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The main objective of this research is to investigate if there is a long-term relationship between “terrorism” and sustainable “economic growth” in Big Ten Countries.

The data was tested via Panel ARDL Analysis. The growth rate (GR) is the dependent variable, and the “Global Terror Index (GTI)” is the independent variable as the terror indicator. The ratio of Foreign Direct Investment (FDI) to the Gross Domestic Product (GDP), and the ratio of External Balance (EB) to Gross Domestic Product (GDP) are included in the model as the control variables due to their effect on the growth rate. A Panel ARDL analysis is conducted to examine the existence of long-term co-integration between terror and the economy. The planning of the study, the formation of its theoretical and conceptual framework, and the literature research were carried out in 2 months, and the collection of data, the creation of the methodology and the analysis of the analyzes were carried out in 2 months, the interpretation of the findings and the development of policy recommendations were carried out within a period of 1 month. The entire study was completed in a total of 5 months.

Results showed that “Terror” has a negative impact on “Growth Rate” in the long term while “External Balance” and “Foreign Direct Investment” positively affect the Growth Rate. The coefficients for the short term are not statistically significant.

The sample is only limited to Big Ten including China, India, Indonesia, South Korea, Argentina, Brazil, Mexico, Turkey, Poland and South Africa. The period for annual data collection covers the years between 2002 and 2019 and due to the unavailability of data.

Considering the risks and the mutual negative effect that turns into a vicious circle between terrorism and the economy, it is necessary to eliminate the problems that cause terrorism in the mentioned countries, on the one hand, and to develop policies that will improve economic performance on the other.

Trustful law enforcement bodies have to be established and supported by all technological means to prevent terror. The conditions causing terror have to be investigated carefully and the problems causing terror or internal conflict have to be solved. International cooperation against terrorism has to be strengthened and partnerships, information, experience sharing have to be supported at the maximum levels.

It is certain that terror might have a negative influence on the performance of economies. But the limited number of studies within this vein and the small size of their sample groups mostly including single-country case studies require conducting a study by using a larger sample group of countries. Big Ten here represents at least half of the population of the world and different regions of the Globe.

The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

The shadow economy (SE) has been a serious issue with varied dimensions in all countries that significantly affect economic growth. Therefore, all countries have made an effort to tackle the SE by pursuing several measures. This study aims to investigate the impact of financial markets (stock and bond) in reducing the SE while considering the role of country risk (political, economic and financial) in N-11 countries.

The study employed first-generation methodological techniques, including a unit root test to identify stationarity in the series, a panel cointegration test and panel autoregressive distributive lag (ARDL) to estimate long-run and short-run relationships. Finally, the Granger causality is applied to determine the direction of the causal relationship.

The study explored that country risk factors are crucial in reducing the size of the SE. Moreover, the significant moderating role of country risk factors in the financial market development and SE nexus suggests that by controlling the country's risk, financial market development can negatively affect the SE.

Due to the availability of data, the study used data, ranging from 1995 to 2015, because the tax burden data is available from 1995 while the maximum data for the SE is available till 2015, using Medina and Schneider's (2019) data estimates for the SE.

The previous studies have focused explicitly on the role of financial institutions' development in the SE. To the best of the author's knowledge, no previous study is attempted to investigate the role of financial markets (bonds and stock) in the size of the SE. Furthermore, previous studies have ignored the important role of country risk factors in the size of the SE. This study investigates the impact of country risk on the SE and the moderating role of country risk in the development of financial markets and the SE nexus.

The main purpose of this paper is to examine the role of population aging in determining the health care expenditure (HCE) in India over the period 1981 to 2018.

While establishing the linkage between population aging and HCE, the study has used economic growth, urbanization and CO2 emissions as control variables and used the autoregressive distributed lag (ARDL) approach to cointegration and VECM based Granger causality approach to estimate both the long-run and short-run relationships among the variables.

