heteroscedasticity

(redirected from Heteroschedasticity)

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]
References in periodicals archive ?
B., Conditional heteroschedasticity in asset returns: a new approach, Econometrica (59: 1991)
Table 1: Cumulative growth rate and structural adjustments in 25 OECD countries: Cross-section analysis Dependent variable Period Period Cumulative growth of real GDP (CG) 2000-2007 2008-2013 Independent variable Structural adjustment (SA) -1.363 ** -1.505 *** (0.531) (0.387) Constant 23.07 *** 2.452 (1.977) (1.431) Observations 25 25 [R.sup.2] 0.223 0.408 Jarque-Bera (Normality test) 2.627 0.841 [0.268] [0.656] Test for heteroschedasticity Breusch-Pagan 0.819 0.568 Notes: Standard errors in parentheses; p-value in square brackets; *** reject the null at 1%; ** reject the null at 5%; * reject the null at 10%.
FGLS is frequently used to remedy any possible problems from panel heteroschedasticity, contemporaneous correlation, and serial correlation (Hitt et al.
The t-tests assumed heteroschedasticity with an alpha of 0.05.
The freshman number of students was incorporated in the data set as a means of standardizing the data set to offset the possibility of heteroschedasticity skewing the results.
For all three (fixed effects) models, the standard diagnostic test showed residual autocorrelation (Wooldridge test), heteroschedasticity (modified Wald test) and contemporaneous correlation (Breusch Pagan LM test).
Chapter 3 is dedicated to volatility modeling, from the AR Conditional Heteroschedasticity (ARCH) model, introduced with the seminal paper of Engle in 1980, onward.
"A Heteroschedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroschedasticity," Econometrics, 48 1980b, pp.
Both OLS regressions for SMEs and large firms, however, are found to have the problem of heteroschedasticity using the Breusch-Pagan/Godfrey test (Greene, 1997, pp.
Table 3 presents coefficients from panel regressions where standard errors explicitly account for heteroschedasticity and for the possible correlation of errors within country clusters over the different periods.
Because the probability of sample inclusion is related to the dependent variables (military participation and wages), sample weights are included and the standard errors are corrected for heteroschedasticity using the Eiker-White correction (Winship and Radbill, 1994).
The model is adjusted for heteroschedasticity and intra-group correlation at the industry level, checking for intra-sectoral heterogeneity.