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This paper constructs the money demand function including the variable of electronic payments while adopting the Autoregressive Distributed Lag (ARDL) bounds testing approach to investigate the relationship between electronic payments and money demand in China. The empirical results show that there is the cointegration among the variables in the constructed function with stability, and the e-payment variable is negatively correlated with the demand for money. According to the findings of this paper, in the long run, for every 1 percent increase in the e-payment variable, the demand for M1 will decrease by approximately 0.01 percent. In addition, the money demand function that contains the e-payment variable performs better than the one that does not in the forecast evaluation. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to estimate the energy saving potential in China's paper industry by determining energy intensity under different scenarios. Cointegration model and stability test are applied to formulate the equilibrium equation. Results show that energy price, industry structure, profit margin and technology have significant impact as they are negatively correlated to changes in energy intensity. Three scenarios (BAU (business as usual), intermediate and active) are designed to estimate the future trend of energy intensity in paper industry. In 2010, the energy intensity (energy consumption per unit of value added) was 4 tce/10,000 RMB, and by the scenarios it is expected to considerably decline. According to the BAU (business as usual) scenario, the energy intensity will decrease to 2.56, 1.43 and 0.70 tce/10,000 RMB by 2015, 2020 and 2025, respectively. With respect to the intermediate scenario it is expected to drop further to 0.44 tce/10,000 RMB. Yet by the active scenario, the energy intensity is expected to considerably decline to 0.36 tce/10,000 RMB by 2025. Using the BAU forecast as a baseline, the quantity of energy savings is estimated to be 185.6 billion tce by 2025. Considering this important potential, we also provided some policy suggestions. [Copyright &y& Elsevier]

This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors such as authors, institutions, countries, and literature, and it further reveals the future application trends of this method. [Method/process] Based on 86 journals in the ISLS field that were downloaded from the Web of Science using the QCA method, the social network analysis (SNA) method and the visual analysis tool Gephi are used to analyse the author cooperation network, the research institution cooperation network, the national cooperation network, the cocitation network, the cutting-edge trends, etc., of journal papers. The analysis shows that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated, and the author cooperation network has scale-free characteristics. The application of the QCA method is still dominant in European and American countries, and China, the USA, and Italy all play key roles in the national cooperation network. Finally, the institutional cooperation network has certain small group attributes. [ABSTRACT FROM AUTHOR]

China, situated in the circum-Pacific seismic belt, experiences frequent seismic activity and faces diverse geological conditions, making structural stability of paramount importance, especially under seismic conditions. The majority of current earthquake generation methods do not consider the nonstationary nature of earthquakes. This paper introduces a spectral representation-random function model for generating nonstationary earthquakes, effectively simulating stochastic seismic ground motion. Furthermore, traditional slope stability analysis methods are deterministic and incapable of providing probabilistic assessments of slope instability. Therefore, this paper proposes a unified framework for static and dynamic structural reliability analysis based on the direct probability integration method, quantifying the impact of stochastic seismic ground motion on the dynamic reliability of slope stability. Finally, the proposed methods are applied to an excavation slope in Nanjing, using sliding displacement and safety factors as evaluation criteria to study the reliability of the slope under the influence of stochastic seismic events. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to test the overshooting effects of monetary expansion on prices of agricultural products at farm production, processing and circulation stages in China, and to investigate the heterogeneity of the overshooting mechanisms in these three links. Design/methodology/approach: Empirical results are obtained through the vector error correction model and the overshooting framework proposed by Saghaian et al. (2002b). Specifically, we first apply the Dickey–Fuller generalized least squares (DF-GLS) method to test the stationarity of the key variables, and then use the Johansen's (1991) method to conduct the cointegration test. Finally, the vector error correction model is employed to examine the overshooting hypotheses in the three stages of China's agricultural sector. Findings: Empirical results indicate that overshooting of prices relative to monetary expansion in China's agricultural sector is a common phenomenon, but with significant heterogeneity. Firstly, at the stage of agricultural production, the overshooting degree and restoration rate of material price are greater than those of agricultural products price. Secondly, at the processing stage of agricultural products, both the purchase price of agricultural products and industrial producer price have an overshooting effect, but the overshooting effect of the former is more significant than the latter. Thirdly, at the circulation stage of agricultural products, the overshooting coefficient of the wholesale price index of agricultural products is the most significant, while that of the retail and purchase price of agricultural products is not significant. Originality/value: The paper contributes to proposing a comprehensive framework on testing the overshooting effects for three main stages of agricultural sector in China and empirically investigating the heterogeneity of the overshooting mechanisms in different stages with time series methods. [ABSTRACT FROM AUTHOR]

Power systems with a high proportion of inverter-based sources like photovoltaics require a substantial short-circuit current ratio to ensure strong voltage support capabilities. However, this also increases the system's short-circuit current capacity and levels, which may potentially affect the safe operation of system equipment and current-carrying conductors. To evaluate the operational risks, this paper proposes a quantitative calculation model for the critical integration proportion of grid-connected inverter-interfaced power sources based on short-circuit current over-limit probability. Firstly, according to the verification criterion about short-circuit current during the selection of the switching equipment and conductors in the power system, the short-circuit current over-limit probability evaluation system with five indices is established. Secondly, considering the impact of the increased grid integration proportion of inverter-based power sources on short-circuit currents, an evaluation process for operational risk probabilities is proposed. Based on this, the critical access proportion for inverter-based power source integration in the power grid can be calculated. Finally, the proposed model is used to assess the operational risk probability for a 220 kV system which includes a high proportion of inverter-based power sources in the Anhui area, China. Through the analysis of cumulative probability distribution curves, the critical grid integration proportion interval for the transition from normal to high proportion stages of inverter-based power sources is determined. [ABSTRACT FROM AUTHOR]