The results of the ARDL bounds test showed that there is a stable and long-run relationship among the variables. The long-run and short-run coefficients reveal that population aging and income per capita exert a statistically significant and positive effect on per capita HCE in India. The VECM causality evidence shows that there is a presence of short-run causality from economic growth and population aging to per capita HCE, urbanization to environmental degradation and further from aging to urbanization. However, the long-run causality evidence confirms unidirectional causality from population aging to the per capita HCE.

The research findings could be improved by considering the changes in mortality rate over time because of other environmental factors such as air pollution, among others as control variables. Various other variables affecting the health of an aged person could be considered for better research outcome which is not included in the present study because of the paucity of data. However, the present research findings would certainly serve effective policy instrument aiming at maximizing health gains that are highly associated with the elderly population and economic growth towards achieving sustainable development in India.

The uniqueness of the present study lies in its estimation where the relationship between population aging and HCE is looked at while considering the impact of other environmental factors separately. The causal relationship is shown among the variables using updated econometrics time-series techniques. The study tried to resolve the ambiguity associated with the relationship between aging and HCE at a macro level.

Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.

Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.

The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.

Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.

This paper aims to examine the causation linking financial technology to economic growth in the East African Community states from 1997 to 2019.

Autoregressive distributed lag is used. Gross domestic product per capita proxies economic growth, automated teller machines, point of sale, debit card ownership and mobile banking measure financial technology.

The results unveil a significant relationship between financial technology and economic growth. The findings show bidirectional causality between automated teller machine and economic growth, with unidirectional causation from economic growth to point of sales and internet banking, mobile banking and government effectiveness to economic growth. The error correction term is negatively significant, demonstrating a long-term convergence between Fintech measures and economic growth.

The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. The government should reduce taxes on financial technology equipment and related services. The use of automated teller machine, debit card ownership and internet banking should be encouraged through cashless transactions. Financial institutions should adopt cashless operation policies to encourage the use of financial technologies.

Research results on the bond between financial technology and economic growth are not conclusive. These studies demonstrate that technological innovations are double edged-swords, with both positive and negative sides. The results are conflicting; some reveal positive relationships, while others show negative links. Hence, research is required to fill the lacuna.

It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

We investigated the association of COVID-19 indicators and economic uncertainty indices on payment-based system cryptocurrency (i.e. Bitcoin, Ripple and Dogecoin) returns.

We used an autoregressive distributed lag (ARDL) model for panel data and performed robustness checks by utilizing a random effect model (REM) and generalized method of moments (GMM). There are 25 most adopted cryptocurrency’s countries and the data spans from 22 March 2021 to 6 May 2022.

This research discovered four findings: (1) the index of COVID-19 vaccine confidence (VCI) recovers the economic and Bitcoin has become more attractive, causing investors to shift their investment from Dogecoin to Bitcoin. However, the VCI was revealed to be insignificant to Ripple; (2) during uncertain times, Bitcoin could perform as a diversifier, while Ripple could behave as a diversifier, safe haven or hedge. Meanwhile, the movement of Dogecoin prices tended to be influenced by public figures’ actions; (3) public opinion on Twitter and government policy changes regarding COVID-19 and economy had a crucial role in investment decision making; and (4) the COVID-19 variants revealed insignificant results to payment-based system cryptocurrency returns.

This study contributed to verifying the vaccine confidence index effect on payment-based system cryptocurrency returns. Also, we further investigated the uncertainty indicators impacting on cryptocurrency returns during the COVID-19 pandemic. Lastly, we utilized the COVID-19 variants as a cryptocurrency returns’ new determinant.

The aim of this study is to examine the nature and determinants of stock market integration between India and other Asia–Pacific countries (Malaysia, Hong Kong, Singapore, South Korea, Japan, China, Indonesia, the Philippines, Thailand and Taiwan) over the period 1991–2021.

Unit root tests, the dynamic conditional correlation-Glosten Jagannathan and Runkle-generalized autoregressive conditional heteroscedasticity (DCC-GJR-GARCH), pooled ordinary least squares (OLS) regression and random effects models are employed for the analysis.

