Abstract
Brazil is a heterogenous country with respect to, among others, economic complexity, economic development and environmental quality. This paper examines the relationship between economic complexity and key environmental variables in Brazil. We deviate from the Environmental Kuznets Curve (EKC) literature by focusing on economic complexity instead of economic development alone to explain cross-section and time-series variation in a range of environmental variables. Our motivation for considering economic complexity as a main explanatory variable lies on the consideration that low economic complexity is associated to products which are peripheral on the product space. These are products which are less connected to other products, limiting the opportunities for other economic activities, and therefore limiting the impact on the environment. As economic complexity increases more opportunities are created, the product space becomes denser, and pollution increases. However, at a high enough level of economic complexity, the structural changes bring knowledge-intensive industries, which demands higher-skilled labour force and wider skills of occupations. At this point, economic complexity is associated to decreasing environmental degradation. Using panel data for Brazil we find that waste generation decreases, but forest fires increase with rising complexity. Complexity is not associated to more deforestation or air pollution.
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Notes
- 1.
Poverty headcount ratio at $3.20 a day (2011 PP) (% of population).
- 2.
More precisely, the ECI is calculated as the average complexity of products exported by a specific economy with international comparative advantage, weighted with the share of exports by the said economy.
- 3.
Aguiar et al. (2007) state that 70% of the total deforested area in the Amazon Basin is destined for cattle production. 13 and three per cent were transformed into temporary and permanent harvests, respectively.
- 4.
Oliveira et al. (2011) and Teixeira et al. (2012) add harvested area for the aforementioned agricultural products (in hectares) and cattle units per square kilometre as control variables. IPEA provides data on harvested area by agricultural products, but the panels are rather incomplete and lead to a drop in the number of observations when employed.
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Appendix
Appendix
1.1 Data Sources
Table 8 contains the sources of all the data employed in our study. This includes both data of variables included in the regressions, and data of variables used to construct or transform variables that could not be found in the necessary disaggregation level. The variables are listed in alphabetical order.
1.2 Descriptive Statistics
Tables 9, 10, 11 and 12 provide descriptive statistics for our five panels. Since we find robust evidence for inverted U-shaped relationships between income per capita and solid waste generation, deforestation and forest fires in Sect. 4, the statistics on income per capita are needed to determine whether the turning points of the EKCs lie within the range.
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Swart, J., Brinkmann, L. (2020). Economic Complexity and the Environment: Evidence from Brazil. In: Leal Filho, W., Tortato, U., Frankenberger, F. (eds) Universities and Sustainable Communities: Meeting the Goals of the Agenda 2030. World Sustainability Series. Springer, Cham. https://doi.org/10.1007/978-3-030-30306-8_1
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