The aim of this paper is to explore the international tourism demand-renewable energy consumption-intra-regional trade nexus across seven South Asian economies. The Emirmahmutoglu–Kose and Dumitrescu–Hurlin causality test results reveal unidirectional causalities stemming from tourist influx and intra-regional trade to renewable energy consumption. Moreover, bidirectional causality is found between tourism demand and regional trade. Thus, these results are anticipated to generate key policy implications

Murshed, Muntasir

English

Munich Personal RePEc Archive

Munich Personal RePEc Archive
Regional Integration, International
Tourism Demand and Renewable Energy
Transition: Evidence from selected South
Asia Economies
Murshed, Muntasir
North South University
2019
Online at https://mpra.ub.uni-muenchen.de/98095/
MPRA Paper No. 98095, posted 13 Jan 2020 03:48 UTC
Regional Integration, International Tourism Demand and 
Renewable Energy Transition: Evidence from selected 
South Asia Economies 
 
Muntasir Murshed 
School of Business and Economics, North South University, Bangladesh 
Email: muntasir.murshed@northsouth.edu 
 
Abstract 
The aim of this paper is to explore the international tourism demand-
renewable energy consumption-intra-regional trade nexus across seven 
South Asian economies. The Emirmahmutoglu–Kose and Dumitrescu–
Hurlin causality test results reveal unidirectional causalities stemming 
from tourist influx and intra-regional trade to renewable energy 
consumption. Moreover, bidirectional causality is found between tourism 
demand and regional trade. Thus, these results are anticipated to generate 
key policy implications.   
Keywords: tourism demand, renewable energy transition 
 
1. Introduction 
The volume of international tourist flows across the globe has surged over time. 
As a result, the factors affecting the international tourism demand have 
attracted attention amidst researchers (Peng et al. 2015). Moreover, growth in 
tourism demand is believed to trigger power consumption through both the 
direct and indirect channels (Lee 2013). Hence, sustainability of international 
tourism influx can largely be attributed to the reliability of power supply as 
well. In the same vein, insufficient access to in-grid electrification is often 
claimed to be the key constraint bottlenecking the growth of tourism demand, 
both within the national and international spheres. Thus, underscoring the 
necessity of enhancing the off-grid electrification rates across the tourist 
destinations, that do not have adequate access to the national grid, 
incorporation of renewable energy resources for off-grid power generation 
purposes seems to be a plausible policy move that entails government 
interventions (Shezan et al. 2015). 
On the other hand, enhancing the share of renewables in total electricity 
outputs is often attributed to cross-border power trade, following the 
indigenous constraints in the form of natural endowment of renewable energy 
resources (Amin and Murshed 2016). In this regard, liberalization of trade 
barriers has often been recommended as a means to initiate a transition from 
non-renewable to renewable energy use (Murshed 2018). Trade liberalization 
policies complement renewable energy sector development within the low-
income countries in particular (Murshed 2019). 
 
Although a plethora of studies have explored the multifaceted 
determinants of international tourism demand, the roles of renewable energy 
adoption and cross-border trade of renewable sources of power have received 
nominal attention in the existing narrative. Thus, this paper aims to bridge this 
gap in literature by empirically investigating the causal nexus between tourist 
arrivals, renewable energy consumption and intra-regional trade across seven 
South Asian economies, namely Bangladesh, India, Pakistan, Sri Lanka, Nepal, 
Maldives and Bhutan.i 
This study is pertinent from the perspective of policy implications with 
respect to attaining international tourism growth across the South Asia and, at 
the same time, enhancing cross-border trade of power to curtail the indigenous 
reliance on the non-renewable fossil fuels for generating power. The growth in 
international tourist arrivals across South Asia has increased by almost 6-folds 
between 1995 and 2017, while South Asia’s share in the global tourist arrival 
figures rose by more than 2.3 times (World Bank 2019). These statistics indicate 
that South Asia is gaining global recognition as one of the emerging tourism 
destinations. On the other hand, the share of renewables in total energy-use 
within South Asian has predominantly been below par, with Nepal being the 
only exception (World Bank 2019). This is a concerning issue keeping South 
Asia’s energy security and environmental sustainability into cognizance. Hence, 
it can be hypothesized that the causal associations between international 
tourism demand, renewable energy use and intra-regional trade could impose 
critically policy implications in this regard. 
2. Methodology and Dataset 
This study employs a simple linear model in which international tourist arrival 
is expressed as a function of renewable energy consumption, intra-regional 
trade participation and other control variables:                                                (1) 
 where the subscript t refers to the corresponding time period and U 
represents the error term; TA denotes the number international tourist arrivals 
which is used to measure the degree of tourism demand; RES refers to the 
renewable energy share in total energy consumption, used as a proxy for 
understanding the propensity of renewable energy consumption; and IRTS 
symbolizes the intra-regional trade share of respective nations in the aggregate 
level of South Asian trade, in order to account for the state of regional 
integration. GDPPC and INF are per capita GDP (in terms of PPP 2011 constant 
US dollars) and domestic inflation rate (proxied by the consumer price index), 
respectively, controlling the econometric model.  
 The variables, where appropriate, are converted to their natural 
logarithms. This study uses annual data stemming across 2000 and 2015 in the 
context of all the seven South Asian economies. The data for IRTS has been 
sourced from the Asia Regional Integration Center database of the Asian 
Development Bank while data for all other variables are compiled from the 
World Development Indicators database maintained by the World Bank.   
 As part of the econometric methodology, the data set is firstly tested for 
cross-sectional dependence among the panels using the Breusch-Pagan (1980) 
Lagrange Multiplier test for cross-sectional dependence, suited for panel data 
sets with small number of cross sections and larger time periods. Table 1 (see 
appendix) reports the results from the cross-sectional dependency analysis 
which provides statistical support in favor of the panels being cross-sectionally 
dependent. Presence of cross-sectional dependence lead to spurious stationarity 
properties whereby second generation unit root tests are used to account for the 
limitation of the first generation tests. The stationarity analyses are done 
tapping the Cointegrated Augmented Dickey-Fuller (CADF) and Cross-
Sectional Augmented Im-Pesaran-Shin (CIPS) techniques proposed by Pesaran 
(2007). The long run cointegrating associations between the variables are 
estimated using the Westerlund (2005) cointegration method. Finally, the causal 
linkages are assessed using the recently developed Emirmahmutoglu–Kose and 
Dumitrescu–Hurlin tests proposed by Emirmahmutoglu and Kose (2011) and 
Dumitrescu and Hurlin (2012), respectively. Both these techniques are affirmed 
to handle cross-sectionally dependent panel data sets in contrast to the 
conventional Granger causality test. 
 
