Heteroskedastic

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Heteroskedastic

A sequence of variables in which each variable has a different variance. Heteroskedastics may be used to measure the margin of the error between predicted and actual data. See also: ARCH.
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Thus, the variables were adjusted for this first-order autocorrelation, and heteroskedasticity was corrected (with the "force homoscedastic model" option in Microcrunch).
This method solves the difficulties posed by autocorrelation, (24) and allows the researcher to control the effects of heteroskedasticity, by first identifying the countries that have the large prediction errors contributing to heteroskedasticity, and then to control for that difficulty by adding dummy variables for those countries.
As the literature describes that most of the time the panel data suffers with the problems of autocorrelation/serial correlation and heteroskedasticity and in this case, the results of fixed effect or random effects regression models may provide spurious regression results.
Keywords: regression model, homoskedasticity, testing for heteroskedasticity, software environment MATLAB
Since estimation based on small areas can be affected by variations in the size of the population area usually associated with the issue of heteroskedasticity, that is, since the errors do not have the same variance (Messner and Anselin 2004), model 2 allows for heteroskedasticity among units.
0.000 (***) Observation 418 418 418 Model Fit(F-stat) 24.14 10.05 (0.000) (***) (0.000) (***) Multicollinearity 1.24 1.24 1.24 (mean VIF) Heteroskedasticit - - 6.900 y (0.000) (***) ([chi square]-Stat) Serial Correlation - - 11.696 (F-Stat) (0.000) (***) OLS with Hetero & Serial Correlation Constant 1.02 (0.317) INVP 2.60 (0.014 (**)) FINP -5.88 (0.000) (***) LCCC -2.08 (0.045) (**) LEV -1.99 (0.056) (*) LIQ 0.35 (0.731) SIZE 0.47 (0.644) BP- LM Test - Hausman Test - Observation 418 Model Fit(F-stat) 43.73 (0.000) (***) Multicollinearity 1.24 (mean VIF) Heteroskedasticit - y ([chi square]-Stat) Serial Correlation - (F-Stat) (1) Figure in the parentheses are t-statistics, except for Bruech-pagan LM test, hausman test, heteroskedasticity and serial correlation test , which are p-values.
Finally, the White (No Cross Terms) test for heteroskedasticity in the model will be conducted.
Heteroskedasticity is basically the violation of one of the assumptions of the regression model that variance of the model is iid i.e.
We combine ordinary least square estimation as the first step, and generalized methods of moments as a second step, to guarantee that estimators are robust to serial correlation and heteroskedasticity. Our main finding is that neither R&D expenditures, nor higher education sector expenditures contribute to reduced inflation differentials within the Eurozone.
(2) with standard errors corrected for heteroskedasticity and autocorrelation using the Newey-West (1987) covariance matrix.
Volatility modeling of financial time series data was pioneered by Engle (1982) who developed Autoregressive Conditional Heteroskedasticity (ARCH) models.