Eastern Caribbean Currency Union: Selected Issues
Author:
International Monetary Fund
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Publication Date:
07 Mar 2008
eISBN:
9781451811728
Language:
English
Keywords:
ISCR; CR; ECCU; exchange rate; tax; tourism-source diversification; source market; tourism arrival; tourism sector; world tourism; Caribbean
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This paper assesses the evolution of Eastern Caribbean Currency Union (ECCU) real exchange rates over time, and examines whether the region has lost competitiveness. The main finding is that there is little evidence of overvaluation of the Eastern Caribbean (EC) dollar. The relationship summarized above permits the calculation of equilibrium current account balances or norms. The financing of ECCU current account imbalances appears stable. This paper also provides evidence on the distinctive impact that tourism plays in the determination of the real exchange rate in tourism-driven economies.

Abstract

This paper assesses the evolution of Eastern Caribbean Currency Union (ECCU) real exchange rates over time, and examines whether the region has lost competitiveness. The main finding is that there is little evidence of overvaluation of the Eastern Caribbean (EC) dollar. The relationship summarized above permits the calculation of equilibrium current account balances or norms. The financing of ECCU current account imbalances appears stable. This paper also provides evidence on the distinctive impact that tourism plays in the determination of the real exchange rate in tourism-driven economies.

V. Tourism Demand in Small-Island Economies34

A. Introduction

1. The tourism sector has become an important source of output growth and foreign exchange earnings in the ECCU region. Estimates suggest that a 1 percent increase in tourist arrivals in the ECCU is associated with about ½ of 1 percent increase in real GDP. In addition, tourism receipts represented the equivalent of over 80 percent of GDP during 1996–2005, while about 60 percent of FDI in the region has been concentrated in the tourism sector.

2. While world tourism has been increasing sharply, the ECCU’s share has declined. In particular, the ECCU’s share of the Caribbean market declined by 0.3 percentage points to 5.1 percent between 1996–2005. Given the significance of the sector, it is important to understand the determinants of tourism flows, in particular why some countries are successful tourism destinations, and the challenges of increasing tourism flows.

3. This chapter examines the main factors affecting tourism flows in small-island economies, using an empirical approach that accounts for the inherent heterogeneity of the tourism product and tourism consumers.35 Tourists derive different experiences from various destinations, suggesting that there may be country-specific factors that host islands could leverage to boost tourism (Papatheodorou, 2001; Zhang and Jensen, 2005). The chapter uses cross-sectional least squares analysis to examine the determinants of tourism arrivals, taking into account the country of origin of tourists. Tourism flows are grouped into country pairings—from source (tourism-originating) country to host island—in order to capture the particularities of the tourism products. The chapter then investigates the extent to which country-specific factors in both source and host countries affect tourism flows. Appendix V.1 outlines the model and country pairings.

B. Factors Affecting Tourism Flows

4. Tourism flows are affected, among other things, by real exchange rate (RER) movements, real income in tourism-source countries, and adverse shocks. Other inhibiting factors include limited air access, crime, and small hotel stock capacity. Tourism flows appear to be directly related to greater accessibility but inversely related with crime, with the exception of Grenada and St. Kitts and Nevis (Figures V.1–V.2). In addition, an increase in hotel stock capacity tends to be associated with a decline in occupancy rates, but this could reflect the delayed impact of higher hotel stock capacity on tourism flows (Figure V.3). The ECCU hotel stock is large in view of its land size and the ECCU countries’ objective of becoming/remaining “niche and unique” tourist destinations (Figure V.4). In addition, tourism flows to the ECCU seem to be more volatile than in other Caribbean islands (Figure V.5).

Figure V.1.
Figure V.1.

Caribbean: Airlift Accessibility and Tourism Flows, 2002 1/

(Number of Direct Scheduled Flights and Stay-over Tourist Arrivals to and from the USA)

Citation: IMF Staff Country Reports 2008, 096; 10.5089/9781451811728.002.A005

Sources: Caribbean Tourism Organization; Traffic By Flight stage 2002, No. 518, International Civil Aviation organization; and U.S. Department of Transportation, Bureau of Transportation Statistics (http://www.transtats.bts.gov).1/ No reliable data are available for the period after 2002.
Figure V.2.
Figure V.2.

