World Regional Studies ›› 2021, Vol. 30 ›› Issue (2): 355-366.DOI: 10.3969/j.issn.1004-9479.2021.02.2019534
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Received:
2019-10-23
Revised:
2020-02-05
Online:
2021-03-30
Published:
2021-04-09
Contact:
Tao LI
通讯作者:
李涛
作者简介:
刘国燕(1984-),女,硕士,助理研究员,研究方向:城市经济与产业创新,E-mail: yaner_126@126.com。
基金资助:
Guoyan LIU, Tao LI. Impact of high-speed railway development on regional innovation from the perspective of spatial effect[J]. World Regional Studies, 2021, 30(2): 355-366.
刘国燕, 李涛. 高铁影响下的中国区域创新时空演化与效应分解[J]. 世界地理研究, 2021, 30(2): 355-366.
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URL: https://sjdlyj.ecnu.edu.cn/EN/10.3969/j.issn.1004-9479.2021.02.2019534
年份 | Moran's I | 年份 | Moran's I | 年份 | Moran's I | 年份 | Moran's I |
---|---|---|---|---|---|---|---|
2002 | 0.3025*** | 2006 | 0.3504*** | 2010 | 0.3835*** | 2014 | 0.3889*** |
2003 | 0.3219*** | 2007 | 0.3355*** | 2011 | 0.3841*** | 2015 | 0.4068*** |
2004 | 0.3622*** | 2008 | 0.3376*** | 2012 | 0.4083*** | 2016 | 0.3978*** |
2005 | 0.3413*** | 2009 | 0.3499*** | 2013 | 0.4020*** | 2017 | 0.4164*** |
Tab.1 The Moran's I index of regional innovation output from 2002 to 2017
年份 | Moran's I | 年份 | Moran's I | 年份 | Moran's I | 年份 | Moran's I |
---|---|---|---|---|---|---|---|
2002 | 0.3025*** | 2006 | 0.3504*** | 2010 | 0.3835*** | 2014 | 0.3889*** |
2003 | 0.3219*** | 2007 | 0.3355*** | 2011 | 0.3841*** | 2015 | 0.4068*** |
2004 | 0.3622*** | 2008 | 0.3376*** | 2012 | 0.4083*** | 2016 | 0.3978*** |
2005 | 0.3413*** | 2009 | 0.3499*** | 2013 | 0.4020*** | 2017 | 0.4164*** |
象限 | 2010年 | 2017年 |
---|---|---|
象限1:HH | 山东、河南、江苏、安徽、湖北、浙江、湖南、福建、广东、辽宁、天津、陕西、河北、上海、北京 | 山东、河南、江苏、安徽、湖北、浙江、江西、湖南、福建、广东、辽宁、天津、陕西、重庆、河北、上海、北京 |
象限2:LH | 黑龙江、山西、江西、宁夏、贵州、海南、广西、内蒙古、吉林 | 宁夏、山西、云南、贵州、广西、海南、吉林、内蒙古 |
象限3:LL | 新疆、云南、西藏、甘肃、青海 | 黑龙江、西藏、新疆、青海、甘肃 |
象限4:HL | 重庆、四川 | 四川 |
Tab.2 LISA clustering results of regional innovation output in 2010 and 2017
象限 | 2010年 | 2017年 |
---|---|---|
象限1:HH | 山东、河南、江苏、安徽、湖北、浙江、湖南、福建、广东、辽宁、天津、陕西、河北、上海、北京 | 山东、河南、江苏、安徽、湖北、浙江、江西、湖南、福建、广东、辽宁、天津、陕西、重庆、河北、上海、北京 |
象限2:LH | 黑龙江、山西、江西、宁夏、贵州、海南、广西、内蒙古、吉林 | 宁夏、山西、云南、贵州、广西、海南、吉林、内蒙古 |
象限3:LL | 新疆、云南、西藏、甘肃、青海 | 黑龙江、西藏、新疆、青海、甘肃 |
象限4:HL | 重庆、四川 | 四川 |
变量 | 系数 | t值 | |
---|---|---|---|
C | -4.086*** | -10.876 | |
R&DP | 0.373*** | 6.813 | |
R&DE | 0.020 | 0.354 | |
PGDP | -0.313*** | -2.936 | |
FDI | 0.003*** | 7.382 | |
GOV | -0.001** | -2.284 | |
CON | 0.395*** | 2.874 | |
FIN | 0.885*** | 16.702 | |
R2 | 0.957 | Durbin-Watson | 1.675 |
sigma^2 | 0.144 | loglikols | -218.944 |
LM test no spatial Lag | 14.149*** | LM test no spatial error | 9.894*** |
robust LM test no spatial lag | 9.238*** | robust LM test no spatial error | 4.982** |
Tab.3 The estimation results of OLS panel model
