DISCUSSION PAPER SERIES 灰 色 収 入 の 推 計 中 国 家 計 調 査 データによる 検 証 岑 智 偉 青 木 芳 将 土 居 潤 子 No.2014-02 京 都 産 業 大 学 大 学 院 経 済 学 研 究 科 603-8555 京 都 市 北 区 上 賀 茂 本 山 Graduate School of Economics Kyoto Sangyo University Motoyama-Kamigamo, Kita-ku, Kyoto, 603-8555, Japan 2014/12/01
2014 12 2007 CHIP 4 1 2010 2010 2 CHIP2007 3 2010 CHIP2007 2010 quantile method 10 38.45% 51.88% 4 2007 UTGI GDP 41.0% 10.9 163.2 1 2007 2008 CHIP *1 0.369 0.398 0.4 5 20% 50% 1 1993 1999 2005 JSPS 25380379 Asia-Pacific Economic Association, Seoul, Korea, September 18-19, 2014 Kar-yiu Wong Corresponding author: cen25@cc.kyoto-su.ac.jp. *1 CHIP 3 1
2007 2010 2 2007 2010 2010 2008 GDP 29.5% 2007 11 3 2011 2007 2010 1 2 2007 2010 2012 2010 2007 2010 2012 1 2 CHIP 2010 2 2010 3 CHIP 4 5 2 2010 2.1 2007 2010 2012 2007 2
2010 (2010) 2010 *2 CHIP2007 *3 ( ) Ỹi i Y i i i C a C b C i = C a,i + C b,i S i i Ỹ i Y i + G i = C i + S i + G i (1) = C i + S i. 1 G i C i = C a,i + C b,i S i C a C b *4 β i β i β i = C a,i C i, β i = C a,i C i. (2) i z i z i G i ξ i (1 ξ i ) 1 *2 2010 *3 7 1 1 10% 2 2 10% 3 2 20% 4 3 20% 5 4 20% 6 9 10% 7 10 10% *4 A 3
Ỹ i = Y i + G i, = C a + C b + S i + z i G i + (1 z i ) G i, = (C a + ξ i z i G i ) + (C b + (1 ξ i )z i G i ) + (S i + (1 z i ) G i ), = C a,i + C b,i + (S i + (1 z i ) G i ) = C i + S i. (3) 1 2 Ỹi Y i β i 3 2 Ỹ i = C i + S i, = C a,i + (S i + (1 z i ) G i ), β i ( ) ( Ca,i ξ i z i + (1 z i ) = + S i + β ) i G i, β i β i ( ) Ca,i = + S i + ω i G i. (4) β i Y i 4 5 Ỹ i Y i = = = ( Ca,i Y i = C a,i β i + S i. (5) ) + S i + ω i G i β i C ) a,i + ω i G i, β i β i ( Ca,i ( β i β i β i β i ) ( Ca,i β i + S i ), C a,i + ω i G i. (6) 2010 Ỹi Y i Ỹi Y i β i = β i β i = β i ω i = 1 *5 G i 2.2 *6 *5 B *6 2 2010 setp1 7 Per Capita Annual Living Expenditure of Urban Households 7 β 1 β 7 step2 e β 1 = β 1,, e β 7 = β 7 7 step3 7 ey 1 ( e β 1 = β 1 ),, ey 7 ( e β 7 = β 7 ) step4 y i ey i 4
( ) *7 1 2008 1 35,462 32,154 7 1 16,885 1 18,577 ( 15,269 ) 2 3 1 110.02% 90.43% 10 7 2 CHIP2007 3 CHIP2007 3.1 CHIP CHIP Chinese Household Income Project 1988 Keith Griffin Carl Riskin John Knight CHIP 2007 CHIP CHIP2007 *8 2007 CHIP urban rural 2 urban *9 *7 6 step1 step4 1 Estimation Value (a) 1 2010 1 e β i = β i 1 Estimation Value (b) Estimation Value (a) Estimation Value (b) eβ i = β i 6 2 *8 2010 2008 2008 CHIP 2008 CHIP 2007 CHIP *9 7 2012 5
3 4995 ( 2 ) 2 CHIP2007 * 10 ( 3-a ) ( 3-b ) CHIP2007 CHIP2007 CHIP2007 4995 2 CHIP 0.05 0.975 3-a Engel s coeffecient 0.05 0.6 CHIP2007 3-a Obs 13647 CHIP2007 4995 CHIP2007 1095.24 390476.2 1857.14 291428.6 1 10 CHIP2007 1095.24 390476.20 1857.14 291428.60 1 CHIP2007 3-b 1 ( 1 ) 1 3 7 CHIP2007 4 *10 step1 2007 7 Per Capita Annual Living Expenditure of Urban Households 7 7 step2 step1 7 CHIP2007 7 step3 7 CHIP2007 step4 Step3 ey i y i 6
