The paper proposes an algorithm that uses forecast encompassing tests for combining forecasts. The algorithm excludes a forecast from the combination if it is encompassed by another forecast. To assess the usefulness of this approach, an extensive empirical analysis is undertaken using a U.S....

This paper applies the maximum likelihood panel cointegration method of Larsson and Lyhagen (2007) to test the strong PPP hypothesis using data for the G7 countries. This method is robust in several important dimensions relative to previous methods, including the well-known issue of...

The paper suggests an econometric methodology for testing the effectiveness of reforms implemented in one major step, i.e., discrete reforms. The methodology is based on the exogeneity properties of variables in an econometric model. The paper specifies the preconditions for setting up an...

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...

This paper examines some recent techniques designed to draw inferences about the credibility of changes in macroeconomic policy regimes. An alternative two-step approach, based on the decomposition between permanent and transitory components of a "credibility variable" is proposed. The...

This paper applies a simple probabilistic approach to debt sustainability analysis to the case of Lebanon. The paper derives ""fan charts"" to depict the probability distribution of the government debt to GDP ratio under a medium-term adjustment scenario, as a result of shocks to GDP growth and...

This paper presents and estimates a small open economy dynamic stochastic general-equilibrium model (DSGE) for the Jordanian economy. The model features nominal and real rigidities, imperfect competition and habit formation in the consumer’s utility function. Oil imports are explicitly modeled...

Using monthly data for a set of variables, we examine the out-of-sample performance of various variance/covariance models and find that no model has consistently outperformed the others. We also show that it is possible to increase the probability mass toward the tails and to match reasonably...

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...

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...