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Uncertainty in Integrated Regional Models

  • Sergio J. Rey

    (San Diego State University)

  • Guy R. West

    (University of Queensland)

  • Mark V. Janikas

    (San Diego State University)

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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File URL: http://128.118.178.162/eps/urb/papers/0401/0401001.pdf
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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
Contact details of provider: Web page: http://128.118.178.162

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  1. 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.
  2. 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).
  3. 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).
  4. 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.
  5. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
  6. West, Guy R, 1986. "A Stochastic Analysis of an Input-Output Model," Econometrica, Econometric Society, vol. 54(2), pages 363-74, March.
  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. R. C. Jensen, 1980. "The Concept of Accuracy in Regional Input-Output Models," International Regional Science Review, , vol. 5(2), pages 139-154, August.
  9. 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.
  10. Jackson, Randall W., 1989. "Probabilistic input-output analysis: Modeling directions," Socio-Economic Planning Sciences, Elsevier, vol. 23(1-2), pages 87-95.
  11. repec:ner:tilbur:urn:nbn:nl:ui:12-4742764 is not listed on IDEAS
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