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Nowcasting Tourism Industry Performance Using High Frequency Covariates

Carl Bonham (), Peter Fuleky, James Jones () and Ashley Hirashima ()
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James Jones: UH-Manoa Department of Economics and University of Hawaii Economic Research Organization
Ashley Hirashima: UH-Manoa Department of Economics and University of Hawaii Economic Research Organization

No 2015-3, Working Papers from University of Hawaii Economic Research Organization, University of Hawaii at Manoa

Abstract: We evaluate the short term forecasting performance of methods that systematically incorporate high frequency information via covariates. Our results indicate that including timely intra-period data into the forecasting process results in significant gains in predictive accuracy compared to relying exclusively on low frequency aggregates. Anticipating growing popularity of these tools among empirical analysts, we o↵er practical implementation guidelines to facilitate their adoption.

Keywords: Nowcast; Ragged edge; Mixed frequency models (search for similar items in EconPapers)
JEL-codes: H51 I12 Q51 Q53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for and nep-tur
Date: 2015-09
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http://www.uhero.hawaii.edu/assets/WP_2015-3.pdf First version, 2015 (application/pdf)

Related works:
Working Paper: Nowcasting Tourism Industry Performance Using High Frequency Covariates (2016) Downloads
Working Paper: Nowcasting Tourism Industry Performance Using High Frequency Covariates (2016) Downloads
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