Tourism development has often been considered as a growth pillar over recent decades; however, studies on whether and how it can contribute to pollution reduction are scant. This study fills the research gaps by exploring the role of tourism development in pollution emissions by investigating two influencing mechanisms—the industry substitution effect and energy substitution effect—in the context of Asian Tigers. Several econometric techniques are used to show that a 1% increase in tourism development can lead to a 0.3862% decrease in carbon emissions. The results of multiple mediating effect analyses indicate that the tourism sector can curb carbon emissions by both replacing high-emissions industries and promoting the use of renewable energy; the effect of the former path is 4% greater than that of the latter. This study should serve as a reference by which policymakers can develop sustainable tourism and reduce pollution emissions.
AhmadNDuLLiangX, et al. (2018) Chinese growth and dilemmas: modelling energy consumption. CO2 emissions and growth in China. Quality & Quantity2: 1–24.
2.
AhmadNDuLLuJ, et al. (2017) Modelling the CO2 emissions and economic growth in Croatia: Is there any environmental Kuznets curve?Energy123: 164–172.
3.
AntonSGNucuAEA (2020) The effect of financial development on renewable energy consumption. A panel data approach. Renewable Energy147: 330–338.
4.
AyhanCKTasliTCOzkokF, et al. (2020) Land use sustainability analysis of rural tourism activities: Yenice. Turkey. Tourism Management76: 103949.
5.
AzamMAlamMMHafeezHM (2018) Effect of tourism on environmental pollution: further evidence from Malaysia. Singapore and Thailand. Journal of Cleaner Production190: 330–338.
6.
BanerjeeAJDoladoR (1998) Error-correlation mechanism tests for co-integration in a single-equation framework. Journal of Time Series Analysis19: 267–283.
7.
BaronRMKennyDA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology51: 1173–1182.
8.
BermanJDEbisuK (2020) Changes in U.S. air pollution during the COVID-19 pandemic. Science of the Total Environment739: 139864.
9.
BhatiAPearceP (2017) Tourist attractions in Bangkok and Singapore: linking vandalism and setting characteristics. Tourism Management63: 15–30.
10.
BreitungJ (2000) The local power of some unit root tests for panel data. Advances in Econometrics15: 161–178.
11.
BreuschTSPaganAR (1980) The Lagrange multiplier test and its applications to model specification in econometrics. Review of Economic Studies47: 239–253.
12.
ChenQQTaylorD (2020) Economic development and pollution emissions in Singapore: evidence in support of the Environmental Kuznets Curve hypothesis and its implications for regional sustainability. Journal of Cleaner Production243: 118637.
13.
ChiJ (2020) The impact of third-country exchange rate risk on international air travel flows: the case of Korean outbound tourism demand. Transport Policy89: 66–78.
14.
ChoiI (2001) Unit root tests for panel data. Journal of International Money and Finance20: 249–272.
15.
ComerioNStrozziF (2018) Tourism and its economic impact: a literature review using bibliometric tools. Tourism Economics25: 109–131.
16.
CroSMartinsAM (2017) Structural breaks in international tourism demand: Are they caused by crises or disasters?Tourism Management63: 3–9.
17.
DoganEAslanA (2017) Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: evidence from panel models robust to heterogeneity and cross-sectional dependence. Renewable and Sustainable Energy Reviews77: 239–245.
18.
EdenhoferOPichs-MadrugaRSokonaY, et al. (2014) IPCC. Summary for Policymakers. Climate Chang 2014: Mitigation of Climate Change-summary for policy makers. Fifth Assessment WGIII AR532.
19.
FangJWenZZhangM, et al. (2014) The analyses of multiple mediation effects based on structural equation modeling. Journal of Psychological Science36: 735–741.
20.
FreitasCR (2017) Tourism climatology past and present: a review of the role of the ISB commission on climate, tourism and recreation. International Journal of Biometeorology61: 107–114.
21.
GamageNSKHewa KuruppugeRHaqIU (2017) Energy consumption, tourism development, and environmental degradation in Sri Lanka. Energy Sources, Part B: Economics, Planning and Policy12: 910–916.
22.
