Endogeneity (econometrics)

<p>In <a href="/facts/Econometrics/7U52gzHt">econometrics</a>, endogeneity broadly refers to situations in which an <a href="/facts/Explanatory_variable/dINfzIF2">explanatory variable</a> is <a href="/facts/Correlation/egkluAEm">correlated</a> with the <a href="/facts/Errors_and_residuals/Ef0LgAS4">error term</a>. The distinction between <a href="/facts/Endogenous_and_exogenous_variables/CTpuBsPM">endogenous and exogenous variables</a> originated in <a href="/facts/Simultaneous_equations_model/QtJbu6bV">simultaneous equations models</a>, where one separates <a href="/facts/Variable_(mathematics)/VbQlrvKz">variables</a> whose values are determined by the <a href="/facts/Economic_model/gNM1Tuct">model</a> from variables which are predetermined. Ignoring simultaneity in the estimation leads to biased estimates as it violates the exogeneity assumption of the <a href="/facts/Gauss%25E2%2580%2593Markov_theorem/j85SGhrw">Gauss–Markov theorem</a>. The problem of endogeneity is often ignored by researchers conducting non-experimental research and doing so precludes making policy recommendations. <a href="/facts/Instrumental_variable/cEQ1xwT6">Instrumental variable</a> techniques are commonly used to mitigate this problem.
</p><p>Besides simultaneity, correlation between explanatory variables and the error term can arise when an unobserved or <a href="/facts/Omitted-variable_bias/eoDm4AJX">omitted variable</a> is <a href="/facts/Confounding/G4TVx1dt">confounding</a> both independent and dependent variables, or when independent variables are <a href="/facts/Errors-in-variables_models/PRDddry0">measured with error</a>.
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Endogeneity (econometrics) open-in-new

Endogeneity (econometrics)