A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was...

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...

Emerging markets are more volatile and face different types of shocks, in size and nature, compared to their developed counterparts. Accurate identification of the stochastic properties of shocks is difficult. We show evidence suggesting that uncertainty about the underlying stochastic process...

Previous early-warning systems (EWSs) for currency crises have relied on models that require a priori dating of crises. This paper proposes an alternative EWS, based on a Markov-switching model, which identifies and characterizes crisis periods endogenously; this also allows the model to utilize...

This paper considers the problem of jointly decomposing a set of time series variables into cyclical and trend components, subject to sets of stochastic linear restrictions among these cyclical and trend components. We derive a closed form solution to an ordinary problem featuring homogeneous...

This paper examines the extent to which conclusions of cross-country studies of private savings are robust to allowing for the possible heterogeneity of savings behavior across countries and the inclusion of dynamics. It shows that neglecting heterogeneity and dynamics can lead to misleading...

Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts. Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures....

Should a closed economy open its trade to all countries or limit itself to participation in regional trade agreements (RTAs)? Based on time-series evidence for a data set for 1950-92, this paper estimates and compares the growth performance of countries that liberalized broadly and those that...

This paper identifies turning points for the U.S. business cycle using different time series. The model, a multivariate Markov-Swiching model, assumes that each series is characterized by a mixture of two normal distributions (a high and low mean) with switching determined by a common Markov...

We provide empirical evidence that deviations from uncovered interest rate parity (UIP) display significant nonlinearities, consistent with theories based on transaction costs or limits to speculation. This evidence suggests that the forward bias documented in the literature may be less...