论文标题
具有随机波动性的多国动态因素模型用于欧元区商业周期分析
A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis
论文作者
论文摘要
本文开发了一种动态因素模型，该模型使用欧元区（EA）针对输出和通货膨胀的特定于国家 /地区的信息来估计输出差距的范围范围。我们的模型假设可以将产出和通货膨胀分解为国家特异性随机趋势和常见的周期性组成部分。通过向潜在状态施加因素结构来引入趋势的共同点。此外，我们将灵活的随机波动率规范引入了对潜在状态的测量误差和创新中的异质性的控制。仔细指定的收缩先验可以将模型推向数据的均匀规范，如果得到数据的支持。我们对输出差距的度量紧密跟踪其他常见的措施，大小和时机的差异很小。为了评估基于模型的输出差距是否有助于预测通货膨胀，我们进行了样本外的预测活动。研究结果表明，在点和密度预测方面，我们的方法都会产生卓越的通胀预测。
This paper develops a dynamic factor model that uses euro area (EA) country-specific information on output and inflation to estimate an area-wide measure of the output gap. Our model assumes that output and inflation can be decomposed into country-specific stochastic trends and a common cyclical component. Comovement in the trends is introduced by imposing a factor structure on the shocks to the latent states. We moreover introduce flexible stochastic volatility specifications to control for heteroscedasticity in the measurement errors and innovations to the latent states. Carefully specified shrinkage priors allow for pushing the model towards a homoscedastic specification, if supported by the data. Our measure of the output gap closely tracks other commonly adopted measures, with small differences in magnitudes and timing. To assess whether the model-based output gap helps in forecasting inflation, we perform an out-of-sample forecasting exercise. The findings indicate that our approach yields superior inflation forecasts, both in terms of point and density predictions.
