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Price Forecasting Model for Perishable Commodities: A Case of Tomatoes in Punjab, Pakistan

Shahzad Muhammad Aamir

MPRA Paper from University Library of Munich, Germany

Abstract: This study focused on developing forecasting model for perishable commodities and tomato is taken as a case to study. The model is developed on in-depth analysis of market dynamics and structure. An estimable theoretically founded model is the major output of this study which is based on true structure of the market. Complete model is comprised of inverted demand equation, Plantation and yield equations and the role of price expectations. The study reveals the fact that the farmers’ production decisions are affected by the expected profitability which is based on the expected output prices. However, due to the involvement of certain intermediaries the farmers couldn’t get the proper prices of its output whereas the domestic production meets 31.5% to its total demand only and the deficit is imported from other provinces of the country and from India. Low per acre yield and inefficient management practices, non-availability of hybrid seed, weather conditions and less profit margins and declining area of production causes the production to fall short of its potential maximum. Moreover, the increased reliance on imports and the increased demand due to increase in population causes the domestic prices to becomes more volatile. The majority of the small farmers sell their product through commission agents and wholesaler that cause imperfections in the market. Tomatoes value chain have certain problems like there exists a disparity between the small and large farmers in cost of production, yield and profitability. The model may forecast the prices on monthly or weekly basis depending upon the data availability.

Keywords: Forecasting; Tomato; Market; Price (search for similar items in EconPapers)
JEL-codes: E17 E31 Q11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-agr and nep-mac
Date: 2017-03-01, Revised 2017-08-01
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