In the context of accelerating economic transformation and upgrading, and comprehensively promoting the construction of digital China and ecological civilization in China, this paper uses text mining and OLS to quantitatively study the relationship between fiscal decentralization, enterprise digital transformation and green innovation in 31 provinces from 2011 to 2021. This study finds that fiscal decentralization will promote enterprise green innovation and digital transformation, and that digital transformation has a partial mediating effect between fiscal decentralization and enterprise green innovation. Furthermore, this expansive study finds that fiscal decentralization has a positive role in promoting the green innovation of heterogeneous enterprises and enterprises in different regions, among which its promotion effect on state-owned enterprises is higher than that of private enterprises, and its promotion effect on enterprises in the central and western regions is higher than that of enterprises in the eastern region. Moreover, an inverted U-shaped relationship exists between fiscal decentralization and the green innovation of enterprise. In addition, financing constraints have a masking effect between fiscal decentralization and green innovation in enterprise and green innovation significantly promotes enterprise environmental, social and governance (ESG) development.
The green transformation of the manufacturing industry is related to the low-carbon and green development of the economy. The study explored the impact mechanism of the implementation of green finance policy on the green transformation of China’s manufacturing industry from 2013 to 2021 from three aspects of capital formation and incentive, credit catalysis, integration and decentralization, and conducted a quasi-natural experiment using difference-in-difference (DID) model. Research finds that: (1) The implementation of green finance significantly promotes the green transformation of China’s manufacturing industry and has good sustainability. The mechanisms of fund formation and orientation, credit catalysis, integration and decentralization are the primary mechanism of green finance to promote the green transformation of the manufacturing industry, and the implementation effect of green finance has apparent heterogeneity; (2) The promoting effect of green finance on the green transformation of the manufacturing industry is solely vast in state-owned industries however now not enormous in non-state-owned industries; (3) The influence of green finance on the green transformation efficiency of manufacturing industry with a better information environment is more significant than manufacturing industry with a worse information environment; (4) Faced with the pressure of investing in green industries, the coping strategies adopted by enterprises in different industries are quite different. The promoting effect of green finance on the green transformation of the manufacturing industry is significant in low-competition industries but insignificant in high-competition industries. This study has enriched the research on the effect of green finance policies, explored solutions based on quasi-nature, and provided policy references for the green transformation of the manufacturing industry.
Our investigation strives to unearth the best portfolio hedging strategy for the G7 stock indices through Bitcoin and gold using daily data relevant to the period 2 January 2016 to 5 January 2023. This study uses the DVECH-GARCH model to model dynamic correlation and then compute optimal hedge ratios and hedging effectiveness. The empirical findings show that Bitcoin and gold were rather effective hedge assets before COVID-19 and diversifiers during the pandemic and Russia–Ukraine war. From hedging effectiveness perspectives, gold and Bitcoin are safe-haven assets, and the investment risk of G7 stock indices could be hedged by taking a short position during thepandemic period and war except for the pair Nikkei/Gold. Additionally, gold beats Bitcoin in terms of hedging efficiency. We thus demonstrate the central role of Bitcoin and gold as financial market participants, particularly during market turmoil and downward movements. Our findings can be of interest to investors, regulators, and governments to take into consideration the role of Bitcoin in financial markets.
This study employs a non-linear framework to investigate the impacts of central bank digital currency (CBDC) news on the financial and cryptocurrency markets. The time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005) is estimated based on weekly data from the first week of January 2015 to the last week of December 2021. The vector of endogenous variables in the VAR estimation contains the Central Bank Digital Currency uncertainty index (CBDCU), cryptocurrency policy uncertainty index, S&P 500 index, VIX, and Bitcoin price. The TVP-VAR model’s time-varying responses demonstrated that the reactions of the cryptocurrency market to central bank digital currency announcements vary remarkably over time. The impacts of the CBDC shocks on the financial market have been increasingly visible during the COVID-19 pandemic. According to the time-varying forecast error decompositions, CBDCU and VIX shocks have accounted for most of the variance in cryptocurrency uncertainty and Bitcoin return shocks, notably during the COVID-19 period.
Purpose This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations. Design/methodology/approach The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets. Findings The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020. Practical implications Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets.
