Two Ways of Estimating a Transport Model

In this article, it is shown how the parameters of a transport model can be estimated in a way that, in contrast to previously used methods, utilizes observations of regional prices as well as of trade costs. The proposed method uses bi-level programming to minimize a weighted least squares' criterion under the restriction that the estimated parameters satisfy the Kuhn-Tucker conditions for an optimal solution of the transport model. We use Monte-Carlo simulations to trace out some properties of the estimator and compare it with a traditional calibration method. The analysis shows that the proposed technique estimates prices as well as trade costs more efficiently.

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Working or Discussion Paper
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JEL Codes:
C15; F11
Series Statement:
Discussion Paper 2005: 1

 Record created 2017-04-01, last modified 2019-08-26

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