Can inbound medical tourism boost Malaysia’s economic growth?

Abstract

Medical tourism is an extensively researched sub-sector of the tourism industry because of its acknowledged role as an important catalyst for economic growth. Nevertheless, the impact of medical tourism on economic growth remains contentious due to associated negative externalities. This paper assesses medical tourism’s role in Malaysia’s long-term economic growth using a neoclassical growth model as its framework and a set of time series econometric approaches, namely cointegration, Granger causality and variance decomposition analysis as core instruments. The results indicate that medical tourism has significant positive impact on Malaysia’s economic growth in the long run.

Keywords

Granger causality economic growth Malaysia medical tourism variance decomposition

Introduction

Key drivers for long-term economic growth are manifold and have often been researched upon extensively as their contributions are vital for ensuring sustainable economic growth and socio-economic well-being (Fellner, 1960; Tobin, 1964). Tourism has long been noted for its capacity to accelerate economic growth, a phenomena termed as the tourism-led growth (TLG) hypothesis. The TLG hypothesis has been the subject of numerous studies to evaluate its validity in both developed and developing economies (e.g. Balaguer and Cantavella-Jordà, 2002; Narayan and Prasad, 2003; Tang and Abosedra, 2016; Tang and Tan, 2015a; Tang et al., 2016). Tang and Tan (2013) noted that, despite its lack of universal validation, the TLG hypothesis was valid in the Malaysian context.

Tourism is a vital component of the Malaysian economy because of its important role in income generation and job creation. A major factor for tourism’s growth in the country is due to tourism’s widely acknowledged capacity to generate multiplier effects through the synergy of forward and backward linkages within the tourism value chain (United Nations Conference on Trade and Development, 2013) which in turn contributes to higher employment, poverty alleviation (Overseas Development Institute, 2007) and narrowing income disparities (Ashley et al., 2007) as well as balance of payment realignments (Malik et al., 2010; Thano, 2015). This multiplier effect is particularly evident in the Malaysian tourism narrative as growth in this sector accelerated in the 1980s subsequent to a policy reconfiguration designed to offset diminishing revenues derivable from the export sector due to a collapse in the price of primary commodities particularly rubber and tin. These policy realignments sought to market Malaysia’s natural attractions, cultural heritage and culinary delights as tourism products with the simultaneous objective of leveraging on the anticipated returns to drive socio-economic growth and poverty reduction initiatives (Mosbah and Al Khuja, 2014; Nanthakumar et al., 2008). A key component of this realignment was the formulation of three tourism master plans, namely the National Tourism Policy in 1992, the National Ecotourism Plan in 1996 and the Malaysian Tourism Transformation Programme in 2010. The net result of the implementation of these plans allied to the earlier reconstitution of the old Tourism Development Corporation of Malaysia as the Malaysian Tourism Promotion Board or more popularly known as Tourism Malaysia in 1992 has been significant growth in both income and job opportunities in the tourism sector. For instance, tourism contributed approximately MYR 161 billion or 14.9% of the nation’s gross domestic product (GDP), raking in MYR 72 billion in tourism receipts on the back of 27.44 million tourist arrivals whilst bringing in MYR 19.4 billion worth of investment and contributing 1.77 million jobs (13% of total employment) in 2014 alone (Mohsen, 2015). These gains resulted in Malaysia being ranked 26 out of 184 countries in the world with regard to Travel and Tourism’s contribution to GDP (World Travel and Tourism Council, 2015).

One of the emerging sub-sectors of tourism in Malaysia is medical tourism. Due to astute policy realignments in the healthcare sector to exploit latent demand both in the ASEAN region and beyond and coupled with a convergence of pull factors (Connell, 2013; Fetscherin and Stephano, 2016), medical tourism has witnessed an exponential growth in both arrivals, receipts and facilities. In terms of arrivals, the figures peaked in 2014 when 882,000 medical tourists sought treatment in Malaysia while gross receipts totalled MYR 900 million in 2015 (International Medical Travel Journal, 2016). Additionally, the number of facilities has more than doubled from 35 in 2009 to 78 in 2014. All these achievements were recorded within a short time frame of approximately 16 years commencing 1998 when Malaysia embarked on imbricating medical tourism as a key sub-sector of tourism.

