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ECONOMETRICS I

ECONOMETRICS I. CHAPTER 9 DUMMY VARIABLE REGRESSION MODELS. Textbook: Damodar N. Gujarati (2004)  Basic Econometrics , 4th edition, The McGraw-Hill Companies. The types of variables that we have encountered in the preceding chapters were essentially ratio scale.

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ECONOMETRICS I

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  1. ECONOMETRICS I CHAPTER 9 DUMMY VARIABLE REGRESSION MODELS • Textbook: Damodar N. Gujarati (2004) Basic Econometrics, 4th edition, The McGraw-Hill Companies

  2. The types of variables that we have encountered in the preceding chapters were essentially ratio scale. • In this chapter, we consider models that may involve nominal scale variables. Such variables are also known as indicator variables, categorical variables, qualitative variables, or dummy variables.

  3. 9.1 THE NATURE OF DUMMY VARIABLES

  4. 9.1 THE NATURE OF DUMMY VARIABLES

  5. 9.2 ANOVA MODELS

  6. 9.2 ANOVA MODELS

  7. 9.2 ANOVA MODELS

  8. 9.2 ANOVA MODELS

  9. 9.2 ANOVA MODELS

  10. 9.2 ANOVA MODELS

  11. 9.2 ANOVA MODELS

  12. Caution in the Use of Dummy Variables • If a qualitative variable has m categories, introduce only (m−1) dummy variables. If you do not follow this rule, you will fall into what is called the dummy variable trap, that is, the situation of perfect collinearity or perfect multicollinearity. • The category for which no dummy variable is assigned is known as the base, benchmark, control, comparison, reference, or omitted category. And all comparisons are made in relation to the benchmark category. • The intercept value (β1) represents the mean value of the benchmarkcategory. In Example 9.1, the benchmark category is the Western region.Hence, in the regression (9.2.5) the intercept value of about 26,159 representsthe mean salary of teachers in the Western states.

  13. Caution in the Use of Dummy Variables

  14. Caution in the Use of Dummy Variables

  15. Caution in the Use of Dummy Variables

  16. Caution in the Use of Dummy Variables

  17. 9.3 ANOVA MODELS WITH TWO QUALITATIVE VARIABLES

  18. 9.3 ANOVA MODELS WITH TWO QUALITATIVE VARIABLES

  19. 9.3 ANOVA MODELS WITH TWO QUALITATIVE VARIABLES

  20. 9.4 REGRESSION WITH A MIXTURE OF QUANTITATIVE AND QUALITATIVE REGRESSORS: THE ANCOVA MODELS

  21. 9.4 REGRESSION WITH A MIXTURE OF QUANTITATIVE AND QUALITATIVE REGRESSORS: THE ANCOVA MODELS

  22. 9.4 REGRESSION WITH A MIXTURE OF QUANTITATIVE AND QUALITATIVE REGRESSORS: THE ANCOVA MODELS

  23. 9.4 REGRESSION WITH A MIXTURE OF QUANTITATIVE AND QUALITATIVE REGRESSORS: THE ANCOVA MODELS

  24. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  25. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  26. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  27. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  28. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  29. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  30. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  31. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  32. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  33. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

  34. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

  35. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

  36. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

  37. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

  38. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

  39. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

  40. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

  41. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

  42. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

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