IDEAS home Printed from https://ideas.repec.org/h/elg/eechap/14533_6.html
   My bibliography  Save this book chapter

Uncertainty and Projections of the Demand for Mail

In: Multi-Modal Competition and the Future of Mail

Author

Listed:
  • Frédérique Fève
  • Jean-Pierre Florens
  • Leticia Veruete-McKay
  • Frank Rodriguez
  • Soterios Steri
  • Frank Rodriguez

Abstract

This compilation of original papers selected from the 19th Conference on Postal and Delivery Economics and authored by an international cast of economists, lawyers, regulators and industry practitioners addresses perhaps the most significant problem that has ever faced the postal sector – electronic competition from information and communication technologies. This has increased significantly over the last few years with a consequent serious drop in mail volume.

Suggested Citation

  • Frédérique Fève & Jean-Pierre Florens & Leticia Veruete-McKay & Frank Rodriguez & Soterios Steri & Frank Rodriguez, 2012. "Uncertainty and Projections of the Demand for Mail," Chapters, in: Michael A. Crew & Paul R. Kleindorfer (ed.), Multi-Modal Competition and the Future of Mail, chapter 6, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:14533_6
    as

    Download full text from publisher

    File URL: https://www.elgaronline.com/view/9780857935816.00011.xml
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Veruete-McKay Leticia & Soteri Soterios & Nankervis John C. & Rodriguez Frank, 2011. "Letter Traffic Demand in the UK: An Analysis by Product and Envelope Content Type," Review of Network Economics, De Gruyter, vol. 10(3), pages 1-28, September.
    2. Jean-Pierre Florens & Vêlayoudom Marimoutou & Anne Peguin-Feissolle, 2007. "Econometric Modeling and Inference," Post-Print halshs-00390164, HAL.
    3. Florens,Jean-Pierre & Marimoutou,Velayoudom & Peguin-Feissolle,Anne, 2007. "Econometric Modeling and Inference," Cambridge Books, Cambridge University Press, number 9780521700061, September.
    4. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809.
    5. Florens,Jean-Pierre & Marimoutou,Velayoudom & Peguin-Feissolle,Anne, 2007. "Econometric Modeling and Inference," Cambridge Books, Cambridge University Press, number 9780521876407, April.
    Full references (including those not matched with items on IDEAS)

    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. Xiaohong Chen & Andres Santos, 2018. "Overidentification in Regular Models," Econometrica, Econometric Society, vol. 86(5), pages 1771-1817, September.
    2. Julio Vicente Cateia, 2019. "Guinea-Bissau Trade: A Panel Data Analysis," Asian Development Policy Review, Asian Economic and Social Society, vol. 7(4), pages 277-296, December.
    3. Atangana Ondoa, Henri & Tomo, Christian Parfait, 2022. "Déterminants des ménages et accès au crédit dans les tontines au Cameroun [Determinants of households and access to credit in Cameroon]," MPRA Paper 113629, University Library of Munich, Germany, revised Jun 2022.
    4. An, Lihua & Nkurunziza, Sévérien & Fung, Karen Y. & Krewski, Daniel & Luginaah, Isaac, 2009. "Shrinkage estimation in general linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2537-2549, May.
    5. Garritt L. Page & Ernesto San Martín & David Torres Irribarra & Sébastien Van Bellegem, 2024. "Temporally Dynamic, Cohort-Varying Value-Added Models," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 1074-1103, September.
    6. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    7. Bhattacharya, Prasad S. & Thomakos, Dimitrios D., 2008. "Forecasting industry-level CPI and PPI inflation: Does exchange rate pass-through matter?," International Journal of Forecasting, Elsevier, vol. 24(1), pages 134-150.
    8. Seitz, Franz & Baumann, Ursel & Albuquerque, Bruno, 2015. "The information content of money and credit for US activity," Working Paper Series 1803, European Central Bank.
    9. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2016. "Forecasting US real private residential fixed investment using a large number of predictors," Empirical Economics, Springer, vol. 51(4), pages 1557-1580, December.
    10. Wolfgang Polasek, 2013. "Forecast Evaluations for Multiple Time Series: A Generalized Theil Decomposition," Working Paper series 23_13, Rimini Centre for Economic Analysis.
    11. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
    12. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
    13. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.
    14. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
    15. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    16. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    17. Michael Artis & Anindya Banerjee & Massimiliano Marcellino, "undated". "Factor forecasts for the UK," Working Papers 203, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    18. Ronald Bewley & Minxian Yang, 2006. "A hybrid forecasting approach for piece-wise stationary time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 513-527.
    19. Giancarlo Lutero & Marco Marini, 2010. "Direct vs Indirect Forecasts of Foreign Trade Unit Value Indices," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 12(2-3), pages 73-96, October.
    20. Pär Österholm, 2009. "Incorporating Judgement in Fan Charts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 387-415, June.

    More about this item

    Keywords

    Economics and Finance;

    Statistics

    Access and download statistics

    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:elg:eechap:14533_6. 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: Darrel McCalla (email available below). General contact details of provider: http://www.e-elgar.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.