With the development of ecological economics, energy-saving green energy chain management has been a wide concern of academia and industries. However, the relatively high cost of green investment makes manufacturers face the problem of financial constraints. On this basis, because the green level information of products is proprietary to manufacturers, manufacturers will lie about the green level of products in order to improve their profits out of the principle of profit maximization. As a result, banks cannot obtain the true green level of products, reducing the benefits of the green energy-efficient supply chain system and making the market of green products volatile. In view of this, blockchain technology is introduced in this paper to improve customer’s product green level sensitivity and obtain lower green credit interest rates from banks. In this paper, a green supply chain financing model based on blockchain technology was constructed under the condition of green information misreporting, and it is compared with the benchmark without blockchain technology. Research shows that the adoption of blockchain can achieve Pareto improvement of green supply chain members. In addition, manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. We compared the profits of green manufacturers with those of retailers and the total emissions of manufacturers. The results show that: (1) When the financing intensity exceeds a certain value, there is an optimal coverage of green financing to ensure that the profit target of manufacturers, the profit target of retailers and the emission reduction target are achieved simultaneously. (2) The adoption of blockchain can achieve Pareto improvement of green energy supply chain members. The actual data of green transformation of Jinyuan New Technology Company were cited. Through calculation, it was found that green transformation can reduce the emissions of enterprises. When the financing intensity is in a certain range, the profits of manufacturers and retailers can be maximized, and the emission reduction degree is the highest. Thus, the practicability and reliability of this model were proved. (3) Manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. The research results of this paper provide solutions for enterprises with limited funds for green transformation and provide a theoretical basis for the government to formulate emission reduction incentive mechanism.
Provash Kumer Sarker, Chi Keung Marco Lau, Ashis Kumar Pradhan
This paper investigates the asymmetric effects of climate policy uncertainty (CPU) and the global price of energy index (GPEI) on Bitcoin prices. It applies the nonlinear ARDL method and the Granger causality test to examine how changes in climate policy uncertainty and energy prices influence Bitcoin prices. Using the monthly data of CPU, GPEI, and BTC from 2013M10–2021M12, the findings show that CPU's increases and GPEI's decreases positively affect BTC in the short term. Specifically, CPU and GPEI's increase and decrease show significantly higher effects on BTC in the long term. The causality result shows bidirectional causality between BTC and CPU's increases/decreases, while unidirectional causality runs from GPEI's increases/decreases to BTC. These findings suggest that Bitcoin investors should be aware of the risks associated with climate policy uncertainty and fluctuations in energy prices, as these factors can significantly asymmetrically impact Bitcoin prices.
Nguyễn Thị Thanh Huyền, Nguyen Hong Yen, Lê Thanh Hà
By identifying the connectedness of seven indicators from January 1, 2019, to June 13, 2022, we choose an extended joint connectedness approach to a vector autoregression model with time-varying parameter (TVP-VAR) to analyze interlinkages between Crypto Volatility (CV) and Energy Volatility (EV). Our findings show that the COVID-19 outbreak seems to have an impact on the dynamic connectedness of the whole system, which peaks at about 60% toward the end of 2019. According to net total directional connectedness over a quantile, throughout the 2020–2022 timeframe, natural gas and crude oil are net shock transmitters, while the CV, clean energy, solar energy, and green bonds consistently receive all other indicators. Specifically, pairwise connectedness indicates that the CV appears to be a net transmitter of shocks to all energy indicators before the COVID-19 outbreak but acts as a net receiver of shocks from clean energy, wind energy, and green bonds in late 2020. The CV mostly has spillover effects on green bonds. The primary net transmitter of shocks to the Crypto market is crude oil. Our findings are critical in helping investors and authorities design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty.
Sofia Karagiannopoulou, Konstantina Ragazou, Ioannis Passas, Alexandros Garefalakis · 5 authors
This study aimed to investigate the interactions between Bitcoin to euro, gold, and STOXX50 during the period of COVID-19. First, a bibliometric analysis based on the R package was applied to highlight the research trends in the field during the period of the COVID-19 pandemic. While investigating the effects of the pandemic on Bitcoin, the number of cases of COVID-19 was used as a proxy. Using daily data for the period 1 March 2020 to 3 March 2020 and based on a vector autoregressive model, impulse response, and variance decomposition were utilized to analyze the dynamic relationships among the variables. The results revealed that the COVID-19 cases and gold hurt the exchange rate of Bitcoin to euro, while there was great volatility regarding the response of Bitcoin to a shock of STOXX50. The Granger causality test was constructed to investigate the relationships among the variables. The results show the presence of unidirectional causality running from new cases to STOXX50 and from STOXX50 to gold. This study contributes to the existing scholarly research into the dynamic relationships that appeared among Bitcoin, gold, and STOXX50 in a period of great uncertainty. Finally, the findings have significant implications for investors, who are interested in diversifying their portfolios.
