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Lucas (1976) pointed out, that when optimization is performed on a deterministic macro model, the resulting policy may not reflect the true optimal solution. Private agents may react to announced policies and consequently model parameters will start to drift. The aim of this paper is to develop...
Persistent link: https://www.econbiz.de/10005706353
Persistent link: https://www.econbiz.de/10005706443
Two lines of literature show that increased uncertainty results in decreased vigor of the control variable in the first time period. The first line uses static models, the second dynamic. Here, the dynamic line is extended from one-state, one-control models to ones with two control variables. We...
Persistent link: https://www.econbiz.de/10005706698
I provided an abstract earlier
Persistent link: https://www.econbiz.de/10005132786
Three methods have been developed by the authors for solving optimal experimentation problems. David Kendrick (1981, 2002, Ch.10) uses quadratic approximation of the value function and linear approximation of the equation of motion to simulate general optimal experimentation (active learning)...
Persistent link: https://www.econbiz.de/10005537450
In this paper, we present a method for using rational expectations in a stochastic linear-quadratic optimization framework in which the unknown parameters are updated through a learning scheme. We use the QZ decomposition as suggested by Sims (1996) to solve the rational-expectations part of the...
Persistent link: https://www.econbiz.de/10005537716
\\begin{abstract} Lucas (1976) pointed out, that when optimization is performed on a deterministic macro model, the resulting policy may not reflect the true optimal solution. Private agents may react to announced policies and consequently model parameters will start to drift. The aim of this...
Persistent link: https://www.econbiz.de/10005537760