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Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment

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Abstract

The timely release of macroeconomic data imposes a distinct structure on the panel: the clustering and sequential ordering of real and nominal variables. We call this orderly release of economic data sequential information flow. The ordered panel generates a new class of restrictions that are helpful in interpreting the real-time estimates of monthly core inflation through the identification of turning points and structural shocks. After establishing the sought-after properties (of smoothness, stability, and forecasting) for core inflation, we turn to the discussion of real-time diagnosis for a low inflation environment. This is done in the context of weekly estimates of Swiss inflation. The intra-monthly estimates for core inflation find that it is worthwhile to update this measure at least twice a month.

Suggested Citation

  • Andreas Fischer & Marlene Amstad, 2004. "Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment," Working Papers 04.06, Swiss National Bank, Study Center Gerzensee.
    • Handle: RePEc:szg:worpap:0406
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    Cited by:

    1. Marlene Amstad & Andreas M. Fischer, 2005. "Time-varying pass-through from import prices to consumer prices: evidence from an event study with real-time data," Staff Reports 228, Federal Reserve Bank of New York.
    2. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    3. Amstad, Marlene & Fischer, Andreas M., 2010. "Monthly pass-through ratios," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1202-1213, July.
    4. Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
    5. Marlene Amstad & Andreas Fischer, 2005. "Shock Identification of Macroeconomic Forecasts based on Daily Panels," Working Papers 05.02, Swiss National Bank, Study Center Gerzensee.
    6. repec:rza:wpaper:503 is not listed on IDEAS
    7. Stan Plessis & Gideon Rand & Kevin Kotzé, 2015. "Measuring Core Inflation in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 527-548, December.
    8. Marlene Amstad & Andreas M. Fischer, 2009. "Are Weekly Inflation Forecasts Informative?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 237-252, April.
    9. Marlene Amstad & Simon Potter & Robert Rich, 2014. "The FRBNY Staff Underlying Inflation Gauge: UIG," BIS Working Papers 453, Bank for International Settlements.

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