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Working Paper
A state space forecasting model with fiscal and monetary control
In this paper we model the U.S. economy parsimoniously in an a theoretic state space representation. We use monthly data for thirteen macroeconomic variables. We treat the federal deficit as a proxy for fiscal policy and the fed funds rate as a proxy for monetary policy and use each of them as control (exogenous) variables, and designate the rest as state variables. The output (measured) variable is the growth rate of quarterly real GDP which we interpolate to obtain a monthly equivalent. We specify a linear relation between state variables and implicitly allow for time variation of the ...
Working Paper
Forecasting with an adaptive control algorithm
We construct a parsimonious model of the U.S. macro economy using a state space representation and recursive estimation. At the core of the estimation procedure is a prediction/correction algorithm based on a recursive least squares estimation with exponential forgetting. The algorithm is a Kalman filter-type update method which minimizes the sum of discounted squared errors. This method reduces the contribution of past errors in the estimate of the current period coefficients and thereby adapts to potential time variation of parameters. The root mean square errors of out-of-sample forecast ...
