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This study aims to examine the relationship between the environment and tourism flows, as well as the economic variables of the 32 states of Mexico for the period 1999–2019 based on data availability. The related literature studying tourism and environmental impacts is scarce at a national level, with most of them being local case studies. Some international studies find that if the relationship exists, it is weak or nonexistent, using CO₂ as a proxy in most cases.

The present study uses panel data and cointegration panel methodologies, while also using geographic information systems to observe the distribution of variables at a state level between tourism and environmental variables.

The findings of the study are as follows: state gross domestic product, the inertia of environmental variables (i.e. volume of water treatment and solid waste), occupied rooms (proxy variable for tourism activity) and average temperature have an impact on the contemporary evolution of environmental variables; national and international tourist variables have no impact on the environment; the panels are integrated in such a way that there is a long-term equilibrium between states and some environmental care variables; and no conclusive evidence is found regarding the impact of tourism activity on the considered environmental variables.

The main limitations and areas of opportunity of the work refer to the amount of data available over time and the precision of the measurement of the variables. The availability, temporality and frequency of the data are also limitations of the research. An example of this is the nonexistence of CO₂ emissions at the state level. Additionally, studying other countries and regions for which there are limitations of data and applied studies is also a challenge.

The results are important for economies (in growth) and societies whose economic growth depends on tourism flows and have done little to reverse the damage that tourism has on the environment.

The models can contribute to study the relation between tourism and environmental variables and could be extended to regions, states and provinces for decision-making on actions to be taken for the present and future.

The originality of the research is innovative for the region: Mexico, Central and Latin America. There are no works that have studied these problems with this methodology and these variables. In terms of originality, the classic models of panel data and cointegration of panel data are useful and easily replicable for others to use for different countries. The results are relevant because there is apparently no relationship between tourism and some environmental variables in the short run, but there exists a weak and strong long-run relation between some of them.

本研究采用面板数据和协整面板模型方法, 同时利用地理信息系统(gis)观察州一级层面旅游和环境方面的变量分布。

本研究根据数据可用性, 研究了墨西哥32个州1999–2019年期间环境与旅游流量及经济变量之间的关系。在国家层面上研究旅游与环境影响的相关文献很少, 而且大多是地方的个案研究。一些国际研究发现, 即使有这种关系, 大多数案例中使用二氧化碳作为替代变量, 这种关系也是很弱或不存在。

i)国家国内生产总值, 环境变量的惯性(即水处理量和固体废物量), 占用的房间(旅游活动的代理变量)和平均温度对环境变量的现有演化有影响。ii)国内和国际旅游变量对环境没有影响。iii)面板数据以这样一种方式集成, 即国家和一些环境变量之间存在一种长期平衡。iv)关于旅游活动对所考虑的环境变量的影响没有确凿的证据。

这项工作的主要局限和机会领域是指随着时间的推移可获得的数据量和变量测量的精度。数据的可用性、时效性和频率也是本研究的局限性。这方面的一个例子是在州一级不存在二氧化碳排放。此外, 由于数据和应用研究的局限, 研究其他国家和地区也是一个挑战。

研究结果对经济增长依赖旅游业流量的经济体和社会具有重要意义, 这些经济体和社会对扭转旅游业对环境的破坏方面做得还不够。

这些模型有助于研究旅游业与环境变量之间的关系, 并可推广到地区、州和省, 以制定当前和未来的行动决策。

这项研究的原创性对该地区(墨西哥、中美洲和拉丁美洲)来说是具有创新性的。没有人用这种方法和这些变量研究过这些问题。就原创性而言, 面板数据和面板数据协整的经典模型是有用的且易于复制, 可供其他国家使用。 研究结果具有一定的相关性, 因为旅游业与部分环境变量在短期内不存在明显的相关性, 但在它们中的一些变量在长期内存在着或强或弱的相关性。

Se examina la relación entre medio ambiente y flujos turísticos, así como variables económicas de los 32 estados de México para el período 1999-2019 basado en la disponibilidad de datos. La literatura relacionada que estudia el turismo y los impactos ambientales es escasa a nivel nacional, siendo la mayoría de ellos estudios de casos locales. Estudios internacionales encuentran que, si la relación existe, es débil o inexistente, utilizando el CO2 como un indicador en la mayoría de los casos.

