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A Primer on Structural Estimation in Accounting Research

Author

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  • Jeremy Bertomeu
  • Ying Liang
  • Iván Marinovic

Abstract

This primer offers a hands-on accessible guide to writing and estimating structural models. We review commonly-used methodologies, including dynamic programming, maximum likelihood, generalized and simulated method of moments, conditional choice probabilities as well as tools to compute standard errors and common diagnostics and tests of economic hypotheses. Special attention is devoted to the bootstrap as a convenient toolbox to estimate complex economic interactions. The methods are illustrated with recent developments in earnings management, auditing, investment, accounting conservatism, and disclosure theory. Intuition and applications are emphasized over formalism.

Suggested Citation

  • Jeremy Bertomeu & Ying Liang & Iván Marinovic, 2023. "A Primer on Structural Estimation in Accounting Research," Foundations and Trends(R) in Accounting, now publishers, vol. 18(1-2), pages 1-137, June.
    • Handle: RePEc:now:fntacc:1400000074
    DOI: 10.1561/1400000074
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    References listed on IDEAS

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    Cited by:

    1. Breuer Matthias, 2025. "Another Way Forward: Comments on Ohlson’s Critique of Empirical Accounting Research," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 15(1), pages 123-139.

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