Does Urbanization Boost Pollution from Transport?

Abstract

The study examines the impacts of urbanization, energy consumption and real GDP on atmospheric pollution from automobile transport in Azerbaijan in the STIRPAT framework. Since the study uses time series variables the unit root properties of employed variables are tested for non-stationarity.Stationarity of the data is tested using conventional Augmented Dickey-Fuller test. The study employs Autoregressive Distributed Lags Bounds Testing (ARDLBT) approach to co-integration. This method is one of the most preferable approaches among alternatives in the case of small samples. Estimation results indicated that the variables are cointegrated, in another word there is a long-run relationship among them. In order to test the quality of the model residuals of the model are tested for the serial correlation, heteroskedasticity, and normality. The model is checked for model misspecification and stability. The results of all abovementioned tests are found to be adequate. The highest impact on pollution among the variables belongs to urbanization which is found to be positive and statistically significant. Energy consumption also has a positive and statistically significant impact on emission. The results also confirm that sustainable development can be reached only keeping the balance among environmental, social and economic factors. Findings of the study may be useful in making appropriate decisions in the fields of diminishing atmospheric pollution from automobile transport caused by urbanization related issues.

Re-evaluating the environmental impacts of tourism: does EKC exist?

“…The study uses CO 2 emissions as a measure of environmental degradation. Mikayilov et al (2017a, b) examined the impacts of urbanization and population on pollution from transportation and did not study the impact of tourism-related income on environmental degradation.…”

“…In this regard, considering the huge positive impacts of tourism on economic growth and the above-mentioned potential adverse effects on the environment, most recent studies have focused on examining the impact of tourism on environmental degradation in the context of comparative analysis of developed and developing countries (Lee and Brahmasrene 2013; León et al 2014; Al-Mulali et al 2014a; Ozturk et al 2015; Paramati et al 2017a), Eastern and Western European Union countries (Paramati et al 2017b), individual countries (Katircioglu 2014a, b; Durbarry and Seetanah 2015), and top 10 tourist destinations (Katircioglu et al 2018a). In addition, a number of empirical studies concluded that trade and urbanization are other drivers of environmental degradation (Katircioglu et al 2016; Mikayilov et al 2017a; Katircioglu et al 2018c; Katircioglu and Katircioglu 2018, inter alia). Trade impacts environment through importing/exporting emission-intensive goods and services, while urbanization causes through different channels, like increased consumption of energy, impacts through the services and consumption of other necessary goods and services.…”

“…The previous researches for Azerbaijan scrutinized the impact of urbanization and population on pollution from transportation (Mikayilov et al 2017a, b), and the relationship between economic growth and CO2 emissions for the period of 1992–2013 and revealed that the EKC hypothesis does not hold for Azerbaijan (Mikayilov et al 2018a). However, these studies did not consider the impact of tourism on environmental degradation.…”

Measuring International Migration in Azerbaijan

“…Therefore, it was identified that these 2 variables are stationary whereas other 9 variables are not. (Note that, [76] also found GDP variable to be I(1) as a result of PP test). Owing to this condition, the first difference of these 9 variables and level forms of the stationary (2) variables are used in the analysis.…”

The Impacts of Industrialization on Freight Movement in China

“…Following the lag length criteria, lag 1 is recommended from the test, and there is no cointegration between the variables at the 0.05 level for both trace test and maximum eigenvalue (see Figure A4). However, in this study, we also carried out the autoregressive distributed lag (ARDL) test for cointegration, since the ARDL cointegration test outperforms all the other cointegration tests for the small sample size (Pesaran et al 2001;Mikayilov et al 2017).…”