Robert Rich (Federal Reserve Bank of New York) Jason Bram (Federal Reserve Bank of New York) Andrew Haughwout (Federal Reserve Bank of New York) James Orr (Federal Reserve Bank of New York) Rae Rosen (Federal Reserve Bank of New York) Rebecca Sela (Leonard K. Stern School of Business, New York University)
Additional information is available for the following
registered author(s):
This paper evaluates the use of measures of regional economic activity to forecast tax revenues for New York State and New York City at 3-, 6-, and 12-month horizons. We construct sales- and withholding-tax base series and then apply the methodology of Stock and Watson (1989, 1991) to estimate regional indexes of coincident economic indicators. Employing an out-of-sample forecasting framework, we find that the use of the coincident indexes leads to statistically and economically significant improvements in tax base forecasts compared to those generated from univariate autoregressions. In addition, the coincident indexes produce forecasts that are generally more accurate than forecasts that rely on the use of the coincident indicators separately. Though our analysis focuses on forecasting movements in tax revenue at the state or local level, it is also intended to draw attention to the value the indexes may provide in other applications. Copyright (c) 2005 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.