Mapping the Timing,Pace, and Scale of the Fertility Transition in Brazil

Between 1960 and 2000, fertility fell sharply in Brazil, but this transition was unevenly distributed in space and time. Using Bayesian spatial statistical methods and microdata from five censuses, we develop and apply a procedure for fitting logistic curves to the fertility transitions in more than 500 small regions of Brazil over this 40‐year period. Doing so enables us to map the main features of the Brazilian fertility transition in considerable detail. We detect early declines in some regions of the country and document large differences between early and late transitions in regard to both the initial level of fertility and the speed of the transition. We also use our results to test hypotheses regarding changes in the level of development at the onset of the fertility transition and identify a temporary stall in the Brazilian transition that occurred in the late 1990s. A web site with project details is at http://schmert.net/BayesLogistic .     

Comparison of some common ratio estimators using pitman measure of nearness

In this article we compare some common ratio estimators for estimating the population total of a given characteristic. The sampling schemes considered are simple random sampling (S.R.S.) and S.R.S.under stratification. The comparisons are made using the Pitman Nearness criterion under the model-based approach. The error term is assumed normal with mean zero and variance σg(x). The function g(x) is a known function of the auxiliary variable x. Special interest is on the cases of g(x) =l and x. The result is found the same as that using MSE criterion, although the PN is very different from the MSE intrinsically.     

Migration bias in indirect estimates of regional childhood mortality levels

Demographers often use Brass‐style indirect methods to obtain childhood mortality estimates for regions within developing countries. Regional populations are not closed to migration, however, and mortality reports of women resident in a certain region on the survey date may contain information on events and exposure that occurred elsewhere as the mother migrated. Including this “imported”; mortality information may cause significant bias in regional estimates. In this paper the authors: (1) investigate the possible magnitude of migration bias using a multiregional simulation model, (2) propose a modification to standard methods which should reduce bias in many circumstances, and (3) apply the modified technique to data from Brazil's 1980 Census. We find that migration bias can indeed be significant, and that in the specific case of São Paulo state, imported mortality information may result in overestimates of local mortality levels of 10–15% when using Brass‐style methods.     

Role clarity,work overload and organizational support: Multilevel evidence of the importance of support

The present study extended the demands-control-support model used in occupational stress research in two ways. First, it hypothesized that role clarity (i.e. role ambiguity), like control, would moderate the relationship between demands and psychological strain. Second, the study assessed support (from leaders) as a macro characteristic of the work-group environment. Data were drawn from a large study of US army soldiers, the study sample consisting of 1786 lower enlisted male soldiers. The inclusion of support as a work-group characteristic lead to a multilevel test of the model. A three-way multilevel interaction among work demands, role clarity and support was observed. As predicted, the relationship between demands and psychological strain was moderated by role clarity; however, this moderating relationship was found only when work-group support was high.     

Carl Warner摄影欣赏

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Hurricane Katrina,a Construction Boom,and a New Labor Force: Latino Immigrants and the New Orleans Construction Industry, 2000 and 2006–2010

Disasters provide opportunities to study the social and economic dimensions of large-scale shifts. Drawn by the surge in demand for low-skill construction workers in the aftermath of Hurricane Katrina in 2005, Latino immigrants represented a substantial share of the New Orleans reconstruction workforce. Scholars, however, have yet to examine how the increased presence of immigrants affected U.S.-born workers in New Orleans. In this analysis, we investigate how the influx of Latino immigrant construction workers shaped the demographic composition and occupational-wage structure of the New Orleans construction sector. Using IPUMS-U.S.A. data from the 2000 and 2006–2010 periods for the New Orleans MSA, we employ logistic and multinomial logistic regression models to analyze a sample of 3,206 foreign-born Latinos, U.S.-born whites, U.S.-born blacks, and others employed in the construction industry. Our analysis indicates that the probability of U.S.-born workers being employed in construction remained stable from the pre- to post-storm period, even as we find evidence of an emerging immigrant employment niche in the post-Katrina construction industry. After the storm, however, Latino immigrants were much more heavily concentrated in occupations at the bottom end of the construction industry’s wage structure, while the relative position of U.S.-born workers improved across the two periods. Together, these findings show that disasters, like other structural shifts, can yield the conditions that produce immigrant employment niches. Moreover, our results indicate that while employment niches provide economic opportunities for the foreign-born, they can also intensify the disadvantage experienced by immigrant workers.     

Medical Statistics at the Medical School of the University of Texas Health Science Center at Houston

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