# Disturbances in the linear model, estimation and hypothesis testing

• C. Dubbelman

1. Front Matter
Pages I-VII
2. C. Dubbelman
Pages 1-23
3. C. Dubbelman
Pages 24-49
4. C. Dubbelman
Pages 50-63
5. C. Dubbelman
Pages 64-90
6. C. Dubbelman
Pages 91-106
7. Back Matter
Pages 107-109

### Introduction

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.

### Keywords

econometrics research value-at-risk

#### Authors and affiliations

• C. Dubbelman
• 1
1. 1.Econometric InstituteErasmus University RotterdamNetherlands

### Bibliographic information

• DOI https://doi.org/10.1007/978-1-4684-6956-1
• Copyright Information Springer-Verlag US 1978
• Publisher Name Springer, Boston, MA
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• Print ISBN 978-90-207-0772-4
• Online ISBN 978-1-4684-6956-1
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