Production functions and population theory

The persistence of the population problem in many developing countries' especially in Asia, must mean that the relation between population trends and productivity has to be kept continually under review. In recent years the economists' interest in this relation has shifted away from the Keynesian stagnation analysis, with its emphasis on the influence of population trends on the level and composition of consumption and investment, to a reconsideration of their influence on production. It is a striking testimony to the influence of Malthus that his theory is still under active consideration and that it frequently serves as starting point, as it does for Professor Belshaw, for an analysis of the economics of population. Divorced from its particular context, in which value judgements particularly distasteful to many commentators abound, and reformulated in terms of modern production theory, it clarifies the main issues, by showing what facts are required and what logic demands in order to provide a useful answer to practical problems of policy. Readers of the first two chapters of Professor Buquet's book will find ample confirmation of the sterility of much of the debate regarding optimum populations which developed largely from differences of opinion about definitions of “good” and “bad” economic criteria for policy than from faults in logic. The debate continues and the posthumous career of Parson Malthus still occasions even personal abuse! It would be difficult, however, to accuse Professor Belshaw of taking sides in the Malthusian debate. He takes the Malthusian analysis for what it is worth, shows where it fits the facts and where it does not, provides convincing evidence of a Malthusian problem in Asia by a skilful round-up of well presented statistics, and then, instead of committing himself to a forecast of what is likely to happen in Asia, he illustrates through the modern theory of production what are the pre-conditions for a removal of the population problem. This is surely a sensible procedure and contrasts favourably with the sibylline utterances of a number of distinguished amateur social scientists.     

The Role of Wilderness Protection and Societal Engagement as Indicators of Well-Being: An Examination of Change at the Boundary Waters Canoe Area Wilderness

A societal decision to protect over 9 million acres of land and water for its wilderness character in the early 1960s reflected US wealth in natural resources, pride in the nation’s cultural history and our commitment to the well-being of future generations to both experience wild nature and enjoy benefits flowing from these natural ecosystems. There is no question that our relationship with wilderness has changed. Individually it is probably quite easy to examine differences in the role wilderness plays in the quality of our lives today compared to some previous time. But how the role of wilderness protection has changed for society is more difficult to describe. In only a few places do we have data across multiple decades that would allow us to even examine how users or their use may have changed over time. At the Boundary Waters Canoe Area Wilderness in northern Minnesota we are fortunate to have multiple studies that can give us some 40 years of insight into how some aspects of use have changed there. For example, an analysis of results of visitor studies at the Boundary Waters Canoe Area Wilderness in 1969, 1991 and 2007 reveal some big differences in who is out there today, most notably the presence of a much older, more experienced and better educated user population, almost exclusively white and predominantly male. It is time to decide whether the best thing for wilderness and or society is to try to restore historic patterns of use (to include younger people, the less wealthy and lower educated) in greater numbers, to try to identify new markets within growing underrepresented populations, or adapt our perception of wilderness stewardship to better include planning for emerging social values of a new generation with other indicators of well-being. A growing population with greater dependence on ecosystem services provided by protected nature could lead to wilderness protection becoming an important quantitative and qualitative element of quality of life indices in the very near future.     

Simultaneous edit-imputation and disclosure limitation for business establishment data

Business establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.     

CUSUM Control Charts for Multivariate Poisson Distribution

A cumulative sum control chart for multivariate Poisson distribution (MP-CUSUM) is proposed. The MP-CUSUM chart is constructed based on log-likelihood ratios with in-control parameters, Θ₀, and shifts to be detected quickly, Θ₁. The average run length (ARL) values are obtained using a Markov Chain-based method. Numerical experiments show that the MP-CUSUM chart is effective in detecting parameter shifts in terms of ARL. The MP-CUSUM chart with smaller Θ₁ is more sensitive than that with greater Θ₁ to smaller shifts, but more insensitive to greater shifts. A comparison shows that the proposed MP-CUSUM chart outperforms an existing MP chart.     

Identifiable finite mixtures of location models for clustering mixed-mode data

For clustering mixed categorical and continuous data, Lawrence and Krzanowski (1996) proposed a finite mixture model in which component densities conform to the location model. In the graphical models literature the location model is known as the homogeneous Conditional Gaussian model. In this paper it is shown that their model is not identifiable without imposing additional restrictions. Specifically, for g groups and m locations, (g!)m–1 distinct sets of parameter values (not including permutations of the group mixing parameters) produce the same likelihood function. Excessive shrinkage of parameter estimates in a simulation experiment reported by Lawrence and Krzanowski (1996) is shown to be an artifact of the model's non-identifiability. Identifiable finite mixture models can be obtained by imposing restrictions on the conditional means of the continuous variables. These new identified models are assessed in simulation experiments. The conditional mean structure of the continuous variables in the restricted location mixture models is similar to that in the underlying variable mixture models proposed by Everitt (1988), but the restricted location mixture models are more computationally tractable.     

Bootstrapping data with multiple levels of variation

The authors consider general estimators for the mean and variance parameters in the random effect model and in the transformation model for data with multiple levels of variation. They show that these estimators have different distributions under the two models unless all the variables have Gaussian distributions. They investigate the asymptotic properties of bootstrap procedures designed for the two models. They also report simulation results and illustrate the bootstraps using data on red spruce trees.     

Improving early phase oncology clinical trial design: The case for finding the optimal biological dose

Historically early phase oncology drug development programmes have been based on the belief that “more is better”. Furthermore, rule-based study designs such as the “3 + 3” design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.