سرمایه گذاری غیر قابل برگشت، عدم اطمینان و ابهام: مورد، بخش انرژی زیستی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|9944||2012||9 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Economics, Volume 34, Issue 1, January 2012, Pages 45–53
We analyze production and investment decisions of an agent in industrial activities that are characterized by two forms of uncertainty: demand uncertainty (in terms of number of buyers) and competitive effect uncertainty (in terms of other energy resource). We apply our model on the bioenergy industries. We compare the case of an ambiguity neutral agent with that of an ambiguity averse agent. We show that the investment decision of an agent depends on the effects of both the capital investment and the level of production on the cost and the uncertainty the agent is confronted with. Moreover, we find that ambiguity aversion tends to decrease the agent's optimal levels of production and investment. Our numerical analysis of the French case illustrates the different effects associated with demand uncertainty and competitive effect uncertainty.
Investments into renewable technologies will have to develop in order to reach the renewable energy target of 20% fixed by the European Union (EU) for 2020.2 To reach the future targets set out by the EU, significant amounts of biomass and investments into biomass based technologies will be necessary.3 Biomass is key to the development of renewable energies, but it must undergo a pretreatment and densification process before it can be transported and stored. Indeed, biomass is a resource that is heterogeneous in quality and is not homogeneously distributed across space. Therefore, the large range of biomass types is not directly usable in some feeding systems and conversion processes. Investment in new pre-treatment facilities is a necessary step in the total biomass supply chain in order to save transport, material, handling costs for users and to reduce investments in transformation facilities. These pre-treatment processes are still in progress and the biomass market is emerging. Although a potential investor has information about the demand and the competitive effect on the supply market, this information still remains imperfect. Indeed, due to the novelty of this market, the agent cannot get a perfect knowledge on the number of buyers before starting the production. He will either have to supply a few potential buyers such as heat and electricity producers, needing to replace coal, or a larger number of potential buyers including producers of second generation biofuel and heat and electricity producers. This uncertainty then affects the agent's perception of the average price. Here and hereafter, we define this uncertainty as the demand uncertainty. Moreover, the competition effect from other energy resource on the price of pretreated biomass is also not well-known by the agent. In fact, the biomass may be sold either to heating or power units as a substitute for coal (the selling price could then be indexed with coal prices) or to Biomass to Liquid (BtL) units as a substitute for fossil fuel and prices could then be indexed with oil prices, which fluctuate even more sharply than coal prices. So, uncertainty about competition affects the agent's perception of the average price and mostly the variance price. We define this uncertainty as the competitive effect uncertainty. Considering these two kinds of uncertainty and their impact on the selling price, a biomass agent has to decide how much capital investment and produced units he will make in biomass activities. Capital investment, also called in the literature the cost of entry, in bioenergy production represents a quasi-sunk cost due to the fact that biomass torrefaction is a specific, and relatively expensive, process. This naturally raises the issue of the effect of both types of uncertainty and of the irreversibility on the investment level and production. Furthermore, in the energy market, the instability of the economy may lead the agent to have uncertainties about his evaluation of the variance of the output price. We use the term ‘ambiguity’ to indicate situations in which the odds of an uncertain event are not precisely known. In other words, a situation in which there is an ‘uncertainty about uncertainty’.4 An agent who has doubts about the odds is considered as an ambiguity-averse agent. So a question arises: how an ambiguity-averse agent behaves when he makes his decisions concerning investment and production? To understand the impact of uncertainty on investment and production in biomass activities, we propose a two-period model in which there is incomplete information about the number of buyers and the competitive effect. Under these uncertainties, an agent has to choose his capital investment for the production of pre-treated biomass units at the following period. We study the cases of an ambiguity-neutral agent and of an ambiguity-averse agent. Following Klibanoff et al. (2005), we extend our work by presenting ambiguity as a second order prior probability distribution over the set of plausible distributions of the competitive effect. This approach allows us to analyze the impact of ambiguity on the investment and production choices. The standard theory of irreversible investments or quasi sunk cost (Henry, 1974 and Sutton, 1991) and options values suggests a negative relation between investment and uncertainty (Dixit and Pindyck, 1994). Empirical studies also confirm this negative relation (Bond et al., 2005, Carruth et al., 2000 and Fan and Zhu, 