2014年-IMF国际货币组织全球_Determinants_of_International_Tourism_46页_556kb

Summary of "Determinants of International Tourism" by Alexander Culiuc

Core Content

This paper investigates the determinants of international tourism flows using a gravity model approach, analyzing a large panel dataset of bilateral tourism flows over a decade. It compares the impact of macroeconomic and structural factors on tourism with that of goods trade, and explores non-traditional variables such as direct flights, hotel availability, climate, and conflict.

Main Findings

1. Gravity Model Performance

• The gravity model explains international tourism flows better than goods trade for equivalent specifications.
• Tourism gravity equations perform better than those for FDI and remittances.
• The elasticity of tourism with respect to the GDP of the origin country is lower than for goods trade.
• Tourism flows are more responsive to changes in the real exchange rate of the destination country, especially on both extensive (tourist arrivals) and intensive (duration of stay) margins.

2. Economic and Trade Variables

• GDPs of origin and destination countries have a strong positive impact on tourism flows.
• Distance has a negative effect, with an elasticity close to that of goods trade.
• Language ties are more important for tourism than for goods trade.
• Historical colonial relationships have a smaller effect on tourism than on goods trade.
• Common currency reduces tourism and merchandise flows, especially in the Eurozone.
• Common border increases tourism flows significantly, as it reduces transportation costs.

3. Supply-side Variables

• The presence of direct flights positively affects tourism flows, but reverse causality dominates—flights are added after tourism increases.
• Hotel room availability is positively correlated with tourism inflows, and reverse causality is not significant.
• Supply-side variables are less important for tourism within OECD countries, suggesting that supply constraints are not binding in developed economies.

4. Demand-side Variables

• Tourists prefer destinations with similar climates and warmer climates.
• Time differences negatively affect tourism, indicating that jet lag is a consideration in travel decisions.
• Cultural capital (measured by UNESCO World Heritage sites) plays a role in attracting tourists.
• Conflict significantly reduces tourism, as tourists avoid countries experiencing ongoing instability.

5. Tourist-nights Analysis

• Tourism flows respond to changes in determinants both through arrival numbers and duration of stay.
• The real effective exchange rate (REER) has a strong impact on the average duration of stay, with appreciation in the destination currency leading to shorter stays.

6. Small Island States

• Tourism to small islands is less sensitive to changes in the country's real exchange rate.
• However, it is more responsive to the introduction or removal of direct flights.
• The own real exchange rate of small islands has little impact on tourism arrivals, suggesting that other factors (like direct flights and natural attractions) are more influential.

Key Contributions

• First comprehensive analysis of the full universe of international tourism flows using a gravity model.
• Comparison with goods trade provides insights into the unique characteristics of tourism.
• Incorporation of non-traditional variables (climate, cultural capital, conflict) enriches the understanding of tourism determinants.
• Analysis of tourist-nights offers a more nuanced view of tourism behavior.
• Special attention to small island states highlights the importance of direct flights and other specific factors in their tourism dynamics.

Methodology and Data

• Data Source: UNWTO dataset, supplemented with macroeconomic and trade data from WDI, IFS, PWT, and CEPII.
• Data Coverage: Full universe of bilateral tourism flows over a decade, with 128,304 observations.
• Data Limitations:
  • Only 80% of observations have unambiguous origin identification.
  • Key variables (e.g., GDPs, distance) are available in 80.8% of the dataset.
  • Only 40% of countries report tourist-nights.
• Empirical Strategy:
  • Uses country fixed effects and country-pair fixed effects to control for multilateral resistance.
  • Applies first differences to estimate the impact of real exchange rates.
  • Uses random effects and Hausman-Taylor estimator to account for time-invariant variables.

Policy Implications

• Exchange rate policy should be considered carefully, especially for destination countries.
• Direct flights are a crucial factor for small island destinations, suggesting the importance of improving air connectivity.
• Climate and cultural factors should be integrated into tourism policy design.
• Conflict is a significant deterrent to tourism, implying the need for stability in tourism-dependent economies.
• OECD countries are less affected by supply-side constraints, indicating that tourism in developed economies is more resilient.

Conclusion

This study provides a detailed analysis of the factors influencing international tourism flows, emphasizing the role of the real exchange rate, direct flights, and non-traditional variables like climate and conflict. It highlights the importance of using comprehensive and robust data for empirical analysis and offers new insights into the dynamics of tourism, particularly for small island states. The findings suggest that tourism is not only economically significant but also highly responsive to a range of macroeconomic and structural determinants.