This is particularly problematic in an ordered probit model where, in contrast to linear models, the existence of a heteroscedastic
disturbance causes both the estimated standard errors and the parameter estimates themselves to be inconsistent (for a discussion see Greene 1997, pp.
Standard errors of all regressions in this paper were obtained by using the Newey and West (1987) procedure to correct for both heteroscedastic
and serial correlated error terms.
By construction, this model allows for two sources of forecast error: error in predicting the value of the coefficients and the heteroscedastic
The regression models are adjusted for the presence of heteroscedasity using White's (1980) heteroscedastic
consistent variance-covariance matrix.
Sources of Monetary Growth Uncertainty and Economic Activity: The Time-Varying-parameter Model with Heteroscedastic
However, this method tends to underestimate standard errors for data sets with heteroscedastic
error distributions (Rogers 1992).
3A) allows the application of normal statistics to heteroscedastic
Since the data is cross-sectional and may involve the heteroscedasticity problem, because high-income households show a much greater variability in their consumption behaviour than do low-income households, the Goldfeld-Quandt test Goldfeld-Quandt (1972) was carried out, assuming that the heteroscedastic
Multiple range tests for correlated and heteroscedastic
To account for variations in unobserved effects of variables on injury severity among observations, Heteroscedastic
Ordered Logit (HOL) models were developed for identifying the association between injury severity and explanatory variables.
cointegration approach was employed using a Johansen test of cointegration, OLS and GARCH (1, 1) model to find out the long-term relationship between the selected macroeconomic variables and the stock prices.
Estimation of tail-related risk measures for heteroscedastic
financial time series: an extreme value approach.