<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">ME</journal-id><journal-title-group><journal-title>Modern Economy</journal-title></journal-title-group><issn pub-type="epub">2152-7245</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/me.2016.73040</article-id><article-id pub-id-type="publisher-id">ME-65055</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Business&amp;Economics</subject></subj-group></article-categories><title-group><article-title>
 
 
  Impact of Tourism on Long-Run Economic Growth of Vietnam
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>urong</surname><given-names>Shih</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ninh</surname><given-names>T. H. Do</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>College of Business, Southern Taiwan University of Science and Technology, Taiwan</addr-line></aff><pub-date pub-type="epub"><day>10</day><month>03</month><year>2016</year></pub-date><volume>07</volume><issue>03</issue><fpage>371</fpage><lpage>376</lpage><history><date date-type="received"><day>24</day>	<month>February</month>	<year>2016</year></date><date date-type="rev-recd"><day>accepted</day>	<month>25</month>	<year>March</year>	</date><date date-type="accepted"><day>28</day>	<month>March</month>	<year>2016</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Tourism is a potential industry as a new impetus for economic growth of Vietnam, and is identified as a key sector in Vietnamese economy, as such, the Vietnam government has identified the tourism industry as a key sector in the national economy and one of the crucial importance in securing its long-term growth. The study examines the role of tourism in driving the economic growth of Vietnam over the period of 1995-2013 by using Tourism-Led Growth Hypothesis (TLGH). The stability of TLGH is analyzed using a Rolling Window regression technique. The analyses performed in this study are based on an econometric methodology consisting of the pooled Ordinary Least Squares test, unit root test, co-integration analysis, and Granger causality test. The findings show that the TLGH is supported in the case of Vietnam. In other words, tourism has indeed played a key role in driving economic growth in Vietnam in recent decades. Moreover, the Rolling Window regression results confirm the stability of the TLGH in the case of Vietnam.
 
</p></abstract><kwd-group><kwd>Tourism</kwd><kwd> Economic Growth</kwd><kwd> Tourism-Led Growth Hypothesis</kwd><kwd> Vietnam</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Vietnam’s economy was traditionally characterized by a large traditional agriculture sector and a small industrial base. However, in 1986, the Vietnam government launched a policy known as “Doi Moi” (“Renovation”), aimed at transforming the economy by promoting a shift away from agriculture toward industrialization. The policy was successful, with the national GDP growth rate increasing from a reported 3.9% in 1986 to 8.6% GDP growth in 1992. <sup>1</sup>The industrial sector remained the leading driver of economic growth in Vietnam until 1996. However, in the line with global trends, Vietnam’s economy has since shifted from an industrialized base toward a more service industrial base. The tourism industry in Vietnam has expanded rapidly in recent years due to the free-market-oriented economy [<xref ref-type="bibr" rid="scirp.65055-ref1">1</xref>] and the recognition by government of tourism as a major economic driver. As an engine for economic growth, tourism industry has many positive impacts in terms of generating foreign exchange earnings, creating employment, and generating income [<xref ref-type="bibr" rid="scirp.65055-ref2">2</xref>] . Honey and Gilpin [<xref ref-type="bibr" rid="scirp.65055-ref3">3</xref>] reported that tourism had had a snowball effect on contributing to economic growth in Vietnam. Moreover, Bennet [<xref ref-type="bibr" rid="scirp.65055-ref4">4</xref>] described Vietnam as an emerging economy with a significant and growing low cost tourism market.