| Literature DB >> 35805763 |
Abstract
Based on China's provincial panel data from 2007 to 2019, the authors of this paper conducted an empirical test on the direct effect of China's fiscal expenditure structure on the reduction in environmental pollution with the use of a fixed effect model. We also creatively added an interaction item comprising vertical fiscal imbalance and the expenditure structure to further study the impact of vertical fiscal imbalance on reducing environmental pollution and its effect on the fiscal expenditure structure. The study results show that a structure in favor of expenditure on people's welfare noticeably reduces environmental pollution. However, after the introduction of the vertical fiscal imbalance indicator, the pollution reduction effect decreases. That is, the vertical fiscal imbalance weakens and distorts the impact of the fiscal expenditure structure on the reduction in environmental pollution. Therefore, it is possible to further motivate local governments with incentive measures, such as fiscal decentralization and the centralization of administrative responsibilities, and regulate the environmental pollution of local governments through use of restrictive measures, such as the "green GDP" evaluation mechanism to further improve the fiscal expenditure structure of local governments, enhance the environmental pollution reduction capability of fiscal expenditure.Entities:
Keywords: environmental pollution; expenditure on people’s welfare; fiscal expenditure structure; vertical fiscal imbalance
Mesh:
Year: 2022 PMID: 35805763 PMCID: PMC9265602 DOI: 10.3390/ijerph19138106
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Summary of the most important articles of the literature.
| Types | Ref. Author(s), Year | Methodology | Sample (If It Is Empirical) | Main Conclusions | Ref. No. |
|---|---|---|---|---|---|
| Fiscal expenditure structure | Wu et al., (2013) | Fixed effect model | Data of 27 provinces in China from 2000 to 2009 | The appeal for political achievements urges local officials to allocate limited resources to areas conducive to economic growth, thereby reducing financial expenditures in people’s welfare areas such as environmental protection, which is harmful to efforts to improve environmental quality. | [ |
| Halkos and Paizanos (2013) | Fixed effect model; | A panel of 77 countries for the time period 1980–2000. | Fiscal expenditure in favor of economic growth is bad for environment quality improvement. | [ | |
| He et al., (2018) | Fixed effects; | seven seriously polluted cities in China, from the period 2007–2015 | The expenditure structure in favor of public services, such as environmental protection, and education, is conducive to reducing environmental pollution. | [ | |
| Halkos and Paizanos (2017) | Dynamic Fixed Effects | panel data for 94 countries for the period 1970–2008 | There is a significant alleviating direct effect of government expenditure on SO2 and NOx emissions, which increases with the level of economic growth and democracy. | [ | |
| Chen and Lu (2014) | Fixed Effects | Panel data of 112 prefecture -level cities in China from 2007 to 2009 | Increasing the share of non-economic fiscal expenditure is conducive to alleviating production-generated pollution. | [ | |
| Yu and Yang (2016) | Fixed Effects | Panel data of 287 cities in China from 2007 to 2013 | Non-economic public expenditure would promote the technological innovation of emission reduction and pollution remediation, and thus the environmental quality could be improved at the same time as reducing pollutant emissions. | [ | |
| Lu et al., (2015) | Fixed Effects; GMM | Data of 103 key environmental protection cities in China from 2007 to 2012 | Increasing the share of China’s non-economic fiscal expenditure is conducive to alleviating the regional emission levels of consumption-generated pollutants. | [ | |
| Vertical fiscal imbalance | Bordignon et al., (2013) | Theoretical model; Dynamic Fixed Effects | Data of 89 chief provincial towns in Italy from 1988 to 1997 | Under the fiscal decentralization system, the central government has more revenue and fewer expenditures, whereas local governments have less revenue and more expenditures, and the vertical fiscal imbalance arises at the historic moment. | [ |
| Boadway R. (2004) | Theoretical model | n.a. | Vertical fiscal imbalance is a common phenomenon in countries with decentralized systems. | [ | |
| Jiménez-Rubio, D. (2011a) | Fixed Effects | A panel data of the highly decentralized Canadian provinces during the period 1979 to 1995. | Vertical fiscal imbalance is a common phenomenon in all decentralized countries, and moderate vertical imbalance is beneficial. | [ | |
