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...

The “hollowing-out,” or “two poles” hypothesis is tested in the context of a Markov chain model of exchange rate transitions. In particular, two versions of the hypothesis—that hard pegs are an absorbing state, or that fixes and floats form a closed set, with no transitions to...

This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it...

External demand was the main driver of growth in Thailand in 2006 and 2007. However, WEO projections indicate moderating foreign demand in 2008, with U.S. growth being revised downwards to reflect the turmoil in housing and credit markets, and high oil prices. While the share of Thai exports to...

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative...

To estimate the New Keynesian model, we use four key macroeconomic series for Thailand. The priors are chosen to reflect general considerations of the appropriate model dynamics and our judgment about the Thai economy. The model is solved initially so that the baseline forecast replicates staff...

The paper constructs a new output gap measure for Vietnam by applying Bayesian methods to a two-equation AS-AD model, while treating the output gap as an unobservable series to be estimated together with other parameters. Model coefficients are easily interpretable, and the output gap series is...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...

This paper develops a small open economy model where entrepreneurs partially finance investment using foreign currency denominated debt subject to a risk premium above and beyond international interest rates. We use Bayesian estimation techniques to evaluate the importance of balance sheet...

This paper investigates the generalized parametric measurement methods of aggregate operational risk in compliance with the regulatory capital standards for operational risk in the New Basel Capital Accord ("Basel II"). Operational risk is commonly defined as the risk of loss resulting from...