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Stochastic frontier models with network selectivity

William Horrace () and Hyunseok Jung
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Hyunseok Jung: University of Arkansas

Journal of Productivity Analysis, 2018, vol. 50, issue 3, No 2, 116 pages

Abstract: Abstract Worker peer-effects and managerial selection have received limited attention in the stochastic frontier analysis literature. We develop a parametric production function model that allows for worker peer-effects in output and worker-level inefficiency that is correlated with a manager’s selection of worker teams. The model is the usual “composed error” specification of the stochastic frontier model, but we allow for managerial selectivity (endogeneity) that works through the worker-level inefficiency term. The new specification captures both worker-level inefficiency and the manager’s ability to efficiently select teams to produce output. As the correlation between the manager’s selection equation and worker inefficiency goes to zero, our parametric model reduces to the normal-exponential stochastic frontier model of Aigner et al. (1977) with peer-effects. A comprehensive application to the NBA is provided.

Keywords: Spatial autoregressive model; Peer-effects; Selectivity; Endogeneity; C31; C44; D24 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11123-018-0537-7

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