Many municipalities or governments face challenges in financing their infrastructure. Hong Kong’s transit operator designed a novel scheme whereby it receives fare revenues, but also partakes in a property management business, exploiting the positive externalities of public transport on property prices. We develop a Stackelberg game of timing under uncertainty to explore the rationale of this scheme. The underlying mathematical problem is nontrivial because the Stackelberg’s leader faces a two-dimensional optimal stopping problem (which cannot be reduced by a change of numeraire) with a gain function that is nondifferentiable due to strategic interactions. We solve this problem analytically via the intermediation of a ‘penalized problem’ and derive interesting, novel managerial insights. The main insight is that internalizing positive externalities provides additional revenue sources for defraying the overall costs of infrastructure investments, thereby accelerating the delivery of infrastructure.

This paper investigates the role of stakeholder preference on corporate social responsibility (CSR) strategies. Using a staggered difference-in-differences approach, we show that Indian firms increase CSR expenses when trade restrictions (Antidumping) are initiated against competing Chinese exports from countries with a high stakeholder preference for CSR. However, when these shocks emanate from countries with a lower stakeholder preference, CSR expenses remain unchanged. Capital expenditure and R&D of Indian firms increase following trade shocks, irrespective of their country of origin. Finally, CSR spending provides these Indian firms with significant real option value only when the demand shocks originate from countries with a higher CSR preference. Collectively, we provide evidence for consumer-driven CSR strategies.

We argue that, compared with domestic M&As, cross-border M&As have positive performance implications for the acquirers in terms of an increase in growth option value when the acquisitions increase the diversity of the acquirers’ technology portfolio. This positive influence is strengthened if the target firms’ foreign country exhibits greater economic uncertainty. Exercise of embedded real options in diverse technology portfolios makes cross-border acquirers likely to experience higher profitability in the long term, while cross border M&As can be detrimental to short term profit. We find support for this real options logic of cross-border acquisitions in an analysis of M&As by the population of U.S. listed firms during 1991-2014.

This paper studies the effects the overlapping ownership in acquisition deals. Different structures (controlling or non-controlling) for the common shareholder are considered. Furthermore, we analyze the acquisition dynamics both when the synergy only depends on controlling the target, as well as when full integration is required.

This paper proposes a decision-making framework for entrepreneurs who are willing to launch their crowdfunding campaign on a crowdfunding platform. In particular, we propose a method, based on real options, for choosing the launch date of the campaign depending on the observed status of the platform. The entrepreneur's objective is to maximize the expected amount of funds she collects on the platform, and this latter depends on the quality of the proposed project, but also on the number and qualities of the concurrent projects during the campaign lifetime. We model the platform state evolution with time using a Markov chain and derive the expected campaign outcome starting from a given status. We then propose a dynamic programming approach that determines the optimal campaign launch time.

Typically product demand follows a product lifecycle (PLC). This means that after a product is introduced, demand for this product first starts to grow, which after some time is followed by a decline in demand. Moreover, in most cases demand is stochastic. This paper combines these two characteristics by employing a geometric Brownian motion process with a first increasing and afterwards decreasing trend. Our aim of the paper is to investigate the optimal investment decision of a firm in production capacity. The investment decision involves deciding about the timing and the size of the investment. We make a distinction between firms being a ``product-lifecycle leader'' and a ``product-lifecycle follower''. For a PLC-leader the growth stage starts at the moment this firm invests. In case of a PLC-follower, the firm enters an existing product lifecycle, implying that the decline can already start before this firm even has invested. One of the interesting results is that a PLC-leader waits for a higher demand level before it invests with the same amount when the expected length of the growth interval is shorter. For the PLC-follower it holds that it may be optimal to invest earlier because of this probability that the decline could already start before the firm invests. In such a case the expected future demand is lower, which makes it optimal that the firm attracts less capacity. This makes the investment cheaper and then the firm does not need to wait for a high demand level to make the investment profitable.

We analyze a revenue sharing contract within a decentralized supply chain, extending prior works to a multiperiod setting under buyer production flexibility. We model a buyer’s capacity choice and utilization under external procurement, where quantities are obtained from a supplier firm. The supplier firm chooses a revenue sharing contract with the buyer by internalizing the impact this would have on buyer decisions relating to capacity, utilization choice and the final downstream price of the product. Our framework provides a valuation of the buyer and supplier firms under uncertainty and predictions on the optimal capacity choice of firms in downstream markets and the pricing policy of upstream firms in relation to buyer capacity constraints, the volatility and growth of downstream prices, and the elasticity of demand. We find that for a fixed revenue sharing contract a high volatility of downstream demand results in higher installed capacity by the buyer to account for future flexibility to adjust production which makes a given contract more valuable for both the buyer and supplier. We generally find however a higher revenue share claimed by the supplier when downstream demand is more volatile. In an extension of this framework we also show that suppliers could impose minimum order quantities to extract value from a buyer firm by limiting buyer’s production flexibility. We also consider the decisions of a vertically integrated firm showing that the gains from vertical integration are higher when volatility is high, that is, when production flexibility is more important.

