Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model

The key role of technological change in the decline of energy and carbon intensities of aggregate economic activities is widely recognized. This has focused attention on the issue of developing endogenous models for the evolution of technological change. With a few exceptions this is done using a deterministic framework, even though technological change is a dynamic process which is uncertain by nature. Indeed, the two main vectors through which technological change may be conceptualized, learning through R&D investments and learning-by-doing, both evolve and cumulate in a stochastic manner. How misleading are climate strategies designed without accounting for such uncertainty? The main idea underlying the present piece of research is to assess and discuss the effect of endogenizing this uncertainty on optimal R&D investment trajectories and carbon emission abatement strategies. In order to do so, we use an implicit stochastic programming version of the FEEM-RICE model, first described in Bosetti, Carraro and Galeotti, (2005). The comparative advantage of taking a stochastic programming approach is estimated using as benchmarks the expected-value approach and the worst-case scenario approach. It appears that, accounting for uncertainty and irreversibility would affect both the optimal level of investment in R&D –which should be higher– and emission reductions –which should be contained in the early periods. Indeed, waiting and investing in R&D appears to be the most cost-effective hedging strategy.Stochastic Programming, Uncertainty and Learning, Endogenous Technical Change

Investment under ambiguity with the best and worst in mind

Recent literature on optimal investment has stressed the difference between the impact of risk and the impact of ambiguity - also called Knightian uncertainty - on investors' decisions. In this paper, we show that a decision maker's attitude towards ambiguity is similarly crucial for investment decisions. We capture the investor's individual ambiguity attitude by applying alpha-MEU preferences to a standard investment problem. We show that the presence of ambiguity often leads to an increase in the subjective project value, and entrepreneurs are more eager to invest. Thereby, our investment model helps to explain differences in investment behavior in situations which are objectively identical

Real Options under Choquet-Brownian Ambiguitys

Real options models characterized by the presence of “ambiguity” (or “Knightian uncertainty”) have been recently proposed. But based on recursive multiple-priors preferences, they typically describe ambiguity through a range of Geometric Brownian motions and solve it by application of a maxmin expected utility criterion among them (worst case). This reduces acceptable individual preferences to the single case of an extreme form of pessimism. In contrast, by relying on dynamically consistent “Choquet-Brownian” motions to represent the ambiguous cash flows expected from a project, we show that a much broader spectrum of attitudes towards ambiguity may be accounted for, improving the explanatory and application potentials of these appealing expanded real options models. In the case of a perpetual real option to invest, ambiguity aversion may delay the moment of exercise of the option, while the opposite holds true for an ambiguity seeking decision maker. Furthermore, an intricate relationship between risk and ambiguity appears strikingly in our model.

Assessing Investment in Precision Farming for Reducing Pesticide Use in French Viticulture

The paper develops a mathematical programming model for assessing the impact of Environmental Policy instruments on French winegrowing farm’s adoption of pesticides-saving technologies. We model choices with regards to investment in precision farming and plant protection practices, in a multi-periodic framework with sequential decision, integrating uncertainty on fungal disease pressure and imperfect information on equipment performance. We focus on recursive models maximizing a Utility function. These models are applied on a representative sample of 534 winegrowers from the French Farm Accountancy Data Network (FADN). As expected, both ecotaxes and green subsidies make precision farming equipment more profitable, but the investment rate remains however low and concentrated on basic systems. One explanation is grower’s financial constraint in a context of market crisis and farm indebtedness. Shortcomings and further development of the models are discussed.Discrete Stochastic Programming, Precision Farming, Viticulture, Pesticides, Environmental Policy, Crop Production/Industries, Farm Management,

Real Options under Choquet-Brownian Ambiguity

Real options models characterized by the presence of ambiguity have been recently proposed. But based on recursive multiple-priors approaches to solve ambiguity, these seminal models reduce individual preferences to extreme pessimism by considering only the worst case scenario. In contrast, by relying on dynamically consistent Choquet-Brownian motions to model the dynamics of ambiguous expected cash flows, we show that a much broader spectrum of attitudes towards ambiguity may be accounted for. In the case of a perpetual real option to invest, ambiguity aversion delays the moment of exercise of the option, while the opposite holds true for an ambiguity lover.Real Options; Ambiguity; Irreversible investment; Optimal stopping; Knightian uncertainty; Choquet-Brownian motions

Bargaining and the timing of investment

The joint determination of the timing of investment and wage bargaining is modelled. Two cases are considered: (a) There is an alternating-offer bargaining game over binding wage contracts and production is possible only when agreement is reached. (b) There are no binding contracts so revenue is divided in period-by-period bargaining post-investment. Investment can occur earlier in case (b) than in case (a) and the equilibrium in case (b) can Pareto-dominate the equilibrium with binding contracts. These conclusions depend on players' discount factors

Risk and return of open-end real estate funds : the German case

Open-end real estate funds (so called “Offene Immobilienfonds”) play a major role in the German market for securitised real estate investments. Such funds are pools of money from many investors, which are invested in real estate by special investment management companies. This study seeks to identify the risk and return profile of this investment vehicle (before and after income taxes), to compare them with those of other major asset classes, and to provide implications for their appropriate role in a mixed-asset portfolio. Addition-ally, an overview of the institutional architecture and role of German open-end real estate funds is given. Empirical evidence suggests that the financial characteristics of open-end real estate funds are in many respects similar to those reported for direct real estate invest-ments. Accordingly, German open-end real estate funds qualify for medium and long-term investment horizons, rather than for shorter holding periods