( 4 ) 4 2 ( 2 ) 4 2 5 6 4 39.54% 1975 CHIP2007 CHIP2007 2010 i U i = C µ a,i a,i C µ b,i b,i. 1 * 11 β i = C a,i µ a,i =. C i µ a,i + µ b,i µ a,i,µ b,i * 12 β i = β i k( ) l β i,k = β i,l 4 µ a,ik,µ b,ik,µ a,il,µ b,il * 13 CHIP2007 CHIP2007 2 β i,k = β i,l β i,k = β i,l *11 A *12 A *13 A 7
2010 β i = β i CHIP2007 2010 7 β i = β i 3.2 7 i Ỹi β i β i ω i 1 6 Ỹ i = ( β i β i β i β i ) C a,i + Y i + ω i G i, Q i Ỹi Θ i = Y i + ω i G i (7) Θ i ( βi β i β i β i ) C a,i β i β i β i β i β i β i Θ i Q i Y i = ω i G i Q i CHIP2007 7 i Ỹi Θ i * 14 7 Q i Y i i = 1 7 * 15 Q i Step1 CHIP2007 7 7 Ỹi Step2 Step1 β i, i = 1 7 β i β i i Step3 Step4 Step1 Ỹi i Q Q i Y i 5a 5b ( 5-a ) *14 β i > e β i Θ i ey i β i < e β i Θ i ey i *15 > 0 β i > e β i Q i < ey i < 0( β i < e β i ) Q i > ey i 8
( 5-b ) 5a Step1 Ỹi Y i 5a 5-a 3 ( 3 ) 3 CHIP2007 i Q i Ỹi i 5-b Ỹi i Q i Y i 5-b 4 ( 4 4 5b 2010 3 5-a 5-b 1 2 3 CHIP2007 1 Ỹi 29511.38 5a Q i 1 32878.29 5b 1 16564.81 Ỹi 1 12946.57 Q i 1 16313.48 1 Q i 98.48% Q i 10 38.45% 6a 6b 2010 β i = β i 1 Ỹi 2010 Q i 2010 * 16 ( 6-a ( 6-b 2010 2008 GDP 17.5% 29.5% 2010 3 1 3 (1) 7 Per Capita Disposable Income * 17 (2) Total Disposable Income of Urban Households (3) Total Disposable *16 4 *17 (1) 9
Income * 18 (2010 2 Urban Total Gray Income UTGI Aggregate Gray Income AGI UTGI= - AGI= - Total Estimation Income of Urban Households 5 6 Ỹi Q i Total Estimation Income of Households Total Net Income of Rural Households 7 1 Annual Per Capita Net Income of Rural Households AGI UTGI AGI 7a 7b Ỹi Q i 1 UTGI AGI GDP ( 7-a ( 7-b 7-a 7-b CHIP2007 2007 1 UTGI Ỹi 7-a GDP 33.3 % 41.2% 8.9 133.2 10.9 163.2 Q i 7-b GDP 41.0% 48.7% 10.9 163.2 13.0 194.6 * 19 2 AGI Ỹi 7-a GDP 18.8% 26.7% 5.0 74.9 7.1 106.3 Q i 7-b GDP 26.5% 34.2%% 7.0 104.8 9.1 136.2 (3) AGI UTGI 2 1 AGI UTGI Total Disposable Income of Urban Households 9.0 Total *18 (1) Basic Conditions of Urban Households 7 Per Capita Annual Income (3) Flow of Funds Accounts Physical Transaction Total Disposable Income (2) Basic Statistics on People s Living Conditions Annual Per Capita Disposable Income of Urban Households *19 / 2007 12 1 14.97 10
Disposable Income 1.8 15.9 7 8 2 AGI UTGI 4 Discussion 3 5-b CHIP2007 i (i = 1,, 7) 7 Q i Ỹi 5-a Q i 7 G i ω i β i β i ω i 1 CHIP2007 β i > β i ω i > 1 * 20 ω i > 1 CHIP2007 7 ω i > 1 β i > β i * 21 5 2010 2007 CHIP 4 1 2010 2 *20 B *21 5 5 1 2 11
3 CHIP2007 CHIP2007 3 7 10 38.45% 4 2007 UTGI GDP 41.0% 10.9 163.2 CHIP2007 2010 CHIP2007 1 G i ω i G i ω i ω i 2 CHIP 6 References 1. Wang, Xiaolu 2007 Gray icome and income difference National Economic Research Institute, China Reform Foundation. http://www.neri.org.cn/gzlw.asp 2. Wang,Xiaolu 2010 Gray income and distribution of national income Comparative Studies, No.48. 3. Wang,Xiaolu 2011 Gray income has been exaggerated? Comparative Studies, No.54. 4. Wang,Xiaolu 2012 Gray income and development trap, CITIC Press Group. 12
