Konferenzbeitrag

Spatial Distribution Dynamics

It is quite common in convergence analyses across regions that data exhibit strong spatial dependence. While the literature adopting the regression approach is now fully aware that neglecting this feature may lead to inaccurate results and has therefore suggested a number of statistical tools for addressing the issue, research is only at a very initial stage within the distribution dynamics approach. In particular, in the continuous state-space framework, a few authors opted for spatial pre-filtering the data in order to guarantee the statistical properties of the estimates. In this paper we follow an alternative route that starts from the idea that spatial dependence is not just noise but can be a substantive element of the data generating process. In particular, we develop a tool that, building on the mean-bias adjustment procedure proposed by Hyndman et al. (1996), explicitly allows for spatial dependence in distribution dynamics analysis thus eliminating the need for pre-filtering. Using this tool, we then reconsider the evidence on convergence across regional economies in the US.

Sprache
Englisch

Erschienen in
Series: 55th Congress of the European Regional Science Association: "World Renaissance: Changing roles for people and places", 25-28 August 2015, Lisbon, Portugal

Klassifikation
Wirtschaft
Geographic Labor Mobility; Immigrant Workers
Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Thema
immigration
convergence
distribution dynamics
spatial effects

Ereignis
Geistige Schöpfung
(wer)
Magrini, Stefano
Gerolimetto, Margherita
Ereignis
Veröffentlichung
(wer)
European Regional Science Association (ERSA)
(wo)
Louvain-la-Neuve
(wann)
2015

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Magrini, Stefano
  • Gerolimetto, Margherita
  • European Regional Science Association (ERSA)

Entstanden

  • 2015

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