Abstract
In this research, we used a gravity model to investigate whether water scarcity variables influence agricultural trade of cereal crops for Saudi Arabia. We compare the OLS, Fixed effects, Random effects, and Poisson Pseudo-Maximum Likelihood (PPML) estimators to determine the best model. The AIC, and multicollinearity, heteroskedasticity, and autocorrelation tests assist in determining estimation procedures and the final model. We cluster the errors by distance to improve the specific country effect variables, such as economic mass. We find that water-related variables influence virtual water imports of cereals, millet, corn, barely, and sesame.
Highlights
The liberalization of world trade has led to the fluid movement of goods and services among countries
There are three waterrelated variables included: Water Dependency Ratio (WDR), which should be negatively related to imports, and Relative Renewable Water to Arable Land Ratio (RRWALR) and Water Footprint Ratio (WFR), which should be positively related to imports
The water footprint ratio for cereals (WFRCE) was calculated by taking the average of wheat, barley, corn, millet, and sesame water footprint for each country as a ratio of Saudi Arabia We found that the AIC
Summary
The liberalization of world trade has led to the fluid movement of goods and services among countries. This more open trading environment has encouraged countries to seek gains from trade, which sometimes leads to difficulties when resources are priced inefficiently. Water management policies in Saudi Arabia have taken a back seat to supply-side policies that increase self-sufficiency in some crops, ignoring the importance of depleting water resources. All of this leads to the conclusion that Saudi Arabia has not benefited from foreign trade because it has squandered its meager groundwater supplies. The agricultural sector relies heavily on non-renewable groundwater in
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