Popper and production: testing parametric restrictions in systems under nonstationarity.

摘要

This study tests symmetry and homogeneity restrictions on a system of factor demand equations for central and western Canadian agriculture under the assumption that the variables are integrated processes and the demands represent cointegrating relationships. It is well known that the distribution of F-statistics derived from ordinary least squares estimates in such systems are not distributed as the ratio of two independent chi2 random variables normalized by their degrees of freedom even asymptotically. Indeed, the use of traditional critical values of F-statistics in such cases will severely underestimate the true critical values and therefore use of traditional critical values would tend to overreject symmetry and homogeneity restrictions. Bootstrapping techniques are employed to generate the true distribution of the F-statistic so that the proper critical values can be compared with the calculated F-statistic on symmetry and homogeneity. For both regions, the calculated F-statistic is not rejected using the proper critical values but would have been strongly rejected using standard critical values. Results are consistent with the argument that the regularity of rejection of the parametric restrictions of symmetry and homogeneity found by Foxand Kivanda [CJAE (1994) 42 (1) pp. 1-13] may be due to inappropriate assumptions regarding the time series properties of the data rather than a rejection of neoclassical production theory. This interpretation is consistent with arguments made by Clarkand Coyle (in the same issue of CJAE) in their comments on Fox and Kivanda.