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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.

This paper aims to study the relationship between employment and tourism activities as well as economic variables for the 32 states of Mexico for the period 1999-2014.

To study the case of Mexico, the authors use panel data and cointegration panel data. They also use geographic information systems to observe changes over time between the variables, which is useful in the empirical evidence.

The main results obtained by the models are as following: domestic tourism is the variable with the greatest impact on the generation of direct employment in the tourism sector, a finding supported by both methodologies; economic growth (measured by state gross domestic product) also directly impacts the generation of employment; and the cointegration of the panels causes a long-term equilibrium among the states and some variables.

The model used leaves out other variables that may influence the performance of the tourist activity. In addition, given the availability of official and homogeneous information, it only covers what has been documented up to 2014.

The aim is to measure the impact of tourism on the variables at the state level, where the economic activities could be based on public policies, as well as the importance of tourism activities in generating employment. In this sense, the impact would be in channeling efforts to support the main economic activities and could serve as a starting point for the evaluation of programs to promote domestic tourism.

This paper reviews the relationship that exists between tourism activity and its effect on other variables, especially employment. It is the first time that these topics are studied for the Mexican economy.

This study aims to examine the effects of energy consumption on economic growth by means of a panel data analysis of 75 net energy-importing countries for the period 1990 to 2012.

For the purpose of the analysis, the countries are classified into two groups, and each group is then classified into subgroups. The first group is formed based on the energy import dependence of the countries and is classified into two subgroups according to whether their dependence is greater than or less than 50 per cent. The second group is formed based on the income level of the countries and is classified into four subgroups, specifically, low-income economies, lower-middle-income economies, upper-middle-income economies and high-income economies.

The findings obtained for both panel data and for each country indicate that there is a positive and statistically significant relationship between energy consumption and economic growth over the long term such that energy consumption contributes more to economic growth as the import dependence of the country decreases. Moreover, the effect of energy consumption on economic growth decreases as the income level of the country increases. This indicates that the efficient use of energy is as important as energy consumption, which is regarded as an important indicator of economic development.

The authors expect that these findings will make a valuable contribution to the results of future studies, as they analyze the relationships among the variables by including the energy intensities of the countries.

Este estudio examina los efectos del consumo de energía en el crecimiento económico, mediante un análisis de datos de panel de 75 países importadores netos de energía para el período 1990-2012.

A los efectos del análisis, los países se clasifican en dos grupos y cada grupo luego se clasifica en subgrupos. El primer grupo se forma en base a la dependencia de los países en materia de importación de energía y se clasifica en dos subgrupos según su dependencia sea superior o inferior al 50%. El segundo grupo se forma sobre la base del nivel de ingresos de los países y se clasifica en cuatro subgrupos: economías de ingresos bajos, economías de ingresos medios-bajos, economías de ingresos medios-altos y economías de ingresos altos.

Los hallazgos obtenidos, tanto para los datos de panel como para cada país, indican que existe una relación positiva y estadísticamente significativa entre el consumo de energía y el crecimiento económico a largo plazo, de modo que el consumo de energía contribuye más al crecimiento económico a medida que disminuye la dependencia de las importaciones del país. Además, el efecto del consumo de energía en el crecimiento económico disminuye a medida que aumenta el nivel de ingresos del país. Esto indica que el uso eficiente de la energía es tan importante como el consumo de la misma, que se considera un indicador importante del desarrollo económico.

Los autores esperan que estos hallazgos aporten una valiosa contribución para estudios futuros, ya que analizan las relaciones entre las variables mediante la inclusión de las intensidades de los países.

Consumo de energía, Crecimiento económico, Importadores netos de energía, Panel de datos

Artículo de investigación

The purpose of this paper is to examine the relationship between financial development, openness in financial services trade and economic growth in BRICS countries for the period 1990–2012.

An index for financial development has been constructed using principal component analysis technique by including banking sector development, stock market development, bond market development and insurance sector development. For the robustness of the result, the long-run cointegrating relationship amongst the variables has been analyzed.

