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Dynamic spatial autoregressive models with autoregressive and heteroskedastic...
We propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and... -
The performance of heteroskedasticity and autocorrelation robust tests: a Mon...
This paper illustrates the pitfalls of the conventional heteroskedasticity and autocorrelation robust (HAR) Wald test and the advantages of new HAR tests developed by Kiefer and... -
Codependence in cointegrated autoregressive models (replication data)
This paper investigates codependent cycles, i.e., transitory components that react to common stimuli in a similar, although not necessarily synchronous fashion. Unlike previous... -
Nonlinear autoregressive leading indicator models of output in G-7 countries ...
This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G-7 countries. Our models use the spread between short-term and long-term... -
Censored latent effects autoregression, with an application to US unemploymen...
A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond... -
A Monte Carlo study of the forecasting performance of empirical SETAR models ...
In this paper we investigate the multi-period forecast performance of a number of empirical self-exciting threshold autoregressive (SETAR) models that have been proposed in the...
