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Research has suggested that firms may benefit from price uncertainty - about input commodities - because it creates an "option value". We use a stylized mathematical model to explore and generalize this claim and to specify its implications for firms' investment decisions under various setups. In particular, we study firms' motivation for investing in such risk management measures as financial hedging (FH) and technology improvement (TI): technology changes that result in less consumption of an input commodity, fewer waste products and emissions, and lower production costs. We derive a simple expression that explicitly quantities firm's attitude toward input-price risk by considering the firm's (positive or negative) risk premium (i.e., what it would pay to "lock in" the unit input price at its mean) and linking that premium to various firm and industry-level characteristics. Also, we examine the comparative risk management advantages of TI and FH and characterize conditions under which these strategies are complements or substitutes. We find that although input-price uncertainty may be beneficial even for risk-averse firms, they can benefit from investing in risk reduction measures (e.g., TI, FH) because they could increase the option value of that uncertainty. A firm's ability to adjust its price in response to both market competition and input-price variation mediates the benefit of risk-reducing measures and also affects the two strategies' complementarity.

This paper models a multi-player environment comprising a grid operator responsible for meeting electricity demands, a photovoltaic (PV) manufacturer, customers who might install PV (solar) systems, and a regulator charged with setting an optimal feed-in tariff (FIT). The grid operator must meet exogenous electricity demand and also buy back all electricity (produced by PV systems) at the FIT set by a regulator, which seeks to minimize grid operator costs. Customers decide whether or not to invest in a PV system. Adoption rates affect the manufacturer and operator by (respectively) establishing the demand for PV and determining how much electricity is fed into the grid. The PV manufacturer's decision variable is the sales price per PV unit. The decisions of all players in the model are intertwined in a way that clearly affects their respective welfare. We demonstrate in particular how technology and market characteristics -- including PV manufacturing cost and market competition -- change the optimal decisions of players and thereby influence the effectiveness of FITs, the number of PV adopters, and the cost to provide the social benefit of on-demand electricity. Our findings confirm the importance of considering technology manufacturers when devising schemes to incentivize adoption of PV systems.

This paper seeks to identify the optimal policies for promoting product recovery and remanufacturing. Using a stylized equilibrium model, we analyze the problem as a Stackelberg game between a regulator and a monopolistic firm. We compare three types of policies that legislated regulation could effect: (i) A recovery target policy that requires firms to recover no less than a specified fraction of their production for proper disposal or possible remanufacturing; (ii) a taxation policy that both taxes manufacturing and subsidizes remanufacturing; and (iii) a newly introduced mixed approach that incorporates a recovery target as well as taxes and subsidies. We study a firm's behavior under the three policy types, including pricing decisions for new and remanufactured products as well as the strategic decision of whether to create a secondary channel for remanufactured products. We find that legislative intervention makes it more likely that firms will maintain a single-market strategy. We further demonstrate the mixed approach's superiority as measured by a comprehensive set of economic and environmental criteria, and show that this finding is robust under two different objective functions for the policy maker, one that does and one that does not entail a budget neutrality constraint.

This paper aims to contribute to the longstanding technology-push vs. demand-pull debate and to the literature on renewable energy policy assessment. We argue that in addition to the traditional push–pull dichotomy, the drivers of technological change must be differentiated by whether they are exogenous or endogenous to the economic system and must be assessed with respect to their contribution to both the creation and the diffusion of innovation. We apply this perspective to study innovation in the renewable energy (RE) industry in 15 European Union countries from 1990 to 2012. Using different panel data estimators, we find that public R&D investments, policies supporting RE and per capita income all have a positive effect on either innovation creation or diffusion, whereas the variability of policy support has a negative impact on diffusion. However, impacts are heterogeneous and differ depending on the innovation dimension considered. Most importantly, we find that economic growth is a stronger driver of RE diffusion than technology-push or exogenous demand-pull mechanisms, whereas it is relatively ineffective at stimulating innovation creation. The effect of economic growth on RE diffusion exhibits a nonlinear, U-shaped pattern that resonates with the Environmental Kuznets Curve hypothesis. RE penetration remains negligible at low levels of growth whereas it increases sharply only after income per capita has reached a given threshold. This effect has both a direct cause (with increased affluence demand for environmental quality rises) and an indirect cause (with increased affluence expensive RE policies become more affordable and get implemented more extensively). Our findings have implications for policy making. They suggest that for RE diffusion to increase, innovation policies should be carefully balanced. Government action should be directed not only at shielding renewables from competition with fossil fuel technologies, but also at stimulating aggregated demand and economic growth.

