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Productivity Measurement in a Service Industry: Plant-Level Evidence from Gambling Establishments in the United Kingdom

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Author Info
David Paton (Business School, University of Nottingham, UK)
Donald S. Siegel () (Department of Economics, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA)
Leighton Vaughan Williams (Department of Economics and Finance, Nottingham Trent University, UK)

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Abstract

Gambling is one of the fastest growing service industries. Unfortunately, there have been no studies of total factor productivity (TFP) in this sector. The purpose of this paper is to fill this gap, based on an analysis of U.K. establishment-level data. These data are derived from the Annual Respondents Database (ARD) file, constructed by the U.K. Office for National Statistics, consisting of individual establishment records from the Annual Census of Production. The ARD file contains detailed data on output, materials, energy, employment, and numerous plant and firm characteristics and is quite similar to the U.S.-based Longitudinal Research Database (LRD). This information can be used to construct measures of TFP. We also construct estimates of labour productivity, since TFP is may be measured with error. We use these data to estimate labour and total factor productivity equations based on a stochastic frontier production function framework. The latter approach enables us to assess whether investment in information technology enhances relative productivity. Our preliminary results suggest that the production function models fit well, generating plausible elasticity estimates and indicating constant returns to scale. While investment in computers per se does not appear to have a productivity enhancing effect, gambling establishments that use Internet-based technology appear to be closer to the frontier.

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Paper provided by Rensselaer Polytechnic Institute, Department of Economics in its series Rensselaer Working Papers in Economics with number 0413.

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Date of creation: Jun 2004
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Handle: RePEc:rpi:rpiwpe:0413

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