Endogenous fertility and human capital in a Schumpeterian growth model

This study develops a scale-invariant Schumpeterian growth model with endogenous fertility and human capital accumulation. The model features two engines of long-run economic growth: R&D-based innovation and human capital accumulation. One novelty of this study is endogenous fertility, which negatively affects the growth rate of human capital. Given this growth-theoretic framework, we characterize the dynamics of the model and derive comparative statics of the equilibrium growth rates with respect to structural parameters. As for policy implications, we analyze how patent policy affects economic growth through technological progress, human capital accumulation, and endogenous fertility. In summary, we find that strengthening patent protection has (a) a positive effect on technological progress, (b) a negative effect on human capital accumulation through a higher rate of fertility, and (c) an ambiguous overall effect on economic growth.     

Normal quantile estimation based on minimizing the error in predicted distribution functions

Estimators of the form [Xbar] + kS for estimating the p quantile of a normal distribution are studied when k is chosen to either minimize the mean square error in the predicted distribution function or to make the predicted distribution function unbiased for p. Here, [Xbar] and S are the usual sample mean and standard deviation, respectively, and the predicted distribution function is the true (normal) distribution function evaluated at the estimated quantile.

These k values are presented for various sample sizes and values of p, and application to warranty determination is discussed.     

Improved Confidence Statements for the Binomial Parameter

In the computation of two-sided confidence intervals for the binomial parameter p (using the binomial mass function), it is known that such intervals achieve a confidence coefficient that in general is not equal to the confidence level 1 – α, say. In this article we present some general results on the confidence coefficient and tabulate them for selected pairs (α, n = number of trials). We treat only the nominal equal tail probability case because it is the most commonly taught and used.     

Bootstrapping a Universal Pivot When Nuisance Parameters are Estimated

In complete samples from a continuous cumulative distribution with unknown parameters, it is known that various pivotal functions can be constructed by appealing to the probability integral transform. A pivotal function (or simply pivot) is a function of the data and parameters that has the property that its distribution is free of any unknown parameters. Pivotal functions play a key role in constructing confidence intervals and hypothesis tests. If there are nuisance parameters in addition to a parameter of interest, and consistent estimators of the nuisance parameters are available, then substituting them into the pivot can preserve the pivot property while altering the pivot distribution, or may instead create a function that is approximately a pivot in the sense that its asymptotic distribution is free of unknown parameters. In this latter case, bootstrapping has been shown to be an effective way of estimating its distribution accurately and constructing confidence intervals that have more accurate coverage probability in finite samples than those based on the asymptotic pivot distribution. In this article, one particular pivotal function based on the probability integral transform is considered when nuisance parameters are estimated, and the estimation of its distribution using parametric bootstrapping is examined. Applications to finding confidence intervals are emphasized. This material should be of interest to instructors of upper division and beginning graduate courses in mathematical statistics who wish to integrate bootstrapping into their lessons on interval estimation and the use of pivotal functions.

[Received November 2014. Revised August 2015.]     

Why People Leave Community Service Organizations: A Mixed Methods Study

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Despite the benefits of volunteering to the individual, organization and community, the retention of volunteers within...     

Experiences of National Disability Insurance Scheme planning from the perspective of adults with intellectual disability

The Australian National Disability Insurance Scheme (NDIS) is attempting to address long‐term inequalities experienced by people with disability. Planning is central to the NDIS. People with intellectual disability will be the largest group of NDIS participants, and their perspectives are underrepresented in the literature. It is important to understand how they experience and perceive NDIS planning. Ten adults with intellectual disability participated in semi‐structured interviews to explore their experiences of NDIS planning. Data were analysed using Braun and Clarke's (2006, Qualitative Research in Psychology, 3, 77) six stages of thematic analysis. Six themes were identified: planning preparation not fit for purpose, creating goals, goals not met, planning not meeting real needs, lack of choice and control and importance of relationship with planner. In principle, the NDIS presents a real opportunity to increase the choice and control, social and economic participation, and independence of people with disability; however, this does not always translate into practice for people with intellectual disability.     

Challenging the techno-politics of anonymity: the case of cryptomarket users

Anonymity is treated as a problem of governance that can be subject to technical resolution. We use the example of the darknet to critically examine this approach. We explore the background assumptions that have been made about anonymity as a quality of social life. We conceive of anonymity as a way of engaging and maintaining social relationships in an anonymous mode. We draw on a study of darknet ‘cryptomarket’ users who mainly use the darknet to buy and sell illicit drugs, discuss drug quality and share information on safe and effective use. We identify the personal satisfaction that comes from interacting anonymously online, the challenges this represents for maintaining trusted interactions and how they are overcome, and the combination of technology and action involved in maintaining anonymity. We argue that attempts to promote de-anonymising norms and technology are based on an erroneous understanding of what anonymity is.     

A zero-augmented gamma mixed model for longitudinal data with many zeros

In many occupational safety interventions, the objective is to reduce the injury incidence as well as the mean claims cost once injury has occurred. The claims cost data within a period typically contain a large proportion of zero observations (no claim). The distribution thus comprises a point mass at 0 mixed with a non-degenerate parametric component. Essentially, the likelihood function can be factorized into two orthogonal components. These two components relate respectively to the effect of covariates on the incidence of claims and the magnitude of claims, given that claims are made. Furthermore, the longitudinal nature of the intervention inherently imposes some correlation among the observations. This paper introduces a zero-augmented gamma random effects model for analysing longitudinal data with many zeros. Adopting the generalized linear mixed model (GLMM) approach reduces the original problem to the fitting of two independent GLMMs. The method is applied to evaluate the effectiveness of a workplace risk assessment teams program, trialled within the cleaning services of a Western Australian public hospital.