1. Ekonometrika

6. 1. WHAT IS ECONOMETRICS

26. 2. THE NATURE OF REGRESSION ANALYSIS

27. Anatomy of econometric modeling

32. A HYPOTHETICAL EXAMPLE in the table refer to a total population of 60 families in a hypothetical community and their weekly income ( X ) and weekly consumption expenditure ( Y ), both in dollars. The 60 families are divided into 10 income groups (from $80 to $260) and the weekly expenditures of each family in the various groups are as shown in the table

33. E ( Y | Xi ) = β 1 + β 2 Xi where β 1 and β 2 are unknown but fixed parameters known as the regression coefficients; β 1 and β 2 are also known as intercept and slope coefficients, respectively. Equation (2.2.1) itself is known as the linear population regression function. Some alternative expressions used in the literature are linear population regression model or simply linear population regression

36. STOCHASTIC SPECIFICATION OF population regression function (PRF) family consumption expenditure on the average increases, the relationship between an individual family’s consumption expenditure and a given level of income? where the deviation ui is an unobservable random variable taking positive or negative values. Technically, ui is known as the stochastic disturbance or stochastic error term.

39. THE SAMPLE REGRESSION FUNCTION (SRF)

42. 3. TWO-VARIABLE REGRESSION MODEL: THE PROBLEM OF ESTIMATION

46. Sering ditemukan pada data cross section

47. Sering ditemukan pada data timeseries

50. The fundamental psychological law . . . is that men [women] are disposed, as a rule and on average, to increase their consumption as their income increases, but not by as much as the increase in their income,” that is, the marginal propensity to consume (MPC) is greater than zero but less than one

55. THE RELATIONSHIP BETWEEN EARNINGS AND EDUCATION CONSUMPTION–INCOME RELATIONSHIP IN THE UNITED STATES, 1982–1996

57. TWO-VARIABLE REGRESSION MODEL: THE PROBLEM OF ESTIMATION Recall the two-variable PRF where ˆ Yi is the estimated (conditional mean) value of Yi . which shows that the ˆ ui (the residuals) are simply the differences between the actual and estimated Y values

59. TWO-VARIABLE REGRESSION: INTERVAL ESTIMATION AND HYPOTHESIS TESTING

62. Type kesalahan Keputusan tepat Kesalahan jenis II Jika Ho salah Kesalahan jenis I Keputusan tepat Jika Ho benar Menolak Ho Menerima Ho Hipotesis o

71. MULTICOLLINEARITY: WHAT HAPPENS IF THE REGRESSORS ARE CORRELATED?

79. AUTOCORRELATION: WHAT HAPPENS IF THE ERROR TERMS ARE CORRELATED?

82. shows a cyclical pattern

83. suggests an upward or downward linear trend in the disturbances

84. indicates that both linear and quadratic trend terms are present in the disturbances

85. indicates no systematic pattern nonautocorrelation

90. Korelasi

105. Korelasi

118. HETEROSCEDASTICITY WHAT HAPPENS IF THE ERROR VARIANCE IS NONCONSTANT?

125. what happens to the regression results if the observations for Chile are dropped from the analysis

130. Park Test

131. Glejser Test

132. Rank spearman

133. DUMMY VARIABLE REGRESSION MODELS

154. Logarithmic Functions