Local Directional Moran Scatter Plot - LDMS

Davide Fiaschi, Lisa Gianmoena and Angela Parenti ()

Discussion Papers from Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy

Abstract: This paper propose a novel methodology to estimate the distribution dynamics of income in presence of spatial dependence by representing spatial dynamics as a random vector field in Moran space. Inference on the local spatial dynamics is discussed, including a test on the presence of local spatial dependence. The methodology also allows to compute a forecast of future income distribution which includes also the effects of spatial dependence. An application to US States is used to illustrate the effective capacities of the methodology.

Keywords: Exploratory data analysis; polarization; random vector field; spatial dynamics; spatial dependence; distribution dynamics; US States. (search for similar items in EconPapers)
JEL-codes: C14 O51 R11 (search for similar items in EconPapers)
Date: 2015-02-01
New Economics Papers: this item is included in nep-ecm and nep-geo
Note: ISSN 2039-1854
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.ec.unipi.it/documents/Ricerca/papers/2015-197.pdf (application/pdf)

Related works:
Journal Article: LOCAL DIRECTIONAL MORAN SCATTER PLOT - LDMS (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pie:dsedps:2015/197

Access Statistics for this paper

More papers in Discussion Papers from Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy Contact information at EDIRC.
Bibliographic data for series maintained by ().