Have you really come a long way? women’s access to power in the United States

Although vast social and political changes over the past decades have opened many opportunities for women, many activists and academics maintain that women continue to face significant barriers to entry into positions of power and influence. The vast majority of American leaders are white and male, but the representation of women in the professions has begun to rise as more and more women enter the leadership ranks of various professions. This article provides a profile of women who currently hold positions of power in the United States—who they are, what sectors they represent, and how their opinions on social and political issues compare and contrast with one another. Analyzing data from the Study of Leadership Characteristics, a recently completed national survey of American elites, this article examines the structure and gender composition of elites in the United States, revealing patterns of both conflict and consensus among women elites.     

Demographic effects of natural disasters: a case study of hurricane andrew*

Many studies have considered the economic, social, and psychological effects of hurricanes, earthquakes, floods, tornadoes, and other natural disasters, but few have considered their demographic effects. In this paper we describe and evaluate a method for measuring the effects of Hurricane Andrew on the housing stock and population distribution in Dade County, Florida. Using information collected through sample surveys and from other data sources, we investigate the extent of housing damages, the number of people forced out of their homes, where they went, how long they stayed, and whether they returned to their prehurricane residences. We conclude that more than half the housing units in Dade County were damaged by Hurricane Andrew; that more than 353,000 people were forced to leave their homes, at least temporarily; and that almost 40,000 people left the county permanently as a direct result of the hurricane. We believe that this study will provide methodological guidance to analysts studying the demographic effects of other large-scale natural disasters.     

THE IMPACT OF DEREGULATION ON THE PRODUCTION STRUCTURE OF THE MOTOR CARRIER INDUSTRY

Empirical analysis of the motor carrier industry pre- and post-regulatory reform reveals that deregulation resulted in significant changes in firm production structure and lower real average costs. Translog cost functions for firms operating in 1977 and 1983 were estimated and compared for "other specialized commodity" carriers. Fitted average costs were computed from these functions. The results indicate significant differences in the cost functions and real costs that cannot be attributed to technological changes but rather suggest efficiency gains. The results also suggest that it is inappropriate to predict outcomes of deregulation using empirical analyses of firms in the regulated environment.     

Type of Status Inconsistency and Schizophrenia*

A number of previous studies have called attention (typically ex post facto) to the finding that schizophrenics tend to have backgrounds with a particular type of status imbalance—their occupational level is lower than their years of education would seem to merit. The data from this study substantiated this finding. Moreover, we found that the greater the magnitude of this type of inconsistency, the higher the proportion of schizophrenia. Since schizophrenics were especially downwardly mobile, however, we tentatively concluded that this type of status inconsistency is not a “cause” of schizophrenia but rather a consequence of that illness.     

Accounting for migration in cohort-component projections of state and local populations

Migration is the most difficult component of state and local population growth to forecast accurately because it is more volatile than either births or deaths, and subject to much larger fluctuations within a short period of time. In addition, migration rates can be based on several different measures of migration and the base population. The choice of the appropriate base population has received little attention from demographic researchers, but can have a tremendous impact on population projections. In this article, I develop three different models for projecting migration, each using a different denominator for migration rates. Population projections for ten states are made, using identical data and cohort component techniques, except for the different formulations of migration rates. Differences among the three sets of projections are noted, and conclusions are drawn regarding their usefulness as forecasts of population growth.     

Non-familial activity and socio-economic differentials in fertility

The relationship between socio-economicstatus and fertility among married women is examined, using data from the 1/1,000 sample from the 1960 United States Census of Population and the 1960 Growth of American Families Study. Both sets of data indicate that the negative relationship between socio-economic status and fertility is still prevalent but may reflect different patterns of child-spacing rather than completed fertility. Labor force participation among these women is found to be negatively related to the number of children ever born. To determine the degree of involvement in this type of non-familial role, the work index or proportion of one’s married life engaged in the labor force is developed. The work index is found to be a particularly sensitive measure of involvement in the worker role vis-a-vis their fertility. The working hypothesis of this study, that such non-familial activity has a different effect according to one’s socio-economic status, is borne out. Participation in the labor force results in a relatively larger reduction in the fertility of upper status women than for those of lower status. However, this relationship apparently holds true only for those women from rural backgrounds but not for those from large urban areas.     

Precision,bias, and uncertainty for state population forecasts: an exploratory analysis of time series models

Many researchers have used time series models to construct population forecasts and prediction intervals at the national level, but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for states in the United States. Using annual population estimates from 1900 to 2000 and a variety of launch years, base periods, and forecast horizons, we construct population forecasts for four states chosen to reflect a range of population size and growth rate characteristics. We compare these forecasts with population counts for the corresponding years and find precision, bias, and the width of prediction intervals to vary by state, launch year, model specification, base period, and forecast horizon. Furthermore, we find that prediction intervals based on some ARIMA models provide relatively accurate forecasts of the distribution of future population counts but prediction intervals based on other models do not. We conclude that there is some basis for optimism regarding the possibility that ARIMA models might be able to produce realistic prediction intervals to accompany population forecasts, but a great deal of work remains to be done before we can draw any firm conclusions.