5. Li,Shi(1993), The income distribution of China s economic development, Peking University Press. 6. Li Shi, Renwei Zhao and Ping Zhang (1998) Changes in income distribution in China s economic reform Management World, No.1,43-57. 7. Li Shi and Zhao Renwei(1999) The residents income distribution in China Economic Research Journal, No.4. 8. Wang,Xiaolu and Fan Gang (2005) China s income gap trend and influence factors analysis Economic Research Journal, No.10,24-36. 9. Luo Chuliang Ximing Yue and Shi Li 2011 A Question about Gray income estimation of Wang Xiaolu Comparative Studies, No.52. A. G ( ) µa ( ) µb Max U = Ca Cb, s.t. y + G S = Ca + C b, (µ a, µ b ) (0, 1) C a, C b C a C b 1 y + G S = s y + G), s * 22 y G C a C b ( ) µa C a = (1 s) (y + G), µ a + µ b ( ) µb C b = (1 s) (y + G). µ a + µ b C = C a + C b β = ( ) C a µa (1 s) (y + G) C a + C = b µ a + µ b (1 s) (y + G), = µ a µ a + µ b. (A1) *22 13
A1 G µ a, µ b B. 2 3 4 i β i β i β i β i = C a,i C i C a,i C i = C a,i Ỹ i S i C a,i Y i S i = = (C a,i + ξ i z i G i ) (Y i S i ) (Y i + z i G i S i ) C a,i (Y i + z i G i S i ) (Y i S i ) C a,i Y i + G i (S i + (1 z i ) G i ) C a,i Y i S i, = ξ iz i G i (Y i S i ) z i G i C a,i (Y i + z i G i S i ) (Y i S i ), = (ξ i (Y i S i ) C a,i ) z i G i (Y i + z i G i S i ) (Y i S i ) = (ξ i β i ) (Y i S i ) z i G i (Y i + z i G i S i ) (Y i S i ). (A2) A2 β i β i ξ i β i β i ξ i β i. (A3) ξ i Y i β i ξ i ξ i > β i β i > β i ξ i β i = β i A3 ξ i = β i = β i 4 ω i ω i = ξ iz i + (1 z i ) β i β i = 1, 14
15 Figure1 Per capita income estimated by the method of Engel s coefficient(by table 3-b) 50,000 40,000 The value by NBSC Estimation Value Difference 30,000 20,000 10,000 0 1-group 2-group 3-group 4-group 5-group 6-group 7-group -10,000 Figure 2 Per capita income estimated by the method of Engel s coefficient(by table 4) 50000 Estimation Value The value by NBSC Difference 40000 30000 20000 10000 0 other 1-group 2-group 3-group 4-group 5-group 6-group 7-group -10000
16 Figure 3 Per capita income estimated by decile and quintile (by table5a) 90,000 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 1-decile 2-decile 2- quintile 3- quintile 4- quintile 9-decile 10-decile 0.6 0.5 0.4 0.3 0.2 0.1 0 Per Capita Annual Income(NBSC) Engel s coeffecient(nbsc,right) Per Capita Annual Income(EV) Engel s coeffecient(ev,right) Figure 4 Per capita income estimated by decile and quintile (by table5b) 120,000 The value by NBSC Adjusted estimated value Difference 100,000 80,000 60,000 40,000 20,000 0 1-decile (10%) 2-decile (10%) 2- quintile (20%) 3- quintile (20%) 4- quintile (20%) 9-decile (10%) 10-decile (10%)
