中国金融发展、城镇化与城乡居民收入差距问题分析
尹晓波(1957—),男,云南大理人,教授,博士生导师。主要研究方向为数量经济学、区域经济学。E-mail:xbyin_hqu@aliyun.com。 |
收稿日期: 2019-08-13
修回日期: 2019-12-28
网络出版日期: 2025-04-11
基金资助
国家社会科学基金项目(15BJY062)
The Study on Financial Development, Urbanization and Urban & Rural Residents' Income Gap in China
Received date: 2019-08-13
Revised date: 2019-12-28
Online published: 2025-04-11
尹晓波 , 王巧 . 中国金融发展、城镇化与城乡居民收入差距问题分析[J]. 经济地理, 2020 , 40(3) : 84 -91 . DOI: 10.15957/j.cnki.jjdl.2020.03.010
Narrowing the gap between urban and rural areas is an important issue in the process of China's economic development.How to integrate the overall development of urban and rural areas with the development of financial construction and make full use of the role of financial development and urbanization in reducing the income gap between urban and rural areas has become the most important part of the future development. Through the study of the theory and mechanism of the interaction of financial development,urbanization and urban-rural income gap,this paper makes an empirical analysis on the problems related to the financial development,the urbanization level and the income gap between the urban and rural residents by taking 1985-2017 years' financial development indicators,urban and rural residents' per capita income ratio and urbanization level data as the object of investigation.According to the conclusion,the paper puts forward some countermeasures to speed up the process of urbanization and narrow the income gap between urban and rural areas.
表1 1985—2017年中国城乡收入差距、金融发展水平以及城镇化水平Tab.1 Urban-rural income gap, financial development level and urbanization level in China from 1985 to 2017 |
年份 | 城镇人均可支配收入(元) | 农村人均纯收入(元) | 城乡居民人均收入比率 | 金融机构贷款年底数额(亿元) | 国内生产总值GDP(亿元) | 金融发展 水平(%) | 城镇化 水平(%) |
---|---|---|---|---|---|---|---|
1985 | 739.1 | 397.6 | 1.85 | 6 198.4 | 9 016.0 | 68.75 | 23.7 |
1986 | 900.0 | 424.0 | 2.12 | 8 142.7 | 10 275.2 | 79.25 | 24.5 |
1987 | 1 002.0 | 463.0 | 2.16 | 9 814.1 | 12 058.6 | 81.39 | 25.3 |
1988 | 1 181.0 | 545.0 | 2.16 | 11 964.3 | 15 042.8 | 79.54 | 25.8 |
1989 | 1 376.0 | 602.0 | 2.28 | 14 248.8 | 16 992.3 | 83.85 | 26.2 |
1990 | 1 510.2 | 686.3 | 2.20 | 17 511.0 | 18 667.8 | 93.80 | 26.4 |
1991 | 1 700.6 | 708.6 | 2.39 | 21 116.4 | 21 781.5 | 96.95 | 26.9 |
1992 | 2 026.6 | 784.0 | 2.58 | 25 742.8 | 26 923.5 | 95.61 | 27.5 |
1993 | 2 577.4 | 921.6 | 2.79 | 32 955.8 | 35 333.9 | 93.27 | 28.0 |
1994 | 3 496.2 | 1 221.0 | 2.86 | 39 976.0 | 48 197.9 | 82.94 | 28.5 |
1995 | 4 283.0 | 1 577.7 | 2.71 | 50 544.1 | 60 793.7 | 83.14 | 29.0 |
1996 | 4 838.9 | 1 926.1 | 2.51 | 61 156.6 | 71 176.6 | 85.92 | 30.5 |
1997 | 5 160.3 | 2 090.1 | 2.46 | 74 914.1 | 78 973.0 | 94.86 | 31.9 |
1998 | 5 425.1 | 2 162.0 | 2.50 | 86 524.1 | 84 402.3 | 102.51 | 33.3 |
1999 | 5 854.0 | 2 210.3 | 2.64 | 93 734.3 | 89 677.1 | 104.52 | 34.8 |
2000 | 6 280.0 | 2 253.4 | 2.78 | 99 371.1 | 99 214.6 | 100.16 | 36.2 |
2001 | 6 859.6 | 2 366.4 | 2.89 | 112 314.7 | 109 655.2 | 102.43 | 37.7 |
2002 | 7 702.8 | 2 475.6 | 3.11 | 131 293.9 | 120 332.7 | 109.11 | 39.1 |
2003 | 8 472.2 | 2 622.2 | 3.23 | 158 996.2 | 135 822.8 | 117.06 | 40.5 |
