This paper presents a statistical procedure to identify effects of three potential structural changes on accounting earnings – temporary, short-run, and long-run. The procedure is applied to quarterly accounting earnings of 39 utility companies. Structural changes are found to be commonplace. Statistical forecasting models that explicitly incorporate structural change effects are found to generate more accurate forecasts than other statistical models in the literature. Although no statistical model significantly dominates Value Line, a firm-specific model with structural change adjustment forecasts as well as Value Line. Moreover, all statistical models examined have significant marginal forecasting power to complement Value Line forecasts.

This paper adapts Dye's (1995) model to evaluate the effects of the 150-hour rule on the audit market. Incorporating the auditors’ education as a joint input with the audit effort for determining the audit quality, we show that the audit fee is higher, pre-rule CPAs are better off, and audit clients are worse off as results of the Rule. Additionally, more pre-rule CPAs elect to enter the audit market. Some less wealthy post-rule CPAs who would otherwise get into the audit market choose not to. Surprisingly, the average audit quality in the market can be lower due to the Rule.

Many firms define their fiscal quarters as 13-week periods so that each fiscal year contains 52 weeks, which leaves out one or two day(s) a year. To compensate, one extra week is added every fifth or sixth year and, consequently, one quarter therein comprises 14 weeks. We find evidence of predictable forecast errors and stock returns in 14-week quarters, suggesting that analysts and investors do not, on average, adjust their expectations for the extra week. The ease with which 14-week quarters can be predicted, and expectations adjusted, suggests a surprising lack of effort on the part of analysts and investors.