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China is a traditional agricultural country, and the integration of rural industries has become an essential policy direction for the current strategy of agricultural modernization in China. The purpose of this study is to evaluate the level of integrated rural industry development in China, identify problems in the development process, and combine analysis of related theories and practices of rural industry integration to propose strategies to enhance the level of integrated rural industry development in China. Hence, this paper, rooted in the integration of rural industries, cross-industry, industry extension, industry agglomeration, and industry penetration, sets up a measurement index system. Using provincial panel data from 2011 to 2020, the paper measures the level of integrated development in rural industries across China and its 31 provinces. Research indicates that during the sample period, the overall level of integrated development in rural industries in various provinces in China has shown an upward trend. Development among the eastern, central, and western regions is highly uneven, but this disparity has been gradually narrowing in recent years. Furthermore, the levels of integrated development in different provinces exhibit significant spatial agglomeration effects. The development level of neighboring regions significantly impacts the province's development status. [ABSTRACT FROM AUTHOR]

The spatial effects of agricultural market integration on industrial agglomeration are an important field of regional economic. This paper collected the data of agricultural market integration and industrial agglomeration in 31 provinces in China from 2010 to 2019, analyzed the spatial effects of the two by constructing a dynamic spatial Dubin model, and explored its long-term and short-term effects of the spatial effects. The results show the following: (1) the primary terms of agricultural market integration were negative and the secondary terms were positive. The impact of agricultural market integration on local industrial agglomeration had a "U-shaped" characteristic. Whether in the short-term or long-term, there was a significant direct effect of "suppression to promotion." (2) The agricultural market integration had a spatial spillover effect on industrial agglomeration in the neighboring areas. This effect had an "inverted U-shaped" characteristic. Whether in the short-term or long-term, there was a prominent spatial spillover effect of "promotion to suppression." (3) For direct effects, the short-term direct effects of agricultural market integration on industrial agglomeration were − 0.0452 and 0.0077, and the long-term direct effects were − 0.2430 and 0.0419. For spatial spillover effects, the short-term spatial spillover effects were 0.0983 and − 0.0179, and the long-term spatial spillover effects were 0.4554 and − 0.0827. The long-term effects were greater than the short-term effects. This paper provides empirical evidence for the effects of agricultural market integration on industrial agglomeration in different regions, and exploring the development of agricultural agglomeration in the long-term. [ABSTRACT FROM AUTHOR]

This paper focuses on the spillover dynamics of shocks originating in China during the last two decades. More specifically, the paper compares the effects of a shock to China's GDP and exchange rate using early 2000s trade patterns with those of two decades later. We use a global vector autoregressive (GVAR) model as it allows to consider trade interactions as well as financial linkages through interest rates, stock prices, and exchange rates. Our results indicate that the shock spillovers from China have become more pronounced over the past two decades. While the world has become more exposed to China's economy, it has become more susceptible to Chinese economic shocks. This paper contributes to the literature by evaluating the dynamics of China's spillover effects and highlights the structural changes in trade between major global trade players. [ABSTRACT FROM AUTHOR]

This paper constructs a two-level data fusion model with the classroom environment monitoring background of colleges and universities. By judging the validity of the data received by each sensor, the model eliminates the influence of neglected monitoring values on fusion accuracy. It uses the adaptive weighted average method to fuse the data of the same type of sensors in each area and then uses the BP neural network to fuse the heterogeneous sensor data in the area. After each region sends the fusion result to the gateway node, the second-level fusion is performed. In the second-level fusion, the error between the actual output result and the expected output of the BP neural network is calculated, and it is used as the basic probability assignment in DS; then the D-S synthesis rule is used for decision-level fusion so as to realize the integration of the college classroom environment. Aiming at the shortcomings of the D-S evidence theory, we improved the algorithm with respect to the distance of evidence and the conflict factor. Through the exploration of the multisource data fusion analysis method, it is found that it plays an important role in early vocal music teaching. The quality of early vocal music-teaching teachers has a particularly important impact on the music level of college students. Schools with preschool education majors are important bases for teacher training in early vocal music teaching. In order to expand the application scope of the concept of multisource data fusion in the field of vocal music teaching in China, it is necessary to change the traditional vocal music teaching mode of existing college teachers and pay attention to the integration of multisource data fusion analysis methods and the reforms of colleges and universities. In this paper, the effectiveness of the two-level fusion model is verified by using two evaluation indicators: the mean absolute percentage error and the correlation coefficient. Then, comparing the calculation results of the improved algorithm and the classical algorithm in this paper, it is proved that the probability accumulation of this algorithm is more obvious and consistent with the expected results, which shows the optimization effect of the improved method. [ABSTRACT FROM AUTHOR]

