Author(s)

Quirino Paris

Department of Agricultural and Resource Economics, University of California, Davis, CA, USA.

The purpose of this paper is to combine the estimation of output price risk and positive mathematical programming (PMP). It reconciles the risk programming presented by Freund with a consistent estimate of the constant absolute risk aversion (CARA) coefficient. It extends the PMP approach to calibration of realized production outputs and observed input prices. The results of this specification include 1) uniqueness of the calibrating solution, 2) elimination of the tautological calibration constraints typical of the original PMP procedure, 3) equivalence between a phase I calibrating solution and a solution obtained by combining phase I and phase II of the traditional PMP procedure. In this extended PMP framework, the cost function specification involves output quantities and input prices—contrary to the myopic cost function of the traditional PMP approach. This extension allows for a phase III calibrating model that replaces the usual linear technology with relations corresponding to Shephard lemma (in the primal constraints) and the marginal cost function (in the dual constraints). An empirical example with a sample of farms producing four crops illustrates the novel procedure.

CARA Coefficient, Chance-Constrained Approach, Positive Mathematical Programming, Solution Uniqueness, Calibrating Model

Paris, Q. (2018) Estimation of CARA Preferences and Positive Mathematical Programming. Open Journal of Statistics, 8, 1-13. doi: 10.4236/ojs.2018.81001.