Introduction

The prospect for the emergence of the tourism sector worldwide includes its contribution to an economy and the upliftment of its nation's well-being. It is a vast industry, and it has been a fundamental sponsor to many countries' growth. This flourishing sector is something that the entire world rejoices. It turns out to be a needed sector for many nations; tourism is an imperative component of the economy's service sector since it adds to the country's national income (GDP). The sustained out flux in international tourist flows has been a clear sign of the buoyant and resilient tourism sector worldwide over the past few decades. The total foreign tourist arrivals will grow by 3.3% a year to reach 1.8 billion by 2030, as projected by the United Nations World Tourism Organization (Shahzad et al., 2017). In this line there are several other benefits of tourism for a host destination, it boosts the revenue of the economy creates job, develop the infrastructure, contributes to the Balance of payment, increase educational significance, and plants a sense of cultural exchange between foreigners and citizens (Yehia, 2019). The tourism sector is quite a different and distinctive industry, as every industry has its importance for countries and their citizens. Still, tourism is slightly more significant as an industry because of what it brings. It regarded as the leading and fastest emerging sector or industry in the World.

GCC countries transform their traditional travel types (e.g., Islamic travel and desert tourism explorations) to a fascinating modern kind of tourism based on vacation, recreation, business, trade, and sports. The growth of international tourism in the Gulf Cooperation Council (GCC) countries surrounded by the broad approach of economic expansion, which is particularly appropriate for countries undergoing oil depletion or making efforts to develop themselves economically. Tourism delivers prospects for the economic diversification of modern GCC countries and ways to elevate a sense of national identification and nationhood. The GCC nations are beginners in the tourism sector, especially in attracting modern types of tourism. Tourism delivers specific prospects for the economic broadening and the national branding of young GCC nations. Hence the GCC countries can be classified as new global destinations (Al-Harmarneh & Stephenson, 2013). Travel and Tourism, directly and indirectly, contribute 10.3% (US$ 8.9 trillion) of global GDP and provide 330 million jobs, i.e., 1 in 10 jobs around the World created by travel and tourism. The contribution of GDP and total employment by travel and tourism for Bahrain is 13.3% and 15%, UAE is 11.9%, and 11.1%, Kingdom of Saudi Arabia 9.5% and 11.2%, for Oman is 7.5% and 8.1% and lastly for Kuwait is 5.3% and 6% (WTTC, 2019)

Considering the vital role of the tourism sector in the global economy over the past decade motivates the GCC policymakers to outlook the tourism sector not only as a source of revenue but also, more decisively, as a tactic to achieve the Sustainable development goals by diversifying their economy from oil to non-oil and resolve their unemployment issues.

Literature Review

The expansion of tourism has been recognized globally as a catalyst for economic growth. Empirical literature available claimed that tourism leads to economic growth, as discussed underline. Durbarry (2004) discovered that tourism adds approximately 0.8% to Mauritius' economic growth in the long run. Oh (2005) suggested a one-way causal association of economic growth that leads to tourism growth. Samina, et al., (2007) felt a secure link between tourism receipts and economic growth, and economic expansion is essential for tourism development. Fayissa, et al., (2007) witnessed that tourism receipts could significantly impact the current GDP and economic growth. Lee & Chang (2008) used a mixed panel co-integration method to discover the influence of tourism on GDP among OECD and non-OECD and revealed that tourism impact on GDP is more significant in non-OECD than in the OECD countries. Akan, et al., (2008) explored the cause and effect link between tourism and economic expansion. Further, they found that tourism had strongly affected by industrial development. Brida, et al., (2008) suggested the one-way causation flowing from tourism to Mexico's real GDP.

Brida & Risso (2009) disclosed one-way causation among tourism and real exchange rate to Chile's real GDP. Malik, et al., (2010) identified one-way causation flowing from tourism to Pakistan's economic growth and exposed a one-way causality between current account deficit to GDP and between tourism and current account deficit. Payne & Mervar (2010) disclosed one-way causation flowing from GDP to tourism receipts and from GDP to real effective exchange rate exists in the Croatia economy. Arslanturk, et al., (2011) investigated the causal association among tourism receipts and GDP using annual time series data from 1968 to 2006. They explored that tourism receipts have an optimistic outcome on Turkey's GDP in the early 1980s. Kreishan (2011) empirically investigated the Tourism-Led-Growth Hypothesis (TLGH) and identified a favourable bond between tourism progress and economic expansion; further, he revealed a one-way Granger causality flowing from tourism progress to economic development. Apergis & Payne (2012) studied the causation among tourism and economic growth using a panel error correction model to discovered dual causation among tourism and economic growth of nine Caribbean nations.

