In a recent paper, Bai and Perron (2006) demonstrate that their approach for testing for multiple structural breaks in time series works well in large samples, but they found substantial deviations in both the size and power of their tests in smaller samples. We propose modifying their...

Extending previous work on the determinants of IMF lending in an interconnected world, we introduce a model of sample selection in which both selection and size dimensions of individual IMF arrangements are presented within a unified econometric framework. We allow for unobserved heterogeneity...

This paper quantifies the savings obtained from risk pooling with a Regional Stabilization Fund (RSF) for the Eastern Caribbean Currency Union. A Monte Carlo experiment is used to estimate the size of a RSF conditional on probabilities of depletion under specific saving-withdrawal rules. Results...

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...

Following a brief review of the recent history of GDP-linked instruments, this paper proposes a set of tools to examine the quantitative properties of GDP-linked warrants. It argues that trigger conditions should be clearly identifiable and payment amounts easily calculable. Based on a design...

Fiscal rules are being increasingly used by both emerging and developed economies. This paper analyzes two alternative fiscal policy rules in terms of their impact on debt sustainability: a rule that fixes the ratio of primary surplus to GDP (""fixed surplus rule"") and one that sets the primary...

This paper estimates a New Keynesian DSGE model with an explicit financial intermediary sector. Having measures of financial stress, such as the spread between lending and borrowing, enables the model to capture the impact of the financial crisis in a more direct and efficient way. The model...

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...

This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior....

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...