欧元区经济周期分析的随机波动多国动态因子模型
A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis
摘要：
本文开发了一个动态因素模型，使用欧元区（EA）国家的具体信息的产出和通货膨胀，以估计一个区域范围内的措施的产出缺口。我们的模型假设产出和通货膨胀可以分解为特定国家的随机趋势和一个共同的周期性成分。通过对潜在状态的冲击施加因子结构，引入趋势的共动。此外，我们引入灵活的随机波动率规范，以控制异方差的测量误差和创新的潜在状态。如果数据支持，仔细指定的收缩先验允许将模型推向同方差规范。我们对产出缺口的测量与其他常用的测量方法密切相关，在幅度和时间上略有差异。为了评估基于模型的产出缺口是否有助于预测通货膨胀，我们进行了样本外预测。研究结果表明，我们的方法产生优越的通货膨胀预测，无论是在点和密度预测。
英文摘要：
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.
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