IDEAS home Printed from https://ideas.repec.org/p/apc/wpaper/2017-094.html
   My bibliography  Save this paper

Brecha de la capacidad de utilización como medida alternativa de la brecha producto: Un enfoque para Perú basado en micro datos

Author

Listed:
  • Alex Contreras M.

    (BCRP, UDEP, UPC y UNI)

  • Pablo Del Aguila R.

    (BCRP y Universidad Católica Santo Toribio de Mogrovejo)

  • Fernando Alonso Regalado S.

    (BCRP y Universidad del Pacífico)

  • F. Martín Martinez P.

    (BCRP y Universidad Nacional Mayor de San Marcos)

Abstract

Proponemos una medida alternativa para la brecha producto de Perú basada en el uso de datos a nivel de firma de la Encuesta de Expectativas Macroeconómicas elaborada por el Banco Central de Reserva del Perú. La evidencia internacional apoya el uso de la brecha de capacidad de utilización como una medida exacta de la brecha producto y de desempleo. Suiza y Turquía han reportado utilizar este indicador para medir la dinámica de inflación y las fluctuaciones del ciclo económico. Calculamos la tasa NAIRCU (non-accelerating inflation rate of capacity utilisation) por empresa, para luego agregar la NAIRCU y obtener un indicador líder del ciclo económico. Este indicador proporciona información 45 días antes que los indicadores más comunes basados en el PIB. Además, proporciona información relevante sobre la dinámica de inflación dos trimestres por adelantado, una característica clave para los propósitos de política monetaria. Por lo tanto, la medida propuesta es un indicador de alta frecuencia y robustez teórica que puede ser utilizada como una medida alternativa dada sus ventajas metodológicas: (i) es libre de revisión, (ii) puede obtenerse de manera oportuna, (iii) no supone el uso de priors estadísticos, y (iv) permite estimar una variable no observable directamente de datos micro.

Suggested Citation

  • Alex Contreras M. & Pablo Del Aguila R. & Fernando Alonso Regalado S. & F. Martín Martinez P., 2017. "Brecha de la capacidad de utilización como medida alternativa de la brecha producto: Un enfoque para Perú basado en micro datos," Working Papers 94, Peruvian Economic Association.
    • Handle: RePEc:apc:wpaper:2017-094
    as

    Download full text from publisher

    File URL: http://perueconomics.org/wp-content/uploads/2014/01/WP-94.pdf
    File Function: Application/pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eva M. Köberl & Sarah M. Lein, 2011. "The NIRCU and the Phillips curve: an approach based on micro data," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(2), pages 673-694, May.
    2. Orphanides, Athanasios & Williams, John C., 2005. "The decline of activist stabilization policy: Natural rate misperceptions, learning, and expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1927-1950, November.
    3. Rose McElhattan, 1985. "Inflation, supply shocks and the stable-inflation rate of capacity utilization," Economic Review, Federal Reserve Bank of San Francisco, issue Win, pages 45-63.
    4. Şahinöz, Saygın & Atabek, Aslıhan, 2016. "An alternative micro-based output gap measure for Turkey: The capacity utilisation gap," Economics Letters, Elsevier, vol. 143(C), pages 44-47.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Orphanides, Athanasios & Wei, Min, 2012. "Evolving macroeconomic perceptions and the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 239-254.
    2. Maria Demertzis & Nicola Viegi, 2008. "Inflation Targets as Focal Points," International Journal of Central Banking, International Journal of Central Banking, vol. 4(1), pages 55-87, March.
    3. Brian Hayes, 2011. "Economics, Control Theory, and the Phillips Machine," ASSRU Discussion Papers 1101, ASSRU - Algorithmic Social Science Research Unit.
    4. Ascari, Guido & Rankin, Neil, 2007. "Perpetual youth and endogenous labor supply: A problem and a possible solution," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 708-723, December.
    5. Stephen Hansen & Michael McMahon, 2016. "First Impressions Matter: Signalling as a Source of Policy Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(4), pages 1645-1672.
    6. George W. Evans & Seppo Honkapohja & Kaushik Mitra, 2012. "Does Ricardian Equivalence Hold When Expectations Are Not Rational?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1259-1283, October.
    7. Lubik, Thomas A. & Matthes, Christian, 2016. "Indeterminacy and learning: An analysis of monetary policy in the Great Inflation," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 85-106.
    8. Marcos Poplawski-Ribeiro & Jan-Christoph Rülke, 2010. "Fiscal Expectations on the Stability and Growth Pact: Evidence from Survey Data," Working Papers 2010-05, CEPII research center.
    9. Fabio Milani, 2006. "A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
    10. William A. Branch & John Carlson & George W. Evans & Bruce McGough, 2009. "Monetary Policy, Endogenous Inattention and the Volatility Trade‐off," Economic Journal, Royal Economic Society, vol. 119(534), pages 123-157, January.
    11. M. Dossche & G. Everaert, 2005. "Measuring inflation persistence: a structural time series approach," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/340, Ghent University, Faculty of Economics and Business Administration.
    12. Jan-Erik Antipin & Farid Jimmy Boumediene & Pär Österholm, 2014. "Forecasting Inflation Using Constant Gain Least Squares," Australian Economic Papers, Wiley Blackwell, vol. 53(1-2), pages 2-15, June.
    13. Athanasios Orphanides & John C. Williams, 2013. "Monetary Policy Mistakes and the Evolution of Inflation Expectations," NBER Chapters, in: The Great Inflation: The Rebirth of Modern Central Banking, pages 255-288, National Bureau of Economic Research, Inc.
    14. Quaghebeur, Ewoud, 2019. "Learning And The Size Of The Government Spending Multiplier," Macroeconomic Dynamics, Cambridge University Press, vol. 23(8), pages 3189-3224, December.
    15. David E. Lindsey & Athanasios Orphanides & Robert H. Rasche, 2013. "The Reform of October 1979: How It Happened and Why," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 487-542.
    16. Paul Hubert & Becky Maule, 2016. "Policy and Macro Signals as Inputs to Inflation Expectation Formation," Working Papers hal-03459462, HAL.
    17. Berg, Kimberly A. & Mark, Nelson C., 2018. "Global macro risks in currency excess returns," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 300-315.
    18. Erceg, Christopher J. & Jakab, Zoltan & Lindé, Jesper, 2021. "Monetary policy strategies for the European Central Bank," Journal of Economic Dynamics and Control, Elsevier, vol. 132(C).
    19. Peter Andrebriq & Carlo Pizzinelli & Christopher Roth & Johannes Wohlfart, 2022. "Subjective Models of the Macroeconomy: Evidence From Experts and Representative Samples [Rationally Confused: On the Aggregate Implications of Information Provision Policies]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 2958-2991.
    20. Stephen J. Cole, 2021. "Learning and the Effectiveness of Central Bank Forward Guidance," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 157-200, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:apc:wpaper:2017-094. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nelson Ramírez-Rondán (email available below). General contact details of provider: https://edirc.repec.org/data/peruvea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.