scholarly journals Can Green Credit Policy Promote Green Innovation Efficiency of Heavily Polluted Industries? Empirical Evidence from the China’s Industry

2021 ◽  
Author(s):  
Su Li ◽  
Feng Tan Da ◽  
Wei Wei Cui ◽  
Jun Zhao
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Natural Experiment ◽  
Policy Impact ◽  
Credit Policy ◽  
Green Innovation ◽  
Ecological Civilization ◽  
Heterogeneity Test ◽  
Financing Cost ◽  
D Investment

Green credit policy as an important tool to guide China's sustainable economic development, how to effectively play the function of capital deployment and improve the efficiency of industrial green innovation is an important issue facing the construction of ecological civilization. This paper uses China's Green Credit Guideline introduced in 2012 as a quasi-natural experiment , based on relevant panel data of industries from 2007 to 2018, uses the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the PSM-DID model to explore how green credit policy impact on the green innovation efficiency of heavily polluted industries, the results show that : green credit policy significantly contributes to green innovation efficiency of heavily polluted industries with a lag. Further study finds that green credit policy pushes heavily polluted industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of industry, the greater the promoted effect of green credit policy on green innovation efficiency of heavily polluted industries. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavily polluted industries, relevant countermeasures are proposed from three aspects: banks, enterprises and government.

scholarly journals The Impact of Green Credit on the Green Innovation Level of Heavy-Polluting Enterprises—Evidence from China

2022 ◽  
Vol 19 (2) ◽  
pp. 650
Author(s):  
Zhifeng Zhang ◽  
Hongyan Duan ◽  
Shuangshuang Shan ◽  
Qingzhi Liu ◽  
Wenhui Geng
Keyword(s):  
Natural Experiment ◽  
Double Difference ◽  
Credit Policy ◽  
Green Innovation ◽  
Innovation Activities ◽  
Corporate Credit ◽  
Credit Financing ◽  
The Cost ◽  
The Impact

This article uses the “Green Credit Guidelines” promulgated in 2012 as an example to construct a quasi-natural experiment and uses the double difference method to test the impact of the implementation of the “Green Credit Guidelines” on the green innovation activities of heavy-polluting enterprises. The study found that, in comparison to non-heavy polluting enterprises, the implementation of green credit policies inhibited the green innovation of all heavy-polluting enterprises. In the analysis of heterogeneity, this restraint effect did not differ significantly due to the nature of property rights and the company’s size. The mechanism test showed that green credit policy limits the efficiency of business investment and increases the cost of financing business debt. Eliminating corporate credit financing, particularly long-term borrowing, negatively impacts the green innovation behavior of listed companies.

scholarly journals A Spatial Difference-in-Differences Approach to Evaluate the Efficiency of Urban Green Innovation under the Pilot Policy of Combining Technology and Finance

CONVERTER ◽  
2021 ◽  
pp. 719-727
Author(s):  
Xuefang Zhang, Wei Dai
Keyword(s):  
Panel Data ◽  
Local Governments ◽  
Natural Experiment ◽  
Spatial Difference ◽  
Green Innovation ◽  
Difference In Differences ◽  
Urban Green ◽  
The Impact

With the “Pilot Policy of Combining Technology and Finance” implemented in 2011 and 2016 as a quasi-natural experiment, taking the panel data of a total of 285 cities in China in 2003-2018 as an example, the spatial difference-in-differences models are used to evaluate the impact of pilot policy of combining technology and finance on urban green innovation efficiency. The study found that technology and finance pilot policies obviously increase the regional green innovation level. At the same time, local governments play an important role in regional green innovation practice activities, involving both positive and negative roles. The research herein provides quantitative support for evaluating the effects of technology and finance pilot policies, and provides a reference for the further innovation and promotion of the technology and finance pilot policies.

scholarly journals Resource Allocation Effect of Green Credit Policy: Based on DID Model

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 159
Author(s):  
Guangyou Zhou ◽  
Chen Liu ◽  
Sumei Luo
Keyword(s):  
Resource Allocation ◽  
Economic Development ◽  
Difference Method ◽  
Double Difference ◽  
Control Group ◽  
Credit Policy ◽  
Access To Credit ◽  
Financing Cost ◽  
Development Levels ◽  
The Impact

From the perspective of the policy impact effect, this paper takes green enterprises as the treatment group and polluters as the control group. Firstly, the double difference method (DID) was adopted to study the effect of green credit policy on enterprises from two aspects, namely the amount of loans obtained by enterprises and the financing cost. The study found that in terms of loan volume, the launch of “Green Credit Guidelines” enabled green enterprises to obtain more credit resources than polluters. In terms of financing cost, green credit policy means green enterprises obtain lower financing cost than polluters. The triple difference method is further used to test the impact of green Credit Guidelines on the access to credit resources and financing costs of enterprises. The results show that for enterprises with different property rights, the effect of green credit policy on non-state-owned enterprises is more significant than that of state-owned enterprises. For enterprises in different regions, the policy effect of green credit policy on enterprises in regions with relatively backward economic development levels is more significant than that of enterprises in regions with relatively developed economic development level. From the empirical results, the policy basically realized the original intention of directing credit resources to green enterprises and realized the Pareto improvement of financial resource allocation.

scholarly journals Formal Credit; Policy Impact; Household Income; Difference-Indifferences Method; Panel Data Regression.