Dritsakis (2012) exposed the tourism led growth hypothesis to be viable for all seven Mediterranean countries. The outcome depicts panel co-integration associations between tourism growth and GDP and that tourist receipts significantly impact GDP. Ekanayake & Long (2012) found no evidence supporting tourism led growth hypothesis for selected 140 developing nations subdivided into six groups (East Asia, Europe, Latin America, Middle East, and North Africa, South Asia and Sub-Sahara Africa). Caglayan, et al., (2012) conducted a panel study on 135 nations subdivided into eleven groups (Europe, America and Latin America, Caribbean countries East Asia, South Asia, and Oceania, Asia, Middle East, and North Africa, Central Asia, and Sub-Sahara Africa). Their outcomes showed dual causation in Europe, one-way causality from economic growth to tourism in America and Latin America & Caribbean countries, and one-way causation from tourism to economic growth in East Asia, South Asia, and Oceania, and no causality in Asia, Middle East and North Africa, Central Asia and Sub-Sahara Africa. Hye & Khan (2013) confirmed the long-run association between income from tourism and Pakistan's growth. Jalil, et al., (2013) exposed the one-way causal connection between tourism and Pakistan's economic growth. Kumar (2014) supported Kenya's commercial growth-led tourism and found a one-way causal effect flowing from output per worker to tourism receipts. Wang (2015) found a strong association between the GDP and tourist income in Guihoz, China. Bayramoglu & Ari (2015) acknowledged a positive one-way causality from foreign tourists' expenditures to economic growth. Tang (2015) indicated that tourism boosts Malaysia's economic growth. Correspondingly, Phiri (2016) stressed that tourism should gradually become an essential element of economic growth and expansion and established tourism-led development where tourism receipts acted as a tool to expand tourism. Ahad (2016) discovered a dual association between tourism expenditure and economic growth in Pakistan.

Blanka & Zyonimir (2016) claimed that tourism leads to development when tourist receipts used to assess tourism development. Similarly, Chris (2015), Leit-Ao & Shahbaz (2016) exposed that tourist arrivals and tourism receipts strongly linked to economic expansion. Seghir, et al., (2015) detected two-way causation for the tourism-growth nexus among 49 countries using co-integration and Granger causality. Alhowaish (2016) investigated the causal relationship between tourism development and economic growth in GCC countries and discover that GCC altogether reveals one-way causation running from economic growth to tourism growth. Moreover, economy-driven tourism growth followed by Kuwait, Saudi Arabia, Qatar, and the United Arab Emirates. While Bahrain supports tourism-led growth, Oman does not exhibit any causal relationship between tourism and economic growth. Ohlan (2017) saw long-run one-way causation running from tourism-economic growth. Likewise, Tabash (2017) found a unique long-term connection between tourism receipts and economic growth. Dogru & Bulut (2018) revealed both-ways causality between tourism receipts and economic development. Usmani, et al. (2020) established that tourist expenditure has a strong influence on economic progress, while tourist arrivals do not significantly impact. Further, they found dual causality running between tourist expenditure and economic development. Khan, et al., (2020) highlighted the importance of tourism in the expansion of emerging economies.

This study's core idea is to create a macro econometrical model that investigates the link between tourism growth, tourism expenditure, and five GCC countries' economic growth.

Data and Methodology

This paper aims to append to the strengthening of this research line by analyzing few macro-economic parameters with economic indicators like GDP as an indicator of economic growth, international tourism receipts as an indicator of tourism growth, and global tourism expenditure as tourism expenditure. The macro-economic models formulated on a Panel basis of investigation.

