IDEAS home Printed from https://ideas.repec.org/p/ekd/010027/10414.html
   My bibliography  Save this paper

Alice: A New Inflation Monitoring Tool

Author

Listed:
  • Zivile Zekaite
  • Gabe de Bondt
  • Elke Hahn

Abstract

The ability to anticipate future inflation developments and the understanding of its driving factors are of the greatest value. Inflation forecasting is an important part of the broader economic analysis, albeit it is well known that inflation is inherently hard to forecast. While most commonly used approaches aim at quantitative inflation forecasts, this study focuses on (composite) leading indicators and qualitative inflation signals, which is a complementary tool to gauge future developments in inflation. This method is also largely statistical but it aims to predict turning points in the inflation cycle rather than directly forecasting the level of inflation. The aim is to provide early-warning signals with respect to the direction of the movements in inflation. We make several important contributions to the existing literature. Firstly, this is the first study to construct a composite leading indicator for both the headline as well as core inflation cycle. Secondly, the sample period goes well beyond the late 1990s and includes the Great Recession as well as the euro area debt crisis. This allows taking advantage of actual euro area data in addition to “synthetic” euro area data that in part go back to the 1960s. The third contribution is a careful analysis of over 150 potential leading series covering different parts of the economy in order to select component series for the leading indicators. Finally, we provide a pseudo real-time evaluation of the performance of the two constructed indicators. The current paper takes a non-model based approach to construct the composite leading indicator of the euro area inflation cycle. We apply the deviation cycle definition with respect to the euro area inflation rate. The random walk filter by Christiano and Fitzgerald (2003) is employed in the current paper to obtain the cyclical components of the reference series. We remove from the series the frequencies that are higher than 12 months and lower than 120 months. This choice is in line with the OECD system of composite leading indicators for the business cycle that is based on the double HP with 12-month and 120-month lower and upper limits for frequency bands. The two constructed Area-wide Leading Inflation CyclE (ALICE) indicators for the euro area headline and core inflation consist of nine and, respectively, seven leading series, with a lead time between 3 and 25 months. The leading series have a broad economic coverage, ranging from external factors, prices and costs measures, economic activity variables, “soft” survey data, financial variables, and market-based inflation expectations. The headline and core ALICE identify ex post major cyclical movements in inflation quite well, especially since 1999. A pseudo real-time analysis confirms these findings and shows that the ALICE for both headline and core inflation perform well, i.e. they indicate turning points of the reference cycle in advance, and do not suffer from major revisions over time. Thus, these indicators appear to have a potential to be useful for the real-time monitoring, analysis and forecasting of inflation developments in the euro area.

Suggested Citation

  • Zivile Zekaite & Gabe de Bondt & Elke Hahn, 2017. "Alice: A New Inflation Monitoring Tool," EcoMod2017 10414, EcoMod.
  • Handle: RePEc:ekd:010027:10414
    as

