A Theory of Soft Capture

Capture of regulatory agencies by firms or other stakeholders has given rise to a rich literature, much of which is dominated by models in which the motivation for the welfare-reducing behavior is found in side-contracting (bribes, corruption), threats (blackmail, political support) or corresponding mechanisms for repeated games (reputation, career concerns, signaling for promotion). Notwithstanding, the empirical support for monetary corruption and 'revolving doors' is scarce and inconclusive. We propose an alternative and more intuitive model for regulatory capture that is based on information transmission and asymmetric information. In a three-tier model, a regulator is charged by a political principal to provide a signal for the type of a regulated firm. Only the firm can observe his type and the production of a correlated signal with a given accuracy is costly for the regulator. The firm can costlessly provide an alternative signal of lower accuracy that is presented to the regulator. In a self-enforcing equilibrium, the regulator transmits the firm-produced signal, internalizes its own savings in information cost and the firm enjoys higher information rents. The main feature of soft capture is that it is not based on a reciprocity of favors but on a congruence of interests between the firm and the regulator.

Cooperative Supply Chains in Peace and at War

In the competition between supply chains, governance structure and coordination mechanisms can be as important as cost-efficiency. Flexible and non-committing contracts among upstream suppliers in cooperative alliances may lead to lower chain surplus through internal competition and renders the coordinator's position vulnerable for hostile take-overs. Cooperative supply chains are found in e.g. food industry, banking services, lawfirms and brokerage. The downstream processing or brand is owned collectively by the suppliers or service-providers. The supplier are linked to the chain by strong delivery (channel) rights and volume-based revenue-sharing schemes. The governance is flexible, promotes entry and market expansion. However, the decentralized decision making comes at a cost in terms of chain performance and resilience. A dynamic two-chain model with a captive and competitive market addresses the particular situation where the competing chain aggressor has a cooperative governance structure. The overt aggression at merger may have more to do with shortcomings in the managerial incentive structure than with the pursuit of market power. The results from the dynamic game is illustrated with empirical findings among dairy cooperatives in Denmark.Agribusiness,

Issues and Challenges in Regulation Economics

Effective economic regulation demands clear objectives, sound economic reasoning and a careful analysis of the inevitable trade-offs between conflicting societal interests. The key problems are linked to the information asymmetry between the regulator and the regulated firms. Although the market principle may provide some useful guidelines, the problems of bankruptcy and windfall profits remain to be addressed. In this overview, we discuss how modern yardstick regimes in combination with franchise auctions provide powerful solutions that may contribute to both societal and industry demands.Agricultural and Food Policy,

Network Regulation under Climate Policy Review

Climate change policy, in particular in Europe, will a¤ect the energy sector through the exposure to massive penetration of distributed energy resources or decentralized generation into electricity distribution and transmission grids. As the prerequisites for infrastructure regulation still prevail in the future, the question arises whether the current regulatory model is still valid. In this paper, we chararcterize some of the e¤ects of climate change policy on the network tasks, assets and costs and contrast this with the assumptions implicit or explicit in current economic network regulation. The resulting challenge is identi ed as the change in the direction of higher asymmetry of information and higher capital intensity, combined with ambiguities in terms of task separation. Methodolog- ically, we argue that this may require a mobilization of the litterature related to delegated and hierarchical systems, e.g. team performance, as the externalities are joint products from multiple independent stages where individual regulation may introduce distortions. To provide guidance, we present a model of investment provision under regulation between a distribution system operator (DSO) and a potential investor-generation. The results from the model con rm the hypothesis that network regulation should nd a focal point, should integrate externalities in the performance assessment and should avoid wide delegation of contracting-billing for climate change technologies.network regulation; climate change; investments; distributed generation

DEA-Based Incentive Regimes in Health-Care Provision

A 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,

A Market-Oriented Approach for Multiple Objective Optimization in Agro-Ecological Land Use Planning

