Spillovers in space and time: Where spatial econometrics and Global VAR models meet

Arbeitspapier

We bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review of where they meet in terms of structure, interpretation, and estimation methods. We discuss the structure of cross-section connectivity (weight) matrices used by these models and its implications for estimation. Primarily motivated by the continuously expanding literature on spillovers, we define a broad and measurable concept of spillovers. We formalize it analytically through the indirect effects used in the spatial literature and impulse responses used in the GVAR literature. Finally, we propose a practical step-by-step approach for applied researchers who need to account for the existence and strength of cross-sectional dependence in the data. This approach aims to support the selection of the appropriate modeling and estimation method and of choices that represent empirical spillovers in a clear and interpretable form.

Angaben zum Objekt

• ISBN: 978-92-899-3239-4
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: ECB Working Paper ; No. 2134

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models ; Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models ; Model Construction and Estimation
• Thema: Weak and strong cross-sectional dependence ; spatial models ; GVARs ; spillovers

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Elhorst, Jean Paul ; Tereanu, Eugen ; Gross, Marco
• Ereignis: Veröffentlichung
• (wer): European Central Bank (ECB)
• (wo): Frankfurt a. M.
• (wann): 2018

Weitere Informationen

• DOI: doi:10.2866/084378
• Handle: http://hdl.handle.net/10419/179349
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