Empirical Prediction Intervals for County Population Forecasts

Population forecasts entail a significant amount of uncertainty, especially for long-range horizons and for places with small or rapidly changing populations. This uncertainty can be dealt with by presenting a range of projections or by developing statistical prediction intervals. The latter can be based on models that incorporate the stochastic nature of the forecasting process, on empirical analyses of past forecast errors, or on a combination of the two. In this article, we develop and test prediction intervals based on empirical analyses of past forecast errors for counties in the United States. Using decennial census data from 1900 to 2000, we apply trend extrapolation techniques to develop a set of county population forecasts; calculate forecast errors by comparing forecasts to subsequent census counts; and use the distribution of errors to construct empirical prediction intervals. We find that empirically-based prediction intervals provide reasonably accurate predictions of the precision of population forecasts, but provide little guidance regarding their tendency to be too high or too low. We believe the construction of empirically-based prediction intervals will help users of small-area population forecasts measure and evaluate the uncertainty inherent in population forecasts and plan more effectively for the future.     

Eigenverantwortung — Berufliche Leistung und Anforderung

Ohne Zusammenfassung     

Asymptotic Representations of the Multivariate Empirical Distribution Function and Applications

Often, many complicated statistics used as estimators or test statistics take the form of the (multivariate) empirical distribution function evaluated at a random vector (V_n). Denote such statistics by S_n. This paper describes methods for the study of various asymptotic properties of S_n. First, under minimal assumptions, a weak asymptotic representation for S_n is derived. This result may be used to show the asymptotic normality of S_n. Second, under slightly more stringent regularity conditions, an almost sure representation of S_n, with suitable order (as.) of the remainder term is studied and then a law of the iterated logarithm for S_n, is derived. In this context, strong convergence results from a sequential point of view are also studied. Finally, weak convergence to a Brownian motion process is established. As an application, we show the limiting normality of S_n, for a random number of summands.     

The sample census of population in Poland, 1949

In this note the author describes the sample census of Poland that was taken after the end of the war. He explains the method by which the sample was selected and the type of information that can be obtained from it.     

Stochastic orders and non-Gaussian risk factor models

The main results of this paper are monotonicity statements about the risk measures value-at-risk (VaR) and tail value-at-risk (TVaR) with respect to the parameters of single and multi risk factor models, which are standard models for the quantification of credit and insurance risk. In the context of single risk factor models, non-Gaussian distributed latent risk factors are allowed. It is shown that the TVaR increases with increasing claim amounts, probabilities of claims and correlations, whereas the VaR is in general not monotone in the correlation parameters. To compare the aggregated risks arising from single and multi risk factor models, the usual stochastic order and the increasing convex order are used in this paper, since these stochastic orders can be interpreted as being induced by the VaR-concept and the TVaR-concept, respectively. To derive monotonicity statements about these risk measures, properties of several further stochastic orders are used and their relation to the usual stochastic order and to the increasing convex order are applied.     

The meaning of nonprofit advocacy: An ordonomic perspective

Orthodox economic theories of the nonprofit sector are focused on its service delivery role but have little to say about nonprofit advocacy. This study explains nonprofit advocacy by building upon the ordonomic approach, a recently developed strand of institutional economics that explores the interdependencies between institutions and ideas. From the ordonomic perspective, the evolution of a modern society occurs through an ongoing realignment between institutions and ideas. The meaning of nonprofit advocacy is shown to be in contributing to this realignment. This leads to a new understanding of the service delivery role of the nonprofit sector. This role is shown to have a compensatory character in that it is intended to maintain a reasonable quality of human life before the time-consuming ideational and institutional adjustments actually take place.     

International work experience and compensation: Is more always better for CFOs?

The CFO is increasingly considered the second most important executive in the firm after the CEO. Still, little is known about the factors that determine CFOs' compensation. Recently, it has often been claimed that, in MNCs, CFOs should have international work experience. But is a CFO's international work experience also reflected in his or her compensation? We combine human capital and social capital perspectives to account for both the upside and the downside of international work experience. We suggest that working abroad provides CFOs with valuable knowledge and skills which increase compensation; however, staying abroad for too long has an adverse effect due to losses in social network ties. We thus propose an inverted U-shaped relationship between CFOs' international work experience and their compensation. Furthermore, we suggest that this relationship is contingent on the characteristics of the CEO. In testing our hypotheses on a sample of the largest MNCs in Europe, we find support for the proposed relationships. Our study contributes to the literature on top management characteristics and executive compensation, specifically by providing a comprehensive understanding of how and when international work experience pays off for CFOs.     

Energy crop production in an urban area: a comparison of habitat types and land use forms targeting economic benefits and impact on species diversity

In urban areas, the potential of biomass production is rarely utilized, although many biomass sources are located in cities, ranging from road margins to public parks. There is, however, increasing interest in these potential biomass sources, as they are close to consumers and provide options to reduce maintenance costs of urban green areas. We analyzed the costs and benefits of utilizing biomass, and compared it to the biodiversity maintained on 17 urban land use forms the Ruhr Metropolitan Area (Germany). Economic costs and benefits were reflected by contribution margins, while biodiversity was measured by species numbers of plants, birds and butterflies. For the 17 land use types, there is a weak overall correlation between contribution margins and species numbers. However, this is mainly due to the two land use forms with the highest contribution margins (cultivation of energy maize and fertilized grassland), which are characterized by the lowest species numbers. For the remaining cases, there is no relationship between contribution margins and species numbers. Comparatively high contribution margins and high mean species numbers were observed for road margins, industrial fallows with wood cutting for biogas production and water-influenced grassland mown traditionally. We conclude that biomass production and the maintenance of urban biodiversity is not necessarily a contradiction.