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Fulltext Dynamics of fractional order nonlinear system: A realistic perception with neutrosophic fuzzy number and Allee effect

Alam Khan N, Abdul Razzaq O, Riaz F, Ahmadian A, Senu N

J Adv Res, 2021 09;32:109-118.
PMID: 34484830 DOI: 10.1016/j.jare.2020.11.015

Introduction: The fusion of fractional order differential equations and fuzzy numbers has been widely used in modelling different engineering and applied sciences problems. In addition to these, the Allee effect, which is of high importance in field of biology and ecology, has also shown great contribution among other fields of sciences to study the correlation between density and the mean fitness of the subject.
Objectives: The present paper is intended to measure uncertain dynamics of an economy by restructuring the Cobb-Douglas paradigm of the renowned Solow-Swan model. The purpose of study is further boosted innovatively by subsuming the perception of logistic growth with Allee effect in the dynamics of physical capital and labor force.
Methods: Fractional order derivative and neutrosophic fuzzy (NF) theory are applied on the parameters of the Cobb-Douglas equation. Distinctively, cogitating fractional order derivative to study the change at each fractional stage; single-valued triangular neutrosophic fuzzy numbers (SVTNFN) to cope the uncertain situations; logistic growth function with Allee effect to analyze the factors in natural way, are the significant and novel features of this endeavor.
Results: The incorporation of the aforementioned theories and effects in the Cobb-Douglas equation, resulted in producing maximum sustainable capital investment and maximum capacity of labor force. The solutions in intervals located different possible solutions for different membership degrees, which accumulated the uncertain circumstances of a country.
Conclusion: Explicitly, these notions add new facts and figures not only in the dynamical study of capital and labor, which has been overlooked in classical models, but also left the door open for discussion and implementation on classical models of different fields.

Matched MeSH terms: Economic Development*
Dynamic linkages between non-renewable energy, renewable energy and economic growth through nonlinear ARDL approach: evidence from Malaysia

Afroz R, Muhibbullah M

Environ Sci Pollut Res Int, 2022 Jul;29(32):48795-48811.
PMID: 35201582 DOI: 10.1007/s11356-022-19346-0

The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980-2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.

Matched MeSH terms: Economic Development*
Fulltext The impact of fiscal decentralization, green energy, and economic policy uncertainty on sustainable environment: a new perspective from ecological footprint in five OECD countries

Zahra S, Badeeb RA

Environ Sci Pollut Res Int, 2022 Aug;29(36):54698-54717.
PMID: 35305216 DOI: 10.1007/s11356-022-19669-y

The paper explores the short-run and long-run asymmetric impact of fiscal decentralization, green energy, and economic policy uncertainty on environmental sustainability proxied by ecological footprint. Using the Nonlinear Autoregressive Distributed lag (NARDL) approach in selected five OECD countries, we find that ecological footprint responds to positive and negative fiscal decentralization asymmetrically in the long run and short run. However, the nature of the response varies significantly across countries. The result also suggests that green energy is a major factor in reducing the ecological footprint in all countries except Canada. Finally, economic policy uncertainty plays a negative and significant role in the ecological footprint in the UK, USA, and Germany while insignificant in Australia and Canada. Implications for effective environmental policies are discussed.

Matched MeSH terms: Economic Development*
Towards a new paradigm: Activity level balanced sustainability reporting

Samudhram A, Siew EG, Sinnakkannu J, Yeow PH

Appl Ergon, 2016 Mar 27.
PMID: 27029522 DOI: 10.1016/j.apergo.2016.03.004

Technoeconomic paradigms based economic growth theories suggest that waves of technological innovations drove the economic growth of advanced economies. Widespread economic degradation and pollution is an unintended consequence of such growth. Tackling environmental and social issues at firm levels would help us to overcome such issues at macro-levels. Consequently, the Triple Bottom Line (TBL) reporting approach promotes firm level economic, environmental and social performances. Incorporating Zink's (2014) 3-pillar presentation model, this paper indicates that economic, social and environmental performances tend to be reported at firm level. All three pillars are not covered evenly at the activity levels. Thus, a loophole is identified whereby excellent environmental performance at activity levels could potentially leave poor social performance undisclosed. A refinement of the TBL paradigm, whereby all three pillars are covered at the activity level, is suggested, to enhance sustainability reporting.

