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The economic impact of climate change (CC) on the Greek economy

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Abstract

The considerable relevant size of the tourism sector for some economies, together with this sector's vulnerability to CC, renders this study an insightful aid to tourism demand forecasting. The paper applies a pooled mean group (PMG) model to identify climate parameters that affect tourism demand. Then, it continues with an input–output table analysis to show the transmission effects of CC on each component of the tourism sector. The PMG model imposes homogeneity on the long-run coefficients and while less restrictive, it is more efficient than other methods of the same family. The estimated gravity equation enables comparisons of the baseline scenario with various different scenarios of CC and finds how tourist arrivals could be affected up to 2080. Our results suggest that there is mostly a positive relationship of the squared difference of temperature and precipitation between Greece and tourist origin countries. Our findings also suggest that CC could lead to a fall in Greek GDP between 1.79 and 2.61%. We believe that our findings will help design appropriate policy actions that may offset or alleviate these negative future negative impacts of CC.

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Notes

  1. The AIC is a measure of the relative quality of a statistical model for a given set of data and, therefore, it provides a means for model selection.

  2. Long run coefficients present the relationship between the variables in equilibrium. If, an external shock is introduced into the system, then it takes some time for the system to re-establish this equilibrium relationship. The adjustment coefficient shows the speed that the system comes to an equilibrium after the external shock. This coefficient should be negative and statistically significant for the equilibrium to be stable (another requirement for the dynamic stability of the PMG model is that the adjustment coefficient should be higher than -2). The higher the speed of adjustment the better is the model.

  3. The gravity model uses the year 2005 as a base year, but the I-O model uses the year 2010 as base year, because no earlier data were available from Eurostat. However, we have allowed the additional assumption that the tourist economy structure and the tourist sector contribution does not change dramatically within these five years and hence it is legitimate to use the 2010 as base year in the I-O model.

References

  • Agiomirgianakis, G., Serenis, D., & Tsounis, N. (2017). Effective timing of tourism policy: The case of Singapore. Economic Modelling, 60, 29–38.

    Article  Google Scholar 

  • Agiomirgianakis, G., Serenis, D., & Tsounis, N. (2015). A distance learning university and its economic impact in a country’s peripheries: The case of Hellenic open university. Operational Research, 17, 165–186.

    Article  Google Scholar 

  • Akter, H., Akhtar, S., & Samina, A. N. (2017). Tourism demand in Bangladesh: Gravity model analysis. Tourism, 65(3), 346–360.

    Google Scholar 

  • Alawin, M., & Abu-Lila, Z. (2016). Uncertainty and gravity model for international tourism demand in Jordan: Evidence from Panel-GARCH model. Applied Econometrics and International Development, 16(1), 131–146.

    Google Scholar 

  • Ali, H. S., Law, S. H., & Zannah, T. I. (2016). Dynamic impact of urbanization, economic growth, energy consumption, and trade openness on CO2 emissions in Nigeria. Environmental Science and Pollution Research, 23, 12435–12443.

    Article  Google Scholar 

  • Ali, W., Abdullah, A., & Azam, M. (2017). Re-visiting the environmental Kuznets curve hypothesis for Malaysia: Fresh evidence from ARDL bounds testing approach. Renewable and Sustainable Energy Reviews, 77, 990–1000.

    Article  Google Scholar 

  • Bank of Greece. (2011). The environmental, economic and social impacts of climate change in Greece, available from: https://www.bankofgreece.gr/bogekdoseis/climatechange_fullreport_bm.pdf. Accessed 25 2019.

  • Barritela, M., Bigano, A., & Roson, R. (2006). A general equilibrium analysis of climate change impacts on tourism. Tourism Management, 27, 913–924.

    Article  Google Scholar 

  • Bayer, C., & Hanck, C. (2013). Combining non-cointegration tests. Journal of Time Series Analysis, 34(1), 83–95.

  • Chasapopoulos, P., Den Butter, F. A. G., & Mihaylov, E. (2014). Demand for tourism in Greece: A panel data analysis using the gravity model. International Journal of Tourism Policy, 5(3), 173–191.

    Article  Google Scholar 

  • Copernicus. (2018). Climate change impact on tourism. Available from https://www.climate.copernicus.eu/resources/information-service/. Accessed 01 May 2018.

  • Du, D., & Ng, P. (2018). The impact of climate change on tourism economies of Greece, Spain, and Turkey. Environmental Economics and Policy Studies, 20(2), 431–449.

    Article  Google Scholar 

  • Eryiǧit, M., Kotil, E., & Eryiǧit, R. (2010). Factors affecting international tourism flows to Turkey: A gravity model approach. Tourism Economics, 16(3), 585–595.

