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Stationarity conditions for the spatial first-order and serial second-order model

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  • Elena Kotyrlo

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    Abstract

    The stationarity conditions for a spatial first-order and serial second-order model in the presence of time-lagged spatial interactions are discussed. The stationarity conditions for serial autoregressive parameters were found on the basis of the structural vector autoregression form of the model. The temporal stationarity was a function of the spatial autoregressive parameters. The value of the time-lagged spatial autoregressive parameter defined the shift of the interval for the first-order serial parameter. However, the sizes of intervals for the values of both serial parameters depended only on the value of the simultaneous autoregressive parameter. Copyright Springer-Verlag 2013

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    File URL: http://hdl.handle.net/10.1007/s12076-012-0083-2
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    Bibliographic Info

    Article provided by Springer in its journal Letters in Spatial and Resource Sciences.

    Volume (Year): 6 (2013)
    Issue (Month): 1 (March)
    Pages: 19-29

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    Handle: RePEc:spr:lsprsc:v:6:y:2013:i:1:p:19-29

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    Web page: http://www.springer.com/economics/journal/12076

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    Related research

    Keywords: Stability; Simultaneity; Time-lagged spatial interaction; Second-order time series; Fertility; C23; J11;

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    1. Florax, R. & Folmer, H., 1991. "Specification and Estimation of Spatial Linear Regression Models: Monte Carlo Evaluation of Pre-Test Estimator," Mansholt Working Papers 1991-4, Wageningen University, Mansholt Graduate School of Social Sciences.
    2. Brigitte Waldorf & Rachel Franklin, 2002. "Spatial Dimensions of the Easterlin Hypothesis: Fertility Variations in Italy," Journal of Regional Science, Wiley Blackwell, vol. 42(3), pages 549-578.
    3. J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
    4. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    5. Elhorst, J. Paul & Lacombe, Donald J. & Piras, Gianfranco, 2012. "On model specification and parameter space definitions in higher order spatial econometric models," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 211-220.
    6. Nicolas Debarsy & Cem Ertur & James P. Lesage, 2012. "Interpreting Dynamic Space-Time Panel Data Models," Post-Print hal-00525740, HAL.
    7. Marcia Castro, 2007. "Spatial Demography: An Opportunity to Improve Policy Making at Diverse Decision Levels," Population Research and Policy Review, Springer, vol. 26(5), pages 477-509, December.
    8. J. Keith Ord & Arthur Getis, 2001. "Testing for Local Spatial Autocorrelation in the Presence of Global Autocorrelation," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 411-432.
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