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The impacts of oil price shocks on tourism receipts for selected MENA countries: Do structural breaks matter?
Abstract
One of the short comings in the tourism literature is that research on the oil price-tourism receipts nexus is limited. However, the available studies, to the best of our knowledge, provide limited evidence on the negative effect of oil prices on tourism receipts. Nevertheless, the related literature did not consider the structural breaks in the analysis, which proven to be important in the empirical work. As such, in this paper, we study the oil price-tourism receipts nexus for selected MENA countries in the presence of structural breaks. This is done by adopting the autoregressive distributed lags (ARDL) bounds test and incorporating the structural breaks. The findings show that the bounds test provide evidence of a long-run relationship between tourism receipts and oil prices after integrating structural breaks into the ARDL model for most countries.
... Considering that oil prices are the direct driver of tourism supply and demand, tourism is highly dependent on oil prices. Theoretically, oil prices affect tourism activities directly and/or indirectly (Kisswani et al., 2020). The development of the tourism sector is one of the main strategies for diversification (Elhaj and Bousrih, 2021). ...
... The development of the tourism sector is one of the main strategies for diversification (Elhaj and Bousrih, 2021). Given that higher oil prices are inevitable, without understanding how oil prices affect tourism travel patterns, it is clear that it will be difficult for managers and policy makers to implement their anticipated tourism plans (Kisswani et al., 2020). ...
In this study, which is based on daily data, the relationship between BIST electricity index and BIST tourism index was measured between 2012:M9 – 2022:M9 periods. The aim of the study is to measure the relationship between BIST electricity index and BIST tourism index. VAR Granger causality test was applied to determine whether there is any causal relationship between the variables. It has been determined as a result of the analysis that the BIST electricity index has no effect on the BIST tourism index. Two-way ineffectiveness was determined among the variables. In addition, it was obtained as a result of the analysis that the applied correlation relationship was weak between these variables. The results obtained from the study are important in terms of measuring the effects among BIST indices.
... A null hypothesis 0 : 0 H is tested against an alternative hypothesis Kisswani et al. (2020) assert ...
Pollution haven hypothesis (PHH) assumes that polluting industries will move to regions with lesser rigorous environmental regulations. On the other hand, pollution halo hypothesis presumes that industries transfer their clean technologies through FDI inflows to the host countries. Following these theoretical perceptions, this paper empirically examines how foreign direct investment (FDI) affects pollution (CO2 emissions) for four selected Asian countries (Malaysia, Philippines, Singapore, Thailand) over the period 1971-2014. This is done by applying the autoregressive distributed lags (ARDL) model of Pesaran et al.. The ARDL model is employed under two scenarios: without and with structural breaks. The long-run findings, for both scenarios, suggest support for the pollution haven hypothesis (PHH) for the Philippines only. Whereas, the findings lend support for the pollution halo hypothesis for Malaysia and Singapore. In addition, the paper explores the causality direction between FDI and pollution (CO2 emissions) using the Vector Error Correction model (VECM). The results show mixed long- and short-run Granger causality findings.
This study explores the impact of the COVID-19 pandemic upon the performance of the U.S. travel and leisure stock, using daily data sets from December 31, 2019, to December 2, 2020. Applying the multifactor model, which is an extension of the capital asset pricing model, the study examines how governmental announcements and policy measures to contain the pandemic situation impact the stock prices controlling for confirmed cases, growth rates, and death rates owing to the pandemic. Further, to reduce the potential bias in heterogeneity, crucial macroeconomic regressors such as oil prices, exchange rates, and a volatility index are included. The study obtains a heterogeneous impact across quantiles. Government stringency measures negatively impact the travel and leisure stock prices, while the announcement of economic support programs positively impacts the stocks, particularly at the high-end quantiles. We advocate that the introduction of asset-light and fee-based strategies will enable the firms to overcome the adverse implications of the pandemic in the long run. This study offers major insights for protecting and developing the recovery of the travel and leisure stock market by considering the importance of government interventions and their effective implementation.