17 Table1 Estimates of the "gray income" of Wang (2010) Engel s coeffecient (a) Estimated value (a) (b) Estimated value (b) (c) The value by NBSC (d) a-c (e) b-c di Σdi*100 ei Σei*100 1-decile(10%) 0.481 5,685 5,350 4,754 931 596 0.56 0.43 2-decile(10%) 0.459 8,646 7,430 7,363 1,283 67 0.78 0.05 2- quintile(20%) 0.429 13,392 11,970 10,196 3,196 1,774 1.94 1.28 3- quintile(20%) 0.404 20,941 17,900 13,984 6,957 3,916 4.22 2.82 4- quintile(20%) 0.379 29,910 27,560 19,254 10,656 8,306 6.46 5.99 9-decile(10%) 0.34 47,772 54,900 26,250 21,522 28,650 13.05 20.66 10-decile(10%) 0.292 164,034 139,000 43,614 120,420 95,386 73.00 68.77 Average 0.379 35,462 32,154 16,885 18,577 15,269 sum 164,965 138,695 100 100 Note: The NBSC is an abbreviation of National Bureau of Statistics of People's Republic of China
18 Table2 Basic statistics of the CHIP2007 Variable Obs Mean Std.Dev. Min Max Per Capita Annual Income of Urban Households 4995 27404.10 22053.09 1095.24 390476.20 Consumption Expenditure 4995 34351.80 27914.88 2850.00 745000.00 Food Expenditure 4995 14398.67 10494.33 1000.00 180000.00 Engel's Coefficient 4995 0.462 0.166 0.005 0.975 Table 3-a Estimates of the "estimated income" by the Engel coefficient method using CHIP2007 (calculation method) Engel s coeffecient Per Capita Annual Income of Urban Households(RMB) Mean Obs Percentage of observations Min Max 0.276 1597 31.98 0.050 0.382 0.331 1514 30.32 0.231 0.410 0.366 1832 36.68 0.260 0.453 0.389 1985 39.75 0.280 0.480 0.413 1881 37.67 0.320 0.500 0.435 2232 44.69 0.331 0.536 0.472 2606 52.18 0.350 0.600 34506.79 1597 31.98 2095.24 291428.60 31385.24 1514 30.32 1857.14 278571.40 30331.23 1832 36.68 1857.14 278571.40 28742.66 1985 39.75 1857.14 278571.40 27709.02 1881 37.67 1857.14 278571.40 26911.13 2232 44.69 1857.14 278571.40 25695.81 2606 52.18 1857.14 278571.40
19 Table3-b Estimates of the "estimated income" and "gray income" by the Engel coefficient method using CHIP2007 (estimation results) Estimated value The value by NBSC (c) Difference The ratio of deviation Engel s coeffecient (a) Per capita annual income of urban households Number of observations Engel's coefficient (b) Per capita annual income of urban households (a-b) c b (%) ci Σci (%) 1-group 0.472 25695.81 2606 0.472 4604.09 21091.72 458.11 23.61 2-group 0.435 26911.13 2232 0.435 6992.55 19918.58 284.85 22.30 3-group 0.413 27709.02 1881 0.413 9568.02 18141.00 189.60 20.31 4-group 0.389 28742.66 1985 0.389 12978.61 15764.05 121.46 17.65 5-group 0.366 30331.23 1832 0.366 17684.55 12646.68 71.51 14.16 6-group 0.331 31385.24 1514 0.331 24106.62 7278.62 30.19 8.15 7-group 0.276 34506.79 1597 0.276 40019.22-5512.43-13.77-6.17 Average 0.383 29325.98 0.383 16564.81 Sum 205281.88 115953.66 89328.22 100.00
