Specification (regression)
Encyclopedia
In regression analysis
Regression analysis
In statistics, regression analysis includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables...

 and related fields such as econometrics
Econometrics
Econometrics has been defined as "the application of mathematics and statistical methods to economic data" and described as the branch of economics "that aims to give empirical content to economic relations." More precisely, it is "the quantitative analysis of actual economic phenomena based on...

, specification is the process of converting a theory into a regression model. This process consists of selecting an appropriate functional form
Function (mathematics)
In mathematics, a function associates one quantity, the argument of the function, also known as the input, with another quantity, the value of the function, also known as the output. A function assigns exactly one output to each input. The argument and the value may be real numbers, but they can...

 for the model and choosing which variables to include. Model specification is one of the first steps in regression analysis. If an estimated model is misspecified, it will be biased and inconsistent.

Specification error and bias

Specification error occurs when an independent variable is correlated with the error term. There are several different causes of specification error:
  • incorrect functional form
  • a variable omitted from the model may have a relationship with both the dependent variable and one or more of the independent variables (omitted-variable bias
    Omitted-variable bias
    In statistics, omitted-variable bias occurs when a model is created which incorrectly leaves out one or more important causal factors. The 'bias' is created when the model compensates for the missing factor by over- or under-estimating one of the other factors.More specifically, OVB is the bias...

    );
  • an irrelevant variable may be included in the model
  • the dependent variable may be part of a simultaneous equation (simultaneity bias)
  • measurement errors may affect the independent variables.
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