Digital Economy Development and the Urban–Rural Income Gap: Intensifying or Reducing
Abstract
:1. Introduction
2. Theoretical Mechanisms and Research Hypotheses
2.1. Mechanisms of Digital Economy Development on Urban–Rural Income Gap
2.1.1. Analysis of the Effect of Digital Economy Development Dividend on Urban–Rural Income Gap
2.1.2. Analysis of the Effect of the “Digital Divide” on the Urban–Rural Income Gap
2.2. The Spillover Effect of Digital Economy Development on the Urban–Rural Income Gap
3. Study Design
3.1. Model Construction
3.2. Selection of Variable Indicators and Descriptive Statistics
3.2.1. Measurement of the Level of Development of the Digital Economy
3.2.2. Measurement of the Urban–Rural Income Gap
3.2.3. Selection of Control Variables
3.2.4. Descriptive Statistics of Variables
4. Empirical Test: Analysis of the Impact of Digital Economy on Urban–Rural Income Gap
4.1. Reality-Based Analysis
4.2. Analysis of the Benchmark Estimation Results
4.3. Spatial Spillover Effects and Regional Heterogeneity Analysis
4.4. Robustness Tests
5. Further Analysis
5.1. Parallel Trend Test
5.2. Baseline Return
5.3. Placebo Test
6. Conclusions and Policy Recommendations
6.1. Research Findings
6.2. Policy Recommendations
6.3. Limitations
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable Type | Variable Name | Variable Symbols |
---|---|---|
Explained Variables | Urban and Rural Income Theil Index | Theil |
Core Explanatory Variables | Digital Economy Development Index | IE |
Control Variables | Industrial Structure Development Level | Instr |
Human Capital Level | Hc | |
Government Financial Spending | Gfi | |
Urbanization Level | Ur |
Variables | Sample Size | Average Value | Standard Deviation | Minimum Value | Maximum Value | |
---|---|---|---|---|---|---|
Explained Variables | Theil | 330 | 0.1030734 | 0.0487446 | 0.0195286 | 0.2559128 |
Core Explanatory Variables | IE | 330 | 0.3650702 | 0.1650525 | 0.1 | 0.9659019 |
Control Variables | Instr | 330 | 55.31526 | 8.608749 | 40.95457 | 83.84265 |
Hc | 330 | 9.034738 | 0.9434325 | 6.763946 | 12.68113 | |
Gfi | 330 | 2427.986 | 1011.165 | 964.0102 | 6283.552 | |
Ur | 330 | 0.5641442 | 0.1276394 | 0.2989 | 0.896 |
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Variables | Theil | Theil | Theil | Theil |
IE | −0.207 *** (0.0120) | −0.0504 *** (0.0122) | −0.393 *** (0.0444) | −0.242 *** (0.0326) |
IE2 | 0.216 *** (0.0418) | 0.224 *** (0.0310) | ||
Instr | 0.000237 (0.000249) | 0.0000898 (0.000225) | ||
Hc | −0.00708 * (0.00342) | −0.00943 ** (0.00304) | ||
Gfi | 0.00000900 *** (0.00000120) | 0.00001000 *** (0.00000122) | ||
Ur | −0.210 *** (0.0234) | −0.189 *** (0.0221) | ||
_cons | 0.179 *** (0.00531) | 0.269 *** (0.0182) | 0.212 *** (0.0102) | 0.318 *** (0.0178) |
Province | YES | YES | YES | YES |
Year | YES | YES | YES | YES |
N | 330 | 330 | 330 | 330 |
R2 | 0.492 | 0.767 | 0.521 | 0.797 |
Year | IE | Theil | ||
---|---|---|---|---|
Moran’s I | Z Value | Moran’s I | Z Value | |
2009 | 0.115 *** | 3.811 | 0.210 *** | 5.851 |
2010 | 0.116 *** | 3.716 | 0.210 *** | 5.851 |
2011 | 0.119 *** | 3.826 | 0.202 *** | 5.650 |
2012 | 0.114 *** | 3.689 | 0.202 *** | 5.649 |
2013 | 0.084 ** | 2.967 | 0.201 *** | 5.635 |
2014 | 0.081 ** | 2.849 | 0.205 *** | 5.766 |
2015 | 0.101 *** | 3.311 | 0.205 *** | 5.758 |
2016 | 0.093 *** | 3.133 | 0.202 *** | 5.679 |
2017 | 0.085 ** | 2.951 | 0.105 *** | 3.399 |
2018 | 0.074 ** | 2.682 | 0.197 *** | 5.574 |
2019 | 0.061 ** | 2.353 | 0.195 *** | 5.539 |
Matrix Type | Geographic Matrix | ||
---|---|---|---|
Model Setting | SDM | SAR | SEM |
Variables | (1) | (2) | (3) |
IE | −0.502 *** (0.000) | −0.596 *** (0.000) | −0.612 *** (0.000) |
IE2 | 0.324 *** (0.000) | 0.385 *** (0.000) | 0.398 *** (0.000) |
