Advanced Search
MyIDEAS: Login to save this paper or follow this series

Continuous-Time Modelling with Spatial Dependence

Contents:

Author Info

  • Johan H.L. Oud

    (Radboud University Nijmegen)

  • Henk Folmer

    (University of Groningen)

  • Roberto Patuelli

    (University of Lugano)

  • Peter Nijkamp

    (VU University Amsterdam)

Abstract

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete representation of reality and may lead to misinterpretation of estimation results. The most compelling reason for a CT approach is that, in contrast to DT modelling, it allows adequate modelling of dynamic adjustment processes. The paper introduces spatial dependence in a CT modelling framework. We propose a nonlinear Structural Equation Model (SEM) with latent variables for estimation of the Exact Discrete Model (EDM), which links the CT model parameters to the DT observations. The use of a SEM with latent variables makes it possible to take measurement errors in the variables into account, leading to a reduction of attenuation bias (i.e., disattenuation). The SE M-CT model with spatial dependence developed here is the first dynamic structural equation model with spatial dependence. The spatial econometric SEM-CT framework is illustrated on the basis of a simple regional labour market model for Germany made up of the endogenous state variables unemployment change and population change and of the exogenous input variables change in regional average wage and change in the structure of the manufacturing sector.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://papers.tinbergen.nl/11117.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 11-117/3.

as in new window
Length:
Date of creation: 09 Aug 2011
Date of revision:
Handle: RePEc:dgr:uvatin:20110117

Contact details of provider:
Web page: http://www.tinbergen.nl

Related research

Keywords: continuous-time modelling; structural equation modelling; latent variables; spatial dependence; panel data; disattenuation; measurement errors; unemployment change; population change; Germany;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

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

Cited by:
  1. Patuelli, R. & Schanne, N. & Griffith, D.A. & Nijkamp, P., 2010. "Persistent disparities in regional unemployment: Application of a spatial filtering approach to local labour markets in Germany," Serie Research Memoranda, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  2. Danny Czamanski & Henk Folmer, 2011. "Introduction: some new methods in regional science," The Annals of Regional Science, Springer, Springer, vol. 47(3), pages 493-497, December.
  3. Patuelli, Roberto & Schanne, Norbert & Griffith, Daniel A. & Nijkamp, Peter, 2011. "Persistence of regional unemployment : Application of a spatial filtering approach to local labour markets in Germany," IAB Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] 201103, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:dgr:uvatin:20110117. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Antoine Maartens (+31 626 - 160 892)).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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