| Jiménez-Rubio, D. (2011b) | Fixed Effects | a panel of 20 OECD countries over a thirty-year period (1970–2001) | There are vertical imbalances in countries with decentralized systems. As long as they are maintained within an appropriate range, it will promote the optimization of local public expenditure structure. | [ | |
| Bardhan and Mookherjee (2003) | Theoretical model | n.a. | Excessive vertical fiscal imbalance will produce many negative effects and harm, such as distorting the public expenditure structure of local governments. | [ | |
| Smith and Revell (2016) | A case study approach | Data from 1990 to 2010 for six cities in Argentina and Mexico | After analyzed the political decentralization and fiscal decentralization of six countries in Latin America, including Argentina and Mexico, and found that excessive power of the provinces would cause severe vertical fiscal imbalance. | [ | |
| Chu et al., (2017) | Panel threshold model | China’s budgetary and extra budgetary revenue and expenditure data from 1994 to 2015 | China’s decentralization system, with political centralization and economic decentralization, leads to more serious vertical fiscal imbalance than that in western countries. | [ | |
| Duan and Zhan (2011) | Fixed Effects | Data of 114 districts and counties in Shanxi Province, China from 1994 to 2005 | Fiscal transfer payments among governments are an important measure for easing vertical fiscal imbalance. | [ | |
| Boetti et al., (2012) | OLS regressions; SFA model; DEA model | Data for 262 cities in Turin, Italy | Italian government’s enhancement of the degree of self-financing of lower-level governments was conducive to easing vertical fiscal imbalance. | [ | |
| Amusa et al., (2008) | Ordinary Least Squares Regression (OLS) | Data from 237 local government (category A and B municipalities) in South Africa in fiscal year 2005/06 | Enhancing the degree of local self-sufficiency was more beneficial to easing vertical fiscal imbalance, instead of fiscal transfer payments among governments. | [ | |
| Oates, W. (1993) | n.a. | n.a. | The excessive vertical fiscal imbalance may make local governments rely too heavily on transfer payments. Local governments’ efforts would be decreased under the soft constraint, thereby damaging the financial autonomy of the local government. | [ | |
| Chu and Shao (2018) | Dynamic panel data Model; GMM | Data at the provincial level in China from 2007 to 2015 | The vertical fiscal imbalance affects the public expenditure behavior of the local government and causes distortion of the public expenditure structure. | [ | |
| Jia et al., (2016) | Dynamic panel data Model; Fixed Effects | Chinese prefectural panel data set from 2001 to 2007 | The vertical fiscal imbalance exacerbates the behavior of land finance, during which political promotion intensifies the behavior, which affects the sustainable development of China’s economy and society. | [ | |
| Wang and Zhang (2017) | Fixed Effects; Instrumental Variable (IV) Regression | Using a large, unique county-level panel dataset for China from 1998 to 2006 | When faced with vertical fiscal imbalance constraints, especially a high level of imbalance, local governments depend on tax revenue from polluting enterprises to ease pressure, which inevitably causes environmental pollution. | [ | |
| Xi, P.H. (2017) | Fixed Effects | Sample panel data of China’s cities from 2003 to 2009 | when faced with vertical fiscal imbalance, the fiscal expenditure may be biased toward the industries which can bring more fiscal revenue, such as construction industry, real estate industry, etc., but these industries also cause environmental pollution. | [ | |
| Xi et al., (2017) | Fixed Effects | China’s provincial panel data from 2003 to 2011 | Under the influence of vertical fiscal imbalance, with respect to the fiscal expenditure structure, governments may lean more towards “resource-intensive” projects, represented by infrastructure construction. Such expenditure increases the GDP in a short time but causes irreversible pollution. | [ | |
| Devarajan et al., (1996) | Theoretical model; Fixed effects | Data for 43 developing countries from 1970–1990 | The sum of expenditures, including general public service, public safety, science and technology, social security, education, culture, sports, and media, as well as energy conservation and environmental protection, was viewed as expenditure on people’s welfare. | [ | |
| Li et al., (2021) | Fixed effects; Pooled Effects; Random effects | Data of Pakistan from 2000 to 2018 | The vertical fiscal imbalance causes environmental degradation by changing the industry structure, and also restrains environment supervision. | [ | |
| Huang and Zhou (2020) | Fixed effects; Quantile Regression | The panel data of China’s 30 provincial level from 1999 to 2016 | In China, a higher level of vertical fiscal imbalance causes even worse environmental pollution. | [ |
n.a. means not applicable.
