This study examines the exchange rate pass-through to the United States(US)restaurant and hotel prices by incorporating the effect of monetary policy uncertainty over the period 2001:M12 to 2019:M01.Using the nonlinea...This study examines the exchange rate pass-through to the United States(US)restaurant and hotel prices by incorporating the effect of monetary policy uncertainty over the period 2001:M12 to 2019:M01.Using the nonlinear autoregressive distributed lag(NARDL)model,empirical evidence indicates asymmetric pass-through of exchange rate and monetary policy uncertainty.Moreover,a stronger pass-through effect is observed during depreciation and a negative shock in monetary policy uncertainty,corroborating asymmetric pass-through predictions.Our results further show that a positive shock in energy prices leads to an increase in restaurant and hotel prices.Furthermore,asymmetric causality indicates that a positive shock in the exchange rate causes a positive shock to restaurant and hotel prices.We found feedback causal effects between positive and negative shocks in monetary policy uncertainty and positive and negative shocks in the exchange rate.Additionally,we detected a one-way asymmetric causality,flowing from a positive(negative)shock to a positive(negative)shock in energy prices.Therefore,these findings provide insights for policymakers to achieve low and stable prices in the US restaurant and hotel industry through sound monetary policy formulations.Highlights.The drivers of restaurant and hotel business in tourism destinations are examined.There is asymmetric pass-through of exchange rate and monetary policy uncertainty.A stronger pass-through is observed during appreciation and a negative shock to monetary policy uncertainty.There is asymmetric causality from positive shock in exchange rate to postive shock in restaurant and hotel prices.展开更多
We introduce a novel approach to multifractal data in order to achieve transcended modeling and forecasting performances by extracting time series out of local Hurst exponent calculations at a specified scale.First,th...We introduce a novel approach to multifractal data in order to achieve transcended modeling and forecasting performances by extracting time series out of local Hurst exponent calculations at a specified scale.First,the long range and co-movement dependencies of the time series are scrutinized on time-frequency space using multiple wavelet coherence analysis.Then,the multifractal behaviors of the series are verified by multifractal de-trended fluctuation analysis and its local Hurst exponents are calculated.Additionally,root mean squares of residuals at the specified scale are procured from an intermediate step during local Hurst exponent calculations.These internally calculated series have been used to estimate the process with vector autoregressive fractionally integrated moving average(VARFIMA)model and forecasted accordingly.In our study,the daily prices of gold,silver and platinum are used for assessment.The results have shown that all metals do behave in phase movement on long term periods and possess multifractal features.Furthermore,the intermediate time series obtained during local Hurst exponent calculations still appertain the co-movement as well as multifractal characteristics of the raw data and may be successfully re-scaled,modeled and forecasted by using VARFIMA model.Conclusively,VARFIMA model have notably surpassed its univariate counterpart(ARFIMA)in all efficacious trials while re-emphasizing the importance of comovement procurement in modeling.Our study’s novelty lies in using a multifractal de-trended fluctuation analysis,along with multiple wavelet coherence analysis,for forecasting purposes to an extent not seen before.The results will be of particular significance to finance researchers and practitioners.展开更多
Background/Objectives:Many economies are on the trajectory of alternative growth drivers other than conventional capital and labor.Access to credit facilities is a pertinent indicator of economic growth.In line with t...Background/Objectives:Many economies are on the trajectory of alternative growth drivers other than conventional capital and labor.Access to credit facilities is a pertinent indicator of economic growth.In line with the United Nations Sustainable Development Goals(UNSDGs-8)agenda,the national goal for sustainable development for most economies and Arab economies is no exception.Therefore,the current study adopts a traditional growth model by exploring the relationship between gross domestic product(GDP)per capita,credit for private sectors,ratio of exports,real GDP,and per labor force participants for selected Arab economies annually from 2001 to 2020.Research design:This study leverages the Fourier Kwiatkowski–Phillips–Schmidt–Shin(KPSS)unit root test and second-generation panel econometrics as estimation techniques,such as Westerlund and Edgerton panel cointegration test,and the use of two estimators,namely the augmented mean group(AMG)and