We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the...

We construct a framework for measuring economic activity in real time (e.g., minute-by-minute), using a variety of stock and flow data observed at mixed frequencies. Specifically, we propose a dynamic factor model that permits exact filtering, and we explore the efficacy of our methods both in a...

We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against...

In recent years, factor models have received increasing attention from both econometricians and practitioners in the forecasting of macroeconomic variables. In this context, Bai and Ng (2008) find an improvement in selecting indicators according to the forecast variable prior to factor...

This paper merges two specifications developed recently in the forecasting literature: the MS-MIDAS model introduced by Gu´erin and Marcellino [2011] and the MIDAS-factor model considered in Marcellino and Schumacher [2010]. The MS-factor MIDAS model (MS-FaMIDAS) that we introduce incorporates...

We present a comprehensive disaggregate approach for short-term forecasting economic activity in Germany by explicitly taking into account the supply or production side and the demand side of GDP. The GDP figures calculated by the two sides usually yield different results and the official GDP...

An updated version of our Markov-switching model of U.S. real GDP clearly suggests the COVID-19 recession was more U shaped than L shaped. As with linear time series models, it is important to account for extreme outliers during the pandemic, but a simple decay function for volatility from...

This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...

We present a comprehensive disaggregate approach for short-term forecasting economic activity in Germany by explicitly taking into account the supply or production side and the demand side of GDP. The GDP figures calculated by the two sides usually yield different results and the official GDP...

We study the role of sentiment variables as predictors for US recessions. We combine sentiment variables with either classical recession predictors or common factors based on a large panel of macroeconomic and financial variables. Sentiment variables hold vast predictive power for US recessions...