2010). However, (Kulatilaka and Perotti, 1998 and Sarkar, 2000) point out that an increase in uncertainty could increase the probability of investing, and thereby has a positive impact on investment. Moreover, Mohn and Misund (2009) argue that any positive impact on investment arising from the fact that greater uncertainty, under certain circumstances, increases the marginal profitability of capital. In all these papers the effect of price uncertainty has been analyzed as the effect of demand uncertainty on capacity choice (Dangl, 1999, Elder and Serletis, 2009, Elder and Serletis, 2010, Isik et al., 2003 and Trigeorgis, 1996). Considering real options approach, Murto et al. (2004) are interested with in the timing of investment projects under demand uncertainty and oligopolistic competition. The important characteristic is that the output price is influenced by both exogenous uncertainty and new capacity investments. This paper is closed to our approach with demand uncertainty and competitive effect even if there is no real uncertainty on the competition. Murto (2006) introduces two types of uncertainty by combining effect of technological uncertainty and uncertainty in output price with real options approach. However, no work has been done on the two types of uncertainty (demand uncertainty and competitive effect uncertainty) that affect prices in different ways: the perception of the average and the variance of the price. Concerning ambiguity, we refer to the basic literature on ambiguity with (Ellsberg, 1961) and Fellner, 1961 and Fellner, 1965, the empirical investigations by (Slovic and Tversky, 1974) and the recent literature with (Klibanoff et al., 2005) and Gollier (2006) to indicate situations for which the odds of an uncertain event are not precisely known. Determining how an ambiguity-averse agent decides to invest and produce in emerging technologies is an important line of research in entrepreneurial decision-making in BtL. Using an analytical approach and numerical analysis, we first note that whatever the certainty or uncertainty context, the agent never invests or produces when he thinks that an increase in capital increases the cost of one more unit. Moreover, we show that the agent's capital investment decision depends on the effects of the amount of capital invested, of the level of production on the cost and on the uncertainty to which the agent is confronted. Then, we observe asymmetric effects of demand uncertainty and competitive effect uncertainty on the optimal amount of investment and optimal production. Finally, we find that ambiguity aversion tends to decrease the agent's level of capital investment and production. The French biomass pre-treatment industry (torrefaction) is taken as an example, and the empirical results show that the model developed here can provide useful advice for pre-treatment biomass investment programs. The remainder of the paper is organized as follows. Section 2 consists of a description of the model. Section 3 analyzes and compares the optimal investment and production decisions of both an ambiguity neutral agent and an ambiguity averse agent. Section 4 presents a numerical analysis. Finally, Section 5 concludes.
نتیجه گیری انگلیسی
In this paper, we assess the impact of two types of uncertainty and of the ambiguity aversion of the agent on his investment and production strategy. We develop a formal model for decision making in which agents are neutral to risk and averse to ambiguity about the true distribution of the competitive effect. We analyze the optimal capacity and production choices in this model. Using an analytical approach and numerical analysis, we first note that whatever the certainty or uncertainty context, the agent never invests or produces when he thinks that an increase in capital increases the cost of one more unit. Moreover, the agent's capital investment decision depends on the effects of the amount of capital invested, of the level of production on the cost and on the uncertainty to which the agent is confronted. Then, we observe asymmetric effects of demand uncertainty (in terms of number of buyers) and competitive effect uncertainty on the optimal amount of investment and optimal production. Finally, in the presence of ambiguity about the competition effect, agents will invest less in their units and their level of production is lower. The main feature of this model is that it helps to understand the behaviour of an agent who faces uncertainty about the market size and market competition if he is averse to ambiguity. This paper emphasizes the need to reduce the effects of ambiguity in the European policy framework that encourages the development of renewable energy production. The introduction of long-term contracts could contribute to reducing them. Actually, these contracts could be defined as agreements between a pretreated biomass producer (seller) and a renewable energy generator owner (buyer) for the purchase of torrefied biomass. By hedging against price volatility, these contracts would reduce the ambiguity impact of the competition effect. They could take the forms of competitive procurement process or bilateral contract negotiation (see Michaud (2010)). An attractive feature of the model is to determine how the risk and ambiguity aversions of the buyer will affect the investment strategy of torrefied biomass producers. Finally, it will be important to check empirically, with potential agents (private forest owners, cooperatives…) the theoretical results obtained in our model and to evaluate the degree of their ambiguity aversion.