73 research outputs found

    Compensation dispersion between and within hierarchical levels

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    This paper studies the dispersion around the expected compensation of workers before and after controlling for hierarchical positions in cross-section data samples. From data for Spanish managers, we find that this dispersion decreases with education and work experience before entering the current job and increases with job tenure. This finding contrasts with previous research that finds a positive association between compensation dispersion and education and work experience. We explain the new finding through a model of learning that separates compensation dispersion between jobs and within jobs (hierarchical positions). The model takes advantage of the information revealed when workers are promoted to their current hierarchical positions and allows for more robust tests of learning theories

    A Model of Final Offer Arbitration in Regulation

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    I study a regulatory process in which both the regulator and the regulated firm propose prices that, in case of disagreement, are settled through final-offer arbitration (FOA)—a practice currently used in Chile for setting prices in the water sector. Rather than submitting a single offer, each party simultaneously submits an offer for each of the firm’s cost units (e.g., cost of raw water, capital cost). While a multiple-offers scheme allow the arbitrator to better approximate her ideal settlement, it may induce parties to submit widely divergent offers. This divergence, however, does not affect the arbitrator’s ability to learn from the offers. Copyright Springer Science+Business Media, Inc. 2005final-offer arbitration, price regulation, Nash equilibrium,

    The determination of the union status of workers

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    SIGLELD:9261.96(227) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    Early identification of problem interactions: A tool-supported approach

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    The principle of "divide and conquer" suggests that complex software problems should be decomposed into simpler problems, and those problems should be solved before considering how they can be composed. The eventual composition may fail if solutions to simpler problems interact in unexpected ways. However, early identification of concrete scenarios where interactions happen remains an outstanding issue. In this paper, we propose that logical abduction can be used to efficiently identify all possible failure scenarios when the composition cannot be achieved fully. We present an tool-supported framework that (i) provides a simple diagramming editor for drawing problem diagrams and describing them using the Event Calculus, (ii) structures the Event Calculus formulae of individual problem diagrams for the abduction procedure, (iii) communicates with an off-the-shelf abductive reasoner in the background and relates the results of the abduction procedure to the problem diagrams. With this tool, it becomes possible to highlight at an early stage, problem diagrams that will interact when composed together. The proposed theory and the tool framework are illustrated with an interaction problem from the smart home application
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