Model Specification

Panel study comprises GCC countries, i.e., United Arab Emirates, Bahrain, Kuwait, Sultanate of Oman, and the Kingdom of Saudi Arabia. Economic growth (y) defined as a function of tourism growth (tr) and tourism expenditure (ex).

Where, i=number of countries (i=1, 2, 3…..); t=time period (t=2000, …..2018); v and ɛ represents sector-specific parameter and random error term, respectively.

The approach to investigating this model is first to go for unit root test, co-integration test followed by two basic approaches (fixed effect and random effect). Then, these approaches test by the Hausman test to select the best approach among them. Lastly, Dumitrescu & Hurlin's (2012) panel causality test for the direction of the causality among the competing variables.

Table 1 depicts the mean values of the tourism expenditure, tourism receipts, and gross domestic product for the sample countries. The United Arab Emirates (UAE) has the highest mean value of tourism receipts, and the lowest cost comes under the banner of Kuwait. The Kingdom of Saudi Arabia has the highest mean value of tourism expenditure, while Bahrain counts the lowest tourism expenditure. Table 2 shows the outcomes of the Pearson Correlation test for panel data of selected countries. The correlation coefficient results show a positive and significant relationship between the variables. Though the correlation coefficient outcomes do not reflect the possible association among variables, they may predict the signs of association among variables.

Table 1 DESCRIPTIVE STATISTICS OF THE VARIABLES FOR THE SELECTED COUNTRIES
Countries	Variables	M ean	Median	Standard Deviation	Minimum	Maximum
UAE	GDP	3.02071E+11	3.3307E+11	94629023637	1.24346E+11	4.22215E+11
	TR	10471062500	8890500000	6716224132	1438000000	21390000000
	EX	12493062500	13247000000	4656110487	3956000000	17999000000
BAHRAIN	GDP	26043503989	27244933511	8123875535	11074813830	37652500000
	TR	2267750000	1874000000	963948096.8	1206000000	4380000000
	EX	1518812500	731000000	1585240306	492000000	4939000000
KUWAIT	GDP	1.20209E+11	1.1503E+11	37546810247	47876510067	1.74161E+11
	TR	625187500	617000000	174890525.3	328000000	931000000
	EX	9043750000	8610000000	3536591306	3750000000	14318000000
OMAN	GDP	56960793238	63193237971	20179844043	21633810143	81076462939
	TR	1507687500	1310000000	788769566.6	546000000	2975000000
	EX	1630562500	1394000000	780621630	804000000	3210000000
SAU	GDP	5.47344E+11	5.86571E+11	1.88854E+11	2.15808E+11	7.86522E+11
	TR	8721687500	7968000000	3783869743	3418000000	16975000000
	EX	16630625000	18094000000	6051160978	4165000000	25137000000

Table 2 PEARSON CORRELATION RESULTS
	Economic Growth (GDP)	Tourism expenditure (EX)	Tourism receipt (TR)
GDP	1
t-stat	-
P-value	-
EX	0.883	1
t-stat	16.635	-
P-value	0.00	-
TR	0.7479	0.71	1
t-stat	9.95	8.915	-
P-value	0.00	0.00	-

Results and Interpretation

In this section, the study discusses the empirical results for GCC countries. A precondition for applying the Pedroni panel co-integration test is to prove that parameters contain a panel unit root. Initially, the study uses all unit root tests viz., Levin, Lin & Chu, Im-Pesaran-Shin (IPS), ADF-Fisher, and PP-Fisher tests. Table 3 presents the unit root results that we reject the unit root's presence at the first difference. However, all the variables achieve stationarity at their primary differences. The results suggest that co-integration can be applied to examine the association among the parameters. The results of Padroni panel co-integration, as presented in Table 4, divulge the presence of short-run association among the settings.

