| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w20303 |
| 来源ID | Working Paper 20303 |
| Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach | |
| Frank Schorfheide; Dongho Song; Amir Yaron | |
| 发表日期 | 2014-07-17 |
| 出版年 | 2014 |
| 语种 | 英语 |
| 摘要 | We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly consumption data after 1959, and monthly asset return data throughout. We maximize the span of the sample to recover the predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our Bayesian estimation provides strong evidence for a small predictable component in consumption growth (even if asset return data are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our measurement error specification implies that consumption is measured much more precisely at an annual than monthly frequency; and the estimated model is able to capture key asset-pricing facts of the data. |
| 主题 | Econometrics ; Estimation Methods ; Macroeconomics ; Money and Interest Rates ; Financial Economics ; Portfolio Selection and Asset Pricing |
| URL | https://www.nber.org/papers/w20303 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/577977 |
| 推荐引用方式 GB/T 7714 | Frank Schorfheide,Dongho Song,Amir Yaron. Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach. 2014. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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