Abstract
This study aims to assess the impact of short-term policies on smallholder farmers’ household food security. It answers three key questions: What is the impact of selected policies on farmers’ household food security? What would have been the impact of these policies if implemented perfectly? Are the perceived impacts of food security policies in line with their estimated impacts? For this purpose, a conceptual model is proposed using a partial equilibrium model approach. The model identifies policy impact pathways. Two demand side policies (food subsidy and minimum wage rate) and two supply side policies (wheat support price and urea subsidy) are assessed. Results show that one of each improves farmers’ household food security. Furthermore, these policies are poorly implemented and consequently their potential benefits are much reduced. The comparison of farmers’ perceptions and their estimated monetary gains shows notable divergence. This study suggests that more research is warranted into the potential of food security policies, as much of their effectiveness is lost due to poor implementation. It also suggests that, for the Punjab, policies emphasising wheat support prices better address food insecurity than urea subsidies.
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Appendices
Appendix 1
Food Composition Table (AIOU 2001) | Amount in 100 g of edible portion | ||
Name of Food | kcal | Name of Food | kcal |
Corn Whole grain flour | 276 | Apple | 57 |
Rice Polished Fried | 268 | Banana Ripe | 96 |
Vermicelli | 345 | Dates Dried | 293 |
Wheat Whole grain flour | 357 | Dates Fresh | 131 |
Wheat flour Granular | 370 | Guava Whole | 73 |
Wheat Bread | 369 | Lemon | 30 |
Wheat Bread | 259 | Lichi | 62 |
Wheat Bread | 364 | Mango Ripe | 64 |
Wheat Bread | 293 | Melon Water | 23 |
Wheat Bread | 263 | Mandarin | 44 |
Wheat Flour | 440 | Orange Sweet | 43 |
Broad Bean Cooked | 175 | Peach | 47 |
Chickpea Cooked | 187 | Pomegranate | 66 |
Lentil Cooked | 178 | Zizyphus | 79 |
Mung Bean Cooked | 120 | Butter Milk | 31 |
Mash Cooked | 158 | Curd | 52 |
Bath Sponge | 18 | Cream | 361 |
Bottle Gourd | 15 | Milk Buffalo Fluid Whole | 105 |
Bringal | 26 | Milk Cow Fluid Whole | 66 |
Cauliflower | 27 | Milk Goat Fluid Whole | 70 |
Cucumber | 16 | Yogurt | 71 |
Lady Finger | 35 | Ice-cream | 148 |
Spinach | 27 | Beef | 244 |
Tinda | 23 | Buffalo Meat | 123 |
Carrots | 37 | Chicken Meat | 187 |
Onion | 44 | Goat Meat | 164 |
Potato | 83 | Sheep Meat | 175 |
Reddish | 23 | Chicken Egg White | 400 |
Turnip | 26 | Duck Egg White (Raw) | 895 |
Cumin Seed | 336 | Butter | 721 |
Liquorice Root | 212 | Ghee | 874 |
Clove | 304 | Ghee (Buffalo) | 900 |
Turmeric | 365 | Lard (Raw) | 899 |
Pepper Black | 268 | Dalda (Hydrogenated Oil) | 892 |
Corn Oil | 900 | Jaleebe | 395 |
Soybean | 887 | Koa (Whole Buffalo Milk) | 401 |
Sugar | 380 | Halwa Sohen | 481 |
Gur | 310 | Carbonated Beverages Pepsi, Coke, etc. | 39 |
Honey | 310 | Lemon Juice | 43 |
Barfi | 384 | Mango Juice | 74 |
Appendix 2
Adult equivalent units by current study
Age groups (years) | Male | Female |
<1 | 0.43 | 0.43 |
1–3 | 0.54 | 0.54 |
4–6 | 0.72 | 0.72 |
7–9 | 0.87 | 0.87 |
10–12 | 1.03 | 0.93 |
13–15 | 0.97 | 0.80 |
16–19 | 1.02 | 0.75 |
20–39 | 1.00 | 0.71 |
40–49 | 0.95 | 0.68 |
50–59 | 0.90 | 0.64 |
60–69 | 0.80 | 0.51 |
70+ | 0.70 | 0.50 |
Source: NSSO 1995
Appendix 3
Descriptive Statistics
Continuous variables | Min | Max | Mean | Std. D |
Calorie intake-Cal i (Kcal/AE/Day) | 612 | 4989 | 3193 | 809 |
Gains from wheat support price-wSub i (Rs) | 0 | 495 ($ 5) | 171 ($ 2) | 156 |
Gains from urea subsidy-uSub i (Rs.) | 0 | 375 ($ 4) | 62 ($0.65) | 73 |
Monthly income-MI i (Rs.) | 2193 ($ 23) | 56,217 ($593) | 19,485 ($206) | 9729 |
Household heads’ age-HHHA i (Years) | 22 | 76 | 46 | 10 |
Family size-fSize i (Numbers) | 1 | 25 | 7 | 3 |
Total earning members-Tear i (Numbers) | 1 | 5 | 1 | 1 |
Land holdings-LH i (Acres) | 1 | 5 | 4 | 1 |
livestock large animals-LSA (L)i (Numbers) | 0 | 26 | 6 | 4 |
livestock small animal-LSA (S)i (Numbers) | 0 | 8 | 3 | 1 |
Household distribution by household heads’ education levels
Education levels | Illiterate | Primary | Middle | Intermediate | Graduation |
Number of households | 96 (17 %) | 195 (34 %) | 80 (14 %) | 158 (27 %) | 47 (8 %) |
Household distribution by getting food subsidy
Received | Did not receive | |
Number of households | 356 (62 %) | 220 (38 %) |
Household distribution by off-farm work
Worked | Did not work | |
Number of households | 480 (83 %) | 96 (17 %) |
Household distribution by receiving minimum wage
Received | Did not receive | |
Number of households | 342 (71 %) | 138 (29 %) |
Household distribution by decision making
Females | Males | |
Number of households | 174 (30 %) | 402 (70 %) |
Household distribution by family structure
Nuclear | Joint | |
Number of households | 348 (60 %) | 228 (40 %) |
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Bashir, M.K., Schilizzi, S. Food security policy assessment in the Punjab, Pakistan: effectiveness, distortions and their perceptions. Food Sec. 7, 1071–1089 (2015). https://doi.org/10.1007/s12571-015-0489-y
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DOI: https://doi.org/10.1007/s12571-015-0489-y