common correlated error mean group(CCEMG),to obtain robust results.Findings:Empirical findings from Westerlund and Edgerton panel cointegration tests validate the long-run equilibrium relationship among the outlined variables.Further empirical results indicate that the share of exports is negatively significant with economic growth in countries such as Kuwait,Lebanon,Tunisia,and Jordan.Additionally,savings and labor force participation have a positive relationship with economic growth in individual countries such as Algeria and Bahrain.As per the panel,there is no significant relationship between labor force participation and economic growth.This indicates that the skilled labor force enhanced economic growth.Conclusions:These findings come with inherent far-reaching policy suggestions for economies and panels.Further details on country-specific policy actions are presented in the concluding section.展开更多
This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooper...This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooperation and Development for the period from 2000 to 2019.We use a two-step dynamic generalized method of moments approach to understand this relationship.The results show that FD augments the posi-tive effects of TI on four of the six environmental indicators,namely ecological foot-print,adjusted net savings,pressure on nature,and environmental performance.However,no significant effects on environmental sustainability and environmental vulnerability indices were found.When considering all of the environmental quality indicators,TI appears to enhance environmental quality.We find evidence to support the existence of the environmental Kuznets curve in the context of each environmen-tal indicator and economic growth.Moreover,FD and energy consumption appear to accelerate environmental degradation.Based on these results,FD should be viewed as an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions.Highlights.Technological innovation and environmental quality nexus is studied.The moderating role of financial development is analyzed.Six different environmental quality indicators are used for OECD countries.Financial development intensifies the environmental benefits of innovation.•The EKC hypothesis is confirmed for all six environmental indicators.展开更多
The slippery slope framework explains tax compliance along two main dimensions,trust in authorities and power of authorities,which influence taxpayers’compliance attitudes.Through frequentist and Bayesian analyses,we...The slippery slope framework explains tax compliance along two main dimensions,trust in authorities and power of authorities,which influence taxpayers’compliance attitudes.Through frequentist and Bayesian analyses,we investigated the framework’s assumptions on a sample of 2786 self-employed taxpayers from eleven post-communist and non-post-communist countries doing business in five economic branches.After using scenarios that experimentally manipulated trust and power,our results confirmed the framework’s assumptions regarding the attitudes of the self-employed taxpayers;trust and power fostered intended tax compliance and diminished tax evasion,trust boosted voluntary tax compliance,whereas power increased enforced tax compliance.Additionally,self-employed taxpayers from post-communist countries reported higher intended tax compliance and lower tax evasion than those from non-post-communist countries.Our results offer tax authorities insights into how trust and power may contribute to obtaining and maintaining high tax compliance levels amid global economic challenges,downturns,and increasing tax compliance costs.展开更多
The correlation between technological innovation,economic growth,renewable energy,and ecological footprint carries significant policy implications for environmental sustainability.Furthermore,financial inclusion can d...The correlation between technological innovation,economic growth,renewable energy,and ecological footprint carries significant policy implications for environmental sustainability.Furthermore,financial inclusion can drastically affect the technology-climate nexus across different countries and its moderating impacts have received sufficient attention.To do this,this study examined how technological innovation,financial inclusion,economic growth,and renewable energy affected emerging economies’ecological footprint from 1990 to 2019.Additionally,this study also scrutinizes the moderating role of financial inclusion with other regressors on ecological footprint.To account for structural shifts,disguised cointegration,and numerous breaks in panel regression,this study applies advanced panel estimation methods for empirical analysis.The estimated outcomes exhibit that the influence of technical innovation,climate technologies,and renewable energy significantly reduces the ecological footprint levels.Besides,economic growth and financial inclusion significantly increase the ecological footprint levels in the emerging economies.Furthermore,the integration of innovative technology and renewable energy in emerging countries mitigates the adverse effects of financial inclusion by making it easier for creative technologies and reducing ecological footprints.These results show that emerging countries’innovative technology and renewable energy sources should be integrated with financial inclusion to enable longterm mitigation of environmental damages and sustainable growth.Based on these estimated findings,the research recommends that emerging economies should hasten technological innovations along with stronger financial development to curtail ecological concerns without hindering the pace of sustainable economic growth.展开更多
