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This chapter is concerned with numerical simulation of dynamic economic models. We focus on some basic algorithms and assess their accuracy and stability properties. This analysis is useful for an optimal implementation and testing of these procedures, as well as to evaluate their performance....
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In a variety of engineering, scientific challenges, mathematics, chemistry, physics, biology, machine learning, deep learning, regression classification, computer science, programming, artificial intelligence, in the military, medical and engineering industries, robotics and smart cars, fuzzy...
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We present a fast and accurate computational method for solving and estimating a class of dynamic programming models with discrete and continuous choice variables. The solution method we develop for structural estimation extends the en- dogenous grid-point method (EGM) to discrete-continuous...
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We consider the optimal strategy of R&D expenditure adopted by a firm that engages in R&D to develop an innovative product to be launched in the market. The firm faces with technological uncertainty associated with the success of the R&D effort and market uncertainty of the stochastic revenue...
Persistent link: https://www.econbiz.de/10014175825
In this paper we propose an algorithm for the solution of optimalcontrol problems with nonlinear models based on a generalised Gauss-Newton algorithm but making use of analytic model derivatives. Themethod is implemented in WinSolve, a general nonlinear model solution program
Persistent link: https://www.econbiz.de/10014079740
We derive an algorithm in the spirit of Rogers and Davis & Burstein that leads to upper bounds for stochastic control problems. Our bounds complement lower biased estimates recently obtained in Guyon & Henry-Labordère. We evaluate our estimates in numerical examples motivated from mathematical...
Persistent link: https://www.econbiz.de/10013023827
Generalising the idea of the classical EM algorithm that is widely used for computing maximum likelihood estimates, we propose an EM-Control (EM-C) algorithm for solving multi-period finite time horizon stochastic control problems. The new algorithm sequentially updates the control policies in...
Persistent link: https://www.econbiz.de/10012979815