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# Session 6.2 small scale rubber farming, china

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• Reply comments:1. The objective of this tableis to show the land use for rubber farming. i.e. the share of rubber land area in total land area.“Percentage in total” just means the share of rubber land area in total land area. 81% illustrate that about 81% of land area are used for planting rubber for the total samples.For the different ethnic groups, we want to compare the differences of land use share for rubber.As we know, Dai and Hani people plant rubber earliest, and Yao people are the last.So the results suggest that the ethnic group who planted rubber earlier, the share of land use for rubber is higher.The ethnic group planted rubber more later, the share of land use for rubber is less.For the different altitude/counties, it is the similar explains.With the increasing of altitude, the share of land use for rubber is decreasing.2.For your comments, I agree with you that we should calculate the frequency.It could show the basic rubber land situation of our samples and describing our sample distributions by different categories.But I think it totally depends on our sample selections, It is unavailable to identify the differences of land use for rubber.So I suggest that at this moment, we just use the current table.
• Left side of the dashed line denotes that price is below the breakeven point, and net revenues of these rubber plots are negativeThe variation of distance in the left side illustrates the riskiness of rubber farming Reply your comment:The reasons that the actual price be below break even price more than 100:It is because that some rubber plots are the first year to harvest. In this situation, the farmers only harvest several times, so the production is very low. But they still need to invest. Hence breakeven price is quit large.e.g. the yield of first year is 2 kg/mu, and the price is 10yuan/kg. expense of input is 150 Yuan/mu, cost of family labor is 300yuan/mu.So the breakeven price is (300+150)/2=225yuan/kg, thus the distance 10-225=-215So there are several points where the actual price is below break even price more than 100.
• Here we need not to assume that rubber harvest starts after 6 year.Because the Harvest phase in the bar graph is just the productive phase.The productive phase is divided into three sub phase:1-5 years: means it is the first to 5th year after the beginning of harvesting. Named: Initial phase of harvesting.6-10years: means it is the 6th to 10th year after the beginning of harvesting. Named: Middle phase of harvestingMore than 10 years: means it is already harvested more than 10 years. Named: Final phase of harvesting
• ### Session 6.2 small scale rubber farming, china

1. 1. Small scale rubber farming and income risk in Xishuangbanna, China Hermann Waibel, Shi Min Institute of Development and Agricultural Economics, School of Economics and Management, Leibniz University Hannover Jikun Huang Center for Chinese Agricultural Policy, Chinese Academy of Sciences
2. 2. Outline  1. Background  2. Objectives  3. Data  4. Results  5. Conclusions
3. 3. Background  Conditions of Xishuangbanna Dai autonomous prefecture • • • Located in the southern of China, bordering Laos, Myanmar 95% of area is mountain Diversity of Ethnic Minorities • Development of rubber economy • • • 1950-60s: Introduction of rubber 1970-80s: Rubber expansion by state-own farms Since 1990s: Expansion of rubber plantation by Small scale farmers • Consequences of rubber for smallholders • • Increase in household income and changes in livelihoods Potential environmental and food security risks  Current researches status • • • Most previous studies are qualitative analysis or smaller case studies Poor representation of smallholder rubber farming in Xishuangbanna Insufficient quantitative information on rubber farming (e.g. yield, input use)
