Does the dutch model really exist?

The policy that led from the "Dutch disease" (in the 1980s) to the "Dutch miracle" (in the 1990s) consists of three tracks: wage moderation, retrenching public expenditure and reducing the tax burden, and slimming the welfare system. The wage moderation track seems to have been the most important. The term "Dutch model" refers to the socioeconomic system of the Netherlands. Most observers point particularly to the relatively low unemployment rate to indicate the success of this model. However, the economic inactivity rate in the Netherlands is not lower than in neighboring countries. This suggests that open unemployment in the Netherlands has been partly replaced with hidden unemployment. In particular, the disability scheme seems to contain a large component of hidden unemployment. Another feature of the Dutch model is its consensus-seeking nature, which is fostered by its institutional structure.     

Regulating an externality-generating public utility: A multi-dimensional screening approach

In this paper, I present a monopoly screening model in which a firm holds private information on fixed abatement costs. Because of the nature of the optimal contracts, bunching is never optimal even with ‘n’ distinct types. A characterization of full and limited information solutions is offered and it is shown that the design standards alone determine the value of an information rent. The variable charge is completely free of any marginal information costs. This allows the variable charge to track marginal damages and thereby ensures that marginal social costs are covered. A fixed charge implements the optimal solution.     

Natural conjugate priors for the instrumental variables regression model applied to the Angrist–Krueger data

We propose a natural conjugate prior for the instrumental variables regression model. The prior is a natural conjugate one since the marginal prior and posterior of the structural parameter have the same functional expressions which directly reveal the update from prior to posterior. The Jeffreys prior results from a specific setting of the prior parameters and results in a marginal posterior of the structural parameter that has an identical functional form as the sampling density of the limited information maximum likelihood estimator. We construct informative priors for the Angrist–Krueger [1991. Does compulsory school attendance affect schooling and earnings? Quarterly Journal of Economics 106, 979–1014] data and show that the marginal posterior of the return on education in the US coincides with the marginal posterior from the Southern region when we use the Jeffreys prior. This result occurs since the instruments are the strongest in the Southern region and the posterior using the Jeffreys prior, identical to maximum likelihood, focusses on the strongest available instruments. We construct informative priors for the other regions that make their posteriors of the return on education similar to that of the US and the Southern region. These priors show the amount of prior information needed to obtain comparable results for all regions.     

Fit performance of several programs used for non-linear least squares problems

Seven computerprograms for non-linear regression or curve fitting problems are compared. The comparison of the programs, running in different computing centra, is restricted to the fit performance. Six model functions are fitted according to the least squares criterion to data series, arising from practical work. The special least squares minimization programs turned out to be better suited for these problems than general optimizing programs.     

Dynamic modelling of pollution abatement in a CGE framework

This paper deals with the specification of pollution abatement in dynamic computable general equilibrium (CGE) models and analyses the dynamic feedback mechanisms between economy and abatement in the context of environmental policy. A Ramsey-type economic model is presented, in which bottom-up technical and economic information on abatement techniques is integrated in a top-down dynamic CGE context. The practical suitability of the specification is illustrated by an empirical application for climate change and acidification in the Netherlands. The results show that a mixture of some slowdown of economic growth, a substantial restructuring of the economy and implementation of most technical abatement measures is optimal.     

Model selection in random effects models for directed graphs using approximated Bayes factors

With the development of an MCMC algorithm, Bayesian model selection for the p ₂ model for directed graphs has become possible. This paper presents an empirical exploration in using approximate Bayes factors for model selection. For a social network of Dutch secondary school pupils from different ethnic backgrounds it is investigated whether pupils report that they receive more emotional support from within their own ethnic group. Approximated Bayes factors seem to work, but considerable margins of error have to be reckoned with.     

Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA

Pareto-Koopmans efficiency in Data Envelopment Analysis (DEA) is extended to stochastic inputs and outputs via probabilistic input-output vector comparisons in a given empirical production (possibility) set. In contrast to other approaches which have used Chance Constrained Programming formulations in DEA, the emphasis here is on joint chance constraints. An assumption of arbitrary but known probability distributions leads to the P-Model of chance constrained programming. A necessary condition for a DMU to be stochastically efficient and a sufficient condition for a DMU to be non-stochastically efficient are provided. Deterministic equivalents using the zero order decision rules of chance constrained programming and multivariate normal distributions take the form of an extended version of the additive model of DEA. Contacts are also maintained with all of the other presently available deterministic DEA models in the form of easily identified extensions which can be used to formalize the treatment of efficiency when stochastic elements are present.     

Integrating ecosystem services into conservation assessments: A review

A call has been made for conservation planners to include ecosystem services into their assessments of conservation priority areas. The need to develop an integrated approach to meeting different conservation objectives and a shift in focus towards human wellbeing are some of the motivations behind this call. There is currently no widely accepted approach to planning for ecosystem services. This study contributes towards the development of this approach through a review of conservation assessments and the extent to which they include ecosystem services. Of the 476 conservation assessments identified by a set of search terms on the Web of Science, 100 were randomly selected for this review. Of these only seven had included ecosystem services, while another 13 had referred to ecosystem services as a rationale for conservation without including them in the assessment. The majority of assessments were based on biodiversity pattern data while 19 used data on ecological processes. A total of 11 of these 19 assessments used processes, which could be linked to services. Ecosystem services have witnessed an increase in attention received in conservation assessments since the year 2000, however trends were not apparent beyond this date. In order to assess which types of ecosystem services and how they have been accounted for in conservation assessments, we extended our review to include an additional nine conservation assessments which included ecosystem services. The majority included cultural ecosystem services, followed by regulatory, provisioning and supporting services respectively. We conclude with an analysis of the constraints and opportunities for the integration of ecosystem services into conservation assessments and highlight the urgent need for an appropriate framework for planning for ecosystem services.