| Literature DB >> 33100487 |
Lichen Chou1, Jie Dai2, Xiaoyan Qian3, Aliakbar Karimipour4, Xuping Zheng5.
Abstract
With the development of Chinese economy, more and more attention has been paid to environmental protection, the implementation of water price policy affects economic and environmental changes in China. This paper analyzes the impact of water price policy on agricultural land use and the scale of water pollution discharge in 240 cities in China between 2001 and 2017, by including data from China Urban Statistical Yearbook and China Land & Resources Almanac. The theoretical analysis of this study indicates that the optimal scale of pollution depends on the local initial endowment, economic investment capital and the marginal cost of environmental pollution caused by government's economic activities. Furtherly, the economic activities have a worsening impact on environmental pollution, but when the government implements environmental protection and water price policy measures in response to environmental pollution caused by economic activities, it has a significant impact on the decline in the scale of pollution. The government has promoted the pollution suppression model in the formulation of water prices, which has internalized the external cost of pollution in economic activities and can effectively reduce the scale of agricultural water pollution discharge.Entities:
Keywords: Agricultural water conversation; Land use; Water pollution; Water price policy
Year: 2020 PMID: 33100487 PMCID: PMC7572319 DOI: 10.1016/j.agwat.2020.106583
Source DB: PubMed Journal: Agric Water Manag ISSN: 0378-3774 Impact factor: 4.516
Chinese main water price policy in recent years.
| Regulation or Policy | Implementation Year | Goal |
|---|---|---|
| National Guidelines on Water Tariffs | 1998 | The price of urban water consists of water supply cost, expense, tax and 8–10% profit. |
| Notice on the Key Work of Deepening Economic System Reform | 2010 | Steadily push forward the reform of water prices, implement a differential pricing system for urbanite water consumption in areas where conditions permit, and advance the comprehensive reform of agricultural water conservation and agricultural water prices. |
| Water Law of the People’s Republic of China | 2016 | Water use shall be measured in accordance with metering charge and over quota progression add to price system. |
| Some Opinions on Pushing Forward the Supply-Side Structural Reform in Agricultural Sector and Accelerating the Cultivation of New Drivers of Agricultural and Rural Development | 2017 | The implementation of water-saving incentives pilot is to give incentives to farmers directly and reward efficient water-saving facilities. |
Fig. 1Relevant Policies of Agricultural Water Price Reform from 2001 to 2019.
Descriptive statistics.
| Variable | Mean | Observations | Definition |
|---|---|---|---|
| Land Price ( | 561,217 | 4557 | Income from the sale of state-owned land in the year (unit: 10,000 yuan) |
| Water ( | 7054 | 3922 | The amount of agricultural wastewater discharge (unit: 10,000 tons) |
| Wage ( | 31,378 | 4772 | Average annual wage of urban employees (unit: yuan) |
| Loan ( | 1.940 | 4233 | Deposit balance of financial institutions at the end of the year (unit: 100 million yuan) |
| Policy | 0.235 | 5661 | Dummy variable, if water price policy is proposed in this year = 1, others = 0 |
| Change | 0.244 | 5615 | Dummy variable, if the Secretary of Municipal Committee changed in the previous year = 1, others = 0 |
Results 1- OLS Estimation.
| Dependent Variable | ||||
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| OLS 1 | OLS 2 | RE 1 | RE 2 | |
| 0.448 | 0.113 | 0.080 | ||
| (0.015) | (0.013) | (0.013) | ||
| 0.685 | 0.077 | 0.243 | ||
| (0.016) | (0.023) | (0.031) | ||
| -1.291 | 0.089 | -0.033 | -0.914 | |
| (0.113) | (0.075) | (0.017) | (0.110) | |
| 0.707**** | -0.263 | -0.288 | 0.052 | |
| (0.055) | (0.071) | (0.040) | (0.061) | |
| Year Dummies | Yes | Yes | No | Yes |
| Constant | 0.924 | 0.755 | 9.425 | 3.772 |
| (0.514) | (0.593) | (0.179) | (0.672) | |
| N | 4075 | 3861 | 3795 | 3795 |
| White Test (P-value) | 0.000 | 0.000 | ||
| Omitted variable Test (P-value) | 0.000 | 0.000 | ||
| Mean VIF | 2.88 | 3.44 | ||
| R square | 0.255 | 0.383 | 0.244 | 0.383 |
Standard errors in parentheses,
p < 0.1,
p < 0.05,
p < 0.01
Results 3- Estimation in Different Region.
| Dependent Variable | ||||
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| East | Middle | West | Coastal | |
| 0.133 | 0.052 | 0.178 | 0.154 | |
| (0.040) | (0.040) | (0.036) | (0.034) | |
| 0.555 | 0.350 | 0.335 | 0.371 | |
| (0.048) | (0.045) | (0.051) | (0.045) | |
| -0.186 | -0.378 | -0.277 | -0.233 | |
| (0.066) | (0.084) | (0.098) | (0.083) | |
| -0.751 | -0.480 | -0.344 | -0.482 | |
| (0.087) | (0.082) | (0.085) | (0.085) | |
| Change | 0.031 | -0.103 | -0.035 | -0.967 |
| (0.052) | (0.065) | (0.075) | (0.063) | |
| Year Dummies | Yes | Yes | Yes | Yes |
| Constant | 5.827 | 7.341 | 3.907 | 5.831 |
| (0.701) | (0.703) | (0.798) | (0.727) | |
| N | 1041 | 1069 | 825 | 1178 |
| R square | 0.398 | 0.151 | 0.267 | 0.261 |
Standard errors in parentheses,
*p < 0.1,
** p < 0.05,
p < 0.01
Results 2- Robust Check.
| Dependent Variable | ||||
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| OLS 1 | OLS 2 | RE 1 | RE 2 | |
| 0.454 | 0.101 | 0.112 | ||
| (0.015) | (0.012) | (0.013) | ||
| 0.677 | 0.047 | 0.161 | ||
| (0.016) | (0.022) | (0.027) | ||
| -1.180 | -1.039 | -0.022 | 0.047 | |
| (0.129) | (0.117) | (0.016) | (0.029) | |
| 0.978**** | -0.244 | -0.090 | -0.212 | |
| (0.068) | (0.071) | (0.038) | (0.043) | |
| Change | 0.012 | 0.011 | 0.012 | 0.011 |
| (0.035) | (0.032) | (0.016) | (0.016) | |
| Year Dummies | Yes | Yes | No | Yes |
| Constant | -3.711 | 0.645 | 7.950 | 7.258 |
| (0.643) | (0.592) | (0.170) | (0.243) | |
| N | 3830 | 3895 | 3829 | 3829 |
| White Test (P-value) | 0.000 | 0.000 | ||
| Omitted variable Test (P-value) | 0.000 | 0.000 | ||
| Mean VIF | 3.80 | 3.92 | ||
| R square | 0.256 | 0.366 | 0.299 | 0.378 |
Standard errors in parentheses
p < 0.1,
p < 0.05,
p < 0.01