Abstract
The goal of the current study is to highlight the factors that could affect retail food prices and develop an econometrical model for estimating the level of the impact of the identified factors. The research covers the period from 2016 to 2018. Multiple regression modelling is used for model creation. The outcomes mad available evidence that the factors mostly affecting the prices are the monthly average price of food product and yield of the agricultural subsector providing main stock for the food product. The current research contributes to scientific literature by showing that retail food prices could be estimated for the short-term period. The limitation of the research is that the developed econometric models are is adequate for the Lithuanian market and ought to be modified if applied in other markets.
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