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150128 ||| eng |
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|a 9781455261369
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100 |
1 |
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|a Kawakami, Kei
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245 |
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|a Identifying Fiscal Policy Transmission in Stochastic Debt Forecasts
|c Kei Kawakami, Rafael Romeu
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260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2011
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300 |
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|a 35 pages
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651 |
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4 |
|a United States
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653 |
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|a Fiscal stance
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653 |
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|a Interest rates
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653 |
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|a Finance
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653 |
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|a Output gap
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653 |
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|a Financial services
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653 |
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|a Real interest rates
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653 |
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|a National Deficit Surplus
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653 |
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|a Debt Management
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653 |
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|a Fiscal Policy
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653 |
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|a Production
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653 |
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|a Debt
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653 |
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|a Fiscal policy
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653 |
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|a Simulation Methods
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653 |
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|a Sovereign Debt
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653 |
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|a Macroeconomics: Production
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653 |
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|a Banks and Banking
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653 |
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|a Macroeconomics
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653 |
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|a Interest Rates: Determination, Term Structure, and Effects
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653 |
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|a Economic theory
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653 |
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|a Public Finance
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653 |
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|a Production growth
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653 |
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|a Production and Operations Management
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700 |
1 |
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|a Romeu, Rafael
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041 |
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7 |
|a eng
|2 ISO 639-2
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989 |
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|b IMF
|a International Monetary Fund
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|a IMF Working Papers
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028 |
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|a 10.5089/9781455261369.001
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856 |
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|u https://elibrary.imf.org/view/journals/001/2011/107/001.2011.issue-107-en.xml?cid=24835-com-dsp-marc
|x Verlag
|3 Volltext
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|a 330
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|a A stochastic debt forecasting framework is presented where projected debt distributions reflect both the joint realization of the fiscal policy reaction to contemporaneous stochastic macroeconomic projections, and also the second-round effects of fiscal policy on macroeconomic projections. The forecasting framework thus reflects the impact of the primary balance on the forecast of macro aggregates. Previously-developed forecasting algorithms that do not incorporate these second-round effects are shown to have systematic forecast errors. Evidence suggests that the second-round effects have statistically and economically significant impacts on the direction and dispersion of the debt-to-GDP forecasts. For example, a positive structural primary balance shock lowers the domestic real interest rate, in turn raising GDP and lowering the median debt-to-GDP projection by an additional 10 percent of GDP in the medium term relative to prior forecasting algorithms. In addition, the framework employs a new long-term (five decade) data base and accounts for parameter uncertainty, and for potentially non-normally distributed shocks
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