The role of shadow economies in ecological footprint quality: empirical evidence from Turkey

Köksal, Cihat; Işık, Mehtap; Katırcıoğlu, Salih

doi:10.1007/s11356-020-07956-5

Cited by 67 publications

(31 citation statements)

References 56 publications

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“…Few studies in the previous literature explored the linkage between shadow economy and environmental pollution. These studies found a positive association between shadow economy and environmental pollution, for example, Biswas et al (2012), Elgin and Oztunali (2014), Hille (2018), Chen et al (2018a, b), Köksal et al (2020), and Pang et al (2020). According to the previously mentioned literature, due to the existence of the shadow economy, the environmental standard is lax in these countries, and therefore the firms take the advantage of these lax environmental standards and produce different products without taking care of environmental standards, and therefore it brings an increase in air pollution in these countries.…”

Section: Introductionmentioning

confidence: 95%

“…In this regard, Pang et al (2019) explored the association between the shadow economy and air pollution for three Chinese provinces, and the empirical results confirm that the shadow economy is the most important source of an increase in air pollution. In the same perspective, Köksal et al (2020) explored the association between shadow economy and ecological footprints for the case of Turkey during the time period from 1961 to 2014. The results of the study confirmed that in the long run, shadow economy plays a positive role in surging up the ecological footprints.…”

Section: Literature Reviewmentioning

confidence: 99%

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RETRACTED ARTICLE: The shadow economy in South Asia: dynamic effects on clean energy consumption and environmental pollution

Sohail

Ullah

Majeed

et al. 2021

Environ Sci Pollut Res

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This study explores the symmetric and asymmetric effects of the shadow economy on clean energy and air pollution of South Asian countries over the period 1991–2019. The short-run ARDL findings for the clean energy model suggest that shadow economy increases clean energy consumption in Pakistan and Sri Lanka, whereas this effect is negative for India and insignificant for other countries. The long-run results indicate the adverse impact only for India and the effects of tax revenue on clean energy are positively significant in Sri Lanka while negatively signiicant in Nepal and Bangladesh. Institutional quality significantly increases clean energy in Pakistan, India, and Nepal. However, in the case of Pakistan and Nepal, institutional quality deteriorated the environmental quality. The results for the pollution model confer that shadow economy increases emissions in Pakistan, decreases in Bangladesh and Nepal, and has no effect in India and Sri Lanka. The nonlinear ARDL results reveal that the positive components of the shadow economy significantly increase clean energy consumption only in Pakistan; however, the negative components of the shadow economy are negatively significant in all countries except Sri Lanka and Nepal. However, the negative component of the informal sector of the economy reduces CO2 emissions in India and increases CO2 emissions in Bangladesh and Nepal. The results offer important policy implications for achieving clean energy and better environmental quality in South Asian countries.

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Section: Introductionmentioning

confidence: 95%

Section: Literature Reviewmentioning

confidence: 99%

RETRACTED ARTICLE: The shadow economy in South Asia: dynamic effects on clean energy consumption and environmental pollution

Sohail

Ullah

Majeed

et al. 2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…The first view is about the transformation of the capitalist system; the second view focuses on the sixth Kondratieff wave, and the third view is related to green growth. Following the literature on Turkey that used various factors, such as financial development (Ozturk and Acaravci, 2013;Katircioğlu ve Taspinar, 2017), urbanization and industrialization (Pata, 2018a(Pata, , 2018b(Pata, , 2018c, income inequality (Uzar and Eyuboglu, 2019), shadow economy (Köksal et al 2020), hydropower energy (Pata and Aydin, 2020), renewable energy (Sharif et al 2020), and information and communications technologies (Barış-Tüzemen et al 2020), we add output volatility as another factor and find evidence in favor of the EKC hypothesis. After determining the long-run relationship between output volatility and CO 2 , we run the restricted ECM to measure the short-run relationship using the ARDL (2,1,1,4) model.…”

