We find that covariance matrix forecasts for an international interest rate portfolio generated by a model that incorporates interest-rate level volatility effects perform best with respect to statistical loss functions. However, within a value-at-risk (VaR) framework, the relative performance of the covariance matrix forecasts depends greatly on the VaR distributional assumption. Simple foreca...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

The Journal of Economic Literature codes classification system (JEL) published by the American Association (AEA) is de facto standard for research literature in economics. JEL used to classify articles, dissertations, books, book reviews, and working papers EconLit, a database maintained AEA. Over time, it has evolved extended with over 850 subclasses. This paper reviews history development sys...

A positive technology shock may lead to a rise or a fall in per capita hours, depending on how hours enter the empirical VAR model. We provide evidence that, independent of how hours enter the VAR, a positive technology shock leads to a weak response in nominal wage inflation, a modest decline in price inflation, and a modest rise in the real wage in the short-run and a permanent rise in the lo...

Recent time series methods are applied to the problem of forecasting New Zealand’s real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz (1978) BIC and the Phillips-Ploberger (1996) PIC criteria. The forecasts generated by the data-deter...

We offer a framework to analyze Value-at-Risk based regulation rules and their possible distortion effects on financial markets. Our model is formulated in a continuous-time economy where investors maximize expected utility subject to some regulatory Value-at-Risk constraint when asset price dynamics are not lognormal and exhibit stochastic volatility. To retain tractability of the optimization...

This paper compares the out-of-sample forecasting accuracy of five classes of time series models for market shares of the six most important Portuguese car market competitors over different horizons. As representative time series models I employ a random walk with drift (Naive), a univariate ARIMA, a near-VAR and a general BVAR. The out-of-sample forecasts are also compared against forecasts ge...

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes Factor, which is obtained without any additional computational effort, can be used to assess the plausibility of the restrictions imposed on the VAR parameter vector by competing DSGE models. In other words, it is possible to rank the amount of abstraction implied by each DSGE mode...

This Paper examines the causality and long-run relationships between economic growth and Tourism development in developing countries using P-VAR approach during 1995-2009. The findings reveal that there is a bilateral causality and positive long-run relationship between economic growth and Tourism development. In the other words, the tourism-led growth hypothesis is confirmed, as well as, outpu...