Gender and Science in Developing Areas: Has the Internet Reduced Inequality?*

Objective. This article examines the impact of the Internet on the research careers of female scientists in three developing areas: Ghana, Kenya, and Kerala, India. Most empirical studies of gender and science focus on the developed world, yet theoretical accounts emphasize more extreme differences in developing areas. Limited evidence from Africa and Asia shows gender inequity is restricted to a few key dimensions, broadly related to differences in human and social capital. Specifically, women are less likely to acquire an advanced degree and more likely to experience educational and organizational “localism.” Such localism is related to constraints on physical mobility that are widely expected to diminish with the introduction of the Internet. Methods. Using longitudinal data on 1,147 scientists in Ghana, Kenya, and south India, we examine gender differences in human and social capital by conducting a series of t tests and chi‐square tests. Results. We show that higher education and Internet access increased dramatically, but localism has not been reduced significantly and may be increasing. Conclusions. This finding casts doubt on the presumption that the removal of communication constraints will soon reduce career differentials resulting from the mobility constraints on women professionals.     

Comparative organization analysis: Sampling and measurement

This paper employs confirmatory factor analysis to evaluate the effects of using multiple indicators and heterogeneous samples in comparative organizational research. The results show that several indicators of different dimensions of organizational structure can be unified into a single measurement model and that theoretical constructs based upon these multiple indicators are applicable to a wide variety of organizational types. The findings imply that the development of a general theory of organizational structure need not be impeded by current sampling and measurement practices.     

Considerations in determining the content of the 1970 census

This paper describes some of the factors that are being considered in planning the content of the 1970 Census. The key factor, is the conclusion by the top Bureau officials that the major needs for data in 1970 can be met by a schedule whose content is similar to that used in 1960. Although there will be some disagreement with this conclusion, it is based on a widespread sampling of opinion in which all interested parties were invited-indeed urged-to present their views.This framework places serious limitations on the opportunity to introduce innovations in schedule content. Since there appears to be no good reason-technical or otherwise-to drop items that were included in 1960, it is not likely that new items will be traded off for old ones. There also does not appear to be any good prospect that it will be possible for new items to be financed by savings in field procedures such as the mail-out mail-back approach. According to the best current estimates, this procedure may produce better coverage and a substantial capital improvement in the form of an address reqister; but it is not likely to result in any major savings in cost.The major innovation in the results produced by the 1970 Census will probably be in the greater availability of data for more small areas. It does not seem likely at present that there will be significant changes in content.     

Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series

I analyze efficient estimation of a cointegrating vector when the regressand and regressor are observed at different frequencies. Previous authors have examined the effects of specific temporal aggregation or sampling schemes, finding conventionally efficient techniques to be efficient only when both the regressand and the regressors are average sampled. Using an alternative method for analyzing aggregation under more general weighting schemes, I derive an efficiency bound that is conditional on the type of aggregation used on the low-frequency series and differs from the unconditional bound defined by the full-information high-frequency data-generating process, which is infeasible due to aggregation of at least one series. I modify a conventional estimator, canonical cointegrating regression (CCR), to accommodate cases in which the aggregation weights are known. The correlation structure may be utilized to offset the potential information loss from aggregation, resulting in a conditionally efficient estimator. In the case of unknown weights, the correlation structure of the error term generally confounds identification of conditionally efficient weights. Efficiency is illustrated using a simulation study and an application to estimating a gasoline demand equation.     

The Inverse of the Freeman – Tukey Double Arcsine Transformation

A formula for the inverse of the Freeman–Tukey double arcsine transformation is derived. This formula is useful when expressing means of double arcsines as retransformed proportions. When the mean is taken from original proportions involving different n's, it is suggested that the harmonic mean of the n's be used in the inversion formula.     

Use of the squared ranks test to test for the equality of the coefficients of variation

A distribution-free test for the equality of the coefficients of variation from k populations is obtained by using the squared ranks test for variances, as presented by Conover and Iman (1978) and Conover (1980), on the original observations divided by their respective expected values. Substitution of the sample mean in place of the expected value results in the test being only asymptotically distribution-free. Results of a simulation study evaluating the size of the test for various coefficient of variation values and probability distributions are presented.     

Another look at subset selection using linear least squares

The QR-factorization provides a set of orthogonal variables which has advantages over other orthogonal representations, such as principal components and the singular-value decomposition, in selecting subsets of regression variables by least squares methods. Stopping rules, in particular, are easily understood. A new stopping rule is derived for prediction. This is derived by approximately minimizing the mean squared error in estimating the squared error of prediction. A clear distinction is made between the kind of stopping rule which is relevant when the objective is prediction, and when the objective is asymptotic consistency. Progress with reducing the bias due to the model selection procedure is briefly summarized.     

EVALUATING THE TRADE-OFFS BETWEEN IDLING AND SHUTTING DOWN PRODUCTION LINES IN PROCESS INDUSTRIES

The costs of starting-up and shutting down production lines (and plants) in a process industry are often quite high. Therefore, when a plant's capacity significantly exceeds its forecast demand over an annual planning horizon, a manufacturer must either plan temporary production line shutdowns during the year, or plan to temporarily idle production lines without formally shutting line(s) down. The trade-offs between these two strategies can be complex. In this paper, we propose a methodology to evaluate the impact of both strategies on a plant's production costs by developing an analytical model based on the authors' experience with several process industries.