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Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

机译：估计的混合RBC模型中的技术冲击和总体波动

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摘要

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of neutral and investment-specific technology shocks in explaining aggregate fluctuations. To achieve this, we estimate the model's posterior density using Bayesian methods. Within this framework we first extend Ireland (2001b, 2004a) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model's errors not explained by the basic RBC model. Our main findings for the model with neutral technical change are: (ⅰ) the VARMA specification of the errors significantly improves the hybrid model's fit to the historical data relative to the VAR and AR alternatives; and (ⅱ) despite setting the RBC model a more difficult task under the VARMA specification, neutral technology shocks are still capable of explaining a significant share of the observed variation in output and its components over shorter-and longer-forecast horizons as well as hours at shorter horizons. When the hybrid model is extended to incorporate investment shocks, we find that: (ⅲ) the VAR specification is preferred to the alternatives; and (ⅳ) the model's ability to explain fluctuations improves considerably.
机译：本文有助于就RBC模型的作用，尤其是中性和特定于投资的技术冲击在解释总体波动方面的作用，进行持续的实证辩论。为此，我们使用贝叶斯方法估计模型的后验密度。在此框架内，我们首先扩展了爱尔兰（2001b，2004a）混合估计方法，以允许矢量自回归移动平均值（VARMA）过程描述模型误差的运动和共同运动，而基本RBC模型并未对此进行解释。我们对具有中性技术变更的模型的主要发现是：（ⅰ）VARMA的误差规范大大提高了混合模型对历史数据的拟合程度（相对于VAR和AR替代方案）； （ⅱ）尽管在VARMA规范下将RBC模型设置为一项更加艰巨的任务，但中性技术冲击仍然能够解释观察到的在较短和较长预测范围以及小时内的输出及其成分变化的显着比例在较短的视野。当将混合模型扩展到包含投资冲击时，我们发现：（ⅲ）VAR规范优于替代方案； （ⅳ）模型解释波动的能力大大提高。

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