The business cycle has long been the focus of empirical economic research. Until recently statistical analysis of macroeconomic fluctuations was dominated by linear time series methods. Over the past 15 years, however, economists have increasingly applied tractable parametric nonlinear time series models to business cycle data; most prominent in this set of models are the classes of Threshold AutoRegressive (TAR) models, Markov-Switching AutoRegressive (MSAR) models, and Smooth Transition AutoRegressive (STAR) models. In doing so, several important questions have been addressed in the literature, including: Do out-of-sample (point, interval, density, and turning point) forecasts obtained with nonlinear time series models dominate those generated with linear models? How should business cycles be dated and measured? What is the response of output and employment to oil-price and monetary shocks? How does monetary policy respond to asymmetries over the business cycle? Are business cycles due more to permanent or to transitory negative shocks? And, is the business cycle asymmetric, and does it matter? "Contributions to Economic Analysis" was established in 1952. The series purpose is to stimulate the international exchange of scientific information. The series includes books from all areas of macroeconomics and microeconomics.
本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度,google,bing,sogou 等
© 2025 onlinetoolsland.com All Rights Reserved. 本本书屋 版权所有