Tourism, Remittances, and Foreign Investment as Determinants of Economic Growth: Empirical Evidence from Selected Asian Economies

Abstract

This research discovers how international tourism affects the economic growth of selected Asian states, e.g., Bangladesh, China, India, Pakistan, and Sri Lanka, throughout 2001–2019. To attain this objective, we have employed various regression estimation approaches, e.g., Fixed Effect Model (FEM) and Fully Modified Ordinary Least Square (FMOLS) technique. The statistical results of the applied techniques reveal that international tourism activities have a positive and significant effect on the GDP growth rate because such kinds of activities considerably contribute to creating opportunities that lead to hoist economic activities and economic growth. Moreover, an influx of tourism increases tourism activities and operations, which opens further doors to opportunities and generates revenue for the government. Similarly, the GDP per capita has been positively and significantly influenced by international tourism activities. The government and host country should emphasize the activities and operations regarding tourism and should also concentrate on the dynamic role, importance, and sensitivity of tourism operations in under-analyzed economies. This research brings a new arrangement of the variable, which has never been considered in prior literature.

1. Introduction

Tourism is extensively recognized as an effective prospect for the development of an economy (Sharpley 2010). This tourism sector has worked as a potential catalyst of the national economy of many countries because it affects the economies of those countries linked with it and creates employment, upsurges local demands, participates directly to balance of payments (BoP), and permits a reallocation of capital. Tourism brings various elements into one chain due to the high complementarity and commonality of the operations required to make a general touristic product. The term “tourism” is defined by the UN World Tourism Organization, as it is a social economic feature that permits the movements of masses from one country or place to another country or place instead of their routine environment for professional, business, and personal objectives. It is also called a movement for non-commercial purposes. Such people are called visitors or tourists who continue their tourism activities and bear expenditures (Paltrade Report 2013). With contemporary and emerging globalization, tourism has emerged as one of the fastest and largest mounting sectors worldwide. The global tourism industry produced an average of 21% of worldwide GDP, and 30% produced employment globally in 2020 (Brida et al. 2020). An upsurge in individual income in emerging countries leads to an upsurge in leisure activities in the shape of tourism, and it will further enhance worldwide trade. Most of the developing and underdeveloped economies have failed to boost their economic growth by conducting high-cost activities. The definition of tourism is further classified as the operations experienced by an individual throughout their journey and rests in resorts situated outside their usual residency for a permanent period (Naudé and Saayman 2005). Moreover, tourists are further called visitors while halting in prominent places for at least 24 h and are called excursionists when they stay for less than 24 h. When people go to a specific viewpoint with the objective of making use of housing, conveyance, foodstuff, and regeneration services, among others, they boost the economy of the receiving country and form a market: the “tourism market”. The term tourism is an uncharacteristic market because a product is not sent, but the right to use goods or services available in a different location from the residency is awarded. Countries have declared tourism as a substantial part of showing country culture, norms, and values, and it has major contributions in the progression of different sectors financially and non-financially, which leads to a rise in economic growth. Moreover, this endeavor assists in seeking the answer to the question of how tourism, remittances, and foreign investment can be proved as significant determinants of economic growth?

Tourism enhances local investment, local life, and local economic operations, and it also makes better local infrastructure. The authorities focus on infrastructure due to tourism operations. On the other hand, high investment regarding infrastructure and equipment is difficult to manage, but tourism development requires low capital demand. Tourism operations are featured by the commonness of SMEs, which assimilate a great diversity of goods and services. Hence, a massive investment in infrastructure and superstructure is coped up by the official authorities and should be dealt with as a source to hoist the employment rate, economic growth rate, and social development of small investors. Moreover, tourism affects currency circulations positively, employment rates, balance of payment, and investment in the formation of physical groundwork, which make activities regarding tourism possible. It also boosts the state budget, enhancing government expenditure via public service and government income due to the collection of direct and indirect amounts of taxes. The determinants of international tourism can be verified by tourism operations, as it generates new ways and opportunities of work with enhancement in size and numbers of rest houses and lodges, inauguration of new restaurants, and development in the transport sector. It also expands productive sectors. Given its size, the sector is expected to have a considerable impact on economic growth, diversification, and the structural information of economies (Ferguson 2007). According to the World Travel and World Tourism Council (WTTC), the tourism industry globally generated some US $1.8 trillion directly in 2019 and is expected to grow by a rate of 4.4% until 2023.

