# Examining the Causal Relationship between Tourism and Economic Growth: Spillover Index Approach for Selected CEE and SEE Countries

## Abstract

**:**

## 1. Introduction

## 2. Previous Related Research

## 3. Methodology

**y**

_{t}is the vector of N variables in the system,

**v**vector of intercepts,

**A**

_{i}coefficient matrices of the system and

**ε**

_{t}vector of error terms (innovations)13. The compact form of (1) is given as ${\mathit{Y}}_{t}=\mathbf{v}+\mathit{A}{\mathit{Y}}_{t-1}+{\mathit{e}}_{t}$14, with the assumption of being a stable15 process and with a MA16(∞) representation ${\mathit{Y}}_{t}=\mathit{\mu}+{\displaystyle \sum _{i=1}^{N}{\mathit{A}}_{}^{i}}{\mathit{e}}_{t-i}$, $\mathit{\mu}\equiv {\left({\mathit{I}}_{Np}-\mathit{A}\right)}^{-1}\mathbf{v}$. The polynomial form of the MA representation is usually observed for the purpose of the forecast error variance decomposition:

_{jk}

_{,i}denote the impulse responses of every variable in the system to shocks in variable k. Due to innovations in ${\mathbf{e}}_{t}$ being correlated, Choleski decomposition could be applied on their variance-covariance matrix such that a lower triangular matrix

**P**

^{−1}is chosen so E(

**P**

^{−1}${\mathbf{e}}_{t}$

**P**

^{−1}${\mathbf{e}}_{t}^{\prime}$) = 0 holds. The model (2) is now in the form ${\mathit{Y}}_{t}=\mathsf{\Phi}(L)\mathit{P}{\mathit{P}}^{-1}=\Theta (L){\mathit{u}}_{t}$. In order to decompose the forecast error variance of every variable in the model, the h-step ahead forecasted value is detracted from the actual value in the h-step ahead, i.e., ${\mathit{Y}}_{t+h}-E({\mathit{Y}}_{t+h})={\displaystyle \sum _{i=0}^{h-1}{\Theta}_{i}{\mathit{u}}_{t+h-i}}$.

**e**

_{k}is the k-th column of matrix

**I**

_{Np}.