3. Results and Discussion 
The results from the CADF and CIPS unit root tests, as reported in table 2, 
reveal that all the variables are non-stationary at their level forms while they 
become stationary at their first differences, implying a common order of 
integration.   
Table 3 outlines the Westerlund cointegration test results which provide 
statistical evidence regarding the presence of cointegrating relationships 
between the variables included in the econometric model.   
 
Finally, the causality results are presented in table 4. The statistical 
estimates from both the techniques coincide to conform the robustness of the 
results across different causality-testing methodologies. The estimates indicate 
that international tourism demand influences the renewable energy 
consumption across South Asia, as perceived from the unidirectional causal link 
stemming from international tourist arrivals to renewable energy share in total 
energy consumption levels. This implies that influx of foreign tourist does exert 
pressures on demand for power, which tend to be met through incorporation of 
renewable energy resources for power generation purposes. From this finding, 
it can be partially claimed that renewable energy resources could be ensuring 
off-grid electrification within the remote tourist destinations across South Asia. 
 
Moreover, a feedback causal association is found between international 
tourist arrivals and intra-regional trade shares which denotes that not only does 
greater regional trade cater the pre-requisite of adequate power supply for 
attracting foreign tourists to travel to South Asia, greater influx of international 
tourists also tends to facilitate trade between the neighboring countries. This 
assumption of intra-regional trade influencing energy supply across the South 
Asian region is affirmed by the statistical evidence of unidirectional causation 
stemming from IRTS to RES. This could be perceived as an indication of cross-
border energy trade taking place between the concerned economies which, in 
turn, appears to be playing a fruitful role in uplifting the overall share of 
renewables in total energy consumption across South Asia. Thus, it is ideal for 
the governments to liberalize intra-regional trade barriers to ease the cross-
border flows of energy resources which would ultimately escalate the overall 
tourism demand across this region.  
 
4. Conclusion 
The roles of renewable energy consumption and intra-regional trade with 
regard to enhancing international tourism demand have received nominal 
attention in the existing literature. Against this milieu, this paper attempted to 
empirically bridge this gap in the context of seven South Asian economies. The 
results broadly point out towards the inter-linkages between these three 
aforementioned macroeconomic aggregates. The causal estimates revealed 
unidirectional causality running from international tourist arrivals and intra-
regional trade to renewable energy share in total energy, while a bidirectional 
causal relationship was found between international tourism demand and 
intra-regional trade. Thus, these findings collectively impose crucial policy 
implications with respect to expanding the tourism industry, facilitating the 
non-renewable to renewable energy transition and strengthening the intra-
regional trade relationships across South Asia.  
It can be assured that implementing appropriate policy measures, 
keeping these causal estimates into cognizance, could ideally empower the 
South Asian economies in pursuing their commitment to attain the targets 
under the Sustainable Development Goals (SDG) of the 2030 agenda of the 
United Nations; especially SDG 7 which aims to ensure energy security across 
the globe through greater use of renewable energy resources and SDG 17 which 
call for building global partnerships and cooperation for sustainable 
development as a whole.   
 
References 
Amin, S. B., & Murshed, M. (2016). The economies of cross-border 
electricity trading in Bangladesh. Prospects & Challenges of Connectivity & 
Trading in Power & Energy: A Regional & International Perspective, 1, 119-128. 
Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its 
applications to model specification in econometrics. The review of economic 
studies, 47(1), 239-253. 
Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality 
in heterogeneous panels. Economic modelling, 29(4), 1450-1460. 
Emirmahmutoglu, F., & Kose, N. (2011). Testing for Granger causality in 
heterogeneous mixed panels. Economic Modelling, 28(3), 870-876. 
Lee, C. G. (2013). Electricity consumption and international tourism: The 
case of Singapore. Anatolia, 24(1), 91-94.   
Murshed, M. (2018). Does improvement in trade openness facilitate 
renewable energy transition? Evidence from selected South Asian economies. 
South Asia Economic Journal, 19(2), 151-170. 
Murshed, M. (2019). Are Trade Liberalization policies aligned with 
Renewable Energy Transition in low and middle income countries? An 
Instrumental Variable approach. Renewable Energy. DOI: 
10.1016/j.renene.2019.11.106 
Peng, B., Song, H., Crouch, G. I., & Witt, S. F. (2015). A meta-analysis of 
international tourism demand elasticities. Journal of Travel Research, 54(5), 611-
633. 
Pesaran, M. H. (2007). A simple panel unit root test in the presence of 
cross‐section dependence. Journal of applied econometrics, 22(2), 265-312. 
Shezan, S. A., Saidur, R., Ullah, K. R., Hossain, A., Chong, W. T., & Julai, 
S. (2015). Feasibility analysis of a hybrid off-grid wind–DG-battery energy 
system for the eco-tourism remote areas. Clean Technologies and 
Environmental Policy, 17(8), 2417-2430. 
Westerlund, J. (2005). New simple tests for panel cointegration. 
Econometric Reviews, 24(3), 297-316. 
World Bank. (2019). World Development Indicators database. World 
Bank.  
 
Appendix 
Table 1: Breusch-Pagan Lagrange Multiplier Cross-Sectional Dependence test 
results 
lnTAt RESt IRTSt lnGDPPCt INFt 
62.272* 69.591* 58.623* 43.183** 62.809* 
Note: * & ** denote statistical significance at 1% and 5%, respectively.  
  
 
 
 
 
 
 
Table 2: Panel Unit Root Test Results 
Test CADF CIPS 
Variable Level                  Level                    
lnTAt -1.699 -2.614** -1.861 -4.011* 
RESt -1.181 -2.413** -1.325 -4.436 
IRTSt -1.021 -2.662** -1.226 -3.298* 
lnGDPPCt -1.822 -2.682** -2.121 -3.318* 
INFt -1.007 -3.818* -1.666 -3.589* 
Note: Considering trend and intercept; The optimal lag selection is based on the Akaike 
Information Criterion (AIC); * & ** denote statistical significance at 1% and 5%, 
respectively. 
 
Table 3: Westerlund panel cointegration test results 
Statistic  Value 
Gt -2.345* 
Ga -9.600 
Pt -22.561* 
Pa -10.778* 
Note: Considering trend and intercept; The optimal lag selection is based on the AIC; * & ** 
denote statistical significance of the critical values, under the null hypothesis on non 
cointegration, at 1% and 5%, respectively. 
 