Except for major explanatory variables, e.g., international tourism and economic growth, there are some control variables, e.g., foreign direct investment, personal remittances, and labor force, that impact economic growth expansion. An influx of foreign direct investment increases economic growth because when FDI comes, the unemployment rate will reduce, which further boosts per capita income. An upsurge in remittances will improve the living standard of the receiving country and enable them to spend more, which shows that remittances strengthen the economic condition of an economy. Exports have credible value in making an economy better. It provides different markets and different opportunities to exporters, which have a positive impact on economic growth. Development in the human capital sector is also a mandatory and essential factor for an economy. Investments in the education and health of human beings have an important value in an economy. This study investigates the impact of tourism on economic growth by employing fixed effect models and fully modified ordinary least squares. The statistical outcomes of the study describe that tourism affects economic growth positively, which shows that when tourism increases, then economic growth also increases. The government should ease the process of getting tourism accommodations and amenities and should also make some clear policies to get the attention of tourists. This research has practical, theoretical, and empirical implications. Theoretically, it contributes to the prior literature by discussing the connection between tourism and economic growth. Moreover, this research finds the relation between tourism and economic growth empirically. It also contributes practically by recommending suggestions to government officials that they should understand the importance of tourism for economic growth and its fruitful impacts on economic growth.

The rest of the sections of this study are as follows: Section 2 is a review of prior literature, theoretical framework, hypotheses development, and theory and theorization. Section 3 discusses the sample size and population, econometric models, variables discussion, and methodological discussion. The Section 4 draw light on the reporting of statistical outcomes in the form of descriptive statistics, correlation, and regression analysis. Moreover, Section 5 describes the details and discussion of the statistical outcomes. The last section highlights the conclusions and recommendations of the study. The references are listed below in all sections.

2. Literature Review

2.1. Tourism and Economic Growth

Different scholars have an assortment of notions vis-à-vis how tourism affects economic expansion in underdeveloped and developing states. Many scholars have a similar interest in the significant contribution of tourism and how it links to the positive growth of an economy. As per World Tourism Organizations, it is a traveling activity for the sake of liberty, except as usual routine work and environment. The fruitful outcomes achieved by native and national economies should be analyzed accordingly (Ayeni and Ebohon 2012; Manzoor et al. 2019). Tourism is considered a driving force for economic advancement. The generation of employment increments in revenue and an influx of foreign exchange are positively impacted by tourism activities (Modeste 1995; Steiner 2006). Several studies have been conducted on underdeveloped economies and have found a significant correlation between tourism and economic growth (Kulendran and Wilson 2000; Durbarry 2002; Croes and Vanegas 2008). Manwa (2012) suggested that to make tourism beneficial to society, we should get monetary benefits. These benefits and acts for benefits assist them in securing and building prominent tourist areas. This was further described by Smith (2007) that the monetary benefits depend on the state’s capacity to offer reasonable and moderate facilities. Risso and Brida (2009) asserted that an increment in tourism activities had a positive impact on Chile’s economic expansion. The main objective of his study was to find the probable fundamental link between tourism costs, economic growth, and exchange rate throughout 1986–2007, and the hypotheses were examined using the Johansen cointegration approach. The author further noted the positive correlation between tourism and economic growth, which is a pivotal factor in contributing to economic growth. They further unveiled that tourism had a positive and significant impact on employment in Croatia, and they further described that tourism significantly contributed to the promotion of employment. They employed the Granger Causality Approach by using data from 2000–2012. By observing and monitoring the above studies, we can hypothesize that the increment in tourism activities has a positive and significant link with growth in economic growth. Overall, international tourism welcomes an upsurge in economic growth (Brida et al. 2016). The study of Fonseca and Sánchez-Rivero (2020) suggested that tourism strengthens income. International tourism leads to economic growth (Li et al. 2018; Fonseca and Rivero 2019; Comerio and Strozzi 2019; Maneejuk et al. 2022). The work of Çağlayan et al. (2012) found no causal link between tourism revenue and GDP in Asia, the Middle East, and North Africa. The above-mentioned studies have, therefore, not shed enough light concerning the tourism impact on economic growth under observed economies. Therefore, this study fills this literature gap.