    Article  Google Scholar 

  • European Commission. (2014). Climate change: Implications for tourism, european climate adaptation platform. available from: https://www.climate-adapt.eea.europa.eu/metadata/publications/climate-change-implications. Accessed 01 May 2018.

  • Eurostat. (2019). Symmetric input-output table at basic prices (product by product), code: [naio_10_cp1700], available from: [http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do]. Accessed 24 Mar 2019.

  • Giannakopoulos, C., Kostopoulou, E., Varotsos, K. V., Tziotziou, K., & Plitharas, A. (2011). An integrated assessment of climate change impacts for Greece in the near future. Regional Environmental Change, 11(4), 829–843.

    Article  Google Scholar 

  • Glisaclimate.org. (2021). What are the major differences between the Special Report on Emissions Scenarios (SRES) and the Representative Concentration Pathways (RCP)? Available from: http://www.glisaclimate.org/node/2416.

  • Gouveia, S., Rebelo, J., Lourenço-Gomes, L., & Guedes, A. (2017). International demand for the Douro (Portugal) river cruises: A gravity model approach. Tourism Economics, 23(8), 1679–1686.

    Article  Google Scholar 

  • Greek Tourism Federation. (2018). Evolution of the number of hotel accomodation in Greece. Available from https://www.sete.gr/el/statistika-vivliothiki/statistika/. Accessed 02 Mar 2020.

  • Gunter and Smeral. (2016). The decline of tourism income elasticities in the global context. Tourism Economics, 22(3).

  • Halicioglu, F. (2007). Residential electricity demand dynamics in Turkey. Energy Economics, 29, 199–210.

    Article  Google Scholar 

  • Harris, R., & Sollis, R. (2003). Applied Time Series Modelling and Forecasting. Wiley.

  • Haug, A. A. (2002). Temporal aggregation and the power of cointegration tests: A Monte Carlo study. Oxford Bulletin of Economics and Statistics, 64, 399–412.

    Article  Google Scholar 

  • Ifantis, P.D. (2017). Tourism. Which regions have generated most revenue? Available from https://www.Euro2day.Gr/news/economy/article/1541759. Accessed 15 July 2018.

  • Jalil, A., & Ma, Y. (2008). Financial development and economic growth: Time series evidence from Pakistan and China. Journal of Economic Cooperation among Islamic Countries, 29, 29–68.

    Google Scholar 

  • Leontief, W. (1986). Input-Output Economics. Oxford University Press.

  • Lorde, T., Li, G., & Airey, D. (2016). Modeling Caribbean tourism demand: An augmented gravity approach. Journal of Travel Research, 55(7), 946–956.

    Article  Google Scholar 

  • Malaj, V., & Kapiki, S. T. (2016). Determinants of tourism flows to Greece: A gravity model approach. Tourismos, 11(2), 202–224.

    Google Scholar 

  • Marques, L. M., Fuinhas, J. A., & Marques, A. C. (2017). Augmented energy-growth nexus: Economic, political and social globalization impacts. Energy Procedia, 136, 97–101.

    Article  Google Scholar 

  • Massidda, C., & Etzo, I. (2012). The determinants of Italian domestic tourism: A panel data analysis. Tourism Management, 33(3), 603–610.

    Article  Google Scholar 

  • Menegaki, A. N. (2019). The ARDL method in the energy-growth nexus field; best implementation strategies. Economies, 7, 105.

    Article  Google Scholar 

  • Michailidou, A. V., Vlachokostas, C., & Moussiopoulos, N. (2016). Interactions between climate change and the tourism sector: Multiple-criteria decision analysis to assess mitigation and adaptation options in tourism areas. Tourism Management, 55, 1–12.

    Article  Google Scholar 

  • Morley, C., Rossello, J., & Santana Gallego, M. (2014). Gravity models for tourism demand: Theory and use. Annals of Tourism Research, 48, 1–10.

  • Pesaran, M. H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration analysis. In S. Strøm (Ed.), Econometrics and economic theory in the 20th century: The ragnar frisch centennial symposium. Cambridge: Cambridge University Press.

  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326.

    Article  Google Scholar 

  • Pintassilgo, P., Rosselló, J., Santana-Gallego, M., & Valle, E. (2016). The economic dimension of climate change impacts on tourism: The case of Portugal. Tourism Economics, 22(4), 685–698.

    Article  Google Scholar 

  • Priego, J., & F., Rosselló, J., Santana Gallego, M., . (2015). The impact of climate change on domestic tourism: a gravity model for Spain. Regional Environmental Change, 15, 2.

