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Uncertainty treatment in input-output analysis

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  • Umed Temurshoev

    (Universidad Loyola Andalucía)

Abstract

TThis work provides an extensive overview of the input-output (IO) literature, both theoretical and empirical, dealing with the inherent IO data uncertainty issues. The survey is carried out on the basis of a specific uncertainty technique used, rather than taking a chronological overview approach, which also allows for easier comparisons and linking of the outcomes of the individual contributions. Thus, we discuss the literature within seven methodological blocks (sections), which include deterministic error analysis, econometric and other (non-Bayesian) statistical approaches, random error analysis and probabilistic approach, full probability density distribution approach, Monte Carlo analysis, Bayesian approach, and other techniques. Within each section, the literature on a certain topic is reviewed in its historical context, which helps to clarify the state of the art. Our main findings from this survey, related discussions, final remarks and observations are given in the concluding section.

Suggested Citation

  • Umed Temurshoev, 2015. "Uncertainty treatment in input-output analysis," Working Papers 2015-004, Universidad Loyola Andalucía, Department of Economics.
  • Handle: RePEc:loy:wpaper:2015-004
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    More about this item

    Keywords

    input-output uncertainty; deterministic and random error analysis; stochastic inputoutput analysis; Monte Carlo simulations; Bayesian approach;
    All these keywords.

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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