Empirical accounting research design for Ph.D

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Karl R. Knapp – Article Summary
Selto, F. H. (1986). Empirical accounting research design for Ph.D. students. The Accounting
Review, 61, 338-350.
Hypothesis / Relevant Factors Discussed / Conclusion / Your Take
Positive is concerned with what is or is not
Normative is concerned with what should or should not be
Framework for constructing research - development and testing of new theories of how the world
works, or refutation of widely held existing theories. (Not normative, how it ought to be).
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Begins with a real world problem
A theory is formed (hypothesis)
Data is collected
Accounting measurements can be either surrogates (proxies) or the actual principle
themselves
Theory credibility comes from hypothesis test results being consistent with the theory and
from ruling out alternative explanations
 Y = dependent variable to be understood
 X = independent variable proposed theory says effects Y
 Vs = factors prior to the study that effect Y
 Zs = current factors other than X that effect Y
Y/X primary, V/Z are control variables, may be thought of as a single term.
Example
 X = a change in accounting methods
 Vs = prior period results (profitability), personality traits, math ability, education, …
 Zs = market return, accounting practices of other firms, true state of the firm, …
Ways to deal with Vs
 Ignore Vs, hoping Vs is random (doesn’t work very often)
 Match sample ex-post to control for Vs (most common)
 Covariance analysis (hard to tell which approach, matching or covariance) works better
Must balance:
Alpha – probability of incorrectly rejecting a true null hypothesis of no treatment
Beta – probability of not rejecting a null hypothesis when there is a treatment effect
Sample Size
Power – take magnitude of proposed treatment effect into account when designing tests. Adjust
by increasing sample size, increasing theory magnitude, dealing with Vs and Zs better.
Don’t hype secondary hypotheses
Don’t rework variables just because results were insignificant (“preliminary”)
Always look for outliers and treat them equally
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