Se utilizaron metodologías de datos de panel y cointegración de panel, además sistemas de información geográfica para observar la distribución de variables a nivel estatal.

i) El Producto Interno Bruto Estatal, la inercia de las variables ambientales (es decir, volumen de tratamiento de agua y residuos sólidos), habitaciones ocupadas (proxy de la actividad turística) y temperatura promedio tienen un impacto en la evolución contemporánea de las variables ambientales, ii) las variables turísticas nacionales e internacionales no tienen un impacto en el medio ambiente, iii) los paneles están integrados de tal manera que existe un equilibrio a largo plazo entre turismo, crecimiento económico y algunas variables ambientales, y iv) no se encuentra evidencia concluyente con respecto al impacto de la actividad turística en las variables ambientales consideradas.

Las principales limitaciones y áreas de oportunidad del trabajo se refieren a la cantidad de datos disponibles en el tiempo y a la precisión de la medición de las variables. La disponibilidad, temporalidad y frecuencia de los datos también son limitaciones de la investigación. Un ejemplo de ello es la inexistencia de emisiones de CO2 a nivel estatal. Además, el estudio de otros países y regiones para los que existen limitaciones de datos y estudios aplicados también es un reto.

Los resultados son importantes para las economías (en crecimiento) y las sociedades cuyo crecimiento económico depende de los flujos turísticos y que han hecho poco por invertir los daños que el turismo produce en el medio ambiente.

Los modelos pueden contribuir a estudiar la relación entre el turismo y las variables medioambientales y podrían extenderse a regiones, estados y provincias para la toma de decisiones sobre las acciones a emprender para el presente y el futuro.

El artículo proporciona un análisis innovador y exploratorio hacia una perspectiva futura que agrega valor al turismo y la planificación para la sostenibilidad. La relación entre turismo y medio ambiente se ha estudiado durante varios años. La UNTWO ha abordado las consecuencias del turismo en el medio ambiente, particularmente, más basura, mayor consumo de agua, emisiones de CO2 y otros aspectos. Pocos trabajos estudian la relación entre estas variables.

La originalidad de la investigación es innovadora para la región: México, América Central y América Latina. No existen trabajos que hayan estudiado estos problemas con esta metodología y estas variables.

En términos de originalidad, los modelos clásicos de datos de panel y cointegración de datos de panel son útiles y fácilmente replicables para que otros los utilicen en diferentes países.

Los resultados son relevantes porque aparentemente no hay una relación entre el turismo y algunas variables ambientales a corto plazo, existe una relación débil y fuerte a largo plazo entre algunas de ellas.

This paper aims to empirically investigate the dynamic interlinkages among globalization, digitalization and economic development in the top 75 most globalized countries from 2000 to 2019. The selection of the 75 most globalized developing countries is based on the overall scores of the KOF Globalization Index (2021).

The research design is based on secondary data collected from the World Bank (2021), the International Telecommunication Union (2021) and the KOF Globalization Index (2021). The study uses panel unit root tests followed by the panel cointegration techniques. Further, the estimation uses panel fully modified ordinary least squares and panel dynamic ordinary least squares methods.

The empirical results reveal that the effect of globalization on economic development is sensitive to different estimation procedures; in some cases, but not in every case, the effect is positive and significant. However, the positive and significant effect of digitalization on economic development is robust across all estimated models. Long-run equilibrium relationships and bidirectional causalities strongly affirm the nexus among globalization, digitalization and economic development, substantiating the interconnectedness among 75 developing economies.