变量 | 系数 | t值 | |
---|---|---|---|
C | -4.086*** | -10.876 | |
R&DP | 0.373*** | 6.813 | |
R&DE | 0.020 | 0.354 | |
PGDP | -0.313*** | -2.936 | |
FDI | 0.003*** | 7.382 | |
GOV | -0.001** | -2.284 | |
CON | 0.395*** | 2.874 | |
FIN | 0.885*** | 16.702 | |
R2 | 0.957 | Durbin-Watson | 1.675 |
sigma^2 | 0.144 | loglikols | -218.944 |
LM test no spatial Lag | 14.149*** | LM test no spatial error | 9.894*** |
robust LM test no spatial lag | 9.238*** | robust LM test no spatial error | 4.982** |
变量 | 统计值 | 变量 | 统计值 |
---|---|---|---|
Hausman test | 24.260** | ||
Wald_spatial_lag | 41.551*** | LR_spatial_lag | 47.715*** |
Wald_spatial_error | 48.092*** | LR_spatial_error | 52.734*** |
Tab.4 The LR and Wald test
变量 | 统计值 | 变量 | 统计值 |
---|---|---|---|
Hausman test | 24.260** | ||
Wald_spatial_lag | 41.551*** | LR_spatial_lag | 47.715*** |
Wald_spatial_error | 48.092*** | LR_spatial_error | 52.734*** |
效应 | 空间权重 | (1) 地理距离 2002—2017 | (2) 时间距离(不含高铁) 2002—2009 | (3) 时间距离(不含高铁) 2010—2017 | (4) 时间距离(含高铁) 2010—2017 |
---|---|---|---|---|---|
直接效应 | R&DP | 0.131** (2.192) | 0.173*** (3.051) | 0.287* (1.933) | 0.833*** (5.421) |
R&DE | -0.162*** (-2.766) | -0.013 (-0.237) | 0.780*** (12.549) | 0.029 (0.216) | |
PGDP | 0.588*** (3.553) | 0.419*** (2.639) | -0.415** (-2.373) | -0.759*** (-4.212) | |
FDI | 0.003*** (4.415) | 0.025 (0.947) | 0.056* (1.687) | 0.087*** (2.920) | |
GOV | -0.000 (-0.537) | 0.078 (1.181) | 0.354*** (4.754) | 0.419*** (5.809) | |
CON | 0.185 (0.746) | -0.270 (-1.481) | 0.081 (0.405) | 0.654*** (3.129) | |
FIN | 0.160* (1.908) | 1.062*** (12.059) | 0.035 (0.367) | -0.090 (-1.016) | |
间接效应 | R&DP | 1.232* (1.897) | 0.496* (1.872) | -0.476 (-1.169) | -4.995*** (-4.367) |
R&DE | -0.691 (-1.047) | -0.268 (-0.988) | -0.914*** (-2.604) | 3.247*** (2.992) | |
PGDP | -0.628 (-0.405) | -2.721*** (-4.533) | -2.824*** (-4.798) | -4.237*** (-4.173) | |
FDI | 0.018** (2.453) | 0.418*** (3.740) | 0.065 (0.513) | 0.139 (0.765) | |
GOV | -0.001 (0.107) | 0.181 (0.592) | 0.953** (2.439) | 0.477 (0.764) | |
CON | 4.894* (1.682) | 2.551*** (3.026) | 3.569*** (4.162) | 4.574*** (3.083) | |
FIN | 2.121* (1.939) | -0.173 (-1.556) | -0.007 (-0.020) | 0.873 (1.185) | |
总效应 | R&DP | 1.362** (2.013) | 0.669** (2.500) | -0.189 (-0.536) | -4.162*** (-3.431) |
R&DE | -0.854 (-1.234) | -0.281 (-1.034) | -0.134 (-0.397) | 3.276*** (2.898) | |
PGDP | -0.041 (-0.026) | -2.302*** (-4.083) | -3.239*** (-5.409) | -4.996*** (-4.629) | |
FDI | 0.021*** (2.683) | 0.443*** (4.045) | 0.121 (0.964) | 0.226 (1.188) | |
GOV | -0.001 (-0.151) | 0.259 (0.844) | 1.307*** (3.456) | 0.896 (1.397) | |
CON | 5.079* (1.651) | 2.281*** (2.637) | 3.651*** (4.087) | 5.228*** (3.345) | |
FIN | 2.281** (2.046) | 0.349 (0.754) | 0.028 (0.078) | 0.782 (1.036) |
