Abstract This paper develops a dynamic factor model that uses euro area 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.

中文翻译：

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用于欧元区经济周期分析的具有随机波动率的多国动态因子模型

摘要 本文开发了一个动态因子模型，该模型使用欧元区国家特定的产出和通货膨胀信息来估计一个区域范围的产出缺口度量。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。趋势中的联动是通过对潜在状态的冲击施加一个因素结构来引入的。此外，我们引入了灵活的随机波动率规范来控制测量误差和潜在状态创新的异方差性。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。我们对产出缺口的衡量与其他普遍采用的衡量指标密切相关，在幅度和时间上差异很小。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，我们的方法在点和密度预测方面都产生了卓越的通货膨胀预测。