DSpace at VNU: Research note: Empirical assessment of the tourism-led growth hypothesis - the case of Vietnam

Tourism Economics, 2014, 20 (4), 885–892 doi: 10.5367/te.2013.0307 Research note: Empirical assessment of the tourism-led growth hypothesis – the case of Vietnam NGUYEN HO MINH TRANG College of Economics, Hue University, 100 Phung Hung street, Hue City, Vietnam, and University of Economics and Law, Vietnam National University, Ho Chi Minh City E-mail: nguyenhominhtrang@gmail.com (Corresponding author.) NGUYEN HUU CHAU DUC Hue University of Medicine and Pharmacy, Hue City, Vietnam, and Department of International Health, Tokyo Medical and Dental University, Tokyo, Japan E-mail: duc.ith@tmd.ac.jp NGUYEN TIEN DUNG University of Economics and Law, Vietnam National University, Ho Chi Minh City, Vietnam E-mail: ntdung@uel.edu.vn This study examines the tourism-led growth hypothesis (TLGH) in Vietnam during the period 1992–2011 The authors use two-step procedures to test the hypothesis They first apply cointegration and the Granger causality test to identify the relationships between tourism earning and gross domestic product (GDP) Second, they use growth decomposition methodology to measure the contribution of tourism to economic growth The results indicate that it is worthwhile for the government to implement economic policies to stimulate economic growth through the tourism sector in Vietnam Keywords: TLGH; economic growth; cointegration; ECM; Granger causality; Vietnam In recent years, tourism business development in Vietnam has attracted research interest Economists have emphasized the importance of tourism to the economy, with rapid tourism growth bringing about an increase of household incomes and government revenues through multiplier effects and improvements in the balance of payments As such, the development of tourism has usually been considered as a positive contribution to economic growth (Dritsakis 2004; Brida et al, 2008; Cortes-Jimenez and Pulma, 2010; Cortes-Jimenez et al, 2011; Xie et al, 2011; Ivanov and Webster, 2013) According to estimates of the World 886 TOURISM ECONOMICS Tourism Organization (2009) the scale of the world tourism industry will reach roughly 11% of the world’s GDP in 2014 Vietnam, in South East Asia, has emerged as a tourist destination for backpackers, culture and nature lovers, sand and sun tourists, and attracts longstay touring by veterans of the Vietnam War In the period 1992–2011, there was a breakthrough improvement in the number of visitors and tourism development Vietnam welcomed just over 250,000 foreign tourist arrivals in 1992, compared to 6,014,000 in 2011 The real tourism earnings increased from US$420 million to US$2,203 million Although the tourism industry has grown significantly in Vietnam, tourism researchers have not paid much attention to the empirical assessment of the role of the tourism sector to Vietnam’s economy This study therefore aims to further this important area of inquiry by answering the following questions Is there tourism-led growth in Vietnam? How much does tourism contribute to economic growth in Vietnam? We empirically investigate the relationships between tourism, economic growth and the real exchange rate; the hypotheses are tested empirically by using cointegration and the Granger causality test Finally, we quantify the contribution of the tourism industry to economic growth through the growth decomposition methodology Literature review Similar empirical analysis to this hypothesis has been conducted in different countries in employing different methods For instance, using Spanish data, Balaguer and Cantavell-Jorda (2002) discovered a stable long-run relationship between tourism and economic growth In Turkey, Gunduz and Hatemi (2005) also found empirical support for the tourism-led growth hypothesis (TLGH) Akinboade and Braimoh (2010) and Brida et al (2010) confirmed empirical support for the TLGH in South