This study examines the oil price asymmetric influences on tourism (tourism receipts) for select MENA countries (namely: Egypt, Israel, Jordan, Lebanon, Morocco, Tunisia, and Turkey). Although annual sample data from 1995–2018 was collected, however, to be able to apply the asymmetric analysis, we transform the annual frequencies into quarterly series using the quadratic match-sum method that has been implemented in various empirical studies. The analysis employs the Shin et al. (2014) methodology known as the nonlinear autoregressive distributed lags (NARDL) model. The asymmetry is introduced via decomposing the oil price (\(P_{t}\)) to positive (\(P_{t}^{ + }\)) and negative (\(P_{t}^{ - }\)) changes. In addition, we take note of the data structural breaks, and incorporate the breaks within the NARDL model. The findings document evidence of long-run relationship (cointegration) among tourism receipts and the positive and negative changes of the oil price (\(P_{t}^{ + }\) and \(P_{t}^{ - }\)) for all seven countries. However, when testing for the long-run asymmetric influence, evidence was found just for Lebanon and Tunisia. In addition, when we analyze the short-run asymmetry, the NARDL results show evidence of asymmetric impact for Jordan, Lebanon, and Tunisia only. These results imply that decision makers should pay attention to the asymmetric influence of oil prices at tourism in the MENA countries, provided that tourism is an important injection to their GDP and that tourism industry is a good source of jobs that can be very helpful in designing policies for reducing unemployment whether in terms of number or gender-workers.
This study scrutinized the asymmetric impact of oil prices, exchange rate, and inflation on tourism demand in Pakistan using [Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014) Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of peter schmidt (pp. 281–314). New York, NY: Springer] nonlinear autoregressive distributed lag (NARDL) model. The NARDL bounds test examined the existence of cointegration in study variables, including CO2 emissions, institutional quality, oil prices, exchange rate, inflation, and tourism demand. The evidence proposes that disregarding the intrinsic nonlinearities may misinform inference. The estimated NARDL model affirmed long-run negative and significant effect of CO2 emissions on tourism demand, while institutional quality was positively associated with tourism demand. Furthermore, the findings of the study also suggested long-run asymmetric relationship between oil prices, exchange rate, inflation, and tourism demand.
We analyse data on the distances travelled using car and air transport modes in New Zealand by a large sample of international tourists from six different countries of origin. We use two-stage hurdle models to relate both the decision to use each mode and the distance travelled by a mode if used to visitor characteristics and prices. In general we find little evidence of price sensitivity for either decision, although older tourists, those with longer stays, and non-tour group travellers may be more price-sensitive. The most important characteristics for determining transport behaviour are shown to be length of stay, purpose of visit and travel style (tour vs non-tour).
Oral presentation for Advances in Tourism Research Stream at AIEST Conference 12-16 Sep 2010, Potchefstroom, South Africa. The International Association of Scientific Experts in Tourism, 60th AIEST Conference, Tourism Development after the Crises: Coping with Global Imbalances And Contributing to the Millennium Goals. The availability and price of oil are intimately linked to the global economy and as a result to tourism. This paper presents the results from research on tourism and oil, undertaken with a particular focus on New Zealand as a long haul destination in the light of dwindling global oil resources. The findings of four distinct research phases will be reported in an integrative analysis. The results highlight that economic prosperity in countries of origin, and in particular tourists’ income, is of critical importance for outbound tourism, especially to long haul destinations. The econometric analysis of in-country behaviour, such as consumption and regional dispersion, reveal that variables such as country of origin, travel purpose or length of stay are currently more important determinants of travel behaviour than fuel prices. Coupled with differentiated oil vulnerabilities by different countries and different levels of price elasticity, the importance of market mix becomes evident. Tourism businesses can reduce their oil vulnerability by addressing a range of risk factors. Government policy and industry initiatives can support these micro economic adaptation processes. Little research is available on the importance of oil shocks for tourism and this paper is an attempt to address this gap. The findings are specific to New Zealand but will be of interest to other long-haul destinations. The analysis integrates across a range of research methods. The research was funded by the Foundation for Research, Science and Technology, New Zealand (contract LINX0704).
