Forecasting with Mixed Frequencies (ICPSR 34712)

Published: Jun 20, 2013 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Michelle T. Armesto, Federal Reserve Bank of St. Louis; Kristie M. Engemann, Federal Reserve Bank of St. Louis; Michael T. Owyang, Federal Reserve Bank of St. Louis

https://doi.org/10.3886/ICPSR34712.v1

Version V1

A dilemma faced by forecasters is that data are not all sampled at the same frequency. Most macroeconomic data are sampled monthly (e.g., employment) or quarterly (e.g., GDP). Most financial variables (e.g., interest rates and asset prices), on the other hand, are sampled daily or even more frequently. The challenge is how to best use available data. To that end, the authors survey some common methods for dealing with mixed-frequency data.

Armesto, Michelle T., Engemann, Kristie M., and Owyang, Michael T. Forecasting with Mixed Frequencies. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2013-06-20. https://doi.org/10.3886/ICPSR34712.v1

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Inter-university Consortium for Political and Social Research

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2013-06-20

2013-06-20

2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
  • Armesto, Michelle T., Kristie M. Engemann, and Michael T. Owyang. Forecasting with Mixed Frequencies. ICPSR34712-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2013-06-20. http://doi.org/10.3886/ICPSR34712.v1

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