2.2. Foreign Investment and Economic Growth

The term “foreign direct investment” is demarcated as a boost in the carrying value of the shareholders’ equity of one economy held by the investor of another economy, where the investments are under the supervisory control of the investor (Richards and Hall 2002). From the past two decades, FDI has mainly increased in south Asian, southeast Asian, and east Asian countries compared to the whole world volume of FDI, and such countries are the principal destination for investments (Durbarry 2004). To justify this link between FDI and economic growth, many studies have been conducted where they found a significant positive, negative, and insignificant liaison between FDI and economic expansion. The most appropriate and best way to achieve and acquire economic growth is through FDI (Oh 2005). Few researchers have declared that FDI works as a fuel for economic upturn in developing economies (Rasul and Manandhar 2009). Numerous studies have been conducted to justify the link between FDI and economic expansion, which are as follows: Chen and Chiou-Wei (2009) worked on panel data while taking a sample of 70 developed and developing economies from 1998–2002 by employing GMM to recognize the link between FDI and economic expansion. They further observed a negative and significant link between FDI and economic growth in developing economies. The statistical outcomes justified the notion that low financial sector development in developing economies and lax rules and regulations leading toward the embezzlement of private capital seriously affected the economic progress of the economy (Arshad et al. 2017). They further investigated how FDI influences the exports and imports of Pakistan by employing the approach of cointegration and error correction during 1973–2002. The statistical outcomes revealed that FDI positively influences imports in the short and long run, but FDI also has an inverse effect on exports in short orientation and a positive effect in long run orientation. Hye and Khan (2013) observed a connection between an FDI influx and economic growth expansion in Pakistan. The research was done throughout 1981–2010 by employing the approach of multiple regression analysis on various variables, i.e., FDI, GDP, remittances, and exterior debt. This study further disclosed that economic growth is directly and positively affected by such variables. Lea (2006) studied the link between FDI and economic growth in Pakistan from 1980–2006 by adopting the least square methods. The results unveiled that the GDP has no significant liaison with FDI. Another study conducted by Wu et al. (2014) observed that there is a positive and significant link between FDI and economic growth during 1966–2014. Mahmoudinia et al. (2011) and Telfer and Sharpley (2015) identified positive and significant links of FDI, trade liberalization, and domestic capital on economic growth during 2008–2013. Rhaman (2016) conducted research on the link between imports, FDI, foreign investment, and economic growth during the period of 1977–2013 by adopting the time series econometric approach. The results show that foreign remittances and FDI are directly influenced by economic growth. The mentioned studies in this paragraph help us to build a hypothesis that there is a significant relationship between FDI and economic growth.

2.3. Remittances and Economic Growth

A word remittance may be defined as a non-commercial transmission of money by a diaspora community in their homeland. India is at the top of the list of receiving remittances. Pradhan et al. (2008) examined the impact of remittances on economic expansion by using panel data of 25 years from 39 developing economies throughout 1980–2004, and their results suggest a significant and positive link of remittance on economic development. Fayissa and Nsiah (2008) found a liaison between remittances and economic expansion in 36 African economies during 1980–2004 and observed a direct and positive link between remittances and economic development. Ramirez (2013) conducted a study that identified the impact of remittances on the expansion of the economy by employing panel data of 23 lower- and upper-income Latin American Caribbean (LAN) economies from the period 1990 to 2007. He further described that remittances have a positive and significant impact on real per capita GDP expansion. Topxhiu and Krasniqi (2017) found that the remittances have significantly and positively impacted economic expansion by employing panel data throughout 2005–2015. Meyer and Shera (2017) studied different economies that are highly receiving remittances, i.e., Moldova, Macedonia, Romania, Bulgaria, Bosnia Herzegovina, and Albania, by adopting panel data from 1999–2013. Their regression outcomes revealed a significant and positive link of remittance on the economic development of selected countries. Comes et al. (2018) identified the link between FDI and remittances on economic expansion by employing panel data from 7 economies from Eastern and Central Europe throughout 2010–2016. The statistical outcomes expressed that the FDI and remittances have a direct and positive impact on economic development for all under-observed economies. Bangladesh receives a great contribution to its economic development (Barai 2012; Chowdhury 2011), but Bangladesh still needs some enhancements to the remittance delivery method to avoid the inappropriate and informal channel to admit the remittances from migrants. Remittances are the second largest factor in Pakistan’s economy. Hussain and Anjum (2014) have disclosed that the remittances positively and significantly affected GDP growth in Pakistan throughout 1973–2011. Similarly, Ahmad et al. (2016) found a significant and positive link between remittances and GDP per capita. Cooray (2012) also found a direct and positive link between remittances and GDP per capita. Azam (2015) identified that remittances are boosting economic expansions in Bangladesh. The above-mentioned studies help to make the hypothesis that there is a positive and significant link between remittances and economic growth.

