scholarly journals Does Financial Excess Support Land Urbanization—An Empirical Study of Cities in China

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 635
Author(s):  
Zhenghui Li ◽  
Fanqi Zou ◽  
Yong Tan ◽  
Jinhui Zhu
Keyword(s):  
Financial Support ◽  
Threshold Value ◽  
Threshold Effect ◽  
Promoting Effect ◽  
Financial Efficiency ◽  
Central Regions ◽  
Provincial Capital ◽  
Moderate Range ◽  
The Impact ◽  
Land Urbanization

Most countries have experienced land urbanization, which is indispensable for financial support, especially for their financing function achievement through land appreciation and other channels in the urbanization process. By using 34 provincial capital (sub-provinces) cities in China as the sample, this paper studies the impact of finance on land urbanization construction based on the panel data from 2003 to 2018 under a differential GMM method; besides, the causes of excessive financial support and results generated on different regions are reported. Moreover, a moderate range of financial support for land urbanization is found under the influence of land finance. We obtain the following results: first, there is excessive financial support for land urbanization with regional differences exhibited; for instance, the eastern and central regions have an excessive financial support but the western region does not. Second, land urbanization with an excessive financial support correlates with financial efficiency, while the relatively large financial efficiency leads to the waste of a large number of financial resources. Third, financial support has a single and significant threshold effect on land urbanization construction, and finance has a promoting effect when land finance is less than the threshold value; otherwise, it has an inhibiting effect.

scholarly journals Is there a moderate range of impact of financialization on corporate R&D?

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253380
Author(s):  
Zhenghui Li ◽  
Yan Wang
Keyword(s):  
Research And Development ◽  
Threshold Effect ◽  
Real Economy ◽  
Promoting Effect ◽  
Dynamic Relationship ◽  
High Level ◽  
Moderate Range ◽  
Threshold Regression Model ◽  
The Impact ◽  
Positive Effect

How to promote corporate research and development is a particularly important issue under the background of the economy being diverted out of the real economy. By selecting samples of 1221 Chinese A-share non-financial listed companies from 2010 to 2019, this paper examines the impact of financialization on research and development through the panel threshold regression model. Then, the moderate range of the impact of financialization on corporate research and development is measured, as well as their heterogeneity is also analyzed. The research shows the following results: first, there is a dynamic relationship and moderate range between financialization and corporate research and development. Financialization has a positive effect on corporate research and development when the level of financialization exceeds 0.4748. Secondly, from further heterogeneous research, financialization has a threshold effect on research and development among enterprises with a high level of research and development. In addition, there is a promoting effect on corporate research and development only when their financialization level exceeds 0.0097 in enterprises with a high level of research and development. Therefore, in order to promote corporate research and development, financialization of non-financial enterprises should make adjustment and regulation according to the action and direction of moderate range.

scholarly journals Threshold Effect of High-Tech Industrial Scale on Green Development—Evidence from Yangtze River Economic Belt

2019 ◽  
Vol 11 (5) ◽  
pp. 1432 ◽  
Author(s):  
Yanhong Liu ◽  
Xinjian Huang ◽  
Weiliang Chen
Keyword(s):  
Yangtze River ◽  
Positive Impact ◽  
Empirical Test ◽  
Threshold Value ◽  
Threshold Effect ◽  
Industrial Scale ◽  
High Tech ◽  
The Yangtze River ◽  
Promoting Effect ◽  
Green Development

Based on the panel data of 11 regions in the Yangtze River Economic Belt from 1998 to 2016, we tested and analyzed the effects of high-tech industrial expansion on green development. For these regions in the Yangtze River Economic Belt, we wanted to investigate the potential linear relationship between the scale of high-tech industry and green development or the possible threshold effect. We wanted to determine if this relationship is different in various regions of the Yangtze River Economic Belt. According to the empirical test, we found that: (1) for the entire Yangtze River Economic Belt region, the influence of high-tech industrial scale on green development doubled the threshold effect, and a marginal efficiency diminishing effect existed with the further increase in scale; (2) due to the differences among the regions, the threshold effect was different in different regions, with a double threshold effect in the lower reaches, a single threshold effect in the middle reaches, and no threshold effect in the upper reaches; and (3) regarding the high-tech industrial scale, the downstream areas were too large to weaken its promoting effect on green development. In the middle reaches, the positive impact on green development was still increasing, and the high-tech industrial scale should be further expanded. However, in the upstream areas, high-tech industrial scales did not reach the threshold value and the relationship between the high-tech industrial scale and green development was linear. Therefore, local high-tech industries should be cultivated and developed.

scholarly journals Do City Size and Population Density Influence Regional Innovation Output Evidence from China?

