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How to Conduct High-quality Empirical Accounting Research By Bin Ke Associate Professor, Pennsylvania State University Visiting Professor, Cheung Kong.

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Presentation on theme: "How to Conduct High-quality Empirical Accounting Research By Bin Ke Associate Professor, Pennsylvania State University Visiting Professor, Cheung Kong."— Presentation transcript:

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

2 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 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 4 Writing a paper is analogous to making a car Design stage Manufacturing stage Marketing stage

5 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 6 Design Stage

7 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 8 Examples of good research Watts and Zimmerman (1986) Scholes and Wolfson (1992) Bernard and Thomas (1990) Burgstahler and Dichev (1997)

9 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 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 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 12 Manufacturing Stage

13 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 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 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 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 17 Marketing Stage

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

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


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