    Download full text from publisher

    File URL: http://ecomod.net/system/files/Final%20draft%20%28EcoMod%29.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nidhaleddine Ben Cheikh & Christophe Rault, 2016. "Recent estimates of exchange rate pass-through to import prices in the euro area," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(1), pages 69-105, February.
    2. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
    3. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    4. Helge Berger & Pär Österholm, 2011. "Does Money Growth Granger Cause Inflation in the Euro Area? Evidence from Out‐of‐Sample Forecasts Using Bayesian VARs," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 45-60, March.
    5. Castro, César & Jerez, Miguel & Barge-Gil, Andrés, 2016. "The deflationary effect of oil prices in the euro area," Energy Economics, Elsevier, vol. 56(C), pages 389-397.
    6. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    7. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    8. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    9. Michele Cavallo, 2008. "Oil prices and inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue oct3.
    10. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    11. Sousa, João & Falagiarda, Matteo, 2017. "Forecasting euro area inflation using targeted predictors: is money coming back?," Working Paper Series 2015, European Central Bank.
    12. Lenza Michele & Warmedinger Thomas, 2011. "A Factor Model for Euro-area Short-term Inflation Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 50-62, February.
    13. Bobeica, Elena & Jarociński, Marek, 2017. "Missing disinflation and missing inflation," Research Bulletin, European Central Bank, vol. 30.
    14. Howard L. Roth, 1986. "Leading indicators of inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 71(Nov), pages 3-20.
    15. J. M. Binner & R. K. Bissoondeeal & A. W. Mullineux, 2005. "A composite leading indicator of the inflation cycle for the Euro area," Applied Economics, Taylor & Francis Journals, vol. 37(11), pages 1257-1266.
    16. Kirstin Hubrich & Frauke Skudelny, 2017. "Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 515-540, August.
    17. Gert Peersman & Ine van Robays, 2009. "Oil and the Euro area economy [Labour market implications of EU product market integration]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 24(60), pages 603-651.
    18. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    19. Bobeica, Elena & Jarociński, Marek, 2017. "Missing disinflation and missing inflation," Research Bulletin, European Central Bank, vol. 30.
    20. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2005. "Leading Indicators for Euro‐area Inflation and GDP Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 785-813, December.
    21. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    22. Elena Bobeica & Marek Jarociński, 2019. "Missing Disinflation and Missing Inflation: A VAR Perspective," International Journal of Central Banking, International Journal of Central Banking, vol. 15(1), pages 199-232, March.
    23. Anindya Banerjee & Bill Russell, 2006. "A markup model for forecasting inflation for the euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 495-511.
    24. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    25. Gabe J. Bondt & Elke Hahn, 2014. "Introducing the Euro Area‐wide Leading Indicator (ALI): Real‐Time Signals of Turning Points in the Growth Cycle from 2007 to 2011," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 47-68, January.
    26. Helge Berger & Pär Österholm, 2011. "Does Money Growth Granger Cause Inflation in the Euro Area? Evidence from Out‐of‐Sample Forecasts Using Bayesian VARs," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 45-60, March.
    27. repec:hal:spmain:info:hdl:2441/784ilbkihi9tkblnh7q2514823 is not listed on IDEAS
    28. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2005. "A Core Inflation Indicator for the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 539-560, June.
    29. Chen, Sophia & Ranciere, Romain, 2019. "Financial information and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1160-1174.
    30. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2012. "Characterising the financial cycle: don't lose sight of the medium term!," BIS Working Papers 380, Bank for International Settlements.
    31. Quinn, Terry & Mawdsley, Andrew, 1996. "Forecasting Irish Inflation: A Composite Leading Indicator," Research Technical Papers 4/RT/96, Central Bank of Ireland.
    32. Massmann, Michael & Mitchell, James & Weale, Martin, 2003. "Business Cycles and Turning Points: A Survey of Statistical Techniques," National Institute Economic Review, National Institute of Economic and Social Research, vol. 183, pages 90-106, January.
    33. Emil Stavrev & Helge Berger, 2012. "The information content of money in forecasting euro area inflation," Applied Economics, Taylor & Francis Journals, vol. 44(31), pages 4055-4072, November.
