9,275 research outputs found
Multi-Period Dea Incentive Regulation in Electricity Distribution.
No full textMulti-period multi-product regulatory schemes for electricity distributors are presented, based on cost information from a productivity analysis model and an agency theoretical decision model. The proposed schemes are operational and demonstrate considerable advantages compared to the popular CPI-X revenue cap regulation. The schemes avoid arbitrariness, too high or negative informational rents as well as ratchet effects and they promote rapid productivity catch-up by making full use of available data. More generally, the paper contributes to the theoretical unification between firm-based Data Envelopment Analysis (DEA) productivity models and micro-economic reimbursement theories.Regulation; Efficiency analysis; Incentive systems
DEA-Based Incentive Regimes in Health-Care Provision
No full textA major challenge to legislators, insurance providers and municipalities will be how to manage the reimbursement of health-care on partially open markets under increasing fiscal pressure and an aging population. Although efficiency theoretically can be obtained by private solutions using fixed-payment schemes, the informational rents and production distortions may limit their implementation. The healthcare agency problem is characterized by (i) a complex multi-input multi-output technology, (ii) information uncertainty and asymmetry, and (iii) fuzzy social preferences. First, the technology, inherently nonlinear and with externalities between factors, yield parametric estimation difficult. However, the flexible production structure in Data Envelopment Analysis (DEA) offers a solution that allows for the gradual and successive refinement of potentially nonconvex technologies. Second, the information structure of healthcare suggests a context of considerable asymmetric information and considerable uncertainty about the underlying technology, but limited uncertainty or noise in the registration of the outcome. Again, we shall argue that the DEA dynamic yardsticks (Bogetoft, 1994, 1997, Agrell and Bogetoft, 2001) are suitable for such contexts. A third important characteristic of the health sector is the somewhat fuzzy social priorities and the numerous potential conflicts between the stakeholders in the health system. Social preferences are likely dynamic and contingent on the disclosed information. Similarly, there are several potential hidden action (moral hazard) and hidden information (adverse selection) conflicts between the different agents in the health system. The flexible and transparent response to preferential ambiguity is one of the strongest justifications for a DEA-approach. DEA yardstick regimes have been successfully implemented in other sectors (electricity distribution) and we present an
operalization of the power-parameter p in an pseudo-competitive setting that both limits the informational rents and incites the truthful revelation of information. Recent work (Agrell and Bogetoft, 2002) on strategic implementation of DEA yardsticks is commented in the healthcare context, where social priorities change the tradeoff between the motivation and coordination functions of the yardstick. The paper is closed with policy recommendations and some areas of further work
DEA-Based Incentive Regimes in Health-Care Provision
No full textA major challenge to legislators, insurance providers and municipalities will be how to manage the reimbursement of health-care on partially open markets under increasing fiscal pressure and an aging population. Although efficiency theoretically can be obtained by private solutions using fixed-payment schemes, the informational rents and production distortions may limit their implementation. The healthcare agency problem is characterized by (i) a complex multi-input multi-output technology, (ii) information uncertainty and asymmetry, and (iii) fuzzy social preferences. First, the technology, inherently nonlinear and with externalities between factors, yield parametric estimation difficult. However, the flexible production structure in Data Envelopment Analysis (DEA) offers a solution that allows for the gradual and successive refinement of potentially nonconvex technologies. Second, the information structure of healthcare suggests a context of considerable asymmetric information and considerable uncertainty about the underlying technology, but limited uncertainty or noise in the registration of the outcome. Again, we shall argue that the DEA dynamic yardsticks (Bogetoft, 1994, 1997, Agrell and Bogetoft, 2001) are suitable for such contexts. A third important characteristic of the health sector is the somewhat fuzzy social priorities and the numerous potential conflicts between the stakeholders in the health system. Social preferences are likely dynamic and contingent on the disclosed information. Similarly, there are several potential hidden action (moral hazard) and hidden information (adverse selection) conflicts between the different agents in the health system. The flexible and transparent response to preferential ambiguity is one of the strongest justifications for a DEA-approach. DEA yardstick regimes have been successfully implemented in other sectors (electricity distribution) and we present an operalization of the power-parameter p in an pseudo-competitive setting that both limits the informational rents and incites the truthful revelation of information. Recent work (Agrell and Bogetoft, 2002) on strategic implementation of DEA yardsticks is commented in the healthcare context, where social priorities change the tradeoff between the motivation and coordination functions of the yardstick. The paper is closed with policy recommendations and some areas of further work.Data Envelopment Analysis, regulation, health care systems, efficiency, Health Economics and Policy,
Rethinking Regulatory Capture