Africa and Uruguay However, most of these studies were based on a model that included three variables – real GDP, tourism earnings and the real exchange rate – and used the Johansen’s cointegration, the error correction model (ECM) and Granger causality test to examine the TLGH In addition, the Granger causality results suggested a bidirectional causality between tourism and economic growth (Seetanah, 2011), unidirectional causality with either the TLGH (Katircioglu, 2010, for Singapore; Cortes-Jimenez et al, 2011 for Tunisia) or economic-driven tourism growth hypothesis (Oh, 2005; Katircioglu, 2009) However, their common disadvantage is that they did not state how much of the economic growth was, in practice, attributable to tourism In contrast, Ivanov and Webster (2007) used the growth decomposition methodology to measure the contribution of tourism to economic growth They also used the growth of real GDP per capital as a measure of economic growth and disaggregated it into economic growth generated by tourism and other industries The methodology is exemplified with an analysis of the contribution of specific industries to economic growth (Ivanov and Webster, 2010) Brida et al (2010) used decomposition to measure the magnitude of the contribution of tourism to the economic growth for Costa Rica In the case of Colombia, Brida et al (2008) used the Johansen’s cointegration, ECM and the Granger Empirical assessment of the TLGH in Vietnam 887 Table Tourism statistics of Vietnam, 1992–2011 (US$ million) Year Real GDP 1992 1995 2000 2005 2010 2011 10,462 20,733 30,427 52,850 102,585 122,880 Real GDP hotel and restaurant sector Real tourism earningsa 541 782 988 1,847 4,184 5,113 420 512 633 925 1,901 2,203 Note: aReal tourism earnings of accommodation establishments and travel agencies Source: Authors’ data collection from the General Statistical Office of Vietnam and the Vietnam National Administration for Tourism causality test and the growth decomposition methodology to examine the TLGH Considering the impact of tourism led-growth on the world’s economy, research in this field is of continuing importance Data Data used in the analysis were gathered from public sources The real GDP annual time series and the real population were collected from the General Statistical Office of Vietnam for the period from 1992 to 2011 Data on the contribution to GDP of the hotel and restaurant sector and tourism earnings were derived from the Vietnam National Administration of Tourism (2011) Finally, a time series of the real effective exchange rate between the Vietnam dong (VND) and other countries was obtained from the International Monetary Fund Table shows the tourism statistics of Vietnam for 1992–2011 Methodology Cointergration and Granger causality test Following previous research and the literature (Brida and Risso, 2009; Akinboade and Braimoh, 2010; Brida et al, 2010; Cortes-Jimenez and Pulina, 2010; Cortes-Jimenez et al, 2011; Seetanah, 2011) we assume that the tourism-growth model in Vietnam takes the following form: lnGDPt = β0 + β1 lnTOURt + β2 lnERt + ut All the variables are expressed in natural logarithms so that elasticity can also be interpreted; β are the parameters of the model; GDP is real gross domestic product; TOUR is tourism earnings (accommodation establishments and travel agencies); ER is the real effective exchange rate; u is the error term with the conventional statistical properties We first checked the stationarity of the data by applying unit root tests on the basis of the Augmented Dickey–Fuller (ADF) test (Dickey and Fuller, 888 TOURISM ECONOMICS 1981) If the series were found to be non-stationary, we tested for stationarity through the first or second differences Next, the cointegration test was used to examine the long-run relationship between tourism and economic growth based on the work of Johansen and Juselius (1990) They propose two test statistics for testing the