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Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes

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  • Mehmet Balcilar

    ()

  • Rangan Gupta

    ()

  • Anandamayee Majumdar

    ()

  • Stephen Miller

    ()

Abstract

This article provides out-of-sample forecasts of Nevada gross gaming revenue (GGR) 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 semi-parametric models, smooth transition autoregressive models, and artificial neural network autoregressive models. In addition to GGR and taxable sales, we employ recently constructed coincident and leading employment indexes for Nevada’s economy. We conclude that the non-linear models generally outperform linear models in forecasting future movements in GGR and taxable sales. Copyright Springer-Verlag 2013

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File URL: http://hdl.handle.net/10.1007/s00181-011-0536-2
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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 44 (2013)
Issue (Month): 2 (April)
Pages: 387-417

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Handle: RePEc:spr:empeco:v:44:y:2013:i:2:p:387-417

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Keywords: Forecasting; Linear and non-linear models; Nevada gross gaming revenue; Nevada taxable sales; C32; R31;

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Cited by:
  1. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.

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