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The Dividend Ratio Model and Small Sample Bias: A Monte Carlo Study

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  • John Y. Campbell
  • Robert J. Shiller

Abstract

Small sample properties of parameter estimates and test statistics in the vector autoregressive dividend ratio model (Campbell and Shiller [1988 a,b]) are derived by stochastic simulation. The data generating processes are co integrated vector autoregressive models, estimated subject to restrictions implied by the dividend ratio model, or altered to show a unit root.

Suggested Citation

  • John Y. Campbell & Robert J. Shiller, 1988. "The Dividend Ratio Model and Small Sample Bias: A Monte Carlo Study," NBER Technical Working Papers 0067, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0067 Note: ME EFG
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    References listed on IDEAS

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    1. Flavin, Marjorie A, 1983. "Excess Volatility in the Financial Markets: A Reassessment of the Empirical Evidence," Journal of Political Economy, University of Chicago Press, vol. 91(6), pages 929-956, December.
    2. Marsh, Terry A & Merton, Robert C, 1986. "Dividend Variability and Variance Bounds Tests for the Rationality ofStock Market Prices," American Economic Review, American Economic Association, pages 483-498.
    3. Marsh, Terry A & Merton, Robert C, 1987. "Dividend Behavior for the Aggregate Stock Market," The Journal of Business, University of Chicago Press, vol. 60(1), pages 1-40, January.
    4. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," Review of Financial Studies, Society for Financial Studies, pages 195-228.
    5. Marsh, Terry A. & Merton, Robert C., 1984. "Dividend variability and variance bounds tests for the rationality of stock market prices," Working papers 1584-84., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    6. Kleidon, Allan W, 1986. "Variance Bounds Tests and Stock Price Valuation Models," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 953-1001, October.
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    Cited by:

    1. Alina Lucia Trifan, 2009. "Testing Capital Asset Pricing Model For Romanian Capital Market," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, pages 1-43.
    2. Mercereau, BenoƮt & Miniane, Jacques Alain, 2008. "Should We Trust the Empirical Evidence from Present Value Models of the Current Account?," Economics Discussion Papers 2008-10, Kiel Institute for the World Economy (IfW).
    3. Diego Comin & Mark Gertler & Ana Maria Santacreu, 2009. "Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations," Harvard Business School Working Papers 09-134, Harvard Business School.
    4. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2016. "Predictability Hidden by Anomalous Observations," Papers 1612.05072, arXiv.org.
    5. Robert J. Shiller, 2014. "Speculative Asset Prices (Nobel Prize Lecture)," Cowles Foundation Discussion Papers 1936, Cowles Foundation for Research in Economics, Yale University.
    6. Lleo, Sebastien & Ziemba, William T., 2014. "Does the bond-stock earning yield differential model predict equity market corrections better than high P/E models?," LSE Research Online Documents on Economics 59290, London School of Economics and Political Science, LSE Library.
    7. Engsted, Tom, 2002. " Measures of Fit for Rational Expectations Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 301-355, July.
    8. Oliver D. Bunn & Robert J. Shiller, "undated". "Changing Times, Changing Values: A Historical Analysis of Sectors within the US Stock Market 1872-2013," Cowles Foundation Discussion Papers 1950, Cowles Foundation for Research in Economics, Yale University.

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