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Causal Inference in Accounting Research

Author

Listed:
  • Gow, Ian D.

    (Harvard University)

  • Larcker, David F.

    (Stanford University)

  • Reiss, Peter C.

    (Stanford University)

Abstract

This paper examines the approaches accounting researchers use to draw causal inferences using observational (or non-experimental) data. The vast majority of accounting research papers draw causal inferences notwithstanding the well-known difficulties in doing so. While some recent papers seek to use quasi-experimental methods to improve causal inferences, these methods also make strong assumptions that are not always fully appreciated. We believe that accounting research would benefit from: more in-depth descriptive research, including a greater focus on the study of causal mechanisms (or causal pathways); increased emphasis on structural modeling of the phenomena of interest. We argue these changes offer a practical path forward for rigorous accounting research.

Suggested Citation

  • Gow, Ian D. & Larcker, David F. & Reiss, Peter C., 2016. "Causal Inference in Accounting Research," Research Papers 3393, Stanford University, Graduate School of Business.
  • Handle: RePEc:ecl:stabus:3393
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