rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: The
    title: Econometric Analysis of Non-Stationary Spatial Panel Data
  name:
    name part: Beenstock, Michael.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Felsenstein, Daniel.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: IX, 275 p. 45 illus., 40 illus. in color. online resource.
  abstract: This monograph deals with spatially dependent non-stationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial non-stationarity in spatial cross-section data, and a full exposition of non stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel. .
  table of contents: 1 Space and Time are Inextricably Interwoven -- 2 Time Series for Spatial Econometricians -- 3 Spatial Data Analysis and Econometrics -- 4 The Spatial Conectivity Matrix -- 5 Unit Root and Cointegration Tests in Spatial Cross-Section Data -- 6 Spatial Vector Autoregressions -- 7 Unit Root and Cointegration Tests for Spatially Dependent Panel Data -- 8 Cointegration in Non-Stationary Panel Data -- 9 Spatial Vector Error Correction -- 10 Strong and Weak Cross-Section Dependence in Non-Stationary Spatial Panel Data. .
  note: by Michael Beenstock, Daniel Felsenstein.
  subject:
    topic: Econometrics
  subject:
    topic: Regional economics
  subject:
    topic: Spatial economics
  subject:
    topic: Statistics
  subject:
    topic: Econometrics
  subject:
    topic: Regional/Spatial Science
  subject:
    topic: Statistics for Business, Management, Economics, Finance, Insurance
  classification: HB139-141
  classification: 330.015195
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Spatial Science, The Regional Science Series
  identifier: 9783030036140
  identifier: https://doi.org/10.1007/978-3-030-03614-0
  record info:
    record creation date: 190327
    record change date: 20191026222458.0
    record identifier: 978-3-030-03614-0