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关于风险的若干评论AI 解读

Abstract Investor risk is a complicated concept in practice and is not well captured by measures of volatility as is well understood by uncertainty theory. Rather than asking statisticians to attempt to measure risk, it may be better to listen to decision theorists, but their suggestions are not very practical. Diversification is clearly helpful in reducing risk but the risk level of one portfolio cannot be measured without knowing the risks of other major portfolios. A…

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基于因果式残差正交化的向量自回归脉冲响应函数AI 解读

A data-determined method for testing structural models of the errors in vector autoregressions is discussed. The method can easily be combined with prior economic knowledge and a subjective analysis of data characteristics to yield valuable information concerning model selection and specification. In one dimension, it turns out that standard t statistics can be used to test the various overidentifying restrictions that are implied by a model. In another dimension, the method…

能否改善人们感知的经济预测质量？AI 解读

A number of topics are discussed concerning how economic forecasts can be improved in quality or at least in presentation. These include the following: using 50% uncertainty intervals rather than 95%; noting that even though forecasters use many different techniques, they are all occasionally incorrect in the same direction; that there is a tendency to underestimate changes; that some expectations and recently available data are used insufficiently; lagged forecasts errors…

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季节调整是线性还是非线性的数据滤波过程？AI 解读

The authors investigate whether seasonal adjustment procedures are linear data transformations. This question was addressed by A. H. Young (1968) and is important for the estimation of regression models with seasonally adjustment data. The authors focus on the X-11 program and rely on simulation evidence, involving linear unobserved component autorgressive integrated moving average models. They define and test a set of properties for the adequacy of a linear approximation to…

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时间序列分析中的“无限方差”与研究策略AI 解读

The possibility that some time series that arise in economics have error or innovation terms that come from infinite variance distributions throws doubt on most of the classical methods of analysis. The evidence in favor of infinite-variance is discussed and a variety of alternative explanations of the long-tailed property of observed distributions examined. Some of these alternative explanations are based on mixtures of distributions and suggest data-transformations that…

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