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The use of BVARs in the analysis of emerging economies

Author

Listed:
  • Ángel Estrada

    (Banco de España)

  • Luis Guirola

    (Banco de España)

  • Iván Kataryniuk

    (Banco de España)

  • Jaime Martínez-Martín

    (Banco de España)

Abstract

The process of internationalisation that many Spanish banks have embarked upon in recent years has resulted in the need for much closer monitoring of the economies in which they are present, especially by a supervisory body such as the Banco de España. In this paper, we present a comprehensive theoretical and empirical modelling approach, developing a set of …five country-specific structural BVARs for Brazil, Mexico, Turkey, Chile and Peru, the economies representing the largest exposures of Spanish banks to the emerging markets. The results obtained show that our modelling strategy provides useful tools to: (i) analyse the structural shocks that underlie their recent macroeconomic behaviour; (ii) study the impact of certain decisions of policymakers on GDP, inflation and other variables; and (iii) carry out accurate conditional and unconditional projections two years ahead of the most policy-relevant variables. These projections, together with the “analyst’s judgement”, constitute the bulk of our assessment of the future behaviour of these economies.

Suggested Citation

  • Ángel Estrada & Luis Guirola & Iván Kataryniuk & Jaime Martínez-Martín, 2020. "The use of BVARs in the analysis of emerging economies," Occasional Papers 2001, Banco de España.
    • Handle: RePEc:bde:opaper:2001
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    References listed on IDEAS

    as
    1. Mark Aguiar & Gita Gopinath, 2007. "Emerging Market Business Cycles: The Cycle Is the Trend," Journal of Political Economy, University of Chicago Press, vol. 115, pages 69-102.
    2. Jonas E. Arias & Juan Rubio-Ramirez & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 2013-24, FEDEA.
    3. Fabio Canova & Matteo Ciccarelli, 2009. "Estimating Multicountry Var Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 929-959, August.
    4. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    5. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    6. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
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    9. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    10. Iván Kataryniuk & Jaime Martínez-Martín, 2019. "TFP Growth and Commodity Prices in Emerging Economies," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(10), pages 2211-2229, August.
    11. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
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    Cited by:

    1. Andres–Escayola, Erik & Berganza, Juan Carlos & Campos, Rodolfo G. & Molina, Luis, 2023. "A BVAR toolkit to assess macrofinancial risks in Brazil and Mexico," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
    2. Danilo Leiva-Leon & Jaime Martinez-Martin & Eva Ortega, 2022. "Exchange Rate Shocks and Inflation Co-movement in the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 18(1), pages 239-275, March.

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    More about this item

    Keywords

    structural analysis; vector autoregressions; bayesian estimation; sign restrictions;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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