Green finance has become an important reform force to promote the sustainable development of China's economy. Therefore, it has a great significance for in-depth analysis of the advantages and disadvantages of regional green finance development, to further promote it by clarifying and predicting the regional differences and dynamic evolution trends. Based on this, this paper will select the relevant index from 2001 to 2020 to construct China Green Finance Core Network (CGFCN) in different years by using Space-L method at the first, then analyze its network characteristics and spatial evolution pattern in depth, and finally predict the future development trend of CGFCN by link prediction. The research results show that: firstly, the evolution of CGFCN is mainly divided into three stages: rapid development, stable development and optimal development, and the closeness of CGFCN is constantly improving. Besides, two strong relationship networks are gradually forming, that is Beijing-Tianjin region and the Yangtze River Detla region. Secondly, with the development of green finance, the community division has changed. It is mainly divided into four communities, named the Beijing-Tianjin-Hebei leading community, the eastern provincial community, the Yangtze River Delta community and the central and southern joint community. Different communities will have different integration in different periods. Thirdly, the future development direction of green finance network is mainly Beijing-Tianjin-Hebei region and Yangtze River Delta regions, and their outward radiation are mainly shown in the eastern coastal and central regions, which also have strong development potential. In this regard, it is proposed to coordinate development across provinces to speed up the "urban integration" of green finance services; Establish an efficient community development mechanism and promote the interconnection of green finance markets and infrastructure between different regions; Strengthen the resource flow among regions and coordinate the resource competition of green finance. [ABSTRACT FROM AUTHOR]

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965–2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results. [ABSTRACT FROM AUTHOR]

A significant corridor under the "Belt and Road Initiative" is announced by the government of China for numerous transport and energy projects. China focuses greatly on the sustainability of these projects, in accordance with Green Investment Principles. For this, environmental, social, governance, and technological considerations are taken into account. This paper offers a novel assessment of the impact of green sustainability under BRI and the current emission scenario in Pakistan. The question that needs to be addressed here is whether the projects under Belt and Road Initiative are as environment friendly as they claim. In the first phase of this study, we review theories establishing evidence based on existing literature to determine the influence of Belt and Road on economic development. In the next phase, we use Environment Kuznets Curve and apply estimates from Johansson's Cointegration Test to quantify the present environmental scenario of Pakistan and probable environmental risk portrayed by the China-Pakistan Economic Corridor (CPEC). This paper helps in determining the relationship between carbon emission and three major variables including energy consumption, economic growth, and foreign direct investment (FDI). Cointegration analysis is applied on time series data comprising of a 40 years' period from 1979 to 2019. The paper finds that (i) the belt and road corridors could substantially improve trade, foreign investment, and living conditions for citizens in participating countries; (ii) moreover, this study confirms the presence of one cointegrated equation suggesting the presence of a long term relationship between the CO2 and independent variables and a short run association running from EnC to CO2. The study also proposes a Green BRI Model which formulates a body that devises environmental performance standards, reviews procedures, and ensures that they get implemented on all CPEC projects. The Belt and Road Initiative increases emissions among participating countries. China and corridor economies need to adopt strict policy reforms that increase transparency, expand trade, improve debt sustainability, and mitigate environmental, social, and corruption risks. [ABSTRACT FROM AUTHOR]

In the recent literature, energy efficiency got the attention of scholars due to its discouraging impact on CO2 emissions, which is considered the most prevalent greenhouse gas that human activities produce. Data reports that China is the leading CO2 emitting country across the globe, and still the environmental degradation is in progress. Thus, the current paper empirically investigates the impact of energy efficiency (ENEF), financial inclusion (FD), GDP, export diversification (EXD), and human capital index (HCI) on the environmental degradation of China over the period from 1988 to 2018. This study uses various time-series tests to empirically investigate the determinant of CO2 emissions, including normality tests, unit root tests, and combined cointegration tests. Besides, the long-run coefficients are analyzed via the fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), and the Canonical Cointegrating Regression (CCR) estimators. The empirical findings reveal that all the variables are cointegrated in the long run. However, the coefficient estimate shows that ENEF and HCI significantly promote environmental sustainability. While GDP, FD, and EXD significantly promote environmental degradation by enhancing the CO2 level in the atmosphere. This study recommends practical policy implications based on the empirical findings: energy-efficient products and energy sources could be promoted. [ABSTRACT FROM AUTHOR]

This paper uses cointegrated error-correction modeling to investigate the nature of Granger causality between corruption and foreign direct investment (FDI) in two rapidly emerging economic superpowers; namely, China and India. The results for China and India indicate that short-run Granger causality unidirectionally runs from FDI to corruption without feedback. These empirical findings (along with supporting theoretical arguments) dispute prior correlational-based studies which claim that corruption instigates changes in FDI. However, our results further support significant long-run causality running from corruption to FDI inflows, but only in India (not in China). This finding reinforces theoretical propositions of lower corruption arbitrariness in China as compared to India. Furthermore, short- and long-run causality between corruption and FDI in India appear dynamic in nature and time-sensitive implying some difficulties for policymakers in their fight against corruption. The paper discusses possible underlying reasons for the empirical results and draws several policy and Asian business implications. [ABSTRACT FROM AUTHOR]

Long-run relationships and structural breaks have often been confused so that many investigators ignore the structural breaks in long-run stock price relationships. In this paper, we investigate the long-run relationships among stock prices in BRICS countries in a bivariate framework. We used a non-linear threshold cointegration test, which endogenously incorporates possible regime shift behaviors into the long-run relationships from 2004 to 2018. The Johansen cointegration test, the Gregory and Hansen cointegration test, and the Hatemi-J regime shift cointegration test, which allow for single and double structural breaks, were used. The principal finding of this paper confirms the presence of cointegration among the BRICS stock markets with two endogenous structural breaks. The study confirms that ignoring the presence of structural breaks in long-run series data can produce ambiguous results. It also confirms the absence of cointegration among these stock markets (Brazil and China, India and China, and China and South Africa) after two endogenous structural breaks. These empirical findings support conjecture on more than just the changes in the relationships between the BRICS stock markets. The disintegrated markets suggest the absence of arbitrage activity and vice versa. Thus, disintegrated markets mean that investors can obtain long-term gains through international portfolio diversification. While the benefit of the diversification is very limited in the long run, it is unlikely to be eliminated in practice. Hence, there is a possibility of obtaining an unusual profit in such a market, and consequently the assumptions of market efficiency could also be violated. [ABSTRACT FROM AUTHOR]

