Knowledge that Transforms

For fossil fuel power plants to be built in the future, carbon capture and storage (CCS) technologies offer the potential for significant reductions in carbon dioxide (CO 2 ) emissions. We examine the break-even value for CCS adoptions, that is, the critical value in the charge for CO 2 emissions that would justify investment in CCS capabilities. Our analysis takes explicitly into account that the supply of electricity at the wholesale level (generation) is organized competitively in some U.S. jurisdictions, whereas in others a regulated utility provides integrated generation and distribution services. For either market structure, we find that emissions charges near $30 per tonne of CO 2 would be the break-even value for adopting CCS capabilities at new coal-fired power plants. The corresponding break-even values for natural gas plants are substantially higher, near $60 per tonne. Our break-even estimates serve as a basis for projecting the change in electricity prices once carbon emissions become costly. CCS capabilities effectively put an upper bound on the increase in electricity prices resulting from carbon regulations, and we estimate this bound to be near 30% at the retail level for both coal and natural gas plants. In contrast to the competitive power supply scenario, however, these price increases materialize only gradually for a regulated utility. The delay in price adjustments reflects that for regulated firms the basis for setting product prices is historical cost, rather than current cost.

We address the value of quick response production practices when selling to a forward-looking consumer population with uncertain, heterogeneous valuations for a product. Consumers have the option of purchasing the product early, before its value has been learned, or delaying the purchase decision until a time at which valuation uncertainty has been resolved. Whereas individual consumer valuations are uncertain ex ante, the market size is uncertain to the firm. The firm may either commit to a single production run at a low unit cost prior to learning demand, or commit to a quick response strategy that allows additional production after learning additional demand information. We find that the value of quick response is generally lower with strategic (forward-looking) customers than with nonstrategic (myopic) customers in this setting. Indeed, it is possible for a quick response strategy to decrease the profit of the firm, though whether this occurs depends on various characteristics of the market; specifically, we identify conditions under which quick response increases profit (when prices are increasing, when dissatisfied consumers can return the product at a cost to the firm) and conditions under which quick response may decrease profit (when prices are constant or when consumer returns are not allowed).

We study a period of severe disequilibrium to investigate whether board characteristics are related to corporate investment, debt usage, and firm value. During the 1930-1938 Depression era, when the corporate sector was shocked by an unprecedented downturn, we document a relation between board characteristics and firm performance that varies in economically sensible ways: Complex firms (that would benefit more from board advice) exhibit a positive relation between board size and firm value, and simple firms exhibit a negative relation between board size and firm value. Moreover, simple firms with large boards do not downsize adequately in response to the severe economic contraction: they invest more (or shrink less) and use more debt during the 1930s. We document similar effects for the number of outside directors on the board. Finally, we also find that companies with properly aligned governance structures are more likely to replace the company president following poor performance.

Preference reversals have been widely studied using risky or riskless gambles. However, little is known about preference reversals under ambiguity (unknown probabilities). Subjects were asked to make a binary choice between ambiguous P-bets (big likelihood of giving small prize) and ambiguous $-bets (small likelihood of giving large prize) and their willingness to accept was elicited. Subjects then performed the same two tasks with risky bets, where the probability of winning for a given risky bet is the center of the probability interval of the corresponding ambiguous bet. Preference reversals are not only replicated under ambiguity but are even stronger than are those under risk. This is due to higher elicited prices for the $-bet and lower elicited prices for the P-bet under ambiguity than under risk. This result can be explained by the shape of the weighting function for different levels of uncertainty and for different elicitation modes.

This paper models the generation, circulation, and completion of new ideas, showing how markets and innovative firms complement each other in a symbiotic relationship. Novel ideas are initially incomplete and require further insight before yielding a valuable innovation. Finding the complementary piece requires ideas to circulate, which creates appropriation risks. Circulation of ideas in markets ensures efficient completion, but because ideas can be appropriated, market entrepreneurs underinvest in idea generation. Firms can establish boundaries that guarantee safe circulation of internal ideas, but because firms need to limit idea circulation, they may fail to achieve completion. Spin-offs allow firms to benefit from the market's strength at idea completion, whereas markets benefit from firms' strength at generating new ideas. The model predicts diverse organizational forms (internal ventures, spin-offs, and start-ups) coexisting and mutually reinforcing each other. The analysis provides new insights into the structure of innovation-driven clusters such as Silicon Valley.

