A gamma goodness-of-fit test based on characteristic independence of the mean and coefficient of variation

Characterization theorems in probability and statistics are widely appreciated for their role in clarifying the structure of the families of probability distributions. Less well known is the role characterization theorems have as a natural, logical and effective starting point for constructing goodness-of-fit tests. The characteristic independence of the mean and variance and of the mean and the third central moment of a normal sample were used, respectively, by Lin and Mudholkar [1980. A simple test for normality against asymmetric alternatives. Biometrika 67, 455–461] and by Mudholkar et al. [2002a. Independence characterizations and testing normality against skewness-kurtosis alternatives. J. Statist. Plann. Inference 104, 485–501] for developing tests of normality. The characteristic independence of the maximum likelihood estimates of the population parameters was similarly used by Mudholkar et al. [2002b. Independence characterization and inverse Gaussian goodness-of-fit. Sankhya A 63, 362–374] to develop a test of the composite inverse Gaussian hypothesis. The gamma models are extensively used for applied research in the areas of econometrics, engineering and biomedical sciences; but there are few goodness-of-fit tests available to test if the data indeed come from a gamma population. In this paper we employ Hwang and Hu's [1999. On a characterization of the gamma distribution: the independence of the sample mean and the sample coefficient of variation. Ann. Inst. Statist. Math. 51, 749–753] characterization of the gamma population in terms of the independence of sample mean and coefficient of variation for developing such a test. The asymptotic null distribution of the proposed test statistic is obtained and empirically refined for use with samples of moderate size.     

Cash flow models: A review

Cash flow management is concerned with the efficient use of the company's cash and short-term investments. Under stable economic conditions, this is a matter of deciding when to transfer assets and how much. The development of models designed to answer these questions is reviewed. More recently, emphasis has been placed on decisions concerned with operating conditions with the object of maintaining a level of cash flow in accordance with unstable conditions, in particular with a high rate of inflation.     

Why older Australians participate in exercise and sport

Research on variables that encourage older adults to exercise is limited. This study was carried out to identify the participation motives of older Australians involved in regular exercise and sport. The 815 participants (399 men, 416 women) ranged in age from 55 to 93 years (M = 63.6, SD = 7.8) and were participating in their activities of choice at least once per week. All participants completed the Participation Motivation Questionnaire for Older Adults. The most common exercise/sport activities that participants were involved in were walking, golf, lawn bowls, tennis, and swimming. The most highly reported motives for participation were to keep healthy, liking the activity, to improve fitness, and to maintain joint mobility. Principal-components analysis of the questionnaire revealed 6 factors: social, fitness, recognition, challenge/benefits, medical, and involvement. Analyses of variance showed significant differences in reasons for participation in exercise and sport based on gender, age, education level, and occupation.     

Women's Employment in Transition, 1992–4: the Case of Poland

Since the early 1990s the Polish economy has, in the move towards a market economy, undergone substantial economic reforms which resulted initially in a severe recession and notably in widespread unemployment. In a country where women have traditionally played a major role in the workforce it is pertinent to ask how their role has been affected during the early years of transition to a market economy, what factors explain this, and what their employment prospects are likely to be in a free market economy. After sketching the key features of women's employment in Poland pre-transition the article then addresses these questions using data drawn mainly from the Labour Force Surveys of 1992 and 1994. It finds that women's labour market position has been changing and in 1994 could be said to be mixed: while on the one hand it seems to be deteriorating (rising rates of inactivity and unemployment, the feminization of part-time work), on the other women seem to have been relatively protected from the worst effects of marketization and are in a better position than men according to some unemployment indicators. Prospects for women's employment under a free market economy also appear to be mixed, with much depending on whether the Polish government introduces a framework of national measures to support and encourage women who enter into paid employment.     

Integrating risk assessment and life cycle assessment: a case study of insulation.

Increasing residential insulation can decrease energy consumption and provide public health benefits, given changes in emissions from fuel combustion, but also has cost implications and ancillary risks and benefits. Risk assessment or life cycle assessment can be used to calculate the net impacts and determine whether more stringent energy codes or other conservation policies would be warranted, but few analyses have combined the critical elements of both methodologies In this article, we present the first portion of a combined analysis, with the goal of estimating the net public health impacts of increasing residential insulation for new housing from current practice to the latest International Energy Conservation Code (IECC 2000). We model state-by-state residential energy savings and evaluate particulate matter less than 2.5 microm in diameter (PM2.5), NOx, and SO2 emission reductions. We use past dispersion modeling results to estimate reductions in exposure, and we apply concentration-response functions for premature mortality and selected morbidity outcomes using current epidemiological knowledge of effects of PM2.5 (primary and secondary). We find that an insulation policy shift would save 3 x 10(14) British thermal units or BTU (3 x 10(17) J) over a 10-year period, resulting in reduced emissions of 1,000 tons of PM2.5, 30,000 tons of NOx, and 40,000 tons of SO2. These emission reductions yield an estimated 60 fewer fatalities during this period, with the geographic distribution of health benefits differing from the distribution of energy savings because of differences in energy sources, population patterns, and meteorology. We discuss the methodology to be used to integrate life cycle calculations, which can ultimately yield estimates that can be compared with costs to determine the influence of external costs on benefit-cost calculations.     

The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*

An auditor gives a going concern uncertainty opinion when the client company is at risk of failure or exhibits other signs of distress that threaten its ability to continue as a going concern. The decision to issue a going concern opinion is an unstructured task that requires the use of the auditor's judgment. In cases where judgment is required, the auditor may benefit from the use of statistical analysis or other forms of decision models to support the final decision. This study uses the generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model to predict which firms would receive audit reports reflecting a going concern uncertainty modification. The GRG2 optimizer has previously been used as a more efficient optimizer for solving business problems. The neural network model formulated using GRG2 has the highest prediction accuracy of 95 percent. It performs best when tested with a small number of variables on a group of data sets, each containing 70 observations. While the logit procedure fails to converge when using our eight variable model, the GRG2 based neural network analysis provides consistent results using either eight or four variable models. The GRG2 based neural network is proposed as a robust alternative model for auditors to support their assessment of going concern uncertainty affecting the client company.     

Revising Infant Mortality Rates for the Early Twentieth Century United States

Accurate vital statistics are required to understand the evolution of racial disparities in infant health and the causes of rapid secular decline in infant mortality during the early twentieth century. Unfortunately, U.S. infant mortality rates prior to 1950 suffer from an upward bias stemming from a severe underregistration of births. At one extreme, African American births in southern states went unregistered at the rate of 15 % to 25 %. In this study, we construct improved estimates of births and infant mortality in the United States for 1915–1940 using recently released complete count decennial census microdata combined with the counts of infant deaths from published sources. We check the veracity of our estimates with a major birth registration study completed in conjunction with the 1940 decennial census and find that the largest adjustments occur in states with less-complete birth registration systems. An additional advantage of our census-based estimation method is the extension backward of the birth and infant mortality series for years prior to published estimates of registered births, enabling previously impossible comparisons and estimations. Finally, we show that underregistration can bias effect estimates even in a panel setting with specifications that include location fixed effects and place-specific linear time trends.