Showing 1 - 6 of 6
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010877668
panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error … heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random …
Persistent link: https://www.econbiz.de/10010877693
unknown heteroskedasticity in the innovations. We first generalize the generalized moments (GM) estimator suggested in …
Persistent link: https://www.econbiz.de/10005766296
For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis this transformation is often considered to stabilize the variance of a series. We investigate under which conditions taking logs is beneficial for forecasting. Forecasts based on the...
Persistent link: https://www.econbiz.de/10005051585
This paper generalizes the approach to estimating a first-order spatial autoregressive model with spatial autoregressive disturbances (SARAR(1,1)) in a cross-section with heteroskedastic innovations by Kelejian and Prucha (2008) to the case of spatial autoregressive models with spatial...
Persistent link: https://www.econbiz.de/10005406007
) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation …
Persistent link: https://www.econbiz.de/10011122680