The saving and investment nexus as postulated by Feldstein and Horioka (FH) (19806.
Feldstein , MS and
Horioka , CY . 1980. Domestic saving and investment capital flows. Economic Journal, 90: 314–29. [CrossRef], [Web of Science ®]View all references) is revisited. The saving investment correlation for China is estimated over the periods 1952–1998 and 1952–1994, the latter culminating in a period of fixed exchange rate regime. Amongst the key results, it is found that saving and investment are correlated for China for both the period of the fixed exchange rate and the entire sample period. With high saving-investment correlation, the results suggest that the Chinese economy is in conformity with the FH hypothesis. This is a valid outcome, for in China capital mobility was fairly restricted over the 1952–1994 period as indicated by the relatively low foreign direct investment.
Few papers have examined the effect of oil prices on tourism receipts and the sensitive susceptibility of tourism to oil price changes. Little attention was paid to examining the asymmetrical effect of oil prices on tourism receipts, testing whether the positive innovations in oil prices has the same effect as their negative counterparts. As such, this paper sheds light on the asymmetrical association of the tourism receipts-oil price nexus for 19 randomly-selected international destinations due to data availability, between 1995 and 2015. This was done by employing the non-linear autoregressive distributed lags (NARDL) model. The empirical findings document a long-run asymmetrical effect, after incorporating the structural breaks, in the case of Austria, France, United Kingdom, Greece, Iceland, Italy, Luxemburg, Norway, Portugal, Sweden and the United States, although the long-run relationship (cointegration) was found for all countries, except for Finland. Furthermore, the short-run asymmetrical impact was detected in the case of Austria, United Kingdom, Portugal, Sweden and the United States. This suggests that governments and tourism businesses and organizations should interpret oil price fluctuations cautiously.
This study investigates the GDP–energy consumption nexus for five Asian countries (ASEAN-5) during the 1971–2013 period by estimating the asymmetric long-run as well as short-run effects in a cointegration framework. We apply the recently developed nonlinear autoregressive distributed lags (NARDL) model of Shin et al. (2011) for individual country-by-country analysis. Meanwhile, we employ the pooled mean group (PMG) estimator of Pesaran and Smith (1995) and Pesaran et al. (1999) for the ASEAN-5 countries pooled as a panel set. The empirical results, in case of country-by-country, show long-run asymmetry for Singapore and Thailand only, when considering structural breaks. However, the panel analysis confirms asymmetry for the sample data. Finally, the causality tests employed show mixed results for both set-ups: country-by-country and panel sample.
This article explores the time-varying causal nexus between tourism development and economic growth for the top 10 tourist destinations in the world, namely China, France, Germany, Italy, Mexico, the Russian Federation, Spain, Turkey, the UK and the United States of America, over the period 1990–2015. To that end, a bootstrap rolling window Granger causality approach based on the modified Granger causality test is used. A new index for tourism activity which combines via principal component analysis the commonly used tourism indicators is also employed. The results of the bootstrap rolling window causality tests reveal that the causal relations between tourism and economic growth vary substantially over time and across countries in terms of both magnitude and direction. It is shown that the causal linkages tend to be more pronounced for a large group of countries following the global financial crisis of 2008. Additionally, Germany, France and China clearly stand out as the countries with the weakest causal nexus, while the UK, Italy and Mexico emerge as the countries that have the strongest causal links. These results have particularly important implications for policymakers.
