This study investigates the application of Factor-Augmented Vector Autoregression (FAVAR) and Bayesian Vector Autoregression (BVAR) models for inflation forecasting. FAVAR models deal with high-dimensional data by extracting latent factors from extensive macroeconomic indicators, while BVAR...

This paper addresses the challenge of inflation forecasting by adopting a thick modeling approach that integrates forecasts from time- and frequency-domain models. Frequency-domain models excel at capturing long-term trends while also accounting for short-term fluctuations. Combining these...

At the request of the Banco Nacional de Angola (BNA), a technical assistance (TA) mission from the Monetary and Capital Markets (MCM) Department visited Luanda, Angola from May 20 to May 24, 2024. The mission helped the authorities review its forecasting and policy analysis system (FPAS),...

Using a large cross-country dataset covering over 150 countries and more than 10 macroeconomic variables, this study examines the consistency of IMF World Economic Outlook (WEO) forecasts with the full information rational expectations (FIRE) hypothesis. Similar to Consensus Economics forecasts,...

This paper presents a novel 5-factor model for agricultural commodity risk premiums, an approach not explored in previous research. The model is applied to the specific cases of corn, soybeans, and wheat. Calibration is achieved using a Kalman filter and maximum likelihood, with data from...