Building on earlier literature, we develop a framework for real options valuation of a sequential oil project. Investments at each sequential stage of oil project lifecycle are highly costly, lumpy and are sunk, for the most part, once expended. More so, each successive stage prior to the production stage typically does not lead to immediate cash flows but opens further investment opportunities. The capital intensity of oil investments, particularly at the development stage, makes them irreversible because the oil wells and operation facilities can only be used to produce oil. These complexities are exacerbated by the various uncertainties faced by these projects. Among these is the uncertainty about the oil price which influences the value of an oil project. Another is the uncertain time to completion of the preceding stages to production stage, particularly the development stage that requires large capital-intensive investments in facilities and infrastructure that take a long time to build. In particular, our framework applies Geometric Brownian Motion to model oil prices and incorporates an uncertain time to completion of the development phase. We obtain some closed form solutions for project values and threshold prices at which the firm should invest immediately. Finally, we undertake sensitivity analysis by varying some input parameters, such as oil price volatility and the expected duration of the development stage. Our case study is Uganda’s oil project in the Albertine Graben region. However, the framework is applicable to a broader range of real options involving lumpy, sequential and costly investments.

We use a compound real options model to investigate the impact of product market characteristics on patent value by considering imperfect patent protection. Patent enforcement can be regarded as a portfolio of options. Once the patent lawsuit is filed, an alleged infringer firm (“challenger”) and an infringed firm (“incumbent”) pay for their ongoing litigation cost using operating cash flows from product market profits. We consider the challenger's strategy to exit the market during litigation due to shortage of funds, the incumbent's strategy to withdraw from value-reducing litigation or to force the challenger to exit the market by a threat to litigate, and firms' strategies to set up royalty payments to avoid a lawsuit, or to settle with each other after a lawsuit is filed. We distinguish between the effects of litigation and settlement on patent values and show first that settlement options raise patent values. By focusing on each firm's ability and willingness to pay for litigation costs, we find that product market characteristics such as the challenger's profit relative to the incumbent's loss of profits due to the alleged infringement (“gain-to-loss ratio”) has to be high enough for settlements to be possible. Settlements are also more likely in less volatile product markets, with more questionable patent validity, and when litigation costs are similar for the two firms. Our model generates new testable implications regarding patent values in a rigorous and comprehensive way.

The increased participation of renewable energy sources, while key to the green shift towards a future with lower carbon emissions, is adding more uncertainty to the electricity markets, due to source intermittency. The distributed aspect of new sources builds up the complexity and may stress the current balancing system. A market-based redispatch is a design intended to efficiently reward providers of flexibility in electricity markets. However, this design may present shortcomings, such as opening up for strategies where market power can be abused to obtain disproportionately high profits. One such strategy happens when power suppliers increase their output in the day-ahead market and decrease it in the real-time market, and this is known as inc-dec gaming. In this paper, we analyse to what degree producers can benefit from engaging in inc-dec gaming, and calculate the impact of measures that aim to prevent or mitigate the harmful effects of inc-dec gaming, and whether implementing these measures entails adverse side effects. An equilibrium problem with equilibrium constraints (EPEC) framework was developed to analyse these issues in a reduced market model with a day-ahead market and a real-time redispatch market. Results indicate that suppliers can abuse market power in order to obtain significant profits through inc-dec gaming. We find that there are effective measures to prevent and mitigate the adverse effects attributable to inc-dec gaming. However, the implementation of these measures brings a trade-off between the suppliers' profits, the system operator's costs, and the consumers' costs, and will not always increase general welfare.

This paper studies investment timing and leverage decisions of firms under caps and floors. Caps and floors have significant effects, not only on investment timing and firm value, but also on leverage ratios and credit spreads. With leverage, a floor has a moderate effect if below a critical level. Above that level, the firm tends to issue less risky debt, being even able to issue risk-free debt, and the floor has a more significant effect, accelerating investment. A lower cap deters investment, increases leverage, but reduces credit spreads. When combined with a floor, in a collar regime, the effects of the cap become non-monotonic, as the firm is able to issue risk-free debt for intermediate levels of the cap. Uncertainty always deters investment, but the effects on leverage and credit spreads are non-monotonic.

We study how common ownership affects the timing and size of capacity investments by duopolists in ways that might lead to anticompetitive outcomes. Alongside accommodation and delay strategies, internalization also allows the leader to block follower entry permanently. We find that internalization magnifies the effect of leader capacity on the follower's capacity and timing, but at low internalization levels the leader still prefers to delay the follower at low demand states and accommodate at high demand states. Finally, we show numerically that a small degree of internalization can be procompetitive by prompting the leader to switch to accommodation later.