number of cointergrating vectors: the trace and maximum eigenvalue statistics The third step was used the ECM technique to find the error correction term The ECM equation for the model in this study is as follows: ΔlnGDPt = β0 + β1ΔlnTOURt + β2ΔlnERt + β3ECt–1 + εt, where Δ denotes the first difference operator, εt is a random error term, and ECt–1 is the one-period lagged value of the error (ECt–1 = lnGDPt–1 – β1 lnTOURt–1 – β2 lnERt–1 – β3ut) Finally, the Granger causality test exhibits the pairwise causal relationship between the variables under consideration It may be unilateral or bilateral So, this study also used the test to find the causality between GDP and tourism separately by simply running the following two regression models: m ΔlnGDPt = λ0 + Σi=1 λ1iΔlnGDPt–i + Σni=1λ2i ΔlnTOURt–i + Σpi=1λ3i ΔlnERt–i+ µt m ΔlnTOURt = φ + Σi=1 φ1iΔlnTOURt–i + Σni=1φ2i ΔlnGDPt–i +Σqi=1φ3i ΔlnERt–i + εt where µt and εt are white noise error processes; m, n, p and q denote the number of lagged variables Growth decomposition methodology In order to support the TLGH in Vietnam, we used growth decomposition methodology to assess tourism’s contribution The proportion of GDP produced by tourism is computed as in Ivanov and Webster (2007), Ivanov and Webster (2010) and Ivanov and Webster (2013) They used the growth of real GDP per capita gr as the measure of economic growth The growth of the real GDP per capita gr is: ⎛ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ ⎛ ⎜ ⎜ gr = ⎜ ⎜ ⎜ ⎝ Yq1(p0) —— N1 —— – 100 Yq0(p0) —— N0 (1) where Yq1(p0) is the GDP in constant prices; Yq0(p0) is the GDP in the base year and N is the average size of the population, and index denote current period, for which index is the base period They disaggregate the nominator of Equation (1) to separate the tourism GDP in constant prices from the GDP i ), and tourism GDP in base period in constant prices of other industries (ΣYq1(p0) i ): from GDP of other sectors in base period (ΣYq0(p0) Empirical assessment of the TLGH in Vietnam ⎛ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ gr = ⎛ t t i i Σi≠1 Yq1(p0) Yq0(p0) Σi≠1 Yq0(p0) ⎜ Yq1(p0) ⎜ ——– +———— – ——– – ———— N1 N1 N0 N0 ⎜ ————————————————— ⎜ Yq0(p0) ⎜ —— N0 ⎝ 889 100 (2) They regroup the expressions in the nominator and come to: ⎛ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ gr = ⎛ t t i i Σi≠1 Yq0(p0) ⎜ Yq1(p0) Yq0(p0) Σi≠1 Yq1(p0) —— – ——– ———–– – ———–– ⎜ N N0 N1 N0 ⎜ —————– + —————————– Yq0(p0) Yq0(p0) ⎜ —— —— ⎜ N0 N0 ⎝ 100 (3) And the first component in this expression: t t Yq1(p0) Yq0(p0) —— – —— N0 N1 g rt = ————— 100 , Yq0(p0) —— N0 (4) represents the direct contribution of the tourism sector to economic growth in the period r Results and discussion The results in Table show that all variables were not stationary in their levels and first differences This is evident by comparing the observed values of the ADF test statistics with the critical values of the test statistics at the 5% significance level However, the second differences of all three variables are stationary under the ADF test Hence it is concluded that these variables are integrated of order I(2) Given that integration of the three series is of the same order, we continued to test whether the three series are cointegrated over the sample period Table shows the existence of one or two cointegrating vectors at the 5% significance Table Unit root estimation (ADF test) Variables lnGDP lnTOUR lnER Levels Statistic 95% CV –3.294231 –0.944522 –0.033436 –3.733 –3.676 –3.030 First differences Statistic 95%C.V –1.999316 –2.958250 –2.908066 Source: Authors’ calculations based on Eviews 6.0 –3.691 –3.691 –3.040 Second differences Statistic 95%C.V – 4.990758 –5.057098 –3.832942 – 3.733 – 3.733 – 3.067 890 TOURISM ECONOMICS Table Johansen cointegration tests results Data trend Test type Trace Max-Eigen None No Intercept No Trend 1 None Intercept No Trend Linear Intercept No Trend 1 Linear Intercept