Widowhood,family size,and post-reproductive Mortality: a comparative Analysis of three populations in Nineteenth-Century Europe

Researchers from a number of disciplines have offered competing theories about the effects oJ childbearing on parents 'postreproductive longevity. The "disposable soma theory" argues that investments in somatic maintenance increase longevity but reduce childbearing. "Maternal depletion" models suggest that the rigors of childrearing increase mortality in later years. Other researchers consider continued childbearing a sign of healthy aging and a predictor of future longevity. Empirical studies have produced inconsistent and contradictory results. Our focus is on the experience of widowhood, which has been ignored in previous studies. We hypothesize that the death of a spouse is a stressful event with long-term consequences for health, especially for women with small children. Data are drawn from historical sources in Sweden, Belgium, and the Netherlands from 1766 to 1980. Postreproductive mortality was highest among young widows with larger families in all three samples. Age at last birth had little or no effect. We conclude that raising children under adverse circumstances can have long-lasting, harmful effects on a mother's health.     

Making sense of census data: A components analysis of employment change among indigenous Australians

The 1996 Census count of indigenous Australians included a substantial number of individuals who were not recorded as indigenous by the previous census. This paper considers the implications of this for interpreting change in employment numbers. Two adjustments are made to employment change data. First, reverse survival of the 1996 population is applied to reconstruct 1991 employment figures. Second, administrative data are used to discount employment generated by participation in labour market programs. The effect is to substantially deflate the strong intercensal employment growth apparent from census counts with the conclusion that the rate of indigenous employment in the mainstream labour market has fallen.     

TEACHING EFFECTIVENESS IN THE DECISION SCIENCES: THE USE OF STUDENT EVALUATIONS

This article presents the results of an AIDS-sponsored investigation of teaching effectiveness in the decision sciences. Two national samples were employed in the study: a sample of 247 business school deans and a sample of 3,292 students from 32 different business schools. Included among the findings are that 87 percent of the deans responding indicate they require some sort of faculty teaching effectiveness evaluation, and that great care must be exercised when interpreting student ratings of an individual instructor's teaching effectiveness.     

Modelling Variability in the Branching Structure of Strawberry Inflorescences

The branching structure of inflorescences of the cultivated strawberry ( Fragaria × ananassa Duch.) is very variable. This paper demonstrates that some aspects of this variability are well described by a simple stochastic model of branching that has two adjustable parameters. The model is shown to provide a good fit to data from a set of almost 700 inflorescences of the cultivar Elsanta, collected over two successive years. For one parameter the maximum likelihood estimator is a moment estimator which is fully efficient even if the detailed branching structure of the inflorescences is not recorded. This parameter provides a convenient summary of branching vigour. The maximum likelihood estimator of the second parameter must be determined iteratively and can be quite inefficient unless the full branching structure is recorded. The model demonstrates that branching structure is affected by the order in which inflorescences emerge on the plant.     

Simplified Estimating Functions for Diffusion Models with a High-dimensional Parameter

We consider estimating functions for discretely observed diffusion processes of the following type: for one part of the parameter of interest we propose to use a simple and explicit estimating function of the type studied by Kessler (2000); for the remaining part of the parameter we use a martingale estimating function. Such an approach is particularly useful in practical applications when the parameter is high-dimensional. It is also often necessary to supplement a simple estimating function by another type of estimating function because only the part of the parameter on which the invariant measure depends can be estimated by a simple estimating function. Under regularity conditions the resulting estimators are consistent and asymptotically normal. Several examples are considered in order to demonstrate the idea of the estimating procedure. The method is applied to two data sets comprising wind velocities and stock prices. In one example we also propose a general method for constructing diffusion models with a prescribed marginal distribution which have a flexible dependence structure.     

The role of tobacco taxes in starting and quitting smoking: Duration analysis of British data

The annual 5% increase in tobacco taxes in real terms proposed in the recent White Paper on smoking has reaffirmed the commitment of successive UK Governments to above-inflation increases in tobacco taxation to encourage people to stop smoking. This paper presents evidence on the determinants of starting and quitting smoking by using data from the British Health and Lifestyle Survey and is the first to identify tax elasticities for starting and quitting smoking using British data. Self-reported individual smoking histories are coupled with a long time series for the tax rate on cigarettes to construct a longitudinal data set. Estimates are obtained for the effect of above-inflation tax rises on the age of starting smoking and the number of years of smoking. The estimates of the tax elasticity of the age of starting smoking are 0.16 for men and 0.08 for women. The estimates of the tax elasticity of quitting are −0.60 for men and −0.46 for women. These are robust to different specifications.     

An Approximate Bayesian Marginal Likelihood Approach for Estimating Finite Mixtures

Estimation of finite mixture models when the mixing distribution support is unknown is an important problem. This article gives a new approach based on a marginal likelihood for the unknown support. Motivated by a Bayesian Dirichlet prior model, a computationally efficient stochastic approximation version of the marginal likelihood is proposed and large-sample theory is presented. By restricting the support to a finite grid, a simulated annealing method is employed to maximize the marginal likelihood and estimate the support. Real and simulated data examples show that this novel stochastic approximation and simulated annealing procedure compares favorably with existing methods.