Swedish employment offices: A new model for evaluating effectiveness

We measure how well Swedish employment offices perform in delivering the services required of them by the Swedish government. In contrast to earlier studies we use a dynamic efficiency framework, which allows us to better model the intertemporal nature of these services, explicitly allowing for placements of intermediate nature across periods. Rather than using second stage analysis to assess the effects of varying local labor market conditions and differences in client characteristics on performance, we include a measure of the office’s expected work load directly in the model. This measure, derived from duration analysis, is designed to capture the variation across offices in resources needed before an average individual can obtain employment. It is estimated from the characteristics of all unemployed individual and local labor market conditions.     

A new multicriteria approach for the analysis of efficiency in the Spanish olive oil sector by modelling decision maker preferences

The efficiency in production is often analysed as technical efficiency using the production frontier function. Efficiency scores are usually based on distance computations to the frontier in an m + s-dimensional space, where m inputs produce s outputs. In addition, efficiency improvements consider the total consumption of each input. However, in many cases, the “consumption” of each input can be divided into input-consumption sections (ICSs), and trade-off among the ICSs is possible. This share framework can be used for computing efficiency. This analysis provides information about both the total optimal consumption of each input, as does data envelopment analysis, and the most efficient allocation of the “consumption” among the ICSs. This paper studies technical efficiency using this approach and applies it to the olive oil sector in Andalusia (Spain). A non-parametrical methodology is presented, and an input-oriented Multi-Criteria Linear Programming model (MLP) is proposed. The analysis is developed at global, input and ICSs levels, defining the extent of satisfaction achieved at all these levels for each company, in accordance with their own preferences. The companies’ preferences are modelled with their utility function and their set of weights. MLP offers more detailed information to assist decision makers than other models previously proposed in the literature. In addition to this application, it is concluded that there is room for improvement in the olive oil sector, particularly in the management of the skilled labour. Additionally, the solutions with two opposite scenarios indicate that the model is suitable for the intended decision making process.     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

A dual-interval vertex analysis method and its application to environmental decision making under uncertainty

In this study, a dual-interval vertex analysis (DIVA) method is developed, through incorporating the vertex method within an interval-parameter programming framework. The developed DIVA method can tackle uncertainties presented as dual intervals that exist in the objective function and the left- and right-hand sides of the modeling constraints. An interactive algorithm and a vertex analysis approach are proposed for solving the DIVA model. Solutions under an associated α-cut level can be generated by solving a series of deterministic submodels. They can help quantify relationships between the objective function value and the membership grade, which is meaningful for supporting in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability. A management problem in terms of regional air pollution control is studied to illustrate applicability of the proposed approach. The results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers to identify desired pollution-abatement strategies with minimized costs and maximized environmental efficiencies.     

A simplex algorithm for piecewise-linear programming III: Computational analysis and applications

The first two parts of this paper have developed a simplex algorithm for minimizing convex separable piecewise-linear functions subject to linear constraints. This concluding part argues that a direct piecewiselinear simplex implementation has inherent advantages over an indirect approach that relies on transformation to a linear program. The advantages are shown to be implicit in relationships between the linear and piecewise-linear algorithms, and to be independent of many details of implementation. Two sets of computational results serve to illustarate these arguments; the piecewise-linear simplex algorithm is observed to run 2–6 times faster than a comparable linear algorithm, not including any additional expense that might be incurred in setting up the equivalent linear program. Further support for the practical value of a good piecewise-linear programming algorithm is provided by a survey of many varied applications.This research has been supported in part by the National Science Foundation under grant DMS-8217261.     

Organization and efficiency in the international insurance industry: A cross-frontier analysis

This paper employs cross-frontier analysis, an innovative tool based on data envelopment analysis, to provide new insight into the relationship between organization and efficiency in international insurance markets. We are the first to empirically test the expense preference hypothesis and the efficient structure hypothesis in a large cross-country study. For this purpose, we consider 23,807 firm-years for 21 countries from northern America and the European Union—a dataset not previously analyzed in this context. We find evidence for the efficient structure hypothesis in selected market segments, but we find no evidence for the expense preference hypothesis. Our results provide insight into the competitiveness of stock and mutual insurers from different countries. At the country level, the results can be used to compare different insurance markets. Our findings are especially interesting for the strategic management of insurance companies as well as for regulators and boards of national insurance associations.     

A recursive linear programming analysis of the future of the pulp and paper industry in the United States: Changes in supplies and demands,and the effects of recycling

The impacts of increased paper recycling on the U.S. pulp and paper sector are investigated, using the North American Pulp And Paper (NAPAP) model. This dynamic spatial equilibrium model forecasts the amount of pulp, paper and paperboard exchanged in a multi-region market, and the corresponding prices. The core of the model is a recursive price-endogenous linear programming system that simulates the behavior of a competitive industry. The model has been used to make forecasts of key variables describing the sector from 1986 to 2012, demand for paper would have the greatest impact on the amount of wood used. But the minimum recycled content policies envisaged currently would have no more effect than what will come about due to unregulated market forces.     

The European regional policy and the socio-economic diversity of European regions: A multivariate analysis

There are significant differences among the European Union regions, which have been heightened due to the most recent enlargement in 2004. This paper aims to analyse this diversity and to propose a classification of European regions that is adjusted to the different axes of socio-economic development and, simultaneously, is useful for European regional policy purposes. Multivariate statistical techniques allow the identification of clusters of socio-economic similarity, which are contrasted with the classes considered in the financial proposal of the European Commission (EC) for the period 2007–2013.