Tab.5 The effect decomposition estimation results of spatial Durbin model
效应 | 空间权重 | (1) 地理距离 2002—2017 | (2) 时间距离(不含高铁) 2002—2009 | (3) 时间距离(不含高铁) 2010—2017 | (4) 时间距离(含高铁) 2010—2017 |
---|---|---|---|---|---|
直接效应 | R&DP | 0.131** (2.192) | 0.173*** (3.051) | 0.287* (1.933) | 0.833*** (5.421) |
R&DE | -0.162*** (-2.766) | -0.013 (-0.237) | 0.780*** (12.549) | 0.029 (0.216) | |
PGDP | 0.588*** (3.553) | 0.419*** (2.639) | -0.415** (-2.373) | -0.759*** (-4.212) | |
FDI | 0.003*** (4.415) | 0.025 (0.947) | 0.056* (1.687) | 0.087*** (2.920) | |
GOV | -0.000 (-0.537) | 0.078 (1.181) | 0.354*** (4.754) | 0.419*** (5.809) | |
CON | 0.185 (0.746) | -0.270 (-1.481) | 0.081 (0.405) | 0.654*** (3.129) | |
FIN | 0.160* (1.908) | 1.062*** (12.059) | 0.035 (0.367) | -0.090 (-1.016) | |
间接效应 | R&DP | 1.232* (1.897) | 0.496* (1.872) | -0.476 (-1.169) | -4.995*** (-4.367) |
R&DE | -0.691 (-1.047) | -0.268 (-0.988) | -0.914*** (-2.604) | 3.247*** (2.992) | |
PGDP | -0.628 (-0.405) | -2.721*** (-4.533) | -2.824*** (-4.798) | -4.237*** (-4.173) | |
FDI | 0.018** (2.453) | 0.418*** (3.740) | 0.065 (0.513) | 0.139 (0.765) | |
GOV | -0.001 (0.107) | 0.181 (0.592) | 0.953** (2.439) | 0.477 (0.764) | |
CON | 4.894* (1.682) | 2.551*** (3.026) | 3.569*** (4.162) | 4.574*** (3.083) | |
FIN | 2.121* (1.939) | -0.173 (-1.556) | -0.007 (-0.020) | 0.873 (1.185) | |
总效应 | R&DP | 1.362** (2.013) | 0.669** (2.500) | -0.189 (-0.536) | -4.162*** (-3.431) |
R&DE | -0.854 (-1.234) | -0.281 (-1.034) | -0.134 (-0.397) | 3.276*** (2.898) | |
PGDP | -0.041 (-0.026) | -2.302*** (-4.083) | -3.239*** (-5.409) | -4.996*** (-4.629) | |
FDI | 0.021*** (2.683) | 0.443*** (4.045) | 0.121 (0.964) | 0.226 (1.188) | |
GOV | -0.001 (-0.151) | 0.259 (0.844) | 1.307*** (3.456) | 0.896 (1.397) | |
CON | 5.079* (1.651) | 2.281*** (2.637) | 3.651*** (4.087) | 5.228*** (3.345) | |
FIN | 2.281** (2.046) | 0.349 (0.754) | 0.028 (0.078) | 0.782 (1.036) |
地区 | R&DP | R&DE | PGDP | FDI | GOV | CON | FIN |
---|---|---|---|---|---|---|---|
直接效应 | |||||||
东部 | 1.803*** (-12.291) | -0.762*** (-6.359) | 0.137 (-0.619) | 0.001*** (-2.737) | -0.000** (-1.986) | 0.233*** (-2.846) | 0.319*** (-3.126) |
东北 | 1.545* (-1.764) | 0.008* (-1.809) | -0.561 (-0.954) | 0.002*** (-2.822) | -0.015 (-1.045) | 1.717** (-2.41) | 0.113** (-2.049) |
中部 | 0.246** (-2.508) | 1.321*** (-3.285) | -1.865*** (-3.808) | 0.002** (-1.886) | 0.001* (-1.805) | 0.919 (-1.257) | 0.378** (-1.975) |
西部 | 0.337* (-1.804) | 0.678** (-2.294) | -0.511* (-1.985) | -0.004* (-1.680) | 0.013*** (-3.927) | 0 (-0.002) | 0.013 (-1.796) |
间接效应 | |||||||
东部 | 0.755*** (-3.292) | -0.316*** (-3.213) | 0.059 (-0.591) | 0.001** (-2.558) | -0.001** (-1.875) | 0.091** (-2.116) | 0.127*** (-3.003) |
