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Bayesian Methods for Completing Data in Space-Time Panel Models

Author

Listed:
  • Carlos Llano

    (Universidad Autonoma de Madrid, Spain)

  • Wolfgang Polasek

    (Institute for Advanced Studies, Vienna, Austria and The Rimini Centre for Economic Analysis, Italy)

  • Richard Sellner

    (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 unified 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 GDP at 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 values with the observed ones.

Suggested Citation

  • Carlos Llano & Wolfgang Polasek & Richard Sellner, 2009. "Bayesian Methods for Completing Data in Space-Time Panel Models," Working Paper series 05_09, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:05_09
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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;
    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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