2.4. Export Volume and Economic Growth

The principal chunk of international trade makes a vital contribution to the development of an economy. We cannot underestimate the capacity of less or highly developed, large or small developed economies, and they can produce and get what is required to fulfill the demand of their economies. However, every economy gives different values to its international trade, specifically imports. It relies on the size of an economy or its size of the market, the capacity and diversity of its available resources, economic progress level, and economic structure. The most important thing is that the economic policy is chased by the economy and trends in the global market. Many earlier scholars have done work to find out the relationship between export and economic growth (Segerstrom et al. 1990; Rivera-Batiz and Romer 1991). Exporting activities are considered the main and mandatory element for the entire country’s economic operations progress (Medina-Smith 2001). The factors regarding the balance of payment and unemployment can be backed and supported through exports. According to the Export-Led Growth hypothesis (ELG), local infrastructure and economies must be furnished and equipped with contemporary and modern tools and techniques to survive on behalf of strict and severe competition in the global market (Shah et al. 2020). Economic growth expansion is a critical issue in underdeveloped economies that rely on the development of export growth expansion. Dollar and Kraay (2003) described that trade origins uplift the economic development of underdeveloped economies, and it also upsurges the living standards of residents. The different economies have achieved better development through exports, i.e., Coast Rica, Malaysia, and China. Li et al. (2010) observed the data of exports, imports, and economic growth expansion by employing the cointegration approach in the China case, and statistical numbers showed that an increase in exports leads to economic growth. Asafu-Adjaye and Chakraborty (1999) arranged a study on the link between exports and economic growth during the period 1960–1994 and found no liaison between variables in the case of India. Moreover, in reviewing the economic history and trade policy of India, these statistics were not surprising.

Taghav et al. (2012) found a liaison between import, export, and economic growth in the case of Iraq during the period from 1962–2011. The statistical outcomes show that in the long run orientation, exports have a positive link and imports have a negative link with economic growth expansion. Guntukula (2018) portrayed the link between imports, exports, and economic growth in India by taking monthly time series data from April 2005 to March 2017. His findings suggest that there is bidirectional causality between exports and economic growth, and also confirm the bidirectional causality between imports and economic development. Similarly, Kumari (2014) found a negative link between imports and economic growth, but there is a positive link between exports and economic development. By observing the above-mentioned research, we can conclude that there is a positive and significant relationship between exports and economic development.

2.5. Human Capital and Economic Growth

Human force is key to achieving further achievements. There are different factors that may impinge human capital or not, and it further leads to the economic growth of an economy. Ogundari and Awokuse (2018) evaluated the existing situation of human capital with health and education. They employed a GMM approach through balance panel data from 1980–2008 in 35 economies. Their statistical outcomes revealed that human capital has a positive impact on economic growth. Moreover, the health contribution to human capital is relatively higher than the education contribution to human capital. Kourtzidis et al. (2019) conducted research on the link between human capital and economic growth. Moreover, they found the significance of the human capital stock on economic growth by employing non-parametric and semi-parametric interpretation on a sample of 100 economies throughout 1970–2014. Their findings unveil that the development in human capital and uplifting of human capital directly and significantly affects a growth in economy. Prior relative literature has confirmed that the development of human capital leads to an acceleration of economic growth (Mankiw et al. 1992). They further showed a positive and significant liaison between the development of human capital and economic growth. The above-mentioned studies signify that there is a positive and significant link between human capital and economic development.

2.6. Conceptual Value

The conceptual value reveals the connection of explained and explanatory variables, as shown in Figure 1.

3. Data and Methods

This current interpretation is based on a deductive approach by utilizing secondary data from 2001 to 2019 from Bangladesh, China, India, Pakistan, and Sri Lanka. The data were retrieved from the World Development Indicators, and fixed effect model (FEM) and fully modified ordinary least square (FMOLS) approaches were employed to estimate the regression. The purpose behind the selection of the sample size is to analyze tourism’s contribution to economic growth because these economies are in the same regions, and all have the best part in generating revenue in the shape of tourism. Moreover, data availability is also the reason for choosing such economies.

Table 1. Percentage of Foreign Direct Investment (FDI) and Tourism in Economic Growth.

