressive Models Estimation of Autoregressive Models The Method of Instrumental Variables (IV) The Method of Instrumental Variables (IV) Detecting Autocorrelation in Autoregressive Models: Durbin h Test Detecting Autocorrelation in Autoregressive Models: Durbin h Test A Numerical Example: The Demand for Money in India A Numerical Example: The Demand for Money in India Illustrative Examples Illustrative Examples The Almon Approach to Distributed-Lag Models: The Almon or Polynomial Distributed Lag (PDL) The Almon Approach to Distributed-Lag Models: The Almon or Polynomial Distributed Lag (PDL) Causality in Economics: The Granger Test Causality in Economics: The Granger Test Summary and Conclusions Summary and Conclusions 17- Dynamic Econometric Model: Autoregressive and Distributed-Lag Models