Financing Constraints, Carbon Emissions and High-Quality Urban Development—Empirical Evidence from 290 Cities in China
Abstract
:1. Introduction
2. Mechanism Analysis
2.1. The Effect of Financing Constraints on the High-Quality Urban Development
2.2. The Effect of Financing Constraints on High-Quality Urban Development through Carbon Emissions
3. Study Design
3.1. Measurement Model Setting
3.2. Variable Measurement and Data Description
3.3. Analysis of the Basic Facts
4. Test of Financing Constraints, Carbon Emissions, and High-Quality Urban Development
4.1. Direct Effect of Financing Constraints on High-Quality Urban Development
4.2. Mediation Effect Test of Financing Constraints Affect the High-Quality Development of Cities through Carbon Emissions
4.3. Test of the Heterogeneity of Financing Constraints Affecting High-Quality Urban Development
4.3.1. Heterogeneity Effect of Different Quantile Financing Constraints on High-Quality Urban Development
4.3.2. Heterogeneity Effect of Financing Constraints at Different Stages on High-Quality Urban Development
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Definitions | Symbols | Measurement Methods |
---|---|---|---|
Dependent Variable | High-quality urban development | hq | The logarithm value of total factor productivity measured by OLS |
Independent Variable | financing constraints | fc | financing constraints was used as the proxy variable |
Mediator Variable | carbon emissions | co2 | Ci = ΣαiβiEi |
Control Variables | economic development level | gdp | The logarithm value of GDP |
The degree of openness | fdi | The proportion of the actual foreign investment in GDP | |
Industrial structure | sec | The added value of the secondary industry accounts for GDP | |
Infrastructure construction | infra | The proportion of total passenger traffic in the total population at the end of the year | |
Population agglomeration | popu | The ratio of the total population to the administrative area at the end of the year | |
Information level | infor | The proportion of post and telecommunications business income in GDP | |
Fixed-asset investment | cap | The logarithm of the total fixed-asset investment | |
Time effect | year | Virtual variable of the year | |
Regional effect | city | Virtual variable of the region |
Variables | hq | fc | co2 | gdp | fdi | sec | infra | popu | infor | cap |
---|---|---|---|---|---|---|---|---|---|---|
Mean | 1.596 | 0.946 | 24.9 | 10.17 | 0.0204 | 48.84 | 22.22 | −3.484 | 0.0278 | 15.48 |
Std. deviation | 0.786 | 0.382 | 20.28 | 0.773 | 0.021 | 10.78 | 22.57 | 0.871 | 0.0165 | 1.137 |
Minimum | 0.108 | 0.198 | 1.672 | 8.039 | 0.000119 | 21 | 3.052 | −6.012 | 0.00658 | 12.27 |
Maximum | 2.917 | 2.141 | 103.4 | 11.81 | 0.15 | 78.7 | 144 | −2.006 | 0.0975 | 17.85 |
The 10th quantile | 0.468 | 0.454 | 6.434 | 9.133 | 0.00196 | 35.5 | 7.318 | −4.756 | 0.0128 | 13.93 |
The 25th quantile | 0.928 | 0.683 | 10.55 | 9.629 | 0.00573 | 42 | 10.62 | −4.006 | 0.0172 | 14.66 |
The 50th quantile | 1.666 | 0.932 | 18.63 | 10.21 | 0.0132 | 49.2 | 15.53 | −3.357 | 0.0235 | 15.55 |
The 75th quantile | 2.266 | 1.183 | 33.03 | 10.73 | 0.0279 | 55.6 | 23.97 | −2.771 | 0.0329 | 16.29 |
The 90th quantile | 2.611 | 1.434 | 53.91 | 11.16 | 0.0481 | 61.8 | 41.86 | −2.5 | 0.048 | 16.93 |
Observations | 4060 | 3967 | 4060 | 3935 | 3498 | 3718 | 3144 | 4011 | 3943 | 3719 |
