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Figure 1. Fractional polynomial regression of household WTP to stabilize at their means the prices of the seven commodities retained for analysis on household.

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Presentation on theme: "Figure 1. Fractional polynomial regression of household WTP to stabilize at their means the prices of the seven commodities retained for analysis on household."— Presentation transcript:

1 Figure 1. Fractional polynomial regression of household WTP to stabilize at their means the prices of the seven commodities retained for analysis on household income for households whose seasonal income does not exceed 10,000 birr, with 95% confidence interval. The histogram plots the proportion of households falling in each income category From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

2 Figure 2. Robustness check for the fractional polynomial regression in figure 1 using robust regression estimates From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

3 Figure 3. Robustness check for the fractional polynomial regression in figure 1 using M-regression estimates From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

4 Figure 4. Robustness check for the fractional polynomial regression in figure 1 using MS-regression estimates From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

5 Figure 5. SUR Estimation of OLS Specifications with θ=0.001
From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

6 Figure 6. SUR Estimation of OLS Specifications with θ=0.01
From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

7 Figure 7. SUR Estimation of OLS Specifications with θ=0.1
From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

8 Figure 8. SUR Estimation of OLS Specifications with θ=0.5
From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

9 Figure 9. SUR Estimation of OLS Specifications with θ=2
From: The Welfare Impacts of Commodity Price Volatility: Evidence from Rural Ethiopia Am J Agric Econ. 2013;95(4): doi: /ajae/aat018 Am J Agric Econ | © The Author (2013). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved. For permissions, please

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