Countries	FDI %	Tourism Revenue %	Remittances %
Bangladesh	0.3	4.4	5.82
China	1.98	11.3	0.13
India	2.7	7.8	3.00
Pakistan	0.5	2.7	8.69
Sri Lanka	0.9	4.0	8.82

Note: Percentage FDI and Tourism in the total GDP of under analyzed economies. Source: World Development Indicators.

shows the percentages of FDI, tourism revenue, and remittances in the economic growth of the selected countries.

3.1. Variable Specifications

The main explanatory, explained, and control variables have specific calculations. The term international tourism is considered a percentage of total exports, which plays a significant role in developing an economy. Economic growth is taken as a dependent variable with its two proxies. The gross domestic product (GDP) is an annual increment in the total value of products produced by all sources of an economy. The GDP per capita (GDPP) is enumerated as the total country GDP divided by the total population of an economy. The term foreign direct investment (FDI) shows the total net inflow in the shape of outsourcing from the percentage of GDP. Personal remittances (PRM) are calculated as the amount of money received from another country in the form of family support. The export goods (EXP) are taken as total national-level trade. It enhances trade activity and has a multifaceted impact on various sectors of an economy. Moreover, it overcomes the ratio of unemployment. The lifetime income approach measures human capital, or we can say total labor force (LBF), as the present value of the expected future labor incomes that could be generated over the lifetime of the people currently living.

Table 2. Variables Definition.

Variables	Abbreviations	Used as	Definition
ITR	International Tourism	IV	The term international tourism is number of tourists who travel to a country other than that in which they have their usual residence, but outside their usual environment, for a period not exceeding 12 months and whose main purpose in visiting is other than an activity remunerated from within the country visited.
FDI	Foreign Direct Investment	CV	Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor.
PRM	Personal Remittences	CV	Personal remittances (PRM) are considered as an amount of money received from another country in the form of family support.
EXP	Exported Goods	CV	Exports of goods and services represent the value of all goods and other market services provided to the rest of the world.
LBF	Labor Force	CV	Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period.
GDP	Economic Growth	DV	GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. GDP per capita is the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output divided by the mid-year population.

Note: Definitions as per World Bank accordingly.

shows the definitions of the independent variables (IV), control variables (CV), and dependent variables (DV).

3.2. Econometric Models

The econometric models represent the relationship between dependent and independent variables in the presence of some control variables. The relationship of such variables is as follows:

$$GD{P}_{it}={\beta }_{°}+{\beta }_{1}IT{R}_{it}+{\beta }_{2}FD{I}_{it}+{\beta }_{3}PR{M}_{it}+{\beta }_{4}EX{P}_{it}+{\beta }_{5}LB{F}_{it}+{\epsilon }_{°}$$

(1)

The above Equation (1) reveals the link of independent variables with one proxy of dependent variable. In this equation, the GDP is used as a dependent variable, the subscriptions “i” is for cross-section, and “t” is for time series. Moreover, “it” represents the panel data. The ${\beta }_{°}$ signifies the constant value and ITR refers to international tourism, FDI portrays foreign direct investment, PRM discloses personal remittances, EXP stands for exported goods, and LBF shows the labor force, and it considers human capital. The ${\epsilon }_{°}$ shows the error terms.

$$GDP{P}_{it}={\beta }_{°}+{\beta }_{1}IT{R}_{it}+{\beta }_{2}FD{I}_{it}+{\beta }_{3}PR{M}_{it}+{\beta }_{4}EX{P}_{it}+{\beta }_{5}LB{F}_{it}+{\epsilon }_{°}$$

(2)

Equation (2) also represents the link of the explained variables and the second proxy of growth expansion. The rest of the variables have a similar relationship to the above equation.

After applying the unit root test for the data stationarity problem, we employed a cointegration test. This approach was built by Kao (1999), and it is used to test the long-term liaison between variables by analyzing cross-section specific intercepts and homogeneous coefficients in 1st stage regressors. Kao (1999) also introduced the Dicky–Fuller testing (ADF) approach. The null hypothesis in such tests is that there is no cointegration. According to the statistics in

Table 3. Results of the Panel Unit—Root Testing.

	Im, Pesaran and Shin W-Stat		ADF—Fisher Chi-Square
Variables	Statistic	Prob.	Statistics	Prob.
GDP (GDP growth)	−1.955	0.025	20.652	0.023
GDPP (GDP per capita growth)	−2.137	0.016	21.879	0.015
ITR (International tourism)	−3.623	0.000	56.184	0.000
FDI (Foreign direct investment)	−1.773	0.038	20.790	0.022
D(PRM) (Personal remittances)	−3.904	0.000	33.953	0.000
EXP (Goods exports)	−4.622	0.000	40.979	0.000
D(LBF) (Labor force)	−1.602	0.054	16.094	0.096

Note: The probability values show that all variables are stationarity at level 1. Source: Own calculation.

and

Table 4. Results of the Panel Cointegration Test.