20 Table 4 Estimates of the "estimated income" and "gray income" by Engel's coefficient method using CHIP2007 (incomplete estimation results) Estimated value The value by NBSC (c) Difference The ratio of deviation Engel s coeffecient (a) Per capita annual ncome of urban households Percentage of observation Engel's coefficient (b) Per capita annual income of urban households (a-b) c b (%) ci Σci (%) other 0.585 22699.11 39.54 1-group 0.472 24793.94 15.72 0.472 4604.09 20189.85 438.52 29.32 2-group 0.435 27963.39 1.50 0.435 6992.55 20970.84 299.90 30.46 3-group 0.413 26766.30 8.21 0.413 9568.02 17198.28 179.75 24.98 4-group 0.389 29082.77 2.60 0.389 12978.61 16104.16 124.08 23.39 5-group 0.366 6-group 0.331 7-group 0.276 34405.73 32.43 0.276 40019.22-5613.49-14.03-8.15 Average 0.428 27618.54 0.383 16564.81 Sum 165711.24 100 115953.66 68849.64 100
21 Table5a Estimates of the "estimated income" and "gray income" by quantile method using CHIP2007 Estimated value The value by NBSC (c) Difference The ratio of deviation Engel s coeffecient (a) Per capita annual income of urban households Percentage of observations Engel's coefficient (b) Per capita annual income of urban households (a-b) c b (%) ci Σci (%) 1-decile(10%) 0.531 7020.42 10.79 0.472 4604.09 2416.33 52.48 2.67 2-decile(10%) 0.504 11219.46 9.31 0.435 6992.55 4226.91 60.45 4.66 2- quintile(20%) 0.488 15425.60 19.90 0.413 9568.02 5857.58 61.22 6.46 3- quintile(20%) 0.468 21626.00 20.04 0.389 12978.61 8647.39 66.63 9.54 4- quintile(20%) 0.439 31110.34 20.16 0.366 17684.55 13425.79 75.92 14.81 9-decile(10%) 0.418 43901.73 9.81 0.331 24106.62 19795.11 82.11 21.84 10-decile(10%) 0.378 76276.11 9.99 0.276 40019.22 36256.89 90.60 40.01 Average 0.461 29511.38 0.383 16564.81 12946.57 Sum 206579.66 100.00 115953.66 90626.00 100.00 1-decile /Tota (%) 3.40 3.97 10-decile/Total (%) 36.92 34.51.
22 Table5b Estimates of the "adjusted estimated income "and "gray income" by quantile method using CHIP2007 Engel s coeffecient Estimated value (a) Per capita annual income of urban households Percentage of observations The value by NBSC Engel's coefficient (b) Per capita annual income of urban households (c)food expenditure (d)gap of Engel's coefficient (e) Adjusted estimated value (f) Difference (e-b) The ratio of deviation 1-decile(10%) 0.531 7020.42 10.79 0.472 4604.09 3584.86-843.89 7864.31 3260.22 70.81 2.85 2-decile(10%) 0.504 11219.46 9.31 0.435 6992.55 5107.45-1607.43 12826.89 5834.34 83.44 5.11 2- quintile(20%) 0.488 15425.60 19.90 0.413 9568.02 7085.97-2636.88 18062.48 8494.46 88.78 7.44 3- quintile(20%) 0.468 21626.00 20.04 0.389 12978.61 7909.76-3432.38 25058.38 12079.77 93.07 10.58 4- quintile(20%) 0.439 31110.34 20.16 0.366 17684.55 7061.46-3208.28 34318.62 16634.07 94.06 14.57 9-decile(10%) 0.418 43901.73 9.81 0.331 24106.62 6659.04-4187.23 48088.96 23982.34 99.48 21.00 10-decile(10%) 0.378 76276.11 9.99 0.276 40019.22 7826.94-7652.28 83928.39 43909.17 109.72 38.45 Average 0.461 29511.38 0.38 16564.81 6462.21-3366.91 32878.29 16313.48 Sum 206579.66 100.00 115953.66 230148.04 151301.46 100.00 1-decile /Tota (%) 3.40 3.97 3.42 f b (%) fi Σfi (%) 10-decile/Total (%) 36.92 34.51 36.47 Note: (d) is calculated as( β i β i β i βi ) C a,i, (e) is calculated as equation (9).