    Article  Google Scholar 

  • Provenzano, D. (2015). A dynamic analysis of tourism determinants in Sicily. Tourism Economics, 21(3), 441–454.

    Article  Google Scholar 

  • Rahman, M. M., & Kashem, M. A. (2017). Carbon emissions, energy consumption and industrial growth in Bangladesh: Empirical evidence from ARDL cointegration and Granger causality analysis. Energy Policy, 110, 600–608.

    Article  Google Scholar 

  • SETE. (2019a). Basic figures in Greek tourism, available from https://sete.gr/el/stratigiki-gia-ton-tourismo/vasika-megethi-tou-ellinikoy-tourismoy. Accessed 27 June 2019.

  • SETE. (2019b). Inbound tourism in Greece, The evolution of tourist indices between 2005–2017. Available from: http://www.insete.gr/Portals/0/statistics/Profil/2018/Incoming%20tourism%20to%20Greece%20total.pdf. Accessed 27 June 2019.

  • SETE. (2019c). H συμβολή του Τουρισμού στην ελληνική οικονομία το 2018. Available from: https://sete.gr/media/10888/2018_symvolhtourismou-2017.pdf.

  • Sheather, S. (2009). A modern approach to regression with R. Springer.

  • Slini, T., & Papakostas, K. T. (2016). 30 years air temperature data analysis in Athens and Thessaloniki, Greece. In Green energy and technology (Vol. PartF2, pp. 21–33).

  • Taplin, J. H. E., & Qiu, M. (1997). Car trip attraction and route choice in Australia. Annals of Tourism Research, 24(3), 624–637.

    Article  Google Scholar 

  • Tsounis, N. (1996). The factor content of Greek Trade with the other E.U. countries. Greek Economic Review, 18, 1–22.

    Google Scholar 

  • Tsounis, N. (2003). The validity of bilateral Heckscher-Ohlin: Some further empirical evidence. International Economy, 56(1), 119–136.

    Google Scholar 

  • UNWTO and International Transport Forum. (2019). Transport-related CO2 emissions of the tourism sector. Available from https://www.e-unwto.org/doi/epdf/. https://doi.org/10.18111/9789284416660. Accessed 10 Mar 2021.

  • van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J. F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., & Rose, S. K. (2011). The representative concentration pathways: An overview. Climatic Change, 109, 5–31.

    Article  Google Scholar 

  • Velasquez, M. E. B., & Oh, J. (2013). What determines international tourist arrivals to Peru? A gravity approach. International Area Studies Review, 16(4), 357–369. https://doi.org/10.1177/2233865913505103.

  • Vietze, C. (2012). Cultural effects on inbound tourism into the USA: A gravity approach. Tourism Economics, 18(1), 121–138.

    Article  Google Scholar 

  • Weadapt.org. (2021). Pathways and scenarios: 10 things to know about the IPCC scenario framework. Available from: https://www.weadapt.org.

  • World Tourism Organization. (2018). Climate change & tourism. Available from https://www.sdt.unwto.org/en/content/climate-change-tourism. Accessed 30 Apr 2018.

  • World Tourism Organization and United Nations Environment Programme. (2008). Climate change and tourism-responding to global challenges. UNWTO, Madrid. https://doi.org/10.18111/9789284412341.

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Acknowledgements

We are grateful to Pedro Pintassilgo (University of Algarve, Portugal) and Maria Santana-Gallego (Department of Applied Economics, Spain) for their directions in finding the CC scenarios data we needed for this paper. We would also like to thank three anonymous reviewers and an editor for the improvement of this paper.

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Authors and Affiliations

  1. Department of Economics and Management of Tourist Businesses, Agricultural University of Athens, Amfissa, 33100, Greece

    Angeliki N. Menegaki

  2. Cyprus Open University, Nicosia, Cyprus

    Angeliki N. Menegaki

  3. Economic Analysis and Policy Lab of Hellenic, Open University, Patras, Greece

    Angeliki N. Menegaki, Nicholas Tsounis & George M. Agiomirgianakis

  4. Laboratory of Applied of Economics, Department of Economics, University of Western Macedonia, Kastoria, Greece

    Nicholas Tsounis

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  1. Angeliki N. Menegaki
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Correspondence to George M. Agiomirgianakis.

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Menegaki, A.N., Tsounis, N. & Agiomirgianakis, G.M. The economic impact of climate change (CC) on the Greek economy. Environ Dev Sustain 24, 8145–8161 (2022). https://doi.org/10.1007/s10668-021-01776-4

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