This paper investigates some finite-sample issues that arise in the analysis of Markovswitching autoregressive models with time-varying probabilities. An extensive simulation study is undertaken to examine the small-sample properties of the maximum likelihood estimator and related statistics,...

We investigate regime-dependent Granger causality between real output, inflation and monetary indicators and map with U.S. Fed Chairperson's tenure since 1965. While all monetary indicators have causal predictive content in certain time periods, we report that the Federal Funds rate (FFR) and...

This paper studies the properties of the sieve bootstrap for a class of linear processes which exhibit strong dependence. The sieve bootstrap scheme is based on residual resampling from autoregressive approximations the order of which increases slowly with the sample size. The first-order...

This paper considers the problem of statistical inference in linear regression models whose stochastic regressors and errors may exhibit long-range dependence. A time-domain sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the...

This paper explores the interactions between cross-sectional aggregation and persistence of volatility shocks. We derive the ARMA-GARCH representation that linear aggregates of ARMA processes with GARCH errors admit, and establish conditions under which persistence in volatility of the aggregate...

This paper derives the autocorrelation function of the squared values of long-memory GARCH processes. The latter are of much interest since they can produce the long-memory conditional heteroscedasticity that many high-frequency financial time series exhibit. An empirical application...

This paper considers the issue of testing for symmetry of the business cycle. It is demonstrated that findings of symmetry should be interpreted with caution since tests tend to have low power to detect asymmetries when applied to data that have been filtered to isolate their stationary...

In this paper we propose a contemporaneous threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the...

This paper proposes a contemporaneous-threshold smooth transition GARCH (or CSTGARCH) model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization to second conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al....

In this paper we examine the properties of several cointegration tests when long run parameters are subject to multiple shifts, resorting to Monte Carlo methods. We assume that the changes in cointegration regimes are governed by a unobserved Markov chain process. This specification has the...