The example of Malaysia substantiates the postulation that medical tourism has emerged as one of the key sub-sectors that have thus far generated substantial revenue for numerous economies (Chaynee, 2003). Hence, it is unsurprising that policy-makers in both developed and developing economies have been assiduously promoting medical tourism in efforts to boost economic growth. However, a review of current literature reveals that the actual impact of medical tourism on economic growth is debatable. This is because while medical tourism spurs economic growth via its positive impact on foreign currency earnings, investments in infrastructure, tax revenues and employment opportunities, it may also generate negative externalities as evidenced by the New Delhi metallo-β-lactamase superbug scare in the United Kingdom (Kumarasamy et al., 2010) and infectious diseases afflicting Third World medical destinations (Cuddington, 1993; Cuddington and Hancock, 1994), the increase in healthcare costs (Gupta, 2008; Hazarika, 2010; NaRanong and NaRanong, 2011; Ramírez de Arellano, 2007) that either directly or indirectly impinge upon the process of economic growth and development.¹

In light of these contradicting outcomes, it is essential to ascertain medical tourism’s role in boosting long-term economic growth. Thus, we chose Malaysia for case study since there is a dearth of empirical research on the role of medical tourism in Malaysia’s economic growth. We utilised co-integration, Granger causality and variance decomposition tests to evaluate both the validity of the medical TLG hypothesis and ascertain its sustainability as a long-term catalyst for economic growth.

Following this introduction, the next section provides a general overview of medical tourism in Malaysia. The subsequent section discusses methodology and results while conclusions and policy implications derived is presented in the final section.

Overview of medical tourism in Malaysia

The Malaysian medical tourism narrative is a testament of public–private sector synergies that have yielded impressive results within a short span of time. These two sectors have often worked in tandem to propel the medical tourism agenda through a variety of strategic policy formulations and investment initiatives.

The role of the private sector in foregrounding medical tourism is essentially predicated on corporate mergers and acquisitions initiatives that have served to create global health service corporations through the establishment and the consolidation of medical centres under mega private healthcare groups such as the Parkway Group in 2010 and the Integrated Healthcare Holding Groups in 2013. The subsequent economies of scale accrued have lowered costs via the provision of a technology-based, human expertise helmed and quality delivery-oriented private medical service sector which has attracted medical tourists seeking affordable, safe and quality treatment. Consequently, these capex have led to the birth of Joint Commission International (JCI) – the gold standard for international accreditation – accredited medical centres, which as of 2015 totalled seven.

In the public sector context, the evolution of Malaysia’s medical tourism sector accelerated from 1998 onwards when a series of tax incentives were instituted in order to promote the medical tourism sub-sector. This led to private medical institutions investing in facility upgrades and expertise enhancements in order to gain international accreditation. Chee (2010) noted that Malaysia was among the first in the Asian region to promote medical tourism as a growth industry. Poon (2008) highlighted that the Malaysian government has thus far allocated at least MYR 110 billion to build new public hospitals to develop the medical tourism sector in Malaysia. Amongst the other direct support measures rendered by the government include the provision of visas for foreign visitors seeking health treatment and tax incentives (International Medical Travel Journal, 2011). In addition, the Ministry of Health has created the Malaysia Healthcare Travel Council to promote medical tourism. Finally, the government has identified medical tourism as one sub-sector of Healthcare, which was designated as one of the 12 National Key Economic Areas (NKEA).

The net result of these initiatives was an exponential growth in both medical tourist arrivals and gross receipts amounting to 341,288 and MYR 254 million, respectively, as of 2008 (Pocock and Phua, 2011). This linear exponential growth was further accelerated with the designation of Healthcare in 2010 as one of the country’s 12 NKEAs deemed to have the potential to spur growth. As part of the Healthcare NKEA, medical tourism is targeted to generate MYR 9.6 billion (Musa et al., 2012) in revenue and MYR 4.3 billion in gross national income and to employ 5300 more medical professionals by 2020 (PEMANDU, 2010). As of 2015, total hospital receipts alone amounted to MYR 900 million which is projected to reach MYR 1.3 billion in 2016. Additionally, medical tourist arrivals have also increased from 641,000 in 2011 to more than 880,000 in 2015 (International Medical Travel Journal, 2016) with arrivals being mainly from Indonesia (72%), Singapore (10%), Japan (5%) and West Asia (2%) (United Nations Economic and Social Commission for Asia and the Pacific, 2007). In terms of destinations, a majority of medical tourists travelled to Penang (61%) (Ormond, 2011).

