Air pollution-mortality models: A demonstration of the effects of random measurement error

Errors of measurement have long been recognized as a chronic problem in statistical analysis. Although there is a vast statistical literature of multiple regression models estimating the air pollution-mortality relationship, this problem has been largely ignored. It is well known that pollution measures contain error, but the consequences of this error for regression estimates is not known. We use Lave and Seskin's air pollution model to demonstrate the consequences of random measurement error. We assume a range of 0% to 50% of the variance of the pollution measures is due to error. We find large differences in the estimated effects on mortality of the pollution variables as well as the other explanatory variables once this measurement error is taken into account. These results cast doubt on the usual regression estimates of the mortality effects of air pollution. More generally our results demonstrate the consequences of random measurement error in the explanatory variable of a multiple regression analysis and the misleading conclusions that may result in policy research if this error is ignored.     

Relationship between generalizedh-Statistics and polykays

Summary In this paper, relationships between generalizedh-statistics which estimate powers and products of central moments unbiasedly and the polykays by using ordered partitions are established. A table expressing generalizedh-statistics of weight 12 in terms of polykays and vice versa is presented. Expressions of weight less than 12 are obtained from this table.

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Zusammenfassung In der vorliegenden Arbeit wird mittels geordneter Zerlegungen eine Beziehung zwischen verallgemeinerterh-Statistik, welche Potenzen und Produkte von zentralen Momenten erwartungstreu abschätzt, und polykays hergestellt. Eime Tabele mit verallgemeinerterh-Statistik vom Gewicht 12 in polykay-Termen, und umgekehrt, wird gegeben. Gewichtsausdrücke kleiner als 12 werden aus dieser Tabelle gewonnen.

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This research has been supported by a grant from FINEP/Ministério do Planejamento e Coordenacão Geral to the IMUFRJ.     

Labor force migration, non-labor force migration, and non-employment reasons for migration

This paper documents the extent and nature of non-employment factors in migration. The labor force status of over 18 million recent interstate migrants in the United States and stated reasons for moving reported in several surveys in the U.S. are examined. Labor force migrants are heterogeneous in terms of the relationships between acquisition of employment and the migration decision, and in terms of the influence of decision makers outside of the migrant household including firms and the government. Numerically important categories of migrants not traditionally captured in migration models exist, including the elderly, the military, and movers from abroad. Whereas non-employment reasons are secondary to employment reasons for a majority of labor force migrants, non-employment factors are singularly important or operate in combination with employment factors for the majority of all migrants. The heterogeneity of migrant types and migration reasons needs to be better captured in migration models.     

Variables sampling plans for the Poisson and the binomial

Variables sampling plans based upon continuous distributions are well known. The usual assumption is that a measurable characteristic associated with a product has a normal distribution, a case which has been treated extensively in the literature. Other continuous distributions, particularly the exponential, have also been used as models. In this paper we discuss variables sampling plans for situations in which the measurable characteristic has either a Poisson or a binomial distribution.     

Reduced Form Auctions Revisited

This note uses the Theorem of the Alternative to prove new results on the implementability of general, asymmetric auctions, and to provide simpler proofs of known results for symmetric auctions. The tradeoff is that type spaces are taken to be finite.     

Collective Risk Control and Group Security: The Unexpected Consequences of Differential Risk Aversion

We provide an analysis of odds‐improving self‐protection for when it yields collective benefits to groups, such as alliances of nations, for whom risks of loss are public bads and prevention of loss is a public good. Our analysis of common risk reduction shows how diminishing returns in risk improvement can be folded into income effects. These income effects then imply that whether protection is inferior or normal depends on the risk aversion characteristics of underlying utility functions, and on the interaction between these, the level of risk, and marginal effectiveness of risk abatement. We demonstrate how public good inferiority is highly likely when the good is “group risk reduction.” In fact, we discover a natural or endogenous limit on the size of a group and of the amount of risk controlling outlay it will provide under Nash behavior. We call this limit an “Inferior Goods Barrier” to voluntary risk reduction. For the paradigm case of declining risk aversion, increases in group size(wealth) will cause provision of more safety to change from a normal to an inferior good thereby creating such a barrier.