Since the underlying of the weather derivatives is not a traded asset, these contracts cannot be evaluated by the traditional financial theory. Cao and Wei (2004) price them by using the consumption-based asset pricing model of Lucas (1978) and by assuming different values for the constant relative risk aversion coefficient. Instead of taking this coefficient as given, we suggest in this paper to estimate it by using the consumption data and the quotations of one of the most transacted weather contracts which is the New York weather futures on the Chicago Mercantile Exchange (CME). We apply the well-known generalized method of moments (GMM) introduced by Hansen (1982) to estimate it as well as the simulated method of moments (SMM) attributed to Lee and Ingram (1991) and Duffie and Singleton (1993). This last method is studied since it is presumed to give satisfactory results in the case of the weather derivatives for which the prices are simulated. We find that the estimated coefficient from the SMM approach must have improbably high values in order to have the calculated weather futures prices matching the observations.