Effect of hurricanes on cotton yield and output in Georgia and Texas

Abstract

Over the past 50 years, Georgia and Texas have both experienced multiple storms and hurricanes with different intensities. Their cotton production industries have successfully remained buoyant despite the challenges imposed by these storms, from flooding and wind damage to nutrient loss and diseases. The overall objective of this research is to assess the impact of major storms on cotton production in the two largest cotton producing states, i.e., Texas and Georgia. Specifically, the study characterized the major storms experienced in the two states over five decades and compared the effects of these storms on cotton yield and output. It is hypothesized that major storms can have significant adverse effects on cotton yield and output if they arrive when the cotton is most vulnerable, i.e., when it is flowering or at the boll stage. High rainfall that often occurs with storms would break the cotton ball and have significant adverse impact on yield and output. Similarly, if the storms are packed with high winds, then they might destroy the cotton plants by blowing them down, breaking stems and destroying bolls. However, if the storms come when the crop is not yet in boll, then they may have little or no impact on yield and/or output. It is also important to note that while a storm may make landfall, it may not have enough energy in it to reach cotton growing areas, and will therefore have not impact on yield and/or output. The study’s results show that storms have had no statistical impact on either cotton yield or output in Texas. In Georgia, yield in years before 1995 when there are storms is statistically significant different from yield in years without storms in the same period. However, yield in years after 1995 when there are storms and in years when there are no storms are both higher than the yield in years before 1995 without storms. Both of them are statistically different at the 5% level of significance. The difference in output followed the same pattern, but the level of statistically significant was at the 1% level. It was found that yield in both states responded to price lagged one period, suggesting that getting a higher price for cotton allowed farmers to make the necessary investment in the following year’s crop to improve yield and output. While lagged price influenced output in Texas, its effect was not statistically significant in Georgia. The results suggest that over the past 50 years, on average, storms may not have the long-term impact on cotton production as may be thought. However, this does not mean that in the year that a storm hit, cotton farmers do not experience real challenges. Using the long-term analysis would lead to the suggestion that focusing on technologies that improved the ability of the cotton plant to withstand winds and heavy rain could address the challenges that occur on cotton farms during storms. It will be prudent, however, to focus on strategies that improved cotton prices so that farmers can make the necessary investments in their production to improve yields. Better financial performance would help cotton farmers deal with adverse natural events like storms because they could improve their financial resilience through savings. Future research should explore this further.