IDEAS home Printed from https://ideas.repec.org/a/fip/fedreq/00038.html
   My bibliography  Save this article

Monitoring Economic Activity in Real Time Using Diffusion Indices: Evidence from the Fifth District

Author

Listed:
  • Santiago Pinto
  • Pierre-Daniel G. Sarte
  • Sonya Ravindranath Waddell

Abstract

We provide an analysis that parses out the conditions under which diffusion indices based on disaggregated information are informative about overall economic activity. Building on work by Pinto, Sarte, and Sharp (2015), we highlight the fact that diffusion indices, appropriately scaled, capture contributions of changes in the extensive margin -- e.g. how many sectors are growing or declining rather than by how much individual sectors are growing or declining -- to aggregate growth. In the Fifth Federal Reserve District, for example, this margin captures the bulk of variations in aggregate employment growth. We then show that the Fifth District employment index, produced in real time using firm-level surveys, closely tracks a synthetic diffusion index constructed ex post using observed data. However, we also underscore that diffusion indices have their limitations. In the Fifth District, for example, the growth rate of average wages (relative to its mean) is frequently of a sign opposite to that indicated by changes in the extensive margin. Finally, we explore some of the implications of producing diffusion indices at a more localized level.

Suggested Citation

  • Santiago Pinto & Pierre-Daniel G. Sarte & Sonya Ravindranath Waddell, 2015. "Monitoring Economic Activity in Real Time Using Diffusion Indices: Evidence from the Fifth District," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 275-301.
  • Handle: RePEc:fip:fedreq:00038
    DOI: 10.21144/eq1010401
    as

    Download full text from publisher

    File URL: https://www.richmondfed.org/-/media/richmondfedorg/publications/research/economic_quarterly/2015/q4/pdf/sarte.pdf
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.21144/eq1010401?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
    ---><---

    References listed on IDEAS

    as
    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    3. Santiago Pinto & Pierre-Daniel G. Sarte & Robert Sharp, 2015. "Learning About Consumer Uncertainty from Qualitative Surveys: As Uncertain As Ever," Working Paper 15-9, Federal Reserve Bank of Richmond.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pedro Elosegui & Mirta González & María Cecilia Pérez & Máximo Sangiácomo, 2022. "A Diffusion Index Analysis of the Argentinean Business Economic Cycle During the COVID-19 Pandemic," BCRA Working Paper Series 2022105, Central Bank of Argentina, Economic Research Department.
    2. Michael E. Trebing, 2017. "Regional Spotlight: Surveying the South Jersey Economy," Regional Spotlight, Federal Reserve Bank of Philadelphia, issue Q2, pages 18-26.
    3. Nika Lazaryan & Santiago Pinto, 2017. "Using the Richmond Fed Manufacturing Survey to Gauge National and Regional Economic Conditions," Economic Quarterly, Federal Reserve Bank of Richmond, issue Q1-Q4, pages 81-137.

    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. Pierre-Daniel G. Sarte, 2010. "Learning about informational rigidities from sectoral data and diffusion indices," Working Paper 10-09, Federal Reserve Bank of Richmond.
    2. Santiago Pinto & Pierre-Daniel Sarte & Robert Sharp, 2020. "The Information Content and Statistical Properties of Diffusion Indexes," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 47-99, September.
    3. Christoph Görtz & John D. Tsoukalas, 2013. "Sector Specific News Shocks in Aggregate and Sectoral Fluctuations," CESifo Working Paper Series 4269, CESifo.
    4. Molnárová, Zuzana & Reiter, Michael, 2022. "Technology, demand, and productivity: What an industry model tells us about business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    5. Altinoglu, Levent, 2021. "The origins of aggregate fluctuations in a credit network economy," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 316-334.
    6. Orphanides, Athanasios & Wei, Min, 2012. "Evolving macroeconomic perceptions and the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 239-254.
    7. Erik Frohm & Vanessa Gunnella, 2021. "Spillovers in global production networks," Review of International Economics, Wiley Blackwell, vol. 29(3), pages 663-680, August.
    8. Lorenzo Burlon, 2015. "Ownership networks and aggregate volatility," Temi di discussione (Economic working papers) 1004, Bank of Italy, Economic Research and International Relations Area.
    9. Kim, Daisoon, 2021. "Economies of scale and international business cycles," Journal of International Economics, Elsevier, vol. 131(C).
    10. Julian Di Giovanni & Galina Hale, 2022. "Stock Market Spillovers via the Global Production Network: Transmission of U.S. Monetary Policy," Journal of Finance, American Finance Association, vol. 77(6), pages 3373-3421, December.
    11. Roberto Roson & Martina Sartori, 2014. "Why can sectoral shocks lead to sizable macroeconomic fluctuations? Assessing alternative theories by means of stochastic simulation with a general equilibrium model," Working Papers 2014:16, Department of Economics, University of Venice "Ca' Foscari".
    12. Can Tian, 2014. "Forecast Shocks in Production Networks," 2014 Meeting Papers 87, Society for Economic Dynamics.
    13. Sharon Traiberman, 2017. "Occupations and Import Competition," 2017 Meeting Papers 1237, Society for Economic Dynamics.
    14. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    15. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    16. Ernesto Pasten & Raphael S. Schoenle & Michael Weber & Michael Weber, 2017. "Price Rigidities and the Granular Origins of Aggregate Fluctuations," CESifo Working Paper Series 6619, CESifo.
    17. Julius Bonart & Jean-Philippe Bouchaud & Augustin Landier & David Thesmar, 2014. "Instabilities in large economies: aggregate volatility without idiosyncratic shocks," Papers 1406.5022, arXiv.org.
    18. Bertinelli, Luisito & Cardi, Olivier & Restout, Romain, 2022. "Labor market effects of technology shocks biased toward the traded sector," Journal of International Economics, Elsevier, vol. 138(C).
    19. Vasco M. Carvalho & Nico Voigtländer, 2014. "Input Diffusion and the Evolution of Production Networks," NBER Working Papers 20025, National Bureau of Economic Research, Inc.
    20. Hännikäinen Jari, 2017. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.

    More about this item

    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:fip:fedreq:00038. 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: Christian Pascasio (email available below). General contact details of provider: https://edirc.repec.org/data/frbrius.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.