4. 4. Objectives  Survey and analyze the status quo of smallholder rubber farming • e.g. Land use, Input, Yield, Productivity, Revenue  Identify and discuss the critical values for rubber yield and price by breakeven analysis  Assess the contribution of rubber to household income  Explore the potential income riskiness of small rubber farmers using appropriate income diversification indices
5. 5. Data  • Baseline survey of SURUMER-SP9 on March 2013 Questionnaire design Pre-survey: July 2012 Pre-test: December 2012 • Sampling Stratified random sampling design (Based on population, rubber area and geographic location) 8 townships; 42 villages • Enumerators training 5 days training: 3 days class room lectures and exercises 2 days field training • Household survey Compensation 30 Yuan /per household 612 households Response rate 84 % (of sample drawn)
6. 6. Results  Rubber farming • Land use for rubber farming Percent in total rubber land (mu/person) Share of rubber land area in total land area (%) 13.36 10.57 81% 100% Han Dai Hani Yi Bulang Jinuo Yao Others 10.46 10.11 18.30 24.04 15.18 18.20 15.91 5.29 6.47 8.58 16.69 15.63 10.52 14.84 10.16 4.33 75% 85% 88% 69% 72% 79% 58% 82% 2.7% 47.5% 17.7% 15.2% 8.5% 6.0% 2.3% 0.1% Altitude≤800 meters 800<Altitude≤1000 meters Altitude>1000 meters County Menghai Jinghong Mengla 12.74 10.53 85% 68.1% 12.93 9.75 74% 27.0% 35.39 21.81 62% 5.0% 10.71 9.80 18.23 7.46 8.35 14.12 77% 84% 79% 8.9% 36.6% 54.5% Total land area (mu/person) Categories All sample (612 households) Ethnic Rubber land area Altitude
7. 7. Results  Contribution of rubber to household income by category Total net income Rubber net income Percentage of rubber income Yuan/person/year Yuan/person/year in total 16515.72 6842.24 41% 0 year 14262.97 6692.15 47% 1-6 years 15570.10 6985.37 45% 7- 16 years 21555.41 6729.40 31% Han 18150.01 3336.54 18% Dai 12845.30 7024.08 55% Hani 22805.97 13372.22 59% Yi 22783.56 1179.63 5% Bulang 16674.77 6493.13 39% Jinuo 39343.31 8791.59 22% Yao 5313.97 -1228.05 -23% Categories Total Education of household head Ethnic groups
8. 8. Results  Contribution of rubber to households income by category Total net income Rubber net income Percentage of rubber income Yuan/person/year Yuan/person/year in total Altitude≤800 meters 16890.27 8537.672 51% 800<Altitude≤1000 meters 12850.11 3768.178 29% Altitude>1000 meters 51437.13 -1812.035 -4% Menghai 10195.23 2686.73 26% Jinghong 14944.51 7177 48% Mengla 20408.45 7869 39% Categories Altitude County
9. 9. Results  Cost of rubber farming input in 2012 (Yuan/mu) Categories Total expenses Expense items Fertilizer Pesticide Hiring labor 164.72 134.90 24.87 4.94 0 year 168.59 137.26 29.95 1.39 1-6 years 156.82 131.71 23.06 2.05 7- 16 years 177.60 139.05 22.24 16.31 Han 262.56 220.64 34.99 6.93 Dai 185.13 157.24 26.19 1.70 Hani 151.98 101.00 25.27 25.71 Yi 89.28 70.28 16.25 2.74 Bulang 110.57 86.53 23.23 0.80 Jinuo 126.28 96.92 22.31 7.04 Yao 106.34 90.36 15.98 0.00 All samples (1667 plots) Education of household head Ethnic groups
10. 10. Results  Cost of rubber farming input in 2012 (Yuan/mu) cont. Categories Total expenses Expense items Fertilizer Pesticide Hired labor Altitude Altitude≤800 meters 164.71 133.97 23.98 6.76 800<Altitude≤1000 meters 170.43 141.68 27.83 0.92 altitude>1000 meters 98.16 81.64 15.20 1.33 Menghai 169.16 141.08 26.51 1.57 Jinghong 203.99 172.80 27.24 3.95 Mengla 118.56 89.70 21.62 7.23 Yes 182.57 146.91 28.94 6.72 No 146.51 122.65 20.72 3.13 County Harvest started
11. 11. Results  Productivity and Revenue of rubber plantation in 2012 (Yuan/mu) Rubber cake Gross Revenue Net revenue kg/mu Yuan/mu Yuan/mu 112.02 2341.30 2158.73 0 year 126.28 2579.72 2383.42 1-6 years 109.40 2286.15 2114.28 7- 16 years 96.94 2118.48 1929.57 Han 128.43 2011.68 1833.69 Dai 113.13 2395.54 2197.85 Hani 105.00 2470.62 2294.80 Yi 118.76 1929.84 1818.00 Bulang 95.76 2015.79 1945.95 Jinuo 108.78 2072.36 1926.61 Yao 40.00 520.00 113.00 Categories All samples (842 harvested plots) Education of household head Ethnic groups
