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Space-Time Lags: Specification Strategy In Spatial Regression Models

Author

Listed:
  • Fernando A. López Hernández

    (Universidad Politécnica de Cartagena)

  • Coro Chasco Yrigoyen

    (Universidad Autónoma de Madrid)

Abstract

he purpose of this article is to analyse the dynamic trend of spatial dependence, which is not only contemporary but time-lagged in many socio-economic phenomena. Firstly, we show some of the commonly used exploratory spatial data analysis (ESDA) techniques and we propose other new ones, the exploratory space-time data analysis (ESTDA) that evaluates the instantaneity of spatial dependence. We also propose the space-time correlogram as an instrument for a better specification of spatial lag models, which should include both kind of spatial dependence. Some applications with economic data for Spanish provinces shed some light upon these issues.

Suggested Citation

  • Fernando A. López Hernández & Coro Chasco Yrigoyen, 2004. "Space-Time Lags: Specification Strategy In Spatial Regression Models," Econometrics 0411005, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0411005
    Note: Type of Document - pdf; pages: 21
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    References listed on IDEAS

    as
    1. Pace, R. Kelley & Barry, Ronald & Gilley, Otis W. & Sirmans, C. F., 2000. "A method for spatial-temporal forecasting with an application to real estate prices," International Journal of Forecasting, Elsevier, vol. 16(2), pages 229-246.
    2. Luc Anselin, 2001. "Spatial Effects in Econometric Practice in Environmental and Resource Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 705-710.
    3. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    4. Badi Baltagi & Dong Li, 2006. "Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 175-185.
    5. Sergio Rey & Brett Montouri, 1999. "US Regional Income Convergence: A Spatial Econometric Perspective," Regional Studies, Taylor & Francis Journals, vol. 33(2), pages 143-156.
    6. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
    7. Mobley, Lee R., 2003. "Estimating hospital market pricing: an equilibrium approach using spatial econometrics," Regional Science and Urban Economics, Elsevier, vol. 33(4), pages 489-516, July.
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    Cited by:

    1. Massimiliano Agovino & Antonio Garofalo, 2013. "Dipendenza spaziale contemporanea e non contemporanea nei tassi di disoccupazione: un tentativo di analisi empirica dei dati provinciali italiani," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2013(3), pages 45-82.

    More about this item

    Keywords

    Spatial dependence; spatial diffusion; ESDA; correlogram; Spanish provinces;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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