Demand for trucks in brazil: an econometric approach
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | https://hdl.handle.net/10438/27732 |
Resumo: | The demand for trucks in Brazil has historically been an unusual choice for econometric analysis, resulting in a scarcity of studies on this subject, inconsistent with the economic relevance of road freight transport and its historical dominance over any other means of transport in the country. This paper addresses the demand for trucks in Brazil, making extensive use of secondary data in multiple linear regression models. Besides the choice of the subject itself, it innovates by including expectational variables to the analysis. In comparison to the surveyed studies on passenger car demand, further improvements were undertaken, as the split of GDP in sectors (agriculture, industry and services), the use of lagged variables, and a nineteen years long timeframe (from 1996 to 2015). The results deepen the knowledge about the truck market behaviour and allow an improvement of the quality of decision making in the truck industry. |
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Manfredini, GonçalvesDemais unidades::RPCA2019-07-24T11:55:12Z2019-07-24T11:55:12Z2018https://hdl.handle.net/10438/27732The demand for trucks in Brazil has historically been an unusual choice for econometric analysis, resulting in a scarcity of studies on this subject, inconsistent with the economic relevance of road freight transport and its historical dominance over any other means of transport in the country. This paper addresses the demand for trucks in Brazil, making extensive use of secondary data in multiple linear regression models. Besides the choice of the subject itself, it innovates by including expectational variables to the analysis. In comparison to the surveyed studies on passenger car demand, further improvements were undertaken, as the split of GDP in sectors (agriculture, industry and services), the use of lagged variables, and a nineteen years long timeframe (from 1996 to 2015). The results deepen the knowledge about the truck market behaviour and allow an improvement of the quality of decision making in the truck industry.engTruck marketTruck demand in BrazilTruck salesCommercial cargo vehicles demandAutomotive industryAutomotive market analysisMultiple linear regressionEconometric modelExpectational variablesSector-sensitive demand for transportationEconomiaTransporte rodoviário de cargaModelos econométricosCaminhãoDemand for trucks in brazil: an econometric approachinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVRede de Pesquisa e Conhecimento AplicadoLICENSElicense.txtlicense.txttext/plain; charset=utf-84707https://repositorio.fgv.br/bitstreams/8946c119-a8b8-4699-97df-3e7e5da589a3/downloaddfb340242cced38a6cca06c627998fa1MD52ORIGINALGonçalves Manfredini - Paper 1 - Truck Market - 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dc.title.eng.fl_str_mv |
Demand for trucks in brazil: an econometric approach |
title |
Demand for trucks in brazil: an econometric approach |
spellingShingle |
Demand for trucks in brazil: an econometric approach Manfredini, Gonçalves Truck market Truck demand in Brazil Truck sales Commercial cargo vehicles demand Automotive industry Automotive market analysis Multiple linear regression Econometric model Expectational variables Sector-sensitive demand for transportation Economia Transporte rodoviário de carga Modelos econométricos Caminhão |
title_short |
Demand for trucks in brazil: an econometric approach |
title_full |
Demand for trucks in brazil: an econometric approach |
title_fullStr |
Demand for trucks in brazil: an econometric approach |
title_full_unstemmed |
Demand for trucks in brazil: an econometric approach |
title_sort |
Demand for trucks in brazil: an econometric approach |
author |
Manfredini, Gonçalves |
author_facet |
Manfredini, Gonçalves |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Demais unidades::RPCA |
dc.contributor.author.fl_str_mv |
Manfredini, Gonçalves |
dc.subject.eng.fl_str_mv |
Truck market Truck demand in Brazil Truck sales Commercial cargo vehicles demand Automotive industry Automotive market analysis Multiple linear regression Econometric model Expectational variables Sector-sensitive demand for transportation |
topic |
Truck market Truck demand in Brazil Truck sales Commercial cargo vehicles demand Automotive industry Automotive market analysis Multiple linear regression Econometric model Expectational variables Sector-sensitive demand for transportation Economia Transporte rodoviário de carga Modelos econométricos Caminhão |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Transporte rodoviário de carga Modelos econométricos Caminhão |
description |
The demand for trucks in Brazil has historically been an unusual choice for econometric analysis, resulting in a scarcity of studies on this subject, inconsistent with the economic relevance of road freight transport and its historical dominance over any other means of transport in the country. This paper addresses the demand for trucks in Brazil, making extensive use of secondary data in multiple linear regression models. Besides the choice of the subject itself, it innovates by including expectational variables to the analysis. In comparison to the surveyed studies on passenger car demand, further improvements were undertaken, as the split of GDP in sectors (agriculture, industry and services), the use of lagged variables, and a nineteen years long timeframe (from 1996 to 2015). The results deepen the knowledge about the truck market behaviour and allow an improvement of the quality of decision making in the truck industry. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018 |
dc.date.accessioned.fl_str_mv |
2019-07-24T11:55:12Z |
dc.date.available.fl_str_mv |
2019-07-24T11:55:12Z |
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https://hdl.handle.net/10438/27732 |
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eng |
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eng |
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openAccess |
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