We consider the problem of dynamic portfolio optimization in a discrete-time, finite-horizon setting. Our general model considers risk aversion, portfolio constraints (e.g., no short positions), return predictability, and transaction costs. This problem is naturally formulated as a stochastic dynamic program. Unfortunately, with nonzero transaction costs, the dimension of the state space is at least as large as the number of assets, and the problem is very difficult to solve with more than one or two assets. In this paper, we consider several easy-to-compute heuristic trading strategies that are based on optimizing simpler models. We complement these heuristics with upper bounds on the performance with an optimal trading strategy. These bounds are based on the dual approach developed in Brown et al. (Brown, D. B., J. E. Smith, P. Sun. 2009. Information relaxations and duality in stochastic dynamic programs. Oper. Res. 58(4) 785–801). In this context, these bounds are given by considering an investor who has access to perfect information about future returns but is penalized for using this advance information. These heuristic strategies and bounds can be evaluated using Monte Carlo simulation. We evaluate these heuristics and bounds in numerical experiments with a risk-free asset and 3 or 10 risky assets. In many cases, the performance of the heuristic strategy is very close to the upper bound, indicating that the heuristic strategies are very nearly optimal.

We study how a manager's short-term interest in the firm's market value may motivate channel stuffing: shipping excess inventory to the downstream channel. Channel stuffing allows a manager to report sales in excess of demand in order to influence investors' valuation of the firm. We apply an inventory model that highlights the potential role of inventory in the manager's channel stuffing and the investors' valuation strategies. Sales in our model are constrained by available inventory. Our model yields a semiseparating and semipooling equilibrium contingent on the initial inventory level: When the demand is lower than a threshold that depends on and is below the initial inventory level, the manager pads sales by a part of the excess inventory and releases the inflated sales report. The investors “correct” the reported sales and are able to infer perfectly the firm's value. When the demand reaches or exceeds this threshold, the manager pads any excess inventory to the sales and reports the initial inventory is sold out, which censors large demand realizations. Then the investors only infer the real demand is no less than the threshold and value the firm accordingly by expectation. Channel stuffing can influence the inventory decision, too. We find both over- and underinvestment in the initial inventory can arise in our model. We discuss empirical and managerial implications of our findings.

We use hospital-level discharge data from cardiac patients in California to estimate the effects of focus on operational performance. We examine focus at three distinct levels of the organization—at the firm level, at the operating unit level, and at the process flow level. We find that focus at each of these levels is associated with improved outcomes, namely, faster services at higher levels of quality, as indicated by lower lengths of stay (LOS) and reduced mortality rates. We then analyze the extent to which the superior operational outcome is driven by focused hospitals truly excelling in their operations or by focused hospitals simply “cherry-picking” easy-to-treat patients. To do this, we use an instrumental variables estimation strategy that effectively randomizes the assignment of patients to hospitals. After controlling for selective patient admissions, the previously observed benefits of firm level focus disappear; focused hospitals no longer demonstrate a statistically significant reduction in LOS or mortality rate. However, at more granular measures of focus within the hospital (e.g., operating unit level), we find that more focus leads to a shorter LOS, even after controlling for selective admission effects.

We derive explicit solutions to life-cycle utility maximization problems involving stock and bond investment, perishable consumption, and the rental and ownership of residential real estate. Prices of houses, stocks and bonds, and labor income are correlated. Because of a positive correlation between house prices and labor income, young individuals want little exposure to house price risk and tend to rent their home. Later in life the desired housing investment increases and will eventually reach and exceed the desired consumption, suggesting that the individual should buy his home—and either additional housing units (for renting out) or house price–linked financial assets. In the final years, preferences shift back to home rental. The derived strategies are still useful if housing positions are only reset infrequently. Our results suggest that markets for real estate investment trusts or other house price–linked contracts lead to nonnegligible welfare gains.

This paper analyzes the impact of endogenous credit terms under capital market imperfections in a capacity investment setting. We model a monopolist firm that decides on its technology choice (flexible versus dedicated) and capacity level under demand uncertainty. Differing from the majority of the stochastic capacity investment literature, we assume that the firm is budget constrained and can relax its budget constraint by borrowing from a creditor. The creditor offers technology-specific loan contracts to the firm, after which the firm makes its technology choice and subsequent decisions. Capital market imperfections impose financing frictions on the firm. Our analysis contributes to the capacity investment literature by extending the theory of stochastic capacity investment and flexible versus dedicated technology choice to understand the impact of capital market imperfections, and by analyzing the impact of demand uncertainty (variability and correlation) on the operational decisions and the performance of the firm under different capital market conditions. We demonstrate that the endogenous nature of credit terms in imperfect capital markets may modify or reverse conclusions concerning capacity investment and technology choice obtained under the perfect market assumption and we explain why. The theory developed in this paper suggests some rules of thumb for the strategic management of the capacity and technology choice in imperfect capital markets.