## 4. Empirical Analysis and Discussion

## 5. Conclusions

## Funding

## Acknowledgments

## Conflicts of Interest

## Appendix A

Country | Start | End |
---|---|---|

Bulgaria | January 2002 | October 2018 |

Czech Republic | January 2002 | September 2018 |

Croatia | January 2003 | October 2018 |

Hungary | January 2001 | October 2018 |

Poland | January 2003 | October 2018 |

Romania | January 2002 | October 2018 |

Slovenia | January 2000 | December 2017 |

Slovakia | January 2003 | October 2018 |

Variable | Type: constant | Type: none |
---|---|---|

TUR_BULG | −13.495 | −13.369 |

IIP_BULG | −16.240 | −16.008 |

TUR_CZECH | −13.532 | −13.430 |

IIP_CZECH | −21.044 | −20.625 |

TUR_CRO | −11.262 | −11.212 |

IIP_CRO | −16.175 | −16.207 |

TUR_HUNG | −11.629 | −11.540 |

IIP_HUNG | −18.029 | −17.731 |

TUR_POL | −12.510 | −12.090 |

IIP_POL | −20.383 | −18.576 |

TUR_ROM | −15.150 | −14.769 |

IIP_ROM | −17.802 | −17.377 |

TUR_SLO | −18.261 | −17.823 |

IIP_SLO | −20.865 | −20.686 |

TUR_SLOVAK | −10.960 | −10.874 |

IIP_SLOVAK | −16.107 | −15.680 |

Country | AIC | HQ | SC | FPE |
---|---|---|---|---|

Bulgaria | 4 | 4 | 3 | 4 |

Czech Republic | 3 | 2 | 2 | 3 |

Croatia | 6 | 2 | 2 | 6 |

Hungary | 2 | 2 | 2 | 2 |

Poland | 6 | 2 | 2 | 6 |

Romania | 2 | 2 | 2 | 2 |

Slovenia | 6 | 2 | 2 | 6 |

Slovakia | 4 | 3 | 2 | 4 |

## References

- Antonakakis, Nikolaos, Mina Dragouni, and George Filis. 2015a. Tourism and growth: The times they are a-changing. Annals of Tourism Research 50: 165–69. [Google Scholar] [CrossRef]
- Antonakakis, Nikolas, Mina Dragouni, and George Filis. 2015b. How Strong is the Linkage between Tourism and Economic Growth in Europe? Economic Modelling 44: 142–55. [Google Scholar] [CrossRef]
- Aslan, Alper. 2013. Tourism development and economic growth in the Mediterranean countries: Evidence from panel Granger causality tests. Current Issues in Tourism 17: 363–72. [Google Scholar] [CrossRef]
- Balaguer, Jacint, and Manuel Cantavella-Jorda. 2002. Tourism as a long-run economic growth factor: The Spanish case. Applied Economics 34: 877–84. [Google Scholar] [CrossRef]
- Balassa, Bela. 1978. Exports and economic growth: Further evidence. Journal of Development Economics 5: 181–89. [Google Scholar] [CrossRef]
- Baron, Reuben, and David Kenny. 1986. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51: 1173–82. [Google Scholar] [CrossRef]
- Brida, Juan-Gabriel, and Manulea Pulina. 2010. A Literature Review on the Tourism-Led-Growth Hypothesis. CRENoS Working paper No. WP10-17. Cagliary, Italy: Centre For North South Economic Research. [Google Scholar]
- Brida, Juan-Garbiel, Isabel Cortes-Jimenez, and Manuela Pulina. 2016. Has the tourism-led growth hypothesis been validated? A literature review. Current Issues in Tourism 19: 394–430. [Google Scholar] [CrossRef]
- Chou, Ming Che. 2013. Does tourism development promote economic growth in transition countries? A panel data analysis. Economic Modelling 33: 226–32. [Google Scholar] [CrossRef]
- Comerio, Niccolò, and Fernanda Strozzi. 2019. Tourism and Its Economic Impact: A Literature Review Using Bibliometric Tools. Tourism Economics 25: 109–31. [Google Scholar] [CrossRef]
- De Vita, Glauco, and Khine Kyaw. 2016. Tourism Specialization, Absorptive Capacity, and Economic Growth. Journal of Travel Research 56: 1–13. [Google Scholar] [CrossRef]
- Demirhan, Banu. 2016. Tourism-Led Growth Hypothesis in Mediterranean Countries: Evidence from a Panel Cointegration and Error Correction Model. Applied Economics and Finance 3: 38–53. [Google Scholar] [CrossRef]
- Diebold, Francis, and Kamil Yilmaz. 2009. Measuring Financial Asset Return and Volatility Spillovers with Application to Global Equity Markets. The Economic Journal 119: 158–71. [Google Scholar] [CrossRef]
- Diebold, Francis, and Kamil Yilmaz. 2012. Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers. International Journal of Forecasting 28: 57–66. [Google Scholar] [CrossRef]
- Dogru, Tarik, and Umit Bulut. 2017. Can Tourism Help Europe’s Struggling Economies? Working paper. Available online: https://www.researchgate.net/publication/317580440_Can_tourism_help_Europe’s_struggling_economies (accessed on 6 February 2019).
- Dragouni, Mina, Filis George, and Nikolaos Antonakakis. 2013. Time-Varying Interdependencies of Tourism and Economic Growth: Evidence from European Countries. MPRA Paper No. 48715. Munich: Munich University Library. [Google Scholar]
- Dumitrescu, Elena-Ivona, and Chrisophe Hurlin. 2012. Testing for Granger non-causality in heterogeneous panels. Economic Modelling 29: 1450–60. [Google Scholar] [CrossRef]
- Eurostat. 2018. Database. Available online: https://ec.europa.eu/eurostat/web/lucas/data/primary-data/2018 (accessed on 6 February 2019).