This paper investigates the asymmetric relationship between energy consumption and economic growth by incorporating financial development, capital and labour into a production function covering the Indian economy from 1960Q1–2015Q4. The nonlinear autoregressive distributed lag bounds testing approach is applied to examine the asymmetric cointegration between the variables. An asymmetric causality test is also employed to examine the causal association between the considered variables. The results indicate cointegration between the variables in the presence of asymmetries. The asymmetric causality results show that only negative shocks to energy consumption have impacts on economic growth. In the same vein, only negative shocks to financial development have impacts on economic growth. By contrast, symmetrically, capital formation causes economic growth. Finally, over the study period, a neutral effect exists between the labour force and economic growth in India. The implications of these results for growth policies in India are also discussed.
This study investigates the relationship between oil price movements and macroeconomic aggregates, such as gross domestic product (GDP), consumer prices (CPI), and unemployment, for OECD countries. To do this, second generation econometric methods have been employed to panel data including panel unit root tests, panel cointegration tests, and panel long-run models. Panel unit root tests suggest that oil prices plus selected macroeconomic aggregates in OECD countries are non-stationary at levels but become stationary at first differences in the existence of multiple structural breaks. Five structural break points have successfully been investigated in the series of this study during panel unit root and panel cointegration tests. Durbin–H panel co-integration tests confirm that there is a long-term relationship between oil prices and those macroeconomic aggregates. On the other hand, results of this study reveal that the price of oil exerts statistically and negatively significant impacts on GDP, CPI, and unemployment in the case of OECD countries in general.
This paper explores the relationship between electricity consumption, foreign direct investment, capital and economic growth in the case of the Kingdom of Bahrain. The Cobb–Douglas production is used over the period of 1980Q1–2010Q4. We have applied the ARDL bounds testing approach and found that cointegration exists among the series. Electricity consumption, foreign direct investment and capital add in economic growth. The VECM Granger causality analysis has exposed the feedback effect between electricity consumption and economic growth and the same is true for foreign direct investment and electricity consumption. This study suggests government authorities to explore new sources of energy to achieve sustainable economic development for the long run.
It is expected that global oil prices will increase in the future. Assessing the overall economic impacts on tourism is difficult, as oil price rises will be concomitant with global changes in other commodity prices, exchange rates, and incomes. A general equilibrium perspective is therefore presented in this paper. The model couples a global general equilibrium model with a purpose-built CGE model of New Zealand, which focuses on describing tourism supply and demand in some detail. The results indicate a decrease in real gross national disposable income of 1.7% for a doubling of oil price and a 9% reduction in the real value of tourism exports. As a result of segment-specific price increases and differing income and exchange rate effects and elasticities, the reduction in demand for tourism in New Zealand by 18 segments differs substantially. The greatest reduction in demand is observed for tourists from the United Kingdom.
While the interrelation between oil price changes, economic activity and employment is an important issue that has been studied mainly for developed countries, little attention has been devoted to inquiries on fluctuations in the price of crude oil and its impact on employment for small open economies. Adopting an efficiency wage model for equilibrium employment that does not require any assumptions regarding labor supply, this paper contributes to the literature by investigating the causality between unemployment and two input prices, namely energy (crude oil) and capital (real interest rate) in an emerging market, Turkey for the period 2005:01-2009:08. Applying a relatively new technique, the Toda-Yamamoto procedure, we find that the real price of oil and interest rate improve the forecasts of unemployment in the long run. This finding supports the hypothesis that labor is a substitute factor of production for capital and energy.
Over the next 10 years, Scottish tourism is expected to grow by 50%. One of the keys to that growth is transport which is a sector that is dependent upon oil. This paper considers oil and the global economy and its relationship to Scottish tourism. Consideration is given to the key variables such as oil forecasts, security of supply, cost of production, world demand, alternative forms of energy including renewables and nuclear power.The combination of these facts means that high oil prices are here to stay. Two scenarios are constructed called Energy Inflation and Paying for Climate Change. These were developed using a triangulation of methods including the use of systems thinking models to construct the scenarios to computable general equilibrium modelling to analyse the impact of oil and energy price rises on Scottish tourism.The Energy Inflation scenario presumes mass belief in the plenitude of available oil reserves and the failure to respond quickly enough to alter demand. This triggers a sudden and prolonged period of economic shocks, political instability and environmental disasters. The Paying for Climate Change scenario assumes rising energy prices, combined with conservation measures such as carbon taxes. Both scenarios raise a number of policy issues for the future including oil and fossil fuels being the main sources of energy as there is no real alternative. Renewables and nuclear power will continue to grow and countries will try to reduce further their reliance on oil. Rising oil prices are also noted as a positive feature, driving innovation and new technologies, which will become more economic as oil prices rise. For Scottish tourism, the impact of rising oil prices could mean a bumpy ride with carbon taxes, more wind farms and the possible end of the low cost carrier.