In response to the recent outbreak of the SARS-CoV-2 virus governments have aimed to reduce the virus's spread through, inter alia, non-pharmaceutical intervention. We address the question when such measures should be implemented and, once implemented, when to remove them. These issues are viewed through a real-options lens and we develop an SIRD-like continuous-time Markov chain model to analyze a sequence of options: the option to intervene and introduce measures and, after intervention has started, the option to remove these. Measures can be imposed multiple times. We implement our model using estimates from empirical studies and our main conclusions are that: (1) measures should be put in place almost immediately after the first infections occur; (2) if the epidemic is discovered when there are many infected individuals already, then it is optimal never to introduce measures; (3) once the decision to introduce measures has been taken, these should stay in place until the number of susceptible or infected members of the population is close to zero; (4) it is never optimal to introduce a tier system to phase-in measures but it is optimal to use a tier system to phase-out measures; (5) a more infectious variant may reduce the duration of measures being in place; (6) the risk of infections being brought in by travelers should be curbed even when no other measures are in place. These results are robust to several variations of our base-case model.

In a competitive industry where production entails pollution, a welfare-maximizing policy maker considers, as control instruments, setting a cap on market output or levying an emission tax. We embed this scenario within a dynamic setup where market demand is stochastic and entry is irreversible. We firstly determine the industry equilibrium under both policies and then the cap level and the tax rate maximizing welfare. Our main findings are: (i) the optimal tax policy dominates the optimal cap policy; (ii) the optimal tax policy implements the first-best outcome.

In competitive industries, foreseeable policy changes lead to inevitable runs which increase the volatility of investment. We show that this phenomenon, well-known in the case of caps and quotas, also applies to taxes and subsidies, and occurs whether policy changes apply only to new entrants or to all firms equally. Looking at the case of raising taxes (or removing a subsidy) we find that runs are smaller when the policy change affects all firms. We also find that the size of the run, i.e., the size of the resulting increase in market quantity is increasing in the magnitude of the tax raise. Finally, we show that during the run firms invest faster and more massively than on the socially optimal path, and therefore welfare decreases. We show that these results have implications for a broad range of policies, such as the removal of renewable energy subsidies in some European countries.

We build a real options model to investigate the optimal amount of payments to landowners for conservation and the optimal timing of their introduction. Such subsidy contracts, which require landowners to conserve land and preclude development, can be used to increase ecosystem services (ESS) provided by the land and/or preserve existing ESS, which would be lost if development occurs. They enhance ESS provision both directly, once the contract has been accepted by the landowner, and also indirectly, by delaying development. Governments and other public bodies trade off the value of the flow of ESS benefits generated by the land with the costs of providing the subsidy. Increasing the (permanent) level of subsidy increases the government's cost and hence reduces value once the landowner accepts the conservation contract, but increases the present value of the ESS benefits by increasing the expected time until development occurs. The level of subsidy that maximises expected ESS value net of subsidy costs thus varies with the relative proximities of the development and conservation contract acceptance thresholds. Assuming that the announcement of a subsidy level is irreversible, we determine the optimal subsidy level and threshold at which the announcement is made. We plan to investigate the impacts on landowner thresholds and optimal subsidies of different expected conservation contract durations and political risk, whereby such subsidised conservation contracts are available only temporarily.

Previously, we introduced a methodology based on exercise boundary fitting in an effort to develop a practical Monte Carlo simulation-based real options approach. We showed that our methodology converges in the case of simple Bermudan and American put options. More recently, we expanded on the model to solve a staged manufacturing problem. As we presented, utilizing boundary fitting allowed us to solve a computationally difficult problem. In another study we explored the use of the boundary fitting methodology for a number of cases, one being a build and abandon mining example. We showed that while the methodology provided good convergence on option value, under certain scenarios, where the optimal exercise boundaries occurred in regions where there were few Monte Carlo paths, the optimization algorithm struggled to converge. The purpose of this paper is to explore convergence issues related to the boundary fitting methodology. Specifically, we develop experiments where we compare our boundary fitting methodology with pseudo-analytical or numerical results for the following cases: Bermudan put option; option to purchase a Bermudan put option; American put option; and build / abandon real option.

We analyze the investment decisions under uncertainty in oligopoly markets by considering a market of many firms with asymmetric cost structure in a discrete time setting where the demand evolves stochastically and follows a linear structure. Considering competitive strategies, increasing the number of firms imposes inevitable complexities to the model structure. We propose a new approach, based on reinforcement learning, to numerically solve the investment timing problem when the number of firms increases. Our approach can be more generally applied to investigate markets of many firms with several investment opportunities.

We propose a model of credit rating migrations that allows for the possibility of rating stickiness. The model aims to capture the mechanism of the rating process, based on the notion of hysteresis in real option models, that underlies the behavior of rating agencies and is used to explain the observed gradual deterioration in ratings. The paper contributes to the ongoing debate whether the downward trend in credit ratings results from the deteriorating credit quality or tightening rating standards. It is shown that corporate credit quality actually slightly improves over time and that there is asymmetry in rating migrations as upgrades become increasingly more difficult, while downgrade standards remaining unchanged.