Matched MeSH terms: Economic Development
Application of Nanotechnology in Wood-Based Products Industry: A Review

Jasmani L, Rusli R, Khadiran T, Jalil R, Adnan S

Nanoscale Res Lett, 2020 Nov 04;15(1):207.
PMID: 33146807 DOI: 10.1186/s11671-020-03438-2

Wood-based industry is one of the main drivers of economic growth in Malaysia. Forest being the source of various lignocellulosic materials has many untapped potentials that could be exploited to produce sustainable and biodegradable nanosized material that possesses very interesting features for use in wood-based industry itself or across many different application fields. Wood-based products sector could also utilise various readily available nanomaterials to enhance the performance of existing products or to create new value added products from the forest. This review highlights recent developments in nanotechnology application in the wood-based products industry.

Matched MeSH terms: Economic Development
Fulltext FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING BOX-JENKINS AND ARTIFICIAL NEURAL NETWORK IN MALAYSIA

NURFARAHIN IDRUS, NORIZAN MOHAMED

UMT Journal of Undergraduate Research, 2020;2(4):89-100.
MyJurnal

Airline industry is one of the largest industries in the world of transport because it is the most important transport in the global transport system. The airline industry has played a very important role in the economic development in Malaysia. Due to the increase in its operating business, the demand for air travel increases day by day. Hence, this study focused on the number of passengers using air transport in Malaysia. The monthly data from January 2005 to December 2015 were obtained from Malaysia Airport Holdings Berhad (MAHB) in Sepang, Selangor. The data is divided into 2 parts, which are in sample data from January 2005 to December 2014 and out sample data from January 2015 to December 2015. The study was conducted to predict airline passengers in Malaysia using the Box-Jenkins model and Artificial Neural Network (ANN) model. Both models were studied to choose the best model. Mean Absolute Percentage Error (MAPE) and Mean Squared Error (MSE) were used to measure the performance of both models. SARIMA was selected as the best model for Box-Jenkins with MAPE and MSE were 7.3458388 and 2.67011 respectively while Multilayer Feed Forward Neural Network (MFFNN) with seven input variables, with MAPE and MSE, 7.251 and 0.0006 respectively were selected as the best model for Multilayer Feed Forward Neural Network (FFNN). In conclusion, these studies have proven that the Multilayer Feed Forward Neural Network (FFNN) model is the best model for considering airplanes in Malaysia compared to the SARIMA model.

Matched MeSH terms: Economic Development
Carbon dioxide (CO2) emissions and economic growth: A systematic review of two decades of research from 1995 to 2017

Mardani A, Streimikiene D, Cavallaro F, Loganathan N, Khoshnoudi M

Sci Total Environ, 2019 Feb 01;649:31-49.
PMID: 30170214 DOI: 10.1016/j.scitotenv.2018.08.229

Understanding the nexus CO2 emissions and economic growth helps economies in formulating energy policies and developing energy resources in sustainable ways. Although during recent years, numerous of the previous studies have been very thoroughly investigated the nexus between economic growth and CO2 emissions, there is a lack of research regarding the qualitative systematic review and meta-analysis in these areas. The main purpose of this review paper is to present the comprehensive overview of the relationship between CO2 emissions and economic growth. In this regard, the Web of Science database has been chosen and a qualitative systematic and meta-analysis method which called "Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)" has been proposed. Therefore, a review of 175 published articles appearing in 55 scholarly international journals between 1995 and 2017 has been achieved to reach a broad review of the nexus between economic growth and CO2 emissions with other indicators. Consequently, the selected articles have been categorized by the author name, the year of publication, data duration, types of techniques, data analysis method, the name of indicators, country, scope (individual country and multi-countries), journals, results, and outcome in which they appeared. The results of this paper demonstrated that the nexus between CO2 emissions and economic growth gives reasons for policy options that have to reduce emissions by imposing limiting factors on economic growth as well. Given the fact that bidirectional causality exists, as far as economic growth increases or decreases, further CO2 emissions are stimulated in higher or lower levels and consequently, a potential reduction of the emissions should have an adverse influence on economic growth.