In its present form, tourism is dependent on the availability of oil and is comparatively oil-intensive. While forecasts for future tourism growth are optimistic, there is also increasing evidence about the imminence of a peak in oil production and the economic effects that this would cause. Globally and on a destination level it will be necessary to consider how a transition towards fossil-fuel free economies might look like for tourism.It is therefore timely and prudent for the tourism sector to consider its current oil requirements and derive indicators for monitoring its oil consumption. In particular, destinations need indicators of the amount of oil consumed by the various markets from which they receive visitors. New Zealand is used as an example for assessing the oil-intensity of its Top 10 countries of origin based on the 10 indicators. Overall, the least exposed markets for New Zealand with respect to oil are Australia, China, Singapore, and Taiwan, although a more detailed analysis would be required for markets that display very heterogeneous travel behaviour. Among the indicators, eco-efficiency is particularly important as it allows comparison of resource inputs with economic outputs.
Many papers have been documenting and analysing the asymmetry and the weakening of the oil price–macroeconomy relationship as off the early eighties. While there seems to be a consensus about the factors causing the asymmetry, namely adjustment costs which offset the benefits of low energy prices, the debate about the weakening of the relationship is not over yet. Moreover, the alternative oil price specifications which have been proposed by Mork (1989), Lee et al. (1995), and Hamilton (1996) to restore the stability of the relationship fail to Granger cause output or unemployment in post-1980 data. By using the concept of accelerations of the oil price, we show that the weakening of this relationship corresponds to the appearance of slow oil price increases, which have less impact on the economy. When filtering out these slow oil price variations from the sample, we manage to rehabilitate the causality running from the oil price to the macroeconomy and show that far from weakening, the oil price accelerations–GDP relationship has even been growing stronger since the early eighties.
This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.
Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. The asymptotic distributions of the tests depend on a trimming parameter ε and critical values were tabulated for ε= 0.05. As discussed in Bai and Perron (2000), larger values of ε are needed to achieve tests with correct size in finite samples, when allowing for heterogeneity across segments or serial correlation in the errors. The aim of this paper is to supplement the set of critical values available with other values of ε to enable proper empirical applications. We provide response surface regressions valid for a wide range of parameters.
The purpose of this paper is to investigate the tests of Hansen (1992) to detect structural breaks in cointegrated relations using Monte Carlo methods. The evaluation takes place within the linear quadratic model. We study models that generate cointegrated relations with single and multiple regressors. The evidence with multiple regressors suggests that the tests have proper size but the power is low when the cost of adjustment is high. In addition to the tests of Hansen, we consider the sensitivity of the augmented Dickey-Fuller (ADF) test for cointegration in the presence of a structural break. Given a break, our Monte Carlo experiments show that the rejection frequency of the ADF test decreases substantially. Thus the ADF test correctly indicates that the constant parameter cointegrating relationship is not appropriate.
This paper develops the statistical theory for testing and estimating multiple change points in regression models. The rate of convergence and limiting distribution for the estimated parameters are obtained. Several test statistics are proposed to determine the existence as well as the number of change points. A partial structural change model is considered. The authors study both fixed and shrinking magnitudes of shifts. In addition, the models allow for serially correlated disturbances (mixingales). An estimation strategy for which the location of the breaks need not be simultaneously determined is discussed. Instead, the authors' method successively estimates each break point.