C. Dubbelman

Disturbances in the linear model, estimation and hypothesis testing (eBook, PDF)

Estimation and Hypothesis Testing

• Format: PDF

Produktbeschreibung

1. 1. The general linear model All econometric research is based on a set of numerical data relating to certain economic quantities, and makes infer ences from the data about the ways in which these quanti ties are related (Malinvaud 1970, p. 3). The linear relation is frequently encountered in applied econometrics. Let y and x denote two economic quantities, then the linear relation between y and x is formalized by: where {31 and {32 are constants. When {31 and {32 are known numbers, the value of y can be calculated for every given value of x. Here y is the dependent variable and x is the explanatory variable. In practical situations {31 and {32 are unknown. We assume that a set of n observations on y and x is available. When plotting the ob served pairs (x l' YI)' (x ' Y2)' . . . , (x , Y n) into a diagram with x 2 n measured along the horizontal axis and y along the vertical axis it rarely occurs that all points lie on a straight line. Generally, no b 1 and b exist such that Yi = b + b x for i = 1,2, . . . ,n. Unless 2 l 2 i the diagram clearly suggests another type of relation, for instance quadratic or exponential, it is customary to adopt linearity in order to keep the analysis as simple as possible.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 108
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781468469561
• Artikelnr.: 44063800

Inhaltsangabe

1. Introduction.- 1.1. The general linear model.- 1.2. BLU ?-estimation.- 1.3. BLU disturbance estimation.- 1.4. Autocorrelation and heterovariance.- 1.5. Autocorrelation simulated and estimated.- 1.A. Appendix.- 2. Tabulable quadratic ratio tests.- 2.1. The form of the test statistic T.- 2.2. Calculable distribution functions.- 2.3. Tabulable distribution functions.- 2.4. On the choice of w and ?.- 2.5. Three specific tests.- 2.6. Significance point calculation.- 2.7. Bounds tests.- 3. BLUF disturbance estimation.- 3.1. The problem.- 3.2. The derivation of w.- 3.3. Special cases.- 3.4. The residual aspect.- 3.5. Durbin's alternative disturbance estimator.- 4. An empirical ?.- 4.1. From the general to a specific w.- 4.2. Measures for ?.- 4.3. Principal components.- 4.4. And empirical P-matrix.- 4.5. Streamlining of P.- 4.6. Generalization for n and k.- 4.7. An empirical hypothesis and a selection device.- 4.A, Appendix.- 5. Evaluation of the tests.- 5.1. Description of the test cases.- 5.2. Values of ? and the selection device.- 5.3. Evaluation of the disturbance estimators in test (Q).- 5.4. Experiments with the matrix J.- 5.5. Evaluation of the disturbance estimators in test (S) and test (V).- References.