The paper aims to contribute to the longstanding technology-push vs. demand-pull debate and to the literature on renewable energy diffusion and renewable energy policy assessment. The authors argue that in addition to the traditional push-pull dichotomy, the drivers of technological change must be differentiated by whether they are exogenous or endogenous to the economic system. They maintain that a specific type of endogenous demand-pull mechanism (i.e. economic growth) is a major catalyst of environmental innovation. We apply this perspective to study the diffusion of renewable energy (RE) technologies in 15 European Union countries from 1990 to 2012. Applying different panel data estimators, the authors find that public R&D investments, policies supporting RE and per capita income all have a positive impact on RE diffusion, whereas the variability of policy support has a negative impact. However, they also find that economic growth is a stronger driver than either public R&D investments or policies supporting RE, and that models that do not take it explicitly into account tend to overestimate the importance of exogenous drivers. Most importantly, they note that the effect of economic growth on RE diffusion exhibits a nonlinear, U-shaped pattern that resonates with the well-known Environmental Kuznets Curve hypothesis. RE penetration remains negligible at low levels of growth whereas it increases sharply only after income per capita has reached a given threshold and the demand for environmental quality rises. Their findings have implications for policy making. They suggest that for RE diffusion to increase, government action should be directed not only at shielding renewables from competition with fossil fuel technologies but also at stimulating aggregated demand and economic growth.

Confronted by increasingly tight budgets and a broad range of alternative options, policy makers need empirical methods to evaluate the effectiveness of policies aimed at supporting the diffusion of renewable energy sources (RES). Rigorous empirical studies of renewable energy policy effectiveness have typically relied on panel data models to identify the most effective mechanisms. A common characteristic of some of these studies, which has important econometric implications, is that they assume that the contribution of RES to total electricity generation will be stationary around a mean. This paper reviews such assumptions and rigorously tests the time series properties of the contribution of RES in the energy mix for the presence of a unit root. To that end, we use both individual and panel unit root tests to determine whether the series exhibit non-stationary behavior at the country level as well as for the panel as a whole. The analysis, applied to a panel of 19 OECD countries over the period 1990-2012, provides strong evidence that the time series of the renewable share of electricity output are not stationary in 17 of the 19 countries examined. This finding has important implications for energy policy assessment and energy policy making, which are discussed in the paper.

INSEAD; In this paper we analyze incentives for investment in renewable electricity generating capacity. In particular, we model the tradeoff between investing in a renewable technology (such as wind) and a non-renewable technology (such as natural gas). The renewable technology has higher investment cost and is intermittent-that is, the supply of electricity from this technology is uncertain. The non-renewable technology is reliable and has a lower investment cost, but generation of electricity from this technology entails fuel expenditures as well as emission (carbon) costs. Motivated by existing electricity markets, we model several interrelated contexts, including: (a) vertically integrated electricity supplier, (b) market competition and (c) partial market competition with long-term fixed-price contracts for renewable electricity. Within these contexts we examine the impact of carbon taxes on the total cost and the share of wind capacity in the total capacity portfolio. We nd that intermittency is the critical aspect of renewable technologies which drives the effectiveness of carbon pricing mechanisms. Our results suggest that, due to intermittency of supply and the need for backup generating capacity, increasing the price of carbon emissions may have an unexpected adverse effect on investment in renewables. In addition, we show that market liberalization can have a negative effect on investment in renewable capacity, total cost and total emissions of the system. Fixed price contracts with renewable generators can mitigate these detrimental effects, but they may also lead to excess renewable capacity and insufficient non-renewable capacity in view of their complementary role as backup generators. We conclude that actions towards reducing the intermittency of the renewable energy sources (e.g., through capacity pooling or unit-specific buffering) may be more effective in promoting investment in renewable generation capacity than reliance on carbon taxes alone.

INSEAD Working Papers Collection; 2010, Issue 32, p1-41; Consider a firm that has the exibility to actively manage and customize the service offered to its customers in a repeat business context. What is the long-term value of such exibility, and how should firms manage the service relationship over time? We propose a dynamic model of the firm-client relationship that relies on behavioral theories and empirical evidence to model the endogenous evolution of service expectations and customer satisfaction as well as their impact on repurchase decisions. In general, we find that firms can extract higher long-term value by managing service experiences and expectations over time. Varying service in the long run is not optimal, however. We characterize the firm's optimal dynamic service policy and show that it converges over time to a steady-state service level. Loss aversion expands the range of constant optimal service policies, suggesting that behavioral asymmetries limit the value of responsive service. Our results provide insights for service suppliers seeking to leverage customer-level data and service exibility in order to prioritize clients and improve long-term performance.

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