The document discusses various methodologies for measuring tourism's contribution to economic growth, including cointegration and Granger causality tests, cross-section analysis, dynamic panel data analysis, Cobb-Douglas production functions, and computable general equilibrium models. It also examines proxy variables used to measure tourism development and the growth decomposition methodology. Empirical results are presented on tourism's contribution to economic growth by region from 2006 to 2010. Finally, factors that can influence tourism's impact on growth are explored, along with regression results from a model of these factors.

1. Tourism and economic growth
Stanislav Ivanov, Ph. D.
Associate Professor and Vice Rector for Academic Affairs
International University College
E-mail: stanislav.ivanov@vumk.eu
Editor-in-chief: European Journal of Tourism Research
http://ejtr.vumk.eu

2. Tourism and economic growth
•Methodologies for measuring tourism’s contribution to economic growth
•Tourism development proxy variables
•Growth decomposition methodology
•Tourism’s contribution to economic growth – empirical results
•Factors influencing tourism’s contribution to economic growth
•References

3. Methodologies for measuring tourism’s contribution to economic growth
Cointegration and Granger causality test
•Models changes in GDP (usually in a logarithmic form) as a function of a tourism development related proxy variable. It is often adopted for checking the tourism-led growth hypothesis (Brida, Barquet & Risso, 2010)
•Advantage: determines the existence of correlation between tourism development and economic growth and the direction of causal relationship.

4. Methodologies for measuring tourism’s contribution to economic growth
Cointegration and Granger causality test
Disadvantages:
-Cannot determine the magnitude of the economic growth in each year of the analysed period that is attributable to tourism development;
-Yearly data are not sufficient to represent the long-term relationship between two variables;
-Inability of the yearly data to eliminate the problems of short-term fluctuations due to business cycles and structural change;
-Failure to delineate countries with special features in terms of different causal relationships (Po & Huang, 2008: 5540).

5. Methodologies for measuring tourism’s contribution to economic growth
Cross-section analysis (e.g. Goel & Budak, 2010)
•Aims at identifying the correlation between tourism and economic growth over a cross section of countries within determined moment of time.

6. Methodologies for measuring tourism’s contribution to economic growth
Cross-section analysis
•Advantage: possibility to model different country characteristics (e.g. membership in an organisation or trading block, oil-exporting country, geographical location, least developed country status, etc.) and to investigate their impacts on economic growth.
•Disadvantage: As regression is applied over a single time moment one cannot capture the dynamic aspects of the relationship between tourism and growth.

7. Methodologies for measuring tourism’s contribution to economic growth
Dynamic panel data analysis (e.g. Proença & Soukiazis, 2008 )
•Allows for the identification of long-run causal relationship between tourism and economic growth over multiple countries, not only a single one, through the integration of panel data analysis with cointegration and Granger causality test (e.g. Narayan et al., 2010).

8. Methodologies for measuring tourism’s contribution to economic growth
Dynamic panel data analysis
•Advantages: overcomes the cross-section analysis weakness by utilising time-series data over a cross- section of countries and allows modelling of countries’ specific characteristics.
•Disadvantage: main challenge is the consistency of statistical data across countries and over time

9. Methodologies for measuring tourism’s contribution to economic growth
Cobb-Douglas production function (e.g. Capo, Riera & Rossello, 2007)
Main challenges:
•firms within the same industry have very different production functions that cannot be aggregated (Ivanov and Webster, 2010);
•Cobb-Douglas production function assumes constant output elasticities of capital and labour given the technology level which does not need to be true in reality.

10. Methodologies for measuring tourism’s contribution to economic growth
Computable General Equilibrium models (e.g. Blake et al., 2008)
•Used to model potential external shocks and their impacts on the economy (increase or decrease in tourism demand, new tourism tax, changes in legislation, etc.).

11. Methodologies for measuring tourism’s contribution to economic growth
Computable General Equilibrium models
•Advantage: provide a comprehensive overview of the potential consequences of the shocks on country, industry and household levels and could be used for forecasting and in government policy planning.
•Disadvantages: identify potential ex ante but not actual ex post tourism impacts. Therefore, they cannot be used to measure the actual contribution of tourism to economic growth, but only to model the eventual consequences to economic growth of potential shocks in tourism demand, supply or government policy.

12. Tourism development proxy variables
Monetary proxy variables:
•Tourism GDP / GVA
•Hotels and restaurants GDP / GVA
•International tourism receipts
•Per capita (real) international tourism receipts
•Tourist expenditures of international visitors from particular country
•Revenues of hotels and restaurants
•Internal travel and tourism consumption

13. Tourism development proxy variables
Non-monetary proxy variables:
•Number of beds in accommodation establishments
•Number of international tourist arrivals
•Total tourist arrivals
•Per capita overnights of domestic and international tourists
•Per capita domestic and international arrivals
•Per capita international tourist arrivals
•Tourism receipts as percent of exports
•Tourism receipts as percent of GDP

14. Growth decomposition methodology
•The growth of the real GDP per capita is expressed as follows:
(1)
100.10)( 1)( 0001              NYNYgpqpqr

15. Growth decomposition methodology
•After disaggregating (1) we get:
(2)
100.0)( 0)( 0)( 1)( 1)( 00011                     NYNYNYNYNYgooooopqtiipqtpqtiipqtpqr

16. Growth decomposition methodology
•Regrouping (2) leads to equation (3) which measures tourism’s direct impact on economic growth (Ivanov & Webster, 2007):
(3)
100.0)( 0)( 1)( 001NYNYNYgooopqtpqtpqtr  