Model | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Method | POLS | FE | SYS-GMM | DIF-GMM |
Variable | hq | hq | hq | hq |
L.hq | 0.3804 *** | 0.4434 *** | ||
(0.0013) | (0.0006) | |||
fc | −0.2066 *** | −0.4761 *** | −1.1918 *** | −0.8428 *** |
(0.0360) | (0.0583) | (0.0151) | (0.0083) | |
gdp | −0.2311 *** | −0.1472 * | −0.5490 *** | −0.4216 *** |
(0.0344) | (0.0809) | (0.0175) | (0.0092) | |
fdi | 2.8507 *** | 0.7007 | 2.0302 *** | −1.7307 *** |
(0.6142) | (0.8038) | (0.2228) | (0.2057) | |
sec | 0.0070 *** | 0.0199 *** | 0.0581 *** | 0.0289 *** |
(0.0015) | (0.0028) | (0.0011) | (0.0005) | |
infra | 0.0027 *** | 0.0059 *** | 0.0060 *** | 0.0029 *** |
(0.0007) | (0.0011) | (0.0002) | (0.0002) | |
popu | 0.0400 ** | −0.6053 ** | 0.1281 | 0.3311 *** |
(0.0182) | (0.2973) | (0.1312) | (0.0068) | |
infor | −0.9138 | −1.6706 | −1.1627 *** | −8.9904 *** |
(0.8607) | (1.1349) | (0.3449) | (0.1393) | |
cap | −0.1386 *** | −0.3603 *** | −0.3198 *** | −0.2579 *** |
(0.0208) | (0.0525) | (0.0095) | (0.0066) | |
_cons | 5.7464 *** | 5.6976 *** | 9.7953 *** | 9.6649 *** |
(0.2512) | (1.1239) | (0.5034) | (0.0402) | |
year | NO | YES | YES | YES |
city | NO | YES | YES | YES |
N | 2993 | 2989 | 2397 | 2993 |
R−sq | 0.127 | 0.221 |
Method | POLS | FE | ||||
---|---|---|---|---|---|---|
Model | (1) | (2) | (3) | (4) | (5) | (6) |
Variable | hq | co2 | hq | hq | co2 | hq |
fc | −0.2066 *** | −6.8262 *** | −0.1552 *** | −0.4761 *** | −1.9145 ** | −0.4725 *** |
(0.0360) | (0.6436) | (0.0364) | (0.0583) | (0.7937) | (0.0583) | |
co2 | 0.0075 *** | 0.0019 | ||||
(0.0010) | (0.0020) | |||||
gdp | −0.2311 *** | −2.0095 ** | −0.2160 *** | −0.1472 * | 10.8209 *** | −0.1674 ** |
(0.0344) | (0.6152) | (0.0342) | (0.0809) | (1.2652) | (0.0832) | |
fdi | 2.8507 *** | 22.7341 ** | 2.6794 *** | 0.7007 | −47.3798 ** | 0.7894 |
(0.6142) | (10.9705) | (0.6091) | (0.8038) | (17.8602) | (0.8117) | |
sec | 0.0070 *** | 0.0291 | 0.0068 *** | 0.0199 *** | −0.3290 *** | 0.0205 *** |
(0.0015) | (0.0271) | (0.0015) | (0.0028) | (0.0478) | (0.0030) | |
infra | 0.0027 *** | −0.0445 *** | 0.0030 *** | 0.0059 *** | 0.0167 | 0.0059 *** |
(0.0007) | (0.0131) | (0.0007) | (0.0011) | (0.0144) | (0.0011) | |
popu | 0.0400 ** | −0.1696 | 0.0413 ** | −0.6053 ** | 16.4634 ** | −0.6362 ** |
(0.0182) | (0.3255) | (0.0181) | (0.2973) | (7.8915) | (0.2932) | |
infor | −0.9138 | 35.7221 ** | −1.1829 | −1.6706 | 15.0590 | −1.6988 |
(0.8607) | (15.3728) | (0.8537) | (1.1349) | (9.4413) | (1.1362) | |
cap | −0.1386 *** | 13.3845 *** | −0.2394 *** | −0.3603 *** | 0.2813 | −0.3609 *** |
(0.0208) | (0.3718) | (0.0247) | (0.0525) | (0.7348) | (0.0527) | |
_cons | 5.7464 *** | −156.0570 *** | 6.9220 *** | 5.6976 *** | −13.6841 | 5.7232 *** |
(0.2512) | (4.4869) | (0.2951) | (1.1239) | (31.0651) | (1.1158) | |
year | NO | NO | NO | YES | YES | YES |
city | NO | NO | NO | YES | YES | YES |
N | 2993 | 2993 | 2993 | 2989 | 2989 | 2989 |
R−sq | 0.127 | 0.580 | 0.143 | 0.221 | 0.942 | 0.221 |
Model | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
Content | Above Q10 | Above Q25 | Above Q50 | Above Q75 | Above Q90 |
Variable | hq | hq | hq | hq | hq |
fc | −0.4530 *** | −0.4714 *** | −0.5511 *** | −0.5936 ** | −0.6986 |
(0.0586) | (0.0665) | (0.0981) | (0.1834) | (0.4345) | |
gdp | −0.0868 | 0.0320 | 0.2183 | 0.4574 * | 1.3778 ** |