</p><p>Tourism is one of the largest and most dynamic industries in the world-economy, and has significant multiplier effects on economic activity. Researchers have long investigated tourism in established areas such as Australia, Taiwan [<xref ref-type="bibr" rid="scirp.65055-ref5">5</xref>] , Span [<xref ref-type="bibr" rid="scirp.65055-ref6">6</xref>] , Italy [<xref ref-type="bibr" rid="scirp.65055-ref7">7</xref>] , or Korea [<xref ref-type="bibr" rid="scirp.65055-ref8">8</xref>] . However, the tourism industry in Vietnam has attracted relatively little attention thus far. In a rare study, H.M.T. Nguyen, H.C.D. Nguyen, and T.D. Nguyen [<xref ref-type="bibr" rid="scirp.65055-ref9">9</xref>] showed that TLGH is valid for Vietnam. However, the analyses focused only on the hotel and restaurant sector, and thus there is no guarantee that the findings can be extended to the tourism industry as a whole. Ridderstaat, Croes, and Nijkamp [<xref ref-type="bibr" rid="scirp.65055-ref10">10</xref>] argued that government policy planners need to understand the validity of the TLGH in their particular case in order to devise appropriate tourism strategies. The present study thus tests the validity of the TLGH for economic growth in Vietnam based on economic and tourism data collected over the period of 1995-2013. Importantly, the study provides a wider perspective on the role played by tourism in stimulating economic growth than earlier studies based on the hotel and restaurant sector alone. As such, the results provide more robust basis on which to formulate effective tourism policies.</p><p>The TLGH has been widely used in the literature to test the causality relationship between tourism and economic growth (Lokman and Abdulnasser 2005 [<xref ref-type="bibr" rid="scirp.65055-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.65055-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.65055-ref12">12</xref>] ). In utilizing the TLGH to investigate the role played by tourism as an economic driver in Vietnam, the present study adopts an econometric methodology based on the pooled Ordinary Least Squares (OLS) test, a unit root test, co-integration analysis, and Granger causality test. Notably, the proposed methodology provides a more reliable understanding of the validity of the TLGH than that obtained using a single metric alone. Lean and Tang [<xref ref-type="bibr" rid="scirp.65055-ref13">13</xref>] argued that the stability of the causality relationship over the sample period was also an important factor. Thus, the present study aims to understand not only the validly of the TLGH in the case of Vietnam, but also its stability over time.</p></sec><sec id="s2"><title>2. Data and Methodology</title><p>Based on previous studies by Lee and Chien [<xref ref-type="bibr" rid="scirp.65055-ref14">14</xref>] , Balaguer and Cantavella-Jorda [<xref ref-type="bibr" rid="scirp.65055-ref6">6</xref>] , and Kasimati [<xref ref-type="bibr" rid="scirp.65055-ref15">15</xref>] , several variables were used including real GDP, tourist receipts, tourist arrivals, and real exchange rate to test the significance between tourism and economic growth. The present study investigates the causality relationship between tourism and economic growth in Vietnam by used of three variables, namely the Gross Domestic Product (GDP), tourist arrivals (TOUR), and the real exchange rate (EXR) [<xref ref-type="bibr" rid="scirp.65055-ref16">16</xref>] . The GDP and tourist arrival information were obtained directly from the annual reports published by the General Statistical Office of Vietnam over the sample period (1995-2013). Tourist expenditure data were available only from 2003 to 2013. Furthermore, Katircioglu [<xref ref-type="bibr" rid="scirp.65055-ref17">17</xref>] found a multicollinearity problem emerges when tourism receipts are used. Thus, tourism expenditure was excluded from analysis. The real exchange rate (Vietnam Dong per USD) was calculated by multiplying the Vietnam Dong per USD and consumer price index in Vietnam. <xref ref-type="table" rid="table1">Table 1</xref> summarizes the data used in the analyses.</p><p>In accordance with the studies of Lee and Chang [<xref ref-type="bibr" rid="scirp.65055-ref18">18</xref>] , Fayissa, Nsiah, and Tadasse [<xref ref-type="bibr" rid="scirp.65055-ref19">19</xref>] , Sadi and Henderson [<xref ref-type="bibr" rid="scirp.65055-ref20">20</xref>] , and Makochekanwa [<xref ref-type="bibr" rid="scirp.65055-ref21">21</xref>] and the analysis model was formulated as follows:</p><disp-formula id="scirp.65055-formula654"><label>(1)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/16-7201249x7.png"  xlink:type="simple"/></disp-formula><p>All of the variables were transformed into a natural logarithm form in order to induce stationarity in the variance-covariance matrix. The model given in Equation (1) was tested using the pooled OLS regression.