Table 4: Panel Granger causality test results 
Dependent 
Variable 
Independent 
Variable 
Emirmahmutoglu
–Kose 
Dumitrescu–
Hurlin 
lnTAt RESt 50.51 -0.649 
RESt lnTAt 77.691* 3.618* 
lnTAt IRTSt 75.219* 2.102** 
IRTSt lnTAt 64.52*** 5.689* 
lnTAt lnGDPPCt 159.768* 1.721*** 
lnGDPPCt lnTAt 48.223 0.182 
lnTAt INFt 52.171 -0.247 
INFt lnTAt 50.682 -0.050 
IRTSt RESt 51.314 0.201 
RESt IRTSt 78.898* 2.281** 
Note: The optimal lag selection is based on the AIC; *, ** & *** denote statistical significance 
at 1% , 5% & 10%, respectively. 
                                                 
i
 The choice of the South Asian countries was based on data availability which resulted in 
exclusion of Afghanistan.   


Regional Integration, International Tourism Demand and Renewable Energy Transition: Evidence from selected South Asia Economies

Munich RePEc Personal Archive

Munich Personal RePEc ArchiveRegional Integration, InternationalTourism Demand and Renewable EnergyTransition: Evidence from selected SouthAsia EconomiesMurshed, MuntasirNorth South University2019Online at https://mpra.ub.uni-muenchen.de/98117/MPRA Paper No. 98117, posted 16 Jan 2020 08:51 UTCRegional Integration, International Tourism Demand and Renewable Energy Transition: Evidence from selected South Asia Economies  Muntasir Murshed School of Business and Economics, North South University, Bangladesh Email: muntasir.murshed@northsouth.edu  Abstract The aim of this paper is to explore the international tourism demand-renewable energy consumption-intra-regional trade nexus across seven South Asian economies. The Emirmahmutoglu–Kose and Dumitrescu–Hurlin causality test results reveal unidirectional causalities stemming from tourist influx and intra-regional trade to renewable energy consumption. Moreover, bidirectional causality is found between tourism demand and regional trade. Thus, these results are anticipated to generate key policy implications.   Keywords: tourism demand, renewable energy transition  1. Introduction The volume of international tourist flows across the globe has surged over time. As a result, the factors affecting the international tourism demand have attracted attention amidst researchers (Peng et al. 2015). Moreover, growth in tourism demand is believed to trigger power consumption through both the direct and indirect channels (Lee 2013). Hence, sustainability of international tourism influx can largely be attributed to the reliability of power supply as well. In the same vein, insufficient access to in-grid electrification is often claimed to be the key constraint bottlenecking the growth of tourism demand, both within the national and international spheres. Thus, underscoring the necessity of enhancing the off-grid electrification rates across the tourist destinations, that do not have adequate access to the national grid, incorporation of renewable energy resources for off-grid power generation purposes seems to be a plausible policy move that entails government interventions (Shezan et al. 2015). On the other hand, enhancing the share of renewables in total electricity outputs is often attributed to cross-border power trade, following the indigenous constraints in the form of natural endowment of renewable energy resources (Amin and Murshed 2016). In this regard, liberalization of trade barriers has often been recommended as a means to initiate a transition from non-renewable to renewable energy use (Murshed 2018). Trade liberalization policies complement renewable energy sector development within the low-income countries in particular (Murshed 2019).  Although a plethora of studies have explored the multifaceted determinants of international tourism demand, the roles of renewable energy adoption and cross-border trade of renewable sources of power have received nominal attention in the existing narrative. Thus, this paper aims to bridge this gap in literature by empirically investigating the causal nexus between tourist arrivals, renewable energy consumption and intra-regional trade across seven South Asian economies, namely Bangladesh, India, Pakistan, Sri Lanka, Nepal, Maldives and Bhutan.i This study is pertinent from the perspective of policy implications with respect to attaining international tourism growth across the South Asia and, at the same time, enhancing cross-border trade of power to curtail the indigenous reliance on the non-renewable fossil fuels for generating power. The growth in international tourist arrivals across South Asia has increased by almost 6-folds between 1995 and 2017, while South Asia’s share in the global tourist arrival figures rose by more than 2.3 times (World Bank 2019). These statistics indicate that South Asia is gaining global recognition as one of the emerging tourism destinations. On the other hand, the share of renewables in total energy-use within South Asian has predominantly been below par, with Nepal being the only exception (World Bank 2019). This is a concerning issue keeping South Asia’s energy security and environmental sustainability into cognizance. Hence, it can be hypothesized that the causal associations between international tourism demand, renewable energy use and intra-regional trade could impose critically policy implications in this regard. 2. Methodology and Dataset This study employs a simple linear model in which international tourist arrival is expressed as a function of renewable energy consumption, intra-regional trade participation and other control variables:                                                (1)  where the subscript t refers to the corresponding time period and U represents the error term; TA denotes the number international tourist arrivals which is used to measure the degree of tourism demand; RES refers to the renewable energy share in total energy consumption, used as a proxy for understanding the propensity of renewable energy consumption; and IRTS symbolizes the intra-regional trade share of respective nations in the aggregate level of South Asian trade, in order to account for the state of regional integration. GDPPC and INF are per capita GDP (in terms of PPP 2011 constant US dollars) and domestic inflation rate (proxied by the consumer price index), respectively, controlling the econometric model.   The variables, where appropriate, are converted to their natural logarithms. This study uses annual data stemming across 2000 and 2015 in the context of all the seven South Asian economies. The data for IRTS has been sourced from the Asia Regional Integration Center database of the Asian Development Bank while data for all other variables are compiled from the World Development Indicators database maintained by the World Bank.    As part of the econometric methodology, the data set is firstly tested for cross-sectional dependence among the panels using the Breusch-Pagan (1980) Lagrange Multiplier test for cross-sectional dependence, suited for panel data sets with small number of cross sections and larger time periods. Table 1 (see appendix) reports the results from the cross-sectional dependency analysis which provides statistical support in favor of the panels being cross-sectionally dependent. Presence of cross-sectional dependence lead to spurious stationarity properties whereby second generation unit root tests are used to account for the limitation of the first generation tests. The stationarity analyses are done tapping the Cointegrated Augmented Dickey-Fuller (CADF) and Cross-Sectional Augmented Im-Pesaran-Shin (CIPS) techniques proposed by Pesaran (2007). The long run cointegrating associations between the variables are estimated using the Westerlund (2005) cointegration method. Finally, the causal linkages are assessed using the recently developed Emirmahmutoglu–Kose and Dumitrescu–Hurlin tests proposed by Emirmahmutoglu and Kose (2011) and Dumitrescu and Hurlin (2012), respectively. Both these techniques are affirmed to handle cross-sectionally dependent panel data sets in contrast to the conventional Granger causality test.  3. Results and Discussion The results from the CADF and CIPS unit root tests, as reported in table 2, reveal that all the variables are non-stationary at their level forms while they become stationary at their first differences, implying a common order of integration.   