Overall financial development has a positive and significant impact on economic growth. To take the full advantage of openness in financial services trade, countries need to put more emphasis on the development of their stock markets, bond markets and the insurance sector. The result shows that openness in financial services trade has a positive impact on economic growth when the stock market, bond market and insurance sector are included in the system.

The policy implication of the findings is that policymakers should focus more on developing all four areas of finance to get the full benefit of the financial system on the process of economic growth.

The authors have constructed the better indicators of financial development in the case of BRICS economies. Most of the studies in BRICS economies have measured the development of the financial sector as either banking sector development or stock market development. However, the present study includes all four areas of finance (banking sector development, stock market development, insurance sector development and bond market development) into account.

This study aims to examine the influence of socioeconomic development on inflation in South Asia using the foreign exchange rate and money supply as control variables.

The study uses annual panel data for five South Asian economies, namely, Bangladesh, India, Nepal, Pakistan and Sri Lanka over the period 1990–2018, applies cointegrating regression techniques, namely, the panel dynamic ordinary least square (OLS) and fully modified OLS estimators to examine the long-run relations and conducts the Toda-Yamamoto Granger causality test to detect the direction of causality among variables.

The cointegrating regression estimations have documented that the socioeconomic development proxied by the human development index (HDI) has no significant impact on inflation. Although economic development represented by gross domestic product (GDP) growth causes inflation, socioeconomic development represented by HDI has no impact on inflation and has demonstrated as a better macroeconomic indicator, and thus creates no inflationary pressure in the economy. The foreign exchange rate has a positive impact on inflation. The broad money supply has the usual positive effect on domestic inflation that endorses the monetarist view about prices. The Toda-Yamamoto Granger causality test has confirmed several unidirectional causalities: inflation causes HDI, money supply causes both inflation and HDI and the foreign exchange rate causes HDI.

The study has practical implications for policymakers in South Asia, to improve HDI, particularly GDP per capita, education and health-care facilities to realize continuous socioeconomic development, which will take care of inflation. Moreover, these counties may follow a conservative monetary policy to control inflationary pressure in their economies.

The study is original and claims to be the first to examine the impact of socioeconomic development on inflation. The findings have socioeconomic values regarding controlling inflation in South Asia.

This study investigated the impact of economic growth on carbon emissions on selected West African countries between 1980 and 2019. Simon-Steinmann's economic growth model provides the relevant theoretical foundation. The main objective of this study was to ascertain whether economic growth will impact carbon emissions.

The study selected six-sample countries in West Africa and used secondary data obtained through the World Bank Group online database covering the period 1980–2019, employing panel econometric methods of statistical analysis.

The outcome indicates that the independent variable showed a positively significant impact on the dependent variable for the pooled samples in the short-run, with significant cointegration.

The study concluded that economic growth significantly impacts the emissions of carbon, and a 1% rise in economic growth will result to 3.11121% unit rise in carbon emissions.

Policy implementation should encourage the use of energy efficient facilities by firms and government and the establishment of carbon trading hubs.

Failure by governments to heed the recommendations of this research will result to serious climate change issues on economic activities with attendant consequences on human health within the region and globally.

This is one of the comprehensive works on subject covering the West African region within the continent.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

This study examines whether international tourism demand in the Visegrád countries is influenced by countries' risk rating on environmental, social and governance (ESG) factors, as non-economic factors relating to ESG risks have been ignored by previous researches on determinants of international tourism demand.

The study investigates panel data for the Visegrád countries comprising the Czech Republic, Hungary, Poland and Slovakia over the period 1995–2019. Recently developed techniques of augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators are employed so as to take care of cross-sectional dependence, nonstationary residuals and possible heterogeneous slope coefficients.

The regression estimates suggest that besides economic factors, the perception of international tourists regarding ESG risk is another important determinant of international tourism demand in the Visegrád countries. The study also established that income levels in the tourists' originating countries are the most critical determinant of international tourism demand to the Visegrád countries.