No full textConventional capture models rely on the idea that regulator is induced to lenient behavior by the regulated firm through offers of monetary transfers, the bribery model, or future employment, the revolving doors model. To avoid socially costly capture, the political principal should then either implement collusion-proof mechanisms through the delegation of welfare gains, or severely restrict the career paths of regulatory staff. The paradox of capture is that neither the two modes of capture, nor the remedy are commonly found in practice. This paper proposes to rethink capture based on the widespread use of industry-commissioned consultants, experts and lobbyists that produce information for regulatory and policy use. A small model (Agrell and Gautier, 2010) introduces a 'soft capture' concept based on a self-enforced collusion between the firm and regulator, linked to the role of the regulator as information-processing intermediate for the political principal. The firm puts processed but biased information at the free disposal of the regulator, 'no strings attached', who can then either use the submitted information or produce a more accurate information by a costly process. Under a set of mild conditions, the equilibrium involves soft capture and the regulator uses the submitted information, leading to some distortions in welfare. A case study of the Occupational Safety and Health Administration (OSHA) in USA serves to motivate and illustrate the model. As shown by the case, the soft capture model may have a stronger positive potential than the conventional models, also implying that policy advice based on it may be valuable
Harmonizing the Nordic Regulation of Electricity Distribution
No full textRegulators for electricity network infrastructure, such as electricity distribution system operations (DSO) face some particular challenges in the Nordic countries. Due to institutional, economic and historical reasons the DSOs in the Nordic area are relatively numerous and heterogeneous in terms of ownership structure, size and operating conditions. Since the deregulation in 1994-1999, the national regulators have independently devised regulation mechanisms that address the heterogeneity through econometric or engineering cost models as a basis for high- powered regimes. The frontier analysis models (such as Data Envelopment Analysis in e.g. Norway and Finland) are particularly useful here, given their incentive properties and cautious estimation of the production set. However, the total information rents in yardstick regimes and the bias in the frontier estimation are related to the number of observations (firms), which undermine their future application in the Nordic area under increasing interregional concentration. This paper develops a proposal for an alternative model, the revenue-yardstick model, that can be ap- plied across the national regulations and permit frontier estimations on final user cost rather than cost estimates, sensitive to e.g. capital cost estimates, periodisation and allocation keys. The core of the model is a dynamic frontier yardstick model such as Agrell, Bogetoft and Tind (2005), but here applied only to strictly exogenous conditions, the output dimensions and the claimed revenues of the DSO. An equilibrium is implemented using asymmetric penalties for positive and negative deviations from the ex post frontier revenue, the yardstick, using the classic superefficiency model in analogy with Shleifer (1985). The model is particularly aimed at an international (interregional) application as it may embed national differences in regulation without jeopardizing the long-term sustainability of the model
Capturing heterogeneity in electricity distribution operations: a critical review of latent class modelling
No full textRecently, several articles (Cullmann, 2012; Agrell et al., 2014; Filippini and Orea, 2014; Llorca et al., 2014) address the issue of benchmarking decision making units with different technologies by using latent class models. This method groups units that have similar technology for better comparison. Under this scheme, there are two implicit assumptions: First, that each class reflects a unique technology where its elements are not outliers. Second, classes are assumed to be stationary and fixed. If this assumption is violated, the classification is transient and time-dependent, inadequate for the regulatory use suggested in the seminal papers. We apply latent class models to classify Swedish electricity distributors under different specifications. In most of the models, we identify one large class with approximately 78.4% of the DMU's and two small classes with 7.4% and 14.2% respectively. Moreover, most of small classes elements switch between categories. We contrast our parametric results with nonparametric outlier detector methods and find a relationship between identified outliers and the elements of smaller residual classes. We believe that our work is an important caveat to the adoption of latent class modelling as an alternative or remedy for conventional models, relying on a homogeneous reference set
Profit-driven planning and analysis of a WEEE recycling facility with a multi-period MILP model
No full textElectronic waste is one of the fastest-growing waste streams in the world. The challenges
associated with the recycling of Waste Electrical and Electronic Equipment (WEEE) represent
both threats, as the improper disposal of this waste can harm the environment and human health,
and opportunities, as this category of waste contains valuable and rare resources that can be
recovered and repurposed, contributing to the circular economy. The EU is leading the way in
improving the collection and treatment of WEEE, but this has not been sufficient to meet the
targets set in its WEEE directive. Therefore, additional efforts must be made to ensure the costeffective
and environmentally sound recycling of WEEE, both in the public and private sectors.
