This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the...

A well known property of the Beveridge Nelson decomposition is that the innovations in the permanent and transitory components are perfectly correlated. We use a single source of error state space model to exploit this property and perform a Beveridge Nelson decomposition. The single source of...

This paper presents a new approximation to the exact sampling distribution of the instrumental variables estimator in simultaneous equations models. It differs from many of the approximations currently available, Edgeworth expansions for example, in that it is specifically designed to work well...

This paper tests for long memory in the volatility of the All Ordinaries Index and its Share Price Index (SPI) futures. This has important implications for those agents concerned with the long term volatility in these markets. We use daily data and a short span of high frequency data to estimate...

We provide Markov chain Monte Carlo (MCMC) algorithms for computing the bandwidth matrix for multivariate kernel density estimation. Our approach is based on treating the elements of the bandwidth matrix as parameters to be estimated, which we do by optimizing the likelihood cross-validation...

If people in conflicts can more accurately forecast how others will respond, that should help them to make better decisions. Contrary to expert expectations, earlier research found game theorists' forecasts were less accurate than forecasts from simulated interactions using student role players....

This paper extends the family of smooth transition autoregressive (STAR) models by proposing a specification in which the autoregressive parameters follow random walks. The random walks in the parameters can capture structural change within a regime switching framework, but in contrast to the...

This paper investigates whether the risk-return relation varies, depending on changing market volatility and up/down market conditions. Three market regimes based on the level of conditional volatility of market returns are specified - 'low', 'neutral' and 'high'. The market model is extended to...

This paper considers the relationship between growth in real per capita GDP and the growth in real per capita GDP of the poorest 20% of a country. It uses the data set compiled by Dollar and Kraay (2002), but come to very different conclusions. We argue that if the purpose is to answer questions...

This article compares the performance of bivariate error correction GARCH and FIGARCH models when estimating long term dynamic minimum variance hedge ratios (MVHRs) on the Australian All Ordinaries Index. The paper therefore introduces the bivariate error correction FIGARCH model into the...