Finally, other extrinsic factors have also coalesced to propel Medical tourism to the forefront of the tourism and healthcare sector. In fact, Malaysia’s emergence as a medical tourism hub resides in its fulfilment of what Connell (2013) defines as the five essentials of medical tourism, namely attraction, amenities, accessibility, accommodation and awareness. From the attraction perspective, cost is one of the key reasons for Malaysia’s emergence as a major medical tourism destination in Asia. With its relatively low exchange rate (USD 1.00 = MYR 4.00), Malaysia offers excellent medical care at affordable rates when compared with its competitors in both the developed and developing world (Smith et al., 2009). In relation to accessibility, Aigbogun et al. (2013) note that easy availability to air transport as provided by low cost carriers like AirAsia, Malindo and Firefly has enabled more medical tourists to seek treatment in the country. This plus the existence of good transport infrastructure in the major cities of Kuala Lumpur, Georgetown and Johor Bahru means that travel costs are minimal. As for accommodation, both Hilmi and Ngo (2011) and Kelly (2010) highlight how hoteliers and wellness resort operators have optimally refined their offerings to cater to the needs of a specific niche market and thus attract more medical tourists to the country. In other words, the availability of suitable accommodation is another pull factor that has abetted the medical tourism sector’s robust growth. In terms of amenities, most private hospitals that are the main purveyors of medical tourism possess not only sophisticated treatment and recuperation facilities but also contemporary communication facilities such as easy internet and telephony access. These facilities are further augmented by ancillary facilities within hospitals such as pharmacies, retail outlets and cafeterias. Medical tourism arrivals in Malaysia have to a large extent boosted by awareness about the excellent treatment and care services provided by Malaysian hospitals. In this regard, word of mouth is a key factor as delineated by Yeoh et al. (2013) while well-structured and informative websites of medical facilities play a key role in drawing in medical tourists (Anvekar, 2012)

In short, the Malaysian medical tourism sector has witnessed phenomenal growth since its evolution from an ancillary income generating sector of the local Healthcare industry to one of the key sub-sectors of the Malaysian tourism industry due to the convergence of crucial pull factors that were carefully modulated both by public sector policy makers and private sector health service providers.

Despite these developments, the Malaysian medical tourism sector is not immune to problems that plague the medical tourism industry in the region. Most of these problems are associated with the issues of equity and accessibility to quality healthcare (Blouin, 2010). Inequality in healthcare arises when only high- and middle-income earners can access healthcare services due to the high costs of treatment attributable to increased demand for finite resources and expertise (Ramesh and Xun, 2006). Consequently, Medical and Health Insurance (MHI) policies have become tools to mitigate rising healthcare costs. As of 2003, data from Bank Negara Malaysia (BNM) revealed that MHI-based premiums totalled almost MYR 1.0 billion in 2002 or 5.5% of all premiums paid (Bank Negara Malaysia, 2002). A decade later, the quantum of these premiums constituted approximately 20% due to inflation (Chin, 2014).

These negative externalities pertaining to equity and costs of quality healthcare raise the question as to how sustainable and viable is medical tourism for Malaysia’s long-term economic growth.

Methodology and results

Since the aim of this study was to examine the effects of medical tourism on economic growth in Malaysia, we applied the following two sectors: Feder (1983) growth model extended by Tang and Tan (2015b)

\ln {GDP}_{t} = β_{0} + β_{1} \ln K_{t} + β_{2} \ln {MTOUR}_{t} + β_{3} \ln {XG}_{t} + ɛ_{t}

(1)

where

\ln GDP

is the natural logarithm of per capita real GDP,

\ln K

is per capita real capital,

\ln MTOUR

is per capita real medical tourism receipts,

\ln XG

is per capita real export of goods and

ɛ_{t}

is the disturbance term.

This study used quarterly data from 1998:Q1 to 2013:Q4. The data were extracted from the International Financial Statistics published by the International Monetary Fund, Monthly Statistical Bulletin published by BNM and Tourism Satellite Account published by the Department of Statistics, Malaysia.² Additionally, the GDP deflator (2005 = 100) was used to compute the real values of each variable.

