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The purpose of this paper is to identify whether any financial integration exists among ASEAN+5 members and some East Asian countries, including China, Japan, Korea, Hong Kong, and Taiwan, through interest rate, exchange rate, level of prices, and real output.

Therefore, the authors intend to identify any long-term relationship among these variables utilizing the data in the most efficient manner via panel cointegration and panel unit root tests. The study likewise uses a panel-based vector error correction (panel-vec) model for comparison and also short-run relationship analysis. The long-run relationship is estimated using dynamic ordinary least square technique and a panel multi-layer perceptron (MLP) neural network.

For the ten countries under consideration, the empirical result supports the long-run equilibrium relationship among real output, exchange rate, interest rate, and level of prices, and that the cointegration relationship implies unidirectional causality from exchange rate to real output. This result is favorable to a model that contains real output as a dependent variable and exchange rate, interest rate, and level of prices as explanatory variables. Panel-vec results indicate no evidence of short-run causality from exchange rate to real output. Furthermore, the comparison result of long-run equation estimation shows the superiority of neural networks over econometric models.

This paper adds to the literature by examining the financial cointegration using a panel model that contains real exchange rate, interest rate, real output, and inflation rate in ASEAN+5. Additionally this paper applied the MLP neural network to yield a robust estimation of the long-run equation obtained among the variables.

The present study aims to analyse the sustainability of the trade deficits in the Association of Southeast Asian Nations (ASEAN)-5 countries using panel framework during the period from 1965 to 2011.

The paper applied a battery of first- and second-generation panel unit root tests and Pedroni's, Kao and Chiang's, Westerlund, and Di Iorio and Fachin cointegration tests to achieve the objective.

The paper found the evidence of sustainable trade deficit in ASEAN-5 countries while utilizing panel unit root tests as well as panel cointegration tests.

The findings have important macroeconomic policies implication for ASEAN-5 countries that these policies had been effective in leading exports and imports to long-run steady-state equilibrium relationship among the ASEAN-5 countries.

The main contribution of the paper is to show that the macroeconomic policies of ASEAN-5 countries had been effective in leading exports and imports to long-run steady-state equilibrium relationship. To the authors' best knowledge, in this area, this is the first study in the panel framework for ASEAN countries.

The purpose of this paper is to explore the relationship between energy consumption and economic growth for Brazil, Russia, China, India, South Africa and Turkey (BRICS-T) countries. In this context, this study investigates energy consumption and real output in BRICS-T countries through panel cointegration.

The data include energy consumption and real output for BRICS-T countries and period of 1990–2014. The variables are transformed into natural logarithm. To analyze these data, this study employed Pedroni cointegration test, the second-generation panel cointegration test, Westerlund and Edgerton (2008) test and FMOLS test.

Results indicate that there is a bi-directional causality relationship between energy consumption and economic growth for BRICS-T countries. An increase in GDP leads to an increase in energy consumption and an increase in energy consumption leads to an increase in GDP.

This study used data that include the period of 1990–2014 for BRICS-T countries. So, further studies can use different periods of data or different countries.

This study provides important evidence that countries with strong growth performance need to follow bi-directional energy policies to increase both energy investments and ensure energy savings.

The purpose of this paper is to re‐examine the long‐run co‐movement and causal relationship between GDP and social security expenditures.

The paper uses panel data unit root tests and panel cointegration tests, as well as estimation techniques appropriate for heterogeneous panels such as fully modified OLS. Data are employed on 12 Asian countries from 1972 to 2000.

The cointegration test results show strong evidence in favor of the existence of a long‐run equilibrium cointegrating relationship between GDP, capital stock and social security expenditures after allowing for heterogeneous country effects. Regarding the panel‐based error correction model and the Granger causality test, there are long‐run, bi‐directional causal linkages between social security expenditures and economic growth. In addition to the robust test, they display similar results.

The paper shows that in every moment, economic growth must be based in the social welfare policy contiguously, and the economic growth process can allow the social welfare policy to proceed contiguously

The purpose of this paper was to examine the long-run causal relations between share price and dividend in the Indian market.