Classification and descriptions of variables.
| Variable Type | Variables | Sign | Description |
|---|---|---|---|
| Explained Variables | Per capita wastewater | pww | Discharge amount of wastewater (10,000 tons) per capita |
| Per capita waste gas | pwg | Discharge amount of waste gas (billion cubic meters) per capita | |
| Per capita solid waste | psw | Discharge of solid waste (10,000 tons) per capita | |
| Core Explanatory Variables | Vertical fiscal imbalance | vfi | (1 − Fiscal revenue decentralization/Fiscal Expenditure Decentralization (1 — Local government’s gap ratio of fiscal self-sufficiency)) × 100 (%) |
| Fiscal expenditure structure | exp | Expenditure on people’s welfare/Total fiscal expenditure × 100 (%) | |
| Control Variables | Foreign direct investment | fdi | Amount of foreign capital actually used in the region (100 million CNY) |
| Energy consumption structure | ecs | Proportion of coal consumption in total energy consumption (%) | |
| Industrial structure | is | Proportion of secondary industry, i.e., the industrial added value, in GDP (%) | |
| Urbanization rate | urba | Proportion of urban population in total provincial population (%) | |
| Real GDP per capita | rgdp | Real GDP per capita (CNY) | |
| Population density | pd | Proportion of total population in the area of this region (per capita square kilometer) | |
| Fixed asset investment | fai | Proportion of fixed asset investment in GDP (%) | |
| Built-up area | bua | Built-up area (square kilometer) |
Descriptive statistics of main variables.
| Variable | Obs | Mean | Std. Dev | Min | Max |
|---|---|---|---|---|---|
|
| |||||
| Per capita wastewater (lnpww) | 403 | 2.501 | 0.619 | 0.127 | 3.874 |
| Per capita waste gas (lnpwg) | 403 | 1.266 | 0.858 | −3.944 | 3.263 |
| Per capita solid wastes (lnpsw) | 403 | 0.463 | 0.948 | −3.979 | 3.241 |
|
| |||||
| Expenditure structure (lnexp) | 403 | 3.945 | 0.122 | 3.577 | 4.327 |
| Vertical fiscal imbalance (lnvfi) | 403 | 4.152 | 0.309 | 2.874 | 4.605 |
|
| |||||
| Industrial structure (lnis) | 403 | 3.831 | 0.226 | 2.949 | 4.235 |
| Foreign direct investment (lnfdi) | 403 | 3.276 | 1.711 | −1.897 | 5.985 |
| Economic development level (lnrgdp) | 403 | 7.624 | 2.819 | 0.437 | 15.424 |
| Energy consumption structure (lnecs) | 403 | 2.993 | 0.502 | 0.198 | 4.486 |
| Population density (lnpd) | 403 | 5.317 | 1.497 | 0.858 | 8.264 |
| Built-up area (lnbua) | 403 | 6.984 | 0.862 | 4.367 | 8.853 |
| Fixed asset investment (lnfai) | 403 | 8.789 | 0.423 | 6.800 | 9.564 |
| Urbanization rate (lnurba) | 403 | 3.970 | 0.267 | 3.068 | 4.495 |
Basic regression results of the effects of vertical fiscal imbalance on the pollution reduction effect of the expenditure structure (three types of waste per capita).
| Variable | Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | |||
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| lnexp | 3.571 | −6.334 ** | −12.451 *** | −10.432 *** | −11.824 *** | −16.132 *** |
| (0.98) | (−2.18) | (−5.35) | (−3.85) | (−6.85) | (−7.34) | |
| lnvfi | 25.793 *** | 0.536 | 20.85 *** | |||
| (3.01) | (0.11) | (6.20) | ||||
| lnexp × lnvfi | 3.837 *** | 0.632 | 3.327 *** | |||
| (6.47) | (0.19) | (6.28) | ||||
| lnrgdp | 0.315 *** | 0.422 *** | −0.076 * | −0.085 * | −0.218 *** | −0.087 ** |
| (4.16) | (4.32) | (−1.83) | (−1.88) | (−3.56) | (−2.37) | |
| lnis | 6.852 ** | 6.735 ** | 1.425 | 1.425 | 4.105 ** | 3.012 |
| (2.32) | (2.49) | (0.86) | (0.85) | (2.32) | (1.38) | |
| lnurba | 3.724 | 1.257 | 3.456 | 3.231 | 0.745 | −0.729 |
| (0.85) | (0.35) | (0.76) | (0.72) | (0.45) | (−0.56) | |
| lnecs | 1.732 | 0.534 | 0.897 | 0.872 | 5.531 *** | 4.597 *** |
| (0.78) | (0.28) | (0.46) | (0.67) | (4.13) | (2.87) | |
| lnpd | −13.87 | 4.891 | −2.137 | −1.715 | −4.165 | 9.435 ** |
| (−1.56) | (0.56) | (−0.57) | (−0.38) | (−1.08) | (2.25) | |
| lnfdi | 1.573 ** | 1.367 ** | −0.189 | 0.013 | −2.736 *** | −2.571 *** |
| (2.32) | (2.38) | (−0.14) | (0.13) | (−7.45) | (−8.35) | |
| lnbua | −7.154 ** | −8.107 ** | −2.514 | −1.738 | −2.470 | −2.127 |
| (−2.19) | (−2.26) | (−0.83) | (−0.80) | (−1.25) | (−0.90) | |
| lnfai | −2.653 ** | −3.098 *** | −0.089 | 0.113 | 0.876 | 0.610 |
| (−2.35) | (−2.87) | (−0.04) | (0.09) | (1.28) | (1.06) | |
| cons | 155.9 *** | 89.39 * | 7.335 | 3.351 | −30.35 | −89.45 *** |
| (3.83) | (1.80) | (0.36) | (0.12) | (−1.45) | (−4.18) | |
| Region-fixed effect | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES |
| N | 403 | 403 | 403 | 403 | 403 | 403 |
| R2 | 0.322 | 0.305 | 0.289 | 0.265 | 0.460 | 0.513 |
Note: ***, **, and * denote significance levels of 1%, 5%, and 10%, respectively; the numbers in the brackets are the statistical values.
