Abstract (EN):
We propose a framework to solve dynamic nonlinear infinite-horizon models like those
found in the standard economic growth literature. We employ a direct method to solve the
underlying optimal control problem, something novel in the economic literature. Instead of
deriving the necessary optimality conditions and solving the originated ordinary differential
equations, this method first discretizes and then optimizes, in effect transforming the problem
into a nonlinear programming problem to be optimized at each sampling instant. We
incorporate the work of Fontes (2001) in order to transform the infinite-horizon problem into
an equivalent finite-horizon representation of the model. This framework presents several
advantages in comparison to the available alternatives that use indirect methods. First, no
linearization is required, which sometimes can be erroneous. The problem can be studied
in its nonlinear form. Secondly, it enables the simulation of a shock when the economy is
not at its steady state, a broad assumption required by all available numerical methods.
Thirdly, it allows for the easy study of anticipated shocks. It also allows for the analysis of
multiple, sequential shocks. Finally, it is extremely robust and easy to use. We illustrate the
application of the framework by solving the standard Ramsey-Cass-Koopsman exogenous
growth model and the Uzawa-Lucas endogenous two-sector growth model.
Language:
English
Type (Professor's evaluation):
Scientific
Notes:
Disponível em http://wps.fep.up.pt/wps/wp506.pdf
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