This paper outlines a strategic plan for the development of the fourth generation of Bank of Canada projection and policy analysis models. The plan features a new Canadian workhorse macroeconomic model as well as a suite of alternative models to better support a risk management approach to...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting inflation with the ability of quantile regression to...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting in ation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting in ation with the ability of quantile regression to...

This paper studies the comparative predictive accuracy of forecasting methods using mixed-frequency data, as applied to nowcasting Philippine inflation, real GDP growth, and other related macroeconomic variables. It focuses on variations of mixed-frequency dynamic latent factor models (DFM for...

Inflation did not fall as much as many economists expected as the Great Recession hit the US economy. One explanation suggested for this phenomenon is that the Phillips curve has become flatter. In this paper we investigate the stability of the US Phillips curve, employing Bayesian VARs to...

In this paper we apply economic narratives to inflation forecasting using a large news corpus and machine learning algorithms. We measure economic narratives quantitatively from the full text content of over 880,000 Wall Street Journal articles and represent them as interpretable news topics....

This paper considers inflation forecasting for a vast panel of countries. We combine the information from common factors driving global inflation as well as country-specific inflation in order to build a set of different models. We also rely on new advances in the Machine Learning literature. We...

Using high frequency price information and strengthening market intelligence on high-impact food items for nowcasting is an integral part of the inflation forecasting framework at the Reserve Bank of India. Three key vegetables viz., tomatoes, onions and potatoes (TOP), with a combined weight of...

In this paper, we analyse the sources of time variation in consumer inflation across ten Central and Eastern European (CEE) countries and five sectors (durables, semidurables, non-durables, food, and services) in the period 2001-2013. With a multi-level factor model we decompose product-level...