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Mr. Kei Kawakami and Rafael Romeu
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.
Mr. Kei Kawakami and Rafael Romeu

I. I ntroduction This study proposes a stochastic debt forecasting framework that identifies and estimates the impact of feedback between fiscal policy and macroeconomic projections – effects which are largely absent from current debt forecasting algorithms. In such algorithms, a distribution of fiscal and debt forecasts is projected by combining simulated macroeconomic scenarios, a fiscal policy reaction function, and a debt motion equation. In the proposed framework, fiscal projections reflect contemporaneous macroeconomic shocks through automatic