In this article, the MGARCH-DCC model is utilised to compare the usefulness of Bitcoin, gold, and crude oil as a hedge and safe haven for the US Islamic stock index. We utilised daily data from August 2014 to April 2022, which covers the most recent COVID-19 epidemic and the Russia-Ukraine conflict. We find the dynamic correlation between Bitcoin and the US Islamic stock index to be low and often negative during major economic and political events, showing that Bitcoin is a safe haven and hedging instrument, especially during the pandemic period. However, we find that Bitcoin is very volatile, limiting its use as a safe haven and hedging instrument compared to gold. Gold is more stable and negatively correlated with the US Islamic stock index, making it more appropriate as a diversifier and hedging instrument. Adding gold to the US Islamic stock index portfolio reduces the portfolio’s risk.
Abstract Carbon dioxide (CO2) emissions primarily contribute to global warming and climate change. The immediate source of CO2 emissions is burning fossil fuels like petrol, diesel, natural gas and coal, accounting for 78% of total emissions. CO2 emissions have risen since the late 1800s, reaching a record high of 33.1 billion tons in 2019. The paper proposes a Blockchain and IoT-based framework to track and trade carbon credits, aiming to reduce carbon dioxide emissions and mitigate their impact on global warming and climate change. We consider electrical energy as one use case for carbon emission and credit trading. The framework will monitor the energy usage of each entity, recording real time carbon emissions in a tamperproof blockchain ledger. Each entity will receive carbon credits based on the recorded emissions, which can then be traded on a blockchain exchange. This will enable entities with higher emissions to offset their emissions by purchasing credits from entities with lower emissions. The blockchain ledger ensures the authenticity and transparency of the carbon emissions data, promoting a secure and efficient solution for reducing carbon emissions. The paper also outlines a reward and penalty mechanism for consumers, encouraging them to reduce their carbon footprint and contribute to a more sustainable future. The paper discusses the blockchain and IoT-based carbon credit exchange architecture, including algorithms for estimating energy consumption, carbon emissions, reward, and penalty. The paper concludes with a proof of concept implementation using the Ethereum platform and a performance evaluation of the algorithms. The paper proposes a comprehensive solution for reducing carbon emissions and mitigating their environmental impact, leveraging the strengths of blockchain and IoT technologies.
The global current situation continues to be turbulent. International crises like the Covid-19 epidemic and the continuing Russian-Ukrainian war have thrown the global economy for a loop. As a result, global economic policy uncertainty has spiked due to the resulting spike in energy prices and economic disruptions. During the outbreak of Covid-19, prices of bitcoin (BTC) have moved higher, but its hedging effect is weakening. Also, combined with rising global inflation expectations and the constant rate hikes by central banks against inflation, bitcoin's hedging effectiveness is waning due to its strong correlation with equities. Furthermore, with the outbreak of the Russian-Ukrainian war, the price of gold continued to rise, and the relationship between gold and the global financial market decreased, confirming gold's diversification ability in a crisis. Simultaneously, the link between gold and bitcoin has weakened marginally. Ultimately, preliminary evidence suggests that gold and bitcoin can be used as complements, rather than substitutes, for diversification purposes during a crisis. This article will construct a portfolio about bitcoin and gold, and examine how individual gold and bitcoin and this portfolio performed as hedging assets throughout the Covid-19 pandemic and the Russian-Ukrainian war.
Digital finance development has an important role in promoting economic transformation and has become a new engine leading the development of the real economy, while green innovation is an important goal of the current economic transformation to a green and sustainable one. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2018, this paper finds that digital finance has a significant promoting effect on the green innovation of new energy enterprises through panel data fixed effects regression model. Furthermore, through sub-sample regression, it is found that the promotion effect of digital finance on new energy enterprises is heterogeneous, and the promotion effect is more significant for state-owned enterprises and enterprises with more decentralized power. The above findings of this paper have important implications for the current economic transformation in China.
