The Effect of Industry Diversification on Consensus and Individual Analysts' Earnings Forecasts

We study the effects of company diversification and analyst diversification on consensus and individual analysts' earnings forecasts. Company diversification is measured both as the number of segments reported by a company and as an entropy measure which decomposes the total diversification into an unrelated and a related component. For the consensus forecast analysis, we examine the effect of these variables both on forecast accuracy and inter-analyst earnings forecast disagreement. For the individual analyst forecast analysis, we examine the effect of the number of business segments followed by an analyst and analyst diversification on individual analyst forecast accuracy. We develop a new measure of individual analyst's diversification which takes into consideration the business segments of all companies followed by an analyst, and its interaction with the business segments of the company whose earnings are being forecasted. The results of our study show that as the level of a company's total diversification increases, analysts are less accurate in their earnings forecasts and have more inter-analyst disagreement. Analysts are less accurate and have more disagreement as unrelated diversification increases. A company's related diversification has no significant impact on these variables. For both forecast accuracy and inter-analyst disagreement, the impact of a unit of unrelated diversification is significantly higher than that of the impact of a unit of related diversification. For individual analysts' earnings forecasts, as the number of business segments followed by an analyst increases and as his level of diversification increases, his earnings forecast accuracy significantly declines. The results of our study have implications for researchers who use analysts? earnings forecasts in their studies, investors who use these forecasts for company valuation and for brokerage firms in evaluating individual analysts