Aging population scenarios: an Australian experience

During the past decade, there has been wide public discussion about the effects of population and immigration policies. There is some consensus that an older population imposes economic costs but uncontrolled population growth imposes congestion and environmental burdens. While many realize that policies which restrict population tend to exacerbate aging, the inevitable trade-off is not widely acknowledged. Fewer still appreciate that there is a sustainable age distribution that is largely imposed on us by nature that cannot be defeated in the long term. In this paper, we look at the ‘aging issue’ for Australia by looking at the total population and age distribution as a joint outcome. For ease of interpretation, the age distribution is converted into a required retirement age (RRA) to maintain dependency ratios at 2010 levels. We examine the effects of alternative policy scenarios on total population and RRAs, benchmarked against a hypothetical population in zero population growth equilibrium. We account for differing demographic groups of immigrants and emigrants as well as trends in mortality. Policy scenarios can be well summarized by plotting the trajectory of the two outcomes, total population and RRA, with the equilibrium values as axes.     

Justice for whom?: Assessing humanist criminology as a catalyst for change in the criminal justice apparatus

Humanist perspectives on criminology incorporate the role of the state in affecting basic justice processes. Separate scholarly work by Alfred McClung Lee, Richard Quinney, and others set the stage for viable alternatives embodied in peacemaking and restorative justice. Tie-ins between critical humanist criminology critiques, basic sociology views toward society, and current developments in alternative justice models are assessed. An evaluation of how humanist criminology has transformed conceptions of community participation (as stressed in the original humanist sociology perspective) will serve as an integral analysis in assessing the impact of social justice models.     

Extending the Box–Cox transformation to the linear mixed model

Summary.  For a univariate linear model, the Box–Cox method helps to choose a response transformation to ensure the validity of a Gaussian distribution and related assumptions. The desire to extend the method to a linear mixed model raises many vexing questions. Most importantly, how do the distributions of the two sources of randomness (pure error and random effects) interact in determining the validity of assumptions? For an otherwise valid model, we prove that the success of a transformation may be judged solely in terms of how closely the total error follows a Gaussian distribution. Hence the approach avoids the complexity of separately evaluating pure errors and random effects. The extension of the transformation to the mixed model requires an exploration of its potential effect on estimation and inference of the model parameters. Analysis of longitudinal pulmonary function data and Monte Carlo simulations illustrate the methodology discussed.     

TIGHT UPPER CONFIDENCE LIMITS FROM DISCRETE DATA

Consider the problem of finding an upper 1 –α confidence limit for a scalar parameter of interest ø in the presence of a nuisance parameter vector θ when the data are discrete. Approximate upper limits T may be found by approximating the relevant unknown finite sample distribution by its limiting distribution. Such approximate upper limits typically have coverage probabilities below, sometimes far below, 1 –α for certain values of (θ, ø). This paper remedies that defect by shifting the possible values t of T so that they are as small as possible subject both to the minimum coverage probability being greater than or equal to 1 –α, and to the shifted values being in the same order as the unshifted ts. The resulting upper limits are called ‘tight’. Under very weak and easily checked regularity conditions, a formula is developed for the tight upper limits.     

Approximating Fisher's information for the functional measurement error model

For the functional measurement error model, the true, unobservable explanatory variables when treated as nuisance parameters yield an increase in the number of nuisance parameters corresponding to an increase in sample size. Fisher's information may not exist for all parameters under this scenario. We propose a simple but effective method of deriving Fisher's information by approximating the design matrix of explanatory variables with a quantile design matrix. We illustrate the application of our method with a numerical example. Adaptation of this method shows very good performance for the prediction problem.     

The Influence of Abusive Supervisors on Followers' Organizational Citizenship Behaviours: The Hidden Costs of Abusive Supervision

In this paper, we identified an expanded array of mediators including interactional justice, organizational‐based self‐esteem, and the meaning of work, which link abusive supervision to two organizational citizenship behaviours – prosocial silence and prosocial voice. Data from 175 employee–supervisor dyads in the Philippines were collected. Results of structural equation modelling revealed that abusive supervision was significantly negatively associated with followers' perceptions of interactional justice, which in turn was negatively associated with supervisor‐rated prosocial voice behaviours. In addition, abusive supervision was negatively associated with followers' beliefs that they are engaged in meaningful work and with organizational‐based self‐esteem, which in turn negatively influenced self‐rated prosocial silence. The discussion focuses on the implications of the hidden costs of abusive supervision in organizations.     

Rethinking measures of migration: On the decomposition of net migration

The purpose of this paper is to “resurrect” the measure of net migration and defend its continued use under specific research circumstances, despite the current dissatisfaction with the measure as expressed by some scholars. We employ data from the 1980 Census of Population to compare five measures of migration, including net migration rates, in- and out-migration rates, migration efficiency ratios and migration turnover rates. We demonstrate the additivity of in- and out-migration rates with net migration rates and migration turnover rates. Also, we show how the migration efficiency ratio and turnover rates are conceptually and mathematically related. Finally, a simple multivariate model is estimated to show how regression coefficients from in-and out-migration rate models are related to net migration and migration turnover rates.