Estimation theory | Econometric models

Endogeneity (econometrics)

In econometrics, endogeneity broadly refers to situations in which an explanatory variable is correlated with the error term. The distinction between endogenous and exogenous variables originated in simultaneous equations models, where one separates variables whose values are determined by the model from variables which are predetermined; ignoring simultaneity in the estimation leads to biased estimates as it violates the exogeneity assumption of the Gauss–Markov theorem. The problem of endogeneity is often ignored by researchers conducting non-experimental research and doing so precludes making policy recommendations. Instrumental variable techniques are commonly used to address this problem. Besides simultaneity, correlation between explanatory variables and the error term can arise when an unobserved or omitted variable is confounding both independent and dependent variables, or when independent variables are measured with error. (Wikipedia).

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From playlist Trigonometry

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From playlist Switching Models in Econometrics

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From playlist Trigonometry

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From playlist Centro di Ricerca Matematica Ennio De Giorgi

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From playlist Ethics, Politics and Economics

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From playlist Trigonometry

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From playlist Learning medical statistics with python and Jupyter notebooks

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From playlist Trigonometry

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From playlist Medical Statistics

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From playlist Turing Seminars

Related pages

Confounding | Errors-in-variables models | Dependent and independent variables | Structural equation modeling | Variable (mathematics) | Correlation | Time series | Consistent estimator | Heckman correction | Ordinary least squares | Regression analysis | Simultaneous equations model | Gauss–Markov theorem | Granger causality | Econometrics | Omitted-variable bias | Bias of an estimator | Errors and residuals