2015 ◽  
Vol 22 (02) ◽  
pp. 144-160
Author(s):  
Ho Dinh Phi ◽  
Duc Dong
Keyword(s):  
Panel Data ◽  
Household Income ◽  
Household Survey ◽  
Policy Impact ◽  
Credit Policy ◽  
Difference In Differences ◽  
Rural Credit ◽  
Panel Data Regression ◽  
Data Regression ◽  
Credit Programs

Many studies have been conducted to estimate effects of rural credit programs on household income in both Vietnam and foreign coutries. Some provided positive evidence of such programs’ efficiency while others suggest that not all credit programs improved household income. Responding to the question of whether formal credit affects household income will contribute to directions determined to adjust allocation of resources for agriculture and rural development. In addition to the use of Difference-in-Differences (DD) method in connection with pooled OLS regression, this paper employs panel data from Vietnam Access to Resources Household Survey (VARHS) in the years 2006–2012, and finds that the formal credit does have effects on the rural household income. Additionally, the paper offers three groups of policies for promoting the role and improving efficiency of the formal credit programs on the household income in rural Vietnam.

scholarly journals Does Green Credit Affect the Green Innovation Performance of High-Polluting and Energy-Intensive Enterprises? Evidence from A Quasi-Natural Experiment

2021 ◽  
Author(s):  
Sheng Liu ◽  
RONGXIN XU ◽  
Xiuying Chen
Keyword(s):  
Natural Experiment ◽  
Technology Innovation ◽  
High Energy ◽  
Green Technology ◽  
Theoretical Research ◽  
Financial Policy ◽  
Credit Policy ◽  
Green Innovation ◽  
Industrial Enterprises ◽  
Innovation Output

Abstract Green credit policy is a practical exploration to guide green development through the allocation of financial resources, but there is a gap in the theoretical research on how green financial policy affects enterprise green technology innovation. Taking the green credit policy in 2012 as a quasi-natural experiment, this paper applies the methods of Propensity Score Matching and Difference in Difference (PSM-DID) to investigate the relationship between green credit policy and enterprises' green technology innovation behavior based on Chinese industrial enterprises database and green patent database. The results show that the implementation of "green credit guidelines" policy has significantly improved the green innovation output of high-polluting and high-energy consuming enterprises, which indicates that the incentive effect of green credit policy on enterprises exceeds the inhibition effect and leads to Porter effect. Moreover, the green credit policy has significantly increased the number of non-invention patents rather than invention patents. In addition, the green credit policy has a more significant effect on the innovation output of heavily polluting enterprises in state-owned and weak market power enterprises. Mechanism test shows that green credit policy mainly affects the green innovation output of heavy polluting enterprises by guiding the loan financing cost and R&D investment allocation.

PENGARUH PEMBANGUNAN INFRASTRUKTUR TERHADAP PDRB DI PROVINSI INDONESIA

Wahana ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 15-27
Author(s):  
Suripto Suripto ◽  
Eva Dwi Lestari
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Infrastructure Investment ◽  
Water Infrastructure ◽  
Infrastructure Development ◽  
Road Infrastructure ◽  
Health Infrastructure ◽  
Spatial Coverage ◽  
The Government

Economic growth is one indicator to measure  the success of economic development in a country. Economic development is closely related to infrastructure. Infrastructure development will have an impact on economic growth both directly and indirectly. Therefore, the role of the government in determining infrastructure development policies is very important to increase economic growth in Indonesia. The purpose of this study is to determine the effect of infrastructure on economic growth in Indonesia including road infrastructure, electricity infrastructure, investment, water infrastructure, education infrastructure and health infrastructure in Indonesia in 2015-2017.The analytical tool used in this study is panel data regression with the approach of Fixed Effect Model. The spatial coverage of this study is all provinces in Indonesia, namely 34 provinces, with a series of data from 2015 to 2017 with a total of 102 observations. The data used is secondary data obtained from BPS Indonesia.The results of the study show that (1) the road infrastructure variables have a negative and not significant effect on GDRP. (2) electrical infrastructure variables have a negative and not significant effect on GDRP. (3) investment variables have a positive and significant effect on GDRP. (4) water infrastructure variables have a positive and not significant effect on GDRP. (5) educational infrastructure variables have a positive and not significant effect on GDRP. (6) health infrastructure variables have a positive and significant effect on GDRP. Keywords: development, infrastructure, investment, GDRP, panel data

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