Green shoots and double dips in the euro area: A real time measure

Abstract

To perform real-time business cycle inferences and forecasts of GDP growth rates in the euro area, we use an extension of the Markov-switching dynamic factor models that accounts for the speci…cities of the day to day monitoring of economic developments such as ragged edges, mixed frequencies and data revisions. We provide examples that show the nonlinear nature of the relations between data revisions, point forecasts and forecast uncertainty. According to our empirical results, we think that the realtime probabilities of recession inferred from the model are an appropriate statistic to capture what the press call green shoots and to monitor the double-dip recessions.

Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model

“…The distinction is important because quarterly growth rates of hard indicators generally correlate well with quarter-on-quarter GDP growth (and monthly growth rates of hard indicators correlate with monthly business cycle indicators like industrial production), while business surveys typically rather fit year-on-year GDP growth. We model these differences along the lines of Camacho et al (2014): For the hard indicators we assume a standard factor structure,…”

“…To extract information from leading indicators of the German business cycle, we use the Markov-switching dynamic factor model (MS-DFM) proposed by Diebold and Rudebusch (1996) and Kim and Yoo (1995) because it has been shown to be a valuable device for assessing the state of an economy (Chauvet, 1998;Kim and Nelson, 1998;Camacho et al, 2014) and its results are much more timely available than those of simple benchmark approaches such as the Bry-Boschan algorithm. However, unlike the previous literature we specify the MS-DFM with three states.…”

Business cycle dynamics after the Great Recession

“…In this paper, we consider small-scale Markov-Switching Dynamic Factor Models (MS-DFMs) as our starting point. These models, whose dynamics depends on whether the economy is in expansion or recession, are increasingly used for short-term forecasting and turning point detection (Chauvet and Potter 2013, Camacho et al 2014. They have been introduced by Diebold and Rudebusch (1996) to simultaneously account for comovement in macroeconomic time series and different dynamics during expansion and recession phases, two business cycle facts that were originally identified by Burns and Mitchell (1946).…”

Forecasting GDP over the Business Cycle in a Multi‐Frequency and Data‐Rich Environment

“…An obvious limitation of the model is its omission of potential switches in the factor representation. It could be relevant to incorporate regime switches in the factor dynamics, as done in Camacho, Perez‐Quiros and Poncela (, ). There could also be a temporal instability in the factor loadings.…”