12. 12. Results  Productivity and Revenue of rubber plantation in 2012 (Yuan/mu) cont. Rubber cake kg/mu Gross Revenue Yuan/mu Net revenue Yuan/mu 1-5 years 6-10 years More than 10 years 91.94 117.68 128.18 1788.59 2527.47 2760.83 1619.37 2358.88 2552.85 Altitude≤800 meters 800<Altitude≤1000 meters altitude>1000 meters 117.19 95.96 43.33 2536.95 1716.16 1430.00 2351.15 1543.06 1346.00 Menghai Jinghong Mengla 82.11 119.99 107.95 2323.36 2480.51 2141.36 2106.61 2271.80 2005.94 Categories Harvest phase Altitude County
13. 13. Results County Breakeven point (mean) Price (Yuan/kg) Yield (kg/mu) Total samples 28.36 46.73 21.97% Menghai 55.08 66.24 31.65% Jinghong 35.80 56.06 27.31% Mengla 10.59 28.02 11.65%
14. 14. Results • Distribution of distance between actual price and breakeven price Kernel density distribution Cumulative distribution 0 0 .2 .01 .4 .02 Total .6 .03 .8 .04 1 Total samples -400 -300 -200 -100 Price_minus_Breakevenprice kernel = epanechnikov, bandwidth = 2.5700 0 100 -400 -300 -200 -100 Price_minus_Breakevenprice 0 100
15. 15. Results .2 .4 .6 .8 1 Cumulative distribution of distance between price and breakeven price for the three counties. 0 • -400 -300 -200 -100 Price_minus_Breakevenprice Menghai Mengla Jinghong 0 100
16. 16. Results • Percent of Yield below Breakeven point by harvest phase 30% 25% • Percent of Yield below Breakeven point by altitude Altitude>800 29.50% 26.89% 20% 21.77% 15% 16.05% 700<Altitude≤800 26.09% 600<Altitude≤700 19.33% 10% 5% Altitude≤600 15.64% 0% 1-5 years 6-10 years More than 10 years 0% 5% 10% 15% 20% 25% 30% 35%
17. 17. Results Categories Total sample Rubber Crops except rubber Livestock Off farm Employment Self-employment Natural resource extraction Cash gift Public transfers Source 612 607 403 111 143 66 444 213 409 Income Yuan/person/year 19530.71 8477.80 4811.86 1317.05 1790.61 2070.30 169.77 623.05 270.27 Net Income Yuan/person/year 16515.72 6842.24 4164.83 600.44 1790.61 2070.30 153.98 623.05 270.27
18. 18. Results • Calculation results of Shannon Equitability Index Average: 0.48 • Shannon Equitability Index by Ethnicity Highest: Yao 0.69 Lowest: Bulang 0.39 0.7 0.6 0.5 0.4 0.69 0.3 0.2 0.39 0.45 0.48 0.48 0.49 0.49 0.55 0.1 0 Bulang Hani Total samples Yi Han Dai Jinuo Yao
19. 19. Results • Shannon Equitability Index by education level of household head Education of household head 0 year 1-6 years 7- 16 years Shannon equitability index 0.47 0.49 0.49 • SEI by share of rubber land in total 0.6 • SEI by household location Categories SEI Altitude 0.5 Altitude≤800 meters 800<Altitude≤1000 meters 0.57 Altitude>1000 meters 0.27 Menghai 0.51 Jinghong 0.47 Mengla 0.4 0.45 0.49 County 0.3 0.2 0.1 0 Percent≤0.5 0.5<Percent≤0.8 0.8<Percent≤1
20. 20. Results • Effect of income diversification on rubber farming riskiness - Index of income diversification : Shannon Equitability Index(SEI) - Index of farming riskiness: For the plots which actual yield below breakeven points: Riskiness=|yield minus Breakeven yield|
21. 21. Conclusions  Rubber has taken over the rural economy in Xishunangbanna and other parts of Southern China (81% of the total land is used for rubber cultivation) and poverty has been reduced in the area.  Land usage, Input, productivity and revenue of smallholders rubber farming differ among ethnic groups, locations and the characteristics of household head.  Over 40 % of household income is now from rubber farming  Over 20% of rubber plots (in harvest phase) are below the breakeven point indicating riskiness of rubber farming which is affected by ethnic groups, harvest phase and altitude.  Diversity in income sources is 0.48 low on average (SEI = 0.48) but varies by ethnic minority groups (Yao = 0.69) and (Bulang =0.39).  There is some notion of a kind of “optimal diversity” based on our simple risk measure.  Econometric analysis can provide more insights into the opportunities and risks of rubber farming.
22. 22. Thanks for your attention!