The study reinstates that the forces of globalization and digitalization will be instrumental in shaping the selected most globalized economies in the long run. Adopting various econometric methodologies takes care of the time-specific and cross-sectional dynamics, as evident in the panel framework considered in this study. The empirical findings truly ascertain the theoretical synergy among the forces of globalization leading to more digitalization and economic development. This makes the empirical interplay highly conducive to framing long-term policies to expand the information communication network in terms of its access and reach.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

Higher economic growth accompanied by rising energy demand poses severe challenges to the long-term environmental sustainability of E7 economies, including Brazil, China, India, Indonesia, Mexico, Russia and Turkey. Thus, this paper explores the influence of foreign direct investment (FDI) inflows on energy diversification for E7 economies.

The dataset is panel data for emerging seven (E7) economies, covering the period 1992–2017. The empirical investigation relies on econometric techniques: panel cointegration test and panel autoregressive distributed lag model.

The findings reveal that energy diversification and FDI inflows are cointegrated. In the long run, higher FDI inflows encourage energy diversification, but energy efficiency improvements discourage energy diversification. In the short run, the effects of FDI inflows on energy diversification vary across E7 economies, highlighting the role of country-specific factors in determining the short-run influence of FDI inflows on energy diversification.

The findings suggested that FDI policies should encourage the adoption of nonconventional energy resources to stimulate energy diversification in E7 economies. Besides, better coordination between energy diversification and energy efficiency policies is required in the long run for a successful transition towards low-carbon economy goals.

This study is a unique empirical exercise that uncovers a cointegrating relationship between energy diversification and FDI inflows for E7 economies. Moreover, the analysis provides homogenous long-run and heterogeneous (country-specific) short-run coefficient estimates for the effect of FDI inflows on energy diversification.

This paper assesses the environment of legitimacy by determining the role of institutional quality and policy uncertainty on the performance of five major South Asian stock markets (India, Pakistan, Bangladesh, Sri Lanka, and Nepal) using 21 years data from 2000 to 2020. The focus of this study is to approach the issue of the environment of legitimacy that leads to sustained market returns.

Panel cointegration tests of Kao and Pedroni are applied, and the Dynamic Panel Vector Autoregressive (PVAR) model is used to determine the estimates.

ADF P-Values of both Kao and Pedroni tests show that the panels are cointegrated; the statistical significance of the results of the Kao and Pedroni panel cointegration test confirms cointegration among the variables. After determining the most appropriate lag, the analysis is done using PVAR. The results indicate that institutional quality, policy uncertainty, and GDP positively affect stock market return. Meanwhile, government actions and inflation negatively affect stock market returns. On the other hand, stock market return positively affects institutional quality, government action, policy uncertainty, and GDP. While stock market return negatively affects inflation.

The sample is taken only from a limited number of South Asian countries, and the period is also limited to 21 years.

Based on our research findings, we have identified several policy implications recommended to enhance and sustain the performance of stock markets.

This paper uses a unique analytical tool, which gives a better insight into the problem. The value of this work lies in its findings, which also have practical implications and theoretical significance.

This study aims to examine whether energy poverty impacts gender inequality and CO₂ emissions in African countries with the biggest economies by gross domestic product (GDP) per capita from 1996 to 2020. Additionally, this study examines the existence of the gender Kuznets curve (GKC) and the environmental Kuznets curve (EKC) theories. Furthermore, it evaluates the connection between economic development and carbon emissions, on the one hand, and economic development and gender inequality on the other.

This study uses the augmented Dickey–Fuller and Phillip–Perron unit root tests to determine the degree of integration between the variables. It also uses the Pedroni and Fisher–Combine Johansen cointegration tests to assess a long-run relationship between the variables. The authors adopted the pooled mean group (PMG)-autoregressive distributed lag model and used the E-Views 12 software to run the analysis.

