[Arrow's impossibility theorem can be viewed as requiring that each subset of two social alternatives be a potential feasible subset or environment, with transitive and complete social choices over these subsets for each profile of individual preference orders. The feasibility assumption for every two-alternative subset is relaxed with consequent changes in the social ordering condition. An Arrow-type impossibility result still obtains when the set of social alternatives is the union of two disjoint sets, each of which has two or more elements, and when \{x, y\} is feasible whenever x is from one set and y is from the other. Variants of the basic theorem are included, one of which requires that strict binary social choices be acyclic.]

When a continuous time model is estimated from its non-recursive discrete approximation, the presence of identities and exogenous variables in the system does not preclude the use of standard procedures. However, if we wish to use the exact discrete model for estimation purposes, the treatment of identities and exogenous variables is not so straightforward. It is found that the procedure based on the exact discrete model is unlikely to be affected by the presence of identities, but when exogenous variables occur in the system some sort of approximation is usually necessary before the model can be estimated with discrete data. An approximate model is constructed to deal with the latter case and the asymptotic properties of estimators derived from this model are investigated. UNDER CERTAIN CONDITIONS, a stochastic model represented by a system of continuously distributed lags can be regarded as the solution of a system,of linear stochastic differential equations. Two general approaches are available if we wish to estimate the parameters of such a system by conventional methods and with discrete data.2 The first approach (see [1 and 2]) is to take a discrete approximation to the model and estimate the approximate model by standard methods. The second approach makes use of the discrete model which is known to correspond to the continuous time model in the sense that observations at equidistant points in time that are generated by the latter system also satisfy the former. The main advantage of the second approach is that no specification error is involved, so that it is possible in some cases to obtain consistent and asymptotically efficient estimators of the parameters in the model. In addition to the arguments of asymptotic theory, the results of a previous study [8] have given some recommendation to the second approach on the basis of small sampling performance. However, the model used in the sampling experiment of this study was relatively simple and it is the aim of the present paper to discuss the use of the second approach in more complicated models. The complications with which we will be concerned are the presence of identities and exogenous variables; both these complications may be expected to occur in more realistic economic, models. Before the procedure is viable when there are identities in the model, we must ascertain whether the disturbance in the exact discrete model has a non-singular

This paper is concerned with the problem of estimating demand and supply schedules in disequilibrium markets. The results of Fair and Jaffee are expanded in three ways. (1) Their directional method I is modified to yield consistent estimates. (2) A maximum likelihood alternative to their quantitative method is proposed. (3) The price equation is generalized to be a multivariate, stochastic function, and a method is proposed for estimating demand and supply schedules in this case.

[This analysis generalizes the concept of a private-goods contract curve to an economy with public goods. It provides a derivation of the properties of the set of Pareto-optimal points in n-space. The paper concentrates on situations where the taxation system for financing the public goods is externally imposed; the efficiency goal is thus "mechanism-constrained Pareto optimality." The results of the main analysis are applied to assess performance of several group decision procedures.]