Table 3 outlines the Westerlund cointegration test results which provide statistical evidence regarding the presence of cointegrating relationships between the variables included in the econometric model.    Finally, the causality results are presented in table 4. The statistical estimates from both the techniques coincide to conform the robustness of the results across different causality-testing methodologies. The estimates indicate that international tourism demand influences the renewable energy consumption across South Asia, as perceived from the unidirectional causal link stemming from international tourist arrivals to renewable energy share in total energy consumption levels. This implies that influx of foreign tourist does exert pressures on demand for power, which tend to be met through incorporation of renewable energy resources for power generation purposes. From this finding, it can be partially claimed that renewable energy resources could be ensuring off-grid electrification within the remote tourist destinations across South Asia.  Moreover, a feedback causal association is found between international tourist arrivals and intra-regional trade shares which denotes that not only does greater regional trade cater the pre-requisite of adequate power supply for attracting foreign tourists to travel to South Asia, greater influx of international tourists also tends to facilitate trade between the neighboring countries. This assumption of intra-regional trade influencing energy supply across the South Asian region is affirmed by the statistical evidence of unidirectional causation stemming from IRTS to RES. This could be perceived as an indication of cross-border energy trade taking place between the concerned economies which, in turn, appears to be playing a fruitful role in uplifting the overall share of renewables in total energy consumption across South Asia. Thus, it is ideal for the governments to liberalize intra-regional trade barriers to ease the cross-border flows of energy resources which would ultimately escalate the overall tourism demand across this region.   4. Conclusion The roles of renewable energy consumption and intra-regional trade with regard to enhancing international tourism demand have received nominal attention in the existing literature. Against this milieu, this paper attempted to empirically bridge this gap in the context of seven South Asian economies. The results broadly point out towards the inter-linkages between these three aforementioned macroeconomic aggregates. The causal estimates revealed unidirectional causality running from international tourist arrivals and intra-regional trade to renewable energy share in total energy, while a bidirectional causal relationship was found between international tourism demand and intra-regional trade. Thus, these findings collectively impose crucial policy implications with respect to expanding the tourism industry, facilitating the non-renewable to renewable energy transition and strengthening the intra-regional trade relationships across South Asia.  It can be assured that implementing appropriate policy measures, keeping these causal estimates into cognizance, could ideally empower the South Asian economies in pursuing their commitment to attain the targets under the Sustainable Development Goals (SDG) of the 2030 agenda of the United Nations; especially SDG 7 which aims to ensure energy security across the globe through greater use of renewable energy resources and SDG 17 which call for building global partnerships and cooperation for sustainable development as a whole.    References Amin, S. B., & Murshed, M. (2016). The economies of cross-border electricity trading in Bangladesh. Prospects & Challenges of Connectivity & Trading in Power & Energy: A Regional & International Perspective, 1, 119-128. Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The review of economic studies, 47(1), 239-253. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460. Emirmahmutoglu, F., & Kose, N. (2011). Testing for Granger causality in heterogeneous mixed panels. Economic Modelling, 28(3), 870-876. Lee, C. G. (2013). Electricity consumption and international tourism: The case of Singapore. Anatolia, 24(1), 91-94.   Murshed, M. (2018). Does improvement in trade openness facilitate renewable energy transition? Evidence from selected South Asian economies. South Asia Economic Journal, 19(2), 151-170. Murshed, M. (2019). Are Trade Liberalization policies aligned with Renewable Energy Transition in low and middle income countries? An Instrumental Variable approach. Renewable Energy. DOI: 10.1016/j.renene.2019.11.106 Peng, B., Song, H., Crouch, G. I., & Witt, S. F. (2015). A meta-analysis of international tourism demand elasticities. Journal of Travel Research, 54(5), 611-633. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of applied econometrics, 22(2), 265-312. Shezan, S. A., Saidur, R., Ullah, K. R., Hossain, A., Chong, W. T., & Julai, S. (2015). Feasibility analysis of a hybrid off-grid wind–DG-battery energy system for the eco-tourism remote areas. Clean Technologies and Environmental Policy, 17(8), 2417-2430. Westerlund, J. (2005). New simple tests for panel cointegration. Econometric Reviews, 24(3), 297-316. World Bank. (2019). World Development Indicators database. World Bank.   Appendix Table 1: Breusch-Pagan Lagrange Multiplier Cross-Sectional Dependence test results lnTAt RESt IRTSt lnGDPPCt INFt 62.272* 69.591* 58.623* 43.183** 62.809* Note: * & ** denote statistical significance at 1% and 5%, respectively.          Table 2: Panel Unit Root Test Results Test CADF CIPS Variable Level                  Level                    lnTAt -1.699 -2.614** -1.861 -4.011* RESt -1.181 -2.413** -1.325 -4.436 IRTSt -1.021 -2.662** -1.226 -3.298* lnGDPPCt -1.822 -2.682** -2.121 -3.318* INFt -1.007 -3.818* -1.666 -3.589* Note: Considering trend and intercept; The optimal lag selection is based on the Akaike Information Criterion (AIC); * & ** denote statistical significance at 1% and 5%, respectively.  Table 3: Westerlund panel cointegration test results Statistic  Value Gt -2.345* Ga -9.600 Pt -22.561* Pa -10.778* Note: Considering trend and intercept; The optimal lag selection is based on the AIC; * & ** denote statistical significance of the critical values, under the null hypothesis on non cointegration, at 1% and 5%, respectively.  Table 4: Panel Granger causality test results Dependent Variable Independent Variable Emirmahmutoglu–Kose Dumitrescu–Hurlin lnTAt RESt 50.51 -0.649 RESt lnTAt 77.691* 3.618* lnTAt IRTSt 75.219* 2.102** IRTSt lnTAt 64.52*** 5.689* lnTAt lnGDPPCt 159.768* 1.721*** lnGDPPCt lnTAt 48.223 0.182 lnTAt INFt 52.171 -0.247 INFt lnTAt 50.682 -0.050 IRTSt RESt 51.314 0.201 RESt IRTSt 78.898* 2.281** Note: The optimal lag selection is based on the AIC; *, ** & *** denote statistical significance at 1% , 5% & 10%, respectively.                                                  i The choice of the South Asian countries was based on data availability which resulted in exclusion of Afghanistan.   

