Abstract From the standpoint of financial statement analysis and forecasting, most business firms are also "miserable experimental designs." Accounting researchers, nevertheless, often rely heavily upon the fallible statistical tools of such designs. A major danger is the mechanical use of statistical techniques in overly superficial settings which have little or no relevance to accounting issues. This paper is directed to this danger which seems to be increasingly common in the accounting literature. Particular attention is directed to autocorrelation in accounting data experimental design." Unfortunately, statistical tools in experimental design and analysis are not easily adapted to miserable situations rampant with non-stationarities, interactions, missing variables, measurement error, autocorrelation, multicollinearities, etc. Autocorrelation is also ignored in many behavioral accounting experiments, especially where subjects are asked to make sequential decisions. For example, little attention is devoted to such issues in lens model studies of decision making.
Robert E. Jensen (Mon,) studied this question.
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