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The Role of Supply Constraints in Multiplier Analysis

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  • Manuel Alejandro Cardenete
  • Ferran Sancho

Abstract

Multiplier analysis based upon the information contained in Leontief's inverse is undoubtedly part of the core of the input-output methodology and numerous applications an extensions have been developed that exploit its informational content. Nonetheless there are some implicit theoretical assumptions whose implications have perhaps not been fully assessed. This is the case of the 'excess capacity' assumption. Because of this assumption resources are available as needed to adjust production to new equilibrium states. In real world applications, however, new resources are scarce and costly. Supply constraints kick in and hence resource allocation needs to take them into account to really assess the effect of government policies. Using a closed general equilibrium model that incorporates supply constraints, we perform some simple numerical exercises and proceed to derive a 'constrained' multiplier matrix that can be compared with the standard 'unrestricted' multiplier matrix. Results show that the effectiveness of expenditure policies hinges critically on whether or not supply constraints are considered.

Suggested Citation

  • Manuel Alejandro Cardenete & Ferran Sancho, 2010. "The Role of Supply Constraints in Multiplier Analysis," Working Papers 432, Barcelona School of Economics.
  • Handle: RePEc:bge:wpaper:432
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    References listed on IDEAS

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    Cited by:

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    2. Alejandro Cardenete, M. & López-Cabaco, Roberto, 2018. "How modes of transport perform differently in the economy of Andalusia," Transport Policy, Elsevier, vol. 66(C), pages 9-16.
    3. Argyrios D. Kolokontes & Achilleas Kontogeorgos & Efstratios Loizou & Fotios Chatzitheodoridis, 2020. "Decomposition Analysis for the Comparison and the Comprehension of Conventional Input-Output Impacts’ Indicators: An Empirical Paradigm," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(2), pages 193-217, June.
    4. Erik Dietzenbacher & Manfred Lenzen & Bart Los & Dabo Guan & Michael L. Lahr & Ferran Sancho & Sangwon Suh & Cuihong Yang, 2013. "Input--Output Analysis: The Next 25 Years," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 369-389, December.
    5. Grant Allan & Christos Barkoumas & Andrew Ross & Ashank Sinha, 2020. "Success in sectoral export promotion and economic and environmental indicators: a multisectoral modelling analysis for the UK," Working Papers 2008, University of Strathclyde Business School, Department of Economics.
    6. Miguel, Francisco Javier de & Llop Llop, Maria & Manresa, Antonio, 1954-, 2011. "Simulating the Impact of Sectorial Productivity Gains on Two Regional Economies: Key Sectors from a Supply Side Perspective," Working Papers 2072/169681, Universitat Rovira i Virgili, Department of Economics.
    7. M. Alejandro Cardenete & M. Carmen Lima & Ferran Sancho, 2017. "A multiplier evaluation of primary factors supply–shocks," Working Papers 17.01, Universidad Pablo de Olavide, Department of Economics, Quantitative Methods and Economic History.
    8. Emerta A. Aragie, 2024. "The Impact of Large-scale Agricultural Investments in Low-income Economies," Journal of Development Policy and Practice, , vol. 9(2), pages 199-218, July.
    9. Francisco Miguel & Maria Llop & Antonio Manresa, 2014. "Sectoral productivity gains in two regional economies: key sectors from a supply-side perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(3), pages 731-744, November.
    10. Miguel Vélez, Francisco Javier de & Llop Llop, Maria & Manresa, Antonio, 1954-, 2013. "Supply Multipliers in Two Regional Economies," Working Papers 2072/213636, Universitat Rovira i Virgili, Department of Economics.

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    More about this item

    Keywords

    Key sectors; Economic linkages; Policy evaluation; Economy-wide modeling;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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