Knowledge that Transforms

[We give an elementary statement and proof of a core equivalence theorem.]

The paper discusses certain problems raised recently by B. Peleg, about the existence of equilibria and 'nice' equilibria for various classes of voting games. First it is shown that under practically every non-dictatorial voting procedure, and for every sincere preference profile, one can find a Nash equilibrium with nice properties. Secondly, a Paretian and anonymous decision procedure is constructed, under which one can always find equilibria with certain attractive properties. Lastly, it is shown that if the number of alternatives is large enough, then for some sincere preference profile, no equilibrium may exist under many decision procedures.

The paper puts forward an approach to the analysis of the problem of strategic voting in democratic choice. It is argued that the notion of K-stability (or other similar concepts of equilibrium) is not adequate as an instrument for analyzing strategic voting. An alternative framework of analysis is suggested and using this framework, the possibility of sincere voting is examined in the context of a class of democratic systems.

[We study the time consistency of optimal monetary policy in a framework akin to the one in [12, Ch. 1] but we assume away lump sum taxation--all taxes are distortionary. Our major result is that under perfect foresight (as defined in [8, 23]) optimal monetary policy is bound to be time inconsistent. The paper is closely related to the previous works of Auernheimer [2], and Kydland and Prescott [15].]

In this paper a reduced form estimator is developed which combines the corresponding restricted 3SLS and the unrestricted LS estimators. This estimator is similar to the 'positive part' Stein-like estimators proposed by Baranchik [2] and S. Sclove [16] in the classical multivariate regression context. It is shown that, whereas the restricted (derived) 3SLS and 2SLS reduced form estimates possess no finite moments (hence have unbounded risk), the modified Stein-like reduced form (MSRF) estimator has finite moments of up to order (T n m), where T is the sample size, n and m are the number of the endogenous and the non-stochastic exogenous variables in the system. Furthermore it is argued that, asymptotically, the difference between the MSRF and the 3SLS estimators is negligible.

textabstractMonte Carlo (MC) is used to draw parameter values from a distribution defined on the structural parameter space of an equation system. Making use of the prior density, the likelihood, and Bayes' Theorem it is possible to estimate posterior moments of both structural and reduced form parameters. The MC method allows a rather liberal choice of prior distributions. The number of elementary operations to be preformed need not be an explosive function of the number of parameters involved. The method overcomes some existing difficulties of applying Bayesian methods to medium size models. The method is applied to a small scale macro model. The prior information used stems from considerations regarding short and long run behavior of the model and form extraneous observations on empirical long term ratios of economic variables. Likelihood contours for several parameter combinations are plotted, and some marginal posterior densities are assessed by MC.