IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i15p6039-d390651.html
   My bibliography  Save this article

Air Transportation Income and Price Elasticities in Remote Areas: The Case of the Brazilian Amazon Region

Author

Listed:
  • Rodrigo V. Ventura

    (IBGE Brazilian Institute of Geography and Statistics, Rio de Janeiro 20031170, Brazil
    COPPE Production Engineering Program, UFRJ Federal University of Rio de Janeiro, Rio de Janeiro 21941450, Brazil)

  • Manoela Cabo

    (IBGE Brazilian Institute of Geography and Statistics, Rio de Janeiro 20031170, Brazil
    COPPE Transportation Engineering Program, UFRJ Federal University of Rio de Janeiro, Rio de Janeiro 21941450, Brazil)

  • Rafael Caixeta

    (MCA Trade, Rio de Janeiro 22775005, Brazil)

  • Elton Fernandes

    (COPPE Production Engineering Program, UFRJ Federal University of Rio de Janeiro, Rio de Janeiro 21941450, Brazil)

  • Vicente Aprigliano Fernandes

    (Instituto de Geografia, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile)

Abstract

The literature, aimed at understanding the income–price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income–price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there is no empirical research. This paper analyses the price–income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitivity regarding local income and an airline´s price variations than those in flights among capitals. The higher difference is in the income elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.

