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From the “Great Inflation” to the “Great Moderation” in Peru: A Time Varying Structural Vector Autoregressions Analysis

Author

Listed:
  • Castillo, Paul

    (Banco Central de Reserva del Perú)

  • Montoya, Jimena

    (Banco Central de Reserva del Perú)

  • Quineche, Ricardo

    (Banco Central de Reserva del Perú)

Abstract

Over the last 30 years, the Peruvian economy has shown a dramatic decrease in the volatility of its macroeconomic aggregates. Following Primiceri (2005), Benati (2008) and Galí and Gambetti (2009), a Bayesian structural vector autoregression with time-varying parameters and variance covariance matrix of the innovations is used to analyse the underlying causes of Peruvian "Great Moderation". The Peruvian economy is modelled using real GDP growth, inflation and the rate of growth of M1 (money base). Our main results show: (1) Monetary policy has contributed significantly to the "Great Moderation" by reducing the volatility of its non-systematic component and by changing its reaction function to demand and supply shocks; (2) Structural reforms also contributed to reduce the responsiveness of GDP and inflation to demand and supply shocks; (3) During the period of high volatility, supply and policy shocks were the most important determinants of macroeconomic instability.

Suggested Citation

  • Castillo, Paul & Montoya, Jimena & Quineche, Ricardo, 2016. "From the “Great Inflation” to the “Great Moderation” in Peru: A Time Varying Structural Vector Autoregressions Analysis," Working Papers 2016-003, Banco Central de Reserva del Perú.
    • Handle: RePEc:rbp:wpaper:2016-003
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    References listed on IDEAS

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    4. Luca Benati, 2003. "Evolving Post-World War II U.K. Economic Performance," Computing in Economics and Finance 2003 171, Society for Computational Economics.
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    6. Luca Benati, 2007. "The Time-Varying Phillips Correlation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(5), pages 1275-1283, August.
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    9. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    10. Andres Arias & Gary Hansen & Lee Ohanian, 2007. "Why have business cycle fluctuations become less volatile?," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 32(1), pages 43-58, July.
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    13. Larraín B., Felipe & Parro, Francisco, 2008. "Chile menos volátil," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(299), pages 563-596, julio-sep.
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    Cited by:

    1. Gabriel Rodríguez & Carlos Guevara, 2018. "The Role of Loan Supply Shocks in Pacific Alliance Countries: A TVP-VAR-SV Approach," Documentos de Trabajo / Working Papers 2018-467, Departamento de Economía - Pontificia Universidad Católica del Perú.
    2. Jhonatan Portilla & Gabriel Rodríguez & Paul Castillo B., 2022. "Evolution of Monetary Policy in Peru: An Empirical Application Using a Mixture Innovation TVP-VAR-SV Model [Metas de Inflación en Una Economía Dolarizada: La Experencia Del Perú]," CESifo Economic Studies, CESifo Group, vol. 68(1), pages 98-126.
    3. Paulo Chávez & Gabriel Rodríguez, 2023. "Time changing effects of external shocks on macroeconomic fluctuations in Peru: empirical application using regime-switching VAR models with stochastic volatility," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 159(2), pages 505-544, May.
    4. Pérez Rojo, Flavio & Rodríguez, Gabriel, 2024. "Impact of monetary policy shocks in the Peruvian economy over time," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 270-288.

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    More about this item

    Keywords

    time varying coe¢ cients; multivariate stochastic volatility; Gibbs sampling; systematic monetary policy; monetary policy shocks; identi cation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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