Matched MeSH terms: Economic Development
A replenishment inventory model for items under time-varying demand rates considering trade credit period and cash discount for a finite time horizon

MOHD OMAR

Sains Malaysiana, 2012;41:493-497.

Many researchers have developed various economic ordering quantity models by assuming an infinite time horizon and constant demand rate. However due to rapid technological advancement, shorter product life cycle and severe competition, those assumptions are no longer realistic. In this paper, we complement that shortcoming by considering an inventory model that satisfies a continuous time-varying demand rate for a finite time horizon when trade credit period and unit cash discount are allowed. The time horizon consists of n different cycles with equal or different cycles length. The trade credit period was assumed to be proportional to the cycle length. We developed mathematical models and presented a numerical example to support the effectiveness of these models.

Matched MeSH terms: Economic Development
Trends in sustainable logistics in major cities in China

Lan S, Tseng ML, Yang C, Huisingh D

Sci Total Environ, 2020 Apr 10;712:136381.
PMID: 31940512 DOI: 10.1016/j.scitotenv.2019.136381

"Smart cities" have become the development direction pursued by city leaders to address challenges related to rapid growth in urban areas. The sustainable development of the logistics sector has important practical significance for the evolution of smart cities. This study assessed the inefficiency rate and total factor productivity (TFP) of logistics in 36 Chinese cities from 2006 to 2015. The directional distance function (DDF) and Luenberger productivity index analytical approaches were used to assess the relevant parameters. The results revealed that the logistics system inefficiency rate of the eastern region was much higher than that of the central and western regions, while that of the western region was slightly higher than that of the central region. This study identified the main constraints of the logistics TFP in different regions in China. This finding is used to promote policy-making and investment planning to improve China's competitive advantage. The results documented that the central region of China needs to accelerate logistics reforms and use its location advantage of its location to form an organic connection with the eastern and western regions. Countries can use such metrics to take actions to improve their logistics performance, as such an improvement has a causal relationship with economic development.

Matched MeSH terms: Economic Development
Fulltext Investing in the health of girls and women: a best buy for sustainable development

Remme M, Vassall A, Fernando G, Bloom DE

BMJ, 2020 06 02;369:m1175.
PMID: 32487585 DOI: 10.1136/bmj.m1175
Matched MeSH terms: Economic Development
The motorcycle deaths to passenger car deaths ratio and economic performance: A panel data analysis

Sirajudeen AO, Law TH, Wong SV, Ng CP

Accid Anal Prev, 2022 Feb;165:106533.
PMID: 34902624 DOI: 10.1016/j.aap.2021.106533

The existing literature in road safety revealed that the relationship between motorcycle deaths and per-head income follows a Kuznets or reverse U-curve pattern, whereby motorcycle deaths incline at lower income levels but decline once the per-head income has exceeded a threshold level. The same reverse U-curve relationship was also observed between per-head income and other road injury-related variables, including road deaths, road injuries, as well as road deaths to road injuries ratio. Evidence showed that motorcycles and passenger cars are the dominant vehicle modes and contributed significantly to global road deaths. The main objective of this study is to examine the relationship between the motorcycle deaths to passenger car deaths (MDC) ratio and per-head Gross Domestic Product (GDP). Examining the relationship between the MDC ratio and GDP per capita can be effective in understanding the relative change between motorcycle and passenger car deaths at different economic development stages, as well as identifying appropriate preventive measures. We apply a panel linear regression analysis on a panel of 38 countries over the period 1965-2013. Result demonstrated that there is a reverse U-curve relationship between the MDC ratio and the logarithm of GDP per capita. This implies that, at lower levels of GDP per capita, motorcycle deaths were more prevalent than passenger car deaths, whereas as the level of GDP per capita rises, passenger car deaths became relatively prevalent than motorcycle deaths. Moreover, there is a reverse U-shaped relationship between motorcycle ownership to passenger car ownership ratio (MPC) and the MDC ratio, while a U-shaped relationship exists between relative growth in higher mobility roads as compared to higher accessibility roads (MPA) and the MDC ratio. Based on our results, policies and interventions to reduce motorcycle and passenger car deaths were suggested in the conclusion of the paper.