The empirical analysis approves the long-run correlation among the variables used in this study. Increased energy poverty and GDP increase CO₂ emissions, whereas income square hurts CO₂ emissions. These results are consistent with the EKC hypothesis, which proposes a non-linear relationship between CO₂ emissions and economic growth in the studied areas (similar to an inverted U shape). Long-term foreign direct investment (FDI) has a negative correlation with CO₂ emissions. On the contrary, energy poverty, GDPsq and FDI find a positive relationship with gender inequality, whereas GDP finds a negative association with gender inequality. The negative relationship between GDPsq and gender inequality establishes a “U”-shaped connection between income and gender inequality. Thus, it supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

This study supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

While several existing panel studies have focused on the linear specifications of the nexus between trade openness and unemployment, nonlinear panel studies on this subject remain less explored. This paper examines the asymmetric nexus between trade openness and unemployment in 34 selected sub-Saharan Africa (SSA) countries for the period spanning from 1991 to 2020.

The Pedroni and Westerlund panel cointegration tests were conducted to ascertain a long run relationship among the studied variables, while the panel nonlinear autoregressive distributed lag approach was applied to account for asymmetries.

The study revealed among other things that trade openness asymmetrically influences unemployment in the selected panel of SSA countries. In the long run, the positive shock in trade openness on unemployment is greater as compared to the negative shock.

The implications of this study include the need to (1) ensure the effective monitoring and supervision of trade flows in the sub-region so that their full benefits are maximized in terms of job creation and (2) ensure that a positive trade balance is maintained in the selected SSA countries.

The positive and negative shocks in trade openness are examined to determine their asymmetric effects on unemployment.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

The present study examines the significance of financial inclusion in reducing income inequality in the Asian context.

This study uses panel estimation techniques such as the Pedroni cointegration test, Kao residual-based test, FMOLS, ARDL and Granger causality, a dataset consisting of the Gini coefficient index, three dimensions of financial inclusion measures and one added variable on financial depth, spanning from 2005 to 2019.

The study finds that in the long-run, income inequality disparity is highly influenced by financial inclusion indicators, such as the number of bank branches, deposit accounts, outstanding loans and domestic credit to the private sector. Whereas in the short run, disparities in income are unaffected by all the indicators of financial inclusion. Further, unidirectional causality from financial inclusion indicators to income inequality necessitates the need for policymakers to design policies and programs that would enhance access to financial services as an essential mechanism to reduce income disparity.

Studies based on a panel of Asian countries that have undergone impressive growth of financial inclusion initiatives since the past decade—but are still facing widening income inequality—are conspicuously rare in the literature. The empirical analysis fills this void by showing the significant role financial inclusion indicators play in steering the Asian economies toward income equality throughout the study period.

This study aims to investigate the dynamic relationship between renewable and non-renewable energy sources on the economic growth of eight countries, the capital stock and labour force being used as control variables in each case. Questions that need to be asked include the following: Is there is an asymmetric and, hence, a non-linear relationship between variables? If yes, how does economic growth interact with both renewable and non-renewable energy consumption (EC)? How different are these relationships in the countries highly rated in the performance of renewable EC compared to those lowly rated?

This paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables.

A newly developed asymmetric panel quantile approach suggests that EC has a significant effect on economic growth in both directions of shocks as well as for the considered sample. The results further support the findings in recent literature on renewable energy deployment, given the importance of renewable EC for economic growth with the increased levels of renewable EC, although the initial investments may have a negative effect on economic growth for some countries.

This study contributes to the literature in twofold. Firstly, it aims to contribute to the ongoing debate in literature by incorporating both renewable and non-renewable energy resources in the production function with labour and capital to test their asymmetric impact on economic growth. Secondly, this paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables. Another point that should be emphasised in this study is the need for studies analysing economic growth and EC for a sample of G20 countries based on a comparative view for the renewable and non-renewable EC in literature.