Kao Residual Cointegration Test
	t-statistics	Prob
ADF	−4.31	0.00
Residual variance	0.011	-
HAC variance	0.013	-

Note: significant value rejects the null hypothesis which means that there is no cointegration.

, the ADF statistics verify that the null hypothesis is rejected. These results suggest that the variables have a cointegration liaison.

This study intends to discover the link between international tourism and economic development. To access this dynamic objective of the current study, we have employed numerous methods to estimate the econometric equations by gradually pursuing the estimation process. Initially, we go toward a fixed effect approach to acquire the information of whether this approach is more helpful to attain desired results or random effect. The numeric value of probability is less than 0.05, which discloses that the alternate hypothesis has been accepted and the null hypothesis has been rejected. To procure the main outcomes, we further employed the Fully Modified Ordinary Least Square (FMOLS) approach, and this approach has a capacity to overcome the chances of accruing endogeneity and serial correlation errors (Gyamfi et al. 2022; Jamil et al. 2022; Alam et al. 2021). This approach is a non-parametric approach that deals with these two prior mentioned errors. Moreover, the long-run estimation of this approach generates impartial, unswerving, and reliable results. The weight benchmark (criteria) of this applied approach controls the error of heterogeneity in the long-run variance and co-integrated panel (Danish et al. 2019). For this entire empirical endeavor, the time span of the data was 2001 to 2019 for Asian regions. As going ahead with regression analysis, we also employed the unit root method to detect the data stationarity because econometric equations have various macro-economic variables, and such factors are highly prone to stationarity error. As for the outcomes, the values of the ADF and Im, Pesaran and Shin W-stat approaches identify that the data are stationary at level (Baz et al. 2020; Rjoub et al. 2021).

4. Results

This section discusses the statistical outcomes of the applied approaches (FEM and FMOLS) in the form of descriptive statistics, a correlation matrix, and regression analysis.

Table 5. Descriptive Statistics.

Variables	Mean	Median	Std. Dev.	Max.	Min.	Obs.
GDP (GDP growth)	6.238	6.386	2.491	14.230	−1.545	95
GDPP (GDP per capita growth)	4.936	5.135	2.826	13.635	−2.243	95
ITR (International tourism)	5.833	4.622	5.768	27.674	0.359	95
FDI (Foreign direct investment)	1.635	1.312	1.062	4.554	0.095	95
PRM (Personal remittances)	4.825	5.183	3.109	10.587	0.090	95
EXP (Goods exports)	10.740	10.396	0.833	12.383	9.672	95
LBF (Labor force)	7.993	7.800	0.716	8.903	6.886	95

Abbreviations: GDP = GDP growth, GDPP = GDP per capita growth, ITR = International tourism, FDI = foreign direct investment, PRM = Personal remittances, EXP = Goods exports, LBF = Labor force, Source: Authors own calculations.

portrays the descriptive statistics in the form of mean, median, maximum, minimum, standard deviation, and observation.

Table 5 highlights that the mean value of the GDP growth rate is 6.238 percent, which shows the average GDP rate in under-analysis economies. The median value of GDP is 6.386 percent, which shows the idle number of GDPs under analysis states. The standard deviation value of GDP is 2.491 percent, which reveals that the mean can deviate percent from its mean value. The maximum value of GDP is 14.230 percent, and the minimum value is −1.545 percent. The number of observations is 95 in all aspects. The average statistic of the GDPP is 4.936 percent, which means that most under-analysis economies have around this figure of GDP per capita. The median value of GDPP is 5.135 percent, which shows the central point. The standard deviation of GDPP is 2.826 percent, which highlights the maximum point, and the minimum value highlights the minimum number of GDPP in under-analysis economies. Rest of the variables also reveal the different statistics of the descriptive analysis.

Table 6. Correlation Analysis.

