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Pression Fiscale Optimale et Croissance Economique en République Démocratique du Congo : 1990 -2020

Author

Listed:
  • Elie Ndemba Tshilambu

    (UPC - Université protestante au Congo)

Abstract

L'objectif du présent article est d'analyser le rôle de la fiscalité et mesurer l'effet de celle-ci à travers son impact sur le capital public, dans la croissance économique en République Démocratique du Congo en s'appuyant sur le modèle de croissance endogène de Barro (1990) et à déterminer le taux optimal de pression fiscale à travers l'estimation du modèle de SCULLY. L'interaction entre la fiscalité et la croissance pourrait avoir une allure non linéaire, sous la forme d'une courbe de LAFFER, le test Hansen va servir à montrer l'effet de seuil dans la relation non linéaire entre la pression fiscale et la croissance économique. Un modèle ARDL a été estimé sur la période 1990-2020 pour analyser la dynamique de ces deux variables. Les résultats obtenus vont dans le sens d'une relation croissante entre la fiscalité et la croissance économique en RDC. Ainsi, à travers l'impôt, les ménages contribuent au financement du capital public qui conduit in fine à améliorer la croissance économique. Il en est ressorti de cette étude que les niveaux des composantes fiscales observés n'ont pas été efficients et optimaux par rapport aux taux de croissance économique observés en RDC durant la période 1990-2020. L'estimation du modèle de SCULLY révèle qu'avec un niveau de 23% de pression fiscale, on peut avoir une croissance économique soutenue.

Suggested Citation

  • Elie Ndemba Tshilambu, 2021. "Pression Fiscale Optimale et Croissance Economique en République Démocratique du Congo : 1990 -2020," Working Papers hal-03210477, HAL.
  • Handle: RePEc:hal:wpaper:hal-03210477
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    References listed on IDEAS

    as
    1. Sinha, Dipendra & Sinha, Tapen, 2007. "Toda and Yamamoto Causality Tests Between Per Capita Saving and Per Capita GDP for India," MPRA Paper 2564, University Library of Munich, Germany.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Politique Budgétaire; Croissance économique; Pression fiscale Classification JEL : E62; E22; O40; C11;
    All these keywords.

    JEL classification:

    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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