Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility.
Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility.
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DOI：
10.1111/rssa.12092
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发表时间：
2015-10
期刊：
影响因子：
--
通讯作者：
Marcellino M
中科院分区：
文献类型：
--
作者：
Carriero A;Clark TE;Marcellino M
这篇论文开发了一种方法，利用就业和工业生产等经济指标以及股票价格和利率等财务指标的季度内可用范围(可能是很大范围)的经济指标，来编制当前季度国内生产总值增长预测。鉴于现有证据表明国内生产总值的冲击方差随时间变化，我们考虑模型的不同版本，既有恒定方差，也有随机波动率。我们使用贝叶斯方法来估计模型，以便于提供模型参数集(可能是大的)的收缩，并方便地生成预测密度。我们提供了关于美国从1985年到2011年的实时国内生产总值增长的即时预测的准确性的结果。在点预测方面，我们的建议显著改进了自回归模型，并与调查预测的表现相当。此外，它还提供了可靠的密度预测，对此随机波动率规范非常有用。
The paper develops a method for producing current quarter forecasts of gross domestic product growth with a (possibly large) range of available within‐the‐quarter monthly observations of economic indicators, such as employment and industrial production, and financial indicators, such as stock prices and interest rates. In light of existing evidence of time variation in the variances of shocks to gross domestic product, we consider versions of the model with both constant variances and stochastic volatility. We use Bayesian methods to estimate the model, to facilitate providing shrinkage on the (possibly large) set of model parameters and conveniently generate predictive densities. We provide results on the accuracy of nowcasts of realtime gross domestic product growth in the USA from 1985 through 2011. In terms of point forecasts, our proposal improves significantly on auto‐regressive models and performs comparably with survey forecasts. In addition, it provides reliable density forecasts, for which the stochastic volatility specification is quite useful.
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影响因子：
2.1
作者：
Carriero, Andrea;Kapetanios, George;Marcellino, Massimiliano
通讯作者：
Marcellino, Massimiliano
影响因子：
2
作者：
Cogley, T;Sargent, TJ
通讯作者：
Sargent, TJ
影响因子：
3
作者：
Faust, Jon;Wright, Jonathan H.
通讯作者：
Wright, Jonathan H.
影响因子：
2.1
作者：
Banbura, Marta;Giannone, Domenico;Reichlin, Lucrezia
通讯作者：
Reichlin, Lucrezia
影响因子：
1.5
作者：
Christoffersen, PF
通讯作者：
Christoffersen, PF