We first determined the degree of integration using Augmented Dickey–Fuller (ADF) and Generalised Least Squares of Dickey–Fuller (DF-GLS) unit root tests. Table 1 shows the results of ADF and DF-GLS unit root tests. At the 5% significance level, the results of the ADF test suggest that medical tourism is I(0) while other variables are I(1) process. Nevertheless, the DF-GLS test suggests that all variables, including medical tourism are integrated at order one, I(1). This signifies that the order of integrations is mixed among the variables of interest, indicating that the bounds testing approach to co-integration as developed by Pesaran et al. (2001) is necessary to assess the presence of a co-integrating relationship between real GDP and its determinants. To do so, we estimate the following unrestricted error-correction model with ordinary least squares (OLS) estimator:

Δ \ln {GDP}_{t} = α + θ_{1} \ln {GDP}_{t - 1} + θ_{2} \ln K_{t - 1} + θ_{3} \ln {MTOUR}_{t - 1} + θ_{4} \ln {XG}_{t - 1} + \sum_{j = 1}^{k} δ_{j} Δ \ln {GDP}_{t - j} + \sum_{j = 0}^{k} γ_{j} Δ \ln K_{t - j} + \sum_{j = 0}^{k} ϕ_{j} Δ \ln {MTOUR}_{t - j} + \sum_{j = 0}^{k} λ_{j} Δ \ln {XG}_{t - j} + e_{t}

(2)

Δ is the first difference operator and e_t is the disturbance term. The results are presented in Panel A of Table 2.

Table 1.

Results of ADF DF-GLS unit root tests.

Variables	ADF	DF-GLS
$\ln {GDP}_{t}$	−2.895 (5)	−2.807 (5)
$Δ \ln {GDP}_{t}$	−4.749 (4)***	−4.408 (4)***
$\ln K_{t}$	−3.071 (4)	−2.004 (2)
$Δ \ln K_{t}$	−4.395 (3)***	−10.217 (1)***
$\ln {MTOUR}_{t}$	−3.579 (0)**	−2.782 (0)
$Δ \ln {MTOUR}_{t}$	−10.878 (0)***	−7.557 (0)***
$\ln {XG}_{t}$	−2.430 (2)	−1.816 (2)
$Δ \ln {XG}_{t}$	−8.723 (1)***	−8.779 (1)***

ADF: Augmented Dickey–Fuller; DF-GLS: Generalised Least Squares of Dickey–Fuller; GDP: gross domestic product.

Note: *** and ** denote significant at the 1 and 5% levels, respectively. Figure in (.) indicates the optimal lag length selected by Akaike Information Criterion.

Table 2.

Results of bounds test for co-integration.

Panel A: Bounds test for co-integration
Calculated F-statistic
$F_{\ln GDP} (\ln GDP \| \ln K, \ln MTOUR, \ln XG)$	6.231***
# Critical values (F-test):
Significance level (%)	Lower I(0)			Upper I(1)
1	4.690			6.143
5	3.435			4.583
10	2.843			3.923
Panel B: Long-run coefficients
Variables		Coefficients	Std. errors	t-statistics
Constant		7.9940***	0.2758	28.9807
$\ln K_{t}$		0.0673***	0.0227	2.9636
$\ln {MTOUR}_{t}$		0.1075***	0.0048	22.3879
$\ln {XG}_{t}$		0.0989*	0.0516	1.9160

Note: *** and * denote significance at the 1 and 10% levels, respectively. # Unrestricted intercept and no trend (k = 3 and T = 65) critical values are obtained from Narayan (2005).

R-squared: 0.972; Adjusted R-squared: 0.942; F-Statistic: 32.586 (0.0000); Shapiro–Wilk: 0.9681 (0.1508); Ramsey RESET [1]: 1.026 (0.3111), [2]: 3.421 (0.1808); Breusch–Godfrey LM test [2]: 0.214 (0.8985), [4]: 2.051 (0.7264); ARCH test [2]: 0.421 (0.8101), [4]: 1.976 (0.7402).

[.] refer to the diagnostics tests order; (.) refer to the p-values.

The calculated F-statistic for bounds test was 6.231 and greater than the 1% upper bound critical values as proposed by Narayan (2005). This implies that there is a long-run equilibrium relationship between real GDP, real capital, real medical tourism and real export of goods in Malaysia from 1998:Q1 to 2013:Q4. We then proceeded to estimate the long-run coefficients by setting real GDP as the dependent variable since our key interest was to assess the response of economic growth to medical tourism, capital and export of goods in Malaysia. The estimated co-integrating equation is illustrated in Panel B of Table 2 with all variables being statistically significant at the 10% level or better. Specifically, a 10% increase in medical tourism will entail a real GDP increase of approximately 1.1% in the long run. In contrast, economic growth increases by approximately 0.67 and 0.98% for every 10% increase in real capital and real export of goods, respectively.