Bu çalışmada, 2017M1-2022M1 dönemleri arasındaki veriler kullanılarak Bitcoin (BTC) ile Karbon Emisyonu (CO2) arasındaki ilişki incelenmiştir. Son zamanlarda yapılan çalışmalara istinaden kripto para ve enerji piyasalarının spekülatif ve kırılgan yapıya sahip olduğu ve bundan dolayı değişkenlerin doğrusal olmayan bir forma sahip olabileceği konusuna dikkat çekildiği gözlenmektedir. Dolayısıyla bu bilgiler çerçevesinde çalışmada öncelikle Luukkonen vd. (1988), Harvey vd. (2008) doğrusallık testi ve Kapetanios vd. (2003) doğrusal olmayan birim kök testi ile değişkenlerin doğrusallık sınaması yapılmaktadır. Akabinde değişkenlerin doğrusal olmayan forma sahip olduğu tespit edildiği için çalışmada Kapetanios vd. (2006) Doğrusal Olmayan Eşbütünleşme analizi kullanılmaktadır. Kapetanios vd. (2006) testi bulgularına göre BTC ile CO2 arasında uzun dönemde doğrusal olmayan bir eşbütünleşme ilişkisi olduğu tespit edilmektedir. Bu durum BTC ile CO2 arasındaki ilişkinin uzun dönemde dengeye doğrusal olmayan bir şekilde yakınsadığı sonucunu göstermektedir. Değişkenler arasında doğrusal olmayan eşbütünleşme ilişkisini tespit ettikten sonra bu ilişkinin yönünü belirlemek amacıyla yapılan Granger nedensellik testi sonucuna göre ise Bitcoin’den Karbon Emisyonuna doğru tek yönlü nedensellik olduğu tespit edilmektedir. Bu bulgu, BTC üretiminde kullanılan enerjinin çevre dostu kaynaklardan elde edilmesine yönelik politikaların benimsenmesi gerektiği biçiminde yorumlanabilir.
Hao Zhang, Ye Duan, Jun Yang, Han Zeng-lin · 5 authors
Green finance is crucial to advancing the decrease of haze pollution in my nation as a new kind of environmental governance. This research constructs a comprehensive evaluation system of green finance to analyze the impact of green finance on haze pollution reduction and to consider the mediating role of energy efficiency in 30 provinces and regions in China. Through a series of robustness tests, the mechanism and path of green finance on haze pollution reduction are confirmed. The main conclusions are as follows: First, the development of green finance has a positive effect on haze pollution reduction. Second, the upgrading of industrial structure and the improvement of technological level are important paths for green finance to promote haze pollution reduction, and can also have an indirect impact through energy efficiency. The moderating and mediating effects of energy efficiency and green finance can effectively promote the reduction of haze pollution. In other words, the development of green finance can achieve the goal of reducing haze pollution by improving energy efficiency. Third, there is regional heterogeneity in green finance for haze pollution reduction, and regions with high levels of green finance are more effective in reducing haze pollution. Fourth, environmental Supervision, environmental decentralization and average wind speed can promote haze pollution reduction, economic development to some extent exacerbated the haze pollution. Based on the above research conclusions, this paper puts forward corresponding countermeasures and suggestions.
Inzamam Ul Haq, Paulo Ferreira, Derick Quintino, Nhan Huynh · 5 authors
The purpose of the research is to explore the dynamic multiscale linkage between economic policy uncertainty, equity market volatility, energy and sustainable cryptocurrencies during the COVID-19 period. We use a multiscale TVP-VAR model considering level (EPUs and IDEMV) and returns series (cryptocurrencies) from 1 December 2019 to 30 September 2022. The data are then decomposed into six wavelet components, based on the wavelet MODWT method. The TVP-VAR connectedness approach is used to uncover the dynamic connectedness among EPUs, energy and sustainable cryptocurrency returns. Our findings reveal that CNEPU (USEPU) is the strongest (weakest) NET volatility transmitter. IDEMV is the most consistent volatility NET transmitter among all uncertainty indices across the original returns and wavelet scales (D1~D6). Energy cryptocurrencies, i.e., GRID, POW and SNC, are more likely to receive volatility spillovers than sustainable cryptocurrencies during a turbulent period (COVID-19). XLM (XNO) is least (most) affected by volatility spillover in system-wide connectedness, and XLM (ADA and MIOTA) showed a consistent (heterogeneous) non-recipient behavior across the six wavelet (D1~D6) scales and original return series. This study uncovers the dynamic connectedness across multiscale, which will support investors considering different investment horizons (D1~D6).