23 Table6a Estimates of the "estimated income"and "gray income" by the income class classification of Wang (2010) using the CHIP2007 Estimated value The value by NBSC (c) Difference The ratio of deviation Engel s coeffecient (a) Per capita annual income of urban households Percentage of observations Engel's coefficient (b) Per capita annual income of urban households Percentage of observations (a-b) c b (%) ci Σci (%) y 7000 0.548 5183.83 4.62 0.472 4604.09 10 579.74 12.59 0.51 7001 y 10000 0.523 8628.66 7.39 0.435 6992.55 10 1636.11 23.40 1.43 10001 y 17000 0.493 13625.23 23.28 0.413 9568.02 20 4057.21 42.40 3.53 17001 y 26500 0.471 21251.47 26.97 0.389 12978.61 20 8272.86 63.74 7.21 26501 y 34000 0.437 29902.18 12.69 0.366 17684.55 20 12217.63 69.09 10.64 34001 y 75000 0.410 47362.93 21.62 0.331 24106.62 10 23256.31 96.47 20.26 75001 y 400000 0.363 104796.60 3.42 0.276 40019.22 10 64777.38 161.87 56.43 Average 0.464 32964.41 0.383 16564.81 16399.61 Sum 230750.90 100.00 115953.66 100 114797.24 100.00 y 7000 Total (%) 2.25 3.97 75001 y 00000 Total (%) 45.42 34.51
24 Table6b Estimates of the "adjusted estimated income "and "gray income" by the income class classification of Wang (2010) using the CHIP2007 Engel s coeffecient Estimated value (a) Per capita annual income of urban households Percentage of observations The value by NBSC Engel's coefficient (b) Per capita annual income of urban households (c)food expenditure (d)gap of Engel's coefficient (e) Adjusted estimated value (f) Difference (e-b) The ratio of deviation y 7000 0.548 5183.83 4.62 0.472 4604.09 3584.86-1053.33 6237.16 1633.07 35.47 1.18 7001 y 10000 0.523 8628.66 7.39 0.435 6992.55 5107.45-1975.58 10604.24 3611.69 51.65 2.62 10001 y 17000 0.493 13625.23 23.28 0.413 9568.02 7085.97-2784.15 16409.38 6841.36 71.50 4.96 17001 y 26500 0.471 21251.47 26.97 0.389 12978.61 7909.76-3540.03 24791.50 11812.89 91.02 8.56 26501 y 34000 0.437 29902.18 12.69 0.366 17684.55 7061.46-3134.66 33036.84 15352.29 86.81 11.13 34001 y 75000 0.410 47362.93 21.62 0.331 24106.62 6659.04-3876.39 51239.32 27132.70 112.55 19.67 75001 y 400000 0.363 104796.60 3.42 0.276 40019.22 7826.94-6796.66 111593.26 71574.04 178.85 51.88 Average 0.464 32964.41 0.38 16564.81 6462.21-3308.68 36273.10 19708.29 Sum 230750.90 100.00 115953.66 253911.69 172867.61 100.00 y 7000 Total (%) 2.25 3.97 2.46 75001 y400000 Total (%) Note: (d) is calculated as( β i β i 45.42 34.51 43.95 β i β i ) C a,i (e) is calculated as equation (9). f b (%) fi Σfi (%)
25 Table7a Estimation results of size of "gray income" using the "estimated income" Estimation(1) (by table 5) Estimation(2) (by table 6) Estimates of Wang (by table1(a)) Estimates of Wang (by table1(b)) (1) Total Net Income of Rural Households (100 million yuan) (a b) 29601.9 29601.9 37301.0 37301.0 a. Annual Per Capita Net Income of Rural Households (yuan) 4140.4 4140.4 5171.0 5171.0 b.rural Population(100 million persons) 7.1 7.1 7.2 7.2 (2) Total Disposable Income of Urban Households (yuan) (c d) 90395.4 