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What It Takes to Solve the U.S. Government Deficit Problem

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Abstract

This paper uses a structural multi-country macroeconometric model to estimate the size of the decrease in transfer payments (or tax expenditures) needed to stabilize the U.S. government debt/GDP ratio. It takes into account endogenous effects of changes in fiscal policy on the economy and in turn the effect of changes in the economy on the deficit. A base run is first obtained for the 2013:1-2022:4 period in which there are no major changes in U.S. fiscal policy. This results in an ever increasing debt/GDP ratio. Then transfer payments are decreased by an amount sufficient to stabilize the long-run debt/GDP ratio. The results show that transfer payments need to be decreased by 2 percent of GDP from the base run, which over the ten years is $3.2 trillion in 2005 dollars and $4.8 trillion in current dollars. The output loss is 1.1 percent of baseline GDP. Monetary policy helps keep the loss down, but it is not powerful enough in the model to eliminate all of the loss. The estimates are robust to a base run with less inflation and to one with less expansion.

Suggested Citation

  • Ray C. Fair, 2011. "What It Takes to Solve the U.S. Government Deficit Problem," Cowles Foundation Discussion Papers 1807, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
  • Handle: RePEc:cwl:cwldpp:1807
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    File URL: http://cowles.yale.edu/sites/default/files/files/pub/d18/d1807.pdf
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    1. Fair, Ray C, 2005. "Estimates of the Effectiveness of Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(4), pages 645-660, August.
    2. Rudolph G Penner, 2011. "Will It Take a Crisis to Fix Fiscal Policy?," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 46(2), pages 62-70, April.
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    More about this item

    Keywords

    Federal deficit; Debt/GDP ratio;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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