(0.0843) | (0.1032) | (0.1572) | (0.2591) | (0.4381) | |
fdi | 1.2248 | 1.4842 | 1.6551 | 1.1656 | −2.0634 |
(0.8772) | (1.1260) | (1.8049) | (3.2049) | (8.5657) | |
sec | 0.0180 *** | 0.0165 *** | 0.0086 * | 0.0032 | 0.0053 |
(0.0031) | (0.0037) | (0.0051) | (0.0092) | (0.0176) | |
infra | 0.0051 *** | 0.0051 ** | 0.0064 ** | 0.0039 | 0.0032 |
(0.0012) | (0.0016) | (0.0025) | (0.0034) | (0.0042) | |
popu | −0.2423 | −0.3974 | −0.2802 | −0.2179 | −2.8257 * |
(0.3458) | (0.3961) | (0.5993) | (0.9718) | (1.4845) | |
infor | −1.8307 | −2.5235 * | −3.8291 ** | −4.1727 * | −3.5177 |
(1.2442) | (1.2872) | (1.5741) | (2.5081) | (4.5081) | |
cap | −0.3933 *** | −0.4492 *** | −0.4891 *** | −0.5349 ** | −0.8732 ** |
(0.0556) | (0.0674) | (0.1045) | (0.1672) | (0.2736) | |
_cons | 6.9083 *** | 6.1454 *** | 5.9085 ** | 4.8974 | −7.9714 |
(1.3227) | (1.5329) | (2.3257) | (3.8367) | (6.1503) | |
year | YES | YES | YES | YES | YES |
city | YES | YES | YES | YES | YES |
N | 2715 | 2309 | 1643 | 875 | 339 |
R−sq | 0.211 | 0.201 | 0.166 | 0.146 | 0.194 |
Model | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Content | Before 2006 | Before 2010 | Before 2014 | Before 2017 |
Variable | hq | hq | hq | hq |
fc | −0.3357 ** | −0.7370 *** | −0.7263 *** | −0.4761 *** |
(0.1554) | (0.0907) | (0.0668) | (0.0583) | |
gdp | 0.7758 *** | −1.1014 *** | 0.0398 | −0.1472 * |
(0.1689) | (0.1414) | (0.0919) | (0.0809) | |
fdi | −3.6527 ** | −0.2396 | 0.7133 | 0.7007 |
(1.2678) | (1.2370) | (0.9078) | (0.8038) | |
sec | 0.0167 ** | −0.0020 | 0.0130 *** | 0.0199 *** |
(0.0053) | (0.0051) | (0.0035) | (0.0028) | |
infra | 0.0037 | 0.0011 | 0.0028 ** | 0.0059 *** |
(0.0081) | (0.0025) | (0.0012) | (0.0011) | |
popu | 1.3183 ** | −1.7745 ** | −0.8033 ** | −0.6053 ** |
(0.4371) | (0.6670) | (0.3650) | (0.2973) | |
infor | 6.9119 *** | 1.9234 | −1.3614 | −1.6706 |
(1.4454) | (1.2649) | (1.1890) | (1.1349) | |
cap | −0.1042 | 0.1241 | −0.3512 *** | −0.3603 *** |
(0.1046) | (0.0821) | (0.0597) | (0.0525) | |
_cons | 0.3496 | 4.9031 * | 3.7068 ** | 5.6976 *** |
(1.9784) | (2.6238) | (1.3814) | (1.1239) | |
year | YES | YES | YES | YES |
city | YES | YES | YES | YES |
N | 810 | 1898 | 2722 | 2989 |
R−sq | 0.336 | 0.372 | 0.163 | 0.221 |
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Wang, S.; Liu, J.; Qin, X. Financing Constraints, Carbon Emissions and High-Quality Urban Development—Empirical Evidence from 290 Cities in China. Int. J. Environ. Res. Public Health 2022, 19, 2386. https://doi.org/10.3390/ijerph19042386
Wang S, Liu J, Qin X. Financing Constraints, Carbon Emissions and High-Quality Urban Development—Empirical Evidence from 290 Cities in China. International Journal of Environmental Research and Public Health. 2022; 19(4):2386. https://doi.org/10.3390/ijerph19042386
Chicago/Turabian StyleWang, Shaobo, Junfeng Liu, and Xionghe Qin. 2022. "Financing Constraints, Carbon Emissions and High-Quality Urban Development—Empirical Evidence from 290 Cities in China" International Journal of Environmental Research and Public Health 19, no. 4: 2386. https://doi.org/10.3390/ijerph19042386
APA StyleWang, S., Liu, J., & Qin, X. (2022). Financing Constraints, Carbon Emissions and High-Quality Urban Development—Empirical Evidence from 290 Cities in China. International Journal of Environmental Research and Public Health, 19(4), 2386. https://doi.org/10.3390/ijerph19042386