GösslingSScottDHallCM (2015) Inter-market variability in CO2 emission intensities in tourism: implications for destination marketing and carbon management. Tourism Management46: 203–212.
23.
HadriK (2000) Testing for stationarity in heterogeneous panel data. Econometrics Journal3: 148–161.
24.
HarrisRDFTzavalisE (1999) Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics91: 201–226.
25.
HeJYChanPWLiQS, et al. (2020) Spatiotemperal analysis of offshore wind field characteristics and energy potential in Hong Kong. Energy201: 117662.
26.
ImKSPesaranMHShinY (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics115: 53–74.
27.
JebliMBYoussefSBApergisN (2019) The dynamic linkage between renewable energy, tourism, CO2 emissions, economic growth, foreign direct investment, and trade. Latin American Economic Review28: 1–19.
28.
JorgensonDWVuKM (2016) The outlook for emerging economies. Journal of Policy Modeling38: 670–682.
29.
KaoC (1999) Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics90: 1–44.
30.
KaoCChiangMHChenB (1999) International R&D spillovers: an application of estimation and inference in panel cointegration. Oxford Bulletin of Economics and Statistics61: 691–709.
31.
KhanMYaseenMRAliQ (2019) Nexus between financial development, tourism, renewable energy, and greenhouse gas emission in high-income countries: a continent-wise analysis. Energy EconomicsAvailable online.
32.
KocakEUlucakRUlucakZS (2020) The impact of tourism developments on CO2 emissions: an advanced panel data estimation. Tourism Management Perspectives33: 100611.
33.
LeeJWBrahmasreneT (2013) Investigating the influence of tourism on economic growth and carbon emissions: evidence from panel analysis of the European Union. Tourism Management38: 69–76.
34.
LevinALinCFChuC (2002) Unit root tests in panel data: asymptotic and finite sample properties. Journal of Econometrics108: 1–24.
35.
LiLHongXFPengK (2019) A spatial panel analysis of carbon emissions, economic growth and high-technology industry in China. Structural Change and Economic Dynamics49: 83–92.
36.
LiddleB (2014) Impact of population, age structure, and urbanization on carbon emissions/energy consumption: evidence from macro-level, cross-country analyses. Population and Environment35: 286–304.
37.
LokhandwalaSGautamP (2020) Indirect impact of COVID-19 on environment: a brief study in Indian context. Environmental Research188: 109807.
38.
MackinnonDPWarsiGDwyerJH (1995) A simulation study of mediated effect measures. Multivariate Behavioral Research30: 41–62.
39.
MaddalaGSWuS (1999) A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics61: 631–652.
40.
MarsiglioS (2015) Economics growth and environment: tourism as a trigger for green growth. Tourism Economics2015; 21: 183–204.
41.
MengWQXuLYHuBB, et al. (2016) Quantifying direct and indirect carbon dioxide emissions of the Chinese tourism industry. Journal of Cleaner Production126: 586–594.
42.
MuhammadSLongXLSalmanM (2020) COVID-19 pandemic and environmental pollution: a blessing in disguise?Science of the Total Environment728: 138820.
43.
NepalRIrsyadMINepalSK (2019) Tourist arrivals, energy consumption and pollutant emissions in a developing economy-implications for sustainable tourism. Tourism Management72: 145–154.
44.
NovelliMMorganNNibigiraC (2012) Tourism in a post-conflict situation of fragility. Annals of Tourism Research39: 1446–1469.
45.
PaoHTYuHCYangYH (2011) Modeling the CO2 emissions, energy use, and economic growth in Russia. Energy36: 5094–5100.
46.
ParkJILeeS (2017) Examining the spatial patterns of green industries and the role of government policies in South Korea: application of a panel regression model (2006-2012). Renewable and Sustainable Energy Reviews78: 614–623.
47.
PedroniP (2001a) Fully modified OLS for heterogeneous cointegrated panels. In: BaltagiBH (ed) Nonstationary Panels, Panel Cointegration, and Dynamic Panels. Bingley: Emerald Group Publishing Limited, pp. 93–130.
48.
PedroniP (2001b) Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics83: 727–731.
