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Amazon deforestation and CO2 emissions: A macroeconomic approach using the GVAR.

  • Published In: Journal of Regional Science, 2025, v. 65, n. 1. P. 189 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Attílio, Luccas Assis 3 of 3

Abstract

We analyzed the relationship between economic variables, Amazon deforestation, and CO2 emissions in Brazil. We used a macroeconomic approach of a system of open economies (global vector autoregressive [GVAR]). We constructed the international economy using 34 countries, representing 77% of the world GDP and 80% of world CO2 emissions. GVAR allows us to simulate the world economy, capture spillover effects, incorporate the externality of gas emissions, treating Brazil as a small open economy, and including trade integration in the analysis. We found that domestic and external shocks affect Amazon deforestation and CO2 emissions; the principal external shock is the Chinese one, followed by the European and the US shocks. China, directly and indirectly, affects CO2 emissions and deforestation in Brazil through two channels (exchange rates and policy rates). The estimates showed that Brazilian currency and commodity prices are relevant for deforestation, while industrial production is for gas emissions. Other results are that (i) the Brazilian economy affects CO2 emissions in Latin America (and the principal influence of China is on Asia), and (ii) the Chinese shock loses importance when using bilateral trade in 1999–2001, when China was not a fundamental trade partner of Brazil. Alternative model configurations demonstrate that soybean prices and Argentina influence Brazilian carbon emissions and Amazon deforestation. Specifically, soybean prices emerge as a major driver of carbon emissions. These results suggest that geography and trade integration matter to understanding Amazon deforestation and CO2 emissions. Our estimates highlight the importance of government policies and international cooperation in curbing Amazon deforestation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Regional Science. 2025/01, Vol. 65, Issue 1, p189
  • Document Type:Article
  • Subject Area:Economics
  • Publication Date:2025
  • ISSN:0022-4146
  • DOI:10.1111/jors.12738
  • Accession Number:183952074
  • Copyright Statement:Copyright of Journal of Regional Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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