Ways to bring private investment to the tourism industry for green growth

The study is motivated by the escalating challenges of climate change and the imperative for green economic growth, particularly salient in the post-COVID-19 recovery period. Despite temporary emission reductions during lockdowns, global CO2 emissions rebounded, underscoring the need for sustainable approaches across sectors. Tourism is a major economic sector with diverse segments but faces environmental pressures and financing constraints for sustainability transitions. The research focuses on ASEAN economies, where capital shortages for green projects are acute and the potential for sustainable tourism is high, aligned with regional strategies (e.g., ASEAN Tourism Strategic Plan 2016–2025 and Green Hotel Standard). The central research question investigates how green growth, financial development, green finance, economic uncertainty, and inflation influence sustainable tourism (as a proxy for private investment in sustainable tourism) across 10 ASEAN countries from 2000 to 2021. The purpose is to identify determinants that can attract private investment into sustainable tourism to foster green growth, offering policy-relevant insights for the region.

Prior studies show mixed relationships between tourism and green growth. Some find tourism expansion can degrade environments and raise emissions (Pulido-Fernandez et al., 2019; Zhang et al., 2022; Guo et al., 2023; Shan & Ren, 2023), while others highlight conditions where tourism supports sustainability and emission reductions, including circular economy approaches and high-income contexts (Ahmad et al., 2022; Xu et al., 2022; Shang et al., 2023; Baloch et al., 2023; Chen, 2023). A second stream emphasizes financing constraints for sustainable tourism, stressing the pivotal role of green finance and private capital. Earlier work discussed government roles in financing tourism (Bodlender, 1982), but recent evidence points to private participation enabled by green bonds and investments in energy-efficient and smart city projects (Mucharreira et al., 2019; Lu et al., 2021; Shang et al., 2023). The literature gap identified is the limited focus on ASEAN regarding how to attract private investors to sustainable tourism. This study addresses the gap by analyzing panel data for ASEAN, linking sustainable tourism to green finance, green growth, financial development, economic uncertainty, and inflation.

Sample and period: Panel of 10 ASEAN countries (Myanmar, Indonesia, Cambodia, Vietnam, Singapore, Philippines, Malaysia, Thailand, Brunei, Laos) from 2000–2021, totaling 220 country-year observations. Dependent variable: Composite indicator of sustainable tourism (SUSTOU), calculated per Blancas and Lozano-Oyola (2022), used as a proxy for private investment in sustainable tourism. Independent variables: Green growth index (GREENG; www.greengrowthindex.gggi.org), financial development (FINAND; domestic credit to private sector as % of GDP; World Bank), green finance (GREEFI; million USD; Climate Bonds Initiative), economic uncertainty index (ECOUN; www.policyuncertainty.com), and inflation rate (INFR; %; World Bank). Empirical strategy: 1) Test cross-sectional dependence (Pesaran and Smith, 1995). 2) Apply second-generation panel unit root test CIPS to determine integration orders. 3) Assess cointegration using Westerlund (2007) ECM panel cointegration test; perform Pedroni (2004) tests as robustness. 4) Conduct Hausman test to check long-run homogeneity, guiding use of Pooled Mean Group (PMG) estimator. 5) Estimate short- and long-run elasticities via PMG. 6) Robustness check using Fully Modified OLS (FMOLS) for long-run coefficients. Data sources and units are as in Table 1; model includes standard PMG error-correction setup with SUSTOU as dependent variable and GREENG, FINAND, GREEFI, ECOUN, INFR as regressors.

Diagnostics: Cross-sectional dependence is present for all series (e.g., SUSTOU CD=34.593, p<0.001; GREEFI CD=138.584, p=0.003). CIPS tests indicate variables are non-stationary at levels but stationary in first differences (e.g., SUSTOU t=-8.494, p=0.000 at first difference). Westerlund cointegration tests support long-run cointegration (e.g., G*=-7.942, p=0.002; P*=-9.057, p=0.003), corroborated by Pedroni tests. PMG results (Table 7): Short run—GREENG positive and significant (0.439, p=0.08 marginal; reported as strongest positive), FINAND insignificant (0.102, p=0.19), GREEFI insignificant (0.039, p=0.24), ECOUN negative (−0.102, p=0.05), INFR negative and significant (−0.093, p=0.00). Long run—all variables significant: GREEFI shows the largest positive effect (0.493, p=0.00), GREENG positive (0.129, p=0.00), FINAND positive (0.094, p=0.03), ECOUN negative (−0.329, p=0.06), INFR negative (−0.168, p=0.04). Interpretation: In the short term, green economic growth most strongly boosts sustainable tourism, while uncertainty and inflation hinder it; green finance and financial development effects materialize over the long run. Robustness: FMOLS confirms signs and significance: GREENG 0.114 (p=0.00), FINAND 0.072 (p=0.03), GREEFI 0.389 (p=0.02), ECOUN −0.019 (p=0.00), INFR −0.368 (p=0.01). Policy implications: Strengthen green finance ecosystems, deepen financial markets, reduce uncertainty and inflation pressures to enhance private investment in sustainable tourism.

The findings directly address the research question by identifying which macro-financial and environmental determinants most effectively attract private investment into sustainable tourism in ASEAN. Short-run dynamics indicate that when economies demonstrate tangible green growth, private investors respond positively, whereas elevated economic policy uncertainty and inflation deter investment in projects with slower payback, such as sustainable tourism. Over the long run, the development of green finance instruments (e.g., green bonds) exerts the strongest positive influence, signaling that transparent, liquid green financing mechanisms lower barriers and improve returns/risk perceptions for private investors. Financial development further supports capital mobilization, while persistent uncertainty and inflation continue to suppress investment. These results underscore the strategic importance of building robust green finance markets and stable macro-policy environments to achieve sustainable tourism objectives, contributing to the literature by providing ASEAN-specific evidence using a composite sustainable tourism indicator.

This paper introduces an ASEAN-specific composite indicator of sustainable tourism and empirically evaluates the roles of green growth, green finance, financial development, economic uncertainty, and inflation (2000–2021). Using PMG estimation with appropriate panel diagnostics and cointegration tests, the study finds: (i) in the short run, green growth strongly promotes sustainable tourism, while uncertainty and inflation hinder it, and green finance/financial development effects are insignificant; (ii) in the long run, green finance exerts the largest positive effect, with additional positive contributions from green growth and financial development, and negative effects from uncertainty and inflation. Policy recommendations include: crafting comprehensive green financial policy packages (tax incentives, preferential rates for green deposits, subsidies), investing in ICT-based tourism services (including virtual tourism), establishing early warning systems to mitigate uncertainty and inflationary pressures, and leveraging blockchain/cryptocurrency mechanisms to mobilize capital for green investments. Future research should examine COVID-19’s impact on private investment in ecotourism and conduct country-level analyses within ASEAN to tailor policies to national contexts.

The study uses a proxy—the composite indicator of sustainable tourism—to represent private sector investment in sustainable tourism due to data unavailability, which may not fully capture actual private investment flows. The analysis is limited to 10 ASEAN countries over 2000–2021, which may affect generalizability beyond the region and period. Results rely on available datasets for green finance and uncertainty indices, which may carry measurement limitations.