Next, we examined the Granger causality between economic growth and its determinants by estimating the following vector error-correction model (VECM):

(1 - L) [\ln {GDP}_{t} \ln K_{t} \ln {MTOUR}_{t} \ln {XG}_{t}] = [a_{1} a_{2} a_{3} a_{4}] + \sum_{j = 1}^{k} (1 - L) [A_{11, j} A_{12, j} A_{13, j} A_{14, j} A_{21, j} A_{22, j} A_{23, j} A_{24, j} A_{31, j} A_{32, j} A_{33, j} A_{34, j} A_{41, j} A_{42, j} A_{43, j} A_{44, j}] \times [\ln {GDP}_{t - j} \ln K_{t - j} \ln {MTOUR}_{t - j} \ln {XG}_{t - j}] + [ψ_{1} ψ_{2} ψ_{3} ψ_{4}] \times [{ECT}_{t - 1}] + [e_{1 t} e_{2 t} e_{3 t} e_{4 t}]

(3)

where

(1 - L)

is the first difference operator and in is the natural logarithm. The residuals

e_{it}

were assumed to be normally distributed and white noise.

{ECT}_{t - 1}

is the one period lagged error-correction term computed from the co-integrating equation (1). The t-statistic on the coefficient of the

{ECT}_{t - 1}

indicates the statistical significance of the long-run Granger causal effects while the likelihood ratio statistics on the first difference lagged explanatory variables indicates the statistical significance of the short-run Granger causal effects.³

Table 3 indicates that the coefficients of ${ECT}_{t - 1}$ were statistically significant at the 5% level in all estimated VECMs thus signalling that economic growth, medical tourism, capital and export of goods in Malaysia Granger-cause each other in the long run.⁴ With reference to the short-run causality results, we noted that capital and exports of goods were statistically significant at the 1% level when economic growth and medical tourism are dependent variables of VECM. Additionally, economic growth is significant at the 1% level only in the capital and export of goods equations. Finally, medical tourism is statistically significant at the 5% level or better in the economic growth and capital equations. To surmise, there are bidirectional causalities, between economic growth and exports of goods, between economic growth and capital, and between capital and medical tourism while there is a unidirectional causality running from exports of goods to medical tourism and medical tourism. As the data clearly indicate that medical tourism Granger-causes economic growth in both the short and long run, we can conclude that medical tourism is an effective catalyst for economic growth in Malaysia, a finding consistent with those of Tang and Tan (2013, 2015a, 2015b). For the sake of brevity, the direction of causality between the variables of interest can be summarised in Figure 1.

Figure 1.

Summary of the short- and long-run Granger causalities.

Table 3.

The results of the Granger causality test – VECM.

Explanatory variables	Dependent variables
	$Δ \ln {GDP}_{t}$	$Δ \ln K_{t}$	$Δ \ln {MTOUR}_{t}$	$Δ \ln {XG}_{t}$
	Likelihood ratio (LR) statistics
$\sum Δ \ln {GDP}_{t - j}$	–	14.233***	0.068	63.239***
$\sum Δ \ln K_{t - j}$	28.529***	–	27.079***	0.070
$\sum Δ \ln M {TOUR}_{t - j}$	33.086***	17.221**	–	3.010
$\sum Δ \ln {XG}_{t - j}$	58.091***	1.447	34.288***	–
${ECT}_{t - 1}$ [t-statistics]	−0.541** [−2.7240]	−0.673*** [−3.4433]	−0.641*** [−4.9522]	−0.557*** [−3.5229]

Note: The asterisks *** and ** denote significance at the 1 and 5% levels, respectively.

Cognisant of the fact that the Granger causality test is insufficient to determine the effectiveness of economic policy as documented in Buiter (1986), we utilised the generalised variance decomposition analysis as proposed by Pesaran and Shin (1998) to affirm the relative strength of real capital, real medical tourism and real exports of goods in Malaysia’s economic growth. As the variables were co-integrated, the VECM framework was used to perform the generalised variance decomposition analysis. Table 4 presents the results.

Table 4.

Generalised variance decomposition analysis of lnGDP.

Horizon	lnGDP _t	lnK _t	lnMTOUR _t	lnXG _t
1	45.84	11.57	17.66	24.93
4	43.68	8.79	25.50	22.04
8	38.28	8.78	31.39	21.54
12	35.03	10.30	33.17	21.49
24	30.07	10.55	37.99	21.39

Note: The above generalised variances are re-scaled into 100.

