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La hipótesis Keynesiana del gasto público frente a la Ley de Wagner: un análisis de cointegración y causalidad para Perú

Author

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  • Elvis Aparco
  • Alex Flores

Abstract

The objective of this article is to verify the achievement of Wagner’s Law opposed to the Keynesian hypothesis relating to public disbursement in Peru. For that, we analyzed the relationship between public expenditure and economic growth in the period between 1950-2016. By estimating an econometric model of cointegration and Granger causality tests, we obtained the results, which show that in the short term the Keynesian hypothesis as to the public charge will be accomplished, however, in the long-term the situation is opposite and will satisfy the Wagner’s Law.

Suggested Citation

  • Elvis Aparco & Alex Flores, 2019. "La hipótesis Keynesiana del gasto público frente a la Ley de Wagner: un análisis de cointegración y causalidad para Perú," Revista de Economía del Rosario, Universidad del Rosario, vol. 22(1), pages 53-73, June.
    • Handle: RePEc:col:000151:017978
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    File URL: https://revistas.urosario.edu.co/index.php/economia/article/view/7764
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    Cited by:

    1. Gomez Segura, Camilo Fabiam & Cuellar Adames, Andres David & Martínez Alvarado, Laura Camila, 2023. "Incidencia del gasto público en el crecimiento económico de los países suramericanos, 1995-2018," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, vol. 42(75), pages 111-128, January.

    More about this item

    Keywords

    Economic growth; public spending; co-integration; unit root; Granger;
    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
    • N16 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Latin America; Caribbean
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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