Regression results of GMM.
| Variable | Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | |||
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| L.lnpww | 0.637 | 0.513 * | ||||
| L.lnpwg | 0.754 ** | 0.627 | ||||
| L.lnpsw | 0.684 ** | 0.526 ** | ||||
| lnexp | 2.416 | −4.125 * | −9.537 ** | −5.267 * | −8.214 ** | −12.125 *** |
| (0.46) | (−1.65) | (−2.21) | (−1.87) | (−2.52) | (−5.34) | |
| lnvfi | 21.651 *** | 0.472 | 18.43 ** | |||
| (2.74) | (0.09) | (2.25) | ||||
| lnexp × lnvfi | 2.165 *** | 0.562 | 2.127 *** | |||
| (2.97) | (0.12) | (5.08) | ||||
| cons | 129.352 *** | 80.394 * | 6.246 | 2.931 | −28.531 | −86.317 *** |
| (2.95) | (1.69) | (0.26) | (0.11) | (−1.25) | (−3.18) | |
| Control | YES | YES | YES | YES | YES | YES |
| Region-fixed effect | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES |
| N | 372 | 372 | 372 | 372 | 372 | 372 |
| AR(1) | 0.019 | 0.038 | 0.022 | 0.037 | 0.025 | 0.034 |
| AR(2) | 0.246 | 0.774 | 0.053 | 0.064 | 0.846 | 0.758 |
| Sargan | 0.325 | 0.513 | 0.216 | 0.198 | 0.502 | 0.461 |
Note: ***, **, and * denote significance levels of 1%, 5%, and 10%; the numbers in the brackets are the statistical values. The GMM used was system GMM, and the command used was xtabond2.
Regression results of pollution reduction effect of fiscal expenditure structure (total amount of three types of waste).
| Variable | Total Amount of Industrial Wastewater | Total Amount of Industrial Waste Gas | Total Amount of Industrial Solid Waste | |||
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| lnexp | −0.852 ** | −0.864 ** | −0.538 | −0.641 | −0.872 ** | −2.975 *** |
| (−2.18) | (−2.42) | (−0.90) | (−0.90) | (−2.12) | (−6.17) | |
| lnvfi | 0.578 | 0.154 | 5.372 *** | |||
| (0.76) | (0.21) | (6.18) | ||||
| lnexp × lnvfi | 1.251 | 0.876 | 1.546 *** | |||
| (1.18) | (0.56) | (3.38) | ||||
| cons | 4.654 | 8.753 * | −26.16 *** | −29.983 *** | −22.761 *** | −45.49 *** |
| (1.23) | (1.89) | (−3.99) | (−3.92) | (−4.53) | (−8.79) | |
| Control | YES | YES | YES | YES | YES | YES |
| Region-fixed effect | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES |
| N | 403 | 403 | 403 | 403 | 403 | 403 |
| R2 | 0.201 | 0.223 | 0.378 | 0.389 | 0.496 | 0.589 |
Note: ***, **, and * denote significance levels of 1%, 5%, and 10%, respectively; the numbers in the brackets are the statistical values.