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Cai Shukai ◽  
Wang Haochen ◽  
Zhou Xiaohong
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Positive Impact ◽  
Threshold Value ◽  
Threshold Effect ◽  
The Other ◽  
City Size ◽  
Regional Innovation ◽  
Innovation Output ◽  
The Impact

This paper proposed a substantial gap to a large-scale population density and city size on regional innovation output. To measure the impact of population density and city size on regional innovation output, this study employs the threshold effect model with panel data of 230 prefectures and cities from 2007 to 2016. Based on the econometric analysis, the results exhibit a positive and significant relationship between population density, city size, and innovation output. This correlation suggests that when one factor increases, the other increases in the parallel direction and vice versa. Moreover, when the city size expands the threshold value of 2.934 percent, the innovation promotes and increases the effects of urban-scale expansion. On the other hand, for medium- and low-density cities, the increase of urban population density has a significant and positive impact on urban innovation output. However, for high-density cities, the increase of population density has no significant impact on innovation output.

scholarly journals Does Innovation Efficiency Suppress the Ecological Footprint? Empirical Evidence from 280 Chinese Cities

2020 ◽  
Vol 17 (18) ◽  
pp. 6826 ◽  
Author(s):  
Haiqian Ke ◽  
Wenyi Yang ◽  
Xiaoyang Liu ◽  
Fei Fan
Keyword(s):  
Economic Development ◽  
Ecological Footprint ◽  
Industrial Structure ◽  
Threshold Value ◽  
Threshold Effect ◽  
Mediating Effect ◽  
Energy Structure ◽  
Central Regions ◽  
Development Levels ◽  
Threshold Regression Model

Innovation is an important motivating force for regional sustainable development. This study measures the innovation efficiency of 280 cities in China from 2014–2018 using the super-efficiency slack-based measure and it also analyzes its impact on the ecological footprint using the generalized spatial two-stage least squares (GS2SLS) method and uses the threshold regression model to explore the threshold effect of innovation efficiency on the ecological footprint at different economic development levels. We find the corresponding transmission mechanism by using a mediating effect model. The major findings are as follows. First, we find an inverse U-shaped relationship between innovation efficiency and the ecological footprint for cities across China as well as in the eastern and central regions. That is, innovation efficiency promotes then suppresses the ecological footprint. Conversely, in western and northeastern China, improvements in innovation efficiency still raise the ecological footprint. Second, for the entire country, as economic development increases from below one threshold value (4.4928) to above another (4.8245), the elasticity coefficient of innovation efficiency to the ecological footprint changes from −0.0067 to −0.0313. This indicates that the ability of innovation efficiency improvements to reduce the ecological footprint is gradually enhanced with increased economic development. Finally, the industrial structure, the energy structure, and energy efficiency mediate the impacts of innovation efficiency on the ecological footprint.

Threshold effects of exchange rate depreciation and money growth on inflation

2014 ◽  
Vol 41 (2) ◽  
pp. 196-215 ◽  
Author(s):  
Rizki E. Wimanda
Keyword(s):  
Exchange Rate ◽  
Threshold Model ◽  
Threshold Value ◽  
Threshold Effect ◽  
Threshold Effects ◽  
Money Growth ◽  
Content Type ◽  
Significant Difference ◽  
The Impact ◽  
Exchange Rate Depreciation