Panel vector error correction model is estimated to examine the long-run causal relations between share price and dividend. Prior to this, panel unit root tests and panel cointegration tests are carried out to test the unit root properties of the data and test for the existence of long-run cointegrating relationship between the variables, respectively.

The results of empirical investigation reveal that there exists bi-directional long-run causality between share price and dividends.

For the chosen sample, data on share price are available only for limited years. This limits the time dimension of the sample. Hence, in the future, the analysis can be extended to cover longer time series.

The interplay between share prices and dividends needs to be given due consideration by firms while framing their policies. A change in dividend policy would have an effect on the market value of the firm; hence, firms need to frame dividend policy in such a way that it would enhance their market value. Similarly, investors need to take into consideration the influence of share prices and dividends on each other. While making investment decisions, they need to consider the dividend history of shares, as better dividends would lead to better share prices.

To the best of the authors' knowledge, this study is the first attempt in the Indian market to examine the long-run causal relations between share price and dividend. The results of this study would be helpful to the investors in taking wise investment decisions. It would also enable firms in formulating appropriate dividend policies.

This paper seeks to use empirical evidence to examine the role of Islamic banks' financing on economic performance of selected countries (Malaysia, Indonesia, Bahrain, UAE, Saudi Arabia, Egypt, Kuwait, Qatar and Yemen).

Using quarterly data (2000:1‐2010:4), this paper utilizes the panel cointegration approach models framework.

The results generally signify that, in the long run, Islamic banks' financing is positive and significantly correlated with economic growth and capital accumulation in these countries. The results obtained from the Granger causality test reveal a positive and statistically significant relationship between economic growth and Islamic banks' financing in the short run and in the long run. It also found that the long run relationship is stronger than the short run relationship.

This paper uses empirical evidence to show the effect of Islamic banks' financing on economic growth of selected Islamic countries. To the best of the authors' knowledge, most of the studies in this field have applied the bound testing approach of cointegration, error correction models (ECMs), Auto Regressive Distributed lag (ARDL) and Vector Autoregressive Model (VAR), and the coefficients obtained by these models cannot be deemed as a general finding applicable for other countries. The superiority of this article is in applying the FMOLS model, which has stable and consistent coefficients and is also a dynamic model.

This paper aims to use the newly developed panel data cointegration analysis and the dynamic time series modeling approach to examine the linkages between financial structure (market‐based vs bank‐based) and economic growth in African economies.

The research investigates the dynamic relationship between financial structure and economic growth in a panel of a group of seven African developing countries over the period of 1986‐2007. The paper uses various indicators/measures of financial structure and financial system, and employs the traditional time‐series analysis for causality as well as the newly developed panel unit root and cointegration techniques and estimated finance‐growth relationship using FMOLS for heterogeneous panel.

From the dynamic heterogeneous panel approach, the paper firstly finds that market‐based financial system is important for explaining output growth through enhancing efficiency and productivity. Second, the authors' empirical evidence supports the view that higher levels of banking system development are positively associated with capital accumulation growth and lead to faster rates of economic growth.

Panel cointegration, group mean panel FMOLS and country‐by‐country time series investigations indicate that the market‐based financial system is important for explaining output growth through enhancing efficiency and productivity, whereas the development of banking system is significantly associated with capital accumulation growth. Further results from the time‐series approach show evidence of unidirectional causality running from market‐oriented as well as bank‐oriented financial systems to economic growth.

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.

The purpose of this paper is to examine whether the purchasing power parity (PPP) holds for countries in the West African Monetary Zone (WAMZ).

The author uses time series and panel data techniques.

Overall, the evidence is inconclusive. The time series and panel unit root tests rejected the PPP. The time series cointegration test supported it. The panel cointegration tests are, however, inconclusive.

The inconclusive evidence implies that the appropriateness of the PPP-based policies which have been implemented in the WAMZ may be difficult to assess. Moreover, the question of whether the WAMZ agenda may face trade obstacles is still widely open. Perhaps fractional unit root and cointegration techniques may help pin down conclusive evidence. Future studies may consider this direction.

The paper is original in the sense that it is the first to utilize a mixture of time series and panel data techniques to examine the PPP hypothesis for these countries.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.