Munich Personal RePEc Archive
Regional Integration, International
Tourism Demand and Renewable Energy
Transition: Evidence from selected South
Asia Economies
Murshed, Muntasir
North South University
2019
Online at https://mpra.ub.uni-muenchen.de/98117/
MPRA Paper No. 98117, posted 16 Jan 2020 08:51 UTC
Regional Integration, International Tourism Demand and 
Renewable Energy Transition: Evidence from selected 
South Asia Economies 
 
Muntasir Murshed 
School of Business and Economics, North South University, Bangladesh 
Email: muntasir.murshed@northsouth.edu 
 
Abstract 
The aim of this paper is to explore the international tourism demand-
renewable energy consumption-intra-regional trade nexus across seven 
South Asian economies. The Emirmahmutoglu–Kose and Dumitrescu–
Hurlin causality test results reveal unidirectional causalities stemming 
from tourist influx and intra-regional trade to renewable energy 
consumption. Moreover, bidirectional causality is found between tourism 
demand and regional trade. Thus, these results are anticipated to generate 
key policy implications.   
Keywords: tourism demand, renewable energy transition 
 
1. Introduction 
The volume of international tourist flows across the globe has surged over time. 
As a result, the factors affecting the international tourism demand have 
attracted attention amidst researchers (Peng et al. 2015). Moreover, growth in 
tourism demand is believed to trigger power consumption through both the 
direct and indirect channels (Lee 2013). Hence, sustainability of international 
tourism influx can largely be attributed to the reliability of power supply as 
well. In the same vein, insufficient access to in-grid electrification is often 
claimed to be the key constraint bottlenecking the growth of tourism demand, 
both within the national and international spheres. Thus, underscoring the 
necessity of enhancing the off-grid electrification rates across the tourist 
destinations, that do not have adequate access to the national grid, 
incorporation of renewable energy resources for off-grid power generation 
purposes seems to be a plausible policy move that entails government 
interventions (Shezan et al. 2015). 
On the other hand, enhancing the share of renewables in total electricity 
outputs is often attributed to cross-border power trade, following the 
indigenous constraints in the form of natural endowment of renewable energy 
resources (Amin and Murshed 2016). In this regard, liberalization of trade 
barriers has often been recommended as a means to initiate a transition from 
non-renewable to renewable energy use (Murshed 2018). Trade liberalization 
policies complement renewable energy sector development within the low-
income countries in particular (Murshed 2019). 
 
Although a plethora of studies have explored the multifaceted 
determinants of international tourism demand, the roles of renewable energy 
adoption and cross-border trade of renewable sources of power have received 
nominal attention in the existing narrative. Thus, this paper aims to bridge this 
gap in literature by empirically investigating the causal nexus between tourist 
arrivals, renewable energy consumption and intra-regional trade across seven 
South Asian economies, namely Bangladesh, India, Pakistan, Sri Lanka, Nepal, 
Maldives and Bhutan.i 
This study is pertinent from the perspective of policy implications with 
respect to attaining international tourism growth across the South Asia and, at 
the same time, enhancing cross-border trade of power to curtail the indigenous 
reliance on the non-renewable fossil fuels for generating power. The growth in 
international tourist arrivals across South Asia has increased by almost 6-folds 
between 1995 and 2017, while South Asia’s share in the global tourist arrival 
figures rose by more than 2.3 times (World Bank 2019). These statistics indicate 
that South Asia is gaining global recognition as one of the emerging tourism 
destinations. On the other hand, the share of renewables in total energy-use 
within South Asian has predominantly been below par, with Nepal being the 
only exception (World Bank 2019). This is a concerning issue keeping South 
Asia’s energy security and environmental sustainability into cognizance. Hence, 
it can be hypothesized that the causal associations between international 
tourism demand, renewable energy use and intra-regional trade could impose 
critically policy implications in this regard. 
2. Methodology and Dataset 
This study employs a simple linear model in which international tourist arrival 
is expressed as a function of renewable energy consumption, intra-regional 
trade participation and other control variables:                                                (1) 
 where the subscript t refers to the corresponding time period and U 
represents the error term; TA denotes the number international tourist arrivals 
which is used to measure the degree of tourism demand; RES refers to the 
renewable energy share in total energy consumption, used as a proxy for 
understanding the propensity of renewable energy consumption; and IRTS 
symbolizes the intra-regional trade share of respective nations in the aggregate 
level of South Asian trade, in order to account for the state of regional 
integration. GDPPC and INF are per capita GDP (in terms of PPP 2011 constant 
US dollars) and domestic inflation rate (proxied by the consumer price index), 
respectively, controlling the econometric model.  
 The variables, where appropriate, are converted to their natural 
logarithms. This study uses annual data stemming across 2000 and 2015 in the 
context of all the seven South Asian economies. The data for IRTS has been 
sourced from the Asia Regional Integration Center database of the Asian 
Development Bank while data for all other variables are compiled from the 
World Development Indicators database maintained by the World Bank.   
 As part of the econometric methodology, the data set is firstly tested for 
cross-sectional dependence among the panels using the Breusch-Pagan (1980) 
Lagrange Multiplier test for cross-sectional dependence, suited for panel data 
sets with small number of cross sections and larger time periods. Table 1 (see 
appendix) reports the results from the cross-sectional dependency analysis 
which provides statistical support in favor of the panels being cross-sectionally 
dependent. Presence of cross-sectional dependence lead to spurious stationarity 
properties whereby second generation unit root tests are used to account for the 
limitation of the first generation tests. The stationarity analyses are done 
tapping the Cointegrated Augmented Dickey-Fuller (CADF) and Cross-
Sectional Augmented Im-Pesaran-Shin (CIPS) techniques proposed by Pesaran 
(2007). The long run cointegrating associations between the variables are 
estimated using the Westerlund (2005) cointegration method. Finally, the causal 
linkages are assessed using the recently developed Emirmahmutoglu–Kose and 
Dumitrescu–Hurlin tests proposed by Emirmahmutoglu and Kose (2011) and 
Dumitrescu and Hurlin (2012), respectively. Both these techniques are affirmed 
to handle cross-sectionally dependent panel data sets in contrast to the 
conventional Granger causality test. 
 
