Supply response of maize in Zambia

The objective of this study is to analyze the supply response of maize in Zambia. The study uses the elasticities of supply to explain how farmers respond to both endogenous and exogenous factors. In this research paper, the method adopted is the Error correction model of the univariate to analyze the response of farmers. The Error correction model estimate both the short run and long run elasticities of agricultural output. However, the model uses maize (Yt) as the dependent variable measured per annual metric tons, maize own price (Pm) as the independent variable measured per metric tons, price of close substitute crop (Psb) measured per metric tons, price of fertilizer (Ft) measured per metric tons and average annual rainfall amount (Rt) to determine how a farmer will respond when these factors change both in the short run and long run. The analysis will be done by using E-views statistical software and the data used will be macroeconomic time series -secondary data for the period of forty (40) years from 1980 to 2020.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17182978
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Supply response of maize in Zambia

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Supply response of maize in Zambia

article en

Abstract

The objective of this study is to analyze the supply response of maize in Zambia. The study uses the elasticities of supply to explain how farmers respond to both endogenous and exogenous factors. In this research paper, the method adopted is the Error correction model of the univariate to analyze the response of farmers. The Error correction model estimate both the short run and long run elasticities of agricultural output. However, the model uses maize (Yt) as the dependent variable measured per annual metric tons, maize own price (Pm) as the independent variable measured per metric tons, price of close substitute crop (Psb) measured per metric tons, price of fertilizer (Ft) measured per metric tons and average annual rainfall amount (Rt) to determine how a farmer will respond when these factors change both in the short run and long run. The analysis will be done by using E-views statistical software and the data used will be macroeconomic time series -secondary data for the period of forty (40) years from 1980 to 2020.

Zenodo (CERN European Organization for Nuclear Research)
Mulungushi University (ZM)
Zero hunger
Openalex Percentile: Top 29%
Geochemistry and Geologic Mapping
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