Structural Decomposition Analysis of Physical Flows in the Economy

Many environmental problems can be attributedto the extraction and emissions of physicalsubstances. Increasing our understanding of theeconomic and technological driving forcesbehind these physical flows can contribute tosolving the environmental problems related tothem. The input-output framework is a usefulsetting in which to integrate detailedinformation about economic structure andphysical flows. In this article a specificmethod in input-output analysis is reviewed,namely Structural Decomposition Analysis (SDA).It is based on comparative static analysis,which decomposes historical changes of a policyvariable into determinant effects. SDA has beenapplied, for example, to analyze the demand andtechnological driving forces of energy use,CO₂-emissions and various other pollutantsand resources. This article examines thetheoretical aspects of structuraldecomposition, in particular those concerningphysical flows and environmental issues.Furthermore, the article includes an extensivesurvey of empirical studies.     

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.     

The product elimination function

Historically, major consideration given to product management has focused on research and development or the introductory stage of the product life cycle. The authors present an empirical study delineating the variables to be considered in the product elimination process. More specifically, the elimination process is evaluated under a situation of poor product performance despite a generally viable market. The basic objectives of the study were: to determine the significant variables in the product elimination process of the Small Appliance Industry; to determine the relative importance of the variables; to examine the interaction among variables. The data obtained through personal structured questionnaire interviews were analyzed and provided a ranking of twenty-six variables relevant to the elimination process. Moreover, the Johnson's Hierarchical Clustering Schemes was applied to determine the interaction among variables. The results indicate that profitability and financial variables are most significant in the elimination decision-process. Second, the primary clusters of importance are concerned with market share, market growth rate, consumer awareness, and competitive action.     

Distance in organizations

There is perhaps no construct that is so fundamental to interpersonal interactions in organizations, yet so incompletely understood, than distance. Part of the difficulty in developing a comprehensive and informed understanding of the role distance plays in organizations is that theory and research in this area have been quite fragmented, focusing on narrow aspects of the construct and lacking the integration necessary to build a more general knowledge base. For example, Graen (1976) has contributed greatly to our understanding of one aspect of distance, presenting a model based on role theory whereby in-group and out-group members are hypothesized to enjoy different rewards, benefit from different leadership behaviors, and experience different levels of satisfaction and performance ratings based on relative closeness (or distance) in their working relationship with their supervisor. Other researchers have explored the phenomena of psychological distance (Rothaus, Morton, & Hanson 1965), spatial distance (Kerr & Jermier 1978; Ferris & Rowland 1985), and physical distance (Sundstrom, Burt, & Kamp 1980; Sundstrom 1986) in the supervisor-subordinate relationship. This research, although a good starting point, does not adequately define or integrate the various aspects of distance in organizations. This article represents an effort to develop a broader and more extensive understanding of the role distance plays in organizations by integrating the various types of distance into a theoretical model. A model of Dyadic Distance in the supervisor-subordinate relationship is presented which develops the new constructs of Dyadic, Psychological, Structural, and Functional Distance, examines their process dynamics and impact on Human Resource Management issues such as performance evaluations and turnover, and proposes needed directions for future research in this important area.     

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.