IDEAS home Printed from https://ideas.repec.org/h/spr/adspcp/978-3-662-05617-2_10.html
   My bibliography  Save this book chapter

Locally Weighted Maximum Likelihood Estimation: Monte Carlo Evidence and an Application

In: Advances in Spatial Econometrics

Author

Listed:
  • Daniel P. McMillen

    (University of Illinois)

  • John F. McDonald

    (University of Illinois)

Abstract

Even small cities have complicated spatial patterns that are difficult to model adequately with a small number of explanatory variables. Shopping centers, parks, lakes, and the like have local effects on variables such as housing prices, land values, and population density. Proximity to such sites can be included as explanatory variables, but the number of potential sites is large and some may be unknown beforehand. Coefficient estimates are biased when relevant sites are omitted, but are inefficient when unimportant ones are included. Moreover, functional forms are often complex for urban spatial patterns even in the absence of local peaks and valleys.

Suggested Citation

  • Daniel P. McMillen & John F. McDonald, 2004. "Locally Weighted Maximum Likelihood Estimation: Monte Carlo Evidence and an Application," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 10, pages 225-239, Springer.
    • Handle: RePEc:spr:adspcp:978-3-662-05617-2_10
    DOI: 10.1007/978-3-662-05617-2_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Fang, Lu & Munneke, Henry J., 2021. "A spatial analysis of borrowers’ mortgage termination decision – A nonparametric approach," Regional Science and Urban Economics, Elsevier, vol. 86(C).
    2. Daniel P. McMillen & Elizabeth T. Powers, 2017. "The eldercare landscape: Evidence from California," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 139-157, September.
    3. Anna Gloria Billé, 2013. "Computational Issues in the Estimation of the Spatial Probit Model: A Comparison of Various Estimators," The Review of Regional Studies, Southern Regional Science Association, vol. 43(2,3), pages 131-154, Winter.
    4. Cohen, Jeffrey P. & Coughlin, Cletus C. & Crews, Jonas, 2019. "Traffic noise in Georgia: Sound levels and inequality," Journal of Housing Economics, Elsevier, vol. 44(C), pages 150-165.
    5. Ko, Kate, 2009. "Home Prices and Urban Corridors," 50th Annual Transportation Research Forum, Portland, Oregon, March 16-18, 2009 207607, Transportation Research Forum.
    6. Jeffrey P. Cohen & Cletus C. Coughlin & Jonas C. Crews, 2017. "Airport Noise in Atlanta: The Inequality of Sound," Working Papers 2017-15, Federal Reserve Bank of St. Louis.
    7. Sabina Buczkowska & Nicolas Coulombel & Matthieu de Lapparent, 2015. "Euclidean distance versus travel time in business location: A probabilistic mixture of hurdle-Poisson models," ERSA conference papers ersa15p1060, European Regional Science Association.
    8. Wrenn, Douglas H. & Sam, Abdoul G. & Irwin, Elena G., 2012. "Searching for the Urban Fringe: Exploring Spatio-Temporal Variations in the Effect of Distance versus Local Interactions on Residential Land Conversion Using a Conditionally-Parametric Discrete-Time D," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125007, Agricultural and Applied Economics Association.
    9. Oscar Martinez Ibañez & Miguel Manjón Antolín & Josep-Maria Arauzo-Carod, 2013. "The Geographical Scope of Industrial Location Determinants: An Alternative Approach," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 104(2), pages 194-214, April.
    10. Koster, Hans R.A. & van Ommeren, Jos & Rietveld, Piet, 2014. "Estimation of semiparametric sorting models: Explaining geographical concentration of business services," Regional Science and Urban Economics, Elsevier, vol. 44(C), pages 14-28.

    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:spr:adspcp:978-3-662-05617-2_10. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.