% % %

2006 5 14 100 * 2010 28 1. 28 2009 111. 53 2011 2009 2012 2011 2010 2011 2008 2008 2011 2012 2009 2008 2011 2008 2012 78 * 43

2013 6 337 2012 4 1050 832 752 624 624 23 95. 81% 60. 9% 22. 53% 34. 83% 42. 76% 3 ~ 5 98 2007 50 2011 1024 1 128. 62% 133. 43% 126. 72% 2007 1 % % 2007 50 1150 750 78. 2 400 2008 168 3346 2120 3. 4 73. 8 2031 2009 364 10002 5594 9. 1 71. 0 83. 5 4408 1. 1 6800 2010 413 11400 6939 10. 3 78. 3 72. 2 4600 6. 4 28900 2011 1024 26200 16400 21. 3 79. 1 73. 4 9800 16. 8 78300 2011 12 99. 23% 2011 218 2011 300 10 302 50. 59% 1. 4 3035 9. 95% 53. 44% 4. 1 823 * 1. 49% 7 1% 5 16. 8 7. 83 4661 * 2011 2010 1500 44

5 70% 44. 4% 2011 2009 2011 1. 64 2009 2011 1024 83. 5% 2010 72. 2% 2. 62 1. 13 2007 0. 08 0. 51 0. 98 43. 13% 2011 21. 3 16. 8 19. 47% 37. 40% * 0. 79 2010 0. 62 ** 1. 00 ~ 1. 25 *** 0. 63 2995. 62 197. 35 12875. 27 312. 56 82. 32% 15. 52% 1. 624 488 1 /3 1 78. 20% 108 1 17. 31% 28 1 3. 215 34. 46% 4. 49% 23. 63% 2 /3 2. 3 ~ 5 * ** *** = / = / / = / / 45

2013 6 19. 77% 60. 21% 15. 04% 4. 98% 1. 24 58. 42% 1. 135 5 3. 70% 50 624 441 70. 67% 4. 89% 30 ~ 100 54. 00% 46. 00% 2. 158 25. 32% 3. 25 145 23. 24% 3 4. 01% 323 51. 76% 2 119 19. 07% 1 37 5. 93% 3 ~ 4 52. 38 46. 63 5000 98. 56% 93. 43% 3000 5000 10000 46

74. 67% 1. 95 2. 60% 2 % 3000 9 1. 44 5000 583 99. 39 10000 32 5. 13 < 6 175 28. 04 0 6 ~ 7 184 29. 49 8 ~ 9 222 35. 58 10 < 43 6. 89 383 61. 38 241 38. 62 42. 47% 99. 26% 98. 88% 98. 1 97. 32% 45. 83% 100. 00% 99. 52% 99. 16% 99. 07% 61. 38% * 98. 89% 4. 80% 1 /5 54. 32% 35. 47% 39. 33% 2. 2011 99. 23% 1 99. 41% 6. 91% 3. 30% 5% 1 1. 2010 3000 2 ~ 3 2010 474 3000 ~ 5000 3 ~ 5 75. 96% 150 24. 04% 2011 1 5000 4 5 20. 00% 3. 24 5. 92% ** * ** = / 47

2013 6 40. 00% 2010 2011 5 ~ 7 4. 25 2 /3 17. 14% 1 5. 73 5 ~ 7 30% ~ 40. 26% 40% 5. 77% 50% 93 14. 90% 10% 80 424 67. 95% 1 ~ 2 102 1 /5 16. 35% 3% 3. 1. 4. 2. 1.. 2011 1 ~ 2 2... 2012 8 65 ~ 72 48

* * 402 Logistic Logistic 2006 2007 2008 2008 檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯檯 3... 2008 11 23 ~ 27 4... 2008 6 92 ~ 96 5... 2011 23 ~ 29 6... 2008. 5 56 ~ 59 7.... 2009. 6 165 ~ 173 8.... 2009 6 248 ~ 265 9... 2011 9 47 ~ 53 10... 2010 10 83 ~ 86 250103 271018 * 71203147 112400420073 49

Vol. 34 Serial No. 402 The Research on Influencing Mechanism of Rural Credit Cooperatives Reform Mode Selection TONG Yuanbao 37 No matter starting from the necessity and the advantages of the modes and based on the realistic national conditions rural credit cooperatives should stick to diversified reform mode. The paper establishes a comprehensive influence mechanism model which includes a financial demand characteristics as the key factor layer policy guidance economic condition and education environment as a base layer and the industrial structure enterprise scale labor quality and the community quality for dielectric layer jumping out of the simple regional economic structure selection principles. It Can be applied to the reform mode selection and adjustment of rural credit cooperatives scientifically. Hainan case analysis gives a good support. An Empirical Analysis on Operation Status of Poverty Alleviation Mutual Fund Cooperatives PAMFC in Shandong Province GAO Yang and XUE Xingli 43 Abstract This article is focusing on the operation of PAMFC in Shandong Province based on a survey. The findings are PAMFC are under great development. There is a high participation rate of the peasants the operation of the organizations is good whereas there are problems e. g. disproportion of financial distribution bottleneck of management force a low rate of cash flow etc. Suggestions are proposed including balancing the financial distribution improving the quality of management staff advocating installment repayment and building a financial bond between PAMFC and other financial institutions. An Empirical Analysis on Factors Affecting Farmers Willingness to Get Loans from Village and Town Banks Based on Logistic Model ZHANG Songcan 49 Basing on the survey data collected from 402 questionnaires in Henan Province the author made a statistical analysis on the potential Willingness and influential factors to get loans from village and town banks by using the binary logistic regression analysis model. The results showed gender age and family income have great influence on the farmer s potential willingness to get loans from village and town banks. Finally the author put forward some proposals such as training Farmers loan knowledge and advancing the construction of rural related system etc. Conception about Income Quality of Migrant Workers KONG Rong and WANG Xin 55 Migrant worker s income has definitions not only at view of quality but also at view of quality. This paper analyzes asymmetrical characteristic between quantity increase and quality lag and explores relativity among conceptions of income quality and quantity through five dimensions which are taken into account in income quality such as adequacy stability structure cost and knowledge. Evidences from yearbook and field survey are provided to prove that income quality of migrant workers needs to be urgently improved. The Analysis of Multidimensional Poverty and Its Impact Factors of Rural Household in Reservoir Area the Example of Danjiangkou Reservoir Hubei Province!! SHI Zhilei and ZOU Weiran 61 This article is based on survey sampling data from the Dangjangkou Reservoir area. The data was used to analyze the poverty of rural households in the reservoir area with the vision of current consumption long - term accumulation of capital and sustainable development. Furthermore we investigated family characteristics as well as circumstances external to the population which can cause poverty. We found that migration greatly influenced the inhabitants. The effect to immigrations varied according to when to removal. The attitude of inhabitants towards the new technology and the strength of social capital in inhabitants are very important for shaking off poverty. Another finding was that neither the policy of external environmental reconstruction nor the Relief - oriented poverty alleviation efforts of government had any discernible impact on the economic development of the peasant households. 111