Purpose – This paper aims to investigate the impact of exchange rate depreciation and money growth to the consumer price index (CPI) inflation in Indonesia. Design/methodology/approach – Using threshold model applied to Phillips curve equation. Findings – Using monthly data from 1980:1 to 2008:12, the econometric evidence shows that there are indeed threshold effects of money growth on inflation, but no threshold effect of exchange rate depreciation on inflation. Even though the threshold value for exchange rate depreciation is found at 8.4 percent, the F-test suggests that there is no significant difference between the coefficient below and that above the threshold value. While two threshold values are found for money growth, i.e. 7.1 and 9.8 percent, and they are statistically different. The impact on inflation is high when money grows by up to 7.1 percent, it is moderate when money grows by 7.1-9.8 percent, and it is low when money grows by above 9.8 percent. Research limitations/implications – This research is using methodology proposed by Hansen which the threshold is based on the minimum SSR. The value of SSR will differ from one model to one model. For example, model using quarterly data will give the different result from that using monthly or yearly data. Also, when the author uses the new data, the result could be different. Practical implications – Even though inflation targeting framework has been adopted by Bank Indonesia (BI) since 2005, BI should not disregard the monetary aggregate variable, especially M1. This is because the growth of money is still matter to influence inflation in the short run. The impact on inflation is found to be larger than the impact of exchange rate depreciation when it is below a certain threshold value. Originality/value – This is the first paper that evaluates the threshold effect of exchange rate and money growth in emerging country, especially in Indonesia.

scholarly journals The Threshold Effect of FDI on Regional Innovation Capability— From the Perspective of Intellectual Property Protection

2021 ◽  
Vol 275 ◽  
pp. 03023
Author(s):  
Wencong Li
Keyword(s):  
Intellectual Property ◽  
Direct Investment ◽  
Threshold Value ◽  
Threshold Effect ◽  
Intellectual Property Protection ◽  
Innovation Capability ◽  
Regional Innovation ◽  
Threshold Regression Model ◽  
The Impact ◽  
The Relationship

As one of the important channels of technology spillover, foreign direct investment (FDI) has a significant impact on regional innovation capability, which is restricted by the intensity of intellectual property protection. In order to explore the relationship between these three factors, this paper constructs a nonlinear threshold regression model based on China’s provincial panel data from 2009 to 2018, and empirically analyzes the threshold effect of FDI on regional innovation capability with the intensity of intellectual property protection as the threshold variable. The results show that the impact of FDI on regional innovation capability has a significant single threshold effect of intellectual property protection intensity. Only when the intensity of intellectual property protection remains near the threshold value, can FDI promote regional innovation capability to the greatest extent.

scholarly journals Research on the Impact of Financial Development on TFP——DEA-Malmquist Index and Hansen Threshold Model Based on Panel Data of Shandong Province, China

2020 ◽  
Vol 4 (2) ◽  
pp. 71
Author(s):  
Wang Fushuai ◽  
Xi Ruichao ◽  
Cai Wenxia
Keyword(s):  
Growth Rate ◽  
Financial Development ◽  
Financial Institutions ◽  
Threshold Model ◽  
Malmquist Index ◽  
Threshold Value ◽  
Threshold Effect ◽  
Scale Efficiency ◽  
Tfp Growth ◽  
The Impact

Shandong’s TFP growth is higher than Chinese average, but the growth rate has slowed in recent years, appearing the phenomenon that the growth momentum of Shandong’s TFP is insufficient. Using DEA-Malmquist Index to measure Shandong’s TFP growth rate, empirical research from the perspective of financial development finds that financial scale, efficiency of financial institutions, fiscal intervention, and scale of foreign capital utilization have significant nonlinear effects on the growth of TFP. Furtherly, through threshold analysis, the efficiency of financial institutions has a significant threshold effect on TFP growth. Financial scale and fiscal intervention are the main core variables that affect the growth of TFP under the threshold effect, and they have the same effect direction on TFP before and after the threshold value. However, the effect intensity of these two core variables on TFP is different.

scholarly journals DAMPAK DEPRESIASI NILAI TUKAR DAN PERTUMBUHAN UANG BEREDAR TERHADAP INFLASI: APLIKASI THRESHOLD MODEL

2011 ◽  
Vol 13 (4) ◽  
Author(s):  
Rizki E. Wimanda
Keyword(s):  
Exchange Rate ◽  
Threshold Model ◽  
Threshold Value ◽  
Threshold Effect ◽  
Jel Classification ◽  
Money Growth ◽  
Significant Difference ◽  
Econometric Evidence ◽  
The Impact ◽  
Exchange Rate Depreciation