Suggested Citation

  • Rodrigo V. Ventura & Manoela Cabo & Rafael Caixeta & Elton Fernandes & Vicente Aprigliano Fernandes, 2020. "Air Transportation Income and Price Elasticities in Remote Areas: The Case of the Brazilian Amazon Region," Sustainability, MDPI, vol. 12(15), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6039-:d:390651
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/15/6039/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/15/6039/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xavier Fageda & Ancor Suárez-Alemán & Tomás Serebrisky & Reinaldo Fioravanti, 2019. "Air transport connectivity of remote regions: the impacts of public policies," Regional Studies, Taylor & Francis Journals, vol. 53(8), pages 1161-1169, August.
    2. Kauano, Érico Emed & Silva, José Maria Cardoso & Diniz Filho, José Alexandre Felizola & Michalski, Fernanda, 2020. "Do protected areas hamper economic development of the Amazon region? An analysis of the relationship between protected areas and the economic growth of Brazilian Amazon municipalities," Land Use Policy, Elsevier, vol. 92(C).
    3. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380, October.
    4. Abate, Megersa, 2016. "Economic effects of air transport market liberalization in Africa," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 326-337.
    5. Morlotti, Chiara & Cattaneo, Mattia & Malighetti, Paolo & Redondi, Renato, 2017. "Multi-dimensional price elasticity for leisure and business destinations in the low-cost air transport market: Evidence from easyJet," Tourism Management, Elsevier, vol. 61(C), pages 23-34.
    6. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284, October.
    7. Brons, Martijn & Pels, Eric & Nijkamp, Peter & Rietveld, Piet, 2002. "Price elasticities of demand for passenger air travel: a meta-analysis," Journal of Air Transport Management, Elsevier, vol. 8(3), pages 165-175.
    8. Wang, Kun & Zhang, Anming & Zhang, Yahua, 2018. "Key determinants of airline pricing and air travel demand in China and India: Policy, ownership, and LCC competition," Transport Policy, Elsevier, vol. 63(C), pages 80-89.
    9. Nelson Granados & Alok Gupta & Robert J. Kauffman, 2012. "Online and Offline Demand and Price Elasticities: Evidence from the Air Travel Industry," Information Systems Research, INFORMS, vol. 23(1), pages 164-181, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiajun Shen & Guangchuan Yang, 2020. "Crash Risk Assessment for Heterogeneity Traffic and Different Vehicle-Following Patterns Using Microscopic Traffic Flow Data," Sustainability, MDPI, vol. 12(23), pages 1-18, November.
    2. Marek Drliciak & Jan Celko & Michal Cingel & Dusan Jandacka, 2020. "Traffic Volumes as a Modal Split Parameter," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    3. Vicente Aprigliano Fernandes & Ricardo R. Pacheco & Elton Fernandes & Manoela Cabo & Rodrigo V. Ventura & Rafael Caixeta, 2021. "Air Transportation, Economy and Causality: Remote Towns in Brazil’s Amazon Region," Sustainability, MDPI, vol. 13(2), pages 1-14, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rodrigo Acuna-Agost & Eoin Thomas & Alix Lhéritier, 2021. "Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 213-226, June.
    2. Yilmazkuday, Hakan, 2021. "Profit margins in U.S. domestic airline routes," Transport Policy, Elsevier, vol. 114(C), pages 245-251.
    3. Becken, Susanne & Carmignani, Fabrizio, 2020. "Are the current expectations for growing air travel demand realistic?," Annals of Tourism Research, Elsevier, vol. 80(C).
    4. Button, Kenneth & Martini, Gianmaria & Scotti, Davide & Volta, Nicola, 2019. "Airline regulation and common markets in Sub-Saharan Africa," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 81-91.
    5. Bernardo, Valeria & Fageda, Xavier & Teixidó, Jordi, 2024. "Flight ticket taxes in Europe: Environmental and economic impact," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    6. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    7. Naima Chrid & Sami Saafi & Mohamed Chakroun, 2021. "Export Upgrading and Economic Growth: a Panel Cointegration and Causality Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 811-841, June.
    8. Patricio Aroca & Juan Gabriel Brida & Juan Sebastián Pereyra & Serena Volo, 2014. "Tourism statistics: correcting data inadequacy using coarsened exact matching," BEMPS - Bozen Economics & Management Paper Series BEMPS22, Faculty of Economics and Management at the Free University of Bozen.
    9. Fulvia Pennoni & Beata Bal-Domańska, 2022. "NEETs and Youth Unemployment: A Longitudinal Comparison Across European Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 739-761, July.
    10. Marco Angrisani & Kevin Foster & Marcin Hitczenko, 2015. "The 2013 Survey of Consumer Payment Choice: technical appendix," Research Data Report 15-5, Federal Reserve Bank of Boston.
    11. Lynn, Peter & Bosch, Oriol, 2021. "Methodological lessons from the pilot longitudinal survey on debt advice," ISER Working Paper Series 2021-03, Institute for Social and Economic Research.
    12. Caudill, Jonathan W. & Getty, Ryan & Smith, Rick & Patten, Ryan & Trulson, Chad R., 2013. "Discouraging window breakers: The lagged effects of police activity on crime," Journal of Criminal Justice, Elsevier, vol. 41(1), pages 18-23.
    13. Adolfo Maza & Paula Gutiérrez-Portilla, 2022. "Outward FDI and exports relation: A heterogeneous panel approach dealing with cross-sectional dependence," International Economics, CEPII research center, issue 170, pages 174-189.
    14. Abayomi Oredegbe, 2022. "Competition and Banking Industry Stability: How Do BRICS and G7 Compare?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 7-31, March.
    15. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    16. Edward Frees & Jee-Seon Kim, 2006. "Multilevel Model Prediction," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 79-104, March.
    17. Jun Zhao & Xiucheng Dong & Kangyin Dong, 2021. "Can agglomeration of producer services reduce urban–rural income inequality? The case of China," Australian Economic Papers, Wiley Blackwell, vol. 60(4), pages 736-762, December.
    18. LU, Yi & Zhao, Jianting & Wu, Xueying & Lo, Siu Ming, 2020. "Escaping to nature in pandemic: a natural experiment of COVID-19 in Asian cities," SocArXiv rq8sn, Center for Open Science.
    19. Kaixing Huang, 2015. "The Economic Impacts of Global Warming on Agriculture: the Role of Adaptation," School of Economics and Public Policy Working Papers 2015-20, University of Adelaide, School of Economics and Public Policy.
    20. Torben Dall Schmidt & Peter Sandholt Jensen, 2012. "Social networks and regional recruitment of foreign labour: Firm recruitment methods and spatial sorting in Denmark," Papers in Regional Science, Wiley Blackwell, vol. 91(4), pages 795-821, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6039-:d:390651. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.