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Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes

  • Mehmet Balcilar

    ()

    (Department of Economics, Eastern Mediterranean University, Famagusta, North Cyprus,via Mersin 10, Turkey)

  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

  • Anandamayee Majumdar

    ()

    (School of Mathematical & Statistical Sciences, Arizona State University)

  • Stephen M. Miller

    ()

    (College of Business, University of Las Vegas, Nevada)

This paper provides out-of-sample forecasts of Nevada gross gaming revenue and taxable sales using a battery of linear and non-linear forecasting models and univariate and multivariate techniques. The linear models include vector autoregressive and vector error-correction models with and without Bayesian priors. The non-linear models include non-parametric and semiparametric models, smooth transition autoregressive models and artificial neural network autoregressive models. In addition to gross gaming revenue and taxable sales, we employ recently constructed coincident and leading employment indexes for Nevada’s economy. We conclude that non-linear models generally outperform linear models in forecasting future movements in gross gaming revenue and taxable sales.

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Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201018.

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Length: 46 pages
Date of creation: Jul 2010
Date of revision:
Handle: RePEc:pre:wpaper:201018
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Web page: http://www.up.ac.za/economics

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