analysts need not imply a high degree of confidence in their point estimates. However, there is a large body of literature that has studied forecast dispersion, and on balance these studies confirm that forecast dispersion is a useful proxy for uncertainty.<sup>15</sup> For each firm, I construct this proxy for uncertainty using all the forecasts issued by analysts within a fiscal year. Following Gilchrist et al. (2005), dispersion is defined as the logarithm of the fiscal year average of the monthly standard deviation of analysts’ forecasts of earnings per share, times the number of shares, scaled by the book value of total assets. That is, where _t_ and _j_ denote year and month respectively. _Ntj_ is the number of shares outstanding, and _SDtj_ is the standard deviation of the per-share earnings forecasts for all analysts making forecasts for month j.

The second measure of managerial information quality is based on insider trading activity (Chen et al. (2007) and Foucault and Fresard (2013)). Managers should be more likely to trade their own stock and make a profit on these trades if they are more confident in their information. Although managers don’t always trade on information, the premise is that on average, managers with better information will trade more. To build this proxy for managerial information, I obtain corporate insiders’ trades from the Thomson Financial Insider Trading database. I measure the quality of managers’ information with the intensity of a firm’s insider trading activity, _INSIDERit_ , calculated as the ratio of the firm’s shares traded by insiders in a year to the total number of firm shares traded. As in other studies I only include open market stock transactions initiated by the top five executives (CEO, CFO, COO, President and Chairman of the Board).<sup>16</sup> Since _INSIDERit_ is a measure of absolute insider trading activity, it captures managerial information but not the direction of such information, that is, whether the firm has a positive or a negative outlook. My second proxy for the firm’s uncertainty about fundamentals is 1 _− INSIDER_ . While insider trades may reveal managers’ firm-specific information not embodied in share prices, a potential drawback to this proxy for uncertainty is that the lack of insider trading might

> that analysts don’t put a lot of weight on what they are hearing from the firm when firms provide noisy information.

> 15Earlier papers using forecast dispersion to proxy for uncertainty include Bomberger and Frazer (1981), Lambros and Zarnowitz (1987) and Barron and Stuerke (1998). Using the Survey of Professional Forecasters (SPF), Lambros and Zarnowitz (1987) show a positive correlation between forecast dispersion and uncertainty, where uncertainty is proxied by the spread of the probability distribution of point forecasts. IBES distributes only point forecasts, but the SPF provides both point forecasts and the histogram of forecasts for GDP, unemployment, inflation, and other major macroeconomic variables. In recent papers, Avramov et al. (2009) and Guntay and Hackbarth (2010) study forecast dispersion as a measure of uncertainty about firms’ future earnings. Guntay and Hackbarth (2010) find that dispersion is positively associated with credit spreads, and it appears to proxy largely for future cash flow uncertainty.

> 16Foucault and Fresard (2013) and Peress (2010).

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