Role of foreign direct Investment and political openness in boosting the eco-tourism sector for achieving sustainability

The paper investigates how political openness and foreign direct investment (FDI) affect ecotourism development in China. Against growing concerns about environmental degradation since the 1960s and the rise of sustainable development from the 1992 Earth Summit to the UN’s 17 SDGs, ecotourism has been promoted as a tool for environmental preservation, green growth, job creation, and sustainability awareness. Despite its importance, many countries have made limited progress due to internal (e.g., political openness) and external (e.g., FDI) factors. Political openness can enhance social inclusion, stability, and participation in sustainability initiatives, while FDI can fund green technologies and projects, especially in developing contexts. China is chosen due to its high CO2 emissions, environmental vulnerability, socialist governance context, and the growing prominence of ecotourism since the 1990s. The study’s purpose is to quantify the effects of political openness (Liberal Democracy Index) and FDI on China’s ecotourism (Tourism Sustainable Development Index), while comparing different forms of openness (political, trade, financial) and incorporating additional controls. It addresses a literature gap by jointly analyzing political openness and FDI for China’s ecotourism using time series data from 1985–2019.

The review is organized in three strands. (1) Tourism industry and sustainable transformation: Studies highlight ecotourism’s role in sustainability, especially post-COVID-19, via nature conservation, reduced fossil fuel use, ICT and digital services, and potential of blockchain and green finance to lower resource intensity. Key enablers include legal frameworks, social awareness, and sustainable infrastructure; ecotourism supports biodiversity, waste reduction, and circular economy, with social readiness critical for uptake. (2) Political openness and green growth: Political risk undermines green technological progress, investor willingness, and macro-financial stability, while stable political conditions foster green prosperity; policy uncertainty is detrimental to capital accumulation and sustainable investment. (3) FDI and sustainable development: Evidence is mixed regarding environmental impacts, but targeted sustainable tourism investments can restore natural resources, create green jobs, and support green technology transfer. Private sector participation is crucial, especially in developing countries, requiring effective investment regulations and incentives. Literature gap: limited research directly linking political openness and FDI to ecotourism in China; this study fills the gap with a time-series approach.

Scope and data: Annual Chinese time-series, 1985–2019, log-transformed. Dependent variable: Tourism Sustainable Development Index (TOSUS), computed per Zhang et al. (2023), as a proxy for ecotourism. Main explanatory variables: FDI inflows (China Statistical Yearbook) and political openness proxied by the Liberal Democracy Index (www.humanprogress.org). Controls: trade openness (World Bank), financial openness (Chinn-Ito index, Portland State University), renewable energy consumption (BP), and green tax (China Statistical Yearbook). Expected signs: all positive. Model: Log-linear specification LTOSUS_t = a0 + a1 LFDI_t + a2 LLDI_t + a3 LTROP_t + a4 LFIOP_t + a5 LREC_t + a6 LGRTAX_t + ε_t. Empirical strategy: (i) Correlation matrix to assess collinearity; (ii) Unit root tests using ADF and PP to determine integration orders; (iii) ARDL bounds testing (Pesaran et al., 2001) to establish long-run cointegration; (iv) ARDL long-run estimation with Error Correction Model (ECM) for short-run dynamics (Charemza and Deadman, 1997); (v) Diagnostics including Wald test and Breusch-Pagan for heteroscedasticity; (vi) Robustness checks via (a) substituting the dependent variable with a Composite Ecotourism Potential Index (CEPI) constructed per Ocampo et al. (2023) and re-estimating ARDL, and (b) re-estimation using GMM. Rationale: ARDL accommodates regressors with mixed integration orders (I(0)/I(1)) and is suitable for small samples; ECM captures short-run adjustments to long-run equilibrium.

