IDEAS home Printed from https://ideas.repec.org/p/cnb/wpaper/2021-4.html
   My bibliography  Save this paper

The Rushin Index: A Weekly Indicator of Czech Economic Activity

Author

Listed:
  • Tomas Adam
  • Ondrej Michalek
  • Ales Michl
  • Eva Slezakova

Abstract

We introduce the Rushin, a weekly index of Czech economic activity. The index is based on alternative, high-frequency indicators and standard, low-frequency macroeconomic data. Various information from the economy is aggregated to extract a signal about real-time dynamics in the real economy. Although the information on the GDP growth rate is not used directly in the construction of the index, the indicator fits GDP data well, particularly in turbulent times such as the global financial crisis and the COVID-19 crisis. Therefore, it can be used for the real-time monitoring of economic activity, nowcasting and identifying turning points in the economy. The name of the index alludes to the name of Czechoslovakia's first finance minister Alois Rasin and the timeliness (rush-) of the index (-in).

Suggested Citation

  • Tomas Adam & Ondrej Michalek & Ales Michl & Eva Slezakova, 2021. "The Rushin Index: A Weekly Indicator of Czech Economic Activity," Working Papers 2021/4, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2021/4
    as

    Download full text from publisher

    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2021_04.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles S. Gascon & Amelia Schmitz, 2020. "Using High-Frequency Data to Track the Regional Economy," The Regional Economist, Federal Reserve Bank of St. Louis, vol. 28(3), August.
    2. Sophia Chen & Ms. Deniz O Igan & Mr. Nicola Pierri & Mr. Andrea F Presbitero, 2020. "Tracking the Economic Impact of COVID-19 and Mitigation Policies in Europe and the United States," IMF Working Papers 2020/125, International Monetary Fund.
    3. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
    4. Gerhard Fenz & Helmut Stix, 2021. "Monitoring the economy in real time with the weekly OeNB GDP indicator: background, experience and outlook," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/20-Q1/, pages 17-40.
    5. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    6. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
    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. Daniel Ollech & Deutsche Bundesbank, 2023. "Economic analysis using higher-frequency time series: challenges for seasonal adjustment," Empirical Economics, Springer, vol. 64(3), pages 1375-1398, March.
    2. Ollech, Daniel, 2021. "Economic analysis using higher frequency time series: Challenges for seasonal adjustment," Discussion Papers 53/2021, Deutsche Bundesbank.
    3. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    4. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
    5. Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
    6. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    7. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    8. Acosta, Juan & Cherrier, Beatrice, 2021. "The Transformation Of Economic Analysis At The Board Of Governors Of The Federal Reserve System During The 1960s," Journal of the History of Economic Thought, Cambridge University Press, vol. 43(3), pages 323-349, September.
    9. Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario & Altissimo, Filippo & Cristadoro, Riccardo & Veronese, Giovanni & Bassanetti, Antonio, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
    10. Perron, Pierre & Wada, Tatsuma, 2016. "Measuring business cycles with structural breaks and outliers: Applications to international data," Research in Economics, Elsevier, vol. 70(2), pages 281-303.
    11. Claudio Borio, 2013. "On Time, Stocks and Flows: Understanding the Global Macroeconomic Challenges," National Institute Economic Review, National Institute of Economic and Social Research, vol. 225(1), pages 3-13, August.
    12. Phurichai Rungcharoenkitkul, 2021. "Macroeconomic effects of COVID‐19: A mid‐term review," Pacific Economic Review, Wiley Blackwell, vol. 26(4), pages 439-458, October.
    13. Parma Chakravartti & Sudipto Mundle, 2017. "An Automatic Leading Indicator Based Growth Forecast For 2016-17 and The Outlook Beyond," Working Papers id:11773, eSocialSciences.
    14. Catalin DUMITRESCU, 2020. "Financial Stability Of Economic Agencies In Conditions Of Economic Crisis," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 57(1), pages 22-33, March.
    15. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    16. Pami Dua & Anirvan Banerji, 2006. "Business Cycles in India," Working papers 146, Centre for Development Economics, Delhi School of Economics.
    17. Apostolos Serletis & Ricardo Rangel-Ruiz, 2007. "Testing for Common Features in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 14, pages 172-187, World Scientific Publishing Co. Pte. Ltd..
    18. Brown, William Jr. & Burdekin, Richard C.K. & Weidenmier, Marc D., 2006. "Volatility in an era of reduced uncertainty: Lessons from Pax Britannica," Journal of Financial Economics, Elsevier, vol. 79(3), pages 693-707, March.
    19. Grossman, Richard, 2017. "Stocks for the Long Run: New Monthly Indices of British Equities, 1869-1929," CEPR Discussion Papers 12121, C.E.P.R. Discussion Papers.
    20. McGuckin, Robert H. & Ozyildirim, Ataman & Zarnowitz, Victor, 2007. "A More Timely and Useful Index of Leading Indicators," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 110-120, January.

    More about this item

    Keywords

    COVID-19 crisis; economic activity index; high-frequency indicators; nowcasting;
    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
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cnb:wpaper:2021/4. 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: Jan Babecky (email available below). General contact details of provider: https://edirc.repec.org/data/cnbgvcz.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.