heteroscedasticity

(redirected from Heteroskedasticity)
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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 ?
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.
According to Christie (1987), earnings and stock returns, measured per share, are standardized by beginning-of-fiscal-year stock price to control heteroskedasticity.
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.
4) Because of apparent heteroskedasticity for payments >25000 DKK this interval was excluded.
Table 4 shows the results of diagnostic tests including Breusch-Godfrey Serial Correlation LM Test, heteroskedasticity Test of Breusch-Pagan-Godfrey, Jarque-Bera Test of normality, and Ramsey RESET Test.
Further Breusch-Pagan-Godfrey's Heteroskedasticity Test (table 8) indicates that this model does not have Heteroskedasticity problem.
For estimation purposes, since money market interest rates display periods of volatility and periods of calm, this suggests the use of well-known generalized autoregressive conditional heteroskedasticity (GARCH) model [see Engle (1982) and Bollerslev (1986) for the seminal contribution].
For this reason, we should implement the Poisson model corrected for heteroskedasticity, as in Aldieri (2011), however, from the summary statistics table, there is first a significant proportion of zeros, the right tail of the distribution is very long.
Diagnostic tests for normality, serial correlation, heteroskedasticity and model specification are applied.
In the figures we can see that the series might present some stylized facts of financial series such as volatility clusters and heteroskedasticity.
274) pointed out, "while heteroskedasticity in Sit is always a potential problem [in the FE model], serial correlation is likely to be more important in certain applications" if t [greater than or equal to] 3.