Risk, Robustness and Volatility

9709876汉森 该项目有助于我们理解风险、稳健性和波动性。 有三个不同的部分：1.分散经济中的风险敏感性和鲁棒性。 动态经济模型的建立，消费者/投资者可以作出决定的基础上的鲁棒性考虑的一部分。 调查借鉴递归效用理论，鲁棒控制理论和权力下放下的不确定性的想法。 特别感兴趣的是，对稳健性的偏好如何反映在均衡价格中，包括风险的市场价格。 2.校准的经验基础。 研究了将微观数据集的估计值整合到动态随机一般均衡模型中的替代方法。 该项目评估并扩展了当前的微观计量经济学方法，以考虑代理异质性和信贷约束。 它获得了围绕微观经济决策的不确定性的新估计。 它研究了新的微观计量经济学投入的一般均衡含义。 3.扩散模型的灵活估计。 扩散模型作为非线性时间序列的模型是有吸引力的，因为它们以简单的方式编码信息，如命中时间概率和长期平稳分布。 特别注意的是专门用于表征的方式，其中扩散系数或局部方差取决于马尔可夫状态。 在非线性扩散模型中，仅这种依赖性就足以将过程拉回到其分布的中心。 时间序列版本的筛选方法，以提供感兴趣的波动率表征。 ??

9709876 Hansen This project contributes to our understanding of risk, robustness and volatility. There are three distinct parts: 1. Risk Sensitivity and Robustness in Decentralized Economies. Models of dynamic economies are built in which consumers/investors can make decisions based in part upon robustness consideration. The investigation draws upon ideas from recursive utility theory, robust control theory and decentralization under Knightian uncertainty. Of particular interest is how a preference for robustness becomes reflected in equilibrium prices including the market price of risk. 2. Empirical Foundations of Calibration. Alternative ways of integrating estimates from micro data sets into dynamic stochastic general equilibrium models are studied. The project assesses and extends current microeconometric methods to account for agent heterogeneity and credit constraints. It obtains new estimates of the uncertainty surround microeconomic decision making. It investigates the general equilibrium implications of the new microeconometric inputs. 3. Flexible Estimation of Diffusion Models. Diffusion models as models of nonlinear time series are attractive because of the simple manner in which they encode information such as hitting time probabilities and long run stationary distributions. Particular attention is devoted to characterizing the manner in which the diffusion coefficient or local variance depends on the Markov state. In nonlinear diffusion models, this dependence alone can be sufficient to pull the process back to the center of its distribution. Time series versions of sieve methods are employed to provide the volatility characterization of interest. ??