The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is l...The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is lacking in the traditional financial sector.The use of technology to automate financial services is becoming more important for economic organizations and industries because the digital age has seen a period of transition in terms of consumers and personalization.The future of FinTech will be shaped by technologies like the Internet of Things,blockchain,and artificial intelligence.The involvement of these platforms in financial services is a major concern for global business growth.FinTech is becoming more popular with customers because of such benefits.FinTech has driven a fundamental change within the financial services industry,placing the client at the center of everything.Protection has become a primary focus since data are a component of FinTech transactions.The task of consolidating research reports for consensus is very manual,as there is no standardized format.Although existing research has proposed certain methods,they have certain drawbacks in FinTech payment systems(including cryptocurrencies),credit markets(including peer-to-peer lending),and insurance systems.This paper implements blockchainbased financial technology for the banking sector to overcome these transition issues.In this study,we have proposed an adaptive neuro-fuzzy-based K-nearest neighbors’algorithm.The chaotic improved foraging optimization algorithm is used to optimize the proposed method.The rolling window autoregressive lag modeling approach analyzes FinTech growth.The proposed algorithm is compared with existing approaches to demonstrate its efficiency.The findings showed that it achieved 91%accuracy,90%privacy,96%robustness,and 25%cyber-risk performance.Compared with traditional approaches,the recommended strategy will be more convenient,safe,and effective in the transition period.展开更多
Let F, N、A and N2 denote the properties of being finite, nilpotent, abelian and nilpotent of classes at most 2, respectively. Firstly we consider the class of finitely generated FTV-groups. Wc show that the property ...Let F, N、A and N2 denote the properties of being finite, nilpotent, abelian and nilpotent of classes at most 2, respectively. Firstly we consider the class of finitely generated FTV-groups. Wc show that the property FC is closed under finite extensions, and extend this result to finitely generated NF-groups. Secondly we prove that a finitely generated NF-group G is in the class ((FC)F, oo) if and only if G is an FA-group. Finally we prove that a finitely genera ted ATF-group in the class ((FC)F,∞)^* is an FM-group. Moreover, G/Z2(G) is finite.展开更多
文摘This study examines the exchange rate pass-through to the United States(US)restaurant and hotel prices by incorporating the effect of monetary policy uncertainty over the period 2001:M12 to 2019:M01.Using the nonlinear autoregressive distributed lag(NARDL)model,empirical evidence indicates asymmetric pass-through of exchange rate and monetary policy uncertainty.Moreover,a stronger pass-through effect is observed during depreciation and a negative shock in monetary policy uncertainty,corroborating asymmetric pass-through predictions.Our results further show that a positive shock in energy prices leads to an increase in restaurant and hotel prices.Furthermore,asymmetric causality indicates that a positive shock in the exchange rate causes a positive shock to restaurant and hotel prices.We found feedback causal effects between positive and negative shocks in monetary policy uncertainty and positive and negative shocks in the exchange rate.Additionally,we detected a one-way asymmetric causality,flowing from a positive(negative)shock to a positive(negative)shock in energy prices.Therefore,these findings provide insights for policymakers to achieve low and stable prices in the US restaurant and hotel industry through sound monetary policy formulations.Highlights.The drivers of restaurant and hotel business in tourism destinations are examined.There is asymmetric pass-through of exchange rate and monetary policy uncertainty.A stronger pass-through is observed during appreciation and a negative shock to monetary policy uncertainty.There is asymmetric causality from positive shock in exchange rate to postive shock in restaurant and hotel prices.
