Martahadi Mardhani*
| M. Shabri Abd. Majid | Abd. Jamal | Khairul Aswadi
© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
Tourism, both domestic and international, is considered to have a significant influence on economic growth in many countries around the world. However, studies that specifically examine the impact of domestic tourism on regional growth have received little attention. This study aims to fill this gap so that the contribution of domestic tourism to regional growth can be identified and enrich the literature on the tourism-led growth hypothesis. This study uses panel data from 33 provinces in Indonesia from 2011 to 2018. The results show that domestic tourism has a significant and positive impact on regional economic growth in Indonesia. The findings prove that domestic tourism is important to develop in promoting regional growth. For the sustainability of domestic tourism, its governance needs to be formulated wisely by involving various stakeholders because domestic tourism will also encourage an increase in international tourism.
consumer price index, domestic tourism expenditure, domestic tourism travel, regional economic growth
Indonesia is the largest archipelago in the world, and it is not only rich in natural resources but also has beautiful natural panoramas, historical heritage, cultural diversity, and friendly people. The potential is different in each region, so it is possible to be developed in an effort to increase the attractiveness of domestic and international tourism so as to encourage regional economic growth.
In particular, domestic tourism is one of the drivers of regional economic growth in various countries. Based on the WWTC report (2018), in 2017, Indonesia's domestic tourism ranked 22nd out of 30 countries with the highest domestic tourism spending in the world, where total domestic tourism spending amounted to US$20.5 billion and contributed 59 percent to internal tourism and travel spending. The large contribution of domestic tourism shows that its existence is important and has an economic impact on the regional economy [1].
Tourism is one of the fastest-growing sectors of the world economy. Tourism development can drive economic growth both directly and indirectly, which can stimulate the growth of other sectors and increase domestic income and effective demand [2, 3]. There is much empirical evidence supporting the tourism-led growth hypothesis and mixed results from several studies explaining the moderating effect of the level of economic development [4].
The development of the tourism sector will have an impact on various economic indicators (e.g., impact on output, GDP, wages/wages, taxes, and employment opportunities). According to Sr and Croes [5], tourism has economic and social impacts through income and employment opportunities. Domestic tourism is one of the determinants of economic growth through increased employment, income, exports, and public sector revenue in the form of taxes [6, 7]. It should be encouraged in an effort to boost international tourism growth [8], one of which is through the promotion of domestic tourism in regional development [9]. As a prerequisite for national domestic tourism policy, stable prices and strong promotion of new destinations are essential [10]. Domestic tourism promotion can provide positive benefits in the framework of tourism development and increase the role of tourism in the regional economy [11]. Domestic tourism is an investment in the sustainable agenda for regional development [12]. Therefore, it is necessary to formulate appropriate policies for sustainable domestic tourism development [13].
Domestic tourism is still less of an object of study compared to international tourism. This may be influenced by the difficulty of obtaining data on domestic tourism movements. Although researchers cannot obtain many references, this study can be new evidence for the world in relation to its role in driving regional economic growth. This is in accordance with the study conducted by Hudson and Ritchie [14], where domestic tourism is most often ignored and rarely researched in tourism analysis. At the same time, tourism has beneficial economic and social impacts, as it can create new sources of external monetary income and employment opportunities in a regional economic activity [15].
In the next section after this, we present as follows. In Section 2, we present the relevant literature review. Section 3 presents the data and research methodology. Furthermore, Section 4 presents the research results and discussion, and Section 5 concludes the research.
Globally, tourism is the fastest-growing industry sector in the world (as found by Wang and Ge [16]; Wen [17]; Wu et al. [18] for China; Saayman et al. [19] for South Africa; Tosun et al. [20] for Turkey; Gokovali and Bahar [2] for Mediterranean countries; Klytchnikova and Dorosh [21] for Latin America; Surugiu and Surugiu [22] in Romania; Dogru and Bulut [23] for 7 European countries). The relatively rapid development of the tourism industry even surpasses all other industries [19], and its development is under the influence of growing interdependence worldwide [24].
The empirical findings of Surugiu and Surugiu [22] in Romania show that there is a relationship between tourism expansion and economic growth. To maintain its consistency, the government should make more consistent tourism development plans and strategies to be implemented at national and regional levels. The findings of Mérida and Golpe [25] for Spain show that there is a causality from economic growth to tourism; there is a two-way causality from 2000 onwards. According to Cárdenas-García et al. [26], based on their study of 144 countries shows that tourism has been able to drive economic growth in least-developed countries and developing countries.
Domestic tourism is the main sector of a mature and sophisticated tourism industry [27]. In addition, it is also one of the determinants of economic growth through increased employment and income [6, 28, 29], which is formed from spatial behavior patterns, and many aspects need to be further investigated [28]. Domestic tourism can contribute significantly to regional growth and development [19]. Domestic tourism in China more effectively reduces regional development imbalances [30]. The study conducted by Habibi et al. [31] for Iran also shows that tourism has had a positive impact by contributing to economic growth across its provinces.