- Eurostat. 2019. Database. Available online: https://ec.europa.eu/eurostat/data/database (accessed on 4 February 2019).
- Gričar, Sergej, Stefan Bojnec, Vesna Karađić, and Svetlana Rakočević. 2016. Comparative Analysis of Tourism-Led Growth in Slovenia and Montenegro. Managing Global Transitions 14: 75–92. [Google Scholar]
- Gwenhure, Yvonne, and Nicholas Odhiambo. 2017. Tourism and economic growth: A review of international literature. Tourism 65: 33–44. [Google Scholar]
- Hajdinjak, Sanja. 2014. Impact of tourism on economic growth in Croatia. Enlightening Tourism. A Pathmaking Journal 4: 30–51. [Google Scholar]
- Kido-Cruz, Antonio, Teresa Kido-Cruz, and James Killough. 2015. Economic Impact Assessment: A Review of Literature on the Tourism Industry. Global Journal of Management and Business Research: Economics and Commerce 15: 1–9. [Google Scholar]
- Koop, Garry, Hashem Pesaran, and Simon Potter. 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74: 119–47. [Google Scholar] [CrossRef]
- Lee, Chien-Chiang, and Chun-Ping Chang. 2008. Tourism development and economic growth: A closer look at panels. Tourism Management 29: 180–92. [Google Scholar] [CrossRef]
- Lin, Hui-Lin, Lon-Mu Liu, Yi-Hseng Tseng, and Yu-Wen Su. 2010. Taiwan international tourism: A time series analysis with calendar effects and joint outlier adjustments. International Journal of Tourism Research 13: 1–16. [Google Scholar] [CrossRef]
- Lütkepohl, Helmut. 1993. Introduction to Multiple Time Series Analysis. Berlin: Springer. [Google Scholar]
- Lütkepohl, Helmut. 2006. New Introduction to Multiple Time Series Analysis. Berlin: Springer. [Google Scholar]
- Lütkepohl, Helmut. 2010. Vector Autoregressive Models. Economics Working Paper ECO 2011/30. Fiesole, Italy: European University Institute. [Google Scholar]
- McKinnon, Ronald. 1964. Foreign exchange constrain in economic development and efficient aid allocation. Economic Journal 74: 388–409. [Google Scholar] [CrossRef]
- Oh, Chi-Ok. 2005. The contribution of tourism development to economic growth in the Korean economy. Tourism Management 26: 39–44. [Google Scholar] [CrossRef]
- Pablo-Romero, María, and José Molina. 2013. Tourism and economic growth: A review of empirical literature. Tourism Management Perspectives 8: 28–41. [Google Scholar] [CrossRef]
- Payne, James, and Andrea Mervar. 2010. The tourism-growth nexus in Croatia. Tourism Economics 16: 1089–94. [Google Scholar] [CrossRef]
- Pesaran, Hashem, and Yongcheol Shin. 1998. Generalized impulse response analysis in linear multivariate models. Economics Letters 58: 17–29. [Google Scholar] [CrossRef]
- Phiri, Andrew. 2015. Tourism and Economic Growth in South Africa: Evidence from Linear and Nonlinear Cointegration Frameworks. MPRA Paper No. 65000. Munich: Munich Personal RePEc Archive. [Google Scholar]
- Shakouri, Bahram, Yazdi Soheila Khoshnevis, Niloofar Nategian, and Niloofar Shikhrezaei. 2017. International Tourism and Economic Growth and Trade: Variance Decomposition Analysis. Journal of Tourism Hospitality 6: 1–11. [Google Scholar] [CrossRef]
- Shareef, Raiz, and Michael McAleer. 2007. Modelling the uncertainty in monthly international tourist arrivals to the Maldives. Tourism Management 28: 23–45. [Google Scholar] [CrossRef]
- Sheldon, Pauline. 1993. Forecasting tourism: Expenditures versus arrivals. Journal of Travel Research 32: 13–20. [Google Scholar] [CrossRef]
- Simnudić, Blanka, and Zvonimir Kuliš. 2016. Tourism and economic growth in Mediterranean countries: Dynamic panel analysis. Acta Economica Et Turistica 1: 177–96. [Google Scholar]
- Škrinjarić, Tihana. 2018. Evaluation of environmentally conscious tourism industry: Case of Croatian counties. Tourism 66: 254–68. [Google Scholar]
- Surugiu, Camelia, and Marius Razvan Surugiu. 2013. Is the Tourism Sector Supportive of Economic Growth? Empirical Evidence on Romanian Tourism. Tourism Economics 19: 115–32. [Google Scholar] [CrossRef]
- Tugcu, Can Tansel. 2014. Tourism and economic growth nexus revisited: A panel causality analysis for the case of the Mediterranean Region. Tourism Management 42: 207–12. [Google Scholar] [CrossRef]
- UNWTO. 2016. Measuring Sustainable Tourism: Developing a Statistical Framework for Sustainable Tourism. UNWTO Statistics and Tourism Satellite Account Programme. Available online: http://cf.cdn.unwto.org/sites/all/files/docpdf/mstoverviewrev1.pdf (accessed on 4 February 2019).
- Urbina, Jilber. 2013. Financial Spillovers Across Countries: Measuring Shock Transmissions. MPRA Working paper. MPRA Paper No. 75756. Munich: Munich University Library. [Google Scholar]
- World Travel & Tourism Council. 2019. Available online: http://www.wttc.org (accessed on 4 February 2019).

