Lichtenstein, Fischhoff and Phillips, 1982; Yates, 1990; Griffin and Tversky, 1992). Exceptions to overconfidence in calibration are that people tend to be underconfident when answering easy questions, and they learn to be well-calibrated when predictability is high and when performing repetitive tasks with fast, clear feedback. For example, expert bridge players(Keren, 1987),race- track bettors(Dowie, 1976: Hausch, Ziemba and Rubinstein, 1981) and meteorologists(Murphy and Winkler, 1984)tend to be well-calibrated There are a number of reasons why we might expect the overconfidence of managers to exceed that of the general population. 1) Capital budgeting decisions can be quite complex. They often require projecting cash flows for a wide range of uncertain outcomes. Typically people are most erconfident about such difficult problems. 2)Capital budgeting decisions are not well suited for learning. Learning occurs "when closely similar problems are frequently encountered, especially if the outcomes of decisions are quickly known and provide unequivocal feedback?"(Kahneman encountered,outcomes are often delayed for long periods of time, and feedback is typically tip ind Lovallo, 1993). But the major investment policy decisions we study here are not frequentl noisy. Furthermore, it is often difficult for a manager to reject the hypothesis that every situation is new in important ways, allowing him to ignore feedback from past decisions altogether. Learnin from experience is highly unlikely under these circumstances(Brehmer, 1980; Einhorn and Hogarth 1978). 3)Unsuccessful managers are less likely to retain their jobs and be promoted. Those who do succeed are likely to become overconfident because of self-attribution bias. Most people overestimate the degree to which they are responsible for their own success(Miller and Ross, 1975; Langer and Roth, 1975; Nisbett and Ross, 1980). This self-attribution bias causes the successful to become overconfident(Daniel, Hirshleifer and Subrahmanyam, 1998; Gervais and Odean, 2001 ). 4) Finally, managers may be more overconfident than the general population because of selection bias. Those who are overconfident and optimistic about their prospects as managers are more likely to apply for these jobs. Firms, too, may select on the basis of apparent confidence and optimism, either because the applicants overconfidence and optimism are perceived to be signs of greater ability or because, as in our model, shareholders recognize that it is less expensive to hire overconfident, optimistic managers who suit their needs than it is to hire rational managers who do 2.2 Overconfidence and Optimism in Finance Recent studies explore the implications of overconfidence for financial markets. In Benos(1998) traders are overconfident about the precision of their own signals and their knowledge of the siLichtenstein, Fischhoff and Phillips, 1982; Yates, 1990; Griffin and Tversky, 1992). Exceptions to overconfidence in calibration are that people tend to be underconfident when answering easy questions, and they learn to be well-calibrated when predictability is high and when performing repetitive tasks with fast, clear feedback. For example, expert bridge players (Keren, 1987), race￾track bettors (Dowie, 1976; Hausch, Ziemba and Rubinstein, 1981) and meteorologists (Murphy and Winkler, 1984) tend to be well-calibrated. There are a number of reasons why we might expect the overconfidence of managers to exceed that of the general population. 1) Capital budgeting decisions can be quite complex. They often require projecting cash flows for a wide range of uncertain outcomes. Typically people are most overconfident about such difficult problems. 2) Capital budgeting decisions are not well suited for learning. Learning occurs “when closely similar problems are frequently encountered, especially if the outcomes of decisions are quickly known and provide unequivocal feedback” (Kahneman and Lovallo, 1993). But the major investment policy decisions we study here are not frequently encountered, outcomes are often delayed for long periods of time, and feedback is typically very noisy. Furthermore, it is often difficult for a manager to reject the hypothesis that every situation is new in important ways, allowing him to ignore feedback from past decisions altogether. Learning from experience is highly unlikely under these circumstances (Brehmer, 1980; Einhorn and Hogarth, 1978). 3) Unsuccessful managers are less likely to retain their jobs and be promoted. Those who do succeed are likely to become overconfident because of self-attribution bias. Most people overestimate the degree to which they are responsible for their own success (Miller and Ross, 1975; Langer and Roth, 1975; Nisbett and Ross, 1980). This self-attribution bias causes the successful to become overconfident (Daniel, Hirshleifer and Subrahmanyam, 1998; Gervais and Odean, 2001). 4) Finally, managers may be more overconfident than the general population because of selection bias. Those who are overconfident and optimistic about their prospects as managers are more likely to apply for these jobs. Firms, too, may select on the basis of apparent confidence and optimism, either because the applicant’s overconfidence and optimism are perceived to be signs of greater ability or because, as in our model, shareholders recognize that it is less expensive to hire overconfident, optimistic managers who suit their needs than it is to hire rational managers who do so. 2.2 Overconfidence and Optimism in Finance Recent studies explore the implications of overconfidence for financial markets. In Benos (1998), traders are overconfident about the precision of their own signals and their knowledge of the sig- 4