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.     

Calculation of the expected lifetime lost due to an extra risk

Methods are given for estimating the average years of life lost when a person is discovered to be at risk from an extra hazard. The methods use the probability per year of the extra risk striking, and the mean and standard deviation of lifetime in the absence of the risk. The formulae are simple enough that only a hand‐held calculator is needed.     

Teacher-Based Racial Discrimination: The Role of Racial Pride and Religiosity Among African American and Caribbean Black Adolescents

This study explored the extent to which private regard and religiosity beliefs serve as protective factors for school bonding among African American and Caribbean black adolescents who experience racial discrimination in school. Findings are drawn from a nationally representative sample of (n = 810) African American and (n = 360) Caribbean black adolescents (52% girls) aged 13–17 (M_age = 15, SD = 1.42) years. Results suggest that perceiving racial discrimination from teachers was associated with lower levels of school bonding for African American and Caribbean black adolescents. For African American adolescents, perceiving more racial discrimination from teachers and reporting lower private regard beliefs was associated with less school bonding. The findings for Caribbean black adolescents revealed that endorsing moderate levels of religiosity and perceiving higher rates of teacher discrimination was associated with less school bonding. The developmental significance and implications for future research are discussed.     

Equilibrium Labor Turnover,Firm Growth,and Unemployment

This paper considers equilibrium quit turnover in a frictional labor market with costly hiring by firms, where large firms employ many workers and face both aggregate and firm specific productivity shocks. There is exogenous firm turnover as new (small) startups enter the market over time, while some existing firms fail and exit. Individual firm growth rates are disperse and evolve stochastically. The paper highlights how dynamic monopsony, where firms trade off lower wages against higher (endogenous) employee quit rates, yields excessive job‐to‐job quits. Such quits directly crowd out the reemployment prospects of the unemployed. With finite firm productivity states, stochastic equilibrium is fully tractable and can be computed using standard numerical techniques.     

The Effects of Multitasking on Operations Scheduling

This study considers a typical scheduling environment that is influenced by the behavioral phenomenon of multitasking. Under multitasking, the processing of a selected job suffers from interruption by other jobs that are available but unfinished. This situation arises in a wide variety of applications; for example, administration, manufacturing, and process and project management. Several classical solution methods for scheduling problems no longer apply in the presence of multitasking. The solvability of any scheduling problem under multitasking is no easier than that of the corresponding classical problem. We develop optimal algorithms for some fundamental and practical single machine scheduling problems with multitasking. For other problems, we show that they are computationally intractable, even though in some cases the corresponding problem in classical scheduling is efficiently solvable. We also study the cost increase and value gained due to multitasking. This analysis informs companies about how much it would be worthwhile to invest in measures to reduce or encourage multitasking.     

A Comparison of Some Methods for the Selection of a Common Eigenvector Model for the Covariance Matrices of Two Groups

Two new nonparametric common principal component model selection procedures based on bootstrap distributions of the vector correlations of all combinations of the eigenvectors from two groups are proposed. The performance of these methods is compared in a simulation study to the two parametric methods previously suggested by Flury in 1988, as well as modified versions of two nonparametric methods proposed by Klingenberg in 1996 and then by Klingenberg and McIntyre in 1998. The proposed bootstrap vector correlation distribution (BVD) method is shown to outperform all of the existing methods in most of the simulated situations considered.     

A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors

This article considers a nonparametric additive seemingly unrelated regression model with autoregressive errors, and develops estimation and inference procedures for this model. Our proposed method first estimates the unknown functions by combining polynomial spline series approximations with least squares, and then uses the fitted residuals together with the smoothly clipped absolute deviation (SCAD) penalty to identify the error structure and estimate the unknown autoregressive coefficients. Based on the polynomial spline series estimator and the fitted error structure, a two-stage local polynomial improved estimator for the unknown functions of the mean is further developed. Our procedure applies a prewhitening transformation of the dependent variable, and also takes into account the contemporaneous correlations across equations. We show that the resulting estimator possesses an oracle property, and is asymptotically more efficient than estimators that neglect the autocorrelation and/or contemporaneous correlations of errors. We investigate the small sample properties of the proposed procedure in a simulation study.     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.