This paper examines stock market integration between the five ASEAN countries and both the US and China in turn, over the period from November 2002 to August 2020. The linkages between both aggregate and financial sector stock indices (both weekly and monthly) are analyzed using fractional integration and fractional cointegration methods. Further, recursive cointegration analysis is carried out for the weekly series to study the impact of the 2007–8 global financial crisis and the 2015 China stock market crash on the pattern of stock market co-movement. The main findings are the following. All stock indices exhibit long-range dependence. There is cointegration between the five ASEAN countries and the US but almost none between the former and China, except between Indonesia and China in the case of the financial sector. The 2007–8 global financial crisis and the 2015 Chinese stock market plunge weakened the linkages between the ASEAN five and both China and the US. The implications of these results for market participants and policy makers are discussed. [ABSTRACT FROM AUTHOR]

This paper separates the exchange rate effect of monetary sterilization from the scale effect as a rationale for a modification of the measure of sterilization rate. The Chinese episode for 2002–2012 is characterized by a robust trend both for renminbi to appreciate vis-à-vis the dollar and for net official foreign assets to grow, which relates two of four scenarios that I generally identify for possible sterilization responses to changes in the exchange rate and official net foreign assets. I find that the modified sterilization rate in China exhibits a sort of strong "hawkish bias" in which sterilization is more sensitive to the exchange rate appreciation than to its depreciation, on one hand, and to the growth of net official foreign assets than to its decline, on the other. While there is no econometric evidence for the "hawkish bias" in the long run, the significant evidence exists for the short-run asymmetry of sterilization adjustment to be biased more toward the hawkish side than dovish side. [ABSTRACT FROM AUTHOR]

The paper proposes a novel hybrid method that extends previous work incorporating the fractionally cointegrated vector autoregressive and the permanent-transitory decomposition model. Using the hybrid method, we investigate whether the rapid rise in China's housing prices is a trend or cyclical fluctuation as well as whether there exists a housing price bubble. The findings indicate there exists a fractional cointegration relationship between housing prices and macroeconomic fundamentals in China, and that the fundamental value of housing prices is determined by macroeconomic factors. In particular, the upward trend in China's housing prices has shifted and decelerated since 2012, in line with GDP and money supply. Moreover, we provide evidence of the existence of a housing price bubble in China since 2012, particularly during the 2015–2018 period. We demonstrate that the hybrid model has a superior forecasting performance and decomposes the trend and cycle components more accurately than the conventional methods when estimating a system of possibly fractional cointegration relationship. [ABSTRACT FROM AUTHOR]

Against the backdrop of China's carbon emission reduction targets and the promotion of the construction of a unified domestic market, what kind of carbon emission effect has market integration had in weakening regional barriers and optimizing resource allocation? This paper adopts a two-way fixed effects analysis based on China's provincial panel data from 2003 to 2019. It uses a mediation model to explore the relationship between market integration and carbon emissions. Furthermore, industrial rationalization and upgrade are the basis for examining whether a competitive or cooperative relationship exists between the carbon emission effects generated and promoting market integration between regions. The study finds a negative relationship between market integration and carbon emissions. In addition, there is significant heterogeneity in the effect of market integration on carbon emissions, and the influence effect is mainly in central China; industrial rationalization can play an enhanced role in the process of the negative impact of market integration on carbon emissions, further enhancing the negative contribution of market integration to carbon emissions. However, market integration can weaken its negative impact on carbon emissions with the industrial upgrade, and there may still be invisible barriers between regions in promoting market integration barriers. [ABSTRACT FROM AUTHOR]

In order to analyze the intergenerational income mobility of urban and rural residents, this paper uses big data technology to study the intergenerational income mobility of urban and rural residents in China, constructs a corresponding model, and presents an interval type-2 fuzzy model based on the distributed integration method. The model constructs an initial interval type-2 fuzzy model through a distributed integration strategy and provides an optimization method for the parameters of the interval type-2 fuzzy model based on the least squares method, which is used to ensure the prediction performance of the model. The experimental study verifies that the big data technology can play an important role in the research on the intergenerational income of urban and rural residents in China. [ABSTRACT FROM AUTHOR]

This paper investigates the long-run and short-run impacts of government spending on inflation in three Asian emerging economies of India, China and Indonesia by applying the cointegration and Vector Error Correction Model to time series data from 1970 to 2010. The results confirm a cointegrating causal link between government spending and inflation in the long run in these countries, regardless of their institutional governance differences. In the short run, government spending (as a percentage of GDP) appears to have a negative impact on inflation in China, while a positive impact in Indonesia and India. The implication is that governments of emerging economies should be prudent with their decisions on government spending. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic impacts of financial development, human capital, and economic growth on CO2 emission intensity in China for the period 1978-2015, with a structural breakpoint in 1992, by employing an autoregressive distributed lag (ARDL) approach. The estimations show that there exists a long-run cointegration linkage among the variables, with three main findings. First, financial openness measured by net FDI inflows can significantly reduce CO2 emission intensity in both the short-term and the long-term, whereas the effects of both financial scale and financial efficiency are limited and insignificant. Second, there exists an inverted N-shaped relationship between human capital and CO2 emission intensity: improving human capital first decreases CO2 emission intensity (before 1992), then increases it in the short-run (after 1992), and, finally, lessens it in the long-run. Last, raising per capita income can also significantly lower CO2 emission intensity in the long-run. Accordingly, some policy implications are also discussed. [ABSTRACT FROM AUTHOR]

