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参考经济周期转折点定时的新方法AI 解读

Abstract–This article proposes a new approach to the analysis of the reference cycle turning points, defined on the basis of the specific turning points of a broad set of coincident economic indicators. Each individual pair of specific peaks and troughs from these indicators is viewed as a realization of a mixture of an unspecified number of separate bivariate Gaussian distributions whose different means are the reference turning points. These dates break the sample into…

马尔可夫转换自回归模型中滤波与平滑概率的推断AI 解读

We derive a statistical theory that provides useful asymptotic approximations to the distributions of the single inferences of filtered and smoothed probabilities, derived from time series characterized by Markov-switching dynamics. We show that the uncertainty in these probabilities diminishes when the states are separated, the variance of the shocks is low, and the time series or the regimes are persistent. As empirical illustrations of our approach, we analyze the U.S.…

从多项经济指标中提取非线性信号AI 解读

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one-step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two-step approach). Second, we…

Euro-sting：欧元区增长的短期指标AI 解读

Abstract We set out a model to compute short‐term forecasts of the euro area GDP growth in real time. To allow for forecast evaluation, we construct a real‐time dataset that changes for each vintage date and includes the exact information that was available at the time of each forecast. With this dataset we show that our simple factor model algorithm, which uses an easy‐to‐replicate methodology, is able to forecast the euro area GDP growth as well as professional forecasters…

领先指标究竟领先什么AI 解读

Abstract We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non‐parametric models and conclude that a combination of the switching regimes and non‐parametric forecasts is the best strategy at…