Regression results of pollution reduction effect of fiscal expenditure structure (pollution intensity).
| Variable | Pollution Intensity (Wastewater) | Pollution Intensity (Waste Gas) | Pollution Intensity (Solid Waste) | |||
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| lnexp | −1.243 *** | −0.997 *** | 0.516 | 0.338 | 0.061 | −2.006 *** |
| (−5.15) | (−3.89) | (0.91) | (0.46) | (0.10) | (−4.92) | |
| lnvfi | 0.728 | 0.341 | 5.789 *** | |||
| (1.12) | (0.31) | (6.89) | ||||
| lnexp × lnvfi | 1.129 | 1.910 | 0.30 *** | |||
| (1.42) | (1.19) | (8.43) | ||||
| cons | 24.42 *** | 26.13 *** | −14.65 ** | −20.35 *** | −11.89 ** | −37.13 *** |
| (8.92) | (6.93) | (−2.17) | (−2.76) | (−2.18) | (−6.87) | |
| Control | YES | YES | YES | YES | YES | YES |
| Region-fixed effect | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES |
| N | 403 | 403 | 403 | 403 | 403 | 403 |
| R2 | 0.797 | 0.799 | 0.090 | 0.109 | 0.098 | 0.356 |
Note: ***, ** denote significance levels of 1%, 5% respectively; the numbers in the brackets are the statistical values.
Impact of fiscal pressure on pollution reduction effect of fiscal expenditure structure.
| Variable | Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | |||
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| lnexp | 2.563 | −8.487 * | −11.45 *** | −13.42 *** | −11.31 *** | −18.97 *** |
| (0.73) | (−1.93) | (−5.76) | (−4.87) | (−6.15) | (−7.89) | |
| lnpre | 12.97 *** | 1.042 | 9.654 *** | |||
| (4.18) | (0.47) | (6.89) | ||||
| lnexp × lnpre | 14.98 *** | 1.932 | 12.86 *** | |||
| (3.47) | (0.84) | (6.76) | ||||
| cons | 166.814 *** | 125.357 ** | 6.652 | −0.682 | −29.57 | −81.78 *** |
| (3.89) | (2.47) | (0.35) | (−0.03) | (−1.41) | (−3.83) | |
| Control | YES | YES | YES | YES | YES | YES |
| Region-fixed effect | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES |
| N | 403 | 403 | 403 | 403 | 403 | 403 |
| R2 | 0.298 | 0.343 | 0.265 | 0.278 | 0.465 | 0.572 |
Note: ***, **, and * denote significance levels of 1%, 5%, and 10%, respectively; the numbers in the brackets are the statistical values.
Heterogeneity test.
| Variable | Eastern | Central | Western | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | Wastewater per Capita | Waste Gas per Capita | Solid Waste per Capita | |
| lnexp | −4.144 ** | −10.145 | −14.425 | −6.447 ** | −12.715 ** | −17.395 * | −8.919 *** | −14.841 *** | −19.065 *** |
| (−1.98) | (−1.46) | (−1.62) | (−2.38) | (−2.46) | (−1.79) | (−5.84) | (−5.20) | (−6.47) | |
| lnvfi | 23.886 | 5.983 | 18.702 * | 25.261 *** | 6.131 * | 20.226 *** | 27.422 *** | 8.563 *** | 22.600 *** |
| (1.58) | (0.673) | (1.67) | (2.71) | (1.71) | (2.87) | (2.98) | (3.91) | (3.77) | |
| lnexp×lnvfi | 2.326 * | 0.452 | 2.253 * | 5.172 ** | 0.726 * | 3.370 ** | 7.271 *** | 0.899 ** | 5.367 *** |
| (1.75) | (1.54) | (1.67) | (2.45) | (1.93) | (2.31) | (6.73) | (2.49) | (7.79) | |
| cons | 80.48 | 1.915 * | 87.330 | 81.321 ** | 3.177 ** | 89.647 ** | 85.244 ** | 1.557 ** | 91.085 ** |
| (1.61) | (1.72) | (1.35) | (2.16) | (2.31) | (2.38) | (2.13) | (2.32) | (2.50) | |
| Control | YES | YES | YES | YES | YES | YES | YES | YES | YES |
| Region-fixed effect | YES | YES | YES | YES | YES | YES | YES | YES | YES |
| Time-fixed effect | YES | YES | YES | YES | YES | YES | YES | YES | YES |
| N | 143 | 143 | 143 | 104 | 104 | 104 | 156 | 156 | 156 |
| R2 | 0.705 | 0.339 | 0.642 | 0.764 | 0.574 | 0.766 | 0.697 | 0.392 | 0.536 |
Note: ***, **, and * denote significance levels of 1%, 5%, and 10%, respectively; the numbers in the brackets are the statistical values.