Caribbean: Tourism Flows and Homicides, 1996–2005 1/

(Above-trend tourist arrivals, and number of murders, index 1996=100)

Citation: IMF Staff Country Reports 2008, 096; 10.5089/9781451811728.002.A005

Sources: Country authorities; World Health Organization; Pan American Health Organization (http://www.paho.org); United Nations, Survey on Crime Trends and the Operations of Criminal Justice Systems (http://www.unodc.org); and Wikipedia (http://www.wikipedia.org).1/ Above-trend tourism arrivalsare extracted using Hodrick Prescott (1997) filter as a proxy for the tourism industry’s potential. When arrivals are above trend (i.e., a positive gap) we assume that the industry has performed well, and the converse when they are below trend.
Figure V.3.
Figure V.3.

Caribbean: Hotel Capacity and Occupancy Rates, 1997–2005 1/

(Index 1997=100)

Citation: IMF Staff Country Reports 2008, 096; 10.5089/9781451811728.002.A005

Sources: Country authorities; Caribbean Tourism Organization; and World Tourism Organization.1/ Occupancy rate is defined as the number of occupied rooms as a percent of total number of rooms available for hire over a specified period. Due to data limitations the regional groups do not capture all the Caribbean islands. The regional groups are as follows: Other Commonwealth captures The Bahamas, Barbados, Belize, Bermuda, Cayman Islands, Jamaica and Trinidad and Tobago; Dutch West Indies refers to Aruba and Curacao; French West Indies refers to Martinique; U.S. Territories reflects Puerto Rico and U.S. Virgin Islands; and Other Countries refers to Cancun and the Dominican Republic.
Figure V.4.
Figure V.4.

Caribbean: Hotel Rooms, 2005 1/

(Number of rooms per square kilometer)

Citation: IMF Staff Country Reports 2008, 096; 10.5089/9781451811728.002.A005

Sources: Country authorities; Caribbean Tourism Organization; CIA, Factbook; Institut National de la Statistique et des Études Économiques (INSEE); World Tourism Organization; UN, World Population Prospects 2006; Caribbean Travel (http://www.caribbeantravelmag.com); Wikipedia (http://www.wikipedia.org); and Fund staff estimates.1/ Where data in 2005 is not available, 2004 data is used.
Figure V.5.
Figure V.5.

Caribbean: Volatility of Expenditure and Average Share of UK and USA Tourists, 1997–2005

(ECCU and five largest Caribbean destinations)

Citation: IMF Staff Country Reports 2008, 096; 10.5089/9781451811728.002.A005

Sources: Country authorities; Caribbean Tourism Organization; and World Tourism Organization.

5. The results from the cross-sectional analysis indicate, not surprisingly, that cheaper destinations (i.e., those with more depreciated RERs) and those with larger hotel room capacity tend to receive more tourists (Table V.1). Specifically, the results indicate that:

  • Tourist flows in islands with a 1 percent more depreciated bilateral RER tend to be about 0.19 percent higher than in other islands, suggesting in general that tourists consider the islands as substitute destinations.

  • Islands that have 1 percent higher number of rooms tend to receive about 0.9 percent more tourists, even after taking into account land size. Since hotel rooms are a proxy for the capacity of the tourism sector, this suggests that islands with more tourism capacity are more competitive.

  • Countries with a 1 percent higher GDP per capita tend to have fewer tourist outflows to the Caribbean. These findings probably reflect the fact that the countries with the highest GDP per capita (Japan, Sweden and Switzerland) have typically had the lowest tourist outflows to the Caribbean.

  • Country-specific factors also seem to be important, in particular, shared language areas tend to receive higher tourists. The results suggest that the ECCU islands’ smaller land size has not adversely affected tourism flows.

Table V.1.

Why Are Some Destinations More Attractive?: Cross-Sectional Analysis 1/

article image
Source: Author’s calculations.

The data cover country-pairings from about 12 source countries for a maximum of 31 destination countries.***,** and* indicate 1 percent, 5 percent and 10 percent levels of significance, respectively. Selected years are reported for brevity.

