Topics in Economic Dynamics and Time Series

研究将在三个不同的主题上完成：第一，该项目开发了一种新的方法来表征弱相依时间序列中的非线性。用非线性主成分分解来表示连续时间马尔可夫过程的演化过程，并总结出相关结构。这些分解有助于我们更好地理解不同地点的相对价格的演变，以及交易或运输成本引起的非线性。这项工作借鉴了三个文献：泛函主成分分析；马尔可夫过程的二次型模型；以及实际汇率的非线性随机模型。其次，研究人员继续研究私人代理人和政策制定者面临模型错误指定的经济。该项目探索并实现了非线性、随机均衡模型的求解方法。它研究了货币模型，在这些模型中，宏观经济政策制定者的错误描述担忧与私人代理人的担忧不同。它建立在时间序列计量经济学文献中关于错误指定和过滤的见解，以调查私人代理人决策中稳健性的替代公式。最后，该项目研究了稳健性、自适应学习和基于信息的惯性模型之间的联系。第三，该项目检验了不确定情况下动态模型对人力资本和投资组合的可观测含义。对资产收益率的时间序列和横截面的含义进行了推导和检验。本文还考虑了非均质性在劳动收入随机结构中的作用。最后，该项目调查了金融市场结构对人力资本影子估值的作用。

Research will be completed on three different topics:First, the project develops a new approach to characterizing nonlinearities in weakly dependent time series. Nonlinear principal component decompositions are used to represent the evolution of continuous-time Markov processes and to summarize the correlation structure. These decompositions help us understand better the evolution of relative prices across locations and the nonlinearities induced by transaction or transport costs. This work draws on three literatures: functional principal component analysis; quadratic-form modeling of Markov processes; and nonlinear, stochastic modeling of real exchange rates. Nonlinear models that are strongly dependent or nonstationary are also considered.Second, the investigator continues his study of economies in which private agents and policy-makers confront model misspecification. The project explores and implements solution methods for nonlinear, stochastic equilibrium models. It studies monetary models in which the misspecification concerns of macroeconomic policy makers differ from those of private agents. It builds from insights in the time-series econometrics literature on misspecification and filtering to investigate alternative formulations of robustness in the decision-making of private agents. Finally, the project studies connections between robustness, adaptive learning and information- based models of inertia.Third, the project examines the observable implications of dynamic models under uncertainty with human capital and portfolio investment. Implications for time series and cross sections of asset returns are deduced and tested. The role of heterogeneity in the stochastic structure of labor income also is considered. Finally, the project investigates the role of financial market structures on the shadow valuation of human capital.