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Is Benford’s Law a Universal Behavioral Theory?

Author

Listed:
  • Sofia B. Villas-Boas

    (Department of Agricultural and Resource Economics, University of California, Berkeley, CA 94720, USA)

  • Qiuzi Fu

    (National School of Development, Peking University, Beijing 100871, China)

  • George Judge

    (Department of Agricultural and Resource Economics and Graduate School, University of California, Berkeley, CA 94720, USA)

Abstract

In this paper, we consider the question and present evidence as to whether or not Benford’s exponential first significant digit (FSD) law reflects a fundamental principle behind the complex and nondeterministic nature of large-scale physical and behavioral systems. As a behavioral example, we focus on the FSD distribution of Australian micro income data and use information theoretic entropy methods to investigate the degree that corresponding empirical income distributions are consistent with Benford’s law.

Suggested Citation

  • Sofia B. Villas-Boas & Qiuzi Fu & George Judge, 2015. "Is Benford’s Law a Universal Behavioral Theory?," Econometrics, MDPI, vol. 3(4), pages 1-11, October.
    • Handle: RePEc:gam:jecnmx:v:3:y:2015:i:4:p:698-708:d:57619
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    References listed on IDEAS

    as
    1. Shao, Lijing & Ma, Bo-Qiang, 2010. "The significant digit law in statistical physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3109-3116.
    2. Salem, A B Z & Mount, T D, 1974. "A Convenient Descriptive Model of Income Distribution: The Gamma Density," Econometrica, Econometric Society, vol. 42(6), pages 1115-1127, November.
    3. Grendar, Marian & Judge, George & Schechter, Laura, 2007. "An empirical non-parametric likelihood family of data-based Benford-like distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 429-438.
    4. Judge,George G. & Mittelhammer,Ron C., 2012. "An Information Theoretic Approach to Econometrics," Cambridge Books, Cambridge University Press, number 9780521869591, October.
    5. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, vol. 71(5), pages 421-421.
    6. George Judge, 2015. "Entropy Maximization as a Basis for Information Recovery in Dynamic Economic Behavioral Systems," Econometrics, MDPI, vol. 3(1), pages 1-10, February.
    7. Judge,George G. & Mittelhammer,Ron C., 2012. "An Information Theoretic Approach to Econometrics," Cambridge Books, Cambridge University Press, number 9780521689731, October.
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    Cited by:

    1. González Fernando Antonio Ignacio, 2019. "Detecting Anomalous Data in Household Surveys: Evidence for Argentina," Journal of Social and Economic Statistics, Sciendo, vol. 8(2), pages 1-10, December.

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    More about this item

    Keywords

    first significant digits; Benford’s law; information theoretic methods; empirical likelihood; minimum divergence measure;
    All these keywords.

    JEL classification:

    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C - Mathematical and Quantitative Methods
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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