| Literature DB >> 31234521 |
Weidong Sun1, Zhigang Chen2,3, Danyang Wang4.
Abstract
Industrial pollution control is a difficult problem in China's current economic transformation, and the Chinese government has implemented many measures to deal with it. However, little research has focused on the relationship between land policy and industrial pollution. Based on the theoretical discussion of the mechanism influencing the market-oriented reform of industrial land (mainly refer to the marketization of land conveyance price and the openness of land conveyance process) on urban industrial pollution, we constructed an analytical framework by linking land policy with industrial pollution. Then, we constructed an econometric model and chose the statistical data of 104 large- and medium-sized cities in mainland China from 2003 to 2016. The results indicate that with the marketization of the industrial land conveyance price, urban industrial pollution is presenting an inverted U-shaped change trend. For cities in different development stages of industrialization, there is no difference in the impact of industrial land conveyance price on urban industrial pollution. However, the openness of industrial land conveyance promotes and inhibits the urban industrial pollution in the stages of industrialization and post-industrialization, respectively. Finally, this paper puts forward some suggestions on how to control industrial pollution from the perspective of further improving the industrial land conveyance mechanism.Entities:
Keywords: containment effect; industrial land; industrial pollution; land price; market-oriented reform
Mesh:
Year: 2019 PMID: 31234521 PMCID: PMC6617276 DOI: 10.3390/ijerph16122213
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Policy evolution of the market-oriented reform of industrial land in China.
Figure 2The theoretic framework of urban industrial land marketization and industrial pollution.
Descriptive statistics of the variables used in the model.
| Variable | Unit | Number of Observations | Mean | Std. Deviation | Minimum | Maximum |
|---|---|---|---|---|---|---|
|
| t/108 yuan | 1444 | 61.54 | 85.86 | 0.16 | 723.97 |
|
| yuan/m2 | 1456 | 486.86 | 318.17 | 68.00 | 3742.00 |
|
| - | 1456 | 0.71 | 0.45 | 0 | 1 |
|
| yuan | 1456 | 42,827.86 | 29,132.67 | 3393 | 167,411 |
|
| 104 dollars | 1456 | 140,953.30 | 252,097.68 | 0.00 | 3,082,563.00 |
|
| kW·h/104 yuan | 1419 | 670.23 | 735.47 | 24.99 | 11,208.10 |
|
| % | 1456 | 49.23 | 9.57 | 18.57 | 85.92 |
Note: poll: the emission intensity of industrial SO2; ilp: the urban industrial land price; ilm: the dummy variable of the reform of industrial land conveyance mode; pgdp: per capita GDP; fdi: foreign direct investment; ene: the consumption intensity of electricity; ind: the industrial structure (the proportion of the secondary industry output value to gross regional product).
Figure 3The change in China’s industrial land supply area and industrial pollution from 2003 to 2015.
Estimation results of full sample model.
| Variables | Dependent Variable: In | |
|---|---|---|
| Fixed Effect | Random Effect | |
|
| 59.509 ** | 55.009 ** |
|
| 2.738 *** | 2.575 *** |
|
| −0.244*** | −0.227 *** |
|
| −0.011 | −0.070 |
|
| −16.985 ** | −15.984 ** |
|
| 1.594 ** | 1.508 ** |
|
| −0.054 ** | −0.051 ** |
|
| −0.063 *** | −0.059 *** |
|
| 0.235 *** | 0.323 *** |
|
| 0.008 *** | 0.010 *** |
|
| 0.655 | 0.675 |
| F/Wald chi2 | F = 630.19, | Wald chi2 (10) = 5638.89 |
| N | 1403 | 1403 |
| Hausman test | Prob > chi2 = 0.0000 | |
Note: Standard errors are in parentheses. ***, **, * indicate significance at 1%, 5%, and 10% respectively.
Estimation results of grouped sample model.
| Variables | Dependent Variable: In | |
|---|---|---|
| Industrialization Stage | Post-Industrialization Stage | |
|
| −4.925 | 171.060 *** |
|
| 1.876 ** | 5.725 *** |
|
| −0.194 *** | −0.407 *** |
|
| 0.144 ** | −0.324 *** |
|
| 3.262 | −54.054 *** |
|
| −0.396 | 5.226 *** |
|
| 0.010 | −0.171 *** |
|
| 0.004 | −0.173 *** |
|
| 0.152 *** | 0.318 *** |
|
| 0.002 | 0.041 *** |
|
| 0.674 | 0.628 |
| F | F = 585.24, | F = 260.32, |
| N | 802 | 601 |
Note: Standard errors are in parentheses. ***, **, * indicate significance at 1%, 5%, and 10% respectively.