Matched MeSH terms: Economic Development
Analysis of the spatial characteristics and influencing factors of agricultural eco-efficiency: evidence from Anhui Province, China, during the period 2011-2018

Wu Y, Rahman RA, Yu Q

Environ Monit Assess, 2022 Feb 08;194(3):154.
PMID: 35132444 DOI: 10.1007/s10661-022-09817-9

Sustainable agriculture is important for preserving environmental health and simultaneously gaining economic profits while maintaining social and economic equity. One way to evaluate sustainable agriculture is by studying agricultural eco-efficiency (AEE). Hence, this study constructed a data-driven method to evaluate and optimize AEE with the aim of providing a basis for improving the sustainable development of regional agriculture. Sixteen cities in Anhui Province, China, were considered in the study, and the variables used were agricultural resource inputs, environmental pollution, and agricultural economic development. Agricultural non-point source pollution (NPSP) emissions were considered the undesired output to build an AEE evaluation index system. Furthermore, a data envelopment analysis (DEA) model was established to analyse AEE from the static and dynamic perspectives. The spatial development and the temporal and spatial characteristics of AEE were also analysed. In addition, we applied a random effect (RE) panel Tobit model to quantitatively analyse the influencing factors of AEE from the input perspective and then proposed reasonable suggestions for improving the sustainable development of regional agriculture. Our findings show that the overall agricultural development in the 16 cities in Anhui Province has been continuously improving, even though there is an agglomeration of spatial development in some regions. In conclusion, this study provides suggestions and references for policy makers and agricultural practitioners regarding how to improve regional AEE and promote the sustainable development of the regional agricultural economy.

Matched MeSH terms: Economic Development
Fulltext Watershed Horizontal Ecological Compensation Policy and Green Ecological City Development: Spatial and Mechanism Assessment

Lin X, Baskaran A, Zhang Y

Int J Environ Res Public Health, 2023 Feb 02;20(3).
PMID: 36768047 DOI: 10.3390/ijerph20032679

Green ecological development has become an inevitable choice to achieve sustainable urban development and carbon neutrality. This paper evaluates the level of green ecological city development in the Xin'an watershed as measured by green total factor productivity (GTFP), analyzes the direct and spatial effects of the Watershed Horizontal Ecological Compensation policy on GTFP, and further examines the moderating effect of the Research and Development (R&D) incentives, industrial structure, and income gap. This paper conducts difference-in-differences (DID) and spatial regression analysis on 27 cities from 2007 to 2019. The results show that GTFP progresses to varying degrees across cities over time, especially in the pilot cities. Crucially, the Watershed Horizontal Ecological Compensation policy significantly improved GTFP, although the effect was slight. Interestingly, the increase in GTFP in pilot cities that implemented the policy spatially suppressed the increase in GTFP in cities that did not implement the policy. Our evidence also shows that the positive effect of the policy is higher in regions with higher R&D incentives and industrial structure upgrading, which indicates that R&D incentives and industrial upgrading are crucial. In comparison, the income gap has not made the expected negative adjustment effect under the Chinese government's poverty alleviation policy. However, the positive policy effect is heterogeneous in the downstream and upstream pilot cities. The "forcing effect" of the policy on the downstream cities is more favorable than the "compensating effect" on the upstream cities. Therefore, policymakers should pay more attention to ensuring the effectiveness of the Watershed Horizontal Ecological Compensation policy in enhancing GTFP as a long-term strategy to guarantee the sustainability of green ecological development in Chinese cities.

Matched MeSH terms: Economic Development
Fulltext Identifying the necessary capacities for the adaptation of a diabetes phenotyping algorithm in countries of differing economic development status

Jackson-Morris A, Sembajwe R, Mustapha FI, Chandran A, Niyonsenga SP, Gishoma C, et al.

