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New coincident and leading indicators for the Lebanese economy

Author

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  • Matta, Samer

Abstract

Weak economic statistics in Lebanon impede economic analysis and decision making. This paper presents a new coincident indicator and a leading indicator for the Lebanese economy. A new methodology, based on the National Bureau of Economic Research-Conference Board approach, was used to construct these indicators. The indicators 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 indications valuable coincident and leading (one-year ahead) indicators 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 indicators 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, 2014. "New coincident and leading indicators for the Lebanese economy," Policy Research Working Paper Series 6950, The World Bank.
    • Handle: RePEc:wbk:wbrwps:6950
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    References listed on IDEAS

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    1. repec:fgv:epgrbe:v:67:n:1:a:4 is not listed on IDEAS
    2. 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.
    3. N/A, 1989. "Annual Report," Evaluation Review, , vol. 13(3), pages 320-320, June.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    5. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
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    Cited by:

    1. Mr. Andrew J Tiffin, 2016. "Seeing in the Dark: A Machine-Learning Approach to Nowcasting in Lebanon," IMF Working Papers 2016/056, International Monetary Fund.
    2. Massimiliano Calì & Wissam Harake & Fadi Hassan & Clemens Struck, 2015. "The Impact of the Syrian Conflict on Lebanese Trade," World Bank Publications - Reports 21914, The World Bank Group.

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