Female Labor Force Participation in Urban and Rural China1

Abstract The objective of this study is to examine female labor force participation and its determinants in rural and urban China. The sociological literature has demonstrated that participation tends to increase in urban and industrialized places where women have higher levels of education and fewer children, where more workers are engaged in service pursuits, and where family structure is less traditional. With the use of data on counties and cities (N = 2,377) from the I-percent sample of the 1982 census of the People's Republic of China, it was found that female labor force participation is likely to rise in areas with increased agricultural employment, educational levels, proportion of female-headed households, and higher male-to-female sex ratios. Both the size of the service sector and the fertility rate had negligible effects on female labor force participation. Although, on average, rural places have slightly higher levels of female labor force participation, when other variables are controlled, urban places have a higher rate of female participation. In addition, the findings suggest that market factors (i.e., education) are more likely to determine the rate of female labor force participation in urban areas; whereas demographic and social factors (i.e., sex ratio and household structure) play a more important role in explaining the female labor force participation in rural counties.     

ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

Small Business Success Among Men- and Women-Owned Firms in Rural Areas1

Abstract Rural women have difficulty finding good jobs. Ownership of small businesses offers an alternative but the sales and income of women-owned firms are significantly lower than those of men-owned firms. Compared with men, women owners are more likely to operate smaller and newer businesses; however, these differences do not completely account for the gap in gross sales between men- and women-owned businesses. The strongest influences on business success are firm size, corporate status, and industrial sector. Though significant, the owner's gender is less important than these organizational characteristics. The factors influencing success of small businesses generally are the same for men- and women-owned businesses. More research on business networks and the start-up phase of small businesses is necessary for a better understanding of the sources of gender differences in success.     

WHO GETS THE NEWS? ALTERNATIVE MEASURES OF NEWS RECEPTION AND THEIR IMPLICATIONS FOR RESEARCH

This article investigates patterns in audience reception of16 news stories that received prominent media coverage in thesummer and fall of 1989. Using a national sample of Americanadults, it compares education, self-reported rates of mediause, interpersonal communication, and prior levels of generalpolitical knowledge as predictors of individual differencesin recall of current news events. Results indicate that respondents'background level of political knowledge is the strongest andmost consistent predictor of current news story recall acrossa wide range of topics, suggesting that there is indeed a generalaudience for news and that this audience is quite sharply stratifiedby preexisting levels of background knowledge. Thus, in surveyresearch applications that require estimates of individual differencesin the reception of potentially influential political communications,a measure of general prior knowledge—not a measure ofnews media use—is likely to be the most effective indicator.The article further concludes that the tendency of individualsto acquire news and information on a domain- or topic-specificbasis fails to undermine the value of political knowledge asa general measure of propensity for news recall.     

Optimal designs for generalized linear models

Summary This paper solves some D-optimal design problems for certain Generalized Linear Models where the mean depends on two parameters and two explanatory variables. In all of the cases considered the support point of the optimal designs are found to be independent of the unknown parameters. While in some cases the optimal design measures are given by two points with equal weights, in others the support is given by three point with weights depending on the unknown parameters, hence the designs are locally optimal in general. Empirical results on the efficiency of the locally optimal designs are also given. Some of the designs found can also be used for planning D-optimal experiments for the normal linear model, where the mean must be positive. This research was carried out in part at University College, London as an M.Sc. project. Thanks are due to Prof. I. Ford (University of Glasgow) and Prof. A. Giovagnoli (University of Perugia) for their valuable suggestions and critical observations.     

丰水区筑坝截流——调丰补歉

该文从中国人口快速增长、经济建设加快、用水量逐年增大 ,加上气候变暖、少雨干旱将持续到 2 0 15年 ,我国北方水生态环境日趋恶化现状 ,说明在丰水区筑坝截流、调丰补歉势在必行 ,完全符合生态经济学发展原则和国际水法     

Defining the linear portion of a sigmoid‐shaped curve: bend points

Formulae are provided that define the ‘bend points’, the beginning and end of the essentially linear dose–response region, for the four‐parameter logistic model. The formulae are expressed in both response and dose units. The derivation of the formulae is shown in order to illustrate the general nature of the methodology. Examples are given that describe how the formulae may be used while planning and conducting bioassays. Copyright © 2003 John Wiley & Sons, Ltd.     

A Numerical Solution to the Nonhomogeneous Two-Stage MVK Model of Cancer

In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.