IDEAS home Printed from https://ideas.repec.org/a/bpj/rmeecf/v11y2015i3p277-303n2.html

New Coincident and Leading Indexes for the Lebanese Economy

Author

Listed:
  • Matta Samer

    (World Bank – Macroeconomics & Fiscal Management Global Practice, Bourrie House, Allenby Street Down Town, Beirut, Beirut, Lebanon)

Abstract

Weak economic statistics in Lebanon impede economic analysis and decision making. This paper presents a new coincident index and a leading index for the Lebanese economy. A new methodology, based on the National Bureau of Economic Research–Conference Board approach, was used to construct these indexes. The indexes can be used as monthly proxies for the evolution of real gross domestic product with a relatively small time lag (four to five months). Notwithstanding the relatively small sample period, the results reveal promising statistical properties that should make these new indexes valuable coincident and leading (one-year ahead) indexes for analyzing the dynamics of the Lebanese economy. However, given limitations on the length of the gross domestic product time series in Lebanon, the accuracy of these indexes in tracking the business cycle of the Lebanese economy is expected to improve over time as more data points become available.

Suggested Citation

  • Matta Samer, 2015. "New Coincident and Leading Indexes for the Lebanese Economy," Review of Middle East Economics and Finance, De Gruyter, vol. 11(3), pages 277-303, December.
    • Handle: RePEc:bpj:rmeecf:v:11:y:2015:i:3:p:277-303:n:2
    DOI: 10.1515/rmeef-2014-0039
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/rmeef-2014-0039
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/rmeef-2014-0039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Issler, Joao Victor & Vahid, Farshid, 2006. "The missing link: using the NBER recession indicator to construct coincident and leading indices of economic activity," Journal of Econometrics, Elsevier, vol. 132(1), pages 281-303, May.
    2. Mr. Joannes Mongardini & Tahsin Saadi Sedik, 2003. "Estimating Indexes of Coincident and Leading Indicators: An Application to Jordan," IMF Working Papers 2003/170, International Monetary Fund.
    3. Sana Souaid Jad, 2011. "The use of surveys to measure sentiment and expected behaviour of key sectors in the economy: evidence from the business survey conducted by the Central Bank of Lebanon," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 248-277, Bank for International Settlements.
    4. Marcellino, Massimiliano, 2005. "Leading Indicators: What Have We Learned?," CEPR Discussion Papers 4977, Centre for Economic Policy Research.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    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. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
    2. Dalibor Stevanovic & Rachidi Kotchoni, 2016. "Forecasting U.S. Recessions and Economic Activity," CIRANO Working Papers 2016s-36, CIRANO.
    3. Issler, Joao Victor & Notini, Hilton & Rodrigues, Claudia & Soares, Ana Flávia, 2013. "Constructing coincident indices of economic activity for the Latin American economy," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    4. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    5. repec:fgv:epgrbe:v:67:n:1:a:4 is not listed on IDEAS
    6. Rafael R. S. Guimaraes, 2022. "Deep Learning Macroeconomics," Papers 2201.13380, arXiv.org.
    7. Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner Piazza Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Artur Brasil Fialho Rodrigues, 2023. "Predicting Recessions in (almost) Real Time in a Big-data Setting," Working Papers Series 587, Central Bank of Brazil, Research Department.
    8. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    9. Shyh-Wei Chen, 2008. "Identifying US turning points revisited: the panel model with the regime switching approach," Applied Economics Letters, Taylor & Francis Journals, vol. 15(11), pages 893-897.
    10. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    11. Mark W. Watson, 2005. "Commentary on \\"what's real about the business cycle?\\"," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 453-458.
    12. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
    13. Cruz-Rodríguez, Alexis, 2004. "Un análisis del ciclo económico de la República Dominicana bajo cambios de régimen [Analysis of business cycle of the Dominican Republic using Markov Switching model]," MPRA Paper 54352, University Library of Munich, Germany.
    14. Fédéric Holm-Hadulla & Kirstin Hubrich, 2017. "Macroeconomic Implications of Oil Price Fluctuations : A Regime-Switching Framework for the Euro Area," Finance and Economics Discussion Series 2017-063, Board of Governors of the Federal Reserve System (U.S.).
    15. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    16. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, April.
    17. Chang-Jin Kim & Jeremy M. Piger & Richard Startz, 2007. "The Dynamic Relationship between Permanent and Transitory Components of U.S. Business Cycles," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(1), pages 187-204, February.
    18. Giancarlo Bruno & Edoardo Otranto, 2003. "Dating the Italian Business Cycle: A Comparison of Procedures," Econometrics 0312003, University Library of Munich, Germany.
    19. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    20. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
    21. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:bpj:rmeecf:v:11:y:2015:i:3:p:277-303:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    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.