W*IE | −1.393 *** (0.000) | ||
W*IE2 | 0.773 *** (0.001) | ||
IE_Direct | −0.546 *** (0.000) | −0.666 *** (0.000) | |
IE_Indirect | −2.503 *** (0.000) | −2.288 ** (0.030) | |
IE_Total | −3.049 *** (0.000) | −2.954 *** (0.007) | |
IE2_Direct | 0.347 *** (0.000) | 0.429 *** (0.000) | |
IE2_Indirect | 1.399 *** (0.002) | 1.474 ** (0.036) | |
IE2_Total | 1.746 *** (0.000) | 1.903 *** (0.010) | |
rho | 0.353 ** (0.016) | 0.774 *** (0.000) | |
lambda | 0.657 *** (0.000) | ||
Obs | 330 | 330 | 330 |
R2 | 0.271 | 0.268 | 0.517 |
Region Variables | Theil | ||||||||
---|---|---|---|---|---|---|---|---|---|
East | Middle | West | |||||||
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
IE | −0.121 *** (0.0109) | −0.290 *** (0.0487) | −0.135 *** (0.0249) | −0.175 *** (0.0243) | −0.495*** (0.139) | −0.264 (0.141) | −0.275 *** (0.0239) | −0.560 *** (0.130) | −0.272 * (0.129) |
IE2 | 0.167 *** (0.0469) | 0.0883*** (0.0241) | 0.538 * (0.231) | 0.348 (0.221) | 0.446 * (0.201) | 0.284 (0.172) | |||
Controls | NO | NO | YES | NO | NO | YES | NO | NO | YES |
_cons | 0.124 *** (0.00551) | 0.161 *** (0.0118) | 0.230 *** (0.0131) | 0.156 *** (0.00775) | 0.197 *** (0.0192) | 0.288 *** (0.0616) | 0.231 *** (0.00780) | 0.270 *** (0.0191) | 0.409 *** (0.0605) |
F | 124.94 | 74.86 | 198.94 | 51.81 | 29.68 | 16.48 | 132.53 | 71.43 | 53.32 |
N | 121 | 121 | 121 | 110 | 110 | 110 | 99 | 99 | 99 |
R2 | 0.512 | 0.559 | 0.913 | 0.324 | 0.357 | 0.490 | 0.577 | 0.598 | 0.777 |
Variable | Theil | ||
---|---|---|---|
(1) | (2) | (3) | |
IE | −0.156 *** (0.030) | −0.109 *** (0.000) | −0.242 *** (0.000) |
IE2 | 0.138 *** (0.030) | 0.095 *** (0.000) | 0.224 *** (0.000) |
Instr | 0.000 (0.000) | −0.000 (0.582) | 0.000 (0.714) |
Hc | −0.007 * (0.003) | −0.002 (0.523) | −0.009 *** (0.002) |
Gfi | 0.000 *** (0.000) | 0.000 *** (0.000) | 0.000 *** (0.000) |
Ur | −0.212 *** (0.024) | −0.236 *** (0.000) | −0.190 *** (0.000) |
Lm | -0.000 (0.960) | ||
Inf | 0.001 (0.765) | ||
_cons | 0.284 *** (0.019) | 0.252 *** (0.000) | 0.316 *** (0.000) |
N | 300 | 270 | 330 |
R2 | 0.774 | 0.761 | 0.797 |
Experimental Group | Inner Mongolia; Sichuan; Guizhou; Yunnan; Shaanxi; Gansu |
Control Group | Beijing; Tianjin; Hebei; Shanxi; Liaoning; Jilin; Heilongjiang; Shanghai; Jiangsu; Zhejiang; Anhui; Fujian; Jiangxi; Shandong; Henan; Hubei; Hunan; Guangdong; Guangxi; Hainan; Chongqing; Qinghai; Ningxia; Xinjiang |
Variable | (1) | (2) |
---|---|---|
Treat×time | −1.525 *** (0.214) | −0.587 *** (0.182) |
Instr | −0.479 *** (0.103) | |
Hc | −0.889 *** (0.226) | |
Gfi | 0.163 *** (0.0370) | |
Ur | −1.645 *** (0.108) | |
Treat | −0.323 ** (0.141) | |
Post | 0.00156 (0.0378) | |
_cons | −2.377 *** (0.0289) | −1.093 (0.838) |
Time Fixed | YES | YES |
Area Fixed | YES | YES |
N | 330 | 330 |
R2 | 0.134 | 0.869 |
Variables | 2010 | 2011 | 2012 |
---|---|---|---|
DID | −0.459 (0.586) | −0.495 (0.463) | −0.469 (0.436) |
Treat | −0.810 (0.537) | −0.863 ** (0.380) | −0.959 *** (0.311) |
_cons | −2.238 *** (0.0406) | −2.238 *** (0.0405) | −2.238 *** (0.0405) |
Time Fixed | YES | YES | YES |
Area Fixed | YES | YES | YES |
N | 180 | 180 | 180 |
R2 | 0.143 | 0.145 | 0.145 |
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Jiang, Q.; Li, Y.; Si, H. Digital Economy Development and the Urban–Rural Income Gap: Intensifying or Reducing. Land 2022, 11, 1980. https://doi.org/10.3390/land11111980
Jiang Q, Li Y, Si H. Digital Economy Development and the Urban–Rural Income Gap: Intensifying or Reducing. Land. 2022; 11(11):1980. https://doi.org/10.3390/land11111980
Chicago/Turabian StyleJiang, Qi, Yihan Li, and Hongyun Si. 2022. "Digital Economy Development and the Urban–Rural Income Gap: Intensifying or Reducing" Land 11, no. 11: 1980. https://doi.org/10.3390/land11111980