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Is it possible to predict food retail prices? Evidence from Lithuanian market


Purpose – the purpose of the article is to develop a model that could be used for estimating the level of the effect of the highlighted determinants on food retail prices.
Research methodology – the study is based on the obtained monthly data of food retail prices that covers the period from

2016 I m. to 2018 XII m. (36 observations). Multiple regression modelling is used in order to create a model of foodretail prices.

Findings – the results provide evidence that the most influential determinants are the price of the alternative products and purchasing power. It also contributes to scholarly thinking, stating, that it is possible to predict the future retail price of a particular product.

Research limitations – the limitation of the current study is that the proposed econometric model is sufficient for the Lithuanian market and ought to be modified if used in other countries.

Practical implications – the development model allows to predict/forecast the food retail prices which are crucial for households budget planning.

Originality/Value – the current study examines the main determinant of retail food prices. It laid a background for future researches, based on examining possibilities to forecast food prices. The research results contribute to classic economic views about market imperfections influence onto supply-demand equilibrium and unproductiveness of consumer illicit market.


Keywords: average retail price, food basket, consumer behaviour, purchasing power, production stock purchase price, agricultural subsector.



Volkov, A.; Morkunas, M.; Skvarciany V. 2019. Is it possible to predict food retail prices? Evidence from Lithuanian market. In International Scientific Conference „Contemporary Issues in Business, Management and Education“, International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering“. EISSN 2538-8711; ISBN 978-609-476-161-4 / eISBN 978-609-476-162-1; https://doi.org/10.3846/cibmee.2019.018; [Conference Proceedings Citation Index (CPCI) integrated index within Web of Science, Clarivate Analytics].


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