The development of a third world country requires a conscious balance between different planning and policy issues, such as population growth rate, gross national income, self reliance and long-term sustainable ecological development. This paper reports on a cross-disciplinary project to design a decision support system (DSS) that aims to assist government policy makers in planning the regional agricultural development of the Bungoma region in Kenya. Contrary to previous research, which has taken the perspective of a central planner and a static market, this model extends the scope by introducing the market mechanisms and price subsidies. The model is based on the Agro-Ecological Zones (AEZ) model, a previously developed non-interactive optimization model that provides an agro-ecological and economic assessment of various types of land uses, including cash-crops, food production, grazing, forestation and farming. This paper maintains the decision analytic scope of the AEZ model to explicitly incorporate a multicriteria decomposition optimization formulation that facilitates a direct trade-off analysis between the various decision criteria within a user-interactive decision support modeling framework. The model uses in-depth information about the Bungoma region, extracted from a large scale FAO database on Kenya that includes information on various climate and soil characteristics (e.g., thermal and moisture regime, soil type, slope class) and socio-economic data (e.g., projected growth rate and product demand patterns) for 90,000 agro-ecological cells. At each stage of the analysis, our system offers the decision maker several alternative planning strategies with different suggested land uses for over 100 different types of crops, fuelwood and livestock land utilization types of evaluation, allowing the decision maker to take into account trade-offs between a number of planning and policy criteria, including food output, net revenue, gross value of output, self sufficiency, production costs, arable land use and degree of erosion.decision analysis, multicriteria decision making, integrated land-use planning and management, decision support systems, Land Economics/Use,

Rate-Adaptive Coded Modulation for Fiber-Optic Communications

Rate-adaptive optical transceivers can play an important role in exploiting the available resources in dynamic optical networks, in which different links yield different signal qualities. We study rate-adaptive joint coding and modulation, often called coded modulation (CM), addressing non-dispersion-managed (non-DM) links, exploiting recent advances in channel modeling of these links. We introduce a four-dimensional CM scheme, which shows a better tradeoff between digital signal processing complexity and transparent reach than existing methods. We construct a rate-adaptive CM scheme combining a single low-density parity-check code with a family of three signal constellations and using probabilistic signal shaping. We evaluate the performance of the proposed CM scheme for single-channel transmission through long-haul non-DM fiber-optic systems with electronic chromatic-dispersion compensation. The numerical results demonstrate improvement of spectral efficiency over a wide range of transparent reaches, an improvement over 1 dB compared to existing methods

Polarity in DEA Models

This article discusses models in data envelopment analysis (DEA) relaxing the standard convexity assumptions. The basic model treats mutually incomparable pairs of sets to be generated by a procedure proposed earlier. Each pair consists of a consumption set and a production set of feasible input-output combinations. Two fundamental operations by the procedure are based on intersection and convex hull generation in the input-output space. A polarity analysis is performed which, subject to the usual assumptions about free disposability and nonnegativity, appears fruitful to do in the framework of blocking and antiblocking sets. It is shown how this leads to an interchange of the above operations extending some classical results from convex analysis. The last part of the paper presents a pair of linear programming models calculating a Farrell productivity index based on a preceeding application of the procedure. This is a generalization of the classical linear programming models in DEA subject to standard assumptions about convexity.Data Envelopment Analysis, polarity, Research Methods/ Statistical Methods,

Multi-Period Dea Incentive Regulation in Electricity Distribution.

Multi-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

Traffic-grooming- and multipath-routing-enabled impairment-aware elastic optical networks

Traffic grooming and multipath routing are two techniques that are widely adopted to increase the performance of traditional wavelength division multiplexed networks. They have been recently applied in elastic optical networks to increase spectral efficiency. In this study, we investigate the potential gains by jointly employing the two techniques in combination with a realistic physical impairment model. To allocate resources and quantify spectral efficiency gains over existing impairment-aware schemes, we present an analytical optimization formulation for small networks and a heuristic for large networks. Through numerical simulations, we demonstrate that traffic grooming and multipath routing, together, increase spectral efficiency and reduce resource consumption over existing schemes. We show that the proposed scheme offers significant performance improvements in networks with low degrees of connectivity, high traffic loads, and long links