Consumer Sentiment: Its Rationality and Usefulness in Forecasting Expenditure - Evidence from the Michigan Micro Data
Consumer Sentiment: Its Rationality and Usefulness in Forecasting Expenditure - Evidence from the Michigan Micro Data
复制标题
消费者情绪：预测支出的合理性和有用性——来自密歇根州微观数据的证据
DOI：
10.3386/w8410
复制
发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Nicholas S. Souleles
中科院分区：
文献类型：
--
作者：
Nicholas S. Souleles;Nicholas S. Souleles
本文提供了对密歇根消费者信心指数基础上的家庭数据的首次全面分析之一。这些数据用于检验消费者预期的合理性，并评估其在预测支出方面的有用性。研究结果也可以解释为不同类型家庭在一段时间内遭受的冲击的特征。预期被发现是有偏差的，至少事后是这样，因为即使在持续近20年的样本期内，预测误差也不能平均出来。人们低估了20世纪80年代初和90年代的反通胀，而且似乎普遍低估了商业周期的幅度。预测也是低效的，因为人们的预测误差与他们的人口特征和/或总体冲击并没有均匀地打击所有人。此外，人们发现情绪在预测未来消费方面很有用，甚至可以控制滞后消费和股票价格等宏观变量。这种过度的敏感性与永久收入假说（PIH）背道而驰。较高的信心与较少的储蓄相关，这与预防动机和预期未来资源的增加相一致。一些对PIH的拒绝被发现是由于预测误差中的系统人口组成部分。但即使控制了这些成分，一些过度的敏感性仍然存在。更广泛地说，这些结果表明前瞻性模型的实证实施需要更好地考虑预测误差的系统异质性。
This paper provides one of the first comprehensive analyses of the household data underlying the Michigan Index of Consumer Sentiment. This data is used to test the rationality of consumer expectations and to assess their usefulness in forecasting expenditure. The results can also be interpreted as characterizing the shocks that have hit different types of households over time. Expectations are found to be biased, at least ex post, in that forecast errors do not average out even over a sample period lasting almost 20 years. People underestimated the disinflation of the early 1980's and in the 1990's, and generally appear to underestimate the amplitude of business cycles. Forecasts are also inefficient, in that people's forecast errors are correlated with their demographic characteristics and/or aggregate shocks did not hit all people uniformly. Further, sentiment is found to be useful in forecasting future consumption, even controlling for lagged consumption and macro variables like stock prices. This excess sensitivity is counter to the permanent income hypothesis [PIH]. Higher confidence is correlated with less saving, consistent with precautionary motives and increases in expected future resources. Some of the rejection of the PIH is found to be due to the systematic demographic components in forecast errors. But even after controlling for these components, some excess sensitivity persists. More broadly, these results suggest that empirical implementations of forward-looking models need to better account for systematic heterogeneity in forecast errors.