1. CHAPTER 9 DUMMY VARIABLE REGRESSION MODELS
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 benchmark category. 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 represents the 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

25. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

32. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

34. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

35. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

36. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

37. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

38. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

39. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

40. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

41. 9.5 THE DUMMY VARIABLE ALTERNATIVE TO THE CHOW TEST

42. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

43. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

44. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

45. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

46. 9.6 INTERACTION EFFECTS USING DUMMY VARIABLES

47. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

48. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

49. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

50. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

51. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

52. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

53. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

54. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

55. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

56. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

57. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

58. 9.7 THE USE OF DUMMY VARIABLES IN SEASONAL ANALYSIS

59. 9.8 PIECEWISE LINEAR REGRESSION

60. 9.8 PIECEWISE LINEAR REGRESSION

61. 9.8 PIECEWISE LINEAR REGRESSION

62. 9.8 PIECEWISE LINEAR REGRESSION

63. FIGURE 9.6 Parameters of the piecewise linear regression.

64. EXAMPLE 9.7 TOTAL COST IN RELATION TO OUTPUT

65. EXAMPLE 9.7 TOTAL COST IN RELATION TO OUTPUT

66. 9.10 SOME TECHNICAL ASPECTS OF THE DUMMY VARIABLE TECHNIQUE

67. The Interpretation of Dummy Variables in Semilogarithmic Regressions

68. EXAMPLE 9.8 LOGARITHM OF HOURLY WAGES IN RELATION TO GENDER