3. Results and Discussion 
The results from the CADF and CIPS unit root tests, as reported in table 2, 
reveal that all the variables are non-stationary at their level forms while they 
become stationary at their first differences, implying a common order of 
integration.   
Table 3 outlines the Westerlund cointegration test results which provide 
statistical evidence regarding the presence of cointegrating relationships 
between the variables included in the econometric model.   
 
Finally, the causality results are presented in table 4. The statistical 
estimates from both the techniques coincide to conform the robustness of the 
results across different causality-testing methodologies. The estimates indicate 
that international tourism demand influences the renewable energy 
consumption across South Asia, as perceived from the unidirectional causal link 
stemming from international tourist arrivals to renewable energy share in total 
energy consumption levels. This implies that influx of foreign tourist does exert 
pressures on demand for power, which tend to be met through incorporation of 
renewable energy resources for power generation purposes. From this finding, 
it can be partially claimed that renewable energy resources could be ensuring 
off-grid electrification within the remote tourist destinations across South Asia. 
 
Moreover, a feedback causal association is found between international 
tourist arrivals and intra-regional trade shares which denotes that not only does 
greater regional trade cater the pre-requisite of adequate power supply for 
attracting foreign tourists to travel to South Asia, greater influx of international 
tourists also tends to facilitate trade between the neighboring countries. This 
assumption of intra-regional trade influencing energy supply across the South 
Asian region is affirmed by the statistical evidence of unidirectional causation 
stemming from IRTS to RES. This could be perceived as an indication of cross-
border energy trade taking place between the concerned economies which, in 
turn, appears to be playing a fruitful role in uplifting the overall share of 
renewables in total energy consumption across South Asia. Thus, it is ideal for 
the governments to liberalize intra-regional trade barriers to ease the cross-
border flows of energy resources which would ultimately escalate the overall 
tourism demand across this region.  
 
4. Conclusion 
The roles of renewable energy consumption and intra-regional trade with 
regard to enhancing international tourism demand have received nominal 
attention in the existing literature. Against this milieu, this paper attempted to 
empirically bridge this gap in the context of seven South Asian economies. The 
results broadly point out towards the inter-linkages between these three 
aforementioned macroeconomic aggregates. The causal estimates revealed 
unidirectional causality running from international tourist arrivals and intra-
regional trade to renewable energy share in total energy, while a bidirectional 
causal relationship was found between international tourism demand and 
intra-regional trade. Thus, these findings collectively impose crucial policy 
implications with respect to expanding the tourism industry, facilitating the 
non-renewable to renewable energy transition and strengthening the intra-
regional trade relationships across South Asia.  
It can be assured that implementing appropriate policy measures, 
keeping these causal estimates into cognizance, could ideally empower the 
South Asian economies in pursuing their commitment to attain the targets 
under the Sustainable Development Goals (SDG) of the 2030 agenda of the 
United Nations; especially SDG 7 which aims to ensure energy security across 
the globe through greater use of renewable energy resources and SDG 17 which 
call for building global partnerships and cooperation for sustainable 
development as a whole.   
 
References 
Amin, S. B., & Murshed, M. (2016). The economies of cross-border 
electricity trading in Bangladesh. Prospects & Challenges of Connectivity & 
Trading in Power & Energy: A Regional & International Perspective, 1, 119-128. 
Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its 
applications to model specification in econometrics. The review of economic 
studies, 47(1), 239-253. 
Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality 
in heterogeneous panels. Economic modelling, 29(4), 1450-1460. 
Emirmahmutoglu, F., & Kose, N. (2011). Testing for Granger causality in 
heterogeneous mixed panels. Economic Modelling, 28(3), 870-876. 
Lee, C. G. (2013). Electricity consumption and international tourism: The 
case of Singapore. Anatolia, 24(1), 91-94.   
Murshed, M. (2018). Does improvement in trade openness facilitate 
renewable energy transition? Evidence from selected South Asian economies. 
South Asia Economic Journal, 19(2), 151-170. 
Murshed, M. (2019). Are Trade Liberalization policies aligned with 
Renewable Energy Transition in low and middle income countries? An 
Instrumental Variable approach. Renewable Energy. DOI: 
10.1016/j.renene.2019.11.106 
Peng, B., Song, H., Crouch, G. I., & Witt, S. F. (2015). A meta-analysis of 
international tourism demand elasticities. Journal of Travel Research, 54(5), 611-
633. 
Pesaran, M. H. (2007). A simple panel unit root test in the presence of 
cross‐section dependence. Journal of applied econometrics, 22(2), 265-312. 
Shezan, S. A., Saidur, R., Ullah, K. R., Hossain, A., Chong, W. T., & Julai, 
S. (2015). Feasibility analysis of a hybrid off-grid wind–DG-battery energy 
system for the eco-tourism remote areas. Clean Technologies and 
Environmental Policy, 17(8), 2417-2430. 
Westerlund, J. (2005). New simple tests for panel cointegration. 
Econometric Reviews, 24(3), 297-316. 
World Bank. (2019). World Development Indicators database. World 
Bank.  
 
Appendix 
Table 1: Breusch-Pagan Lagrange Multiplier Cross-Sectional Dependence test 
results 
lnTAt RESt IRTSt lnGDPPCt INFt 
62.272* 69.591* 58.623* 43.183** 62.809* 
Note: * & ** denote statistical significance at 1% and 5%, respectively.  
  
 
 
 
 
 
 
Table 2: Panel Unit Root Test Results 
Test CADF CIPS 
Variable Level                  Level                    
lnTAt -1.699 -2.614** -1.861 -4.011* 
RESt -1.181 -2.413** -1.325 -4.436 
IRTSt -1.021 -2.662** -1.226 -3.298* 
lnGDPPCt -1.822 -2.682** -2.121 -3.318* 
INFt -1.007 -3.818* -1.666 -3.589* 
Note: Considering trend and intercept; The optimal lag selection is based on the Akaike 
Information Criterion (AIC); * & ** denote statistical significance at 1% and 5%, 
respectively. 
 
Table 3: Westerlund panel cointegration test results 
Statistic  Value 
Gt -2.345* 
Ga -9.600 
Pt -22.561* 
Pa -10.778* 
Note: Considering trend and intercept; The optimal lag selection is based on the AIC; * & ** 
denote statistical significance of the critical values, under the null hypothesis on non 
cointegration, at 1% and 5%, respectively. 
 