Although tourism contributes to the development of a country, the tourism sector must be managed properly to avoid clashes with anti-tourism communities [32]. The study by Tovar and Lockwood [33] in rural Australia showed that tourism is an important economic sector in regional development, where support from the community is a prerequisite for a sustainable tourism industry.
The study of Mazumder et al. [34] in Southeast Asia shows that the tourism sector in those countries has successfully overcome the difficulties of regional tourism development and has economic potential. In contrast, development requires transparent goal formulation, implementation, and integration of goals into national plans, community participation, tourism entrepreneurship, and government cooperation and integration in developing tourism. Because the tourism industry is built on and dependent on local environmental, physical, and cultural resources [35], support for the tourism industry can help protect facilities and infrastructure that the community can use, maintain tourism capacity, and provide an attractive atmosphere for foreign visitors [36].
In contrast to the above findings, a study in Portugal showed that there is a vague interpretation of the concept of sustainable tourism in regional development, a lack of discussion on sustainability to be implemented, and difficulties in conducting strategic planning caused by closed public participation in planning [35]. To promote regional development through the tourism sector, participation of stakeholders from within the value chain pathway is required [37].
In regional development, tourism has contributed to spurring regional economic growth in various countries (e.g., Gugushvili et al. [38] for Georgia). Quality services are decisive for tourists in determining their choice of destination, even more than pricing policies [39]. To strengthen the tourism sector, regional cooperation is indispensable in realizing bright tourism in the future [39].
Beech and Simpson [40], in their study in the UK, suggested that the role of tourism in regional development is uneven based on indicators of tourism demand and employment, where the restructuring and internationalization of tourism demand has led to relative changes in supporting core areas. Torres and Momsen's [41] study in Mexico shows that tourism development planning has failed to stimulate balanced regional development, meaning that there is inequality and justice in development. In contrast, in China, tourism development has a positive impact on regional development balance and can reduce regional inequalities [42].
The active participation of the national government and local governments in tourism development planning is necessary to reduce the development gap between regions. In New Zealand, local governments are very proactive in managing the tourism sector by identifying tourism potential to contribute to regional development framed by the political philosophy of new regionalism [43]. Therefore, to maximize the economic development benefits of the tourism sector, it is necessary to plan tourism development to provide infrastructure and information [44].
Based on previous studies, the proposed hypotheses for this modeling are:
H1: Domestic tourist expenditure has a positive and significant effect on determining regional economic growth.
H2: The number of domestic tourist trips has a positive and significant effect on determining regional economic growth.
3.1 Data
The data used in this study are secondary in the form of time series and cross-section. The time series data in this study uses annual data from 2011 to 2018. At the same time, the cross-section data is data from 33 provinces (excluding North Kalimantan because it was just established as a new autonomous region on April 22, 2013). The data for this study is sourced from Statistics Indonesia, which consists of statistical publications from Gross Regional Domestic Product (GRDP), Domestic Tourist Profile, and Tourism Satellite Account (TSA) - Ministry of Tourism of Indonesia.
In Table 1, it can be observed that the research variables tested and analyzed in the modeling of this study consist of domestic tourist expenditure (DTE) and domestic tourist trips (DTT), consumer price index (CPI) as independent variables, and real gross regional domestic product (GRDP) as the dependent variable. Data processing is done using the static panel data method. In order for the data to be normally distributed, all data, except CPI, have been transformed into natural logarithm measurements.
The transformation of time series data into natural logarithm form aims to overcome several problems, such as bringing the data distribution closer to normal and reducing heteroscedasticity so that the data variation becomes more stable [45]. In addition, this transformation allows interpretation in the form of elasticity, making it easier to analyze the percentage change in the dependent variable against the percentage change in the independent variable [46]. Converting data to natural logarithms also linearizes exponential trends, thus simplifying data analysis [46].
