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Testowanie wielokrotne przy budowie liniowego modelu ekonometrycznego

100%
Denkowska S.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2011
|
issue 876
27-42
EN
The development of econometric models is often accompanied by multiple testing of numerous statistical hypotheses. Even during the regression model’s variable-selection stage a substantial number of methods are based on multiple testing. However, uncontrolled parallel testing of many hypotheses may lead to “very poor models”, so it is advisable where possible to limit the number of testings and apply the methods of selecting explanatory variables which are not based on multiple inference (e.g. Hellwig’s method) or those which keep this effect under control (using the modified method of graph analysis). In practical statistical research it is common to use sequential methods of variable selection for the regression model in which the final version of the model is achieved by gradual “improvements” of consecutive versions of the model. In sequential methods of variable selection for an econometric model in which the assumed criterion is the statistical significance of the parameters, controlling the effect of multiple testing is a very complicated task. In such procedures, apart from parallel multiple inference, sequential inference may also be involved, which considerably hinders the ability to control this effect. Controlling multiple testing is necessary during the final stage of developing the econometric model, i.e. during its verification. While using sequential methods, it is advisable to control parallel testing during consecutive stages of “improving” the versions of the econometric model while inferring the statistical significance of regression parameters in the regression model. The empirical example presented in the article shows how to control multiple testing in the process of developing the econometric model using the procedures of multiple testing based on p-values. In this empirical example, control was introduced model-construction phase, which allowed us to shorten the algorithm used to develop the model by eliminating statistically insignificant variables in the early stages of its development.
2

Testowanie jednoczesne przy weryfikacji ocen parametrów strukturalnych liniowego modelu ekonometrycznego

100%
Denkowska S.
Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie
|
2011
|
issue 873
53-68
EN
In the process of verifying an econometric model, two stages can be identified. The first embraces “commonsensical” analysis of the results: whether they are in accordance with the theory of economy or observable results of experiments. The second consists of statistical analysis in which we test the statistical significance of this model both by using the global test and by testing each partial regression coefficient separately. Each of these analyses is usually conducted at the α level and the fact of multiple testing is disregarded. Disregarding multiple testing may result in bad decisions being made regarding the statistical significance of regression coefficients, which are in fact insignificant. Applying the procedures of multiple testing during the final stage of developing the econometric model used to test the significance of structural parameters of the linear econometric model allows us to determine whether the remaining structural parameters have been regarded as significant only because of multiple testing during the verification of their statistical significance.
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