Since 2015, when China opened up its onshore bond markets more substantially, foreign investors have significantly increased their investments in Chinese local currency bonds. This study aims to examine the effects of foreign participation on Chinese government bond yields. This study adopts a robust least squares model and a cointegration model. (Greater) foreign participation can significantly decrease 10-year Chinese government bond yields. There are almost no studies of the benefits and costs of foreign participation in Chinese bond markets. The conclusion drawn from this study is the first of its kind in the academic literature on the Chinese market, and contributes to knowledge about foreign participation in local currency bond markets. [ABSTRACT FROM AUTHOR]

From 2004 to 2015, the minimum wage's employment effect varied according to the minimum wage level, FDI, per capita gross domestic product, and labor production in 31 Chinese provinces. Regardless of the amount of investment, the minimum wage raise lowered hiring as FDI intake increased. In this research paper, we aim to study different scenarios that can help raise the minimum wage without harming employment. We will evaluate the influence of employment's minimum wage change in China (world's largest emerging market) and the U.S. (the largest developed country) using co-integration regression analysis. The minimum wage system is a basic wage and social security system that the governments have used to interfere directly in labor market wages. The data enumerated and collected is from 2003 to 2016, which is published annually by both governments. Our emphasis is on the overall employment impact, accommodation, and foodservice industry impact. According to the findings, the minimum wage increase has a minor impact on overall employment in China. However, it has a beneficial impact on employment in the U.S. In China and the U.S., minimum wage raise has a significant beneficial influence on employment in the retail and foodservice industries. The impact on the U.S., however, is higher than on China. [ABSTRACT FROM AUTHOR]

Given the continuum of views regarding the impact of trade openness on the growth of economies in our globalised world, this paper investigates the comparative case of the USA and China, two of the world's largest economies and power houses, for the period 1985–2020. We find contradicting growth effects of trade in the US and China, with trade having a mixed or negative effect on the former but a consistently positive effect on the latter, both in the short and long run. We provide some commentary in light of the recent global debates on trade and propose policy recommendations in the context of these countries. [ABSTRACT FROM AUTHOR]

This paper investigates the volatility persistence in sovereign bond yields of India and China during study period of 2010–2018. For that purpose, the researcher has applied the Engle and Lee (in: Engle and Lee (eds) Cointegration, causality, and forecasting: a Festschrift in honour of Clive WJ Granger, Oxford University Press, Oxford, pp 475–497, 1999) C-GARCH model to decompose the volatility of 10-year sovereign bond yields of India and China into permanent and transitory components. The results reveal that permanent conditional volatility shows long memory with long-run component's half-life decay ranges from 91 to 97 days for India and China, respectively. However, the temporary component of volatility much smaller with short-run component's half-life decay ranges from.70 to.75 for India and China, respectively. [ABSTRACT FROM AUTHOR]

With growing regulatory and market pressure to implement green practices, SMEs are facing enormous challenges to simultaneously improve operational and green performances of their supply chains. The paper aims to understand the green practices adopted by Chinese SMEs in the packaging sector in order to assess the impact of these practices in improving the operational performance. Case study-based research methodology is adopted and semi-structured interviews are conducted to collect data from seven SMEs in this study. Both in-case and cross-case analyses are performed to understand the green practices being adopted with the focus on improving the operational performance. The findings of this study indicate that although most SMEs understand the importance of green practices, they have limited knowledge to integrate these practices to improve operational performance. Integration and alignment of green activities with the operational improvement measures are identified as critical factors to develop an efficient green supply chain. [ABSTRACT FROM AUTHOR]

Little attention has been paid to the influence of telecommunications on energy consumption, especially from an empirical perspective in the emerging economies. This paper firstly employs an autoregressive distribution lag bound test to examine the co-integration relationship among our model variables. Then, it mainly follows a partial least squares regression to investigate the long-run effect and an error correction model to explore the short-run impact of telecommunication services on energy intensity in China. Our main conclusions reveal a co-integration relationship among all the variables in our expanded STIRPAT model. Besides, it is also indicated that the energy intensity reduction effect of telecommunication services is statistically significant both in the short and long term. Additionally, the impacts of population, income, industrial structure, energy consumption structure, and energy price on energy intensity are also examined. [ABSTRACT FROM AUTHOR]

