Assessing technological innovation and sustainable environment: Tourism perspective of advanced panel methods

Figures & data

Figure 1. International tourist arrival to four South Asian economies (1995–2019).

Source: World Bank (2022)

Figure 2. CO₂ emissions from Four South Asian economies (1995–2019).

Source: World Bank (2022)

Figure 3. Theoretical representation of variables’ association.

Source: Authors own work based on the theoretical Framework.

Table 1. Variables specification and data sources.

Variable	Specification	Unit	Data Source
${\mathit{CO}}_2$	Carbon dioxide release into the atmosphere via combustion of fossil fuel.	Kilo ton (kt)	World Bank (2021)
$\mathbf{GDP}$	Monetary measure of the marketed value of all finished goods and services during a particular period of time.	Constant US$ 2015
$\mathbf{GDPS}$	Square of GDP	Constant US$ 2015
$\mathbf{TOUR}$	Number of international tourist arrivals.	Number of arrivals
$\mathbf{REC}$	The proportion of gross inland renewable energy consumption to total (primary) gross inland energy consumption estimated over a calendar year.	% of total final energy consumption
$\mathbf{TI}$	Technological innovation refers to number of patents by residents and non-residents.	No. of patents

Source: Authors own work based on the data obtained from the given sources.

Table 2. Slope heterogeneity.

Slope Heterogeneity Test	Statistics
Model-1
$\tilde{\Delta }$	13.014***
${\tilde{\Delta }}^{\mathrm{Adjusted}}$	14.492***
Model-2
$\tilde{\Delta }$	8.636***
${\tilde{\Delta }}^{\mathrm{Adjusted}}$	9.815***

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

Table 3. Cross-section dependence.

Cross-Section Dependence
${\mathit{CO}}_{2,\mathit{it}}$	${\mathbf{GDP}}_{\mathbf{it}}$
13.24***	13.585***
${\mathbf{GDPS}}_{\mathbf{it}}$	${\mathbf{TOUR}}_{\mathbf{it}}$
13.584***	7.218***
${\mathbf{REC}}_{\mathbf{it}}$	${\mathbf{TI}}_{\mathbf{it}}$
12.807***	9.612***

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

Table 4. Unit root testing (Pesaran, 2007).

Variables	$\text{Intercept and Trend}$
	$\mathrm{I}(0)$	$\mathrm{I}(1)$
${\mathit{CO}}_{2,\mathit{it}}$	−1.941	−5.467***
${\mathbf{GDP}}_{\mathbf{it}}$	−2.144	−4.067***
${\mathbf{GDPS}}_{\mathbf{it}}$	−2.181	−3.968***
${\mathbf{TOUR}}_{\mathbf{it}}$	−1.093	−4.259***
${\mathbf{REC}}_{\mathbf{it}}$	−1.877	−5.282***
${\mathbf{TI}}_{\mathbf{it}}$	−3.778***	–

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%. I(0) is for level, and I(1) is for the first.

Source: Authors own work based on the data obtained from the given sources.

Table 5. Cointegration results (Westerlund, 2007).

Model-1
Statistics	Value	Z-value
${\mathit{G}}_{\mathit{\tau }}$	−8.589***	−12.855
${\mathit{G}}_{\mathit{a}}$	−15.405*	−1.554
${\mathit{P}}_{\mathit{\tau }}$	−13.054***	−7.752
${\mathit{P}}_{\mathit{a}}$	−17.793***	−3.195
Model-2
${\mathit{G}}_{\mathit{\tau }}$	−7.706***	−10.828
${\mathit{G}}_{\mathit{a}}$	−13.364	−0.427
${\mathit{P}}_{\mathit{\tau }}$	−12.763***	−7.365
${\mathit{P}}_{\mathit{a}}$	−16.531**	−2.138

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

Table 6. CS-ARDL.

$\mathrm{Variable}(s)$	$\mathrm{Short}-\mathrm{Run}$
	$\mathrm{Model}-1$ $\mathrm{Coefficients}$ $[\mathrm{Std}.\mathrm{Error}]$	$\mathrm{Model}-2$ $\mathrm{Coefficients}$ $[\mathrm{Std}.\mathrm{Error}]$
$\Delta \mathit{GDP}$	0.372*** [0.1101]	0.697*** [0.1103]
$\Delta \mathit{GDPS}$	–	−0.0223*** [0.00521]
$\Delta \mathit{TOUR}$	−0.0201*** [0.0047]	−0.0245*** [0.0062]
$\Delta \mathit{REC}$	−2.004*** [0.3129]	−1.684*** [0.3179]
$\Delta \mathit{TI}$	−0.0438*** [0.0059]	−0.0428*** [0.00891]
$\mathbf{ECM}(-1)$	−0.887*** [0.0385]	−0.930*** [0.0345]
$\mathbf{Long}-\mathbf{Run}$
$\mathit{GDP}$	0.514*** [0.1491]	2.412*** [0.371]
$\mathit{GDPS}$	–	−0.099*** [0.0138]
$\mathit{TOUR}$	−0.0231*** [0.0049]	−0.0259*** [0.00312]
$\mathit{REC}$	−2.311*** [0.4610]	−1.844*** [0.4097]
$\mathit{TI}$	−0.0538*** [0.0103]	−0.0477*** [0.00781]

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

Table 7. Robustness check using AMG.

$\mathrm{Variable}(s)$	$\mathrm{Model}-1$ $\mathrm{Coefficients}$	$\mathrm{Model}-2$ $\mathrm{Coefficients}$
$\mathit{GDP}$	0.604***	1.134***
$\mathit{GDPS}$	–	−0.0320***
$\mathit{TOUR}$	−0.0255***	−0.0507***
$\mathit{REC}$	−1.956***	−1.996***
$\mathit{TI}$	−0.0341***	−0.0225***

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

Table 8. Dumitrescu-Hurlin panel causality.

$H_0$	${\mathrm{Wald}}_{\mathrm{Stats}}$	${\overline{Z}}_{\mathrm{stats}}$	$p-\mathrm{value}$
GDP – CO2	4.268***	3.463	0.000
CO2 – GDP	2.882**	2.220	0.026
GDPS – CO2	5.180***	4.355	0.000
CO2 – GDPS	3.295***	2.728	0.006
REC – CO2	2.584*	1.852	0.064
CO2 – REC	3.550***	3.042	0.002
TOUR – CO2	5.505***	4.524	0.000
CO2 – TOUR	3.196***	2.606	0.009
TI – CO2	4.197***	3.839	0.000
CO2 – TI	6.518***	6.697	0.000

Note: Significance level is denoted by *** for 1%, ** for 5% and * for 10%.

Source: Authors own work based on the data obtained from the given sources.

World Bank. (2022). World Development Indicators. Retrieved from https://databank.worldbank.org/source/world-development-indicators

 Google Scholar

World Bank. (2021). World Development Indicators. Retrieved from https://databank.worldbank.org/source/world-development-indicators

 Google Scholar

Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics (Chichester, England), 22(2), 265–312. https://doi.org/10.1002/jae.951

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Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709–748. https://doi.org/10.1111/j.1468-0084.2007.00477.x

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