The empirical results show that the DCC between each pair of sample countries is less than 0.5, indicating weak ties between the pairs of sample countries. Also, the DCC between India and other Asia–Pacific stock markets is positive and low, implying low level of integration. The correlation between India and China stock markets is found to be the highest, implying significant level of integration. The main reason for it would be strong economic linkages and bilateral trade relationship between India and China. Moreover, gross domestic product (GDP), interest rate (IR), consumer price index (CPI)-inflation and money supply (MS) differentials are the major driver of stock market integration between India and other Asia–Pacific countries.

The findings of the study have important implications for investors, portfolio managers and policymakers. It is found that the DCC between India and other Asia–Pacific countries (considered in the study) except China is low, which indicates weak ties between the pairs of sample countries. This implies that the Indian stock market provides good investment opportunities for foreign investors. Also, investors and portfolio managers can attain more diversified benefits and can minimize country risk by investing across Asia–Pacific countries. Further, knowledge about the factors that integrate the Indian stock market with the other Asia–Pacific stock markets will help policymakers frame suitable economic and financial stabilization policies.

This study contributes to the extant literature: first, by examining the linkages of Indian stock market with other Asia–Pacific countries; second, although previous studies confirmed the existence of linkages among the various stock markets, few researchers pay attention to the factors driving the process of stock market integration. This study provides additional evidence by examining the significant macroeconomic factors driving the process of such integration in the Asia–Pacific region considered under the study.

This paper aims to emphasize economic complexity, tourism, information and communication technology (ICT), renewable energy consumption and foreign direct investment (FDI) as the determinants of carbon emissions.

These economies rely on the tourism sector, and Asian countries rank among the top tourism economies worldwide in terms of tourism receipts. This study uses a series of empirical estimators, i.e. cross-sectional augmented auto-regression distributive lag and panel cointegration, to validate the main hypotheses.

The econometric results confirm an inverted U-shaped association between economic complexity and carbon emissions, validating the economic complexity index induced environment Kuznets curve hypothesis for the selected Asian economies.

Finally, the empirical results admit articulating some imperative policy suggestions to attain a sustainable environment on behalf of outcomes.

Furthermore, ICT and renewable energy consumption are environment-friendly indicators, while FDI and the international tourism industry increase environmental pressure in selected countries. In addition, this study also explores the interaction between renewable energy and ICT with FDI and their effects on carbon emissions. Interestingly, both interaction terms positively respond to the environmental correction process.

Because ICT with FDI may not reduce environmental pollution unless the energy used in FDI projects is greener. Moreover, in Asian economies, industrial and other sectors could increase environmental quality via the role of ICT in FDI.

修正亚洲前 8 大经济体的旅游环境库兹涅茨曲线假设：ict 和可再生能源消耗的作用

这些经济体依赖旅游业, 就旅游收入而言, 亚洲国家在全球旅游经济体中名列前茅。本研究使用一系列经验估计量, 即 CS-ARDL 和面板协整来验证我们的主要假设。

本文强调经济复杂性、旅游、信息和通信技术 (ICT)、可再生能源消费和外国直接投资 (FDI) 作为碳排放的决定因素

计量经济学结果证实了经济复杂性与碳排放之间的倒 U 型关联, 验证了 ECI 对选定亚洲经济体的环境库兹涅茨曲线 (EKC) 假设。

最后, 实证结果承认阐明了一些必要的政策建议, 以代表结果实现可持续环境。

此外, 信息通信技术和可再生能源消耗是环境友好型指标, 而外国直接投资和国际旅游业增加了选定国家的环境压力。此外, 本研究还探讨了可再生能源和 ICT 与外国直接投资之间的相互作用及其对碳排放的影响。有趣的是, 这两个交互项都对环境校正过程做出了积极响应。

ICT 与 FDI 可能不会减少环境污染, 除非 FDI 项目中的能源使用更环保。此外, 在亚洲经济体中, 工业和其他部门可以通过 ICT 在 FDI 中的作用提高环境质量。

环境库兹涅茨曲线; 外商直接投资;信息和通信技术; 可再生能源;旅游;亚洲主要旅游经济体

文章类型： 研究型论文