东北 | 0.061* (-1.705) | 0.026 (-0.147) | -0.069 (-0.362) | 0 (-0.156) | -0.001 (-0.902) | 0.046* (-1.726) | 0.007** (-1.861) |
中部 | 0.041* -1.679 | 0.359* -1.74 | -0.468 (-0.866) | 0.001** -2.107 | 0 -0.353 | 0.179 -0.566 | 0.051** -2.382 |
西部 | 0.249** -1.971 | 0.491** -1.752 | -0.349* -1.827) | -0.003* (-1.825) | 0.009*** -2.713 | -0.034 (-0.116) | 0.007 -0.736 |
总效应 | |||||||
东部 | 2.558*** (-7.603) | -1.078*** (-5.662) | 0.197 (-0.617) | 0.002*** (-2.851) | -0.001 (-2.018) | 0.324* (-1.651) | 0.116*** (-3.342) |
东北 | 1.607* (-1.714) | 0.034* (-1.675) | 0.631 (-0.573) | 0.003** (-2.531) | -0.016 (-0.991) | 1.763** (-2.104) | 0.120** (-1.954) |
中部 | 0.288** (-2.108) | 1.68 (-2.231) | -2.333* (-2.890) | 0.003** (-1.986) | 0.001* (-1.747) | 1.099 (-1.196) | 0.429** (-2.174) |
西部 | 0.586*** (-1.869) | 1.169** (-2.131) | -0.860** (-2.028) | -0.007* (-1.902) | 0.022*** (-3.784) | -0.034 (-0.049) | 0.021 (-1.087) |
Tab.6 The effect decomposition estimation results of spatial Durbin model by Region
地区 | R&DP | R&DE | PGDP | FDI | GOV | CON | FIN |
---|---|---|---|---|---|---|---|
直接效应 | |||||||
东部 | 1.803*** (-12.291) | -0.762*** (-6.359) | 0.137 (-0.619) | 0.001*** (-2.737) | -0.000** (-1.986) | 0.233*** (-2.846) | 0.319*** (-3.126) |
东北 | 1.545* (-1.764) | 0.008* (-1.809) | -0.561 (-0.954) | 0.002*** (-2.822) | -0.015 (-1.045) | 1.717** (-2.41) | 0.113** (-2.049) |
中部 | 0.246** (-2.508) | 1.321*** (-3.285) | -1.865*** (-3.808) | 0.002** (-1.886) | 0.001* (-1.805) | 0.919 (-1.257) | 0.378** (-1.975) |
西部 | 0.337* (-1.804) | 0.678** (-2.294) | -0.511* (-1.985) | -0.004* (-1.680) | 0.013*** (-3.927) | 0 (-0.002) | 0.013 (-1.796) |
间接效应 | |||||||
东部 | 0.755*** (-3.292) | -0.316*** (-3.213) | 0.059 (-0.591) | 0.001** (-2.558) | -0.001** (-1.875) | 0.091** (-2.116) | 0.127*** (-3.003) |
东北 | 0.061* (-1.705) | 0.026 (-0.147) | -0.069 (-0.362) | 0 (-0.156) | -0.001 (-0.902) | 0.046* (-1.726) | 0.007** (-1.861) |
中部 | 0.041* -1.679 | 0.359* -1.74 | -0.468 (-0.866) | 0.001** -2.107 | 0 -0.353 | 0.179 -0.566 | 0.051** -2.382 |
西部 | 0.249** -1.971 | 0.491** -1.752 | -0.349* -1.827) | -0.003* (-1.825) | 0.009*** -2.713 | -0.034 (-0.116) | 0.007 -0.736 |
总效应 | |||||||
东部 | 2.558*** (-7.603) | -1.078*** (-5.662) | 0.197 (-0.617) | 0.002*** (-2.851) | -0.001 (-2.018) | 0.324* (-1.651) | 0.116*** (-3.342) |
东北 | 1.607* (-1.714) | 0.034* (-1.675) | 0.631 (-0.573) | 0.003** (-2.531) | -0.016 (-0.991) | 1.763** (-2.104) | 0.120** (-1.954) |
中部 | 0.288** (-2.108) | 1.68 (-2.231) | -2.333* (-2.890) | 0.003** (-1.986) | 0.001* (-1.747) | 1.099 (-1.196) | 0.429** (-2.174) |
西部 | 0.586*** (-1.869) | 1.169** (-2.131) | -0.860** (-2.028) | -0.007* (-1.902) | 0.022*** (-3.784) | -0.034 (-0.049) | 0.021 (-1.087) |
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