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FOOD SCIENCE & TECHNOLOGY

Impacts of improved agricultural technologies on food security and child nutrition in rural Ethiopia

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Article: 2276565 | Received 30 Aug 2022, Accepted 24 Oct 2023, Published online: 02 Nov 2023

Figures & data

Figure 1. Sample distribution across periods of the survey.

Source: Authors’ computation using ESS (2013 and 2015).
Figure 1. Sample distribution across periods of the survey.

Table 1. FE results row planting: outcome variable is per capita consumption expenditure

Table 2. FE results row planting: outcome variables: ln per capita consumption expenditure, ln child nutrition, food shortage, and worry about food

Table 3. FE, PSM, and ETE methods’ results on the impact of row planting on the welfare of rural households

Table 4. FE results for HYVs: outcome variable is per capita consumption expenditure

Table 5. FE, PSM, and ETE methods’ results on the impact of HYVs on per capita consumption and child nutrition

Table 6. FE method’s results for fertilizer use: outcome variable is per capita consumption expenditure

Table 7. FE, PSM, and ETE methods’ results on the impact of fertilizer use on the welfare of rural households

Table 8. Summaries of FE, PSM, and ETE methods’ results for the three technologies

Table 9. Heterogeneous/Differential impacts of the three technologies by area under improved technology, gender, and observation year

Table A1. A Description of the variables by type for row planting technology

Table A2. Covariate balance indicators before and after matching: quality test

Table A3. Test of sensitivity analysis to hidden biases (Rosenbaum bounds test results)

Figure B1. Propensity score distribution and common support for propensity score estimation of technology one: spacing.

Figure B1. Propensity score distribution and common support for propensity score estimation of technology one: spacing.

Figure B2. Propensity score distribution and common support for propensity score estimation of technology two: HYVs.

Figure B2. Propensity score distribution and common support for propensity score estimation of technology two: HYVs.

Figure B3. Propensity score distribution and common support for propensity score estimation of technology three: Fertilizers.

Notes: Untreated: On-support indicates the observations in the non-adoption group that have a suitable comparison. Untreated: Off-support indicates the observations in the non-adoption group that do not have a suitable comparison.Source: Author’s calculations using ESS (2013 and 2015).
Figure B3. Propensity score distribution and common support for propensity score estimation of technology three: Fertilizers.