49.
PedroniP (2004) Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis: new results. Economic Theory20: 597–627.
50.
PereiraAMRuiMandRodriguesP (2016) G.A new carbon tax in Portugal: A missed opportunity to achieve the triple dividend?Energy Policy93: 110–118.
51.
PesaranHHShinYSmithRP (1999) Pooled mean group estimation of dynamic heterogeneous panels. Journal of American Statistical Association94: 621–634.
52.
PesaranMH (2004) General diagnostic tests for cross section dependence in panels. Social Science Electronic Publishing7: 1240.
53.
PesaranMH (2007) A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics22: 265–312.
54.
PortoNEspinolaN (2019) Labor income inequalities and tourism development in Argentina: a regional approach. Tourism Economics25: 1265–1285.
55.
RamosN (2014) Communitarian ecotourism in the Colombian Darién and Urabá Region: an opportunity for peace-building. In: WohlmutherCWintersteinerW (eds) International handbook on tourism and peace. Klagenfurt: Drava Verlag, pp. 143–154.
56.
RicoAMartínez-blancoJMontlleóM, et al. (2019) Carbon footprint of tourism in Barcelona. Tourism Management70: 491–504.
57.
ScottDPeetersPGösslingS (2010) Can tourism deliver its “aspirational” greenhouse gas emissions reduction targets?Journal of Sustainable Tourism18: 393–408.
58.
SobelME (1982) Asymptotic confidence intervals for indirect effects in structural equation models. Sociological methodology13: 290–312.
59.
SolarinSA (2014) Tourist arrivals and macroeconomic determinants of CO2 emissions in Malaysia. Anatolia25: 228–241.
60.
SunYY (2016) Decomposition of tourism greenhouse gas emissions: revealing the dynamics between tourism economic growth, technological efficiency, and carbon emissions. Tourism Management55: 326–336.
61.
TangCCZhongLSNgP (2017) Factors that influence the tourism industry’s carbon emissions: a tourism area life cycle model perspective. Energy Policy109: 704–718.
WuYTamVWYShuaiCY, et al. (2019) Decoupling China’s economic growth from carbon emissions: empirical studies from 30 Chinese provinces (2001-2015). Science of the Total Environment656: 576–588.
68.
XuXReedM (2017) Perceived pollution and inbound tourism in China. Tourism Management Perspectives21: 109–112.
69.
YaoXLKouDShaoS, et al. (2018) Can urbanization process and carbon emission abatement be harmonious?Environmental Impact Assessment Review71: 70–83.
70.
YorkRRosaEADietzT (2003) STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecological Economics46: 351–365.
71.
ZafarMWZaidiSASinhaA, et al. (2019) The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries. Resource Policy62: 427–436.
72.
ZamanKShahbazMLoganathanN, et al. (2016) Tourism development, energy consumption and environmental Kuznets curve: trivariate analysis in the panel of developed and developing countries. Tourism Management54: 275–283.
73.
ZhangGXZhangPDZhangZG, et al. (2019a) Impact of environmental regulations on industrial structure upgrading: an empirical study on Beijing-Tianjin-Hebei region in China. Journal of Cleaner Production238: 117848.
74.
ZhangJZhangY (2018) Carbon tax, tourism CO2 emissions and economic welfare. Annals of Tourism Research69: 18–30.
75.
ZhangLGaoJ (2016) Exploring the effects of international tourism on China’s economic growth, energy consumption and environmental pollution: evidence from a regional panel analysis. Renewable and Sustainable Energy Reviews2016; 53: 225–234.
76.
ZhangLPangJXChenXP, et al. (2019b) Carbon emissions, energy consumption and economic growth: evidence from the agricultural sector of China’s main grain-producing areas. Science of The Total Environment665: 1017–1025.
77.
ZhangSLiuXY (2019) The role of international tourism and renewable energy in environment: new evidence from Asian countries. Renewable Energy139: 385–394.
78.
ZhangSYChanCS (2016) Nature-based tourism development in Hong Kong: importance-performance perceptions of local residents and tourists. Tourism Management Perspectives20: 38–46.
