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Multiplier Estimates: To Bias Or Not To Bias?

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  • Erik Dietzenbacher

Abstract

ABSTRACT It is well known that multiplier estimates within an interindustry context may be biased when the input coefficients are stochastic. Several conditions have been derived under which the estimates were shown to be biased, all with the same sign. In contrast to these analytical results, however, simulations using a stochastic transactions table unexpectedly reported the unbiasedness of multiplier estimates. This note argues that the sample sizes were too small. It is shown that for increased sample sizes the multiplier estimates are all positively and significantly biased, in line with the analytical results, but the biases are very small.

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  • Erik Dietzenbacher, 2006. "Multiplier Estimates: To Bias Or Not To Bias?," Journal of Regional Science, Wiley Blackwell, vol. 46(4), pages 773-786, October.
    • Handle: RePEc:bla:jregsc:v:46:y:2006:i:4:p:773-786
    DOI: 10.1111/j.1467-9787.2006.00477.x
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    Cited by:

    1. Malcolm Beynon & Max Munday, 2008. "Stochastic key sector analysis: an application to a regional input–output framework," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 863-877, December.
    2. Rueda-Cantuche, José M. & Amores, Antonio F., 2010. "Consistent and unbiased carbon dioxide emission multipliers: Performance of Danish emission reductions via external trade," Ecological Economics, Elsevier, vol. 69(5), pages 988-998, March.
    3. Beynon, Malcolm J. & Munday, Max, 2008. "Considering the effects of imprecision and uncertainty in ecological footprint estimation: An approach in a fuzzy environment," Ecological Economics, Elsevier, vol. 67(3), pages 373-383, October.
    4. Umed Temurshoev, 2015. "Uncertainty treatment in input-output analysis," Working Papers 2015-004, Universidad Loyola Andalucía, Department of Economics.
    5. Nagashima, Fumiya, 2018. "The sign reversal problem in structural decomposition analysis," Energy Economics, Elsevier, vol. 72(C), pages 307-312.
    6. Omar Rifki & Hirotaka Ono & Shigemi Kagawa, 2017. "The robustest clusters in the input–output networks: global $$\hbox {CO}_2$$ CO 2 emission clusters," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 6(1), pages 1-29, December.

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