Trend 1 Quadratic Intercept Trend 1 Source: Authors’ calculations based on Eviews 6.0 Table Pairwise Granger causality tests Null lnTOUR does not Granger cause lnGDP lnGDP does not Granger cause lnTOUR lnER does not Granger cause lnGDP lnGDP does not Granger cause lnER lnER does not Granger cause lnTOUR lnTOUR does not Granger cause lnER Optimal lag F-value Probability Result 2 24.5225 5.13897 1.01170 1.05950 0.0001* 0.0227** 0.3295 0.3747 lnTOUR => lnGDP lnGDP => lnTOUR 2 0.41050 1.17883 4.37913 6.08172 1.23188 3.08596 10.4820 1.85776 1.09500 0.5308 0.4363 0.05308 0.0137** 0.2834 0.0800 0.0020* 0.1918 0.3635 lnER => lnGDP lnGDP => lnER lnER => lnTOUR lnTOUR => lnER Note: *Significant at the 1% level; **significant at the 5% level Source: Authors’ calculations based on Eviews 6.0 level On the basis of these results, we can interpret that a unique cointegrating relationship emerges for GDP, tourism and the exchange rate The dynamics of the cointegration technique were used to explore the longrun equilibrium among the variables Thus, the error term in our model can be used as the equilibrium error Owing to two variables, GDP and tourism integrated I(2), and the cointegrating relationship, the ECM is: Δ(lnGDP, 2)t = 0.00108+ 0.0388Δ(lnTOUR, 2) + 0.2357Δ(lnER, 2) + 0.4105ECt-1 R2 = 0.64; DW = 1.92 The relationship between tourism and economic growth shows that tourism is an exogenous variable in the coefficient of the error correction equation (0.4105) In particular, GDP is adjusted for long-run balance of tourism at a rate of about 41.05% This confirms that tourism is as a factor of long-run economic growth in Vietnam Table reports the statistical analysis of the causal relationships between Empirical assessment of the TLGH in Vietnam 891 Table Contribution of hotel and restaurant sector to Vietnamese economic growth in the period 1992–2011 Year Real rate of growth of GDP per capita (%) 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 6.78 6.22 7.02 7.75 7.60 6.48 4.15 3.2 5.36 5.47 5.68 5.78 6.30 7.03 6.90 7.14 5.03 5.55 5.67 4.79 Real rate of growth of GDP of hotels and restaurants per capita (%) The contribution of hotels and restaurants to economic growth (%) 15.10 13.10 22.14 18.93 10.66 3.24 2.90 1.00 2.67 3.51 7.47 3.62 6.64 15.52 8.38 13.48 8.09 2.51 7.56 6.30 0.35 0.34 0.61 0.59 0.37 0.12 0.10 0.03 0.09 0.11 0.24 0.12 0.21 0.49 0.29 0.47 0.30 0.10 0.28 0.24 Source: Authors’ calculations based on data of the General Statistical Office of Vietnam lnGDP, lnTOUR and lnER for Vietnam All hypotheses were tested by a standard F-test The results also suggest that causality runs from tourism earnings to GDP, but causality does not run from GDP to tourism earnings Table shows the real variation of per capita GDP in the tourism sector and the contribution of tourism (hotel and restaurant sector) to the variation of total GDP This result confirms once again tourism-led growth in Vietnam Conclusion and policy implications The empirical results indicate that a long-run relationship exists between tourism and economic growth in Vietnam The causality experiment points out that there is tourism-led growth in Vietnam However, it is clear that the contribution of the hotel and restaurant sector is relatively low compared to its potential Therefore, in order to stimulate economic growth through tourism in Vietnam, a detailed development strategy is required to give direction to the tourism sector This is beyond the scope of this research, but at the macro level the following measures are suggested in order to stimulate economic growth through tourism: (i) development of a Vietnam tourism brand; (ii) improvements to the means of transportation and communication to benefit both domestic and international travellers; 892 TOURISM ECONOMICS (iii) government support for the developing tourism infrastructure systems and facilities to attract private investors; (iv) enhancing tourism connections to