We are occupied with a simple example concerning the limit theory of the OLSE when the innovation process of the regression has the form of a martingale transform the i.i.d. part of which lies in the domain of attraction of an \alpha-stable distribution, the scalling sequence has a potentially...

We analyze optimality properties of maximum likelihood (ML) and other estimators when the problem does not necessarily fall within the locally asymptotically normal (LAN) class, therefore covering cases that are excluded from conventional LAN theory such as unit root nonstationary time series....

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...

We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes. The new method, denoted as Markov-switching three-pass...

This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analyti-cal knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We...

The dynamic CUSUM test for structural change proposed by Kramer, Ploberger and Alt (1988) is investigated when the errors are serially correlated in a linear dynamic model. We show that the dynamic CUSUM test can be modified to allow for serial correlation in the disturbance using the same...

In econometrical literature, various incomplete-data models have been developed to reflect economic phenomena. For incomplete-data models, it is not easy to construct test statistics because the observed log-likelihood function often involves intractable integrals which make it very difficult to...

Wavelet analysis is a new mathematical tool developed as a unified field of science over the last decade. As spatially adaptive analytic tools, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent/strong dependence, seasonality...

Spatial/Spatiotemporal interdependence - i.e., that the outcomes, actions, or choices of some unit-times depend on those of others - is substantively and theoretically ubiquitous and central in binary outcomes of interest across the social sciences. However, most empirical applications omit...

I estimate a forward-looking, dynamic, discrete-choice monetary policy reaction function for the US economy, that accounts for the fact that there are substantial restrictions in the period-to-period changes of the Fed's policy instrument. I find a substantial contrast between the periods before...