90395.4 102436.2 102436.2 (3) Total Estimation Income of Urban Households (100 million yuan) (e d) 178936.4 199873.1 195068.7 215137.3 c.annual Per Capita Disposable Income of Urban Households (yuan) 14908.6 14908.6 16885.0 16885.0 d.urban Population(100 million persons) 6.1 6.1 6.1 6.1 e.annual Per Capita Estimation Income of Urban Households (yuan) 29511.4 32964.4 32154.0 35462.0 (4) Total Income of Households (100 million yuan) (1+2) 119997.3 119997.3 139737.2 139737.2 (5) Total Estimation Income of Households (100 million yuan) (1+3) 208538.3 229475.1 232369.7 252438.3 (6) Total Disposable Income(100 million yuan) 158558.6 158558.6 185926.3 185926.3 (7) Urban Total Gray Income (UTGI, 100 million yuan) (3-2) 88541.0 109477.8 92632.4 112701.1 (8) Aggregate Gray Income (AGI, 100 million yuan) (5-6) 49979.6 70916.4 46443.4 66512.0 (9) GDP(100 million yuan) 265810.3 265810.3 314045.4 314045.4 (10) Urban Total Gray Income (UTGI) to GDP ratio(%) (7 9) 33.3 41.2 29.5 35.9 (11) Aggregate Gray Income(AGI) to GDP ratio(%) (8 9) 18.8 26.7 17.5 25.0 Note: a ~ d, (6), (9) is the published data of China Statistical Bureau, others are calculated in this paper. In addition, e in Table 9a is the estimated value of Table 5a and Table 7a.
26 Table7b Estimation results of size of "gray income" using "adjusted estimated income" Estimation(1) (by table 5) Estimation(2) (by table 7) Estimates of Wang (by table1(a)) Estimates of Wang (by table1(b)) (1) Total Net Income of Rural Households (100 million yuan) (a b) 29601.9 29601.9 37301.0 37301.0 a. Annual Per Capita Net Income of Rural Households (yuan) 4140.4 4140.4 5171.0 5171.0 b.rural Population(100 million persons) 7.1 7.1 7.2 7.2 (2) Total Disposable Income of Urban Households (yuan) (c d) 90395.4 90395.4 102436.2 102436.2 (3) Total Estimation Income of Urban Households (100 million yuan) (e d) 126262.8 149433.9 195068.7 215137.3 c.annual Per Capita Disposable Income of Urban Households (yuan) 14908.6 14908.6 16885.0 16885.0 d.urban Population(100 million persons) 6.1 6.1 6.1 6.1 e. Adjusted Annual Per Capita Estimation Income of Urban Households (yuan) 32878.3 36273.1 32154.0 35462.0 (4) Total Income of Households (100 million yuan) (1+2) 119997.3 119997.3 139737.2 139737.2 (5) Total Estimation Income of Households (100 million yuan) (1+3) 228952.9 249536.6 232369.7 252438.3 (6) Total Disposable Income(100 million yuan) 158558.6 158558.6 185926.3 185926.3 (7) Urban Total Gray Income (UTGI, 100 million yuan) (3-2) 108955.6 129539.3 92632.4 112701.1 (8) Aggregate Gray Income (AGI, 100 million yuan) (5-6) 70394.2 90978.0 46443.4 66512.0 (9) GDP(100 million yuan) 265810.3 265810.3 314045.4 314045.4 (10) Urban Total Gray Income (UTGI) to GDP ratio(%) (7 9) 41.0 48.7 29.5 35.9 (11) Aggregate Gray Income(AGI) to GDP ratio(%) (8 9) 26.5 34.2 17.5 25.0 Note: a ~ d, (6), (9) is the published data of China Statistical Bureau, others are calculated in this paper. In addition, e in Table 9b is the estimated value of Table 5b and Table 7b.