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What is blue in terms of OLS estimators?
OLS estimators are BLUE (i.e. they are linear, unbiased and have the least variance among the class of all linear and unbiased estimators). Each assumption that is made while studying OLS adds restrictions to the model, but at the same time, also allows to make stronger statements regarding OLS.
What do you mean by specification error?
In the context of a statistical model, specification error means that at least one of the key features or assumptions of the model is incorrect. Some forms of misspecification will result in misleading estimates of the parameters, and other forms will result in misleading confidence intervals and test statistics.
What is the definition of a model specification?
Statistical model specification. (Redirected from Specification (regression)) Jump to navigation Jump to search. In statistics, model specification is part of the process of building a statistical model: specification consists of selecting an appropriate functional form for the model and choosing which variables to include.
Can you use statistical assessments in model specification?
You can use statistical assessments during the model specification process. Various metrics and algorithms can help you determine which independent variables to include in your regression equation. I review some standard approaches to model selection, but please click the links to read my more detailed posts about them.
What causes a model to have an incorrect specification?
There are several different causes of specification error: An incorrect functional form could be employed; a variable omitted from the model may have a relationship with both the dependent variable and one or more of the independent variables (causing omitted-variable bias);
Is the specification of a regression model based on statistics?
Specification should not be based only on statistical measures. In fact, the foundation of your model selection process should depend largely on theoretical concerns. Be sure to determine whether your statistical results match theory and, if necessary, make adjustments.