All variables are in logarithms with the exception of the (number of) direct flights and the dummy variables (pre-fix “DV”). The last four dummy variables are regional dummies to capture the extent to which these regions have higher tourism flows than the ECCU countries.

Positive denotes an appreciation.

6. To investigate the extent to which country-specific factors affect the results, we consider the significance of these factors in individual ECCU countries. Tourism flows in the ECCU are sensitive to RER movements and increases in hotel capacity, but are generally not affected by increases in real income per capita in the source country (Table V.2). The specific results suggest that:

  • A real exchange rate depreciation has a significant positive impact on tourism flows. The price elasticity ranges from 0.39 percent to 1.34 percent, and is more elastic (greater than unity) in the more established ECCU tourist destinations—Antigua and Barbuda and St. Lucia.

  • An increase in real income per capita in source markets does not statistically affect tourism flows, with the exception of Grenada, and St. Vincent and the Grenadines. The latter two islands face highly elastic demand—3.82 and 1.82 percent, respectively. The statistical insignificance of tourism flows to real income per capita in some islands is probably driven by the short-run dynamics, in particular, that tourism growth since the early 2000s in these islands coincided with the world recession.36

  • An increase in hotel capacity has varying impact on tourism flows across countries. Capacity has a statistically negative impact on tourism flows to Grenada and St. Kitts and Nevis, and no impact on Antigua and Barbuda, Dominica and St. Vincent and the Grenadines. This could reflect lags in the impact of hotel capacity on tourism, since hotel room expansion in the ECCU countries has been supply-driven.37 Hotel capacity tends to be positively associated with tourism flows to St. Lucia.

  • An increase in homicides has varying impact on tourism flows across Caribbean countries. Murders have a statistically negative impact on tourism flows to St. Lucia, and no impact on flows to Antigua and Barbuda, Dominica and Grenada. Unusually, higher homicide rates tend to be positively related with tourism flows to St. Vincent and the Grenadines and St. Kitts and Nevis—possibly reflecting the fact that the slump in tourism arrivals in the late 1990s/early 2000s coincided with a drop in homicide rates while the ensuing increase in tourism arrivals coincided with a rise in homicide rates.

Table V.2.

Determinants of Tourism Flows to ECCU Countries: Panel Least Squares 1/

article image
Source: Author’s calculations.

The data cover country-pairings from about 12 source countries over period 1996 to 2005. The panel is unbalanced due to some missing observations.***,** and* indicate 1 percent, 5 percent and 10 percent levels of significance, respectively. All the reported findings, with the exception of Dominica, are based on cross-sectional time series using feasibile least squares allowing for presence of autocorelation within panel and heteroscedasticity across panels. Dominica findings are based on Prais-Winsten regressions, where panels are corrected for within panel AR(1) process.

Δ denotes change. All variables are in logarithms with the exception of the dummy variables (pre-fix “DV”).

Positive denotes an appreciation.

7. The U.K. and U.S. are important sources of tourist flows to the ECCU region (Figure V.5). Generally, the flows from source countries differ significantly, exhibiting the following characteristics (Table V.3):

  • British tourists tend to be price-insensitive but income elastic, suggesting that an increase in real income per capita has a significant impact on tourism flows but a real exchange rate depreciation does not. These findings could reflect their tendency to use vacation packages—which include hotel and flights—priced in pounds sterling as this insulates them from relative price movements. Tourism flows tend to be significantly lower in islands that have greater airlift to the U.K., probably reflecting the tendency of tour operators to use charter flights.38 An increase in hotel stock capacity does not have a significant impact on tourism flows. Previous tourism flow arrivals seem to have a negative impact on current tourism, suggesting that tourists are sensitive to their past experience on the island or prefer to visit new destinations.

  • American tourists tend to be price and income-insensitive, which indicate that neither real exchange rate depreciation nor increases in real income per capita have a statistically significant effect on tourism flows. However, an increase in hotel capacity and accessibility tends to be associated with a rise in tourism arrivals from Canada and the U.S.

  • The findings underscore the sensitivity of tourism flows to exogenous shocks.