</p><p>Many macroeconomic time series contain unit root. Therefore, unit root tests are important in examining the stationarity of a time series. Prior to performing co-integration analysis, the stationarity properties of the three variables (GDP, TOUR and EXR) were investigated using the Augmented Dickey-Fuller [<xref ref-type="bibr" rid="scirp.65055-ref22">22</xref>] unit root test. Many macroeconomic time series contain unit root. The ADF test has been developed in 1979, which is used to examine the presence of a unit root for all the variables in the levels and in first differences. In this study, ADF test helped out to choose the most adequate unit root tests. The pairwise causality relationship between economic growth and tourism was then investigated using the following bivariate regressions.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Summary statistics of analyzed data</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >GDP</th><th align="center" valign="middle" >TOUR</th><th align="center" valign="middle" >EXR</th></tr></thead><tr><td align="center" valign="middle" >Mean</td><td align="center" valign="middle" >69.07211</td><td align="center" valign="middle" >3429758</td><td align="center" valign="middle" >15715.95</td></tr><tr><td align="center" valign="middle" >Median</td><td align="center" valign="middle" >49.42000</td><td align="center" valign="middle" >2927876</td><td align="center" valign="middle" >15746.00</td></tr><tr><td align="center" valign="middle" >Maximum</td><td align="center" valign="middle" >171.3900</td><td align="center" valign="middle" >7572352</td><td align="center" valign="middle" >20933.42</td></tr><tr><td align="center" valign="middle" >Minimum</td><td align="center" valign="middle" >20.74000</td><td align="center" valign="middle" >1351300</td><td align="center" valign="middle" >11032.58</td></tr><tr><td align="center" valign="middle" >Std. Dev.</td><td align="center" valign="middle" >47.72835</td><td align="center" valign="middle" >1844306</td><td align="center" valign="middle" >2981.106</td></tr></tbody></table></table-wrap><disp-formula id="scirp.65055-formula655"><label>(2)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/16-7201249x8.png"  xlink:type="simple"/></disp-formula><disp-formula id="scirp.65055-formula656"><label>(3)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/16-7201249x9.png"  xlink:type="simple"/></disp-formula><p>where <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/16-7201249x10.png" xlink:type="simple"/></inline-formula> is the deterministic component and <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/16-7201249x11.png" xlink:type="simple"/></inline-formula> is white noise. To investigate the long-run relationship between tourist arrival (TOUR) and GDP, this study employs the testing procedure which developed by Engle and Granger [<xref ref-type="bibr" rid="scirp.65055-ref23">23</xref>] . They noted that with two time-series variables co-integrated (i.e. at least one directional Granger causation exists), Granger causality tests can be performed.</p></sec><sec id="s3"><title>3. Empirical Results</title><p>At the first step in cointegration analysis, the pooled OLS regression is implemented. <xref ref-type="table" rid="table2">Table 2</xref> presents the results of the pooled OLS regression test. It is observed that the GDP is significant correlated with both TOUR and EXR. Moreover, the coefficient of TOUR is positive (2.172). In other words, the number of tourist arrivals increases with an increasing GDP. In additional, the real exchange rate (EXR) has negative sign, an indication that decrease in EXR results in increasing Vietnam’s economic growth in the long run. Moreover, the relationship between GDP, TOUR, and EXR are mutually. Thus, when EXR decreases, the volume of international tourist arrivals (TOUR) increases, and GDP increases.</p><p>Schubert, Brida, and Risso [<xref ref-type="bibr" rid="scirp.65055-ref24">24</xref>] found that in most economic time-series studies, OLS regressions produce significant parameters and a high R-square result. Consequently, a causality test is required. However, prior to performing causality analysis, a unit root test must first be applied to study the stationarity of the variables. <xref ref-type="table" rid="table3">Table 3</xref> shows the results of the Augmented Dickey-Fuller unit root test for the present variables given a 10% significance level. As shown, both variables are unit root or non-stationarity at Level, but stationary at First different. According to Phillips [<xref ref-type="bibr" rid="scirp.65055-ref25">25</xref>] , if the residual is non-stationary at Level but stationary at first different, the Johansen co-integration test must be applied to test for the presence of a long-run equilibrium relationship in the regression model.