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A Monthly Economic Activity Index System for Suriname

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  • Bhaghoe, Sailesh

Abstract

Advancements in data collection and data processing techniques revolutionized access and availability of high frequency data in macroeconomics. A large body of literature focusses on these high frequency data advancements in advanced economies. However, small less-developed economies often lack adequate and reliable databases of economic indicators on economic performance on a high frequency basis. Therefore, adequate information with regard to the business cycles and other economic phenomena are often not available for decision-making. This study elaborates on the construction of a Monthly Economic Activity Index System (henceforth MEAI) with survey data for Suriname. Using the System of National Accounts and the International Recommendations for the Index of Industrial Production as references to construct the high frequency indicators (henceforth HFIs), a non-model based approach is applied. This paper contributes to the scanty literature and use of HFIs in a less-developed open economy.

Suggested Citation

  • Bhaghoe, Sailesh, 2018. "A Monthly Economic Activity Index System for Suriname," EconStor Preprints 226693, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:226693
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    File URL: https://www.econstor.eu/bitstream/10419/226693/1/CBvS-WP-18-03.pdf
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    References listed on IDEAS

    as
    1. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    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. Craigwell, Roland & Maurin, Alain, 2007. "A sectoral analysis of Barbados’ GDP business cycle," MPRA Paper 33428, University Library of Munich, Germany.
    4. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Working Papers 9808, Banco de España.
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    More about this item

    Keywords

    Monthly Economic Activity Index; Real GDP; Gross value added;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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