Population Projections by Age for Florida and its Counties: Assessing Accuracy and the Impact of Adjustments

Projections of total population have been evaluated extensively, but few studies have investigated the performance of projections by age. Of those that did, most focused on projections for countries or other large areas. In this article, we evaluate projections by age for Florida and its counties, as produced and published between 1996 and 2010 by the Bureau of Economic and Business Research at the University of Florida. We first compare the precision and bias of projections of total population with the precision and bias of projections by age, at both the state and county levels. This is followed by a more detailed examination of county-level projection errors for individual age groups, first in the aggregate and then disaggregated by sex and population size. The second part of the analysis focuses on a number of adjustments that were implemented in projections published in 2006 and 2009. Intended to improve accuracy, these adjustments involved updates to the base population, fertility rates, and survival rates. We compare the accuracy of projections incorporating these adjustments with the accuracy of projections excluding them. We believe this study offers a unique opportunity to examine a variety of characteristics regarding the forecast accuracy of small-area population projections by age.     

An Experimental Test of Loss Aversion

This paper experimentally investigates a preference condition for loss aversion in the framework of cumulative prospect theory (CPT). We propose the concepts of absolute and relative loss premiums in order to measure the extent of loss aversion and to derive notions of increasing, constant, and decreasing loss aversion. While in only one of the 28 choice situations analyzed loss neutrality and loss seeking can be rejected, about 51% of all choices are loss averse and, due to the large extent of loss aversion revealed by these choices, the average loss premium is positive for most choice situations. Female subjects exhibit both a more frequent occurrence and a larger extent of loss aversion.     

Regulated Competition in Social Health Insurance: A Three-Country Comparison

The objectives guiding healthcare reforms in Germany, Switzerland and the Netherlands were to increase efficiency and consumer satisfaction in the provision of healthcare services. This paper reviews the incentives for and instruments of competition for consumers, sickness funds and healthcare providers in these three countries which are necessary to fulfil these objectives. Incentives for risk selection of sickness funds are high in Germany and Switzerland while they are low in the Netherlands. Incentives for consumer choice are also highest in Germany and Switzerland. In all three countries sickness funds have only a few instruments of competition. The effects of competition have been disappointing so far. The objectives of competitive healthcare reforms can be achieved only if incentives for and instruments of competition consistently support competitive behaviour on the part of market actors.     

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.     

Ecosystem services of urban green spaces in African countries—perspectives and challenges

The concept of ecosystem goods and services is increasingly used to describe how biodiversity and ecosystems are linked to human well-being and that it should be placed at the core of sustainable urban development. Predictions of a tremendous future increase of urbanization in Africa necessitate an investigation into the research on ecosystem goods and services in the urban green infrastructure of Africa. Ecosystem goods and services (ES) are described as the benefits humans derive directly or indirectly from ecosystem functions and are classified as supporting, provisioning, regulating and cultural services. A literature study focusing on journal papers was conducted. Additionally a case study based on two masters studies was further refined. ES studies in African cities are biased towards South Africa and include assessments and economic valuations in which several different methods were used to determine direct consumptive and non-consumptive and indirect use values. Emphasis was placed on the multifunctional nature of ES. The main objectives of these studies were to sensitize policy makers, planners and the general public about the importance of biodiversity and ES. Ecosystem-based adaptation is discussed as the most appropriate approach in terms of applying knowledge about ES and their values in African cities as many residents still rely on ES from natural areas, but the major ecological, economic and political challenges are acknowledged. A case study focusing on domestic gardens (private green spaces) have indicated that the demand and supply of certain ES differ along a socio-economic gradient due to poor service delivery and smaller plots in the poorer areas mainly due to the legacy of separate development of the past. Where provisioning services are mainly outsourced in cities, it was found that plant species useful as food, medicine, etc. were more frequent in the gardens of poorer residents than in those of more affluent areas. The tendency to pay more for residential properties close to public open spaces, as in Europe, could not be statistically proven in the more affluent areas of a South African city, although the property values in proximity of public open spaces in some of the areas studied were lower than further away.     

Strategic Grading in the Product Acquisition Process of a Reverse Supply Chain

Most recommerce providers have moved to a quality‐dependent process for the acquisition of used products. They acquire the products via websites at which product holders submit upfront quality statements and receive quality‐dependent acquisition prices for their used devices. Motivated by this development of reverse logistics practice, the aim of this study is to analyze the product assessment process of a recommerce provider in detail. To this end, we first propose a sequential bargaining model with complete information which captures the individual behavior of the recommerce provider and the product holder. We determine the optimal strategies of the product holder and the recommerce provider in this game. We find that the resulting strategies lead to an efficient allocation, although the recommerce provider can absorb most of the bargaining potential due to his last mover advantage. In a second step, we relax the assumption of complete information and include uncertainty about the product holder's valuation of the product. We show the trade‐off underlying the recommerce provider's optimal counteroffer decision and analyze the optimal strategy, using a logistic regression approach on a real‐life dataset of nearly 6,000 product submissions. The results reveal a significant improvement potential, compared to the currently applied strategy.