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. Author manuscript; available in PMC: 2025 Oct 1.
Published in final edited form as: World Dev. 2024 Jul 6;182:106714. doi: 10.1016/j.worlddev.2024.106714

Table A7:

Impact of regional food price increase on food insecurity with different sample sizes
(1) (2) (3) (4) (5) (6) (7) (8)
HHs that remain in sample until last round Sample with HHs in all four rounds
Short run Medium run Short run Medium run
Outcome variables: Moderate-or-severe Severe Moderate-or-severe Severe Moderate-or-severe Severe Moderate-or-severe Severe
Food price increase 1.008*
(0.005)		 1.006
(0.008)		 1.014***
(0.005)		 1.025***
(0.010)		 1.007
(0.005)		 1.006
(0.008)		 1.014***
(0.005)		 1.027***
(0.010)
Health shock 0.934
(0.127)		 0.840
(0.195)		 0.711**
(0.102)		 0.388***
(0.119)		 0.959
(0.132)		 0.808
(0.191)		 0.743**
(0.110)		 0.376***
(0.119)
Non-agri. income loss 2.872***
(0.595)		 1.725*
(0.507)		 1.033
(0.220)		 0.585
(0.215)		 2.970***
(0.621)		 1.817**
(0.543)		 1.021
(0.225)		 0.491*
(0.187)
Loss of crop 1.540*
(0.350)		 1.795*
(0.539)		 1.083
(0.256)		 0.811
(0.278)		 1.507*
(0.344)		 1.774*
(0.535)		 1.115
(0.267)		 0.980
(0.342)
Theft of property 1.201
(0.238)		 0.854
(0.268)		 1.091
(0.234)		 1.021
(0.364)		 1.169
(0.234)		 0.859
(0.270)		 1.108
(0.246)		 1.062
(0.388)
Negative ag. Price shock 0.948
(0.189)		 1.276
(0.438)		 1.331
(0.279)		 0.892
(0.313)		 0.933
(0.187)		 1.271
(0.437)		 1.400
(0.306)		 0.894
(0.315)
No of observations 3,023 1,214 2,574 973 2,976 1,192 2,444 936
Number of households 761 306 657 247 744 298 611 234

Note: Conditional logit model. Odds ratio presented and standard errors are in parentheses.

***

indicates significance at 1% level

**

at 5%

*

at 10%. All dependent variables are dummy variables. “HH” represents households