消费、总财富和预期股票回报:分位数协整方法

IF 0.7 4区 经济学 Q3 ECONOMICS Studies in Nonlinear Dynamics and Econometrics Pub Date : 2021-09-13 DOI:10.1515/snde-2020-0059
Ricardo Quineche
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引用次数: 1

摘要

摘要本文通过分位数协整方法实证研究了美国消费、资产财富和劳动收入之间的长期关系。使用这种方法的优点是,它允许根据消费水平在这些变量之间建立非线性关系。我们使用Phillips–Hansen型完全修正的分位数估计量来估计系数,以校正协整关系中内生性的存在。为了检验每个分位数的协整零点,我们应用了分位数CUSUM检验。结果表明:(i)在整个消费分布中,消费对劳动收入的变化比对资产财富的变化更敏感,(ii)消费相对于劳动收入(资产财富)的弹性在消费分布的右(左)尾比在左(右)尾更大,(iii)该系列是围绕中位数协整的,但不在消费分布的尾部,(iv)使用为消费分布的右(左)尾部获得的估计cay,可以提高对实际超额股票收益的长期(短期)预测能力。
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Consumption, aggregate wealth and expected stock returns: a quantile cointegration approach
Abstract This paper empirically examines the long-run relationship between consumption, asset wealth and labor income (i.e., cay) in the United States through the lens of a quantile cointegration approach. The advantage of using this approach is that it allows for a nonlinear relationship between these variables depending on the level of consumption. We estimate the coefficients using a Phillips–Hansen type fully modified quantile estimator to correct for the presence of endogeneity in the cointegrating relationship. To test for the null of cointegration at each quantile, we apply a quantile CUSUM test. Results show that: (i) consumption is more sensitive to changes in labor income than to changes in asset wealth for the entire distribution of consumption, (ii) the elasticity of consumption with respect to labor income (asset wealth) is larger at the right (left) tail of the consumption distribution than at the left (right) tail, (iii) the series are cointegrated around the median, but not in the tails of the distribution of consumption, (iv) using the estimated cay obtained for the right (left) tail of the distribution of consumption improves the long-run (short-run) forecast ability on real excess stock returns over a risk-free rate.
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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