Table 3 SUMMARY OF PANEL UNIT ROOT TEST
	Levin, Lin & Chu		Im, Pesaran & Shin W-stat		ADF		PP
	Statistics	Probability	Statistics	Probability	Statistics	Probability	Statistics	Probability
GDP	-2.05E+00	0.0201	-0.13361	0.4469	7.88706	0.6399	14.8079	0.1392
D(GDP)	-6.53E+00	0.00*	-4.32358	0.00*	35.2721	0.0001*	35.7309	0.0001*
EX	1.65E+00	0.95	3.21972	0.9994	5.61316	0.8466	13.6444	0.1898
D(EX)	-9.54E+00	0.00*	-7.02373	0.00*	54.0477	0.00*	58.113	0.00*
TR	1.97E+00	0.9757	2.95297	0.9984	4.6971	0.9105	1.58804	0.9986
D(TR)	-7.65E+00	0.00*	-7.80308	0.00*	52.5878	0.00*	45.9911	0.00*
*depicts the 1% significance level  Source; Authors computation E-views 10

Table 4 PEDRONI CO-INTEGRATION TEST RESULT
Dimension	Test	Statistic	Probability
Within-group co-integration tests	Panel-v	0.27961	0.3899
	Panel-rho	0.138655	0.5553
	Panel-pp	-0.57846	0.2815
	Panel-ADF	-0.54993	0.2912
Between-group co-integration tests	Group-rho	1.212106	0.8875
	Group-pp	-0.42332	0.336
	Group-ADF	-0.79886	0.3157
Source; Authors computation E-views 10

After Padroni panel co-integration inference, we estimated the influence of Tourism Growth (TR), Tourism Expenditure (EX) on Economic Growth (GDP) by employing two essential test

i. Fixed effect model and

ii. Random effect model.

To check which model is appropriate, we have to use the Hausman test. If the Hausman test statistic is significant, we have to reject the null hypothesis means we have to accept the fixed effect model, as illustrated in Table 5. The fixed-effect model displays neither of the parameters influences economic growth supported by the Wald test for GCC countries. Durbin-Watson test indicates no serial correlation in the model and its best fit due to R2 and Adjusted R2.

Table 5 FIXED RANDOM EFFECT MODEL RESULTS
Variable	Coefficient	Probability
EX(-1)	1.391644	0.4094
TR(-1)	2.268269	0.1871
C	3.98E+10	0.0002
R2	0.979245
Adj. R2	0.977076
Durbin-Watson	1.862459
Hausman Test	22.65915	0.000
Source; Authors computation E-views 10

Finally, we tested the causality among the parameters using a Dumitrescu & Hurlin (2012) panel causality test. As depicted in Table 6, the result proposes that tourism growth and tourism expenditure on economic growth do not support any causation among them; however, tourism expenditure and tourism growth have dual causation themselves.

Table 6 DUMITRESCU HURLIN PANEL CAUSALITY TESTS
	W-Stat.	Zbar-Stat.	Probability	Inference
TR does not homogeneously cause GDP	1.35153	0.17027	0.8648	Insignificant
GDP does not homogeneously cause TR	0.88244	-0.35683	0.7212	Insignificant
EX does not homogeneously cause GDP	0.56368	-0.71502	0.4746	Insignificant
GDP does not homogeneously cause EX	1.18115	-0.02118	0.9831	Insignificant
EX does not homogeneously cause TR	3.87122	3.00156	0.0027*	Significant
TR does not homogeneously cause EX	2.97242	1.99161	0.0464**	Significant
*,** represent 1% ,5% significance level Source; Authors computation E-views 10

Conclusion

There are significant works available that examined the tourism-led growth postulate using both single nations and cross-nation study. Out of those studies, the majority establishes a positive affiliation among tourism expenditure, tourism receipts, and economic growth. This study's core motive is to add in the existing literature that tourist expenditure, tourism growth can also play a significant contributor to economic growth. This paper aimed to explore the association among international tourist expenditure, global tourist receipts, and economic growth in five GCC countries (United Arab Emirates, Bahrain, Kuwait, Sultanate of Oman and Kingdom of Saudi Arabia) individually dynamic panel study.

Panel analyses the linkage between economic growth and tourism growth, tourism expenditure using the dynamic panel data model. The empirical results derived from the panel data fixed effect model display that tourism expenditure and tourism growth do not exhibit any short-run causal influence on GCC countries' economic growth. The Dumitrescu-Hurlin panel causality test indicates no causality among tourism growth, tourism expenditure, and economic growth of GCC countries'. A similar finding was evident by Ekanayake & Long (2012) and Caglayan, et al., (2012). Though, the result also indicates dual causation among tourism expenditure and tourism growth.

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