In recent years, Fund staff has prepared cross-country analyses of macroeconomic vulnerabilities in low-income countries, focusing on the risk of sharp declines in economic growth and of debt distress. We discuss routes to broadening this focus by adding several macroeconomic and macrofinancial...

This paper provides a survey of business cycle facts, updated to take account of recent data. Emphasis is given to the Great Recession which was unlike most other post-war recessions in the US in being driven by deleveraging and financial market factors. We document how recessions with financial...

This paper provides a survey of business cycle facts, updated to take account of recent data. Emphasis is given to the Great Recession which was unlike most other post-war recessions in the US in being driven by deleveraging and financial market factors. We document how recessions with financial...

We propose a parsimonious semiparametric method for macroeconomic forecasting during episodes of sudden changes. Based on the notion of clustering and similarity, we partition the time series into blocks, search for the closest blocks to the most recent block of observations, and with the...

Financial crises pose unique challenges for forecast accuracy. Using the IMF's Monitoring of Fund Arrangement (MONA) database, we conduct the most comprehensive evaluation of IMF forecasts to date for countries in times of crises. We examine 29 macroeconomic variables in terms of bias,...

This paper uses several macroeconomic and financial indicators within a Markov Switching (MS) framework to predict the turning points of the business cycle. The presented model is applied to monthly German real-time data covering the recession and the recovery after the financial crisis. We show...

Financial crises pose unique challenges for forecast accuracy. Using the IMF's Monitoring of Fund Arrangement (MONA) database, we conduct the most comprehensive evaluation of IMF forecasts to date for countries in times of crises. We examine 29 macroeconomic variables in terms of bias,...