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Negative IO Supply Shock Analyses: A Disaster and a Solution

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Rethinking Input-Output Analysis

Part of the book series: SpringerBriefs in Regional Science ((BRIEFSREGION))

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Abstract

This chapter deals with impact analyses of negative supply shocks, such as natural and man-made disasters. One of the most used approaches in this field is the inoperability IO model. It is shown to be a regular demand-driven IO model formulated in relative changes, which inadequately estimates only the negative demand-side impacts of disasters and completely ignores to positive substitution effects on the supply side of the economy. Next, an easy to use nonlinear, the supply-use programming model is presented. Its basic assumption is that economic actors, after a disaster, primarily try to restore their old pattern of economic transactions as much as possible. Finally, by adding the usual fixed ratio assumptions of IO and SU models, an indication is given of the heavy overestimation of the negative impacts of a disaster when demand-driven IO of SU models are used.

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Notes

  1. 1.

    On 26 August 2019, “inoperability input–output model” scored 836 hits on Google Scholar.

  2. 2.

    Dietzenbacher and Miller (2015) show that it is far simpler to do the normalization at the beginning of (7.1) instead of integrating it in its separate terms as done in the IMM literature. This far more elegantly results in: \({\mathbf{q}} = {({{\hat{\mathbf{x}}}_{ - 1}})^{ - 1}}{({\mathbf{I}} - {\mathbf{A}})^{ - 1}}\Delta {\mathbf{y}}\).

  3. 3.

    Kujawski’s early (2006) critique of the IIM only related to this assumption of fixed technical coefficients and excess supply in all industries, which did not have an impact on the proliferation of the IIM.

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Authors and Affiliations

  1. University of Groningen, Groningen, The Netherlands

    Jan Oosterhaven

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  1. Jan Oosterhaven
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Correspondence to Jan Oosterhaven .

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Oosterhaven, J. (2019). Negative IO Supply Shock Analyses: A Disaster and a Solution. In: Rethinking Input-Output Analysis. SpringerBriefs in Regional Science. Springer, Cham. https://doi.org/10.1007/978-3-030-33447-5_7

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