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Rounding Error: A Distorting Influence on Index Data

Author

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  • Kozicki, Sharon
  • Hoffman, Barak

Abstract

Rounding error is an important source of measurement error that is common in index data. The problem can be traced to rounding that occurs to limit the number of digits after the decimal place to be reported in rebased index data. Rounding error introduces distortions that affect variance properties, alter the lag distributions of time series models, and cause a systematic bias in estimated coefficients. For instance, spuriously choppy inflation rates are obtained when constructed using the official CPI, rebased with 1982-84 = 100. Fortunately, the distortions can be generally avoided by using versions of data that have greater precision.

Suggested Citation

  • Kozicki, Sharon & Hoffman, Barak, 2004. "Rounding Error: A Distorting Influence on Index Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(3), pages 319-338, June.
    • Handle: RePEc:mcb:jmoncb:v:36:y:2004:i:3:p:319-38
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    Citations

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    Cited by:

    1. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    3. Marco Ercolani, 2010. "Transitional price rises with the adoption of the euro: aggregate and disaggregate sector evidence," Journal of Economic Policy Reform, Taylor and Francis Journals, vol. 13(2), pages 137-157.
    4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    5. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29, January.
    6. Nelson, Edward, 2008. "Ireland and Switzerland: The jagged edges of the Great Inflation," European Economic Review, Elsevier, vol. 52(4), pages 700-732, May.
    7. Sharon Kozicki & P. A. Tinsley, 2012. "Effective Use of Survey Information in Estimating the Evolution of Expected Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 145-169, February.
    8. Sharon Kozicki & P. A. Tinsley, 2006. "Survey-Based Estimates of the Term Structure of Expected U.S. Inflation," Staff Working Papers 06-46, Bank of Canada.
    9. Jeremy M. Piger & Robert H. Rasche, 2008. "Inflation: Do Expectations Trump the Gap?," International Journal of Central Banking, International Journal of Central Banking, vol. 4(4), pages 85-116, December.
    10. Baoxue Zhang & Tianqing Liu & Z. Bai, 2010. "Analysis of rounded data from dependent sequences," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(6), pages 1143-1173, December.
    11. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    12. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.

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