Abstract
This study examines the effect of previous price and climatic variables on maize supply in Ghana. For this purpose, two separate approaches are used: (i) a lag model using the OLS technique and (ii) a quantile regression approach. Results from the lag model indicates that an increase in previous year maize price and previous growing season temperature positively affect current year maize supply. However, an increase in previous growing season rainfall negatively affects current year maize supply. The quantile regression results show that maize supply responds differently to previous maize price and climatic variables across the different quantiles of crop area distribution.
Keywords
- Lag Model Search this journal for Lag Model (opens in a new tab)
- Quantile Regression Search this journal for Quantile Regression (opens in a new tab)
- Maize Supply Search this journal for Maize Supply (opens in a new tab)
- Climatic Variables Search this journal for Climatic Variables (opens in a new tab)
- Price Search this journal for Price (opens in a new tab)
- Crop Area Search this journal for Crop Area (opens in a new tab)
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Copyright (c) 2013 Henry De-Graft Acquah, Clement Kweku Kyei (Author)

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Keywords
- Lag Model Search this journal for Lag Model (opens in a new tab)
- Quantile Regression Search this journal for Quantile Regression (opens in a new tab)
- Maize Supply Search this journal for Maize Supply (opens in a new tab)
- Climatic Variables Search this journal for Climatic Variables (opens in a new tab)
- Price Search this journal for Price (opens in a new tab)
- Crop Area Search this journal for Crop Area (opens in a new tab)
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