IDEAS home Printed from https://ideas.repec.org/a/taf/specan/v17y2022i1p1-6.html
   My bibliography  Save this article

Raising the bar (19)

Author

Listed:
  • Paul Elhorst
  • Maria Abreu
  • Pedro Amaral
  • Arnab Bhattacharjee
  • Steven Bond-Smith
  • Coro Chasco
  • Luisa Corrado
  • Jan Ditzen
  • Daniel Felsenstein
  • Franz Fuerst
  • Philip McCann
  • Vassilis Monastiriotis
  • Francesco Quatraro
  • Umed Temursho
  • Jihai Yu

Abstract

This editorial summarizes the papers published in issue 17(1) (2022). This issue begins with a second editorial calling on researchers to publish replication results from previous studies. The first paper applies a spatiotemporal Bayesian hierarchical model for understanding the dynamics of second home ownership in Corsica. The second paper determines the optimal time to invest in a new airport using real options analysis. The third paper employs unit root tests to provide empirical evidence that environmental policy changes have not been effective up to now. The fourth paper provides empirical evidence that regional spillover effects should play a crucial role in the policy discussion about climate change. The fifth paper forecasts the direct impact of climate change on crop yields in the agricultural sector and the indirect impacts on other sectors of the Brazilian economy up to 2100. The sixth paper investigates whether the percentage of women in national parliaments positively affects public expenditures on social needs both internally and in neighbouring countries. The seventh paper sets out a general framework for store sales evaluation and prediction.

Suggested Citation

  • Paul Elhorst & Maria Abreu & Pedro Amaral & Arnab Bhattacharjee & Steven Bond-Smith & Coro Chasco & Luisa Corrado & Jan Ditzen & Daniel Felsenstein & Franz Fuerst & Philip McCann & Vassilis Monastirio, 2022. "Raising the bar (19)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 17(1), pages 1-6, January.
  • Handle: RePEc:taf:specan:v:17:y:2022:i:1:p:1-6
    DOI: 10.1080/17421772.2022.2018168
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/17421772.2022.2018168
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/17421772.2022.2018168?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:taf:specan:v:17:y:2022:i:1:p:1-6. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RSEA20 .

    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.