In the short run (i.e. four quarters), 43.7% of the variations in economic growth was explained by its own innovation. In contrast, a shock in real capital, real medical tourism and real export only explained about 8.8, 25.5 and 22%, respectively, of variations in economic growth. Over the long run (i.e. 24 quarters), real medical tourism explained approximately 38% of variations in economic growth. On the other hand, real exports of goods and real capital, respectively, explained about 21.4 and 10.6% of all variations. Thus, it can be concluded that medical tourism is a key determinant of Malaysia’s economic growth in both the short and long run.

Conclusions and policy implications

This paper sought to determine the extent of medical tourism’s role in Malaysia’s long-run economic growth. To answer this research question, we employed a series of parametric tests, namely the co-integration, Granger causality and the generalised variance decomposition tests. We found that economic growth, medical tourism and other determinants in Malaysia were co-integrated and that the response of economic growth to medical tourism was slightly higher than that to capital and export of goods. The generalised variance decomposition analysis also identified medical tourism as the most important factor in explaining the variations in economic growth in both the short and long run. Finally, we found that medical tourism Granger-causes economic growth in Malaysia, regardless of short or long run.

Several policy implications arise from these findings. First, medical tourism’s function as an effective catalyst can be further augmented through the provision of Goods and Service Tax (GST) exemption on medical supplies and equipment. This will help reduce treatment, medication and hospitalisation costs that will consequently attract medical tourists in search of affordable treatment. Alternatively, a GST refund mechanism can be made available for genuine medical tourists. Second, the private sector should be incentivised to open more medical facilities that cater to tourists in our economic corridors. For example, investing in medical facilities in the Iskandar Region of Johor would enable healthcare providers to tap into the Singaporean clientele base seeking quality yet affordable medical services abroad to offset high medical costs at home. In this regard, Malaysia is eminently placed to fulfil that demand as exchange rate differentials are currently skewed in its favour. Third, local medical tourism purveyors should seek international accreditation from renowned organisations like the JCI in the United States, the Australian Council for Healthcare Standards International in Australia and quality healthcare advice (QHA) Trent in the United Kingdom in order to gain the confidence of medical tourists from Europe, the Americas and Australasia. Furthermore, accreditation has the winnowing effect of filtering out low-quality healthcare providers thus indirectly foregrounding Malaysia as a provider of safe and quality healthcare. Finally, legal protection for patients, easier facilitation of litigation and prompt disposal of claims arising from malpractice would engender trust in foreign tourists seeking medical treatment while simultaneously functioning as a quality control mechanism that ensures the highest standards of service are adhered to. All these efforts will emplace Malaysia as a destination that provides affordable, safe and quality medical services, thus optimising the impact of medical tourism on economic growth in Malaysia.

Footnotes

Acknowledgement

We would like to thank the two anonymous reviewers for their critical and valuable suggestion on the earlier draft of this research paper. Any flaws that remain in this paper are our own responsibility.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first author would like to acknowledge Universiti Sains Malaysia Short-Term Research Grant No. 304/CDASAR/6313179.

Notes

Author Biographies

Chor Foon Tang is a senior lecturer at the Centre for Policy Research and International Studies, Universiti Sains Malaysia. He holds a Ph.D. degree in Economics from University of Malaya. His research interest encompasses Development Economics, Tourism Economics, and Applied Macroeconomics.

Ahmad Sofwan Nathan Abdullah is attached to the School of Languages, Literacies and Translation, Universiti Sains Malaysia. He has a Bachelor of Arts (Hons) and a Master of Arts (MA) from University of Malaya. He has written or co-written as well as edited 5 books, 15 book chapters, and journal articles on issues ranging from Higher Education, Socio-Economic Empowerment to Tourism.

References

Aigbogun

Yassin

Shoukat

(2013) A model for accelerating the growth of health care tourism in Malaysia. Journal of Business and Economics 4(2): 169–179.

Anvekar

(2012) Medical tourism in India: A strategic approach towards effective branding in health care services marketing. American Journal of Management 12(2/3): 108–116.

Ashley

De Brine

Lehr

et al. (2007) The Role of Tourism Sector in Expanding Economic Opportunity. Corporate Social Responsibility Initiative Report No. 23, Cambridge, MA: Kennedy School of Government, Harvard University.

Balaguer

Cantavella-Jordà

(2002) Tourism as a long-run economic growth factor: The Spanish case. Applied Economics 34(7): 877–884.

Bank Negara Malaysia (2002) Developments in medical and health insurance business. Available at: www.bnm.gov.my/files/publication/dgi/en/2002/05.Box1.pdf (accessed 12 July 2015).

