heteroscedasticity

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Related to Heteroskedastic: Homoscedastic

het·er·o·sced·as·tic·i·ty

(het'ĕr-ō-skĕd'as-tis'ĭ-tē),
Nonconstancy of the variance of a measure over the levels of the factor under study.
[hetero + G. skedastikos, pertaining to scattering, fr. skedannumi, to scatter]

heteroscedasticity

an irregular scattering of values in a series of distributions; accompanied by a comparable scatter of variances.
References in periodicals archive ?
The results of the likelihood ratio test indicate the presence of heteroskedastic errors across panels (chi(2) = 13.
A conditionally heteroskedastic time series model for speculative prices and rates of return.
09 statistics Wald test heteroskedastic heteroskedastic Third Model Coefficient Prob.
It may provide robust estimates since it does not make strong assumptions concerning the disturbance term, and the disturbance term can be both serially dependent and conditionally heteroskedastic.
002 Test items Remarks (1) Comparing FE is better than models: FE vs pooled model pooled (2) Comparing RE is better than FE models: FE vs RE (3) Testing for No cross-sectional cross-sectional dependence dependence or contemporaneous correlation (4) Testing for Serial correlation serial correlation in disturbance terms: Yes in FE, but not in RE (5) Testing for Heteroskedastic heteroskedasticity TABLE 3 Estimation results for the forest area and carbon stock models Variables Estimates t-values p-values Forest area (in ha) model: Intercept 919 170 8.
Silva and Tenreyro (2006) propose a Poisson pseudo-maximum-likelihood estimator, PPML henceforth, which allows keeping the zero observations; this estimator is robust under heteroskedastic error terms.
Next, instrumental variables are needed to account for the endogeneity of entrepreneurship, after which a two-stage OLS estimation method will provide consistent estimators (even though a robust estimation is recommended because of the existence of an important heteroskedastic factor caused by the use of sample averages as observations).
Further relaxing the PCA restrictions on the idiosyncratic error structure of the data has a more pronounced effect; this is apparent in the difference between the CFNAI and the dynamic-factor-based index with heteroskedastic errors (labeled DF-HC in panel B of figure 2) and between the CFNAI and the dynamic factor-based index with heteroskedastic and serially correlated errors (labeled DF-HAC in panel C).
04 Spain*Clay Likelihood Ratio -- 1114 -- Notes: p-values based on White heteroskedastic standard errors.
Given the complexity in the heteroskedastic variance of the model error in our application, the specification of the prior information on the structure of the model error is extremely difficult.
This table reports results from estimation of equation 1, 2 and 3 by random effects generalized least squares using heteroskedastic structure.