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A High-frequency Monthly Measure of Real Economic Activity in Pakistan

Author

Listed:
  • Mahmood, Asif
  • Masood, Hina

Abstract

Evaluating the current state of the business cycle is of crucial importance to policymakers for making effective decisions. However, economic data are often noisy and available with a substantial lag. Determining the underlying state of an economy is thus very difficult in practice as traditional national accounts data are often available on quarterly or annual basis. To overcome these gaps, policymakers, especially at the central banks, started to closely track the changes in high-frequency economic activity indicators. In this paper, learning from global best practices, we attempt to develop a composite monthly measure of real economic activity for Pakistan using available high-frequency data. Our constructed measure closely tracks the trend in the real GDP, which is available with relatively large lags from Pakistan Bureau of Statistics. Provided this important characteristic, we test and found a reasonable power of our monthly measure to nowcast real GDP growth for a reference quarter.

Suggested Citation

  • Mahmood, Asif & Masood, Hina, 2024. "A High-frequency Monthly Measure of Real Economic Activity in Pakistan," MPRA Paper 121838, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:121838
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    File URL: https://mpra.ub.uni-muenchen.de/121838/1/MPRA_paper_121838.pdf
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    2. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    3. Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
    4. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    5. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    6. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
    7. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    8. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
    9. 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.
    10. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    11. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    12. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022. "Measuring real activity using a weekly economic index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
    13. Mr. Michael Stanger, 2020. "A Monthly Indicator of Economic Growth for Low Income Countries," IMF Working Papers 2020/013, International Monetary Fund.
    14. Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
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    More about this item

    Keywords

    Economic Activity; High-frequency data; GDP;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production

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