    Terrorist attacks, such as the 9/11 attacks, and hurricanes tend to result in a decline in British tourists. However, American tourists do not seem to be sensitive to hurricanes.

Table V.3.

Factors that Affect Tourism Flows from Main Source Markets to the Caribbean: Panel Least Squares 1/

article image
Source: Author’s calculations.

The data cover country-pairings from about 31 host countries over period 1996 to 2005. The panel is unbalanced due to some missing observations.***,** and* indicate 1 percent, 5 percent and 10 percent levels of significance, respectively. Selected countries are reported for brevity. All the reported findings, with the exception of France and Germany are based on cross-sectional time series using feasibile least squares allowing for presence of autocorelation within panel and heteroscedasticity across panels. The French and German results are based on cross-sectional time series using feasibile least squares allowing for presence of autocorelation and heteroscedasticity across panels.

Δ denotes change. All variables are in logarithms with the exception of the dummy variables (pre-fix “DV’). The last three dummy variables are regional dummies to capture the extent to which the regions are significantly different from the sample mean. DV_other refers to Cancun, Dominican Republic, Haiti and Suriname. The other regional dummy variables are omitted as they are not significant.

Positive denotes an appreciation.

C. Conclusions

8. In order to boost tourism flows, the ECCU authorities could focus on improving competitiveness, ensuring inflation stability, bolstering law enforcement, and promoting tourism-source diversification. Labor market reforms and improvements in the investment climate could enhance efficiency and help improve price competitiveness. Fiscal consolidation—particularly expenditure restraint—could help bolster inflation stability. Diversifying tourism source markets would help reduce vulnerability to shocks emanating from the source markets themselves. Improving law enforcement is also important, since a highly-publicized crime can significantly affect tourist perceptions of safety.

Appendix V.1: Data and Estimation Methodology

1. Data description:

The dataset includes 31 host countries and 12 source countries between 1996 and 2005. The host countries are: Anguilla, Antigua and Barbuda, Aruba, The Bahamas, Barbados, Belize, Bermuda, Bonaire, British Virgin Islands, Cancun (Mexico), Cayman Islands, Curacao, Dominica, Dominican Republic, Grenada, Guadeloupe, Guyana, Haiti, Jamaica, Martinique, Montserrat, Puerto Rico, St. Kitts and Nevis, St. Lucia, St. Maarten, St. Vincent and the Grenadines, Saba, St. Eustatius, Suriname, Trinidad and Tobago, and U.S. Virgin Islands. The source countries are Belgium, Canada, France, Germany, Japan, Italy, Netherlands, Spain, Sweden, Switzerland, U.K., and the U.S.

2. Data sources:

Data Description and Sources

article image

3. Econometric methodology:

The following models are estimated:

(i) Cross-sectional analysis (Table V.1):

Xij=α0Hiα1Yjα2Dijα3Pijα4ϑijα5ziα6 This is estimated for each year—1996 through 2005.

(ii) Panel analysis for each individual host country (Table V.2):

Xjt=α0Htα1Yjtα2Djα3Pjta4ϑjα5ztα6 This is estimated for each individual host country.

(iii) Panel analysis for each individual source country (Table V.3):

X i t = α 0 H i t α 1 Y t α 2 D i α 3 P i t α 4 ϑ i α 5 z i t α 6       where:

X denotes tourism arrivals;39 H denotes hotel stock and is a proxy for supply capacity; and Y denotes real GDP and reflects the demand-generating capacity of the source country. D captures airlift accessibility and is defined as the number of direct scheduled flights; P denotes the bilateral real exchange rate (RER) and is a proxy for the relative ‘price’ of tourism.ϑ denotes country-pair specific factors, including colonial ties and z captures other factors relevant to tourism such as crime and exogenous shocks (captured by the September 11 terrorist attacks and hurricanes). Subscripts i, j and t reflect host country, source country and time period, respectively.

To address endogeneity, crime, RER and hotel stock are lagged by one year.

