IDEAS home Printed from https://ideas.repec.org/p/rbp/wpaper/2019-019.html
   My bibliography  Save this paper

The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness

Author

Listed:
  • Aquino, Juan

    (Banco Central de Reserva del Perú)

Abstract

This paper empirically assesses the concern on whether the slope of the Phillips curve with respect to the output gap has decreased (i.e. the Phillips curve has “flattened”). We derive a generalized lag-augmented version of the New-Keynesian Phillips Curve for a small open economy (Galí and Monacelli, 2005) in order to specify a semi-structural estimation equation. For the Peruvian economy, such equation is estimated via the Generalized Method of Moments for the Inflation-Targeting regime (January 2002 - March 2019) and the post-crisis (January 2008 - March 2019) periods. We found that the slope parameter has remained stable for both estimation periods. Moreover, the expectation channel has gained more relevance for the post-crisis period, a result that is consistent with a lower persistence of inflation dynamics. Our results are also consistent with the presence of long run nominal homogeneity across estimation samples.

Suggested Citation

  • Aquino, Juan, 2019. "The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness," Working Papers 2019-019, Banco Central de Reserva del Perú.
    • Handle: RePEc:rbp:wpaper:2019-019
    as

    Download full text from publisher

    File URL: https://www.bcrp.gob.pe/docs/Publicaciones/Documentos-de-Trabajo/2019/documento-de-trabajo-019-2019.pdf
    File Function: Application/pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bentolila, Samuel & Dolado, Juan J. & Jimeno, Juan F., 2008. "Does immigration affect the Phillips curve? Some evidence for Spain," European Economic Review, Elsevier, vol. 52(8), pages 1398-1423, November.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Michael McLeay & Silvana Tenreyro, 2020. "Optimal Inflation and the Identification of the Phillips Curve," NBER Macroeconomics Annual, University of Chicago Press, vol. 34(1), pages 199-255.
    4. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
    5. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Is the Phillips Curve Alive and Well after All? Inflation Expectations and the Missing Disinflation," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 197-232, January.
    6. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    7. Ms. Dora M Iakova, 2007. "Flattening of the Phillips Curve: Implications for Monetary Policy," IMF Working Papers 2007/076, International Monetary Fund.
    8. Cavaliere, Giuseppe & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2011. "Testing For Unit Roots In The Presence Of A Possible Break In Trend And Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 27(5), pages 957-991, October.
    9. Donald W. K. Andrews, 1999. "Consistent Moment Selection Procedures for Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 67(3), pages 543-564, May.
    10. Leandro M. Magnusson & Sophocles Mavroeidis, 2014. "Identification Using Stability Restrictions," Econometrica, Econometric Society, vol. 82(5), pages 1799-1851, September.
    11. Lieberknecht, Philipp, 2018. "Financial Frictions, the Phillips Curve and Monetary Policy," MPRA Paper 89429, University Library of Munich, Germany.
    12. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    13. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    14. Dennery, Charles, 2019. "Dampened expectations in the Phillips Curve: A note," Economics Letters, Elsevier, vol. 184(C).
    15. Kuttner, Ken & Robinson, Tim, 2010. "Understanding the flattening Phillips curve," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 110-125, August.
    16. Sbordone, Argia M., 2005. "Do expected future marginal costs drive inflation dynamics?," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1183-1197, September.
    17. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    18. A. W. Phillips, 1958. "The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957," Economica, London School of Economics and Political Science, vol. 25(100), pages 283-299, November.
    19. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.
    20. Andrew Pickering & Hector Valle, 2008. "Openness, imported commodities and the Phillips Curve," Bristol Economics Discussion Papers 08/608, School of Economics, University of Bristol, UK.
    21. Punnoose Jacob & Thomas van Florenstein Mulder, 2019. "The flattening of the Phillips curve: Rounding up the suspects," Reserve Bank of New Zealand Analytical Notes series AN2019/06, Reserve Bank of New Zealand.
    22. Watson, Anna, 2016. "Trade openness and inflation: The role of real and nominal price rigidities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 137-169.
