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

Mehmet Balcilar, Rangan Gupta, Anandamayee Majumdar and Stephen Miller

Empirical Economics, 2013, vol. 44, issue 2, 387-417

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

Keywords: Forecasting; Linear and non-linear models; Nevada gross gaming revenue; Nevada taxable sales; C32; R31 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes (2011)
Working Paper: Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes (2010)
Working Paper: Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes (2010)
Working Paper: Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes (2010)
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DOI: 10.1007/s00181-011-0536-2

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