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Bayesian Methods for Completing Data in Space-time Panel Models

Author

Listed:
  • Llano, Carlos

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

  • Polasek, Wolfgang

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

  • Sellner, Richard

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

Abstract

Completing data sets that are collected in heterogeneous units is a quite frequent problem. Chow and Lin (1971) were the first to develop a united framework for the three problems (interpolation, extrapolation and distribution) of predicting times series by related series (the 'indicators'). This paper develops a spatial Chow-Lin procedure for cross-sectional and panel data and compares the classical and Bayesian estimation methods. We outline the error covariance structure in a spatial context and derive the BLUE for the ML and Bayesian MCMC estimation. Finally, we apply the procedure to Spanish regional GDP data between 2000-2004. We assume that only NUTS-2 GDP is known and predict GDPat NUTS-3 level by using socio-economic and spatial information available at NUTS-3. The spatial neighborhood is defined by either km distance, travel-time, contiguity and trade relationships. After running some sensitivity analysis, we present the forecast accuracy criteria comparing the predicted with the observed values.

Suggested Citation

  • Llano, Carlos & Polasek, Wolfgang & Sellner, Richard, 2009. "Bayesian Methods for Completing Data in Space-time Panel Models," Economics Series 241, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:241
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    File URL: https://irihs.ihs.ac.at/id/eprint/1924
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    References listed on IDEAS

    as
    1. Di Fonzo, Tommaso, 1990. "The Estimation of M Disaggregate Time Series When Contemporaneous and Temporal Aggregates Are Known," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 178-182, February.
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    Cited by:

    1. Morito Tsutsumi & Daisuke Murakami, 2014. "New Spatial Econometrics–Based Areal Interpolation Method," International Regional Science Review, , vol. 37(3), pages 273-297, July.

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    More about this item

    Keywords

    Interpolation; Spatial panel econometrics; MCMC; Spatial Chow-Lin; Missing regional data; Spanish provinces; 'Polycentric-periphery' relationship;
    All these keywords.

    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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