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Econometrics

Econometrics I Summer 2011/2012 Course Guarantor :  prof. Ing. Zlata Sojková, CSc ., Lecturer : Ing. Martina Hanová, PhD. Econometrics. Regression Specification Error Test Types of specification errors : • Omitted variables • Incorrect functional form

sebastian-ramirez
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Econometrics

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  1. Econometrics I Summer 2011/2012 Course Guarantor:  prof. Ing. Zlata Sojková, CSc., Lecturer: Ing. Martina Hanová, PhD. Econometrics

  2. RegressionSpecificationError Test Typesofspecificationerrors: • Omitted variables • Incorrect functional form • Correlation between X and e, Ramsey's RESET Test

  3. RESET test

  4. Akaikeinformationcriterion Bayesian information criterion (BIC) or Schwarz criterion (also SBC, SBIC) Verification of the model specification

  5. Heteroskedasticity occurs when the variance of the disturbance is not constant. • often encountered in cross section data • not affect the parameter estimates • bias the variance of the estimated parameters. • t-values for your estimated coefficients cannot be trusted. • Goldfeld–Quandt test • Breusch–Pagan test or LagrangeMultiplier • White test Heteroscedasticity

  6. White test has become extremely widely used, the most powerful and most respected. Auxiliaryregression ei^2=b0 + b1*X1 + b2*X2 + b3*X1^2 + b4*X2^2 + b5*X1*X2 + ui White test

  7. violationoftheordinaryleastsquaresassumptionthattheerrorterms are uncorrelated Durbin–Watson Breusch–Godfrey test or Lagrangemultiplier test Autocorrelation

  8. Durbin-Watson test

  9. occurs when two or more predictors in the model arecorrelated provide redundant information about the response Consequences: Increased standard error of estimates Often confusing and misleading results Multicollinearity

  10. compute correlations between all pairs of predictors – correlationmatrix Farrar-Glauber Test calculation of the paired correlation coefficients Detecting multicollinearity

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