Foundations of Dominant-Strategy Mechanisms

Robert Wilson criticizes applied game theory's reliance on common-knowledge assumptions. In reaction to Wilson's critique, the recent literature of mechanism design has adopted the goal of finding detail-free mechanisms in order to eliminate this reliance. In practice this has meant restricting attention to simple mechanisms such as dominant-strategy mechanisms. However, there has been little theoretical foundation for this approach. In particular it is not clear the search for an optimal mechanism that does not rely on common-knowledge assumption would lead to simpler mechanisms rather than more complicated ones. This paper tries to fill the void. In the context of an expected revenue maximizing auctioneer, we investigate some foundations for using simple, dominant-strategy auctions.     

Robustness to the unavailability of data in block designs

We present general results for finding or boundingt _maxB , the maximum number of arbitrary whole blocks of observations which can be removed from a block design, and still leave all of the elementary treatment contrasts estimable. The block sizes may be larger than the number of treatments. The results are applied to BBDs, reinforced BIBDs and BBDs, BTIBDs, and a series of variance balanced incomplete block designs with two block sizes. Also given for most of these designs, are results fort _max, the maximum number of arbitrary, scattered observations that can become unavailable, and still leave all of the elementary treatment contrasts estimable.The work was undertaken while Dr. Whittinghill was visiting Ohio State University, and supported by a grant from the Natural Sciences Division, Colby College, Waterville, Maine.     

Urban Regulations and the Price of Land and Housing in Korea

South Korea is a remarkable macroeconomic success story, but it has performed relatively poorly in one respect: the provision of high quality housing at reasonable prices. This paper analyzes the Korean housing market and the market for related inputs, with special emphasis on the regulatory environment.     

Aggregation effects on price and expenditure elasticities in a quadratic almost ideal demand system

Abstract.  While it is well known that demand elasticities calculated at the macro level will in general differ from those calculated at the micro level because of aggregation effects, there remain the questions of how large the effects are and how they vary with the degree of inequality in the income distribution. We explore these questions with models based on a quadratic version of the Almost Ideal Demand System. We investigate the elasticity differences theoretically and then calibrate the models and generate numerical results, using income data for seven countries with widely different distributions. The aggregation effects are found generally to be rather small, even with highly unequal income distributions.     

Forecasting first births

This study is concerned with one aspect of the family cycle, namely, the transition from young married to young married with small children. The focus is on developing models to forecast entries into this latter stage for the purpose of marketing research. "Using ordinary least squares, forecasting models were estimated for (1) total number of first births, (2) number of white first births, and (3) number of nonwhite first births." Models are estimated for both the United States and California using data from official sources.     

Forecasting and random processes

On the simple model of a (univariate) random process some general problems of “random logic” are discussed. New random approaches to explorative, normative and systematic (normex) forecasting are developed, and some applications are suggested.     

A comparison of alternative methods of updating input-output coefficients

In recent years there has been a growing number of input-output models of economies ranging in scale from the rural to the national. While offering invaluable insights into the interaction of sectors within an economy, the input-output model suffers from the fact that its coefficient values are altered over time due particularly to technological change. Two of the prominent techniques designed to update these technical coefficients, the RAS and linear programming methods, are compared herein with regard to changes in U.S. national coefficients between 1963 and 1967. Suggestions for improvements to the latter method are outlined.