Topics in Macroeconomics and Forecasting

总体而言，本项目涉及时间序列计量经济学和实证宏观经济学三个领域。第一个领域包括商业周期预测的方法和经验问题。第二个是关于经济时间序列的长期属性的计量经济学推断。该项目的第三部分考察了有关动态均衡宏观经济模型的计量经济学问题。最近在计算技术和数据可用性方面的进步，使人们有可能用数百个经济时间序列来考虑宏观经济预测。这么多潜在重要的时间序列提出了重要的方法问题。该项目解决了与参数不稳定性、变化周期模式和高维系统预测相关的经验和方法问题。经济理论表明，对个体关系（如货币收入关系）的研究提供了不稳定性的证据，以简化形式预测商业周期。从宏观经济理论和经济预测的角度来看，对这种不稳定性获得更好的经验理解是有意义的。了解关系是否、如何以及何时发生了变化，为宏观经济动力学的理论研究提供了经验基础，并提出了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议程的一部分。它涉及开发预测工具以评估全球气候变化的经济后果这一高度优先目标。政府和工业界现在使用的预测工具在方法上受到严重的批评。本项目开发的时间序列方法可以更好地预测全球变暖和政府限制或大幅减少温室气体排放的政策所预期的经济结构变化类型的影响。

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.