Glob Health Action, 2023 Dec 31;16(1):2157542.
PMID: 36692486 DOI: 10.1080/16549716.2022.2157542

BACKGROUND: In 2019, the World Health Organization recognised diabetes as a clinically and pathophysiologically heterogeneous set of related diseases. Little is currently known about the diabetes phenotypes in the population of low- and middle-income countries (LMICs), yet identifying their different risks and aetiology has great potential to guide the development of more effective, tailored prevention and treatment.
OBJECTIVES: This study reviewed the scope of diabetes datasets, health information ecosystems, and human resource capacity in four countries to assess whether a diabetes phenotyping algorithm (developed under a companion study) could be successfully applied.
METHODS: The capacity assessment was undertaken with four countries: Trinidad, Malaysia, Kenya, and Rwanda. Diabetes programme staff completed a checklist of available diabetes data variables and then participated in semi-structured interviews about Health Information System (HIS) ecosystem conditions, diabetes programme context, and human resource needs. Descriptive analysis was undertaken.
RESULTS: Only Malaysia collected the full set of the required diabetes data for the diabetes algorithm, although all countries did collect the required diabetes complication data. An HIS ecosystem existed in all settings, with variations in data hosting and sharing. All countries had access to HIS or ICT support, and epidemiologists or biostatisticians to support dataset preparation and algorithm application.
CONCLUSIONS: Malaysia was found to be most ready to apply the phenotyping algorithm. A fundamental impediment in the other settings was the absence of several core diabetes data variables. Additionally, if countries digitise diabetes data collection and centralise diabetes data hosting, this will simplify dataset preparation for algorithm application. These issues reflect common LMIC health systems' weaknesses in relation to diabetes care, and specifically highlight the importance of investment in improving diabetes data, which can guide population-tailored prevention and management approaches.

Matched MeSH terms: Economic Development
Achieving pro-poor growth and environmental sustainability agenda through information technologies: as right as rain

Imran M, Khan KB, Zaman K, Musah MB, Sudiapermana E, Aziz ARA, et al.

Environ Sci Pollut Res Int, 2021 Aug;28(30):41000-41015.
PMID: 33774795 DOI: 10.1007/s11356-021-13630-1

The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975-2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high-technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country's economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.

Matched MeSH terms: Economic Development
Stochastic convergence in carbon emissions based on a new Fourier-based wavelet unit root test

Erdogan S, Solarin SA

Environ Sci Pollut Res Int, 2021 May;28(17):21887-21899.
PMID: 33410083 DOI: 10.1007/s11356-020-12033-y

Most of the existing studies on stochastic convergence of emission have not adequately considered smooth structural changes. The primary purpose of this paper is to examine the validity of stochastic convergence at different income levels by recently proposed Fourier-based wavelet augmented Dickey-Fuller test with smooth shifts. Empirical results can be summed up as follows: (i) carbon emission per capita follows the stationarity process in 35 high-income countries, while carbon emission per capita follows the stationarity process in 27 upper-middle-income countries; (ii) besides, carbon emission per capita follows stationarity process in 30 lower-middle-income countries, while carbon emission per capita follows stationarity process in 13 low-income countries; (iii) in light of these findings, it can be said that stochastic convergence among different income groups is valid. The implications of the empirical findings for environmental planning and management are discussed in the body of the paper.

Matched MeSH terms: Economic Development
The role of tourism and renewable energy in testing the environmental Kuznets curve in the BRICS countries: fresh evidence from methods of moments quantile regression

Aziz N, Mihardjo LW, Sharif A, Jermsittiparsert K

Environ Sci Pollut Res Int, 2020 Nov;27(31):39427-39441.
PMID: 32651778 DOI: 10.1007/s11356-020-10011-y

BRICS are among the rising nations which drive economic growth by excessive utilization of resources and resulting in environment degradation. Although there is bulk of research on environmental Kuznets curve (EKC), very limited studies explored the scope in context of tourism in BRICS countries. So this research is conducted to explore the association of tourism, renewable energy, and economic growth with carbon emissions by using annual data of BRICS countries from the year 1995 to 2018. By using the recent approach of method of moments quantile regression (MMQR), the finding shows that tourism has stronger significant negative effects from 10th to 40th quantile while the effects are insignificant at remaining quantiles. Furthermore, an inverted U-shape EKC curve is also apparent at all quantiles excluding 10th and 20th quantiles. For renewable energy, the results are found negatively significant across all quantiles (10th-90th) which claim that CO2 emission can be reduced by opting renewable sources. Hence, the empirical results of the current study provide insights for policymakers to consume renewable energy sources for the sustainable economic growth and solution of environmental problems.