Table 1. Data and measurement of variables
|
Variable |
Measurement |
Source |
|
Gross Regional Domestic Product (GRDP) |
Natural logarithm |
BPS-Statistics Indonesia |
|
Domestic Tourist Expenditure (DTE) |
Natural logarithm |
BPS-Statistics Indonesia TSA-Ministry of Tourism of Indonesia |
|
Domestic Tourist Trip (DTT) |
Natural logarithm |
BPS-Statistics Indonesia TSA-Ministry of Tourism of Indonesia |
|
Consumer Price Index (CPI) |
Percentage |
BPS-Statistics Indonesia |
3.2 Econometric methodology
This study was conducted to empirically analyze the impact of domestic tourism on regional economic growth in Indonesia. In the panel data model estimation, to see whether variable X affects Y, it can be known by looking at the probability value. If the probability value is < 0.10 < 0.05 < 0.01, then it is considered that variable X affects variable Y based on each category. This study uses two equations to prove the impact of domestic tourism stimulation on economic growth. In general, the equations to model the relationship between domestic tourism and economic growth can be written in Model 1 and Model 2 below:
Model 1
$G R D P_{i t}=f\left(D T E_{i t}, C P I_{i t}\right)$ (1)
$\ln G R D P_{i t}=\beta_0+\beta_1 \ln D T E_{i t}+\beta_2 C P I_{i t}+\varepsilon_{i t}$ (2)
Model 2
$G R D P_{i t}=f\left(D T T_{i t}, C P I_{i t}\right)$ (3)
$\ln G R D P_{i t}=\beta_0+\beta_1 \ln D T T_{i t}+\beta_2 C P I_{i t}+\varepsilon_{i t}$ (4)
where, lnGRDPit is the natural logarithm of gross regional domestic product in province i in year t, lnDTEit is the natural logarithm of domestic tourism expenditure in province i in year t, lnDTTit is the natural logarithm of domestic tourist trips in province i in year t, CPI is the percentage of consumer price index in province i in year t, β0 is a constant, β1-β2 are regression coefficients and εit is the error term.
The panel data model analysis was conducted using three methods: pooled least square, fixed effect, and random effect. Of the three methods, several tests were also carried out to select the most appropriate model, namely by conducting the Chow test and the Hausman test. Chow test is a test used to select the model to be used between pooled least squared or fixed effect. Conversely, the Hausman test is a test to select the model to be used between a fixed effect or random effect.
Data on variables determining regional economic growth through domestic tourism expenditure, number of domestic tourist trips, and consumer price index as control variables from 33 provinces in Indonesia during the period 2011-2018.
Table 2 shows the summary statistics of the estimated model of the determinants of regional economic growth through domestic tourism expenditure and the number of domestic tourist trips. The results presented/reported are the number of observations, mean, standard deviation (std. dev), minimum (min), and maximum (max). Table 1 presents the summary statistics for the variables used in this empirical analysis. It shows that over the sample period, on average, gross regional domestic product, domestic tourist expenditure, domestic tourist trips, and consumer price index are 32.50, 28.70, 15.16, and 134%, respectively.
Furthermore, Table 3 shows the estimation results of the panel data model of the relationship between domestic tourist expenditure and regional economic growth (GRDP). The estimation results are carried out through three tests, namely pooled OLS, Fixed effect, and random effect.
Table 3 shows the panel regression estimation values for regional economic growth attributable to domestic tourism. These results compare the three estimates, namely pooled OLS, fixed effect, and random effect. These three estimates have confirmed that the F-test is positive and significant at the 1% level. The panel data regression model must be tested to select the right regression model. This model selection is done through the Chow test and Hausman test. The Chow test is needed to compare the choice of estimation between a common effect or a fixed effect. In comparison, the Hausman test is needed to compare the choice of estimation between a fixed effect or random effect.
4.1 Chow test
The p-value can indicate this test. If the p-value <0.05 (statistically significant), then the estimation model used is fixed effect, but if the p-value >0.05 (not statistically significant), then the appropriate estimation model is common effect. From the results of Table 3, the resulting value in the statistical distribution of Chi squares is 911.84 (Model 1) and 888.22 (Model 2) with the resulting probability of 0.00, which is declared significant, so statistically, what happens is to reject H0 and accept H1. Thus, based on this estimation, the appropriate model is a fixed effect. In addition, all the explanatory variables are statistically significant. The goodness of fit of this approach is also improved, as seen from the Adjusted R-squared (R2) of 0.79 → 0.99 (Model 1) and 0.72 → 0.99 (Model 2).
4.2 Hausman test
If we reject the null hypothesis, namely when the value of the Hausman statistic is greater than its critical value, then the right model is a fixed effect model, while conversely, if we fail to reject the null hypothesis, namely when the value of the Hausman statistic is smaller than its critical value, then the right model is a random effect model. This test can be done by comparing the Chi-square value with the p-value. If the p-value < 0.05 (statistically significant), then the appropriate estimation model is fixed effect, but if the p-value > 0.05 (not statistically significant), then the appropriate estimation model is random effect. Table 3 shows that the chi-squares values are 71.37 (Model 1) and 28.56 (Model 2), respectively, with a p-value of < 0.00 or < 0.05, which is significant, so statistically, what happens is to reject H0 and accept H1. Thus, based on this estimation, the appropriate model is a fixed effect. In addition, all the explanatory variables are statistically significant. The goodness of fit of this approach is also improved, as seen from the Adjusted R-squared (R2) of 0.46 → 0.99 (Model 1) and 0.29 → 0.99 (Model 2).
