HOUSEHOLD CHANGE AND RURAL SCHOOL ENROLLMENT IN MALAWI AND KENYA

This study examines school enrollment in two sub-Saharan African nations, Malawi and Kenya. The article advances a refined family economy theoretical framework for understanding variations in school enrollment. It recasts family economy frameworks to consider not only how the household institution mediates a broad social change, but also how the family institution itself may be influenced by a macroinstitutional change. The findings suggest that household structural changes, as well as changes in parents' activities and perceptions, help explain enrollment practices in rural Malawi and Kenya.     

SUNK COSTS, PROFIT VARIABILITY, AND TURNOVER

Dynamic competitive models of industry evolution suggest that firm profit will be more volatile, and turnover lower, in industries with higher sunk costs. These implications are consistent with empirical observation. (JEL L00 )     

An alternative to farmer age as an indicator of life-cycle stage: The case for a farm family age index

In studies of farming, the age of the principal decision-maker (PDM) has been associated with numerous farm structural and managerial features and has been widely accepted as a good indicator of the influence of life-cycle factors on decision-making. As such, it has become an important aspect of many quantitative studies of agricultural change. However, contemporary studies of family farming demonstrate that the concept of a single PDM in family farms is becoming an anachronism as alternative enterprises, pluriactivity and the scale of family farms force more diffuse management/operating systems. This raises questions concerning whether the age of the PDM can still be taken as representative of farm structure, strategy or life-cycle stage? Using a study conducted in the Grampian Mountains region of Scotland in 2003 this note investigates the impact of using an alternative index—compiled by averaging the age of family members working on the farm. It suggests that PDM age is a relatively poor indicator of farm structural and managerial features compared to a family age index and calls for researchers to think about alternative approaches to measuring ‘age’ as an indicator.     

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.     

Liability in child welfare

Child welfare workers and agencies are vulnerable to lawsuits. Recent court rulings have more clearly defined the liability of workers. The distinguishing variable is custody. Children injured while in the custody of the state are entitled to sue for damages. Children injured by their parent, even if under the supervision of a child welfare agency, are not entitled to claim a violation of their 14th Amendment rights. These cases are reviewed and strategies designed to minimize vulnerability are offered.     

A measure of slope-rotatability for second order response surface experimental designs

In the design of experiments for estimating the slope of a response surface, slope-rotatability is a desirable property. In this paper, a measure is introduced that enables us to assess the degree of slope-rotatability for a given response surface design. The measure takes the value zero if and only if the design is slope-rotatable, and becomes larger as the design deviates from a slope-rotatable design. Examples of applying this measure to some response surface designs are also given.     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

Influence of behavioural tactics on recruitment and reproductive trajectory in the kittiwake

Many studies have provided evidence that, in birds, inexperienced breeders have a lower probability of breeding successfully. This is often explained by lack of skills and knowledge, and sometimes late laying dates in the first breeding attempt. There is growing evidence that in many species with deferred reproduction, some prebreeders attend breeding places, acquire territories and form pairs. Several behavioural tactics assumed to be associated with territory acquisition have been described in different species. These tactics may influence the probability of recruiting in the breeding segment of the population, age of first breeding, and reproductive success in the first breeding attempt. Here we addressed the influence of behaviour ('squatting') during the prebreeding period on demographic parameters (survival and recruitment probability) in a long-lived colonial seabird species: the kittiwake. We also investigated the influence of behaviour on reproductive trajectory. Squatters have a higher survival and recruitment probability, and a higher probability of breeding successfully in the first breeding attempt in all age-classes where this category is represented. The influence of behaviour is mainly expressed in the first reproduction. However, there is a relationship between breeding success in the first occasion and subsequent occasions. The influence of breeding success in the first breeding attempt on the rest of the trajectory may indirectly reflect the influence of behaviour on breeding success in the first occasion. The shape of the reproductive trajectory is influenced by behaviour and age of first breeding. There is substantial individual variation from the mean reproductive trajectory, which is accounted for by heterogeneity in performance among individuals in the first attempt, but there is no evidence of individual heterogeneity in the rate of change over time in performance in subsequent breeding occasions     

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.