We analyze contract choices, loan-repayment behavior, and welfare in a model of a competitive credit market when borrowers have a taste for immediate gratification. Consistent with many credit cards and subprime mortgages, for most types of nonsophisticated borrowers the baseline repayment terms are cheap, but they are also inefficiently front loaded and delays require paying large penalties. Although credit is for future consumption, nonsophisticated consumers overborrow, pay the penalties, and back load repayment, suffering large welfare losses. Prohibiting large penalties for deferring small amounts of repayment—akin to recent regulations in the US credit-card and mortgage markets—can raise welfare.

We modify the Salop (1979) model of price competition with differentiated products by assuming that consumers are loss averse relative to a reference point given by their recent expectations about the purchase. Consumers' sensitivity to losses in money increases the price responsiveness of demand—and hence the intensity of competition—at higher relative to lower market prices, reducing or eliminating price variation both within and between products. When firms face common stochastic costs, in any symmetric equilibrium the markup is strictly decreasing in cost. Even when firms face different cost distributions, we identify conditions under which a focal-price equilibrium (where firms always charge the same “focal” price) exists, and conditions under which any equilibrium is focal.

We explore the learning process and behavior of an individual with unrealistically high expectations (overconfidence) when outcomes also depend on an external fundamental that affects the optimal action. Moving beyond existing results in the literature, we show that the agent's beliefs regarding the fundamental converge under weak conditions. Furthermore, we identify a broad class of situations in which “learning” about the fundamental is self‐defeating: it leads the individual systematically away from the correct belief and toward lower performance. Due to his overconfidence, the agent—even if initially correct—becomes too pessimistic about the fundamental. As he adjusts his behavior in response, he lowers outcomes and hence becomes even more pessimistic about the fundamental, perpetuating the misdirected learning. The greater is the loss from choosing a suboptimal action, the further the agent's action ends up from optimal. We partially characterize environments in which self‐defeating learning occurs, and show that the decisionmaker learns to take the optimal action if, and in a sense only if, a specific non‐identifiability condition is satisfied. In contrast to an overconfident agent, an underconfident agent's misdirected learning is self‐limiting and therefore not very harmful. We argue that the decision situations in question are common in economic settings, including delegation, organizational, effort, and public‐policy choices.