- Correlation and stationarity: Correlation matrix shows no serious collinearity. ADF and PP unit root tests indicate mixed integration orders: LTOSUS, LTROP, LGRTAX are I(0); LLDI, LFIOP, LREC (and FDI by PP) are I(1). - Cointegration: ARDL bounds F-statistic = 5.391 exceeds the upper critical bound (e.g., 1% I(1) bound = 4.23), confirming a long-run relationship among variables. - Long-run ARDL coefficients (dependent: TOSUS): LFDI 0.012 (p=0.001) → a 1% increase in FDI raises TOSUS by 0.01% (≈0.012%). LLDI 0.539 (p=0.016) → 1% increase in political openness raises TOSUS by 0.53%. LTROP 0.186 (p=0.044) → trade openness increases TOSUS by 0.19%. LFIOP 0.235 (p=0.013) → financial openness increases TOSUS by 0.24%. LREC 0.092 (p=0.001) → renewable energy consumption boosts TOSUS. LGRTAX 0.215 (p=0.532) → green tax effect is statistically insignificant. - Short-run ECM results: D(LLDI) 0.326 (p=0.033) → 1% increase in political openness raises TOSUS by ~0.32% in the short run. D(LTROP) 0.094 (p=0.012) → trade openness positive in short run (~0.09%). D(LFIOP) 0.242 (p=0.055) → financial openness positive and marginally significant (~0.24%). D(LREC) 0.059 (p=0.008) → renewable energy positive in short run. D(LFDI) −0.055 (p=0.294) and D(LGRTAX) 0.031 (p=0.193) → short-run effects not significant. ECM term −0.864 (p=0.001) indicates rapid adjustment to long-run equilibrium. - Diagnostics: Wald test p=0.00; Breusch-Pagan p=0.583 indicates no heteroscedasticity. - Robustness (CEPI as dependent variable): Long-run signs consistent; notable effects: LFDI 0.009 (p=0.032), LLDI 0.458 (p=0.014), LFIOP 0.341 (p=0.043), LREC 0.055 (p=0.047); green tax remains insignificant. Short-run signs align with main results. - Robustness (GMM): Coefficient signs align with ARDL; key predictors (FDI, trade, financial openness) show significance consistent with main findings.

The results directly address the research question by quantifying the effects of political openness and FDI on China’s ecotourism. Political openness is a strong and consistent driver of ecotourism in both short and long horizons, supporting the theoretical view that democratization and reduced political risk enhance social inclusion, stabilize expectations, and encourage green investment and participation in sustainable activities. FDI’s impact is significant only in the long run, indicating that foreign capital and technology transfers require time to materialize in ecotourism outcomes through project gestation, diffusion of green technologies, and development of related infrastructure. Trade and financial openness also promote ecotourism—trade likely via exposure to green technologies and practices, and financial openness via expanded access to green finance and greater financial inclusion that increases both investment capacity and consumer demand for eco-services. Renewable energy consumption bolsters ecotourism by enabling cleaner operations (transport, accommodation, services). Green tax instruments, designed mainly to regulate industrial emissions, do not show a statistically significant effect on the service-oriented ecotourism sector in this period, suggesting potential policy design or sectoral targeting issues. Overall, internal (political openness) and external (FDI) factors complement each other, but political openness exhibits the strongest and most pervasive influence on ecotourism development.

The study demonstrates that in China (1985–2019): (i) FDI promotes ecotourism in the long run only; (ii) political openness substantially raises the ecotourism index in both short and long run and is more influential than trade or financial openness; (iii) financial and trade openness contribute positively; (iv) renewable energy consumption supports ecotourism; and (v) green tax policies have limited, statistically insignificant effects on ecotourism. Policy recommendations include: ensuring political stability and openness to strengthen investor confidence and public participation; modernizing and broadening green financial markets—leveraging fintech and blockchain—to increase access to green finance; intensifying poverty alleviation to enhance inclusion and demand for eco-services; and creating local green funds to mobilize household participation in community-level green projects (e.g., green electricity). Future research should examine subnational (regional/provincial/city) dynamics, assess COVID-19 impacts using qualitative methods, and evaluate the feasibility of cryptocurrency-based payments for ecotourism.

The analysis is limited to national-level annual data for China from 1985–2019, which may mask subnational heterogeneity. The study does not assess regional/provincial/city-level effects, nor the specific impacts of the COVID-19 pandemic. The green tax’s limited effect in the service sector suggests that the chosen proxy and period may not fully capture sector-specific policy impacts. While robustness checks (alternative dependent variable and GMM) support the findings, causality beyond the ARDL framework is not established definitively.