</p><p>The results presented in <xref ref-type="table" rid="table4">Table 4</xref> show that the null hypothesis is rejected at 10 percent significance level. Therefore, it can be concluded that tourism and economic growth are co-integrated. In other words, a meaningful long-run relationship exists between tourism and economic growth in Vietnam.</p><p>Co-integration does not by itself indicate the direction of the causal relationship. Thus, a Granger causality test was further used to confirm the validity of the TLGH in Vietnam.</p><p><xref ref-type="table" rid="table5">Table 5</xref> shows the F-test results for both hypotheses, namely tourism does not Granger cause economic growth (3.3108), economic growth does not Granger cause tourism (0.8375). Rejection of the null hypothesis of tourism-led economic growth is accepted. In other words, the TLGH is empirically supported in the case of Vietnam. However, for the second hypothesis, the null hypothesis is not rejected (0.8375). Thus, it is inferred that, economic growth is not a driver tourism growth in Vietnam. This result is consistent with that observed for other countries such as Spanish [<xref ref-type="bibr" rid="scirp.65055-ref6">6</xref>] , and may be caused by a small sample size.</p><p>The stability of the TLGH was investigated using the Rolling Window regression technique. No statistical procedure is available for determining the optimal window size. Following Lean and Tang [<xref ref-type="bibr" rid="scirp.65055-ref12">12</xref>] , the window size was set at 10 years. <xref ref-type="fig" rid="fig1">Figure 1</xref> shows that the TLGH remains stable over the time for the Vietnam economy.</p></sec><sec id="s4"><title>4. Conclusions</title><p>This study has utilized a Tourism-Led Growth Hypothesis (TLGH) to explore the causality relationship between</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Pooled OLS regression</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >Coefficient</th><th align="center" valign="middle"  colspan="2"  >Std. Error</th><th align="center" valign="middle" >t-Statistic</th><th align="center" valign="middle" >Prob.</th></tr></thead><tr><td align="center" valign="middle" >LOG (TOUR)</td><td align="center" valign="middle" >2.172605</td><td align="center" valign="middle"  colspan="2"  >0.216521</td><td align="center" valign="middle" >10.03415</td><td align="center" valign="middle" >0.0000</td></tr><tr><td align="center" valign="middle" >LOG (EXR)</td><td align="center" valign="middle" >−2.943712</td><td align="center" valign="middle"  colspan="2"  >0.335003</td><td align="center" valign="middle" >−8.787115</td><td align="center" valign="middle" >0.0000</td></tr><tr><td align="center" valign="middle" >R-Squared</td><td align="center" valign="middle" >0.885357</td><td align="center" valign="middle"  colspan="3"  >Mean Dependent Var</td><td align="center" valign="middle" >4.014249</td></tr><tr><td align="center" valign="middle" >Adjusted R-Squared</td><td align="center" valign="middle" >0.878613</td><td align="center" valign="middle"  colspan="3"  >S.D. Dependent Var</td><td align="center" valign="middle" >0.681372</td></tr><tr><td align="center" valign="middle" >S.E. of Regression</td><td align="center" valign="middle" >0.237394</td><td align="center" valign="middle"  colspan="3"  >Akaike Info Criterion</td><td align="center" valign="middle" >0.061111</td></tr><tr><td align="center" valign="middle" >Sum Squared Residual</td><td align="center" valign="middle" >0.958052</td><td align="center" valign="middle"  colspan="3"  >Schwarz Criterion</td><td align="center" valign="middle" >0.160526</td></tr><tr><td align="center" valign="middle" >Log Likelihood</td><td align="center" valign="middle" >1.419442</td><td align="center" valign="middle"  colspan="3"  >Hannan-Quinn Criter</td><td align="center" valign="middle" >0.077936</td></tr><tr><td align="center" valign="middle" >Durbin-Watson Stat</td><td align="center" valign="middle" >1.201880</td><td align="center" valign="middle" ></td><td align="center" valign="middle"  colspan="2"  ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Augmented dickey-fuller test of stationary</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >ADF Test</th><th align="center" valign="middle"  colspan="3"  >Level</th><th align="center" valign="middle"  colspan="3"  >First Different</th><th align="center" valign="middle"  colspan="3"  >Second Different</th></tr></thead><tr><td align="center" valign="middle" >Intercept</td><td align="center" valign="middle" >Intercept &amp; Trend</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Intercept</td><td align="center" valign="middle" >Intercept &amp; Trend</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Intercept</td><td align="center" valign="middle" >Intercept &amp; Trend</td><td align="center" valign="middle" >None</td></tr><tr><td align="center" valign="middle" >GDP</td><td align="center" valign="middle" >5.412</td><td align="center" valign="middle" >0.821</td><td align="center" valign="middle" >10.411</td><td align="center" valign="middle" >0.441</td><td align="center" valign="middle" >−4.760<sup>**</sup></td><td align="center" valign="middle" >2.140</td><td align="center" valign="middle" >−4.503<sup>**</sup></td><td align="center" valign="middle" >−4.529<sup>*</sup></td><td align="center" valign="middle" >−5.121<sup>***</sup></td></tr><tr><td align="center" valign="middle" >TOUR</td><td align="center" valign="middle" >1.936</td><td align="center" valign="middle" >−0.442</td><td align="center" valign="middle" >4.221</td><td align="center" valign="middle" >−3.192<sup>*</sup></td><td align="center" valign="middle" >−5.140<sup>**</sup></td><td align="center" valign="middle" >−2.167<sup>*</sup></td><td align="center" valign="middle" >−4.774<sup>**</sup></td><td align="center" valign="middle" >−4.673<sup>*</sup></td><td align="center" valign="middle" >−4.539<sup>***</sup></td></tr><tr><td align="center" valign="middle" >EXR</td><td align="center" valign="middle" >0.057</td><td align="center" valign="middle" >−3.264</td><td align="center" valign="middle" >2.344</td><td align="center" valign="middle" >−3.284<sup>*</sup></td><td align="center" valign="middle" >−3.189</td><td align="center" valign="middle" >−1.618<sup>*</sup></td><td align="center" valign="middle" >−4.777<sup>**</sup></td><td align="center" valign="middle" >−4.834<sup>**</sup></td><td align="center" valign="middle" >−5.072<sup>***</sup></td></tr></tbody></table></table-wrap><p>Note: <sup>*</sup>Significant at 10% level; <sup>**</sup>Significant at 5% level; <sup>***</sup>Significant at 1% level.</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Augmented dickey-fuller test of stationary</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="5"  >Unrestricted Cointegration Rank Test (Trace)</th></tr></thead><tr><td align="center" valign="middle" >Hypothesized</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Trace</td><td align="center" valign="middle" >0.05</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >No. of CE(s)</td><td align="center" valign="middle" >Eigenvalue</td><td align="center" valign="middle" >Statistic</td><td align="center" valign="middle" >Critical Value</td><td align="center" valign="middle" >Prob.<sup>**</sup></td></tr><tr><td align="center" valign="middle" >None<sup>*</sup></td><td align="center" valign="middle" >0.735329</td><td align="center" valign="middle" >40.60144</td><td align="center" valign="middle" >29.79707</td><td align="center" valign="middle" >0.0020</td></tr><tr><td align="center" valign="middle" >At most 1<sup>*</sup></td><td align="center" valign="middle" >0.585743</td><td align="center" valign="middle" >18.00389</td><td align="center" valign="middle" >15.49471</td><td align="center" valign="middle" >0.0205</td></tr><tr><td align="center" valign="middle" >At most 2</td><td align="center" valign="middle" >0.162876</td><td align="center" valign="middle" >3.022315</td><td align="center" valign="middle" >3.841466</td><td align="center" valign="middle" >0.0821</td></tr><tr><td align="center" valign="middle"  colspan="5"  >Unrestricted Cointegration Rank Test (Maximum Eigenvalue)</td></tr><tr><td align="center" valign="middle" >Hypothesized</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Trace</td><td align="center" valign="middle" >0.05</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >No. of CE(s)</td><td align="center" valign="middle" >Eigenvalue</td><td align="center" valign="middle" >Statistic</td><td align="center" valign="middle" >Critical Value</td><td align="center" valign="middle" >Prob.