2004 | 9 421.6 | 2 936.4 | 3.20 | 178 197.8 | 159 878.3 | 111.46 | 41.8 |
2005 | 10 493.0 | 3 254.9 | 3.22 | 194 690.4 | 184 937.4 | 105.27 | 43.0 |
2006 | 11 759.5 | 3 587.0 | 3.28 | 225 347.2 | 216 314.4 | 104.18 | 44.3 |
2007 | 13 785.8 | 4 140.4 | 3.33 | 261 690.9 | 265 810.3 | 98.45 | 45.9 |
2008 | 15 780.8 | 4 760.6 | 3.31 | 303 394.6 | 314 045.4 | 96.61 | 47.0 |
2009 | 17 174.7 | 5 153.2 | 3.33 | 400 000.0 | 340 902.8 | 117.34 | 48.3 |
2010 | 19 109.4 | 5 919.0 | 3.23 | 483 600.0 | 401 512.8 | 120.44 | 49.9 |
2011 | 21 809.8 | 6 977.3 | 3.13 | 547 900.0 | 473 104.0 | 115.81 | 51.3 |
2012 | 24 564.7 | 7 916.6 | 3.10 | 672 875.0 | 519 470.1 | 129.53 | 52.6 |
2013 | 26 955.1 | 8 895.9 | 3.03 | 766 327.0 | 568 845.2 | 134.72 | 53.7 |
2014 | 28 844.0 | 10 489.0 | 2.75 | 867 868.0 | 636 463.0 | 136.36 | 54.8 |
2015 | 31 194.8 | 11 422.0 | 2.73 | 936 387.0 | 689 052.1 | 135.89 | 56.1 |
2016 | 33 616.0 | 12 363.0 | 2.72 | 1 061 667.0 | 744 127.0 | 142.67 | 57.4 |
2017 | 36 396.0 | 13 432.0 | 2.71 | 1 196 900.0 | 827 122.0 | 144.71 | 58.5 |
表2 ADF检验结果Tab.2 ADF test results |
变量 | ADF检验 | 检验式 | Prob. | 5%临界值 | 结论 |
---|---|---|---|---|---|
-0.891920 | (0,0,2) | 0.8923 | -1.313888 | 不平稳 | |
-0.077850 | (0,0,2) | 0.3642 | -0.464274 | 不平稳 | |
-3.326565 | (0,0,2) | 0.0025 | -3.310202 | 平稳 | |
-1.580804 | (0,0,2) | 0.0065 | -1.096149 | 平稳 | |
-0.019412 | (0,0,2) | 0.6630 | -1.961409 | 不平稳 | |
-0.784220 | (0,0,2) | 0.3614 | -1.962813 | 不平稳 | |
-2.896967 | (0,0,2) | 0.0067 | -1.964418 | 平稳 |
注: 是 的一阶差分、 是 的二阶差分, 和 以此类推;(A,T,K)分别表示ADF的截距项、趋势项和滞后阶数,例如: (0,0,2)表示用None不含有趋势项和截距项滞后2阶检验 的二阶差分序列。 |
表3 Johansen协整检验结果Tab.3 Johansen co-integration test results |
Null Hypothesis: D(ET,2) has a unit root | |||
Exp genous: None | |||
Lag Length: 2 (Fixed) | |||
t-Statistic | Prob.* | ||
Augmented Dickey-Fuller test statistic | -2.906945 | 0.0065 | |
Test critical values: | 1% level | -2.717511 | |
5% level | -1.964418 | ||
10% level | -1.605603 |
表4 Granger因果检验结果Tab.4 Granger causality test results |
零假设 | 最优滞后阶数 | F统计值 | P值 |
---|---|---|---|
FIR不是CZ的格兰杰原因 | 2 | 3.85878 | 0.0292 |
CZ不是FIR的格兰杰原因 | 2 | 5.57504 | 0.0166 |
GI不是CZ的格兰杰原因 | 2 | 4.00361 | 0.0396 |
CZ不是GI的格兰杰原因 | 2 | 5.69976 | 0.0218 |
GI不是FIR的格兰杰原因 | 2 | 3.58401 | 0.0331 |
FIR不是GI的格兰杰原因 | 2 | 6.21881 | 0.0145 |
(0.464817) (0.705773) (1.163335)
t=(7.009017)(2.478309)(-3.173833)
表5 OLS分析Tab.5 OLS analysis |
Dependent Variable: GI Method: Least Squares Date: 04/26/17 Time: 22:31 Sample: 1996 2016 Included observations: 21 | ||||
Coefficient | Std. Error | t-Statistic | Prob. | |
C | 3.257912 | 0.464817 | 7.009017 | 0.000000 |
FIR | 1.749123 | 0.705773 | 2.478309 | 0.023300 |
CZ | -3.692229 | 1.163335 | -3.173833 | 0.005300 |
R-squared | 0.999652 | Mean dependent var | 2.978211 | |
Adjusted R-squared | 0.998502 | S.D. dependent var | 0.298210 | |
S.E. of regression | 0.251541 | Akaike info criterion | 0.209146 | |
Sum squared resid | 1.138916 | Schwarz criterion | 0.358363 | |
Log likelihood | 0.803971 | Hannan-Quinn criter. | 0.241530 | |
F-statistic | 5.054860 | Durbin-Watson stat | 0.391887 | |
Prob(F-statistic) | 0.018103 |
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