Bezruchka

(2000) Medical tourism as medical harm to the third world: Why? For whom? Wilderness and Environmental Medicine 11(2): 77–78.

Bishop

Litch

(2000) Medical tourism can do harm. British Medical Journal 320(7240): 1017.

Blouin

(2010) Trade in health services: Can it improve access to health care for poor people? Global Social Policy 10(3): 293–295.

Buiter WH (1986) Ganger-Causality and Policy Ineffectiveness: A Rejoinder. NBER Technical Working Paper No. 61. National Bureau of Economic Research, Cambridge, MA.

10.

Chaynee

(2003) Health Tourism to Earning, Kuala Lumpur: Malaysian Institute of Economic Research.

11.

Chee

(2010) Medical tourism and the state in Malaysia and Singapore. Global Social Policy 10(3): 336–357.

12.

Chee

Whittaker

(2010) Guest editors’ introduction to the special issue: Why is medical travel of concern to global social policy? Global Social Policy 10(3): 287–291.

13.

Chin C (2014) Policyholders to pay more for coverage. The Star, 20 April.

14.

Connell

(2013) Contemporary medical tourism: Conceptualisation, culture and commodification. Tourism Management 34: 1–13.

15.

Cuddington

(1993) Modeling the macroeconomic effects of AIDS, with an application to Tanzania. World Bank Economic Review 7(2): 173–189.

16.

Cuddington

Hancock

(1994) Assessing the impact of AIDS on the growth path of the Malawian economy. Journal of Development Economics 43(2): 363–368.

17.

Feder

(1983) On exports and economic growth. Journal of Development Economics 12(1–2): 59–73.

18.

Fellner

(1960) Rapid growth as an objective of economic policy. American Economic Review 50(2): 93–105.

19.

Fetscherin

Stephano

(2016) The medical tourism index: Scale development and validation. Tourism Management 52: 539–556.

20.

Grag

(2013) “All is not well” with medical tourism. International Journal of Community Medicine 38(1): 59–61.

21.

Gupta

(2008) Medical tourism in India: Winners and losers. International Journal of Medical Ethics 5(1): 4–5.

22.

Hall

(2011) Health and medical tourism: A kill or cure for global public health? Tourism Review 66(1–2): 4–15.

23.

Hazarika

(2010) Medical tourism: Its potential impact on health workforce and health systems in India. Health Policy and Planning 25(3): 248–251.

24.

Hilmi

Ngo

(2011) Factors affecting hoteliers’ decision to advertise in travel magazine. Journal of Management and Strategy 2(3): 62–72.

25.

International Medical Travel Journal (2011) Tax exemption for private hospitals to boost medical tourism in Malaysia. International Medical Travel Journal: News. Available at: www.imtj.com/news/EntryId82=289724 (accessed 13 July 2015).

26.

International Medical Travel Journal (2016) Record year for Malaysian medical tourism. International Medical Travel Journal: News. Available at: www.imtj.com/news/record-year-malaysia-medical-tourism (accessed 27 August 2016).

27.

Kelly

(2010) Analysing wellness tourism provision: A retreat operators’ study. Journal of Hospitality and Tourism Management 17(1): 108–116.

28.

Kremers

JJM

Ericsson

Dolado

(1992) The power of cointegration tests. Oxford Bulletin of Economics and Statistics 54(3): 325–348.

29.

Kumarasamy

et al. (2010) Emergence of a new antibiotic resistant mechanism in India, Pakistan, and the UK: A molecular, biological, and epidemiological study. Lancet Infectious Diseases 10(9): 597–602.

30.

Malik

Chaudhry

Sheikh

(2010) Tourism, economic growth and current account deﬁcit in Pakistan: Evidence from co-integration and causal analysis. European Journal of Economics, Finance and Administrative Sciences 22: 21–31.

31.

Mohsen AS (2015) Tourism industry now 6th largest GDP contributor, says Najib. The Sun, 19 October.

32.

Mosbah

Al Khuja

MSA

(2014) A review of tourism development in Malaysia. European Journal of Business Management 6(5): 1–9.

33.

Musa

Doshi

Wong

et al. (2012) How satisfied are inbound medical tourists in Malaysia? A study of private hospitals in Kuala Lumpur. Journal of Travel and Tourism Marketing 29(7): 629–646.

34.

