2021•Unpublished venueRequires access

Analysis of Soybean Demand in North Sumatra Province

Surtan Hasibuan, Rulianda Purnomo Wibowo, Rahmanta Rahmanta

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Abstract

The purpose of this study is to analyse soybean demand in North Sumatra Province. The variables used are soybean price, previous year soybean price (t-1), maize price, population and soybean demand. North Sumatra Province was chosen as the research location because this area is one of the provinces with the highest soybean demand rate in Indonesia but one of the provinces that produces the lowest soybean in Indonesia. The data used in this study is secondary data, in the form of time series annual data from 2000-2019, so that 20 observations were obtained. In this study, the equation uses a distributed lag finate model. The results showed that population was the most significant effect on soybean demand, while soybean price, previous year soybean price (t-1) and maize price did not significantly effect on soybean demand.

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What this paper is about

The purpose of this study is to analyse soybean demand in North Sumatra Province. The variables used are soybean price, previous year soybean price (t-1), maize price, population and soybean demand. North Sumatra Province was chosen as the research location because this area is one of the provinces with the highest soybean demand rate in Indonesia but one of the provinces that produces the lowest soybean in Indonesia. The data used in this study is secondary data, in the form of time series annual data from 2000-2019, so that 20 observations were obtained. In this study, the equation uses a distributed lag finate model. The results showed that population was the most significant effect on soybean demand, while soybean price, previous year soybean price (t-1) and maize price did not significantly effect on soybean demand.

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Available abstract

The purpose of this study is to analyse soybean demand in North Sumatra Province. The variables used are soybean price, previous year soybean price (t-1), maize price, population and soybean demand. North Sumatra Province was chosen as the research location because this area is one of the provinces with the highest soybean demand rate in Indonesia but one of the provinces that produces the lowest soybean in Indonesia. The data used in this study is secondary data, in the form of time series annual data from 2000-2019, so that 20 observations were obtained. In this study, the equation uses a distributed lag finate model. The results showed that population was the most significant effect on soybean demand, while soybean price, previous year soybean price (t-1) and maize price did not significantly effect on soybean demand.

Key concepts: Population, Mathematics, Agricultural science, Biology, Demography, Sociology

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