1 | Also referred to as TLGH and GLTH where H stands for hypothesis. |

2 | If we exclude the financial crisis and the impact in year 2009, the growth rates are: 8.72%, 5.15%, 7.03%, 5.50%, 5.89%, 7.57%, 6.34% and 4.44%. |

3 | Here several tables give overview for many countries, with none of those included in this paper. |

4 | Here only 4 papers exist which observe some of the countries in this paper. |

5 | None of the research included countries which are in this paper. |

6 | Only 2 papers are found here which include some of the countries in this paper, with 2 overlapping as in reference Brida et al. (2016). |

7 | Here only 2 papers exist which observe some of the countries in this paper. |

8 | Similar in terms of economy at whole or similar geographical position. |

9 | Generalized method of moments. |

10 | Fully modified ordinary least squares. |

11 | Dynamic ordinary least squares. |

12 | Vector AutoRegression. |

13 | It holds that E( ε_{t}) = 0, E(ε_{t}ε_{t}′) = Σ_{ε} < ∞ and E(ε_{t}ε_{s}’) = 0 for t ≠ s. |

14 | With ${\mathit{Y}}_{t}={\left[\begin{array}{cccc}{\mathit{y}}_{t}& {\mathit{y}}_{t-1}& \cdots & {\mathit{y}}_{t-p}\end{array}\right]}^{\prime}$, $\mathbf{v}={\left[\begin{array}{cccc}\mathit{v}& \mathbf{0}& \cdots & \mathbf{0}\end{array}\right]}^{\prime}$ and A = $\left[\begin{array}{ccccc}{\mathit{A}}_{1}& {\mathit{A}}_{2}& \cdots & {\mathit{A}}_{p-1}& {\mathit{A}}_{p}\\ {\mathit{I}}_{N}& 0& \cdots & 0& 0\\ 0& {\mathit{I}}_{N}& & \vdots & \vdots \\ \vdots & & \ddots & \vdots & \vdots \\ 0& 0& \cdots & {\mathit{I}}_{N}& 0\end{array}\right]$ and ${\mathit{e}}_{t}={\left[\begin{array}{cccc}{\mathit{\epsilon}}_{t}& \mathbf{0}& \cdots & \mathbf{0}\end{array}\right]}^{\prime}$. |

15 | The model is stabile if det( I_{Np} − Az) ≠ 0 for |z| ≤ 1. |

16 | Moving average. |

17 | These variables were used as previous literature utilizes them when using monthly data. Moreover, this way we get more data available. All of the data are seasonally adjusted. |

18 | Other countries which were considered to include but due to unavailability of data were excluded from the analysis: Albania, Bosnia and Herzegovina, Macedonia, Montenegro and Serbia. |

19 | Number of arrivals as a variable to measure tourism demand is used in relevant literature such as Sheldon (1993); Shareef and McAleer (2007); Lin et al. (2010); and almost every empirical reference in this paper. |

20 | For more information on the total, direct and indirect effects of one variable to another, please see Baron and Kenny (1986). |

21 | |

22 | With the exception of Payne and Mervar (2010) who use Toda– Yamamoto long-run causality tests. |

**Figure 2.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Bulgaria, h = 12 months.

**Figure 3.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Czech Republic, h = 12 months.

**Figure 4.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Croatia, h = 12 months.

**Figure 5.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Hungary, h = 12 months.

**Figure 6.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Poland, h = 12 months.

**Figure 7.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Romania, h = 12 months.

**Figure 8.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Slovenia, h = 12 months.

**Figure 9.**Net rolling spillover indices for growth rates of tourism arrivals and IIP for Slovakia, h = 12 months.

Author(s) (year) | Countries | Time Span | Results |
---|---|---|---|

Dragouni et al. (2013) | Austria, Cyprus, Germany, Greece, Italy, Netherlands, Portugal, Spain, Sweden, UK | 1995–2012 | No relationship: Sweden and UK Bidirectional: Austria, Portugal and Spain TUR to IIP: Italy, Netherlands IIP to TUR: Cyprus, Germany, Greece |

Antonakakis et al. (2015a) | Austria, Germany, Greece, Italia, Portugal, Spain | 1995–2012 | Relationship varies, depends upon economic events. Tourism-led growth mostly found for Italy, Greece and Spain. |

Antonakakis et al. (2015b) | Austria, Cyprus, Germany, Greece, Italy, Netherlands, Portugal, Spain, Sweden, UK | 1995–2012 | Relationship varies, depends upon economic events. Tourism-led growth mostly found for Italy, Greece and Spain. |