Table 4: Panel Granger causality test results 
Dependent 
Variable 
Independent 
Variable 
Emirmahmutoglu
–Kose 
Dumitrescu–
Hurlin 
lnTAt RESt 50.51 -0.649 
RESt lnTAt 77.691* 3.618* 
lnTAt IRTSt 75.219* 2.102** 
IRTSt lnTAt 64.52*** 5.689* 
lnTAt lnGDPPCt 159.768* 1.721*** 
lnGDPPCt lnTAt 48.223 0.182 
lnTAt INFt 52.171 -0.247 
INFt lnTAt 50.682 -0.050 
IRTSt RESt 51.314 0.201 
RESt IRTSt 78.898* 2.281** 
Note: The optimal lag selection is based on the AIC; *, ** & *** denote statistical significance 
at 1% , 5% & 10%, respectively. 
                                                 
i
 The choice of the South Asian countries was based on data availability which resulted in 
exclusion of Afghanistan.   


Munich Personal RePEc ArchiveRegional Integration, InternationalTourism Demand and Renewable EnergyTransition: Evidence from selected SouthAsia EconomiesMurshed, MuntasirNorth South University2019Online at https://mpra.ub.uni-muenchen.de/98095/MPRA Paper No. 98095, posted 13 Jan 2020 03:48 UTCRegional Integration, International Tourism Demand and Renewable Energy Transition: Evidence from selected South Asia Economies  Muntasir Murshed School of Business and Economics, North South University, Bangladesh Email: muntasir.murshed@northsouth.edu  Abstract The aim of this paper is to explore the international tourism demand-renewable energy consumption-intra-regional trade nexus across seven South Asian economies. The Emirmahmutoglu–Kose and Dumitrescu–Hurlin causality test results reveal unidirectional causalities stemming from tourist influx and intra-regional trade to renewable energy consumption. Moreover, bidirectional causality is found between tourism demand and regional trade. Thus, these results are anticipated to generate key policy implications.   Keywords: tourism demand, renewable energy transition  1. Introduction The volume of international tourist flows across the globe has surged over time. As a result, the factors affecting the international tourism demand have attracted attention amidst researchers (Peng et al. 2015). Moreover, growth in tourism demand is believed to trigger power consumption through both the direct and indirect channels (Lee 2013). Hence, sustainability of international tourism influx can largely be attributed to the reliability of power supply as well. In the same vein, insufficient access to in-grid electrification is often claimed to be the key constraint bottlenecking the growth of tourism demand, both within the national and international spheres. Thus, underscoring the necessity of enhancing the off-grid electrification rates across the tourist destinations, that do not have adequate access to the national grid, incorporation of renewable energy resources for off-grid power generation purposes seems to be a plausible policy move that entails government interventions (Shezan et al. 2015). On the other hand, enhancing the share of renewables in total electricity outputs is often attributed to cross-border power trade, following the indigenous constraints in the form of natural endowment of renewable energy resources (Amin and Murshed 2016). In this regard, liberalization of trade barriers has often been recommended as a means to initiate a transition from non-renewable to renewable energy use (Murshed 2018). Trade liberalization policies complement renewable energy sector development within the low-income countries in particular (Murshed 2019).  Although a plethora of studies have explored the multifaceted determinants of international tourism demand, the roles of renewable energy adoption and cross-border trade of renewable sources of power have received nominal attention in the existing narrative. Thus, this paper aims to bridge this gap in literature by empirically investigating the causal nexus between tourist arrivals, renewable energy consumption and intra-regional trade across seven South Asian economies, namely Bangladesh, India, Pakistan, Sri Lanka, Nepal, Maldives and Bhutan.i This study is pertinent from the perspective of policy implications with respect to attaining international tourism growth across the South Asia and, at the same time, enhancing cross-border trade of power to curtail the indigenous reliance on the non-renewable fossil fuels for generating power. The growth in international tourist arrivals across South Asia has increased by almost 6-folds between 1995 and 2017, while South Asia’s share in the global tourist arrival figures rose by more than 2.3 times (World Bank 2019). These statistics indicate that South Asia is gaining global recognition as one of the emerging tourism destinations. On the other hand, the share of renewables in total energy-use within South Asian has predominantly been below par, with Nepal being the only exception (World Bank 2019). This is a concerning issue keeping South Asia’s energy security and environmental sustainability into cognizance. Hence, it can be hypothesized that the causal associations between international tourism demand, renewable energy use and intra-regional trade could impose critically policy implications in this regard. 2. Methodology and Dataset This study employs a simple linear model in which international tourist arrival is expressed as a function of renewable energy consumption, intra-regional trade participation and other control variables:                                                (1)  where the subscript t refers to the corresponding time period and U represents the error term; TA denotes the number international tourist arrivals which is used to measure the degree of tourism demand; RES refers to the renewable energy share in total energy consumption, used as a proxy for understanding the propensity of renewable energy consumption; and IRTS symbolizes the intra-regional trade share of respective nations in the aggregate level of South Asian trade, in order to account for the state of regional integration. GDPPC and INF are per capita GDP (in terms of PPP 2011 constant US dollars) and domestic inflation rate (proxied by the consumer price index), respectively, controlling the econometric model.   The variables, where appropriate, are converted to their natural logarithms. This study uses annual data stemming across 2000 and 2015 in the context of all the seven South Asian economies. The data for IRTS has been sourced from the Asia Regional Integration Center database of the Asian Development Bank while data for all other variables are compiled from the World Development Indicators database maintained by the World Bank.    As part of the econometric methodology, the data set is firstly tested for cross-sectional dependence among the panels using the Breusch-Pagan (1980) Lagrange Multiplier test for cross-sectional dependence, suited for panel data sets with small number of cross sections and larger time periods. Table 1 (see appendix) reports the results from the cross-sectional dependency analysis which provides statistical support in favor of the panels being cross-sectionally dependent. Presence of cross-sectional dependence lead to spurious stationarity properties whereby second generation unit root tests are used to account for the limitation of the first generation tests. The stationarity analyses are done tapping the Cointegrated Augmented Dickey-Fuller (CADF) and Cross-Sectional Augmented Im-Pesaran-Shin (CIPS) techniques proposed by Pesaran (2007). The long run cointegrating associations between the variables are estimated using the Westerlund (2005) cointegration method. Finally, the causal linkages are assessed using the recently developed Emirmahmutoglu–Kose and Dumitrescu–Hurlin tests proposed by Emirmahmutoglu and Kose (2011) and Dumitrescu and Hurlin (2012), respectively. Both these techniques are affirmed to handle cross-sectionally dependent panel data sets in contrast to the conventional Granger causality test.  3. Results and Discussion The results from the CADF and CIPS unit root tests, as reported in table 2, reveal that all the variables are non-stationary at their level forms while they become stationary at their first differences, implying a common order of integration.   