This paper investigates the impact of exchange rate depreciation and money growth to the CPI inflation in Indonesia. Using monthly data from 1980:1 to 2008:12, our econometric evidence shows that there are indeed threshold effects of money growth on inflation, but no threshold effectof exchange rate depreciation on inflation. Even though the threshold value for exchange rate depreciation is found at 8.4%, the F-test suggests that there is no significant difference between the coefficient below and that above the threshold value. While, two threshold values are found for money growth, i.e. 7.1% and 9.8%, and they are statistically different. The impact on inflation is high when money grows by up to 7.1%, it is moderate when money grows by 7.1% to 9.8%, and it is low when money grows by above 9.8%.JEL Classification: C22; E31; E51.Keywords: Inflation, Threshold Effect; Indonesia

scholarly journals Threshold Effect of the Government Intervention in the Relationship Between Business Cycle and Population Health: Evidence From China

2021 ◽  
Vol 9 ◽  
Author(s):  
Kuang-Cheng Chai ◽  
Yang Yang ◽  
Zhen-Xin Cui ◽  
Yang-Lu Ou ◽  
Ke-Chiun Chang
Keyword(s):  
Business Cycle ◽  
Population Health ◽  
Government Intervention ◽  
Threshold Value ◽  
Threshold Effect ◽  
Chinese Government ◽  
The Business Cycle ◽  
The Government ◽  
The Impact ◽  
The Relationship

China is an emerging country, and government intervention is always considered as an important part of the solutions when people facing challenges in China. Under the impact of the coronavirus disease 2019 (COVID-19) epidemic and the global economic downturn, the Chinese government quickly brought the epidemic under control and restored the positive economic growth through strong intervention. Based on the panel data of provincial level in China and the government intervention as the threshold variable, this paper empirically analyzed the non-linear effect of business cycle on population health by using the panel threshold regression model. The empirical results show that the impact of the business cycle on population health is significantly negative, and government intervention has a single threshold effect on the relationship between business cycle and population health. When the government intervention is below the threshold value, the business cycle has a significant negative effect on the improvement of the population health level; when the level of government intervention exceeds the threshold value, the relationship between business cycle and population health becomes significantly positive. To some extent, the conclusions of this paper can guide the formulation and revision of government health policy and help to adjust the direction and intensity of government intervention. The Chinese government and other governments of emerging countries should do more to harness the power of state intervention in their response to the business cycle.

AN EMPIRICAL STUDY ON THE IMPACT OF CHINA’S OFDI ON THE INDUSTRIAL STRUCTURE UPGRADING OF COUNTRIES ALONG THE BELT AND ROAD AND THE THRESHOLD EFFECT OF INFRASTRUCTURE LEVELS

2021 ◽  
pp. 1-41
Author(s):  
HUI WANG ◽  
XIN ZHONG
Keyword(s):  
Industrial Structure ◽  
Threshold Effect ◽  
Belt And Road Initiative ◽  
Promoting Effect ◽  
Promotion Effect ◽  
Central Eastern Europe ◽  
Belt And Road ◽  
The Impact ◽  
The Belt And Road ◽  
Industrial Structure Upgrading

This paper empirically investigates the impact of China’s OFDI on the industrial structure upgrading of countries along the Belt and Road (B&R) and examines the threshold effect of the infrastructure levels on that impact based on the panel data of 52 B&R countries from 2006 to 2017. The results show that China’s OFDI can significantly promote the industrial structure upgrading of B&R countries and that the Belt and Road initiative implementation can help to strengthen the promoting effects of China’s OFDI in the comprehensive FGLS, the Diff-GMM and the System GMM estimation. Moreover, China’s technology transfer OFDI has the greatest promotion effect, followed by capital transfer OFDI; labor transfer OFDI has the least promotion effect. China’s OFDI plays a larger role in promoting the industrial structure upgrading of Central Asia and South Asia countries, followed by ASEAN and CIS countries and it plays a smaller role in West Asia and Central-Eastern Europe countries. There is a threshold effect of the B&R countries’ infrastructure level. When the transportation infrastructure, energy infrastructure, communication infrastructure and overall infrastructure levels exceed the corresponding thresholds, the promoting effect of China’s OFDI will be further enhanced in the comprehensive FGLS estimation. Our study proposes that under the Belt and Road initiative, to improve the infrastructure level of the B&R countries, and to increase the effectiveness of China’s OFDI in promoting the industrial structure upgrading of the B&R countries, China should further strengthen international cooperation, expand outward investment, and strengthen the infrastructure connectivity construction with B&R countries.

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