The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process,...

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process,...

Interest rate data are an important element of macroeconomic forecasting. Projections of future interest rates are not only an important product themselves, but also typically matter for forecasting other macroeconomic and financial variables. A popular class of forecasting models is linear...

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across...

In this chapter we provide a guide for the construction, use and evaluation of leading indicators, and an assessment of the most relevant recent developments in this field of economic forecasting. To begin with, we analyze the problem of indicator selection, choice of filtering methods, business...

Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine...

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier...

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier...