# Implications of Oil Price Fluctuations for Tourism Receipts: The Case of Oil Exporting Countries

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Data and Methodology

#### 3.1. Data and Variables

#### 3.2. Methodology

#### 3.2.1. Cross-Sectional Dependency Test

#### 3.2.2. Panel Unit Root Tests

#### 3.2.3. Panel Cointegration Test

#### 3.2.4. Panel Granger Non-Causality Test

- ${H}_{0}:\text{}{\beta}_{i}=0,\text{}{\forall}_{i}=1,\dots ,\text{}$;
- ${H}_{1}:\text{}{\beta}_{i}=0,\text{}{\forall}_{i}=1,\dots ,\text{}{N}_{1}\text{}\left(0\le \frac{N1}{N}1\right)\text{};$
- ${H}_{1}:\text{}{\beta}_{ii}\ne 0,\text{}{\forall}_{i}={N}_{1}+1,\text{}{N}_{2}+2\dots ,\text{}N$.

_{0}=$\text{}{\beta}_{i}$= 0.

## 4. Empirical Findings

#### 4.1. Descriptive Statistics

#### 4.2. Cross-Sectional Dependency Test Results

#### 4.3. Panel Unit Root Test

#### 4.4. Panel Cointegration Test Results

#### 4.5. Panel Causality Test

#### 4.6. Robustness Check

_{(t−1)}) was positive in models and statistically significant. The speeds of adjustments (λ) for models (1) and (2) are 15% and 8%, respectively. Low speed of adjustments in model 1 and 2 reveal that attaining the target tourism income is not the primary concern of countries heavily relying on crude oil exports.

## 5. Summary and Conclusions

## 6. Policy Implication

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Becken, S. Developing indicators for managing tourism in the face of peak oil. Tour. Manag.
**2008**, 29, 695–705. [Google Scholar] [CrossRef] [Green Version] - Bandekar, B.; Sankaranarayanan, K.G. Contribution of Tourism Sector to India’s GDP. J. Radix Int. Educ. Res. Consort.
**2014**, 3, 1–11. [Google Scholar] - World Travel and Tourism Council (WTTC). Economic Impact of Tourism. 2016. Available online: http://www.wttc.org/research/economic-research/economic-impact-analysis (accessed on 24 April 2020).
- World Travel & Tourism Council (WTTC). Retrieved 5 October 2019. Available online: https://www.wttc.org/-/media/files/reports/economic-impact-research/regions-2019/world2019.pdf (accessed on 24 April 2020).
- World Tourism Organization of the United Nations (UNWTO). Tourism Highlights. 2016. Available online: http://www.e-unwto.org/doi/book/10.18111/9789284418145 (accessed on 24 April 2020).
- Ghosh, A.R.; Ostry, J.D. Export instability and the external balance in developing countries. Staff Pap.
**1994**, 41, 214–235. [Google Scholar] [CrossRef] - Gylfason, T. From Double Diversification to Efficiency and Growth. Comp. Econ. Stud.
**2017**, 59, 1–20. [Google Scholar] [CrossRef] - Fletcher, J.; Fyall, A.; Gilbert, D.; Wanhill, S. Tourism Principles and Practice, 5th ed.; Pearson Education: London, UK, 2013. [Google Scholar]
- Sharpley, R. The challenges of economic diversification through tourism: The case of Abu Dhabi. Int. J. Tour. Res.
**2002**, 4, 221–235. [Google Scholar] [CrossRef] - Hartwick, J.M. Intergenerational equity and the investing of rents from exhaustible resources. Am. Econ. Rev.
**1977**, 67, 972–974. [Google Scholar] - Gunn, C.A.; Var, T. Tourism Planning: Basics, Concepts, Cases; Routledge: New York, NY, USA, 2002. [Google Scholar]
- Ghalia, T.; Fidrmuc, J. The curse of tourism? J. Hosp. Tour. Res.
**2018**, 42, 979–996. [Google Scholar] [CrossRef] [Green Version] - Katircioglu, S.T. Revisiting the tourism-led-growth hypothesis for Turkey using the bounds test and Johansen approach for cointegration. Tour. Manag.
**2009**, 30, 17–20. [Google Scholar] [CrossRef] - Shahbaz, M.; Kumar, R.R.; Ivanov, S.; Loganathan, N. The nexus between tourism demand and output per capita with the relative importance of trade openness and financial development: A study of Malaysia. Tour. Econ.
**2017**, 23, 168–186. [Google Scholar] [CrossRef] [Green Version] - De Vita, G. The long-run impact of exchange rate regimes on international tourism flows. Tour. Manag.
**2014**, 45, 226–233. [Google Scholar] [CrossRef] - Cheng, K.M.; Kim, H.; Thompson, H. The exchange rate and US tourism trade, 1973–2007. Tour. Econ.
**2013**, 19, 883–896. [Google Scholar] [CrossRef] [Green Version] - Vita, G.D.; Kyaw, K.S. Role of the exchange rate in tourism demand. Ann. Tour. Res.
**2013**, 43, 624–627. [Google Scholar] [CrossRef] - Tang, J.; Sriboonchitta, S.; Ramos, V.; Wong, W.K. Modelling dependence between tourism demand and exchange rate using the copula-based GARCH model. Curr. Issues Tour.
**2016**, 19, 876–894. [Google Scholar] [CrossRef] - Kreishan, F.M. Tourism and economic growth: The case of Jordan. Eur. J. Soc. Sci.
**2010**, 15, 63–68. [Google Scholar] - Tang, C.F.; Abosedra, S. Small sample evidence on the tourism-led growth hypothesis in Lebanon. Curr. Issues Tour.
**2014**, 17, 234–246. [Google Scholar] [CrossRef] - Tang, C.F.; Abosedra, S. The impacts of tourism, energy consumption and political instability on economic growth in the MENA countries. Energy Policy
**2014**, 68, 458–464. [Google Scholar] [CrossRef] - Becken, S. Oil, the global economy and tourism. Tour. Rev.
**2011**, 66, 65–72. [Google Scholar] [CrossRef] [Green Version] - Yeoman, I.; Lennon, J.J.; Blake, A.; Galt, M.; Greenwood, C.; McMahon-Beattie, U. Oil depletion: What does this mean for Scottish tourism? Tour. Manag.
**2007**, 28, 1354–1365. [Google Scholar] [CrossRef] - Becken, S.; Ngyen, M.; Schiff, A. Developing an Economic Framework for Tourism and Oil; LEaP Report; Lincoln University: Christchurch, New Zealand, 2010; p. 12. Available online: www.lincoln.ac.nz/leap (accessed on 24 April 2020).
- Chatziantoniou, I.; Filis, G.; Eeckels, B.; Apostolakis, A. Oil prices, tourism income and economic growth: A structural VAR approach for European Mediterranean countries. Tour. Manag.
**2013**, 36, 331–341. [Google Scholar] [CrossRef] [Green Version] - Cheng, M.; Chung, L.; Tam, C.S.; Yuen, R.; Chan, S.; Yu, I.W. Tracking the Hong Kong Economy. Occas. Pap.
**2012**, 3, 2012. [Google Scholar] - Logar, I.; van den Bergh, J.C. The impact of peak oil on tourism in Spain: An input–output analysis of price, demand and economy-wide effects. Energy
**2013**, 54, 155–166. [Google Scholar] [CrossRef] [Green Version] - Kisswani, K.M.; Zaitouni, M.; Moufakkir, O. An examination of the asymmetric effect of oil prices on tourism receipts. Curr. Issues Tour.
**2020**, 23, 500–522. [Google Scholar] [CrossRef] - Becken, S.; Lennox, J. Implications of a long-term increase in oil prices for tourism. Tour. Manag.
**2012**, 33, 133–142. [Google Scholar] [CrossRef] [Green Version] - Lennox, J. Impacts of high oil prices on tourism in New Zealand. Tour. Econ.
**2012**, 18, 781–800. [Google Scholar] [CrossRef] - Huang, X.; Silva, E.; Hassani, H. Causality between oil prices and tourist arrivals. Stats
**2018**, 1, 10. [Google Scholar] [CrossRef] [Green Version] - Mønster, D.; Fusaroli, R.; Tylén, K.; Roepstorff, A.; Sherson, J.F. Causal inference from noisy time-series data—Testing the Convergent Cross-Mapping algorithm in the presence of noise and external influence. Future Gener. Comput. Syst.
**2017**, 73, 52–62. [Google Scholar] [CrossRef] [Green Version] - Katircioglu, S.; Katircioglu, S.; Altun, O. The moderating role of oil price changes in the effects of service trade and tourism on growth: The case of Turkey. Environ. Sci. Pollut. Res.
**2018**, 25, 35266–35275. [Google Scholar] [CrossRef] - Al-Mulali, U.; Gholipour, H.F.; Al-hajj, E. The nonlinear effects of oil prices on tourism arrivals in Malaysia. Curr. Issues Tour.
**2020**, 23, 942–946. [Google Scholar] [CrossRef] - Meo, M.S.; Chowdhury, M.A.F.; Shaikh, G.M.; Ali, M.; Masood Sheikh, S. Asymmetric impact of oil prices, exchange rate, and inflation on tourism demand in Pakistan: New evidence from nonlinear ARDL. Asia Pac. J. Tour. Res.
**2018**, 23, 408–422. [Google Scholar] [CrossRef] - Loganathan, N.; Streimikiene, D.; Mursitama, T.N.; Shahbaz, M.; Mardani, A. How Real Oil Prices and Domestic Financial Instabilities are Good for GCC Countries Tourism Demand in Malaysia? Econ. Sociol.
**2018**, 11, 112–125. [Google Scholar] [CrossRef] - Amin, S.B.; Kabir, F.A.; Khan, F. Tourism and energy nexus in selected South Asian countries: A panel study. Curr. Issues Tour.
**2019**, 1–5. [Google Scholar] [CrossRef] - World Bank. World Development Indicators (Web-Based Online Database); World Bank: Washington, DC, USA, 2018; Available online: http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators&preview=on (accessed on 24 April 2020).
- Organization of the Petroleum Exporting Countries (OPEC). Proceedings of the OPEC Annual Statistical Bulletin 2015; OPEC: Vienna, Austria, 2015; p. 50. [Google Scholar]
- Fayissa, B.; Nsiah, C.; Tadasse, B. Impact of tourism on economic growth and development in Africa. Tour. Econ.
**2008**, 14, 807–818. [Google Scholar] [CrossRef] [Green Version] - Adamou, A.; Clerides, S. Prospects and limits of tourism-led growth: The international evidence. Rimini Cent. Econ. Anal. WP 41-09
**2009**. [Google Scholar] [CrossRef] [Green Version] - Kyaw, K.S.; Macdonald, R. Capital flows and growth in developing countries: A dynamic panel data analysis. Oxf. Dev. Stud.
**2009**, 37, 101–122. [Google Scholar] [CrossRef] - Sanchez Carrera, E.J.; Brida, J.G.; Risso, W.A. Tourism’s impact on long-run Mexican economic growth. Econ. Bull.
**2008**, 23, 1–8. [Google Scholar] [CrossRef] [Green Version] - Das, J.; Dirienzo., C. Global tourism competitiveness and freedom of the press: A nonlinear relationship. J. Tour. Res.
**2009**, 47, 470–479. [Google Scholar] [CrossRef] - Johnson, T.; de Dios, E.; Martin, A.L. Governance and Institutional Quality and the Links with Economic Growth and Income Inequality: With Special Reference to Developing Asia; Asian Development Bank Economics Working Paper Series; Asian Development Bank: Mandaluyong, Philippines, 2010; p. 193. [Google Scholar]
- Saha, S.; Yap, G. The moderation effects of political instability and terrorism on tourism development: A cross-country panel analysis. J. Travel Res.
**2014**, 53, 509–521. [Google Scholar] [CrossRef] - Saha, S.; Yap, G. Corruption and tourism: An empirical investigation in a non-linear framework. Int. J. Tour. Res.
**2015**, 17, 272–281. [Google Scholar] [CrossRef] - Teorell, J.; Samanni, M.; Holmberg, S.; Rothstein, B. The quality of government dataset, version 6Apr11; The Quality of Government Institute, University of Gothenburg: Gothenburg, Sweden, 2011; Available online: http://www.qog.pol.gu.se (accessed on 24 April 2020).
- Song, H.; Witt, S.F. Forecasting international tourist flows to Macau. Tour. Manag.
**2006**, 27, 214–224. [Google Scholar] [CrossRef] [Green Version] - Rudez, H.N. The GDP impact on international tourism demand: A Slovenia based case. Tour. Hosp. Manag.
**2008**, 14, 217–228. [Google Scholar] - Baltagi, B.H. Econometric Analysis of Panel Data, 3rd ed.; JW & Sons: London, UK, 2005. [Google Scholar]
- Pesaran, M.H. A simple panel unit root test in the presence of cross-section dependence. J. Appl. Econom.
**2007**, 22, 265–312. [Google Scholar] [CrossRef] [Green Version] - Frees, E.W. Assessing cross-sectional correlation in panel data. J. Econom.
**1995**, 69, 393–414. [Google Scholar] [CrossRef] - Maddala, G.S.; Wu, S. A comparative study of unit root tests with panel data and a new simple test. Oxf. Bull. Econ. Stat.
**1999**, 61, 631–652. [Google Scholar] [CrossRef] - Levin, A.; Lin, C.F.; Chu, C.S.J. Unit root tests in panel data: Asymptotic and finite-sample properties. J. Econom.
**2002**, 108, 1–24. [Google Scholar] [CrossRef] - Im, K.S.; Pesaran, M.H.; Shin, Y. Testing for unit roots in heterogeneous panels. J. Econom.
**2003**, 115, 53–74. [Google Scholar] [CrossRef] - Pesaran, H.M. General Diagnostic Tests for Cross-Sectional Dependence in Panels; University of Cambridge, Cambridge Working Papers in Economics: Cambridge, UK, 2004; p. 435. [Google Scholar]
- Kao, C. Spurious regression and residual-based tests for cointegration in panel data. J. Econom.
**1999**, 90, 1–44. [Google Scholar] [CrossRef] - Engle, R.F.; Granger, C.W. Co-integration and error correction: Representation, estimation, and testing. Econom. J. Econom. Soc.
**1987**, 55, 251–276. [Google Scholar] [CrossRef] - Westerlund, J. Testing for error correction in panel data. Oxf. Bull. Econ. Stat.
**2007**, 69, 709–748. [Google Scholar] [CrossRef] [Green Version] - Dumitrescu, E.I.; Hurlin, C. Testing for Granger non-causality in heterogeneous panels. Econ. Model.
**2012**, 29, 1450–1460. [Google Scholar] [CrossRef] [Green Version] - Lee, C.C.; Chang, C.P. Tourism development and economic growth: A closer look at panels. Tour. Manag.
**2008**, 29, 180–192. [Google Scholar] [CrossRef] - Tugcu, C.T. Tourism and economic growth nexus revisited: A panel causality analysis for the case of the Mediterranean Region. Tour. Manag.
**2014**, 42, 207–212. [Google Scholar] [CrossRef] - Al-mulali, U.; Fereidouni, H.G.; Lee, J.Y.; Mohammed, A.H. Estimating the tourism-led growth hypothesis: A case study of the Middle East countries. Anatolia
**2014**, 25, 290–298. [Google Scholar] [CrossRef] - Dogru, T.; Bulut, U. Is tourism an engine for economic recovery? Theory and empirical evidence. Tour. Manag.
**2018**, 67, 425–434. [Google Scholar] [CrossRef] - Arellano, M.; Bond, S. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud.
**1991**, 58, 277–297. [Google Scholar] [CrossRef] [Green Version] - Blundell, R.; Bond, S. Initial conditions and moment restrictions in dynamic panel data models. J. Econom.
**1998**, 87, 115–143. [Google Scholar] [CrossRef] [Green Version] - Snieška, V.; Barkauskienė, K.; Barkauskas, V. The impact of economic factors on the development of rural tourism: Lithuanian case. Procedia-Soc. Behav. Sci.
**2014**, 156, 280–285. [Google Scholar] - Shahbaz, M.; Naeem, M.; Ahad, M.; Tahir, I. Is natural resource abundance a stimulus for financial development in the USA? Resour. Policy
**2018**, 55, 223–232. [Google Scholar] [CrossRef]

International Tourist Arrivals (1000) | International Tourism Receipts | |||||||
---|---|---|---|---|---|---|---|---|

2010 | 2016 | 2017 | Change (%) | (US$ million) | ||||

16/15 | 17/16 | 2010 | 2016 | 2017 | ||||

Middle East | 55,442 | 55,556 | 58,113 | −4.4 | 4.6 | 52,150 | 58,959 | 67,654 |

North Africa | 19,682 | 18,895 | 21,717 | 5.0 | 14.9 | 9662 | 9003 | 10,009 |

**Table 2.**International tourism receipts (in thousands) and tourist arrivals by country of destination.

2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | Average | |
---|---|---|---|---|---|---|---|---|---|

Algeria | |||||||||

Int. Tourism receipts | 324,000 | 300,000 | 295,000 | 326,000 | 316,000 | 347,000 | 246,000 | 172,000 | 290,750 |

Number of arrivals | 2070 | 2395 | 2634 | 2733 | 2301 | 1710 | 2039 | 2451 | 2292 |

Bahrain | |||||||||

Int. Tourism receipts | 2,163,000 | 1,766,000 | 1,752,000 | 1,875,000 | 1,913,000 | 2,372,000 | 4,021,000 | 3,836,000 | 2,462,250 |

Number of arrivals | 11,952 | 6732 | 8062 | 9163 | 10,452 | 9670 | 10,158 | 11,370 | 9695 |

Iran | |||||||||

Int. Tourism receipts | 2,631,000 | 2,489,000 | 2,483,000 | 3,306,000 | 4,197,000 | 4,771,000 | 3,914,000 | 398,714 | |

Number of arrivals | 2938 | 3354 | 3834 | 4769 | 4968 | 5237 | 4942 | 4867 | 4364 |

Kuwait | |||||||||

Int. Tourism receipts | 574,000 | 644,000 | 780,000 | 619,000 | 615,000 | 931,000 | 831,000 | 643,000 | 704,625 |

Number of arrivals | 5208 | 5574 | 5729 | 6217 | 6528 | 6941 | 7055 | 6179 | |

Oman | |||||||||

Int. Tourism receipts | 1,072,000 | 1,515,000 | 1,723,000 | 1,888,000 | 1,971,000 | 2,247,000 | 2,390,000 | 2,791,000 | 1,949,625 |

Number of arrivals | 1441 | 1018 | 1241 | 1392 | 1611 | 1909 | 2335 | 2372 | 1625 |

Qatar | |||||||||

Int. Tourism receipts | 4,463,000 | 7,220,000 | 8,452,000 | 10,576,000 | 12,131,000 | 12,593,000 | 15,757,000 | 10,170,286 | |

Number of arrivals | 1699.5 | 2056.7 | 2323.5 | 2611.9 | 2839.2 | 2941.1 | 2938.2 | 2256.5 | 2458 |

Saudi Arabia | |||||||||

Int. tourism receipts | 7,536,000 | 9,317,000 | 8,400,000 | 8,690,000 | 9,263,000 | 11,183,000 | 13,438,000 | 14,848,000 | 10,334,375 |

Number of arrivals | 10,850 | 14,179 | 16,332 | 15,772 | 18,260 | 17,994 | 18,044 | 16,109 | 15,943 |

UAE | |||||||||

Int. tourism receipts | 8,577,000 | 9,204,000 | 10,924,000 | 12,389,000 | 15,221,000 | 17,481,000 | 19,496,000 | 21,048,000 | 14,292,500 |

Number of arrivals | |||||||||

Yemen | |||||||||

Int. Tourism receipts | 1,291,000 | 910,000 | 1,005,000 | 1,097,000 | 1,199,000 | 116,000 | 116,000 | 819,143 | |

Number of arrivals | 1025 | 829 | 874 | 990 | 1017 | 366.7 | 850 |

Variable | Mean | SD | Min | Max |
---|---|---|---|---|

LTR | 20.78 | 1.29 | 17.45 | 23.36 |

LOIL | 4.04 | 0.54 | 3.19 | 4.65 |

GFC | 27.37 | 14.83 | 15.49 | 33.78 |

GEX | 2.79 × 10^{10} | 3.09 × 10^{10} | 2.38 × 10^{9} | 1.67 × 10^{11} |

GDPPC | 21,907.78 | 21,456.27 | 538.2873 | 94,944.09 |

EF | 61.579 | 9.814 | 35.9 | 77.7 |

I | 5.977 | 6.703 | −4.863 | 39.26 |

LTR | LOIL | GFC | GEX | GDPPC | EF | |
---|---|---|---|---|---|---|

LOIL | 0.264 | |||||

GFC | −0.458 | −0.362 | ||||

GEX | 0.519 | 0.385 | −0.240 | |||

GDPPC | 0.601 | 0.131 | −0.414 | 0.163 | ||

EF | 0.231 | 0.035 | −0.291 | −0.348 | 0.617 | |

I | 0.036 | 0.172 | 0.135 | 0.142 | −0.475 | −0.517 |

Pesaran (2004) | ||
---|---|---|

Statistic | p-Value | |

LTR | 7.460 | 0.000 |

LOIL | 5.832 | 0.000 |

GDPPC | 8.165 | 0.000 |

GFC | 14.00 | 0.000 |

GEX | 6.182 | 0.000 |

I | 11.55 | 0.000 |

EF | 8.177 | 0.000 |

Frees test of cross-sectional independence = 0.278 | ||

Note: Critical values from Frees’ Q distribution: | ||

α | Statistic | |

0.10 | 0.3583 | |

0.05 | 0.4923 | |

0.01 | 0.7678 |

M and W | LLC | IPS | CADF | |||||
---|---|---|---|---|---|---|---|---|

Levels | Statistic | p-Value | Statistic | p-Value | Statistic | p-Value | Statistic | p-Value |