This paper made the first attempt to summarize the rules from a regional perspective and use panel data to explore the carbon Kuznets curve (CKC) between e-commerce and carbon dioxide emissions. The impact of online shopping on carbon emission has mixed conclusions. No CKC tests set mainly focuses on the e-commerce sector, which can help this research determine the relationship between e-commerce and carbon emissions. From a macro point of view, we examine both developed and developing regions by testing the CKC hypothesis. We try to explain it by exploring the econometric relationship between e-commerce and CO2 emissions. At first, we attempt to accurately measure the CO2 emissions by carefully distinguishing the carbon emission increments caused by the primary energy resulting from the secondary energy. Then, we use panel data collected from different Chinese cities during 2001–2017. The analyzed variables are stationary at their first differences with the LLC test, IPS test, Fisher-ADF test, Fisher-PP test, CADF, and CIPS unit root tests. The analyzed variables are cointegrated by employing the Pedroni panel cointegration test, the Kao panel cointegration test, and the Westerlund panel cointegration test. Using the DOLS, we also find that increases in trade openness decrease carbon emissions while increases in foreign direct investment (FDI) and market size contribute to the level of emissions. The quadratic-shape CKC hypothesis is supported for China, Eastern China, and Western China, and it is an inverted "U" shape. The cubic-form CKC is supported for Central China, and it is an "N" shape. Our study provides important insights for enacting regional and country-level e-commerce regulations and reducing carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to econometrically investigate the level of financial co-integration of the least developed countries (LDCs) of Asia and Pacific region. In addition, the paper also tested the co-integration of LDCs with the world’s second largest economy “China.” For this, the paper employed the foreign exchange data sets of respective LDCs. It also aimed to assess the dynamic conditional correlation (DCC) between the foreign exchange rates of LDCs and China, and further, examined the past and current level of their co-relational dependence. Design/methodology/approach – The authors created data sets namely LDCs of Asia and Pacific, LDCs of SAARC, LDCs of ASEAN, LDCs of Pacific, LDCs of SAARC and ASEAN, LDCs of ASEAN and Pacific, and LDCs of SAARC and Pacific. In addition, the authors tested the co-integration of these seven groups with China, and thus, making a total of 14 data sets. The analysis was carried out using the Johansen and Gregory-Hansen multivariate co-integration econometric techniques. To assess the DCC, multivariate DCC GARCH model was employed. Findings – It was found that at the intra-regional level, exchange rates of LDCs of SAARC, ASEAN and Pacific were co-integrated and showed the existence of 1-3 co-integrating equations. At inter-regional level SAARC-ASEAN, ASEAN-Pacific and SAARC-Pacific were also co-integrated and showed 1-3 co-integrated equations. However, on the inclusion of China in the study, the degree of co-integration of exchange rate of China with LDCs of SAARC and ASEAN increased, while with Pacific, the result was mixed. Conditional correlation estimated of multivariate DCC GARCH model suggested that except for Afghanistan, there was an upward shift in the correlation dynamics of exchange rates of LDCs with China, post global financial crisis. Practical implications – Asia and Pacific region constituted of 53 countries, of which 13 were LDCs. Enhanced financial integration among LDCs of Asia-Pacific region and also between LDCs and major economies of the region like China will strengthen economic and financial integration efforts in the region. Originality/value – The present paper attempted a comparative assessment of the co-movements of the foreign exchange markets of LDCs, the countries which have remained largely neglected in academic discourses on financial integration. [ABSTRACT FROM AUTHOR]

This paper uses data for China during the period 1982-2010 and tests the effect of FDI inflows on income inequality, which is measured by the urban Gini coefficient. A small-sample cointegration test and autoregressive distributed lag bounds test are used as the cointegration tests. According to them, the variables under consideration are not cointegrated. The GMM estimation results show that income inequality worsens with FDI flows into China. The evidence from China shows a non-linear effect of FDI inflows on income inequality. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between the logarithms of carbon dioxide (CO2) emissions and real Gross Domestic Product (GDP) in China by applying fractional integration and cointegration methods. These are more general than the standard methods based on the dichotomy between stationary and non-stationary series, allow for a much wider variety of dynamic processes, and provide information about the persistence and long-memory properties of the series and thus on whether or not the effects of shocks are long-lived. The univariate results indicate that the two series are highly persistent, their orders of integration being around 2, whilst the cointegration tests (using both standard and fractional techniques) imply that there exists a long-run equilibrium relationship between the two variables in first differences, i.e. their growth rates are linked together in the long run. This suggests the need for environmental policies aimed at reducing emissions during periods of economic growth. [ABSTRACT FROM AUTHOR]

Based on the research of currency crisis pressure index, bank crisis pressure index, and asset bubble crisis pressure index, this paper introduces an external shock pressure index reflecting the impact of global economic changes on economy and synthesizes systemic financial crisis pressure based on the above four pressure indexes; then, all the alternative early warning indicators and the systemic risk pressure index constructed in this paper were tested for Granger causality. We build financial systemic risk pressure indexes, including currency crisis pressure (CCP) banking crisis pressure (BCP) index, bubble crisis pressure (PBP) index, and external shock pressure (ESP) index to predict financial crises. Finally, four indicators that have a significant impact on the systemic financial crisis pressure index were selected, namely, the stock price index change rate, industrial added value growth rate, domestic and foreign real deposit interest rate differential, and foreign direct investment as a percentage of GDP. A dynamic Logit model with lagging binary variables is constructed, and compared with the traditional static Logit line, the actual dynamic fitting effect is better than the static Logit model. The dynamic Logit model is used to predict the early warning status of systemic financial crisis in 2020, and the forecast of various early warning indicators is realized by the ARIMA model. The final prediction results show that the probability of a systemic financial crisis in China in 2020 is extremely low, almost zero. This is in line with the overall improvement in the international economic situation in 2020 and the steady growth of the domestic economy. [ABSTRACT FROM AUTHOR]

