Dvera I. Saxton ds3409a@student.american American University College of Arts and Sciences

1. Do export-oriented food economies &GDP per capita, and level of agricultural development effect food insecurity? Dvera I. Saxton ds3409a@student.american.edu American University College of Arts and Sciences PhD Student, Anthropology

2. Research Question, Hypothesis • How do trends towards export-oriented agriculture impact food insecurity at the global level? • I hypothesize that food security decreases as GDP per capita decreases and as the percentage of food exports increases. • H0 = 0 (There is no relationship between food insecurity, food exports, GDP pc, and level of agricultural development) • H1≠ 0 (There is a significant relationship between food insecurity, food exports, GDP pc, and level of agricultural development)

3. Introduction • Relationships between structural adjustment programs (SAPs), export-oriented agriculture and food insecurity • Not poverty, but the structural causes of poverty, implemented from above • Restructuring of state to attract and support foreign investors rather than social safety nets, public health and education, farmer subsidies, etc. • Privatization of land, natural and social resources, work. • Food Security: “access by all people at all times to enough food for an active healthy life (The World Bank 1986)” (Gani and Prasad 2007:311). • Does this kind of development really help the poorest of the poor, the hungriest of the hungry?

4. Literature Review • Qualitative: • Stonich (1991), Honduras, 1950-1986: sharp decline in food produced for domestic consumption with advent of SAPs. • Kent (2002), Sub-Saharan Africa: Shift from relative food self-sufficiency via subsistence farming , vs. present day dependence on cash economy and imported foods. • Quantitative: • Gani and Prasad (2007) “confirm a positive correlation between food availability, per capita energy and protein supply and human development [and] a negative but statistically insignificant effect on food prices and vulnerability…” (2007:316-317). Need to consider variables other than economic growth. • Glewwe and Hall (1992), World Bank economists in Lima, Peru • Used household-level data on food purchasing power over a period of five years to measure food security • Noted decrease in purchasing power between 1985-1990, blamed this on the Peruvian government’s short-term reinvestment in state and neglect of debt repayments • However, this neglects the impacts of SAPs before 1985. • Make uninformed assumptions about the state of food security in the countryside, stating that rural people are more food secure (what about Shining Path? Indigenous/race factors? Access to land for the poor? Gender?) • Encouraging that they are using household-level data. • But, can we always trust World Bank data and analysis? What are their biases, objectives? What about other large databases with limited resources and time??

5. Data • Sources: FAO STAT (food export data) and WDI (GDP pc, Irrigation, population) • Sample size: 124 total countries, 60 with undernourishment under 3% (filtered out), 64 with undernourishment above 3% (focus) • Data is interval-level ratio • Dependent variable: • % Undernourishment in Children Under 5 (proxy measure for food security) • Independent variables: • % Food exports per capita • GDP per capita (measure of overall development and economic strength) • % Irrigated Land (proxy measure for agricultural development)

6. Descriptive Statistics: Global Disparity

7. Estimates, Dependent Variable Percent Undernourishment Under Age 5a *Correlation is significant at the 0.05 level (2-tailed) a No collinearity detected

8. Conclusions & Policy Recommendations • Food security=availability, price, access, and vulnerability (Gani and Prasad 2007; Sen 1999). • Varies across and within countries, thus, need a more holistic approach to data collection and analysis. • Use models with many indicators, since many things contribute to poverty and food insecurity, not just wealth, but politics, social organization, gender, age, etc. • Survey data within specific vulnerable populations over long periods of time to better inform policies. • Lots of countries don’t have data available due to war or political restrictions on travel (e.g. North Korea, Afghanistan, Myanmar, DRC, Palestine, Chad, Sudan, Haiti, etc.)

9. Conclusions & Policy Recommendations • Just outcomes will not result from making global generalizations, given the wide-ranging economic, social, political, and environmental disparity within and between nations. • There may not be just one approach to food security, given the level of global economic and social disparity, as well as environmental factors. • Paradigm Shift!! • Quantitative methods are important tools in the realms of policy making and international development, but perhaps we need to rethink how they are applied to certain problems, and to consider the outcomes certain decisions have created in the past. • Yes, this means more time and more money, but to change the world requires structural changes within the apparatuses of capital and power (including applications with quantitative and qualitative methods). • We cannot neglect the ethical dimensions of the social sciences, whether they are conducted quantitatively or qualitatively or in some combination (how data are collected, how they are used, what are the impacts).