<sup>**</sup></td></tr><tr><td align="center" valign="middle" >None<sup>*</sup></td><td align="center" valign="middle" >0.735329</td><td align="center" valign="middle" >22.59756</td><td align="center" valign="middle" >21.13162</td><td align="center" valign="middle" >0.0309</td></tr><tr><td align="center" valign="middle" >At most 1<sup>*</sup></td><td align="center" valign="middle" >0.585743</td><td align="center" valign="middle" >14.98157</td><td align="center" valign="middle" >14.26460</td><td align="center" valign="middle" >0.0384</td></tr><tr><td align="center" valign="middle" >At most 2</td><td align="center" valign="middle" >0.162876</td><td align="center" valign="middle" >3.022315</td><td align="center" valign="middle" >3.841466</td><td align="center" valign="middle" >0.0821</td></tr></tbody></table></table-wrap><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> The Granger causality test results</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Null Hypothesis:</th><th align="center" valign="middle" >F-Statistic</th><th align="center" valign="middle" >Probability</th><th align="center" valign="middle" >Result</th></tr></thead><tr><td align="center" valign="middle" >lnTOUR does not Granger Cause lnGDP</td><td align="center" valign="middle" >3.3108</td><td align="center" valign="middle" >0.0711<sup>*</sup></td><td align="center" valign="middle" >Significant</td></tr><tr><td align="center" valign="middle" >lnGDP does not Granger Cause lnTOUR</td><td align="center" valign="middle" >0.8375</td><td align="center" valign="middle" >0.5066</td><td align="center" valign="middle" >Non-Significant</td></tr><tr><td align="center" valign="middle" >lnEXR does not Granger Cause lnGDP</td><td align="center" valign="middle" >1.4273</td><td align="center" valign="middle" >0.2979</td><td align="center" valign="middle" >Non-Significant</td></tr><tr><td align="center" valign="middle" >lnGDP does not Granger Cause lnEXR</td><td align="center" valign="middle" >2.9714</td><td align="center" valign="middle" >0.0895<sup>*</sup></td><td align="center" valign="middle" >Significant</td></tr><tr><td align="center" valign="middle" >lnEXR does not Granger Cause lnTOUR</td><td align="center" valign="middle" >3.1419</td><td align="center" valign="middle" >0.0796<sup>*</sup></td><td align="center" valign="middle" >Significant</td></tr><tr><td align="center" valign="middle" >lnTOUR does not Granger Cause lnEXR</td><td align="center" valign="middle" >1.0225</td><td align="center" valign="middle" >0.4274</td><td align="center" valign="middle" >Non-Significant</td></tr></tbody></table></table-wrap><p>Note: <sup>*</sup>Significant at 10% level.</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> The rolling regression for TLGH</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/16-7201249x12.png"/></fig><p>tourism and economic growth in Vietnam over the period of 1995-2103. The sample data have been analyzed by means of pooled OLS, a unit root test, the Johansen co-integrated test, and the Granger causality test. The results have shown that the TLGH is confirmed in the case of Vietnam. In addition, the Johansen co-integration test results have shown that the GDP growth rate, real exchange rate and number of tourist arrivals are co-integrated in Vietnam over the sample period. These results have confirmed the findings of H.M.T. Nguyen, H.C.D. Nguyen, and T.D. Nguyen [<xref ref-type="bibr" rid="scirp.65055-ref9">9</xref>] based on a narrower perspective of the hotel and restaurant sector that the TLGH is valid for Vietnam. Importantly, the present study has not only confirmed the validity of the TLGH in Vietnam, but has also established its stability over a ten-year period.</p><p>The present findings are of significant importance to policy makers in Vietnam since they show that the tourism industry is a major driver of economic growth. As such, the Vietnam government should actively promote the tourism sector through the adoption of vigorous investment and development policies and should formulate and promulgate policies and practices aimed at promoting Vietnam as a tourism destination throughout the world. Tourism has a relatively short history in Vietnam. However, the recent growth in tourist arrivals indicates that there is a huge potential for development in the tourism business. Overall, the present results show that the tourism industry has been instrumental in driving economic growth in Vietnam in recent years, and given suitable investment and development policies, it may be reasonably expected to continue to do so in the coming years and decades.</p></sec><sec id="s5"><title>Cite this paper</title><p>Wurong Shih,Ninh T. H. Do, (2016) Impact of Tourism on Long-Run Economic Growth of Vietnam. 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