Should Macroeconomic Forecasters Use Daily Financial Data and How?
University of Cyprus - Department of Economics
University of North Carolina (UNC) at Chapel Hill - Department of Economics; University of North Carolina Kenan-Flagler Business School
University of Cyprus - Department of Economics; University of Bologna - Rimini Center for Economic Analysis (RCEA)
November 19, 2010
We introduce easy to implement regression-based methods for predicting quarterly real economic activity that use daily financial data. Our analysis is designed to elucidate the value of daily information and provide real-time forecast updates of the current (nowcasting) and future quarters. Our findings show that while on average the predictive ability of all models worsens substantially following the financial crisis, the models we propose suffer relatively less losses. Moreover, these predictive gains are primarily driven by the asset classes of government securities, equities, and especially corporate risk.
Number of Pages in PDF File: 66
Keywords: MIDAS Regressions, Macro Forecasting, Leads, Daily Financial Information, Daily Factors
JEL Classification: C22, C53, G10working papers series
Date posted: November 20, 2010
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