LTR | 5.113 | 0.745 | 0.798 | 0.787 | 1.294 | 0.902 | −0.039 | 1.000 |

LOIL | 0.884 | 0.998 | 3.460 | 0.999 | 4.806 | 1.000 | −0.991 | 0.944 |

GDPPC | 0.265 | 1.000 | 1.387 | 0.917 | 6.814 | 1.000 | −2.202 | 0.181 |

GFC | 1.649 | 0.989 | −1.026 | 0.152 | 1.993 | 0.976 | −1.057 | 0.926 |

GEX | 11.722 | 0.164 | −1.233 | 0.108 | −2.103 | 0.136 | −1.998 | 0.312 |

I | 10.248 | 0.248 | −1.584 | 0.056 | −1.205 | 0.114 | −2.118 | 0.230 |

First Differences | ||||||||

LTR | 63.776 *** | 0.000 | −4.168 *** | 0.000 | −4.195 *** | 0.000 | −2.791 ** | 0.017 |

LOIL | 27.260 *** | 0.000 | −11.273 *** | 0.000 | −2.663 *** | 0.003 | −3.158 *** | 0.002 |

GDPPC | 16.822 ** | 0.032 | −2.351 *** | 0.009 | −1.738 ** | 0.041 | −2.869 ** | 0.011 |

GFC | 19.849 ** | 0.010 | −3.435 *** | 0.000 | −1.633 * | 0.051 | −2.947 *** | 0.007 |

GEX | −1.483 * | 0.075 | −4.147 *** | 0.000 | −1.564 * | 0.058 | −3.830 *** | 0.001 |

I | 58.141 *** | 0.000 | −6.942 *** | 0.000 | −4.239 *** | 0.000 | −2.912 *** | 0.009 |

Method | Statistic | p-Value | |
---|---|---|---|

Kao | MDF | −5.713 *** | 0.005 |

DF | −2.041 *** | 0.009 | |

ADF | −6.027 ** | 0.010 | |

Westerlund | G_{t} | −4.639 *** | 0.003 |

G_{a} | −3.527 * | 0.056 | |

P_{t} | −5.734 ** | 0.034 | |

P_{a} | −9.583 * | 0.064 |

Hypothesis | Wald Statistic | Z-Bar Statistic | p-Value | Causal Statistic |
---|---|---|---|---|

LOIL $\to $ LTR | 4.626 *** | 6.245 | 0.000 | YES |

LTR $\to $ LOIL | 0.834 | 1.053 | 0.170 | NO |

GDPPC $\to $ LTR | 3.126 *** | 5.261 | 0.003 | YES |

LTR $\to $ GDPPC | 2.031 ** | 2.988 | 0.016 | YES |

GFC $\to $ LTR | 1.851 * | 2.491 | 0.052 | YES |

LTR $\to $ GFC | 4.173 *** | 5.806 | 0.001 | YES |

GEX $\to $ LTR | 1.895 * | 2.351 | 0.072 | YES |

LTR $\to $ GEX | 0.302 | 0.773 | 0.219 | NO |

I $\to $ LTR | 1.086 | 1.536 | 0.103 | NO |

LTR $\to $ I | 0.871 | 1.103 | 0.161 | NO |

EF $\to $ LTR | 1.716 * | 2.311 | 0.085 | YES |

LTR $\to $ EF | 0.285 | 0.694 | 0.251 | NO |

One-Step GMM (1) | Two-Step GMM (2) | |
---|---|---|

LTR_{t−1} | 0.85 ** (0.02) | 0.92 *** (0.007) |

LOIL | −1.13 ** (0.04) | −0.35 *** (0.008) |

GDPPC | 0.64 * (0.06) | 0.04 ** (0.04) |

GFC | −0.11 * (0.09) | −0.12 ** (0.04) |

GEX | 1.05 ** (0.03) | 2.3 *** (0.007) |

I | 0.03 *** (0.002) | 0.08 * (0.09) |

EF | −0.12 * (0.07) | −0.05 ** (0.03) |

Constant | 6.02 * (0.09) | 10.82 * (0.08) |

Time Dummy | Yes | Yes |

Instruments | L1, L2 | L1, L2 |

AR(1) | 0.12 | 0.16 |

AR(2) | 0.32 | 0.41 |

Hansen (p-value) | 0.21 | 0.16 |

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## Share and Cite

**MDPI and ACS Style**

Hesami, S.; Rustamov, B.; Rjoub, H.; Wong, W.-K.
Implications of Oil Price Fluctuations for Tourism Receipts: The Case of Oil Exporting Countries. *Energies* **2020**, *13*, 4349.
https://doi.org/10.3390/en13174349

**AMA Style**

Hesami S, Rustamov B, Rjoub H, Wong W-K.
Implications of Oil Price Fluctuations for Tourism Receipts: The Case of Oil Exporting Countries. *Energies*. 2020; 13(17):4349.
https://doi.org/10.3390/en13174349

**Chicago/Turabian Style**

Hesami, Siamand, Bezhan Rustamov, Husam Rjoub, and Wing-Keung Wong.
2020. "Implications of Oil Price Fluctuations for Tourism Receipts: The Case of Oil Exporting Countries" *Energies* 13, no. 17: 4349.
https://doi.org/10.3390/en13174349