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Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth

机译:比较美联储,蓝筹股和美国产出增长的时间序列预测

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We evaluate the predictive content of Federal Reserve and Blue Chip forecasts of output growth by utilizing two comparable forecasts as benchmarks: a univariate autoregres-sive (AR) model, and a vector autoregressive (VAR) model which includes output growth, growth in residential investment, and consumers' assessments of business conditions. We first show the forecasts are all directionally accurate, free of systematic bias, and efficient. Second, the asymmetric information hypothesis cannot be supported. Third, the Federal Reserve and private forecasts are generally less informative than the VAR forecasts and thus lack past information on residential investment growth and consumers' assessments of business conditions.
机译:我们通过使用两个可比较的预测作为基准来评估美联储和蓝筹股对产出增长的预测的预测内容:单变量自回归(AR)模型和向量自回归(VAR)模型,其中包括产出增长,住宅投资增长,以及消费者对业务状况的评估。我们首先显示预测都是方向正确的,没有系统的偏差,并且有效。其次,不对称信息假设无法得到支持。第三,美联储和私人预测通常没有VAR预测提供更多信息,因此缺乏有关住宅投资增长和消费者对商业状况评估的过去信息。

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