A global assessment of food and non-food spending: evidence from 173 countries and implications for food security

Abstract

Background: Understanding how price and income dynamics influence food demand across countries is essential for addressing global food security. However, food demand must be considered within the broader context of overall demand, which includes other necessities, such as housing, clothing, and health care. By understanding the drivers of both food and non-food spending, policymakers can make informed decisions about pricing, subsidies, and other economic policies. In this study, we analyzed spending patterns across 173 countries using newly released data from the International Comparison Program (ICP) of the World Bank (2021 data cycle). We used the Quadratic Almost Ideal Demand System (QUAIDS) to estimate demand and derived income and price elasticities across spending categories, such as food, health care, and education, among others. Cross-country demand estimates based on ICP data have been used in large-scale models of global food security, health and nutrition, agricultural land use, and the environment. Given the dynamic nature of global markets, updated estimates are crucial for ensuring the accuracy and relevance of these models in addressing contemporary challenges. Results: Consistent with previous research, we find that income and prices have more influence on food demand in lower income countries. For instance, the income elasticity for food is 0.63 on average, with values ranging from 0.70 in Sub-Saharan Africa to 0.38 in North America. While food demand is inelastic across countries, the own-price responsiveness for food tends to be higher in low-income countries. The cross-price elasticities show that food and clothing are substitutes. However, there is a complementary relationship between food and health care, suggesting that lower health care costs could improve food security. Both food and education are essential goods, leading to their low responsiveness to changes in both income and prices. In addition, food and education are the only categories, where income and price responsiveness significantly vary across countries and regions. Conclusions: Cross-country demand estimates are important for accurately assessing the impact of income and prices on vulnerable populations. As the global population grows, understanding the relationship between income, prices, and spending becomes crucial. Such insights are essential for designing effective policies to address food insecurity.