Abstract
This study investigates the effect of climate change on crop production in Turkey using time series data from 1980 to 2019. Our model covers both climatic and non-climatic factors, including average precipitation, average temperature, cultivation area, fertilizer use, and gas-diesel consumption. After checking the results of our preliminary tests, we used the Toda–Yamamoto causality test and the Autoregressive Distributed Lag (ARDL) cointegration approach to analyze causality and long-run relationships among variables. The outcomes of the ARDL bounds test confirm the cointegration between crop production with climatic and non-climatic factors. The long-run estimation results demonstrate that a 1% increase in precipitation, cropland, fertilizer consumption per cropland, and agricultural gas-diesel oil use per cropland increases production by 0.59%, 0.43%, 0.33%, and 0.07%, respectively. Furthermore, a 1% temperature increase reduces production by 0.19% in the long run. Through causality analysis, we found multiple unidirectional causal relationships between variables. While average temperature is the Granger cause of cropland and gas-diesel use, cropland is the Granger cause of crop production. Given these concerning results regarding the detrimental impact of climate change on crop production, it is evident that governments should prioritize their efforts to tackle the causes of climate change. Furthermore, implementing adaptation strategies such as promoting drought-resistant cultivars and adopting efficient irrigation techniques is crucial.
Highlights
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Average precipitation is the variable with the highest impact on crop production. A 1% increase in precipitation boosts crop production by 0.59% in the long run.
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Temperature increases lead to a decrease in crop production in the long run.
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Gas-Diesel oil usage per cropland has a positive effect on production, albeit with a relatively weak effect, particularly in the long run.
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In the long run, cropland is the most influential variable in the non-climatic factors. In addition, cropland is the only granger cause of crop production among the studied variables.
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Data Availability
Data are available on request.
Notes
Here, stationarity refers to weak or covariance stationarity, which indicates that the mean and variance of the time series are constant over time, and the covariance with its lags is independent of time and depends only on the lag length (Mert and Çağlar 2019).
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Çakan, V.A., Tipi, T. What are the Implications of Climatic and Non-climatic Factors on Crop Production? Evidence from Turkey. Int J Environ Res 18, 10 (2024). https://doi.org/10.1007/s41742-023-00560-8
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DOI: https://doi.org/10.1007/s41742-023-00560-8