This paper proposes an empirical Bayes approach for Markov switching autoregressions that can constrain some of the state-dependent parameters (regression coefficients and error variances) to be approximately equal across regimes. By flexibly reducing the dimension of the parameter space, this can help to ensure regime separation and to detect the Markov switching nature of the data. The permut...

This paper demonstrates how parsimonious models of sinusoidal functions can be used to fit spatially variant time series in which there is considerable variation of a periodic type. A typical shortcoming of such tools relates to the difficulty in capturing idiosyncratic variation in periodic models. The strategy developed here addresses this deficiency. While previous work has sought to overcom...

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previous...

Empirical tests of the arbitrage pricing theory using measured variables rely on the accuracy of standard inferential theory in approximating the distribution of the estimated risk premiums and factor betas. The techniques employed thus far perform factor selection and model inference sequentially. Recent advances in Bayesian variable selection are adapted to an approximate factor model to inve...

The study of the asymmetric behavior of macroeconomic variables over the business cycles phases has had a long tradition in economics. In this work we find evidence in favor of the hypothesis of having a STAR-type nonlinear asymmetric behavior of the economic activity, over the last two decades, in three Latin American countries: Brazil, Colombia, and Mexico. For Chile and Venezuela the null hy...

This paper contributes to the literature by empirically examining whether the influence of public debt on economic growth differs between the short and the long run and presents different patterns across euro-area countries. To this end, we use annual data from both central and peripheral countries of the European Economic and Monetary Union (EMU) for the 1960-2012 period and estimate a growth ...

In this paper we suggest a number of statistical tests based on neural network models, that are designed to be powerful against structural breaks in otherwise stationary time series processes while allowing for a variety of nonlinear specifications for the dynamic model underlying them. It is clear that in the presence of nonlinearity standard tests of structural breaks for linear models may no...

This article explores the scale and behaviour of abnormal equity returns for 12 regional electricity companies (RECs) in the UK. Using the Capital Asset Pricing Model (CAPM) and the Kalman Filter, we estimate time variation in abnormal returns (alpha) and in systematic risk (beta) coefficients. Substantial time variation in both returns and risk is demonstrated, with strong evidence of regulato...

This paper investigates the determinants of Polish small firm’s intentions to expand production in the context of possible economic expansion on accession to the EU. Using a non-linear specification a model is developed using twenty-seven explanatory variables derived from a questionnaire given to Polish small firms in late 1999 asking about their motivations in expanding production. Seven of t...

Long-run variance estimation can typically be viewed as the problem of estimating the scale of a limiting continuous time Gaussian process on the unit interval. A natural benchmark model is given by a sample that consists of equally spaced observations of this limiting process. The paper analyzes the asymptotic robustness of long-run variance estimators to contaminations of this benchmark model...