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Principal Investigator(s): Armesto, Michelle T., Federal Reserve Bank of St. Louis; Engemann, Kristie M., Federal Reserve Bank of St. Louis; Owyang, Michael T., Federal Reserve Bank of St. Louis
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.
These data are flagged as replication datasets and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.
These data are freely available.
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. doi:10.3886/ICPSR34712.v1
Persistent URL: http://doi.org/10.3886/ICPSR34712.v1
Scope of Study
Data Collection Notes:
The data are distributed as a Microsoft Excel file, which provides data, tables, and figures used in the publication.
These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigators if further information is desired.
Original ICPSR Release: 2013-06-20
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