The results of the Chow test and Hausman test indicate that the appropriate estimation for this modeling is fixed effect. Therefore, only fixed effects will be discussed further in this study. It can be observed here that for the fixed effect estimation in Model 1, the variable that has a major effect on determining the value of regional economic growth is only the domestic tourist expenditure variable. It is indicated by the coefficient, which is positive and significant at the level. In contrast, the coefficient for the CPI variable is also positive but not significant.
Testing Model 2 is consistent with Model 1, where the number of domestic tourist trips has a major effect on increasing tourist expenditure. In other words, domestic trips are stable in determining regional growth in Indonesia. The increase in domestic trips is in line with the increase in tourist expenditure, where the more domestic trips, the more expenditure increases.
Table 2. Descriptive statistics
|
Variable |
Description |
Obs |
Mean |
Std. Dev. |
Min |
Max |
|
lnGRDP |
Natural logarithm of gross regional domestic product |
264 |
32.50 |
1.17 |
30.40 |
35.09 |
|
lnDTE |
Natural logarithm of domestic tourist expenditure |
264 |
28.70 |
1.22 |
26.03 |
31.87 |
|
lnDTT |
Natural logarithm of domestic tourist trip |
264 |
15.16 |
1.15 |
12.86 |
17.81 |
|
CPI |
Consumer price index (%) |
264 |
131.31 |
10.19 |
112.58 |
161.83 |
Table 3. Panel data model estimation results
|
|
|
Pooled OLS |
Fixed Effect |
Random Effect |
|
|
Independent Variable |
Dependent Variable: lnGRDP |
||
|
Model 1 |
lnDTE |
0.857509*** (31.65713) |
0.266703*** (14.07407) |
0.306278*** (16.69054) |
|
CPI |
0.006046* (1.864917) |
0.0000258 (0.039592) |
0.000245 (0.376784) |
|
|
F-statistic |
504.3059*** |
1029.385*** |
112.5671*** |
|
|
Chow test |
|
911.837725*** |
|
|
|
Hausman test |
|
|
71.369529*** |
|
|
Adjusted R-squared |
0.792850 |
0.992534 |
0.458997 |
|
|
|
Observations |
33 |
33 |
33 |
|
Model 2 |
lnDTT |
0.862120*** (25.95505) |
0.318604*** (7.743878) |
0.405283*** (10.71883) |
|
CPI |
-0.000489 (-0.130607) |
-0.001229 (-1.573058) |
-0.001151 (-1.473389) |
|
|
F-statistic |
339.2141*** |
694.3174*** |
54.09702*** |
|
|
Chow test |
|
888.220243*** |
|
|
|
Hausman test |
|
|
28.563652*** |
|
|
Adjusted R-squared |
0.720042 |
0.988966 |
0.287637 |
|
|
|
Observations |
33 |
33 |
33 |
Notes: Natural logarithm of Gross Regional Domestic Product (lnGRDP) is the dependent variable; figures in parenthesis are the t-statistic; ***significant at 1% level, **significant at 5% level, and *significant at 10% level.
Source: Author’s calculation
In this section, we will discuss the findings of this study and its relation to previous studies. The findings of this study on the effect of domestic tourist expenditure on economic growth are in line with studies conducted by Surugiu and Surugiu [22] for Romania, Bento [47] for Portugal, Cortés-jiménez [48] for Spain and Italy; Paci and Marrocu [49]; Eriksen and Ahmt [50]; Bond et al. [51]; Beech and Simpson [40] for coastal and inland China. In contrast, the findings of Kang et al. [52] for South Korea show that at the macro level, tourism activities have not been concentrated and have not provided an equitable distribution of benefits for the entire region. In the case of Indonesia, in general, the tourism sector has been proven to affect economic growth in the short and long term [3]. As part of efforts to promote sustainable economic growth, the concept of tourism villages has been developed. These villages, which integrate unique local features with tourism, history, and cultural elements, have emerged as prominent tourist destinations [53]. The millennial generation plays a crucial role in their development, actively participating and taking responsibility for advancing tourism villages within their local communities [54].
The cited literature study shows that some results are in line with the findings of this study. In other words, this study matches and supports previous research that has been conducted in many countries, proving that domestic tourism also contributes to a country's regional development.
The results of the study show that domestic tourism expenditure and regional economic growth variables have a long-term relationship. The existence of this relationship shows that there is an equilibrium in the long run. In addition, based on the results of hypothesis testing, it also has a significant and positive effect on regional economic growth at the real level of one percent. The results indicate that if there is a change in domestic tourism expenditure, it will trigger regional economic growth in each province in Indonesia. The results of this study are new evidence in enriching scientific findings related to the contribution of domestic tourism in encouraging accelerated and equitable regional development. We suggest more studies on the importance of domestic tourism in regional economic development in each country, especially developing countries.
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