The research outcomes of the study include the need for the Visegrád countries to direct policies towards further mitigating their ESG risks in order to improve future international tourism demand in the area. They also need to ensure exchange rate stability to prevent volatility and sudden spikes in the relative price of tourism in their countries.

This study examines the causal relationship between exports and economic growth in sub-Saharan African (SSA) countries during the period 1980 to 2017. The study also examines whether the causality between these two macroeconomic variables depends on the countries' stage of development as proxied by their per capita income.

The study uses a panel cointegration test and panel Granger-causality model to examine the link between exports and growth. The study also incorporates external debt as an intermittent variable in a bivariate setting between exports and economic growth, thereby creating a dynamic multivariate panel Granger-causality model.

Although the study found the existence of a long-run relationship between exports and economic growth, the study failed to find any export-led growth response in both low-income and middle-income countries. Instead, the study found evidence of a bidirectional causality and a neutrality response in middle-income and low-income countries, respectively. The study, therefore, concludes that the benefits of an export-led growth hypothesis may have been oversold, and that the strategy may not be desirable to some low-income developing countries.

These findings have important policy implications as they indicate that the causality between exports and economic growth in SSA countries varies with the countries' stage of development. Consistent with the contemporary literature, the study cautions low-income SSA countries against over-relying on an export-led growth strategy to achieve a sustained growth path as no causality between exports and economic growth has been found to exist in those countries. Instead, such countries should consider pursuing new growth strategies by building the domestic demand side of their economies alongside their export promotion strategies in order to expand the real sector of their economies. For middle-income countries, the study recommends that both export promotion strategies and pro-growth policies should be intensified as economic growth and exports have been found to reinforce each other in those countries.

Unlike the previous studies, the current study disaggregated the full sample of SSA countries into two subsets – one comprising of low-income countries and the other consisting of middle-income countries. In addition, the study uses a multivariate Granger-causality model in order to address the emission-of-variable bias. To our knowledge, this may be the first study of its kind in recent years to examine in detail the causal relationship between exports and economic growth in SSA countries using an ECM-based multivariate panel Granger-causality model.

本研究旨在探討在1980年至2017年期間撒哈拉以南非洲國家的出口、與其經濟增長之間的因果關係，亦探討這兩個宏觀經濟變量之間的因果關係、會否取決於有關國家所處以人均收入來衡量的發展階段。

本研究雖然發現出口與經濟增長存有一個長期性關係，唯未能於低收入國家或中等收入國家、找到任何出口帶動的增長反應。研究反而找到證據，證實中等收入國家為一雙向性因果關係反應，而低收入國家則為一中立性反應。因此，研究的結論是：出口必能帶動經濟增長這假設被過度吹噓，而且，對部份低收入發展中國家而言，實施以出口帶動經濟增長的策略或許是沒有用的。

本研究的結果在政策方面有其重要意義。這是因為研究結果顯示、於撒哈拉以南非洲國家、出口與經濟增長之間的因果關係，會因有關國家所處的發展階段而有所變更。與當代文獻一樣，本研究提醒低收入的撒哈拉以南非洲國家，不要過度依賴以出口帶動增長的策略來謀求踏上持續增長之路，這是因為在這些國家，出口與經濟增長之間的因果關係仍未確立。他們反而應考慮推行新增長經濟策略，方法是在實施推動出口的策略的同時，也要建立其經濟的國內需求面，以擴大其經濟實業部門。就中等收入國家而言，本研究建議他們應增強推動出口的策略及強化促進增長的政策，這是因為在這些國家裏，經濟增長及出口已被證實會互為增強。

有別於過去的研究，本研究把撒哈拉以南非洲國家的整體樣本分解為兩個子集：一個包括低收入國家，另一個則包括中等收入國家。而且、研究使用了多變量面板格蘭傑因果關係模型、以處理遺漏變數偏差的問題。據我們了解，這大概是近年首個同類研究、以基於歐洲共同市場多變量面板格蘭傑因果關係模型、來詳細探討於撒哈拉以南非洲國家、出口與經濟增長之間的因果關係。