    34. Jeff Fuhrer & Jane Sneddon Little & Yolanda K. Kodrzycki & Giovanni P. Olivei (ed.), 2009. "Understanding Inflation and the Implications for Monetary Policy: A Phillips Curve Retrospective," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262013630, December.
    35. C. Alan Garner, 1995. "How useful are leading indicators of inflation?," Economic Review, Federal Reserve Bank of Kansas City, vol. 80(Q II), pages 5-18.
    36. Hahn, Elke & Mestre, Ricardo, 2011. "The role of oil prices in the euro area economy since the 1970s," Working Paper Series 1356, European Central Bank.
    37. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, March.
    38. Gibson, Heather D. & Lazaretou, Sophia, 2001. "Leading inflation indicators for Greece," Economic Modelling, Elsevier, vol. 18(3), pages 325-348, August.
    39. J. M. Binner & A. Fielding & A. W. Mullineux, 1999. "Divisia money in a composite leading indicator of inflation," Applied Economics, Taylor & Francis Journals, vol. 31(8), pages 1021-1031.
    40. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    41. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    42. Strauss, Jack, 2013. "Does housing drive state-level job growth? Building permits and consumer expectations forecast a state’s economic activity," Journal of Urban Economics, Elsevier, vol. 73(1), pages 77-93.
    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. de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.
    2. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    3. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.
    4. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department.
    5. Tan, Hao & Mathews, John A., 2010. "Identification and analysis of industry cycles," Journal of Business Research, Elsevier, vol. 63(5), pages 454-462, May.
    6. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    7. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2019. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 541-569, September.
    8. D. S. G. Pollock, 2016. "Econometric Filters," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 669-691, December.
    9. Pandey, Radhika & Patnaik, Ila & Shah, Ajay, 2019. "Measuring business cycle conditions in India," Working Papers 19/269, National Institute of Public Finance and Policy.
    10. Roger Alejandro Banegas-Rivero, 2016. "Business Cycle, Asymmetries and non-linearity in Bolivia, 1950-2015. Ciclos económicos, asimetrías y no-linealidades en Bolivia, 1950-2015," Working Papers, Documentos de trabajo, Centro de Desarrollo Economico y Social (CEDES). 201609, Instituto de Investigaciones Económicas y Sociales 'Jose Ortiz Mercado' (IIES-JOM), Facultad de Ciencias Economicas, Administrativas y Financieras, Universidad Autonoma Gabriel Rene Moreno.
    11. Meller, Barbara & Metiu, Norbert, 2015. "The synchronization of European credit cycles," Discussion Papers 20/2015, Deutsche Bundesbank.
    12. Thierry Aimar & Francis Bismans & Claude Diebolt, 2010. "Le cycle économique : une synthèse," Revue Française d'Économie, Programme National Persée, vol. 24(4), pages 3-65.
    13. Mariano Kulish & Adrian Pagan, 2021. "Turning point and oscillatory cycles: Concepts, measurement, and use," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 977-1006, September.
    14. Kajal Lahiri, Wenxiong Yao, and Peg Young, 2003. "Cycles in the Transportation Sector and the Aggregate Economy," Discussion Papers 03-14, University at Albany, SUNY, Department of Economics.
    15. Robert Pater, 2014. "Are there two types of business cycles? a note on crisis detection," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(3), pages 1-28, December.
    16. Ritabrata Bose & Ashima Goyal, 2020. "Disaggregated Indian industrial cycles: A Spectral analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-033, Indira Gandhi Institute of Development Research, Mumbai, India.
    17. Monica Billio & Massimiliano Caporin & Guido Cazzavillan, 2008. "Dating EU15 monthly business cycle jointly using GDP and IPI," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(3), pages 333-366.
    18. Dilip Nachane & Aditi Chaubal, 2022. "A Comparative Evaluation of Some DSP Filters vis-à-vis Commonly Used Economic Filters," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 161-190, September.
    19. Jakob De Haan & Robert Inklaar & Richard Jong‐A‐Pin, 2008. "Will Business Cycles In The Euro Area Converge? A Critical Survey Of Empirical Research," Journal of Economic Surveys, Wiley Blackwell, vol. 22(2), pages 234-273, April.
    20. Padhan, Rakesh & Prabheesh, K.P., 2020. "Business cycle synchronization: Disentangling direct and indirect effect of financial integration in the Indian context," Economic Modelling, Elsevier, vol. 85(C), pages 272-287.

    More about this item

    Keywords

    Euro area; Forecasting; nowcasting; Business cycles;
    All these keywords.

    JEL classification:

    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:ekd:010027:10414. 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: Theresa Leary (email available below). General contact details of provider: https://edirc.repec.org/data/ecomoea.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.