IDEAS home Printed from https://ideas.repec.org/p/ihs/ihsesp/295.html
   My bibliography  Save this paper

Spatial Chow-Lin Models for Completing Growth Rates in Cross-sections

Author

Listed:
  • Wolfgang Polasek

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

Abstract

Growth rate data that are collected incompletely in cross-sections is a quite frequent problem. Chow and Lin (1971) have developed a method for predicting unobserved disaggregated time series and we propose an extension of the procedure for completing cross-sectional growth rates similar to the spatial Chow-Lin method of Liano et al. (2009). Disaggregated growth rates cannot be predicted directly and requires a system estimation of two Chow-Lin prediction models, where we compare classical and Bayesian estimation and prediction methods. We demonstrate the procedure for Spanish regional GDP growth rates between 2000 and 2004 at a NUTS-3 level. We evaluate the growth rate forecasts by accuracy criteria, because for the Spanish data-set we can compare the predicted with the observed values.

Suggested Citation

  • Wolfgang Polasek, 2013. "Spatial Chow-Lin Models for Completing Growth Rates in Cross-sections," Economics Series 295, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:295
    as

    Download full text from publisher

    File URL: http://www.ihs.ac.at/publications/eco/es-295.pdf
    File Function: First version, 2013
    Download Restriction: no

    More about this item

    Keywords

    Interpolation; missing disaggregated values in spatial econometrics; MCMC; Spatial Chow-Lin methods; predicting growth rates data; spatial autoregression (SAR); forecast evaluation; outliers;

    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)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ihs:ihsesp:295. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Doris Szoncsitz). General contact details of provider: http://edirc.repec.org/data/deihsat.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.