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Disturbances in the linear model, estimation and hypothesis testing: Estimation and Hypothesis Testing

Autor C. Dubbelman
en Limba Engleză Paperback – 31 iul 1978
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.
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Specificații

ISBN-13: 9789020707724
ISBN-10: 9020707728
Pagini: 120
Ilustrații: 108 p.
Dimensiuni: 152 x 229 x 6 mm
Greutate: 0.17 kg
Ediția:1978
Editura: Springer Us
Colecția Springer
Locul publicării:New York, NY, United States

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Research

Cuprins

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.