Section: The Findings Of the Ardl Bounds Testmentioning

confidence: 99%

“…The findings of most of the studies support the EKC hypothesis (see Lise, 2006;Yavuz, 2014;Shahbaz et al, 2013;Tutulmaz, 2015;Bölük and Mert, 2015), whereas some of them do not support the EKC hypothesis (see Lise and Montfort, 2007;Akbostancı et al, 2009;Ozturk and Acaravci, 2010;Katircioğlu and Katircioğlu,2018a). Aside economic growth, a large part of the literature focuses on the relationship between carbon emission and other factors, such as agriculture (Dogan, 2016), foreign direct investment (Balibey, 2015;Seker et al, 2015;Gökmenoğlu and Taspinar, 2016), tourism (Vita et al, 2015), trade openness (Halicioglu, 2009;Ertugrul et al, 2016;Ozatac, 2017;Pata 2019), export product diversification (Gozgor and Can, 2016), fiscal policy (Katircioglu and Katircioglu, 2018b), financial development (Ozturk and Acaravci, 2013;Katircioğlu and Taspinar, 2017), urbanization and industrialization (Pata, 2018a(Pata, , 2018b(Pata, , 2018c, income inequality (Uzar and Eyuboglu, 2019), shadow economy (Köksal et al 2020), hydropower energy (Pata and Aydin, 2020), renewable energy (Sharif et al 2020), as well as information and communications technologies (Barış-Tüzemen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Output Volatility on CO2 Emissions in Turkey: Testing EKC Hypothesis with Fourier Stationarity Test

Genç

Ekinci

Sakarya

2021

Preprint

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This study uses the environmental Kuznets curve (EKC) approach to determine the dynamic short- and long-term impacts of the volatility of economic growth (VOL) on carbon dioxide (CO2) emissions in Turkey from 1980 to 2016. The results of the Autoregressive Distributed Lag (ARDL) approach indicate that there is a long-run relationship between CO2, per capita real GDP, and VOL. The coefficients obtained from the ARDL estimation indicate that economic growth increases CO2 emissions, but VOL decreases CO2 emissions in the long run. However, the coefficients obtained from the ARDL error correction model show that VOL increases CO2 emissions in the short run. We also find that the EKC is valid in Turkey.

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“…Furthermore, urbanism and entire population of the world have been involved in the research results for comparison aims as well. Koksal, Işik and Katircioğlu [10] state that developed economies concentrate more on light manufacturing industries including apparel, leather, wood, metal products and agribusiness.…”

Section: Literature Reviewmentioning

confidence: 99%

The Linkage among Sea Transportation, Trade Liberalization and Industrial Development in the context of Carbon Dioxide Emissions: An Empirical Investigation from China

Kalaycı

Özden

2020

Preprint

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The major goal of this paper is to focus on the existing literature regarding the linkage between maritime, trade liberalization and industrial development in the context of CO2 by using econometrical model. In this context, it is attempted to reveal the effects of independent variables on CO2 (dependent variable) for China from 1980 to 2013 (annual data) by implementing Phillips-Perron (PP), Zivot-Andrews unit root tests, FMOLS, DOLS, CCR, ARDL and GMM methods. According to results of FMOLS, DOLS and CCR models there is a long-term stable relationship between sea transportation, trade liberalization, industrial development and carbon dioxide emissions which is proved empirically. Similarly, Short term ARDL estimation results reveal that the main determinants of CO2 in the short-run are changed in industrial development and maritime transport at 1% significance level. Table 6 summarizes the short-term ARDL results and the findings regarding the error correction model. According to Table 6, error correction model works in order to reach short-run adjustment. In the short term, approximately 78% of shocks in industrial development, maritime transport and trade liberalization are compensated within a period of time and the system is re-established in the long term. China produced half of the 1.2 million electric media used worldwide; the government directs its attention to the rehabilitation and reuse of all these lithium-ion batteries. Large-scale production of biofuels can still be several years away. Crude oil might be very difficult to promote alternative fuels on a national scale unless crude oil prices surge so high as to become unaffordable. Authorities underline: China will become the world’s number one economy. Now renewable energy will be more important, which should be encouraged to use by government on transportation so as to reduce the CO2 emissions. However, China can be leader excess oil use for transport if they want to dominate the economy worldwide.

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The role of shadow economies in ecological footprint quality: empirical evidence from Turkey

Cited by 67 publications

References 56 publications

RETRACTED ARTICLE: The shadow economy in South Asia: dynamic effects on clean energy consumption and environmental pollution

RETRACTED ARTICLE: The shadow economy in South Asia: dynamic effects on clean energy consumption and environmental pollution

The Impact of Output Volatility on CO2 Emissions in Turkey: Testing EKC Hypothesis with Fourier Stationarity Test

The Linkage among Sea Transportation, Trade Liberalization and Industrial Development in the context of Carbon Dioxide Emissions: An Empirical Investigation from China

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