Benchmarking in the Dutch Waste-Water Treatment Sector

The Dutch water boards have recently completed a performance measurement and evaluation project for waste-water treatment. This project was intended to strengthen the boards' accountability to their stakeholders and to identify starting points for performance improvement. The Balanced Scorecard was used as a framework to develop a broad set of performance indicators. This article describes the benchmarking project and how the Dutch water boards intend to use the results to improve performance. Finally, the Dutch project is compared with the UK's Best Value project.     

The rise of defensive engineering: how personal liability considerations impact decision-making

Abstract

Based on a survey of Australian engineers (n = 275) this paper examines the impact of personal liability considerations on engineering decision-making. Almost all respondents who make high-stakes decisions saw questions of liability as having both positive (90%) and negative (87%) impacts. Our analysis shows that awareness of personal liability acts to focus the attention of many engineers on the moral dimension of their work. However, it also encourages more expensive decision-making, inhibition of innovation and professional paralysis. We argue that while personal legal liability is a legitimate way to focus engineers’ attention on the potential impact of their work, a problem arises when decision-makers are held responsible for disasters over which they had little control. The focus then shifts to ‘defensive engineering’ practices that are aimed at limiting individual liability rather than disaster prevention. Legal processes that are seen to unfairly allocate blame do not encourage practices that support future disaster prevention.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Equity in Financing Primary and Secondary Education

Abstract . Per pupil educational costs for Kansas counties are analyzed according to degree to which the county is rural. The loss or gain due to migration of educated young people is then added into the costs. Those costs are then compared to ability to pay according to a number of indicators in each category of the county. The impact of various forms of taxation to support schools is analyzed. Rural counties spend more per pupil and pay higher per capita property taxes. The differences in cost between rural and urban areas is even greater when the effects of migration are included. Household incomes tend to be lower in more rural counties. The effects of a court-ordered change in school finance will increase the inequalities between rural and urban areas. It is contended that reliance on the property tax contributes highly to this inequality.     

The optimal trade-off between interest rate risk and annual return of bond ladders

Bond laddering is a popular fixed-income investment strategy. The main purpose of this paper is to develop a methodology for determining private investors’ most interest rate risk (IRR)-return-efficient investment horizon for bond ladders (BLs), which are virtually free of credit risk. Two IRR measures of a continuously rolling and homogenous BL (CRHBL) are analytically derived under the assumption that interest rates are martingales. The first measure is the modified duration, which assumes a flat term structure of interest rates. However, this assumption is not fully supported by the empirical data and, thus, an additional IRR measure is proposed. Under each of these two measures, the ratios between the annual return in excess of the demand deposit rate and IRR of CRHBLs with different investment horizons are calculated. As expected, CRHBLs with rather low IRR are most risk-return-efficient. The results for the theoretical CRHBLs also apply to “real-world” discrete BLs. Thus, the proposed methodology can help private investors construct IRR-return-efficient discrete BLs.     

The Tipping Point of Design: How Product Design and Brands Interact to Affect Consumers’ Preferences

Existing research on product design has demonstrated the importance of aesthetics in generating favorable consumer responses. However, the literature has only recently begun to explore if and to what extent the impact of product design is influenced by brand strength. Whereas some research indicates that strong brands may benefit less strongly from aesthetically attractive designs, other research suggests that attractive designs are more persuasive when they are paired with a strong brand. In this research, these two competing predictions were tested through three studies with German car buyers. In Study 1, participants were exposed to a fictitious car that was paired with a randomly chosen brand name. In Study 2, participants were presented with a set of existing cars and were asked to choose one. Both studies yield converging evidence and show that product design and brands interact in a positive fashion, suggesting that attractive designs exert a greater influence on consumers’ decision processes when they are accompanied by a strong brand. Study 3 extended these findings by demonstrating that strong brands only increase the impact of attractive designs when perceived risk is high but not when it is low.     

Why they moved — Emigration from the Swedish countryside to the United States, 1881–1910

Swedish emigration rates were among the highest in Europe in the late nineteenth century. The majority of the emigrants originated from the countryside. In the article the determinants of emigration from the Swedish countryside to the United States are explored using panel regression methods on a newly constructed dataset consisting of yearly observations for 20 counties over the period 1881–1910. Amidst sharp fluctuations the emigration rate declined over the long term, which is explained by a rise in the standard of living and improved employment opportunities at home. Persistent regional differences in the emigration rate are explained by regional differences in population density and emigration tradition.