Long memory analysis for marketing intelligence; the case of coriander seed prices in Kota district of Rajasthan

Richard Kwasi Bannor, Rajesh Sharma and Madhu Sharma

Indian Journal of Agricultural Marketing, 2015, vol. 29, issue 2

Abstract: This study explored modelling and forecasting of wholesale coriander monthly prices in Kota district of Rajasthan using Autoregressive Fractionally Integrated Moving-Average Model (ARFIMA). Based on minimum AIC and BIC values, ARFIMA (1, 0.375, 2) was selected as the best fit model for forecasting of coriander prices. The result shows the mean absolute percentage error of ARFIMA (1, 0.375, 2) on predictions from January 2005 to August 2015 is 7.21whereas the mean absolute percentage error of ARFIMA (1, 0.375, 2) based on predictions from January 2003 to August is 7.08 percent. It is therefore suggested that ARFIMA model should be considered when forecasting of coriander prices in Kota. This will promote market intelligence for farmers and various stakeholders in coriander marketing.

Keywords: Marketing (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:ags:injagm:399545

DOI: 10.22004/ag.econ.399545

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