    23. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    24. Filippo Occhino, 2019. "The Flattening of the Phillips Curve: Policy Implications Depend on the Cause," Economic Commentary, Federal Reserve Bank of Cleveland, issue July.
    25. Eugenio Gaiotti, 2010. "Commentary: Has Globalization Changed the Phillips Curve? Firm-Level Evidence on the Effect of Activity on Prices," International Journal of Central Banking, International Journal of Central Banking, vol. 6(1), pages 51-84, March.
    26. Joseph E. Gagnon & Christopher G. Collins, 2019. "Low Inflation Bends the Phillips Curve," Working Paper Series WP19-6, Peterson Institute for International Economics.
    27. James B. Bullard, 2018. "The Case of the Disappearing Phillips Curve: a presentation at the 2018 ECB Forum on Central Banking Macroeconomics of Price- and Wage-Setting, Sintra, Portugal," Speech 314, Federal Reserve Bank of St. Louis.
    28. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    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. Szafranek, Karol, 2017. "Flattening of the New Keynesian Phillips curve: Evidence for an emerging, small open economy," Economic Modelling, Elsevier, vol. 63(C), pages 334-348.
    2. Mazali, Antonio Alberto & Divino, Jose Angelo, 2010. "Real Wage Rigidity and the New Phillips Curve: The Brazilian Case," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(3), September.
    3. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    4. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    5. Sebastian Fossati, 2013. "Unit root testing with stationary covariates and a structural break in the trend function," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 368-384, May.
    6. Juan Carlos Berganza & Pedro del Río & Fructuoso Borrallo, 2016. "Determinants and implications of low global inflation rates," Occasional Papers 1608, Banco de España.
    7. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    8. Mariam Camarero & Juan Carlos Cuestas & Javier Ordonez, 2006. "Purchasing Power Parity versus the EU in the Mediterranean countries," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 157-167.
    9. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    10. Cavaliere, Giuseppe & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2011. "Testing For Unit Roots In The Presence Of A Possible Break In Trend And Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 27(5), pages 957-991, October.
    11. Masakatsu Okubo, 2011. "The Intertemporal Elasticity of Substitution: An Analysis Based on Japanese Data," Economica, London School of Economics and Political Science, vol. 78(310), pages 367-390, April.
    12. Esra N. Kılcı & Burcu Kıran Baygın, 2019. "Analysis of the Relationship between Real Effective Exchange Rate, Common Equity Tier 1 Ratio and Return on Equity: Evidence from Turkey," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 7(2), pages 319-332, December.
    13. Acaravici, Ali, 2010. "Structural Breaks, Electricity Consumption and Economic Growth: Evidence from Turkey," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 140-154, July.
    14. repec:kap:iaecre:v:17:y:2011:i:3:p:315-333 is not listed on IDEAS
    15. Khan, Zeeshan & Hussain, Muzzammil & Shahbaz, Muhammad & Yang, Siqun & Jiao, Zhilun, 2020. "Natural resource abundance, technological innovation, and human capital nexus with financial development: A case study of China," Resources Policy, Elsevier, vol. 65(C).
    16. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
    17. Baffigi, Alberto & Bontempi, Maria Elena & Felice, Emanuele & Golinelli, Roberto, 2015. "The changing relationship between inflation and the economic cycle in Italy: 1861–2012," Explorations in Economic History, Elsevier, vol. 56(C), pages 53-70.
    18. Lebogang Mateane & Christian R. Proaño, 2020. "Does monetary policy react asymmetrically to exchange rate misalignments? Evidence for South Africa," Empirical Economics, Springer, vol. 58(4), pages 1639-1658, April.
    19. Atanu Ghoshray & Issam Malki & Javier Ordóñez, 2022. "On the long-run dynamics of income and wealth inequality," Empirical Economics, Springer, vol. 62(2), pages 375-408, February.
    20. Skrobotov Anton, 2018. "On Trend Breaks and Initial Condition in Unit Root Testing," Journal of Time Series Econometrics, De Gruyter, vol. 10(1), pages 1-15, January.
    21. Uäžur Sivri, 2017. "Is Inflation Rate Of Turkey Stationary? Evidence From Unit Root Tests With And Without Structural Breaks," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 20, pages 29-52, December.

    More about this item

    Keywords

    New-Keynesian Phillips curve; small open economy; Generalized Method of Moments.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rbp:wpaper:2019-019. 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: Research Unit (email available below). General contact details of provider: https://edirc.repec.org/data/bcrgvpe.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.