Business cycle and uncertainties: Evaluating the behaviour of the automotive industry in relation to the COVID-19 period in Brazil

Submitted by Lorenza Monaco, UCL Institute for Innovation and Public Purpose on Thu, 12/30/2021 - 11:17
in

Publication Type:

Journal Article

Authors:

de Andrade, G.G.; Betarelli, A.A., Jr.; da Silva, C.A.G.; Faria, W.R.

Source:

International Journal of Automotive Technology and Management, Inderscience Publishers, Volume 21, Number 4, p.273-294 (2021)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120983881&doi=10.1504%2fIJATM.2021.119403&partnerID=40&md5=6e57e01238162348d5bc509aed943dfc

Keywords:

Automobiles, Automotive industry, Automotives, Autoregressive vectors, Business cycles, Commercial vehicles, Convergence time, COVID-19, Economics, Paper analysis, Short-term forecasts, Tax reductions, uncertainty, Value engineering, VAR models

Abstract:

Drawing on autoregressive vector (VAR) model, this paper analyses supply and demand of automobiles and light commercial vehicles in Brazil from January 2012 to February 2020. Then, it points out how the automotive activity in the country responds to shocks of political proposals or unexpected shocks. The results on the short-term forecast suggest that credit, income, price, and tax influence the business cycles of the industry and returns to a stationary trend over a period of five months. Therefore, the analysis suggests that the automotive activity has a capacity for quick recovery in face of an eventual adverse shock, such as COVID-19 outbreak. This convergence time can be shortened by credit and tax reduction policies, as well as the new automation and electrification technologies in the automotive industry. Copyright © 2021 Inderscience Enterprises Ltd.

  • Share this

  GIS Gerpisa / gerpisa.org
  4 Avenue des Sciences, 91190 Gif-sur-Yvette

Copyright© Gerpisa
Concéption Tommaso Pardi
Administration Alexandra Kuyo, Lorenza Monaco,, 

Powered by Drupal, an open source content management system