Variables	GDP	GDPP	ITR	FDI	PRM	EXI	LBF
GDP	1.000
GDPP	0.981	1.000
ITR	−0.171	−0.084	1.000
FDI	0.556	0.575	0.019	1.000
PRM	−0.494	−0.470	0.205	−0.597	1.000
EXP	0.553	0.579	−0.190	0.606	−0.820	1.000
LBF	0.512	0.478	−0.430	0.512	−0.840	0.898	1.000

Abbreviations: GDP= GDP growth, GDPP = GDP per capita growth, ITR = International tourism, FDI = Foreign direct investment, PRM = Personal remittances, EXP = Goods exports, LBF = Labor force.

reveals the strength, association, and correlation of the variables. The GDP has a positive and strong association with GDPP (0.981 percent) and has a negative but low strength of association with international tourism (−0.171) and personal remittances (−0.494 percent) respectively. Moreover, the GDP has a positive and moderate association with foreign direct investment (0.556 percent), exports of goods (0.553 percent), and labor force (0.512 percent), respectively. In 3rd column of Table 3, the GDPP is weakly and negatively correlated with international tourism (−0.084 percent) and personal remittance (0.470 percent) but positively and moderately associated with foreign direct investment (0.575 percent), (0.579 percent), and (0.478 percent), respectively. Furthermore, in column 4, international tourism is weakly and inversely correlated with EXP and LBF but positively associated with FDI and PRM, respectively. In column 5, FDI is inversely and moderately correlated with PRM (−0.597 percent) and positively associated with EXP and LBF. In column 6, the PRM is highly and inversely associated with EXP, and LBF (−0.820, −0.840) respectively. These statistical outcomes have disclosed the strength, association, direction, and correlation among the variables.

In

Table 7. Tourism and GDP growth rate.

	GDP as Dependent Variable
	Fixed Effect Model		FMOLS
Variables	Coefficients	Prob.	Coefficients	Prob.
C	−6.553	0.041	0.695	0.003
ITR	0.085	0.051 *	0.148	0.014 **
FDI	0.788	0.002 ***	0.811	0.002 ***
PRM	0.229	0.027 **	−0.217	0.283
EXP	0.587	0.016 **	0.829	0.025 **
LBF	10.185	0.013 **	1.123	0.031 **
Adjusted R-square		0.456	0.497
S.E. of regression		1.837	1.690
Prob (F-statistic)		0.000
Long-run variance		2.965

Note: *** 1%, ** 5%, * 10%. Source: Own calculation.

, the regression estimation results are displayed while considering GDP as a dependent variable by employing a fixed effect model and fully modified ordinary least squares (FMOLS). The statistical outcomes reveal that international tourism has a significant and positive relationship with the GDP growth rate, which shows that an increment or an upsurge in tourism activities leads to better economic growth. The FDI, personal remittances, exports, and labor force have a positive impact on GDP growth, as shown in the fixed effect model. The relationship of the rest of the variables expresses that FDI invites new opportunities and welcomes new projects where the masses can access a number of various types of employment, which will enhance the income of an individual and collectively enhance the gross domestic product rate. Moreover, personal remittances also increase the spending capacity of an individual, which helps to run economic activity more. Exports will also run further economic activities and provide opportunities that will also enhance the revenue of a household. Moreover, skill and avoiding malnutrition is mandatory to develop an economy, which reveals a direct positive link of the labor force with GDP growth rate. The value of the adjusted r-square is 0.497. The value of S.E. of regression is 1.837 and 1.6902. The long-run variance has a 2.965 value. The value of the probability statistics is 0.000, which reveals the overall significance of the model.

Table 8. Tourism and GDP per capita growth.

	GDPP as Dependent Variable
	Fixed Effect Model		FMOLS
Variables	Coefficients	Prob.	Coefficients	Prob.
C	3.111	0.101	0.532	0.033 **
ITR	0.104	0.069 *	0.167	0.007 ***
FDI	0.817	0.002 ***	0.850	0.002 ***
PRM	1.193	0.002 **	0.188	0.007 ***
EXP	−0.241	0.791	0.429	0.008 ***
LBF	1.366	0.014 **	2.379	0.107
Adjusted R-square		0.569	0.608
S.E. of regression		1.854	1.715
Prob (F-statistic)		0.000
Long-run variance		3.156

Note: *** 1%, ** 5%, * 10%. Source: Own calculation.

represents the regression outcomes of how GDP per capita impacts international tourism by employing fixed effects and fully modified ordinary least square approaches. The results assert that international trade brings positive aspects to an economy to make its economy advanced, well-equipped, and well-furnished in a befitting manner. According to the statistics of the above Table, the main independent variables (tourism) have a positive and significant link with GDP per capita, which shows that an incoming and boosting tourism industry will have a four-sided effect of social, political, cultural, and economical. It will impart benefits to the general masses of the beneficiary economy. Moreover, FDI also has a positive effect on the GDP growth rate. The increasing exports, remittance, and labor force have a positive and significant impact on GDP growth, as specified by the two models.