文摘We introduce a novel approach to multifractal data in order to achieve transcended modeling and forecasting performances by extracting time series out of local Hurst exponent calculations at a specified scale.First,the long range and co-movement dependencies of the time series are scrutinized on time-frequency space using multiple wavelet coherence analysis.Then,the multifractal behaviors of the series are verified by multifractal de-trended fluctuation analysis and its local Hurst exponents are calculated.Additionally,root mean squares of residuals at the specified scale are procured from an intermediate step during local Hurst exponent calculations.These internally calculated series have been used to estimate the process with vector autoregressive fractionally integrated moving average(VARFIMA)model and forecasted accordingly.In our study,the daily prices of gold,silver and platinum are used for assessment.The results have shown that all metals do behave in phase movement on long term periods and possess multifractal features.Furthermore,the intermediate time series obtained during local Hurst exponent calculations still appertain the co-movement as well as multifractal characteristics of the raw data and may be successfully re-scaled,modeled and forecasted by using VARFIMA model.Conclusively,VARFIMA model have notably surpassed its univariate counterpart(ARFIMA)in all efficacious trials while re-emphasizing the importance of comovement procurement in modeling.Our study’s novelty lies in using a multifractal de-trended fluctuation analysis,along with multiple wavelet coherence analysis,for forecasting purposes to an extent not seen before.The results will be of particular significance to finance researchers and practitioners.
文摘Background/Objectives:Many economies are on the trajectory of alternative growth drivers other than conventional capital and labor.Access to credit facilities is a pertinent indicator of economic growth.In line with the United Nations Sustainable Development Goals(UNSDGs-8)agenda,the national goal for sustainable development for most economies and Arab economies is no exception.Therefore,the current study adopts a traditional growth model by exploring the relationship between gross domestic product(GDP)per capita,credit for private sectors,ratio of exports,real GDP,and per labor force participants for selected Arab economies annually from 2001 to 2020.Research design:This study leverages the Fourier Kwiatkowski–Phillips–Schmidt–Shin(KPSS)unit root test and second-generation panel econometrics as estimation techniques,such as Westerlund and Edgerton panel cointegration test,and the use of two estimators,namely the augmented mean group(AMG)and common correlated error mean group(CCEMG),to obtain robust results.Findings:Empirical findings from Westerlund and Edgerton panel cointegration tests validate the long-run equilibrium relationship among the outlined variables.Further empirical results indicate that the share of exports is negatively significant with economic growth in countries such as Kuwait,Lebanon,Tunisia,and Jordan.Additionally,savings and labor force participation have a positive relationship with economic growth in individual countries such as Algeria and Bahrain.As per the panel,there is no significant relationship between labor force participation and economic growth.This indicates that the skilled labor force enhanced economic growth.Conclusions:These findings come with inherent far-reaching policy suggestions for economies and panels.Further details on country-specific policy actions are presented in the concluding section.
基金This research paper did not receive any financial aid from any source.
文摘This study analyzes the role of financial development(FD)on the impact of technologi-cal innovation(TI)on six environmental quality indicators for the 25 economies that are part of the Organization for Economic Cooperation and Development for the period from 2000 to 2019.We use a two-step dynamic generalized method of moments approach to understand this relationship.The results show that FD augments the posi-tive effects of TI on four of the six environmental indicators,namely ecological foot-print,adjusted net savings,pressure on nature,and environmental performance.However,no significant effects on environmental sustainability and environmental vulnerability indices were found.When considering all of the environmental quality indicators,TI appears to enhance environmental quality.We find evidence to support the existence of the environmental Kuznets curve in the context of each environmen-tal indicator and economic growth.Moreover,FD and energy consumption appear to accelerate environmental degradation.Based on these results,FD should be viewed as an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions.Highlights.Technological innovation and environmental quality nexus is studied.The moderating role of financial development is analyzed.Six different environmental quality indicators are used for OECD countries.Financial development intensifies the environmental benefits of innovation.•The EKC hypothesis is confirmed for all six environmental indicators.
基金funded through the following research grants:Czech Science Foundation Project No.18-14082SUni-versity of Economics(Prague),Faculty of Finance and Accounting VSE Project No.IP 100040+1 种基金Science without Borders program no.229760/2013-9(CNPq—Brazilian National Council for Scientific and Technological Development)CAPES-PrInt Project No.88887.310237/2018-00“Cérebro,Cognição e Comportamento:Teoria e Aplicação para Inovação em Negócios”.
