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A Statistical Model for the Identification of Key Sectors in I-O Models

  • Marco Percoco

    ()

Following the seminal work by Bullard and Sebald [Effects of Parametric Uncertainty and Technological Change on In put-Out put Models, Rev. of Ec. And Stat., vol. 59,75-81], in this paper we present an innovative approach to sensitivity analysis in Input-Out put model. In particular, we propose a statistical model capable to compute a sensitivity index associated to each technical coefficient. We call the ordered set of these indices Importance Matrix. Finally, in order to show a simple example for this methodology, we consider the case of the Chicago economy. Keywords: Input-Out put Models, Sensitivity Analysis, Importance Matrix JEL Classification: C15, C67, D5

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa04p90.

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Date of creation: Aug 2004
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Handle: RePEc:wiw:wiwrsa:ersa04p90
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  1. Lahiri, Sajal, 1983. "A note on the underestimation and overestimation in stochastic input-output models," Economics Letters, Elsevier, vol. 13(4), pages 361-366.
  2. West, Guy R, 1986. "A Stochastic Analysis of an Input-Output Model," Econometrica, Econometric Society, vol. 54(2), pages 363-74, March.
  3. Bullard, Clark W & Sebald, Anthony V, 1988. "Monte Carlo Sensitivity Analysis of Input-Output Models," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 708-12, November.
  4. Lahiri, Sajal & Satchell, Steve, 1985. "Underestimation and overestimation of the Leontief inverse revisited," Economics Letters, Elsevier, vol. 18(2-3), pages 181-186.
  5. Simonovits, A, 1975. "A Note on the Underestimation and Overestimation of the Leontief Inverse," Econometrica, Econometric Society, vol. 43(3), pages 493-98, May.
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