Bu çalışmada, Bitcoin ile gelişmiş ve gelişmekte olan ülkelerin hisse senedi piyasaları arasındaki volatilite yayılım ilişkisinin incelenmesi ve bulguların finansal piyasaları etkileyen küresel olaylar bağlamında değerlendirilmesi amaçlanmıştır. Bu amaçla 03.01.2017-25.03.2022 dönemi, Bitcoin, MSCI ABD, MSCI Avrupa ve MSCI gelişmekte olan piyasalar endeksi günlük verilerine zamanla değişen parametre vektör otoregresif (TVP-VAR) modeli uygulanmıştır. Uygulama sonucunda Bitcoin’in MSCI ABD ve MSC Avrupa karşsısında net volatilite alıcısı olduğu ve MSCI gelişmekte olan piyasalar karşısında net volatilite yayıcısı olduğu gözlenmiştir. MSCI ABD’nin net volatililite yayıcısı ve MSCI gelişmekte olan piyasaların ise net volatilite alıcısı olduğu tespit edilmiştir. Ayrıca Bitcoin’in gelişmiş ve gelişmekte olan piyasalarla zayıf bağlantılı olduğu gözlenmiştir. Bulgular, volatilite yayılımının aşırı artış-azalış gösterdiği dönemlerde tüm dünyayı etkileyen küresel olaylar olduğunu göstermiştir.
Nicolás Malz, Felipe Corral Montoya, Paola Yanguas-Parra, Pao-Yu Oei
Juxtaposing China’s current situation and policies toward coal and renewables at home and abroad, we argue that China remains in a paradoxical state of carbon lock-in. We analyze the techno-economic, institutional and political factors that contribute to China’s coal-related policies following a novel approach that blends different theories and frameworks to establish an interdisciplinary dialogue between various strands of research that were hitherto unconnected. This is accomplished by applying a political economy framework through the lens of techno-institutional carbon lock-in theory in three case studies encompassing China itself, as well as China’s climate and energy policy abroad in Pakistan and Mozambique. The article draws four major conclusions about China’s energy paradox: 1) An imperative for economic growth lies at the heart of the Chinese governance system’s incentive structure, which has resulted in a coal-based energy and industrial policy. 2) China’s government should use the experimental, decentralized nature of its regionally-decentralized regime and energy sector to their advantage by promoting disruption rather than incumbency. 3) To address the structural and institutional deficiencies that maintain or even strengthen carbon lock-in, energy governance should be shaped around the primary challenge of strengthening renewable energy advocates throughout all levels of government. 4) The discussion of coal financing abroad must now go beyond the discontinuation of new projects; the building of alternative cleaner projects should be considered and the ones in progress should be halted.
At present, environmental and competitive pressures urge enterprises to engage in research and development (R&D) of green products, and a green supply chain has become the main trend in the sustainable development of enterprises. This study analyzes the optimal operation decisions of a green supply chain for two manufacturers under different competitive and cooperative relationships, considering factors such as government subsidies, consumer green preferences, and the impact of the green information trust. The results show that government subsidies can lead to higher social welfare when manufacturers have a cooperative relationship, but the optimal choice of subsidies (for R&D costs or product production costs) depends on the level of competition and the difficulty of R&D. For the manufacturers, the optimal choice of R&D strategy (individual or joint) and the use of blockchain technology also depends on the level of difficulty of R&D and the type of government subsidies. Overall, this study highlights the importance of considering various factors when making decisions in a green supply chain to achieve the best outcomes for all parties involved.
