The document develops an optimization model to analyze household food security and simulate various policy scenarios. It summarizes previous studies on the determinants of food security and presents descriptive statistics and econometric results from a study in Nepal. The model indicates that natural capital factors like water access and social capital factors like caste and remittances significantly impact food security, and next steps are proposed to improve the model.

1. Food Security:
Development of an Optimal
Investment and
Consumption Model
Steven Archambault
*Job Market Candidate, University of New Mexico, Dept. of
Economics, MSC 05 30601, Albuquerque, NM 87131-0001 USA,
Phone: 505-277-5304, Fax: 505-277-9445,
Email: sarchamb@unm.edu

2. Study Objective:
-Develop a general dynamic optimization model of
household food security.
-Use the model to simulate various policy scenarios
•Brief definition of food security
•Previous work
•Development of the model
•Simulation results
•Next steps

3. Food Security Defined—Food and
Agriculture Organization
‘Food security exists when all people, at all times, have physical and
economic access to sufficient, safe and nutritious food to meet their
dietary needs and food preferences for an active and healthy life’
-World Food Summit 1996, 2002
-Households concerned about current and future
consumption
-Food security is higher when food is available today and
tomorrow
Tradeoffs
-Assets can be consumed now, or in the future
-Assets can be invested in capital in hopes that this will
generate future assets

5. Organized into….
Human Capital Physical Capital
Food Security
Social Capital Natural Capital

6. Previous Studies
-Determinants of Food Security: A question of vulnerability
and access to food (Amartya Sen)
•Land degradation (Holden and Shiefraw, 2004; •Access to loans (Coates et al., 2006)
Misselhorn, 2005)
•Assets (Misselhorn, 2005)
•Income (Coates et al., 2006)
•Role of policies (Holden and Shiefraw, 2004;
•Household production (Feleke et al., 2005) Misselhorn, 2005)
•Environmental degradation (Misselhorn, •Education (Babatunde et al., 2005)
2005)
•Geographic distribution (WFP, 2006)
•Role of policies (Holden and Shiefraw, 2004) •Farm size (Babatunde et al., 2005)
•Informal labor and Social Relations •Land quality (Feleke et al., 2005)
(Kerr, 2005)
•Class or Social group (Kerr, 2005) •Assets (Animals) (Feleke et al., 2005)
•Shocks (Conflict, Drought)(Alderman et al., •Available inputs (Feleke et al., 2005)
2006; Baro and Deubel, 2006) •Market acess (Misselhorn, 2005)

7. Food Security in Nepal
•30% of the rural population does not have access to
regular nutritious food (WFP, 2006)
•Seasonal food production (lean period: 2 weeks-2
months)
•Geography plays a role in access to food (mountainous,
hilly, and terai (plains))
•Environmental and conflict, and other shocks
•Poor Education (64% with lowest food intake have no
school)
•50%-60% of children in poor food consumption
households have stunting.

8. Food Security in Nepal
Number of
HHs % of HHs
Ranking (weighted) (Weighted)
Very Poor 259.44 15.54% 56.5% L
Poor 184.29 11.00%
Fairly Good 503.41 30.00%
Good 674.42 40.23% 43.5% H
Very Good 54.05 3.23%
N=1676

10. A few assumptions
Natural Capital
•Deforestation leading to soil erosion and flooding,
should impact food security.
•Poor soil fertility should impact food security (requires
more fertilizer)
•Access to water resources important for maintaining
food security
Social Capital
•Remittances give income to increase food security
•Higher castes, better network for maintaining food security

11. Descriptive Stats..continuous variables
N=1687
Variable Mean Std. Dev. Min Max
HH Size 6.630113 3.814438 1 89
land size 0.5120865 0.6037985 0 6.47
remittance 16556.55 46465.74 0 800000
# cows 1.984588 2.257924 0 18
# goats 2.763485 6.01346 0 150
# poultry 4.505039 28.68469 0 1000
water dist 3.850889 14.32928 0 360
tax 173.8868 1337.246 0 30000

