An application of the extended cross impact method to generating scenarios of social change in Japan

Scenarios of Japanese society in 2000 are obtained by applying an extended correlational cross impact analysis. Since the scope of the scenarios is extensive, a procedure is developed to generate the scenarios that consists of a preprocessing of the events of interest and a step-by-step application of a cross impact method. Three scenarios are described, based on a workshop where the procedure was applied.     

WEALTH AND THE DISTRIBUTION OF INCOME, CANADA 1969–70

This paper explores the sensitivity of the size distribution of family income in Canada to alternative definitions of income. These alternative definitions examine both wealth generally in the form of an annuity equivalent, and home ownership in the form of imputed rent. An adjustment for family size differences is also made. The impact of these adjustments is assessed for average incomes, inequality, and the incidence of low income for different age groups. The adjustments do have significant effects that vary by age; in particular, the economic position of the elderly seems understated by the usual data. Also, methodological considerations, such as the direct use of micro data and the choice of inequality indicator are shown to be significant.     

Sub additive measures of relative information and inaccuracy

Summary In the study of information theoretic measures, additivity has been the basic requirement. However it is quite interesting to investigate the sub-additive measures. Starting from subadditivity for measures associated with a pair of distributions of a discrete random variable, it has been changed into an equality relation using another function of a pair of distributions., Under the sum property of the function and the measures, the relation is expressed in terms of a functional equation of which the most general complex solutions have been obtained. In terms of the real continuous solutions of the functional equation, the sub-additive measures of Relative information and Inaccuracy have been defined and characterized. Particular cases and simple properties particularly the convexities of some of these new measures have also been studied.     

Henry George and Organized Labor:

A bstract . Henry George supported labor unions and was proud of his membership in the Printers' Union. But he did not regard them as the final solution of labor exploitation. He championed labor as one of the producing classes. His foray into politics as the candidate of organized labor's third party was characteristic; he had had much involvement in politics earlier. Although he supported labor's immediate demands, he sought mainly to use his candidacy to build a constituency for the single tax. Samuel Gompers , then head of the American Federation of Labor , at first worked for George's election but came to the belief that the unions alone should direct and control their political efforts. This view prevailed, though he and George remained good friends. But it is now a question whether Gompers' policy, at this time, serves labor's best interests.     

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.