4. Cointegration results:

Tourism arrivals and real GDP in the ECCU are found to be cointegrated and exhibit the following long-run relationship: ln(GDP) = 3.73 + 0.67ln(tourism) + 0.01t, where tourism is the total number of tourists that arrived in the ECCU region, real GDP is the total ECCU real GDP, and t is a linear time trend. The analysis uses annual ECCU data covering the period 1979–2005. In the short run, Δln(GDP) = −0.44(ln(GDPt-1) – 0.67ln(tourismt-1) – 0.01t – 3.73) + 0.44(Δln(GDPt-1) + 0.50Δln(GDPt-2) – 0.19.ln(tourismt-3). Panel analysis—based on Pedroni (2004)—involving the six ECCU countries for the period 1996–2005 also supports these findings.

References

  • Durbarry, R., 2001, “Tourism Expenditure in the U.K.: Analysis of Competitiveness Using a Gravity-Based Model,” University of Nottingham Business School, mimeograph.

    • Search Google Scholar
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  • Fodor’s, 2006, Fodor’s Caribbean 2007, Fodor’s Travel Guides (New York City).

  • Hodrick, R.J., and E.C. Prescott, 1997, “Postwar U.S. Business Cycles: An Empirical Investigation,” Journal of Money, Credit and Banking, Vol. 29, pp. 1–16.

    • Search Google Scholar
    • Export Citation

  • Papatheodorou, A., 2001, “Why People Travel to Different Places,” Annals of Tourism Research, Vol. 28, pp. 164–79.

  • Pedroni, P., 2004, “Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis,” Econometric Theory, Vol. 20, pp. 597–625.

    • Search Google Scholar
    • Export Citation

  • Zhang, J., and C. Jensen, 2005, “Comparative Advantage in Tourism: A Supply-Side Analysis of Tourism Flows” Institute of Local Government Studies (akf) Working Paper, Denmark.

    • Search Google Scholar
    • Export Citation
34

Prepared by Nkunde Mwase.

36

Due to limited long-run data, the short-and-long run effects could not be decomposed.

37

Due to data constraints, only a one-year lag is considered.

38

The airlift variable used in the estimation only captures scheduled flights.

39

Tourism arrivals data were used due to lack of reliable comprehensive expenditure data.

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Cover IMF Staff Country Reports
Eastern Caribbean Currency Union: Selected Issues
Author:
International Monetary Fund
Volume/Issue:
Volume 2008: Issue 096
Publisher:
International Monetary Fund
ISBN:
9781451811728
ISSN:
1934-7685
Pages:
102
DOI:
https://doi.org/10.5089/9781451811728.002
  • Figure V.1.
    View in gallery
    Figure V.1.

    Caribbean: Airlift Accessibility and Tourism Flows, 2002 1/

    (Number of Direct Scheduled Flights and Stay-over Tourist Arrivals to and from the USA)

  • Figure V.2.
    View in gallery
    Figure V.2.

    Caribbean: Tourism Flows and Homicides, 1996–2005 1/

    (Above-trend tourist arrivals, and number of murders, index 1996=100)

  • Figure V.3.
    View in gallery
    Figure V.3.

    Caribbean: Hotel Capacity and Occupancy Rates, 1997–2005 1/

    (Index 1997=100)

  • Figure V.4.
    View in gallery
    Figure V.4.

    Caribbean: Hotel Rooms, 2005 1/

    (Number of rooms per square kilometer)

  • Figure V.5.
    View in gallery
    Figure V.5.

    Caribbean: Volatility of Expenditure and Average Share of UK and USA Tourists, 1997–2005

    (ECCU and five largest Caribbean destinations)

Figure V.1.

Caribbean: Airlift Accessibility and Tourism Flows, 2002 1/

(Number of Direct Scheduled Flights and Stay-over Tourist Arrivals to and from the USA)
Figure V.2.

Caribbean: Tourism Flows and Homicides, 1996–2005 1/

(Above-trend tourist arrivals, and number of murders, index 1996=100)
Figure V.3.

Caribbean: Hotel Capacity and Occupancy Rates, 1997–2005 1/

(Index 1997=100)
Figure V.4.

Caribbean: Hotel Rooms, 2005 1/

(Number of rooms per square kilometer)
Figure V.5.

Caribbean: Volatility of Expenditure and Average Share of UK and USA Tourists, 1997–2005

(ECCU and five largest Caribbean destinations)