نوع مقاله : مقاله پژوهشی
استادیار گروه اقتصاد دانشگاه دریانوردی وعلوم دریایی چابهار
عنوان مقاله [English]
Achieving environmentally sustainable development goals requires identifying new sources of environmental degradation. Therefore, in this study, the impact of shadow economy, information globalization, trade and market size on emissions during the years 1990-2020 in developing countries has been investigated using the Threshold (TAR) model. The results showed that in the short and long term, the shadow economy has a negative impact on environmental pollution in developing countries. In the long run, the co-integration results showed a long-term relationship between the variables in the study. The existence of a long-term relationship between the variables showed that with the increase of the shadow economy, the emission of polluting gases also increased. In the long run, policymakers can use the shadow economy as a tool to influence environmental pollution. In addition, the effect of the threshold index of globalization, trade, market size and shadow economy were estimated in four models. In general, the results of the estimation showed that the shadow economy (SE) has more weight in the output and the emission of pollutant gases increases. Therefore, environmental policymakers and planners to reduce emissions should consider informal and covert activities to make regulations more effective for the environment, as well as the globalization of information and trade to improve the performance of companies and individuals.
Globalization has substantially impacted economic, social, and political aspects in all countries of the world through trade, capital ﬂows, and technology transfer. Since the industrial revolution, governments, to increase their income, have continuously increased the extraction and consumption of renewable and non-renewable resources. There is a close relationship between economic development, trade, urbanization, energy consumption, financial development, foreign direct investment and the use of natural resources. Therefore, there has been an escalation in consumption, and therefore in production to meet demand, which directly impacts the environment. However, several of these determinants are quantiﬁed in the legally established commercial and productive activities regulated and not regulated in terms of environmental impact, although they generate polluting gas emissions. This fact raises the need to investigate new determinants of pollution since the identiﬁcation of new sources of environmental degradation can be used for the analysis of mitigation measures. In this sense, the shadow economy constitutes a source of contamination of the countries’ environment regardless of the level of development. The shadow economy includes all unrecorded activities outside the framework of public and private sector establishments. Thus, the shadow economy can be a hidden determinant of polluting gas emissions due to its ability to avoid environmental regulation policies. In this sense, the shadow economy as a source of pollution persists despite the internationalization of production that has fostered globalization and the growth of the market’s size. Therefore, the governments of various countries, especially those of developing countries, are looking for effective ways to deal with the large shadow economy, understanding its drivers and also trying to reduce high levels of pollution derived from this activity. In this context, this research aims to examine the environmental impact of the shadow economy, globalization, trade, and the market size using a sample of 51 developing countries during 1990–2020.
Our interest is to study the environmental impact of the shadow economy, globalization, trade, and market size in 51 developing countries. The period analyzed in this research is between 1990–2020. The environmental impact is measured through polluting gases in metric tons per person (PEG). The independent variables are the black economy as a percentage of real product per capita (SE), the KOF globalization index, trade as a percentage of real product per capita (T), and the size of the market measured by the population between 15 and 64 years. Following Hansen, we employed a panel threshold regression approach to explore the non-linear effects between the threshold variables and the dependent variable. In this study, the panel threshold model was used to analyze the impact of three threshold variables, informational globalization index (IGI), trade (T), and market size (MS). The main argument supporting the use of threshold regressions is that, from a point, the impact of the regressors on the dependent is different. This hypothesis is based on the theory of the environmental Kuznets curve. In environmental economics, various investigations use threshold regressions to assess the nonlinear link between factors that inﬂuence pollution and emissions. The panel threshold regression model was constructed as follows:
where i and t represent the region and time respectively, qit represents the threshold variable, and γ is the speciﬁc threshold value. I is the exponential function when the condition is true, the value is 1, and 0 in another case, and, ﬁnally, εit is the random error term.
The present study provides a signiﬁcant contribution to both the literature, empirical analyses, and policymakers, since the ﬁrst contribution is the inclusion of the shadow economy as a determinant of environmental pollution. Activities that moved from the formal to the informal economy to evade environmental regulations or payment of environmental taxes were included and are clandestinely damaging the environment. In environmental economics, global polluting gas emissions continue to be under solid attention and analysis; the larger the shadow economy, the greater the increases in total emissions from emissions, although this will depend on time and each country’s economies. Such observations result from the fact that the shadow economy is not constrained by environmental regulations, making controls almost impossible and therefore impacting the environment to a greater extent. The environmental Kuznets curve offers a robust theoretical framework for analysis that allows guiding the search for new sources of environmental pollution. The idea that environmental pollution is a problem that will be resolved with economic development does not necessarily have empirical support in all contexts and particularly in developing countries, which continue to pollute to maintain the economic growth necessary to achieve the social objects. The second contribution of this research is analyzing the combined effect of the shadow economy, globalization, trade, and market size using non-linear methods. Therefore, it extends the current literature to previous studies by further documenting the differences in the effects of globalization, trade, and market size on emissions. The results show that when the threshold variable is an indicator of information globalization, the effect of IGI on environmental quality is positive and significant. The shadow economy and market size increase emissions and reduce their trade. Similarly, we found that when the trade threshold variable is, the effect of the lower threshold is positive and the upper limit is negative and significant. IGI also has a significant positive effect on the spread of infection. Similar results are obtained with the previous model in terms of shadow economy and market size. When the market size is a threshold variable, the negative effects are only below the threshold. The results showed that the index of globalization of information and trade has a positive impact and the shadow economy has a negative impact on the environment. Finally, when the shadow economy is a threshold variable. The effect of the lower and upper thresholds, the effect of SE on the quality of the environment is negative and significant, the globalization of information and trade has reduced emissions and the size of the market is negative and significant.