Topics in Macroeconomics and Forecasting

总的来说，这个项目涉及时间序列的三个方面 计量经济学和经验宏观经济学。 第一区域 包括商业周期的方法论和实证问题 预测。 第二个问题是关于 经济时间序列的长期特性 第三部分 该项目研究动态均衡的计量经济学问题 宏观经济模型。 计算技术和数据可用性的最新进展 使我们有可能考虑宏观经济预测， 数以百计的经济时间序列。 这个大 一些潜在的重要时间序列引起了重要的 方法问题。 该项目涉及经验和 与参数不稳定性、变化 循环模式和高维系统中的预测。 经济理论建议和个体关系研究 (such（如货币收入关系）提供证据 商业周期的简化形式预测的不稳定性。 获得对这种不稳定性的更好的经验理解是 从宏观经济理论和 经济预测。 了解是否、如何以及何时 关系的变化提供了一个经验基础， 宏观经济动态的理论研究，并建议 开发适应性预测模型的方法。 这个项目是我们全球变化经济学研究的一部分 施政纲要的演讲 它关系到发展中国家的高度优先目标， 用于评估经济后果的预测工具 全球气候变化 政府现在使用的工具 和工业界进行预测， 方法论的批评。 年发展起来的时间序列方法 这个项目可以提供更好的影响预测， 预期经济结构性变化的类型 从全球变暖和政府的政策，以限制或 大幅减少温室气体排放。

Overall, this project addresses three areas of time series econometrics and empirical macroeconomics. The first area consists of methodological and empirical issues in business cycle forecasting. The second concerns econometric inference about the long-run properties of economic time series. The third part of the project examines econometric issues about dynamic equilibrium macroeconomic models. Recent advances in computational technology and data availability have made it possible to contemplate macroeconomic forecasting with literally hundreds of economic time series. This large number of potentially important time series raises important methodological issues. This project addresses empirical and methodological issues related to parameter instability, changing cyclical patterns, and forecasting in high-dimensional systems. Economic theory suggests and studies of individual relations (such as the money-income relation) provide evidence of instability in reduced form forecasts of the business cycle. Obtaining a better empirical understanding of this instability is of interest from the perspectives of both macroeconomic theory and economic forecasting. Understanding whether, how and when relations have changed provides an empirical foundation for theoretical investigations of macroeconomic dynamics and suggest ways to develop adaptive forecasting models. This project is part of our economics of global change research agenda. It relates to the very high priority goal of developing forecasting tools for assessing the economic consequences of global climate change. The tools that are now used by government and industry to make forecasts are subject to serious methodological criticisms. The time series methods developed in this project could provide much better forecasts of the impacts of the types of structural changes in the economy anticipated from global warming and from government policies to constrain or sharply reduce emissions of greenhouse gases.