Table 3 outlines the Westerlund cointegration test results which provide statistical evidence regarding the presence of cointegrating relationships between the variables included in the econometric model.    Finally, the causality results are presented in table 4. The statistical estimates from both the techniques coincide to conform the robustness of the results across different causality-testing methodologies. The estimates indicate that international tourism demand influences the renewable energy consumption across South Asia, as perceived from the unidirectional causal link stemming from international tourist arrivals to renewable energy share in total energy consumption levels. This implies that influx of foreign tourist does exert pressures on demand for power, which tend to be met through incorporation of renewable energy resources for power generation purposes. From this finding, it can be partially claimed that renewable energy resources could be ensuring off-grid electrification within the remote tourist destinations across South Asia.  Moreover, a feedback causal association is found between international tourist arrivals and intra-regional trade shares which denotes that not only does greater regional trade cater the pre-requisite of adequate power supply for attracting foreign tourists to travel to South Asia, greater influx of international tourists also tends to facilitate trade between the neighboring countries. This assumption of intra-regional trade influencing energy supply across the South Asian region is affirmed by the statistical evidence of unidirectional causation stemming from IRTS to RES. This could be perceived as an indication of cross-border energy trade taking place between the concerned economies which, in turn, appears to be playing a fruitful role in uplifting the overall share of renewables in total energy consumption across South Asia. Thus, it is ideal for the governments to liberalize intra-regional trade barriers to ease the cross-border flows of energy resources which would ultimately escalate the overall tourism demand across this region.   4. Conclusion The roles of renewable energy consumption and intra-regional trade with regard to enhancing international tourism demand have received nominal attention in the existing literature. Against this milieu, this paper attempted to empirically bridge this gap in the context of seven South Asian economies. The results broadly point out towards the inter-linkages between these three aforementioned macroeconomic aggregates. The causal estimates revealed unidirectional causality running from international tourist arrivals and intra-regional trade to renewable energy share in total energy, while a bidirectional causal relationship was found between international tourism demand and intra-regional trade. Thus, these findings collectively impose crucial policy implications with respect to expanding the tourism industry, facilitating the non-renewable to renewable energy transition and strengthening the intra-regional trade relationships across South Asia.  It can be assured that implementing appropriate policy measures, keeping these causal estimates into cognizance, could ideally empower the South Asian economies in pursuing their commitment to attain the targets under the Sustainable Development Goals (SDG) of the 2030 agenda of the United Nations; especially SDG 7 which aims to ensure energy security across the globe through greater use of renewable energy resources and SDG 17 which call for building global partnerships and cooperation for sustainable development as a whole.    References Amin, S. B., & Murshed, M. (2016). The economies of cross-border electricity trading in Bangladesh. Prospects & Challenges of Connectivity & Trading in Power & Energy: A Regional & International Perspective, 1, 119-128. Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The review of economic studies, 47(1), 239-253. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460. Emirmahmutoglu, F., & Kose, N. (2011). Testing for Granger causality in heterogeneous mixed panels. Economic Modelling, 28(3), 870-876. Lee, C. G. (2013). Electricity consumption and international tourism: The case of Singapore. Anatolia, 24(1), 91-94.   Murshed, M. (2018). Does improvement in trade openness facilitate renewable energy transition? Evidence from selected South Asian economies. South Asia Economic Journal, 19(2), 151-170. Murshed, M. (2019). Are Trade Liberalization policies aligned with Renewable Energy Transition in low and middle income countries? An Instrumental Variable approach. Renewable Energy. DOI: 10.1016/j.renene.2019.11.106 Peng, B., Song, H., Crouch, G. I., & Witt, S. F. (2015). A meta-analysis of international tourism demand elasticities. Journal of Travel Research, 54(5), 611-633. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of applied econometrics, 22(2), 265-312. Shezan, S. A., Saidur, R., Ullah, K. R., Hossain, A., Chong, W. T., & Julai, S. (2015). Feasibility analysis of a hybrid off-grid wind–DG-battery energy system for the eco-tourism remote areas. Clean Technologies and Environmental Policy, 17(8), 2417-2430. Westerlund, J. (2005). New simple tests for panel cointegration. Econometric Reviews, 24(3), 297-316. World Bank. (2019). World Development Indicators database. World Bank.   Appendix Table 1: Breusch-Pagan Lagrange Multiplier Cross-Sectional Dependence test results lnTAt RESt IRTSt lnGDPPCt INFt 62.272* 69.591* 58.623* 43.183** 62.809* Note: * & ** denote statistical significance at 1% and 5%, respectively.          Table 2: Panel Unit Root Test Results Test CADF CIPS Variable Level                  Level                    lnTAt -1.699 -2.614** -1.861 -4.011* RESt -1.181 -2.413** -1.325 -4.436 IRTSt -1.021 -2.662** -1.226 -3.298* lnGDPPCt -1.822 -2.682** -2.121 -3.318* INFt -1.007 -3.818* -1.666 -3.589* Note: Considering trend and intercept; The optimal lag selection is based on the Akaike Information Criterion (AIC); * & ** denote statistical significance at 1% and 5%, respectively.  Table 3: Westerlund panel cointegration test results Statistic  Value Gt -2.345* Ga -9.600 Pt -22.561* Pa -10.778* Note: Considering trend and intercept; The optimal lag selection is based on the AIC; * & ** denote statistical significance of the critical values, under the null hypothesis on non cointegration, at 1% and 5%, respectively.  Table 4: Panel Granger causality test results Dependent Variable Independent Variable Emirmahmutoglu–Kose Dumitrescu–Hurlin lnTAt RESt 50.51 -0.649 RESt lnTAt 77.691* 3.618* lnTAt IRTSt 75.219* 2.102** IRTSt lnTAt 64.52*** 5.689* lnTAt lnGDPPCt 159.768* 1.721*** lnGDPPCt lnTAt 48.223 0.182 lnTAt INFt 52.171 -0.247 INFt lnTAt 50.682 -0.050 IRTSt RESt 51.314 0.201 RESt IRTSt 78.898* 2.281** Note: The optimal lag selection is based on the AIC; *, ** & *** denote statistical significance at 1% , 5% & 10%, respectively.                                                  i The choice of the South Asian countries was based on data availability which resulted in exclusion of Afghanistan.   

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