In this thesis, we propose a multi-period MILP model for the planning of a WEEE recycling
facility in Belgium and conduct various analyses to provide insights on what elements are the
most crucial to the profitability of such a facility. The originality of our approach lies in the
multi-period aspect of the model, and the addition of a limited amount of labour to be allocated
to various labour-intensive tasks of WEEE recycling. Our main findings are that labour is the
most critical resource, both in cost and utilization, such that the optimal quantity of WEEE to
process is the one that results in complete utilization of labour, with little to no overtime. As
such, the flexibility of labour, both in possible task allocation and overtime capabilities, is
crucial to the proper functioning of the facility, especially when taking into account possible
deviations from the optimal plan, caused by the heterogeneity of WEEE and other variations
such as the timing of deliveries.nhhma
Pharmacogenetics of ophthalmic topical β-blockers
No full textGlaucoma is the second leading cause of blindness worldwide. The primary glaucoma risk factor is elevated intraocular pressure. Topical β-blockers are affordable and widely used to lower intraocular pressure. Genetic variability has been postulated to contribute to interpersonal differences in efficacy and safety of topical β-blockers. This review summarizes clinically significant polymorphisms that have been identified in the β-adrenergic receptors (ADRB1, ADRB2 and ADRB3). The implications of polymorphisms in CYP2D6 are also discussed. Although the candidate-gene approach has facilitated significant progress in our understanding of the genetic basis of glaucoma treatment response, most drug responses involve a large number of genes, each containing multiple polymorphisms. Genome-wide association studies may yield a more comprehensive set of polymorphisms associated with glaucoma outcomes. An understanding of the genetic mechanisms associated with variability in individual responses to topical β-blockers may advance individualized treatment at a lower cost
Multiple Objective Optimisation in Agro-ecological Land Use Planning
No full textA new interactive decision support system for agro-ecological land use planning in developing countries is presented. The optimization system is based on the Agro-Ecological Zones (AEZ) model of FAO and operates with multiple objectives in an flexible and user friendly fashion. The decision variables are the agricultural cell activities and the intensity of livestock farming and forestation. An application to the Bungoma region in Kenya illustrates the approach, from the stage of defining decision criteria; related to food support, resiliency, economic growth and ecological sustainability; to the final decision making phase with local decision makers. Implemented on-site, the system is to facilitate analysis, communication and enforcement of local land development plans. Rather than forwarding the hierarchically defined values and trade-offs of a governmental agency or foreign-aid service, the model shifts the power to the regional authorities, which are more likely to commit to and follow up agreed-on land-use plans
A multicriteria framework for inventory control
No full textAn interactive multicriteria framework for an inventory control decision support system is presented. Previous formulations of the simultaneous order quantity, safety stock and service-level problem have assumed explicit preference articulation, although comparisons of total annual cost and e.g. service level are complex without the knowledge of local trade-off ratios and the nondominated set. The procedure is constructive in the sense that the preference structure of the decision maker is assessed progressively under the exploration of the solution space. The framework is intended for inclusion in a decision support system for production and operations management or to be used as a separate module for strategic inventory control. Implementations as FORTRAN modules and spreadsheet macros are available
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