Matched MeSH terms: Economic Development
Effects of energy consumption, economic growth, and financial development on carbon emissions: evidence from heterogeneous income groups

Ehigiamusoe KU, Lean HH

Environ Sci Pollut Res Int, 2019 Aug;26(22):22611-22624.
PMID: 31165972 DOI: 10.1007/s11356-019-05309-5

This paper examines the effects of energy consumption, economic growth, and financial development on carbon emissions in a panel of 122 countries. We employ both first-generation and second-generation cointegration and estimation procedures in order to address diverse economic and econometric issues such as heterogeneity, endogeneity, and cross-sectional dependence. We find a cointegration relationship between the variables. Energy consumption, economic growth, and financial development have detrimental effects on carbon emissions in the full sample. When the sample is split into different income groups, we reveal that economic growth and financial development mitigate carbon emissions in high-income group but have the opposite effects in low-income and middle-income groups. The implication of the findings is that energy consumption increases carbon emissions. While high levels of income and financial development decrease carbon emissions, low levels of income and financial development intensify it. Based on the findings, the paper makes some policy recommendations.

Matched MeSH terms: Economic Development
Examining the asymmetric effects of stock markets on Malaysia's air pollution: a nonlinear ARDL approach

Al-Mulali U, Solarin SA, Ozturk I

Environ Sci Pollut Res Int, 2019 Dec;26(34):34977-34982.
PMID: 31664668 DOI: 10.1007/s11356-019-06710-w

The objective of this research is to examine the effects of stock market on air pollution in Malaysia during the period 1980-2017. To realize this aim, a nonlinear autoregressive distributed lag (ARDL) model is constructed. The short results in general revealed that the increase in stock markets will increase CO2 emissions and its significance increases in the long run. Moreover, the decline in stock market will reduce Malaysia's CO2 emissions but only in the long run. From the outcomes obtained, a number of policy recommendations were provided for the investigated country.

Matched MeSH terms: Economic Development
Fulltext The spillover of tourism development on CO2 emissions: a spatial econometric analysis

Jiaqi Y, Yang S, Ziqi Y, Tingting L, Teo BSX

Environ Sci Pollut Res Int, 2022 Apr;29(18):26759-26774.
PMID: 34859343 DOI: 10.1007/s11356-021-17026-z

Climate change and tourism's interaction and vulnerability have been among the most hotly debated topics recently. In this context, the study focuses on how CO2 emissions, the primary cause of global warming and climate change, respond to changes in tourism development. In order to do so, the impact of tourism development on CO2 emissions in the most visited countries is investigated. A panel data from 2000 to 2017 for top 70 tourist countries are analysed using a spatial econometric method to investigate the spatial effect of tourism on environmental pollution. The direct, indirect, and overall impact of tourism on CO2 emissions are estimated using the most appropriate generalized nested spatial econometric (GNS) method. The findings reveal that tourism has a positive direct effect and a negative indirect effect; both are significant at the 1% level. The negative indirect effect of tourism is greater than its direct positive effect, implying an overall significantly negative impact. Further, the outcome of financial development and CO2 emissions have an inverted U-shaped and U-shaped relationship in direct and indirect impacts. Population density, trade openness, and economic growth significantly influence environmental pollution. In addition, education expenditure and infrastructure play a significant moderating role among tourism and environmental pollution. The results have important policy implications as they establish an inverted-U-shaped relationship among tourism and CO2 emissions and indicate that while a country's emissions initially rise with the tourism industry's growth, it begins declining after a limit.

Matched MeSH terms: Economic Development

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