12. Descriptive Stats…Dummy Variables
N=1687 # %
farm 751 44.52%
garden 1387 82.22%
agric 1490 88.32%
agric rain 799 47.36%
agric nat 738 43.75%
agric chem/nat 379 22.47%
farm pesticide 349 20.69%
floodser 60 3.56%
bandh 109 6.46%
credit_bank 273 16.18%
education 409 24.24%
janjati 631 37.40%
dalit 315 18.67%
western 591 35.03%
midwest 280 16.60%
farwest 273 16.18%

13. Econometric Model—Logistic Regression
n=R
e ∑β W k ki
Yi =
k =1
n=R
1+ e ∑β W
k =1
k ki
Ordered Logit
n=R
Pr(outcomek=n) = Pr(Zn-1< ∑β W
k =1
k ki + ui < Z )
n
Logit
n=R
Pr(outcome=1) = Pr(0< ∑ β kWki + ui )
k =1

14. Econometric Results
Predicted Correctly?
Ordered Logit 5 Logit Binary
predicted actual % predicted actual %
foodsec 1w 76 259.4 29.29% 200 443.7 45.07%
foodsec 2w 0 184.3 0.00% 1019 1232 82.72%
foodsec 3w 288 503.4 57.21%
foodsec 4w 293 674.4 43.44%
foodsec 5w 1 54.05 1.85%
total 658 1676 39.27% 1219 1676 72.75%
Ordered Logit 3==48%

15. Econometric Results…
waterdist -0.02938 0.00683 -4.30 *** -0.02998 0.00739 -4.06 ***
landsize 0.303959 0.09987 3.04 *** 0.514702 0.1636 3.15 ***
tax -7.6E-05 7.2E-05 -1.1 -0.00013 0.00011 -1.10
transport 3.34E-05 0.00011 0.3 -1.50E-06 9.5E-05 -0.02
remit 4.49E-06 1.77E-06 2.53 *** 8.71E-06 3.27E-06 2.66 ***
cownum -0.11655 0.03471 -3.4 *** -0.13392 0.04001 -3.35 ***
poultnum 0.00752 0.00229 3.28 *** 0.008372 0.0116 0.72
goatnum -0.01998 0.02046 -1 -0.0099 0.0222 -0.45
agric1 -0.12314 0.1622 -0.8 -0.0246 0.21101 -0.12
agricrain -0.3622 0.12882 -2.8 *** -0.41675 0.18188 -2.29 **
agricchemboth -0.1817 0.17463 -1 -0.38148 0.24855 -1.53
agricnatchem -0.15397 0.1611 -1 -0.07392 0.21521 -0.34
pesticide 0.874976 0.17276 5.06 *** 0.963391 0.26739 3.60 ***
floodser -0.07976 0.31008 -0.3 -0.36087 0.46544 -0.78
bandh 0.901603 0.2827 3.19 *** 0.88895 0.42734 2.08 **
credit_bank 0.368958 0.21039 1.75 ** 0.264561 0.25854 1.02
educationM 0.278764 0.15875 1.76 ** 0.23131 0.20159 1.15
janjati -1.2849 0.15262 -8.4 *** -0.76327 0.2024 -3.77 ***
dalit -0.78364 0.19802 -4 *** -0.63847 0.24209 -2.64 ***
western 0.1216 0.19783 0.61 0.566664 0.31833 1.78 *
midwest -0.54738 0.21627 -2.5 *** -1.06253 0.24895 -4.27 ***
farwest -0.86245 0.22764 -3.8 *** -1.40677 0.26116 -5.39 ***
Log pseudo-
likelihood -2016.2 -777.729
Wald chi2(23) 256.05 208.37
Prob > chi2 0.00000 0.00000
Pseudo R2 0.1278 0.2037

16. Conclusions and Next Steps
• Natural Capital impacts on food security…access to
water, irrigation matter
• Long-term drought might be a problem associated with
climate change
• Might want to look at GIS data, forest cover
• Social Capital has a few variables showing strong
impact on food security…castes matter, remittances
matter
• Could look more into caste data
• Add in conflict data, employment data, other costs,
shocks, food aide, policy variables, etc.