This paper employs the threshold cointegration methodology to assess the long- and short-run dynamics of asymmetric adjustment between economic policy uncertainty (EPU) of China-India, China-Japan, China-Korea, India-Japan, India-Korea, and Japan-Korea pairs using monthly EPU data ranging from January 1997 to April 2020. The relationship between the EPU pairs is examined in terms of Engle-Granger and threshold cointegrations. The findings provide evidence of long-run threshold cointegration and that the adjustments towards the long-run equilibrium position are asymmetric in the short run for the China-India and India-Japan EPU pairs in M-TAR specification with nonzero threshold values. Also, the results suggest a unidirectional causal relationship between China-India, China-Japan, and India-Korea EPU pairs in the long and short run using the spectral frequency domain causality approach. However, a bidirectional causal relationship between China-Korea, India-Japan, and Japan-Korea pairs exists in the long and short run. Therefore, the findings provide some clues to economic policymakers within the Asian subregion for possible policy uncertainty synergies and spillovers among the Asian countries. [ABSTRACT FROM AUTHOR]

The purpose behind this paper is to empirically examine the relationship between trade openness and life expectancy for the Chinese economy. Data are collected for the period 1970–2015. Autoregressive Distributed Lag (ARDL) Modeling technique is utilized to find out the presence of long- and short-run relationship between trade openness and life expectancy. The findings indicated a stable long-run positive relationship between trade openness and life expectancy. Government expenditures, number of physicians and human capital growth have also positively and significantly impacted life expectancy. Similarly, growth of employment and number of beds in hospitals have influenced life expectancy negatively. Moreover, in the short run, government expenditures, growth of employment, number of physicians and human capital growth have maintained their relationship with life expectancy both in terms of coefficient signs and significance level while the relationship between trade openness, number of hospital beds and life expectancy is reversed. [ABSTRACT FROM AUTHOR]

No consensus has been reached about whether the Taylor rule performs well in China. Most studies have either ignored the nonstationarity of the variables in the Taylor rule model or assumed a constant cointegrating vector. China is a transition economy, undergoing gradual reform. Consequently, the fixed coefficient cointegration approach is unable to capture the long-run relationship among interest rate, inflation gap, and output gap. Therefore, this paper develops a time-varying coefficient Taylor rule and estimates it using a smooth time-varying cointegrating approach. The results show a time-varying long-run relationship among the variables in the Taylor rule. The coefficient on the inflation gap is significantly less than 1, indicating that the nominal interest rate's response to inflation is inadequate. Moreover, the coefficient on the output gap is significantly greater than 0, implying that the response of the nominal interest rate to the output gap is sensitive. The People's Bank of China should adjust the short-term interest rate should be more flexible especially to changes in inflation. [ABSTRACT FROM AUTHOR]

This paper establishes one comprehensive index system and investigates the coupling coordination between tourism development and economic growth of Beichuan County following the 2008 Wenchuan earthquake, as well as examines the causal relationship. The results of the coupling coordination degree model (CCDM) illustrate that the coordinating level of tourism development and economic growth increases in 2001–2017, with strong fluctuation in 2008. The causal results using unit root test, Cointegration test, and Grange causal test show that tourism can significantly promote economic growth in 2008–2017. The outcomes may be attributed to the disaster shock, macro-policy and government-led reconstruction mode. Lastly, the theoretical and practical implications for policymakers are provided. [ABSTRACT FROM AUTHOR]

China's growing importance to the Australian economy has been well recognized in policy circles but remained relatively untested in formal empirical analysis. This paper examines the reactions of Australian macroeconomic variables to Chinese money growth and inflation over the post-2002 period using VAR estimation, historical decompositions and long-run cointegration models. The consistent impact of Chinese money growth on Australian inflation and on the exchange rate seen in the VAR analysis is supplemented by evidence of cointegrating relationships between the Australian variables and both Chinese money growth and Chinese inflation. [ABSTRACT FROM AUTHOR]

Forecasting CO2 emissions is the bases of making environmental planning and ecological strategy decisions. This paper constructed a multi-sector intertemporal optimization model to forecast the CO2 emission trends of 14 industrial departments in 31 provinces of China from 2012 to 2050. The results indicate that (1) the energy efficiency level of each province will be improved continuously under the influence of technology progress, and CO2 emissions in most provinces will reach the peak during the forecast period. (2) CO2 emissions of metal-manufacturing industries are the highest in all provinces, and the emissions of transportation service industries, construction industries, and other service industries show a trend of gradual increase from west to east. (3) Under the influence of the capital and technology, CO2 emissions caused by transportation service industries in eastern provinces will reach the peak earlier than those in central and western regions. (4) Combined with the industrial structure and the technical input level, the chemical industries in the western provinces have a great potential for emission reduction. Moreover, construction and transportation industries in the eastern and central provinces have a great potential for emission reduction. [ABSTRACT FROM AUTHOR]

In this paper, we explore the link between scientific and technical research and economic growth in China and USA over the sample period 1981-2012 using the extended Cobb-Douglas model with capital per worker and the quantity of scientific and technical journal articles (research publications) per worker. We examine the cointegration relationship and present the short-run and long-run results using the autoregressive distributed lag bounds procedure. Further, we examine the direction of causality between research publications per worker results and economic growth variables using the Toda and Yamamoto (J Econom 66(1-2):225-250, ) procedure. Our results indicate for both countries research publications per worker positively influence the output per worker both in the short-run and the long-run. The causality results for China indicate a bi-directional causality between research publications per worker and output per worker, duly emphasizing the mutually reinforcing effect. In case of USA, we note a unidirectional causation output per worker to research publications per worker indicating that output Granger cause research publications. [ABSTRACT FROM AUTHOR]

