Forecasting Corporate Capital Accumulation in Italy: The Role of Survey-Based Information

Claire Giordano, M. Marinucci, A. Silvestrini
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引用次数: 2

Abstract

While there is a vast macroeconomic literature that singles out the main drivers of capital accumulation in advanced economies during and after the global financial and sovereign debt crises’ recessionary phase, there is much less research seeking to identify both models and variables that possess out-of-sample forecasting ability for gross fixed capital formation. Moreover, micro-founded variables are scarcely employed in macroeconomic forecasting of real investment. We fill this gap by considering a battery of univariate and multivariate time-series models to forecast investment of non-financial corporations in Italy, an interesting case study due to its steep downturn during the two afore-mentioned crises. We find that a vector error correction model augmented with firm survey-based variables accounting for business confidence, demand uncertainty and financing constraints generally outperforms the autoregressive benchmark and a series of competing multivariate time-series models in various, alternative, evaluation samples that take into account the impact of both the global financial crisis and the sovereign debt crisis on forecast accuracy.
预测意大利企业资本积累:基于调查的信息的作用
尽管有大量宏观经济文献指出了发达经济体在全球金融危机和主权债务危机衰退阶段期间和之后资本积累的主要驱动因素,但寻求识别具有总固定资本形成的样本外预测能力的模型和变量的研究要少得多。此外,微观变量很少用于实际投资的宏观经济预测。我们通过考虑一系列单变量和多变量时间序列模型来预测意大利非金融公司的投资,这是一个有趣的案例研究,因为它在上述两次危机期间急剧下滑。我们发现,在考虑到全球金融危机和主权债务危机对预测准确性的影响的各种可选评估样本中,向量误差修正模型与考虑商业信心、需求不确定性和融资约束的基于企业调查的变量相结合,通常优于自回归基准和一系列相互竞争的多元时间序列模型。
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