Topics in Dynamic Macroeconomics

动态宏观经济学专题

• 批准号: 9107681
• 负责人: Thomas Sargent
• 金额: $ 14.1万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-08-01 至 1995-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9107681&HistoricalAwards=false
• 关键词: Topics; Dynamic; Macroeconomics

This research should make valuable methodological and substantive contributions to our understanding of dynamics of economic growth, consumption, saving and other important economic variables. The project pursues research on learning in economic systems; recursive dynamic models of economic fluctuations; and monetary history. The two lines of research on learning are artificial intelligent learning via classifier systems and learning via recursive ARMA models. Two classes of recursive dynamic models are considered, one with "signalling " within incomplete markets and another with complete markets. Two areas of monetary history are examined: the macroeconomics of the periods preceding, during, and following the French revolution and government switches from one commodity money standard to another. Models in game theory and macroeconomics often have multiple equilibria, and there is no self-evident way for either agents inside the model or economists to select among them. In monetary economics, there are a variety models that display such multiplicities. The research by this project on learning algorithms is very important because it provides means of reducing the number of possible outcomes in some cases to a single rational equilibrium. The predictions of that model can then be tested empirically. Dynamic stochastic models are used in macroeconomics and finance to build theories about how variables like consumption and interest rates covary over time. But these models are often computationally demanding to analyze or completely intractable. The research on recursive dynamic models explores ways that these models can be quickly and inexpensively formulated and solved. Economic history provides a laboratory within which recent developments in macroeconomic theory can be tested. The investigator has turned up a number of documents that show the seriousness with which leaders of France around the time of the French Revolution were experimenting with a range of arrangements extending from "real bills" schemes to "optimal tax smoothing" policies. This project will use dynamic macroeconomic and monetary theories to study these and other historical episodes.

这项研究应该对我们理解经济增长、消费、储蓄和其他重要经济变量的动态作出有价值的方法和实质性贡献。该项目致力于研究经济系统中的学习；经济波动的递归动态模型；还有货币历史。学习研究的两条路线是通过分类器系统进行人工智能学习和通过递归ARMA模型进行学习。考虑了两类递归动态模型，一类是不完全市场中的“信号”模型，另一类是完全市场中的“信号”模型。本书考察了货币历史的两个领域：法国大革命之前、期间和之后的宏观经济，以及政府从一种商品货币标准转向另一种商品货币标准。博弈论和宏观经济学中的模型通常具有多重均衡，模型中的主体或经济学家都没有不言自明的方法来从中进行选择。在货币经济学中，有各种各样的模型显示出这种多样性。该项目对学习算法的研究非常重要，因为它提供了在某些情况下将可能结果的数量减少到单个理性均衡的方法。然后，该模型的预测可以进行实证检验。动态随机模型在宏观经济学和金融学中用于建立关于消费和利率等变量如何随时间协变的理论。但是这些模型通常需要计算来分析，或者完全难以处理。递归动态模型的研究探索了如何快速、低成本地建立和求解这些模型。经济史为检验宏观经济理论的最新发展提供了一个实验室。调查人员找到了大量文件，显示出法国领导人在法国大革命前后对一系列安排的认真态度，从“真实账单”计划到“最佳税收平滑”政策。这个项目将使用动态宏观经济和货币理论来研究这些和其他历史事件。