Investment Under Uncertainty: Theory and Applications

最近关于不确定性下投资决策的研究强调了期权价值的重要性，或者等待解决一些不确定性并收集更多信息的重要性。这项工作主要局限于“经典”经济环境，即拥有完美的风险市场、没有规模经济或外部性的环境。本项目使用随机最优控制技术的相应扩展，将分析扩展到“非经典”设置。然后，更一般的理论将应用于一些重要的政策问题。示例包括以下内容。(1)建立具有规模经济和外部性的不确定性条件下的投资标准，构建产业演化模型，并与新的增长理论相联系。(2)由于劳动收入风险很难或不可能分散，贸易调整，更普遍的是由于工厂关闭导致的失业，改变了风险承担。这个问题和适当的政策将会被模仿。(3)缓慢调整的实际刚性将与名义惯性结合到就业波动的宏观经济模型中。(4)在评估减少环境损害的新技术时，必须权衡等待收集更多信息的价值与等待过程中不可逆转损害的风险。这将被表述为一个带滤波的随机控制问题。

Recent research on investment decisions under uncertainty has highlighted the importance of option values, or of waiting to resolve some uncertainty and gather more information. This work is mostly restricted to "classical" economic environments, with perfect risk markets and without economies of scale or externalities. This project extends the analysis to "non- classical" settings, using corresponding extensions of techniques of stochastic optimal control. The more general theory will then be applied to some important policy issues. Examples include the following. (1) Criteria for investment under uncertainty with scale economies and externalities will be developed, built into a model of industry evolution, and linked to the new theory of growth. (2) Since labor income risk is hard or impossible to diversify, trade adjustment, and more generally job losses due to plant closure, alter risk- bearing. The issue, and appropriate policies, will be modelled. (3) Real rigidities of slow adjustment will be combined with nominal inertia into macroeconomic models of employment fluctuations. (4) When evaluating new technologies to reduce environmental damage, the value of waiting to gather more information must be traded off against the risk of irreversible damage while we wait. This will be formulated as a stochastic control problem with filtering.