Popularising Delphi method

The article reports on a methodical part of a combined substantive and methodical investigation experimenting with a new type of Policy Delphi method. The common problem defined for both parts was the question whether Delphi method could be transformed in an instrument of controlling technological change by employees. The question was answered positively by the participating (bank) employees, all union members engaged with an automatisation project, themselves. Self rating scales, an evaluation questionnaire and numerous data collected about the research process showed that the most relevant social categories of participants managed to serve as “experts” according to the high levels of cognition, effort, involvement and self-confidence required in a Delphi research project. Participants with low job level, women and non-trained union members joined in very well. The special steps required to broaden a successful participation of all categories, particular methods and techniques of information transmitting questioning and reporting, did not violate the quality of scientifically valid information gathering. So the result was a practical and scientific instrument.     

The economics of urban yard space: An “implicit-market” model for housing attributes

A theoretical housing model is developed embodying the approach of the recent hedonic price literature. Instead of focusing on a scalar “housing service” consumption measure, the model portrays housing as a commodity with two attributes: floor space and yard space. Developers react to a consumer bid-rent function, which relates dwelling rent to floor space, yard space, and location, in choosing the profit-maximizing characteristics of their housing complexes. The spatial behavior of the developer's choice variables is investigated (an interesting question is whether yards are larger farther from the urban center), and a comparative static analysis of the housing market equilibrium is presented.     

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.     

Network Structure and Airline Scheduling

This paper provides a simple analysis of the effects of network structure on the scheduling, traffic, and aircraft size choices of a monopoly airline. The analysis shows that switching to a hub-and-spoke network leads to increases in both flight frequency and aircraft size, while stimulating local traffic in and out of the hub. In addition, HS networks are shown to be preferred by the airline when travel demand is low, when flights are expensive to operate, and when passengers place a high value on flight frequency but are not excessively inconvenienced by the extra travel time required for a connecting trip. The welfare analysis shows that the flight frequency, traffic volumes, and aircraft size chosen by the monopolist are all inefficiently low under both network types. Moreover, in the most plausible case, the monopolist's network choice exhibits an inefficient bias toward the HS network, apparently reflecting an excessive desire to economize on the number of flights.     

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.     

The financing of R & D in some socialist countries of Eastern Europe

In the countries of Eastern Europe the financing of R & D represents a difficult problem in terms of economic scientific policy. In these countries it is not only a question of a simple apportionment of centrally-held financial means to subordinate institutions, but also one of supporting promising fields of science, protecting long-term and costly research programmes against risks and losses, and, above all, providing an incentive for R & D institutions to work out economically meaningful R & D results and translate them into economic practice. This last point is of particular importance in a system lacking a free market mechanism. A historical survey of the development of financing methods in the R & D field and of the numerous attempts to reform these methods will show the extent of the efforts made in Eastern Europe (whether successfully or not does not concern us here) to find an adequate solution to these problems.