We examine the effect of investment lumpiness on firms' default risk. A structural model is established and shows that firms with lumpier (or more indivisible) investments will encounter higher credit risk, all else being equal. We use the model solutions to simulate investment and default dynamics for a variety of firms structurally similar to their empirical counterparts. Using the relative size of investments, time between investments, and the skewness of investment rates as the proxies of investment lumpiness, the regression exercises of the simulated samples demonstrate that the degree of lumpiness is monotonically related to the probability of default. The models' implications are generally supported by reduced-form tests using actual data. This article sheds new light on the linkage between firms' investment patterns and default risk.

The learning curve has a significant impact on production cost (hence corporate profit) in a number of industries. While the learning curve is well recognized in the Economics literature and its effect on operating costs and production decisions widely studied, its effect on corporate investment has been largely unexplored. To our knowledge, there is one paper that examines this issue, but it is limited to unlevered firms. We therefore examine a levered firm's optimal investment and financing choices when using learning-curve technology. The main findings are as follows. The effect of leverage on the investment decision depends on the level of debt. Using the optimal debt level will result in earlier and larger investment. Thus, leverage has a positive effect on investment overall, and the difference between levered and unlevered firm is an increasing function of learning speed. The optimal leverage ratio (without a borrowing constraint) is an increasing function of learning speed. With a borrowing constraint, the investment decision is similar to the unconstrained-borrowing case, but the leverage ratio is initially increasing and subsequently decreasing in learning speed. Moreover, it is a decreasing function over a wider range for a more stringent borrowing constraint, for decreasing-returns-to-scale technology and for a less volatile product market.

Most capital projects have an implementation lag. We examine the effect of implementation lag on a levered firm’s investment decision. The main finding is that implementation lag can potentially have a substantial effect on a levered company’s investment trigger, and this effect can be significantly different from that of an unlevered company. The exact relationship between lag and investment trigger depends on the level of debt used by the firm. For an optimally-levered firm, a crucial determinant of the lag-investment relationship is the fraction of investment cost that has to be incurred upfront. If this fraction is small, investment trigger is a decreasing function of implementation lag and the effect can be economically significant. If this fraction is large, investment trigger can be either increasing or decreasing in lag, depending on parameter values, but the magnitude of the effect is not large. Optimally levering a firm makes the implementation lag more investment-friendly relative to an unlevered firm, thus it is possible that the lag has a negative effect on investment if the firm is unlevered but a positive effect if the same firm is optimally-levered. For an optimally-levered firm, implementation lag generally has a non-negative effect on investment.