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Uncertainty in Integrated Regional Models

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  • Sergio J. Rey

    (San Diego State University)

  • Guy R. West

    (University of Queensland)

  • Mark V. Janikas

    (San Diego State University)

Abstract

This paper examines the nature of uncertainty in integrated econometric+input-output (ECIO) regional models. We focus on three sources of uncertainty: [a] econometric model parameter uncertainty; [b] econometric disturbance term uncertainty; and [c] input-output coefficient uncertainty. Through a series of Monte Carlo simulations we analyze the relative importance of each component as well as the question of how their interaction may propagate through the integrated model to affect the distributions of the endogenous variables. Our results suggest that there is no simple answer to the question of which source of uncertainty is most important in an integrated model. Instead, that answer is conditioned upon the focus of the analysis and whether the industry specific or macro level variables are of central concerns.

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Bibliographic Info

Paper provided by EconWPA in its series Urban/Regional with number 0401001.

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Length: 34 pages
Date of creation: 16 Jan 2004
Date of revision:
Handle: RePEc:wpa:wuwpur:0401001

Note: Type of Document - pdf; prepared on Debian; pages: 34
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Web page: http://128.118.178.162

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Keywords: regional econometric model; input-output; integrated; uncertainty;

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References

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  1. Scott, James K. & Johnson, Thomas G., 1998. "The Community Policy Analysis Network: A National Infrastructure for Community Policy Decision Support," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 28(2).
  2. LeSage, James P. & Magura, Michael, 1991. "Using interindustry input-output relations as a Bayesian prior in employment forecasting models," International Journal of Forecasting, Elsevier, vol. 7(2), pages 231-238, August.
  3. Dan S. Rickman, 2001. "Using Input-Output Information for Bayesian Forecasting of Industry Employment in a Regional Econometric Model," International Regional Science Review, , vol. 24(2), pages 226-244, April.
  4. Ray C. Fair & John B. Taylor, 1989. "Full Information Estimation and Stochastic Simulation of Models with Rational Expectations," Cowles Foundation Discussion Papers 921, Cowles Foundation for Research in Economics, Yale University.
  5. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
  6. Jackson, Randall W., 1989. "Probabilistic input-output analysis: Modeling directions," Socio-Economic Planning Sciences, Elsevier, vol. 23(1-2), pages 87-95.
  7. Gerking, Shelby D, 1976. "Input-Output as a Simple Econometric Model," The Review of Economics and Statistics, MIT Press, vol. 58(3), pages 274-82, August.
  8. Gerking, S.D., 1976. "Input-output as a simple econometric model," Open Access publications from Tilburg University urn:nbn:nl:ui:12-4742764, Tilburg University.
  9. West, Guy R, 1986. "A Stochastic Analysis of an Input-Output Model," Econometrica, Econometric Society, vol. 54(2), pages 363-74, March.
  10. Deller, Steven C. & Shields, Martin, 1998. "Economic Impact Modeling as a Tool for Community Economic Development," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 28(2).
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Citations

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Cited by:
  1. Arbex, Marcelo & Perobelli, Fernando S., 2010. "Solow meets Leontief: Economic growth and energy consumption," Energy Economics, Elsevier, vol. 32(1), pages 43-53, January.
  2. Sporri, C. & Borsuk, M. & Peters, I. & Reichert, P., 2007. "The economic impacts of river rehabilitation: A regional Input-Output analysis," Ecological Economics, Elsevier, vol. 62(2), pages 341-351, April.
  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. Malcolm Beynon & Max Munday, 2008. "Stochastic key sector analysis: an application to a regional input–output framework," The Annals of Regional Science, Springer, vol. 42(4), pages 863-877, December.
  5. Marco Percoco & Geoffrey Hewings & Lanfranco Senn, 2006. "Structural change decomposition through a global sensitivity analysis of input-output models," Economic Systems Research, Taylor & Francis Journals, vol. 18(2), pages 115-131.

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