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| Inna Tsener |
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| ''A geometric programming approach to dynamic economic models'' |
| ( 2020, Vol. 40 No.2 ) |
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| Geometric programming (GP) has several attractive features: it is tractable in large-scale problems, requires no initial guess or tuning of solver parameters, guarantees the convergence to a global optimum and can deal with kinks. In this note, I argue that GP is a potentially promising tool in economics. First, I show that a stylized finite-horizon growth model can be mapped into a GP format by using simple transformations. Second, I show that GP methods produce accurate and reliable solutions including the case of occasionally binding constraints which cannot be easily treated with conventional solvers. Examples of MATLAB codes are provided. |
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| Keywords: dynamic optimization, geometric programming, finite horizon, occasionally binding constraints, condensation |
JEL: C6 - Mathematical Methods and Programming: General
D9 - Intertemporal Choice and Growth: General |
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| Manuscript Received : Jan 18 2019 | | Manuscript Accepted : Apr 17 2020 |
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