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Atmósfera

Print version ISSN 0187-6236

Abstract

ANSER, Muhammad Khalid et al. The Role of Sustainable Technological Innovations in the Relationship between Freight Pricing and Environmental Degradation: Evidence from a Panel of 39 R&D economies. Atmósfera [online]. 2022, vol.35, n.2, pp.395-420.  Epub May 16, 2022. ISSN 0187-6236.  https://doi.org/10.20937/atm.52922.

This study is in line with the United Nations Framework Convention on Climate Change (UNFCCC) to evaluate the post-Paris Agreement (COP21) through technological innovations and carbon pricing in a panel of 39 R&D economies from 1995 to 2018. The results show that sustainable technological innovations and smart applications of insurance and financial services help decrease GHG emissions in the lowest to highest quantile distribution. In contrast, air transportation freight, air freight pricing, and foreign direct investment (FDI) inflows escalate GHG emissions due to unsustainable logistics activities, inefficient freight pricing, and dirty production, which confirmed the ‘pollution haven’ hypothesis across countries. The impact of air freight revenues has a differential impact on GHG emissions in the different quantiles’ distribution, as in the lowest quantiles (i.e., τ0.2 to τ0.4), air freight revenues increase GHG, whereas, at the highest quantiles’ distribution (i.e., τ0.9) emissions decrease. Thus, the viability of air freight revenues is further assessed using Panel Granger causality and panel innovation matrix. The results show the bidirectional causality between i) air freight pricing and GHG emissions, ii) air transportation freight (and freight pricing, freight revenues, FDI) and technology innovations, iii) FDI and air freight revenues, while there is a unidirectional causality running from i) insurance and financial services to GHG emissions, ii) GHG emissions to technological innovations and FDI inflows, and iii) air transportation freight to FDI inflows.

Keywords : Technological innovation, Air freight; Freight revenue, GHG emissions, Inbound FDI, Panel regression.

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