BULGARIA | TUR | IIP | FROM |
---|---|---|---|

TUR | 89.15 | 20.85 | 5.43 |

IIP | 3.08 | 96.92 | 1.54 |

To | 1.54 | 5.43 | 6.97 |

To including own | 93.77 | 123.2 | 3.21 |

CZECH REPUBLIC | TUR | IIP | FROM |
---|---|---|---|

TUR | 87.65 | 12.35 | 6.17 |

IIP | 2.24 | 97.76 | 1.12 |

To | 1.12 | 6.17 | 6.97 |

To including own | 91.01 | 116.28 | 3.36 |

CROATIA | TUR | IIP | FROM |
---|---|---|---|

TUR | 89.24 | 10.76 | 5.38 |

IIP | 4.52 | 95.48 | 2.26 |

To | 2.26 | 5.38 | 7.64 |

To including own | 96.02 | 111.62 | 3.68 |

HUNGARY | TUR | IIP | FROM |
---|---|---|---|

TUR | 85.34 | 14.66 | 7.33 |

IIP | 10.21 | 89.79 | 5.11 |

To | 5.11 | 7.33 | 12.44 |

To including own | 100.66 | 111.78 | 5.86 |

POLAND | TUR | IIP | FROM |
---|---|---|---|

TUR | 98.15 | 1.85 | 0.92 |

IIP | 11.57 | 88.43 | 5.78 |

To | 5.78 | 0.92 | 6.71 |

To including own | 115.5 | 91.2 | 3.25 |

ROMANIA | TUR | IIP | FROM |
---|---|---|---|

TUR | 93.34 | 5.66 | 2.83 |

IIP | 3.74 | 96.26 | 1.87 |

To | 1.87 | 2.83 | 4.70 |

To including own | 98.95 | 104.75 | 2.31 |

SLOVENIA | TUR | IIP | FROM |
---|---|---|---|

TUR | 79.29 | 20.71 | 10.36 |

IIP | 12.41 | 87.59 | 6.21 |

To | 6.21 | 10.36 | 16.56 |

To including own | 97.91 | 118.66 | 7.65 |

SLOVAKIA | TUR | IIP | FROM |
---|---|---|---|

TUR | 92.35 | 7.65 | 3.82 |

IIP | 12.13 | 87.87 | 6.06 |

To | 6.06 | 3.82 | 9.89 |

To including own | 110.54 | 99.34 | 4.71 |

Country | Measure | TUR | IIP | Country | Measure | TUR | IIP |
---|---|---|---|---|---|---|---|

Bulgaria | Mean | −1.209 | 1.209 | Poland | Mean | 3.315 | −3.315 |

Max | 2.312 | 6.045 | Max | 6.725 | −1.155 | ||

Min | −6.045 | −2.312 | Min | 1.155 | −6.725 | ||

Czech Republic | Mean | −8.142 | 8.142 | Romania | Mean | 0.169 | −0.169 |

Max | −2.856 | 12.726 | Max | 3.483 | 1.331 | ||

Min | −12.726 | 2.856 | Min | −1.331 | −3.483 | ||

Croatia | Mean | −2.106 | 2.106 | ||||

Max | 0.038 | 4.101 | |||||

Min | −4.101 | −0.038 | |||||

Hungary | Mean | −2.932 | 2.932 | ||||

Max | 1.049 | 6.607 | |||||

Min | −6.607 | −1.049 | |||||

Slovenia | Mean | −5.115 | 5.115 | ||||

Max | 0.270 | 12.740 | |||||

Min | −12.740 | −0.270 | |||||

Slovakia | Mean | −1.166 | 1.166 | ||||

Max | 4.836 | 3.751 | |||||

Min | −3.751 | −4.836 |

© 2019 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Škrinjarić, T.
Examining the Causal Relationship between Tourism and Economic Growth: Spillover Index Approach for Selected CEE and SEE Countries. *Economies* **2019**, *7*, 19.
https://doi.org/10.3390/economies7010019

**AMA Style**

Škrinjarić T.
Examining the Causal Relationship between Tourism and Economic Growth: Spillover Index Approach for Selected CEE and SEE Countries. *Economies*. 2019; 7(1):19.
https://doi.org/10.3390/economies7010019

**Chicago/Turabian Style**

Škrinjarić, Tihana.
2019. "Examining the Causal Relationship between Tourism and Economic Growth: Spillover Index Approach for Selected CEE and SEE Countries" *Economies* 7, no. 1: 19.
https://doi.org/10.3390/economies7010019