With the proposal of the two-carbon goal, energy conservation and emission reduction will become the focus of China’s energy system in the future for a long time to come. The establishment of a complete and efficient carbon traceability system will play an important role in promoting carbon emission reduction in the power system. Based on blockchain, this paper uses the consensus mechanism, time stamp, decentralization features, smart contract and other functions of blockchain, combined with the power flow calculation and the characteristics related to carbon emission and active power of the generator set, to obtain the corresponding carbon emission intensity of the generator set and carbon flow rate. It realizes the calculation and tracing of carbon emission flow in power distribution network and ensures the reliability of carbon traceability results, high efficiency of information transmission and transparency of traceability process. Firstly, based on the characteristics of the master-slave multi-chain structure in the consortium chain, In this paper, high-voltage substation nodes are the main chain nodes, and carbon flow tracing and calculation are carried out for the associated low-voltage substations, and the information of high-voltage or low-voltage substation nodes is guaranteed to be tamper-free through the hash anchoring method. The master-slave multi-chain model adopted in this paper is that the main chain adopts EA-DPoS (Evaluation and Agent-DPoS) algorithm, the slave chain adopts improved PBFT algorithm, and the comprehensive evaluation and reward and punishment mechanism are introduced to complete the consensus. Secondly, considering the security requirements of the power system data and the fact that some nodes of the distribution network do not have powerful computing resources comparable to those of the power grid company or major nodes, this paper encrypts and decrypts relevant data in the main chain node by combining the smart contract of blockchain. Meanwhile, cloud service providers with computing resources are responsible for generator power distribution combined with power flow calculation and carbon emission intensity calculation of the generator set. The power grid company adopts the cloud computing framework based on the double check mechanism to calculate the carbon flow rate while verifying the correct calculation results of the cloud service provider, and finally realizes the safe and accurate tracing of the carbon flow of the distribution network.
Blockchain technology has been widely used in many industries. One current application is in remanufacturing. In this paper we consider the combination of remanufacturing and blockchain, and model a supply chain composed of a manufacturer, a third-party firm, and an online platform. Among them, the manufacturer faces the cap-and-trade regulation and adopts blockchain to record the information on the used products and then remanufactures products. The platform has the power to expand the potential market size and can operate in the marketplace or reselling mode. The third-party firm collects used products for the manufacturer. We conduct a Stackelberg game analysis and obtain the following major findings: First, the optimal production quantities and optimal collection rates with and without blockchain in the marketplace and reselling modes increase with the allocated cap and platform-enabled power. Second, in the reselling or marketplace mode, the manufacturer should not adopt blockchain if the emissions intensity is low; otherwise, it should adopt blockchain. Third, selecting the reselling (marketplace) mode is more profitable for the manufacturer if the platform-enabled power is low (high). Fourth, for quantity coordination, the reselling mode under the wholesale price contract can always coordinate the manufacturer and platform, and the manufacturer, online platform, and third-party firm. However, the marketplace mode with a commission rate can only coordinate the manufacturer, online platform, and third-party firm. For social welfare coordination, the manufacturer, online platform, and third-party firm can achieve coordination in the marketplace or reselling mode. Finally, extending the work to consider the cross-channel effect, we find that the major findings for both quantity coordination and social welfare coordination in the reselling and marketplace modes still hold.
Çalışmanın amacı kripto para piyasasına öncülük eden Bitcoin ile seçilmiş altcoinler arasındaki ilişkinin ve nedenselliğin varlığını tespit ederek yatırımcıların kararlarına ışık tutmaktır. Bu amaç doğrultusunda çalışmada, Bitcoin (BTC) ile Ethereum(ETH), Binance Coin (BNB), Cardano (ADA) , Litecoin (LTC), Tron (TRX), Stellar (XLM), IOTA altcoinlerinin arasındaki eşbütünleşme ve nedensellik ilişkisi araştırılmıştır. Uzun dönemli ilişkinin var olup olmadığı Engle Granger Eşbütünleşme yöntemiyle, kısa dönemli ilişkinin var olup olmadığı Sıradan En Küçük Kareler Yöntemiyle (OLS), nedensellik ilişkisinin var olup olmadığı ise Toda Yamamato Nedensellik yöntemiyle test edilmiştir. Çalışma kapsamında veri seti olarak 14.06.2018-01.12.2021 tarihleri arasında kripto para birimlerinin günlük kapanış fiyatları kullanılmıştır. Araştırma sonucunda Engle Granger Testine göre BTC ile seçilen altcoinler arasında uzun dönemli eşbütünleşme ilişkisi bulunamamıştır. OLS testine göre bağımsız ve bağımlı değişkenler arasında kısa dönemli ilişkinin var olduğu sonucuna ulaşılmıştır. Toda Yamamato Testine göre BTC’den ADA, ETH, IOTA, TRX, XLM alt coinlerine doğru granger nedensellik olduğu, BTC’den BNB ve LTC coinlerine doğru granger nedensellik olmadığı ve BTC’den etkilenmedikleri sonucuna ulaşılmıştır.