17. Tourism’s contribution to economic growth – empirical results
Region
2006
2007
2008
2009
2010
Average
(2000-2010)
WORLD
0.0374%
0.0650%
-0.0799%
-0.1290%
0.0670%
0.0145%
AFRICA
-0.2499%
0.2741%
-0.0577%
-0.0674%
-0.0256%
0.1938%
ASIA
0.1811%
0.2060%
0.0012%
-0.0286%
0.1022%
0.1073%
EUROPE
0.0698%
0.0027%
-0.0862%
-0.1608%
0.0175%
-0.0069%
LATIN AMERICA AND THE CARIBBEAN
-0.1245%
0.2018%
-0.0966%
-0.1938%
0.1335%
0.0799%
NORTHERN AMERICA
-0.0240%
0.0182%
-0.0946%
-0.1700%
0.1153%
-0.0225%
OCEANIA
-0.0489%
-0.1375%
-0.3253%
0.2447%
0.0641%
-0.0007%
•Global picture

18. Tourism’s contribution to economic growth – empirical results
Region
2006
2007
2008
2009
2010
Average
(2000-2010)
WORLD
0.0374%
0.0650%
-0.0799%
-0.1290%
0.0670%
0.0145%
EUROPE
0.0698%
0.0027%
-0.0862%
-0.1608%
0.0175%
-0.0069%
Bulgaria
0.1030%
-2.0286%
-0.0974%
-0.1184%
0.2695%
0.2899%
Spain
0.0730%
-0.0872%
-0.1547%
-0.5488%
-0.0096%
-0.0190%
•Countries comparison

19. Factors influencing tourism’s contribution to economic growth
Research question
Factor
Variable
Does tourism contribute to economic growth more in smaller countries?
Population size
Log average midyear population size
Does tourism stimulate the economy more in smaller economies?
Economy size
Log average GDP in USD in constant 2005 prices
Does tourism GDP volume stimulate per capita economic growth?
Tourism GDP
Log average tourism GDP in USD in constant 2005 prices
Does tourism have higher contribution to growth in economies where it has a greater share of the GDP?
Tourism share in country GDP
Average tourism share in country GDP (percent)
Does tourism contribute more to economic welfare in poorer countries?
Economic wealth of local population
Log average per capita GDP in USD in constant 2005 prices
Are there regional variations in tourism’s contribution to economic growth?
Geographic region
Dummy variables for regions
Does tourism stimulate LDCs’ economic growth more than for other countries?
LDCs
Dummy variables for LDCs

20. Model
Unstandardized Coefficients
Standardized Coefficients
t
Significance
B
Std. Error
Beta
(Constant)
-0.529
0.763
-0.694
0.489
Log average total population (2000-2010)
0.056
0.049
0.233
1.134
0.259
Log average GDP (1999-2009) in constant 2005 prices (USD)
-0.002
0.049
-0.010
-0.045
0.965
Average per capita GDP (1999-2009) in constant 2005 prices (USD)
-3.024E- 6
0.000
-0.091
-0.725
0.469
Average tourism and travel GDP (2000-2010) in constant 2005 prices (USD)
-0.001
0.001
-0.083
-1.032
0.303
Average tourism share in GDP (2000-2010)
5.398
0.544
0.707
9.930
0.000
Asia dummy variable
0.021
0.098
0.017
0.212
0.832
Europe dummy variable
0.059
0.114
0.048
0.521
0.603
Latin America and the Caribbean dummy variable
-0.227
0.106
-0.183
-2.147
0.033
Northern America dummy variable
0.134
0.302
0.034
0.443
0.659
Oceania dummy variable
-0.183
0.165
-0.075
-1.111
0.268
Least developed countries dummy variable
0.045
0.122
0.033
0.372
0.711
Excluded variables
Beta In
t
Significance
Partial Correlation
Collinearity Statistics
Tolerance
Africa dummy variable
.
.
.
.
0.000
R
R2
Adjusted R2
Standard Error of the Estimate
Model summary
0.659
0.435
0.396
0.3994144%

21. References
•Blake, A., Arbache, J. S., Sinclair, M. T., and Teles, V. (2008), ‘Tourism and poverty relief’. Annals of Tourism Research, Vol 35, No 1, pp 107-126.
•Brida, J. G., Barquet, A., and Risso, W. A. (2010), ‘Causality between economic growth and tourism expansion: Empirical evidence from Trentino-Alto adige’, Tourismos, 5(2), pp 87-98.
•Capo, J. P, Riera, A. F., and Rossello, J. N. (2007), ‘Tourism and long-term growth. A Spanish perspective’, Annals of Tourism Research, Vol 34, No 3, pp 709–726.
•Goel, R. K., and Budak, J. (2010), ‘Tourism policies and cross-country growth: A disaggregated analysis’, Tourism Economics, Vol 16, No 3, pp 535-548.
•Ivanov, S., and Webster, C. (2007), ‘Measuring the impact of tourism on economic growth’, Tourism Economics, Vol 13, No 3, pp 379–388.
•Ivanov, S., and Webster, C. (2010), ‘Decomposition of economic growth in Bulgaria by industry’, Journal of Economic Studies, Vol 37, No (2), pp 219-227.
•Narayan, P., Narayan, S., Prasad, A., and Prasad, B. C. (2010). Tourism and economic growth: a panel data analysis for Pacific Island countries. Tourism Economics, 16(1), 169–183.
•Po, W.-C., and Huang, B-N. (2008), ‘Tourism development and economic growth – a nonlinear approach’, Physica A, Vol 387, 5535–5542.
•Proença, S., and Soukiazis, E. (2008), ‘Tourism as an economic growth factor: a case study for Southern European countries’, Tourism Economics, Vol 14, No 4, pp 791–806.

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