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Chow-Lin Methods in Spatial Mixed Models

Author

Listed:
  • Wolfgang Polasek

    () (Institute for Advanced Studies, Vienna, Austria; University of Porto, Porto, Portugal; The Rimini Centre for Economic Analysis (RCEA))

  • Richard Sellner

    (Institute for Advanced Studies, Vienna, Austria)

  • Carlos Llano

    (Universidad Autónoma de Madrid, Facultad de Ciencias Económicas y Empresariales, Departamento de Análisis Económico, Madrid, Spain)

Abstract

Missing data in dynamic panel models occur quite often since detailed recording of the dependent variable is often not possible at all observation points in time and space. In this paper we develop classical and Bayesian methods to complete missing data in panel models. The Chow-Lin (1971) method is a classical method for completing dependent disaggregated data and is successfully applied in economics to disaggregate aggregated time series. We will extend the space-time panel model in a new way to include cross-sectional and spatially correlated data. The missing disaggregated data will be obtained either by point prediction or by a numerical (posterior) predictive density. Furthermore, we point out that the approach can be extended to more complex models, like flow data or systems of panel data. The panel Chow-Lin approach will be demonstrated with examples involving regional growth for Spanish regions.

Suggested Citation

  • Wolfgang Polasek & Richard Sellner & Carlos Llano, 2010. "Chow-Lin Methods in Spatial Mixed Models," Working Paper series 47_10, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:47_10
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    Keywords

    Space-time interpolation; Spatial panel econometrics; MCMC; Spatial Chow-Lin; missing regional data; Spanish provinces; MCMC; NUTS: nomenclature of territorial units for statistics;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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