This study aims to analysis the influence of economic growth (EG) and energy consumption (EC) on sulfur dioxide emissions (SE) in China. Accordingly, this study explores the link between EG, EC, and SE for 30 provinces in China over the span of 2000e2019. This study also analyzes cross-sectional dependence tests, panel unit root tests, Westerlund panel cointegration tests, Dumitrescu-Hurlin (D-H) causality tests. According to the test results, there is an inverted U-shaped association between EG and SE, and the assumption of the Environmental Kuznets Curve (EKC) is verified. The signs of EG and EC in the fixed effect (FE) and random effect (RE) methods are in line with those in the dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS) and autoregressive distributed lag (ARDL) estimators. Moreover, the results verified that EC can obviously positive impact the SE. To reduce SE in China, government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency. This requires the comprehensive use of policies, regulations, economic incentives, and public participation to promote sustainable development. [ABSTRACT FROM AUTHOR]

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A large amount of carbon dioxide emissions have drawn more and more attention recently. Existing regional research is mainly based on the classification of geographical location, without considering the differences in urbanization. Using panel data of 30 provinces in China during the period of 1997–2014, this paper investigates the impact of population, per capita GDP, energy intensity, urbanization, industry proportion and tertiary industry proportion on CO2 emissions. Taking into account regional differences, 30 provinces in China are divided into four regions according to the features of "urbanization–CO2 emissions." The results show that the impacts of population and per capita GDP on CO2 emissions in the LU–LC region are higher than the other three regions. The energy intensity has positive effect on CO2 emissions in the four regions. The impact of energy intensity on CO2 emissions in HU–HC and HU–LC regions is greater than the other two regions. Meanwhile, the impact of urbanization on CO2 emissions differs across regions. The urbanization has a significant negative effect on CO2 emissions in the HU–LC region, indicating the urbanization increases CO2 emissions. However, the urbanization has a positive effect on CO2 emissions in the LU–HC region, indicating the urbanization increases CO2 emissions in the region. The impact of industry proportion is not statistically significant in all the regions, while the impact of tertiary industry proportion on CO2 emissions is negatively significant in the HU–LC and LU–HC regions, which indicates that the adjustment and upgrading of industrial structure play important roles in the decrease in carbon emissions. [ABSTRACT FROM AUTHOR]

There are conflicting views as to the relationship between a nation’s defense expenditure (DE) and its population’s income inequality (INEQ). DE, always an important part of government budget, can easily crowd out transfer payments, necessary to improve INEQ; however, these payments may also create a demand that may raise the income levels of the lower income earners. Consequently, the relationship between DE and INEQ is an important question. This paper examines the relationship between DE and INEQ in China for the period of 1989–2012. Utilizing basic cointegration and causality tests, our objective is to add to the literature by providing evidence that China’s DE, in fact, do have an impact on INEQ. [ABSTRACT FROM AUTHOR]

The present paper examines the prices co-movement between West Texas crude oil and China's biofuel crops including soya, corn, wheat, cotton and sugar. Specifically, piecewise cointegration model is developed via hybrid neural network approach which can test the structural change of the linkages without prior knowledge of the input data distribution. And then a comparative framework is applied to identify changes in linkages through time and cointegration methodologies and causality tests are employed. Our results indicate that there is no long term co-movement between the oil and the biofuel crops futures pairs. However, our analysis identified that there is uni-directional short run causality between the oil and the biofuel crops futures pairs most of the time, that being said, China's biofuel crops futures prices are often unilaterally led by West Texas crude oil in short run. Furthermore, our findings also indicate that the short run causality changed in different periods. [ABSTRACT FROM AUTHOR]

This paper is an empirical assessment of the government finance and food security nexus in China from 1978 to 2016. Using autoregressive distributed lag for linear and threshold cointegration, the results suggest that China’s government finance and food security have reinforced each other throughout the reform era when a structural break was allowed in the model. However, the strength of cointegration and Granger causality in the government-led food security link is stronger, hence supporting the state interventionist view that a strong state has played a dominant role in fulfilling national food security in China. China’s government finance and food security changes indicate food sector reform probabilities under fiscal constraint, as regime-switching indicators have delineated the Chinese government’s difficult fiscal periods and the main reforms in the food sector. In practice, this result implies that further policy reforms can be effective for China’s future food security. [ABSTRACT FROM AUTHOR]

In 2014, the IMF reported that China became the largest economy in the world according to Purchasing Power Parity rates. This study aims to explain the Chinese economic miracle. It focuses on frequently suggested factors influencing China’s real gross domestic product (GDP), such as export promotion, exchange rate policy, and foreign direct investment (FDI). The paper employs the Bounds test of the autoregressive distributed lag (ARDL) model to test for cointegration. Once cointegration is established, Granger Causality is investigated using the vector autoregressive model and the Toda and Yamamoto (1995) method. Two different combinations of the real macroeconomic variables exports, exchange rate, imports, and FDI were employed to examine Granger causal relationships. All explanatory variables, except for the exchange rate, were found to have plausible relationships with GDP. The exchange rate and GDP relationship was unexpected; a Renminbi appreciation was associated with an increase in GDP. To investigate this paradox, a third ARDL model was estimated with exports as the dependent variable and the exchange rate, world GDP, and FDI as the independent variables. In this model, we found evidence of cointegration and a plausible relationship between real exports and the real exchange rate. Exchange rate devaluation increased exports and thus indirectly increased GDP. Such findings help to resolve the unexpected results. Nonetheless, according to the Granger causality tests the established statistical evidence is rather weak. We found that both the exchange rate and FDI are no longer strong drivers of economic growth in China. [ABSTRACT FROM AUTHOR]