Real-Time Measurement of Business Conditions

By Borağan Aruoba, Francis X. Diebold, Chiara Scotti. 2007

861 citations recorded by the source corpus.

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 framework in a prototype empirical example and a simulation study calibrated to the example.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/eaf062a5424cb4dad5f35efb1c64e3e8b8ed5737

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In Economics and Econometrics

Citations in the corpus

Diagnosing the Financial System: Financial Conditions and Financial Stress (2012, methodology): “…financial conditions indexes in the literature, however, the NFCI uses a very flexible estimation procedure for these weights that builds off the work of Stock and Watson (2002), Doz, Giannone, and Reichlin (2006), and Aruoba, Diebold, and Scotti (2009) and is described in detail in the appendix.”
Googling Investor Sentiment around the World (2019, positive): “We further include a variable to measure U.S. macroeconomic activities (ECONOMYUS), which is constructed by Aruoba, Diebold, and Scotti (2009).”
Real-Time Forecasting With a Mixed-Frequency VAR (2015, neutral): “The quarterly variable ỹq,t+3h was defined as average of unobserved monthly variables in (4) and corresponds to log GDP.”
Surprise and Uncertainty Indexes: Real-Time Aggregation of Real-Activity Macro Surprises (2016, methodology): “to the Aruoba et al. (2009) business condition index updated on a daily basis by the Federal Reserve Bank of Philadelphia. While the ADS index is a real time measurement of the state of the economy, the surprise index presented in this paper measures agents’ optimism or pessimism about the economy b”
Introducing the Euro-STING: Short Term INdicator of Euro Area Growth (2010, neutral): “INTERNATIONAL MACROECONOMICS ISSN 0265-8003”
DYNAMIC FACTOR MODELS (2018, methodology): “In a closely related application to U.S. data, Aruoba, Diebold, and Scotti (2009) implement a DFM with a single dynamic factor and a weekly variable, four monthly variables, and a quarterly variable to produce an index of economic activity that can be updated weekly.”
Now-Casting and the Real-time Data Flow (2013, positive): “…holds: zkt = zt , t = k, 2k, ... , while for the flow variables, most notably GDP, we have: zkt = k−1∑ i=0 zt−i , t = k, 2k, ... , 1For example, the model of Aruoba, Diebold, and Scotti (2009) in the current version is specified at daily frequency but the highest frequency of the data is weekly.”
Forecasting with Mixed Frequencies (2010, background): “For example, Clements and Galvão (2008) introduced a common factor to the MIDAS model with an autoregressive (AR) component.”
Macroeconomics and the Reality of Mixed Frequency Data (2016, background): “…Harvey and Pierse (1984), Bernanke et al. (1997), Zadrozny (1990), Mariano and Murasawa (2003), Mittnik and Zadrozny (2004), and more recently Aruoba et al. (2009), Ghysels and Wright (2009), Kuzin et al. (2009), Marcellino and Schumacher (2010), Foroni and Marcellino (2014) and Schorfheide…”
Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics (2016, methodology): “Aruoba et al. (2009) developed a weekly index using mixed-frequency data (weekly, monthly, and quarterly), and the resulting “ADS” index is released in real time by the Federal Reserve Bank of Philadelphia.”
Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions (2010, positive): “We have described real activity monitoring in Aruoba et al. (2009), and we have provided enhancements in Aruoba and Diebold (2009). Indeed the so-called ADS Index is now maintained by the Federal Reserve Bank of Philadelphia, updated in real time and written to the web whenever new data, or revision”