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Informational Performance, Competitive Capital-Market Scaling, and the Frequency Distribution of Tobin’s Q

Author

Listed:
  • Paulo dos Santos

    () (Department of Economics, New School for Social Research)

  • Ellis Scharfenaker

    () (Department of Economics, University of Missouri Kansas City)

Abstract

We develop a systemic interpretation of the functioning of capital markets that formally accounts for the observed frequency distribution of Tobin’s q, reported in Scharfernaker and dos Santos, 2015. Considering Tobin’s q as a ratio of expected total rates of return, we draw on an epistemological understanding of the tools of statistical mechanics to interpret capital markets as a competitive informational system. The strong modality in the distribution of q is taken to be conditioned by the arbitrage operations of corporate insiders. We take the persistent spread in the distribution of q to reflect the presence of obstacles to that agency, which impose an informational constraint on the operation of capital markets. This spread is also shaped by the fact that the measure of Tobin’s q e↵ectively scales the expected returns for an individual corporation relative to those expected of all corporations. This scaling reflects aggregate measures of bullishness in investors’ valuations that insiders do not seek to exploit. In addition to accounting for the frequency distribution of q observed for the past 50 years, this interpretation points to a systemic diagnostic for the presence of speculative equity-price bubbles, and o↵ers a new informational characterization efficiency in capital markets. According to the latter, U.S. capital markets have experienced a steady secular loss in their informational efficiency since the early 1980s.

Suggested Citation

  • Paulo dos Santos & Ellis Scharfenaker, 2016. "Informational Performance, Competitive Capital-Market Scaling, and the Frequency Distribution of Tobin’s Q," Working Papers 1607, New School for Social Research, Department of Economics.
  • Handle: RePEc:new:wpaper:1607
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    File URL: http://www.economicpolicyresearch.org/econ/2016/NSSR_WP_072016.pdf
    File Function: First version, 2016
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    References listed on IDEAS

    as
    1. Myers, Stewart C. & Majluf, Nicolás S., 1945-, 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Working papers 1523-84., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Stewart C. Myers & Nicholas S. Majluf, 1984. "Corporate Financing and Investment Decisions When Firms Have InformationThat Investors Do Not Have," NBER Working Papers 1396, National Bureau of Economic Research, Inc.
    3. Myers, Stewart C. & Majluf, Nicholas S., 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Journal of Financial Economics, Elsevier, vol. 13(2), pages 187-221, June.
    4. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    5. Ellis Scharfenaker & Gregor Semieniuk, 2015. "A Statistical Equilibrium Approach to the Distribution of Profit Rates," SCEPA working paper series. SCEPA's main areas of research are macroeconomic policy, inequality and poverty, and globalization. 2015-05, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    6. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    7. Toni M. Whited, 2001. "Is It Inefficient Investment that Causes the Diversification Discount?," Journal of Finance, American Finance Association, vol. 56(5), pages 1667-1691, October.
    8. Ali A. Bolbol & Mark A. Lovewell, 2001. "Three Views on Stock Markets and Corporate Behavior: Tobin, Veblen, and Marx," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 23(3), pages 527-543, March.
    9. Lindenberg, Eric B & Ross, Stephen A, 1981. "Tobin's q Ratio and Industrial Organization," The Journal of Business, University of Chicago Press, vol. 54(1), pages 1-32, January.
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    Cited by:

    1. Ellis Scharfenaker & Duncan Foley, 2017. "Maximum Entropy Estimation of Statistical Equilibrium in Economic Quantal Response Models," Working Papers 1710, New School for Social Research, Department of Economics, revised May 2017.

    More about this item

    Keywords

    Tobin’s q; Information Theory; Statistical Mechanics; Observational Economics;

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • G1 - Financial Economics - - General Financial Markets
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

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