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How to Conduct High-quality Empirical Accounting Research

How to Conduct High-quality Empirical Accounting Research. By Bin Ke Associate Professor, Pennsylvania State University Visiting Professor, Cheung Kong Graduate School of Business. A brief intro. to my research interests.

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How to Conduct High-quality Empirical Accounting Research

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  1. How to Conduct High-qualityEmpirical Accounting Research By Bin Ke Associate Professor, Pennsylvania State University Visiting Professor, Cheung Kong Graduate School of Business

  2. A brief intro. to my research interests • Overall goal is to study how firms allocate scarce economic resources to maximize shareholder value • Specific research areas • Earnings management • Insider trading • Professional investors (analysts and money managers) • Taxes • The common theme of my research is to understand how (accounting) information is produced, disclosed, and used by various decision makers inside and outside the firm

  3. Implicit Assumptions • You are highly motivated (i.e., willingness to work hard) • You understand why academic research is important to you and the society • You have a systematic framework to guide your empirical research

  4. Writing a paper is analogous to making a car • Design stage • Manufacturing stage • Marketing stage

  5. The assembly line for a typical paper • Design stage • Start with a general motivational question • Ask a specific question to be tested • Manufacturing stage • Conceive a research design • Sample selection • Data analysis and interpretation • Marketing stage • Write the paper • Endure the review process • Bingo! Paper is published! • The entire cycle typically lasts at least 2 years

  6. Design Stage

  7. What is a good question? • Nobody has done it before • The research question has an impact • Academic community • Practitioners (corporate managers and investors) • Regulators • Readers outside China

  8. Examples of good research • Watts and Zimmerman (1986) • Scholes and Wolfson (1992) • Bernard and Thomas (1990) • Burgstahler and Dichev (1997)

  9. Key questions at the design stage • WWW • What is your research question? • Why is it interesting (i.e., who cares)? • What are your predictions?

  10. How can you develop interesting questions? • No easy answers • A few tips • Develop your own and systematic view of the world • Write down your ideas • Explain your ideas to experienced researchers

  11. Different views of the world • Views on capital market efficiency • Traditional views • Fama (1970) • Behavioral finance view • Shleifer (2000), Barberis and Thaler (2002) • Views on managerial compensation contracts • Optimal contracting (compensation contract is a response to agency problems) • Managerial power view (compensation contract itself is a manifestation of agency problems) • Bebchuk and Fried (2004)

  12. Manufacturing Stage

  13. Research design issues • The structural model • Firm performance=f(governance) • What variables should be in and what variables should be out? • Empirical proxies for theoretical constructs • Causality vs. association • Interpretation of your results (i.e., can the research design answer intended question?)

  14. From theoretical constructs to empirical proxies • Example 1 • What is information asymmetry? • How to measure it? • Huddart and Ke (2004) • Example 2 • What is earnings management? • How to measure it? • Jones (1991) • Burgstahler and Dichev (1997) • What are the consequences of poorly measured constructs?

  15. How to demonstrate a causal relation? • Manipulate the causes • Beatty, Ke and Petroni (2002) • Ke and Petroni (2004) • Ke, Petroni and Yu (2005) • Statistical solutions • Fixed effects regression • Ke and Ramalingegowda (2005) • Two-stage least squares • Huddart, Ke and Shi (2005)

  16. From results to interpretation • Understand your research design’s limitations • What you can say from your results • What you cannot say from your results • Disclose your limitations • Example: Francis and Ke (2004)

  17. Marketing Stage

  18. How to sell your “car”? • Write clearly and logically • Simplicity is beauty • Logical arguments • Satisfy reviewers’ concerns • Have some good luck

  19. Summary • Good questions • Clear predictions • Strong research design • Robust results

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