other sectors, regions and localities to strengthen supply chains and boost ‘spillover’ effects References Akinboade, O.A., and Braimoh, L.A (2010), ‘International tourism and economic development in South Africa: a Granger causality test’, International Journal of Tourism Research, Vol 12, pp 149– 163 Balaguer, J., and Cantavell-Jorda, M (2002), ‘Tourism as a long – run growth factor: the Spanish case’, Applied Economics, Vol 34, pp 877–884 Brida, J.G., and Risso, W.A (2009), ‘Tourism as a factor of long-run economic growth: an empirical analysis for Chile’, European Journal of Tourism Research, Vol 2, No pp 178–185 Brida J.G., Pereyra, J.S., Risso, W.A., Devesa, W.J.S., and Aguirre, S.Z (2008), ‘The tourism-led growth hypothesis: empirical evidence from Colombia’, Tourismos, Vol 4, No 2, pp 13–27 Brida, J.G., Lanzilotta, B., Lionetti, S., and Risso, W.A (2010), ‘The tourism-led growth hypothesis for Uruguay’, Tourism Economics, Vol 16, No 3, pp 765–771 Cortes-Jimenez, I., and Pulina, M (2010), ‘Inbound tourism and long-run economic growth’, Current Issues in Tourism, Vol 13, No 1, pp 61–74 Cortes-Jimenez, I., Nowak, J.-J., and Sahli, M (2011), ‘Mass beach tourism and economic growth: lessons from Tunisia’, Tourism Economics, Vol 17, No 3, pp 531–547 Dickey, D.A., and Fuller, W.A (1981), ‘Likelihood ratio statistics for auto-regressive time series with a unit root’, Econometrica, Vol 49, pp 1057–1072 Dritsakis, N (2004), ‘Tourism as a long-run economic growth factor: an empirical investigation for Greece’, Tourism Economics, Vol 10, pp 305–316 Gunduz, L., and Hatemi, A (2005), ‘Is the tourism-Led growth hypothesis valid for Turkey?’, Applied Economics Letters, Vol 12, pp 499–504 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 Ivanov, S., and Webster, C (2013), ‘Tourism’s impact on growth: the role of globalization’, Annals of Tourism Research, Vol 41, 231–236 Johansen, S., and Juselius, K (1990), ‘Maximum likelihood estimation and inference on cointegrationwith application to the demand for money’, Oxford Bulletin of Economics and Statistics, Vol 52, pp 169–210 Katircioglu, S.T (2009), ‘Revisiting the tourism-led-growth hypothesis for Turkey using the bounds test and Johansen approach for cointegration’, Tourism Management, Vol 30, pp 17–20 Katircioglu, S.T (2010), ‘Testing the tourism-led growth hypothesis for Singapore – an empirical investigation from bounds test to cointegration and Granger causality tests’, Tourism Economics, Vol 16, No 4, pp 1095–1101 Oh, C.O (2005), ‘The contribution of tourism development to economic growth in the Korean economy’, Tourism Management, Vol 26, pp 39–44 Seetanah, B (2011), ‘Assessing the dynamic economic impact of tourism for island economies’, Annals of Tourism Research, Vol 38, No 1, pp 291–308 Vietnam National Administration of Tourism (2011) ‘International visitors to Vietnam in December and 12 months of 2011’ (http://www.vietnamtourism.gov.vn/english/index.php?cat=012040&itemid =5143, accessed 26 January 2012) World Tourism Organization (2009), ‘UNWTO world tourism barometer’ (http://unwto.org/facts/ eng/barometer.htm, accessed April 2009) Xie, F., Lacher, R.G., and Nepal, S.K (2011), ‘Economic impacts of domestic tourism in the rural developing world: a case study of Zhangjiaje city, China’, Tourism Review International, Vol 14, pp 29–42  ... long-run balance of tourism at a rate of about 41.05% This confirms that tourism is as a factor of long-run economic growth in Vietnam Table reports the statistical analysis of the causal relationships... in the base year and N is the average size of the population, and index denote current period, for which index is the base period They disaggregate the nominator of Equation (1) to separate the. .. concluded that these variables are integrated of order I(2) Given that integration of the three series is of the same order, we continued to test whether the three series are cointegrated over the sample