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...

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....

We analyze the performance of kernel density methods applied to grouped data to estimate poverty (as applied in Sala-i-Martin, 2006, QJE). Using Monte Carlo simulations and household surveys, we find that the technique gives rise to biases in poverty estimates, the sign and magnitude of which...

This paper proposes a new definition of Offshore Financial Centers (OFCs) and develops a statistical method to differentiate between OFCs and non-OFCs using data from the Coordinated Portfolio Investment Survey (CPIS), the International Investment Position (IIP), and the balance of payments. The...

This paper estimates the output gap in Russia using a utilization-adjusted production function approach, which we argue is preferable to traditional output gap methods. The approach amounts to (1) using available surveys to estimate the "natural rates" of capacity and labor utilization above...

The paper developes a VAR macrofinance model of the Czech economy. It shows that yield misalignments from the yields implied by the macrofinance model partially determine subsequent yield changes over three to nine months. These yield misalignments tend to persist for a number of months. This...

Current estimates of global poverty vary substantially across studies. In this paper we undertake a novel sensitivity analysis to highlight the importance of methodological choices in estimating global poverty. We measure global poverty using different data sources, parametric and nonparametric...

This Selected Issues paper analyzes the entrenched inflation in Russia. It presents a possible explanation for the entrenched inflation stating that the Russian economy is facing increasing supply-side constraints in goods and labor markets. The paper focuses on measuring the performance of...

Trade theories covering Preferential Trade Agreements (PTAs) are as diverse as the literature in search of their empirical support. To account for the model uncertainty that surrounds the validity of the competing PTA theories, we introduce Bayesian Model Averaging (BMA) to the PTA literature....