5. Discussion

In the above Table 7, the regression estimation results are displayed while considering GDP growth rate and GDP per capita as proxies of dependent variable (economic growth) by employing fixed effect and fully ordinary least square methods. The statistical outcomes reveal that international trade has a significant and positive relationship with the GDP growth rate, which shows that an increment or an upsurge in tourism activities leads to better economic growth. Moreover, the rapid growth of tourism led to a growth in household incomes and government revenues directly and indirectly by means of multiplier effects, improving the balance of payments and urging tourism-promoted government policies. FDI lifts the economy by fascinating employment opportunities, allocating expertise and technologies, augmenting efficiency, and continuous long-oriented development in emerging states. Remittances contribute a major chunk to enlarge economic growth via their direct impact on the utilization of products and services, incomes, and investment. However, remittances can also have an inverse impact on economic development in beneficiary states by declining incentives to work and, consequently, overwhelming labor streaming or labor force contributions. Import is an essential factor in Pakistan’s economic development. Furthermore, the key contribution has been noted in this economy from its exports by acquiring foreign capital to finance importations, debt facilitations, sustaining its currency, and resolving and mitigating the determined problem of BoP insufficiency. Labor signifies human participation in generating the products and services of an economy. The outcomes are quite abundant regarding relevant skills to cover up the massive demand. Such outcomes often cause an increase in wages in a few industries. The value of the adjusted r-square is 0.456, which shows that 45 percent of the independent variables impacted the dependent variables.

Table 8 represents the regression outcomes of how GDP per capita impacts international tourism by employing a fixed effect approach and a fully modified ordinary least square. The outcomes of the employed techniques signify that international tourism has a direct and significant liaison with GDP per capita because its fundamental interpretation discloses how an individual can procure more income by augmenting activities regarding tourism. Moreover, individuals readily offer services for prosperity measures. The FDI creates job opportunities and runs economic activities in a beneficiary country, which boosts GDP per capita. Similarly, remittances, labor force, FDI, and exports have also contributed positively to boosting an individual’s income in an economy. Such factors attribute and attract an individual prosperity and enlarge economic operations, which consequently control the inflation rate. The current results are quite different from previous studies due to its significant contribution in the literature. It checks the empirical relationship of international tourism with economic growth and gives suggestions to official and relevant authorities that they should consider the significant contribution of tourism activities to the GDP growth rate.

6. Conclusions and Policy Recommendations

This research exemplifies the link between international tourism and economic growth by employing fixed effect and fully modified ordinary least square approaches throughout 2001–2019. Five selected Asian countries, i.e., Sri Lanka, Bangladesh, Pakistan, China, and India, were finalized for interpretation by using secondary data. The outcomes of the fully modified ordinary least square (FMOLS) show that international tourism positively and significantly affects GDP growth because an influx of tourism will increase the revenue of the government and individuals, which will also enhance opportunities and reduce unemployment. Moreover, the swift growth of tourism led to an improvement and an expansion of clan and official incomes directly and indirectly by means of a compounding effect, increasing BoP and hoist tourism, nurturing government regulations. FDI escalates the economy by generating employment possibilities, allocating skills and technologies, intensifications in productivity, and continuous long-oriented expansion in emerging economies. The remittances have a key chunk in contributing to economic growth via their direct impact on utilization, savings, and investment. However, remittances inversely affect growth in beneficiary economies by overwhelming incentives to work and, consequently, declining the labor supply or labor force contribution. Under analysis economies, growth relies on its exports by acquiring foreign capital to finance imports, service debt, robust and stabilize its currency, and wane the tenacious problem of the balance of payment scarcity. Labor reveals the human factor in generating the merchandise and services of an economy. The FDI, exports, personal remittance, and development in the human capital sector have a positive and significant impact on economic growth expansion. This arrangement of the variable has never been part of the literature under these economies.

The government should consider the importance and sensitivity of international tourism for better economic growth. Developing and underdeveloped economies cannot effort capital expenditure to bring an increment in the GDP growth rate, and even they have no contemporary approaches to upsurge economic growth. Almost every state has a favor for tourism and can generate revenue. They should make some rules and regulations regarding the promotion of tourism in their states. Moreover, tourism significantly affects the economic growth of a country. However, data unavailability restricted us from expanding our sample size yearly and country-wise.