Nanthakumar

Ibrahim

Harun

(2008) Tourism development policy, strategic alliances and impact of consumer price index on tourist arrivals: The case of Malaysia. TOURISMOS: An International Multidisciplinary Journal of Tourism 3(1): 83–98.

35.

NaRanong

(2011) The effects of medical tourism: Thailand’s experience. Bulletin of the World Health Organization 89(5): 317–392.

36.

Narayan

(2005) The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics 37(17): 1979–1990.

37.

Narayan

Prasad

(2003) Does tourism Granger causes economic growth in Fiji? Empirical Economics Letters 2(5): 199–208.

38.

Ormond

(2011) Medical tourism, medical exile: Responding to the cross-border pursuit of health care in Malaysia. In: Minca

Oakes

(eds) Real Tourism: Representation, Practice and the ‘Material’ in Contemporary Travel, Oxford: Routledge, pp. 143–161.

39.

Overseas Development Institute (2007) Can tourism offer pro-poor pathways to prosperity? Examining evidence on the impact of tourism on poverty. Available at: www.odi.org/sites/odi.org.uk/ﬁles/odi-assets/publications-opinion-ﬁles/110.pdf (accessed 26 August 2016).

40.

PEMANDU (2010) Economic transformation programme: A roadmap for Malaysia. Available at: http://etp.pemandu.gov.my/download_centre.aspx (accessed 22 August 2016).

41.

Pesaran

Shin

(1998) Generalized impulse response analysis in linear multivariate models. Economics Letters 58(1): 17–29.

42.

Pesaran

Shin

Smith

(2001) Bounds testing approaches to the analysis of level relationship. Journal of Applied Econometrics 16(3): 289–326.

43.

Pocock

Phua

(2011) Medical tourism and policy implications for health systems: A conceptual framework from a comparative study of Thailand, Singapore and Malaysia. Globalisation and Health 7(12): 1–12.

44.

Poon

(2008) Malaysian Economy, 2nd ed. Petaling Jaya: Prentice Hall.

45.

Ramesh

Xun

(2008) Realigning public and private health care in Southeast Asia. The Pacific Review 21(2): 171–187.

46.

Ramírez de Arellano

(2007) Patients without borders: The emergence of medical tourism. International Journal of Health Services 37(1): 193–198.

47.

Smith

Chanda

Tangcharoensathien

(2009) Trade in health-related services. Lancet 373(9663): 593–601.

48.

Tang

Abosedra

(2016) Tourism and growth in Lebanon: New evidence from bootstrap simulation and rolling causality approaches. Empirical Economics 50(2): 679–696.

49.

Tang

Tan

(2013) How stable is the tourism-led growth hypothesis in Malaysia? A view from disaggregated tourism markets. Tourism Management 37: 52–57.

50.

Tang

Tan

(2015a) Does tourism effectively stimulate Malaysia’s economic growth? Tourism Management 46: 158–163.

51.

Tang

Tan

(2015b) Tourism-led growth hypothesis in Malaysia: Evidence based upon regime shift cointegration and time-varying Granger causality techniques. Asia Pacific Journal of Tourism Research 20(S1): 1430–1450.

52.

Tang

Tiwari

Shahbaz

(2016) Dynamic inter-relationships among tourism, economic growth and energy consumption in India. Geosystem Engineering 19(4): 158–169.

53.

Thano

(2015) The impact of tourism on the balance of payments. American Journal of Economics and Finance Management 1(5): 529–536.

54.

Tobin

(1964) Economic growth as an objective of government policy. American Economic Review 54(3): 1–20.

55.

United Nations Conference on Trade and Development (2013) Sustainable tourism: Contribution to economic growth and sustainable development. In: Proceedings of the Single-Year Expert Meeting on Tourism's Contribution to Sustainable Development, Geneva, Palais des Nations, Salle XXVI, 14–15 March 2013 (pp. 1–20).

56.

United Nations Economic and Social Commission for Asia and the Pacific (2007) Medical travel in Asia and the Pacific: Challenges and opportunities. Available at: www.unescap.org/ESID/hds/lastestadd/MedicalTourismReport09.pdf (accessed 13 July 2015).

57.

World Travel and Tourism Council (2015) Travel and tourism: Economic impact 2015 Malaysia. Available at: www.wttc.org/-/media/ﬁles/reports/economic impact research/countries 2015/malaysia2015.pdf (accessed 28 August 2016).

58.

Yeoh

Othman

Ahmad

(2013) Understanding medical tourists: Word-of-mouth and viral marketing as potent marketing tools. Tourism Management 34: 196–201.