文摘The slippery slope framework explains tax compliance along two main dimensions,trust in authorities and power of authorities,which influence taxpayers’compliance attitudes.Through frequentist and Bayesian analyses,we investigated the framework’s assumptions on a sample of 2786 self-employed taxpayers from eleven post-communist and non-post-communist countries doing business in five economic branches.After using scenarios that experimentally manipulated trust and power,our results confirmed the framework’s assumptions regarding the attitudes of the self-employed taxpayers;trust and power fostered intended tax compliance and diminished tax evasion,trust boosted voluntary tax compliance,whereas power increased enforced tax compliance.Additionally,self-employed taxpayers from post-communist countries reported higher intended tax compliance and lower tax evasion than those from non-post-communist countries.Our results offer tax authorities insights into how trust and power may contribute to obtaining and maintaining high tax compliance levels amid global economic challenges,downturns,and increasing tax compliance costs.
文摘The correlation between technological innovation,economic growth,renewable energy,and ecological footprint carries significant policy implications for environmental sustainability.Furthermore,financial inclusion can drastically affect the technology-climate nexus across different countries and its moderating impacts have received sufficient attention.To do this,this study examined how technological innovation,financial inclusion,economic growth,and renewable energy affected emerging economies’ecological footprint from 1990 to 2019.Additionally,this study also scrutinizes the moderating role of financial inclusion with other regressors on ecological footprint.To account for structural shifts,disguised cointegration,and numerous breaks in panel regression,this study applies advanced panel estimation methods for empirical analysis.The estimated outcomes exhibit that the influence of technical innovation,climate technologies,and renewable energy significantly reduces the ecological footprint levels.Besides,economic growth and financial inclusion significantly increase the ecological footprint levels in the emerging economies.Furthermore,the integration of innovative technology and renewable energy in emerging countries mitigates the adverse effects of financial inclusion by making it easier for creative technologies and reducing ecological footprints.These results show that emerging countries’innovative technology and renewable energy sources should be integrated with financial inclusion to enable longterm mitigation of environmental damages and sustainable growth.Based on these estimated findings,the research recommends that emerging economies should hasten technological innovations along with stronger financial development to curtail ecological concerns without hindering the pace of sustainable economic growth.
基金from funding agencies in the public,commercial,or not-for-profit sectors.
文摘The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is lacking in the traditional financial sector.The use of technology to automate financial services is becoming more important for economic organizations and industries because the digital age has seen a period of transition in terms of consumers and personalization.The future of FinTech will be shaped by technologies like the Internet of Things,blockchain,and artificial intelligence.The involvement of these platforms in financial services is a major concern for global business growth.FinTech is becoming more popular with customers because of such benefits.FinTech has driven a fundamental change within the financial services industry,placing the client at the center of everything.Protection has become a primary focus since data are a component of FinTech transactions.The task of consolidating research reports for consensus is very manual,as there is no standardized format.Although existing research has proposed certain methods,they have certain drawbacks in FinTech payment systems(including cryptocurrencies),credit markets(including peer-to-peer lending),and insurance systems.This paper implements blockchainbased financial technology for the banking sector to overcome these transition issues.In this study,we have proposed an adaptive neuro-fuzzy-based K-nearest neighbors’algorithm.The chaotic improved foraging optimization algorithm is used to optimize the proposed method.The rolling window autoregressive lag modeling approach analyzes FinTech growth.The proposed algorithm is compared with existing approaches to demonstrate its efficiency.The findings showed that it achieved 91%accuracy,90%privacy,96%robustness,and 25%cyber-risk performance.Compared with traditional approaches,the recommended strategy will be more convenient,safe,and effective in the transition period.
文摘Let F, N、A and N2 denote the properties of being finite, nilpotent, abelian and nilpotent of classes at most 2, respectively. Firstly we consider the class of finitely generated FTV-groups. Wc show that the property FC is closed under finite extensions, and extend this result to finitely generated NF-groups. Secondly we prove that a finitely generated NF-group G is in the class ((FC)F, oo) if and only if G is an FA-group. Finally we prove that a finitely genera ted ATF-group in the class ((FC)F,∞)^* is an FM-group. Moreover, G/Z2(G) is finite.
