We develop two nonparametric approaches to test the empirical properties of the credit cycle. The first one is based on Almost Periodically Correlated (APC) time series utilizing the idea of Flexible Fourier Form and subsampling procedure. The second approach is based on spectral analysis provided the stationarity assumption of cyclical fluctuations. Based on the monthly series of credit aggregate and industrial production from selected eighteen EU countries, we show that the empirical properties of the credit cycle differ
We contribute to the existing literature in both, theoretical and empirical, aspects. From theoretical viewpoint we develop methods of formal statistical inference about the main properties of elements of the financial cycle. The statistical uncertainty assessed within both approaches complements standard procedure applied in the macroprudential literature. Our empirical findings show substantial diversity of the credit cycle across analysed countries. Also cyclical component in the credit series is identified much stronger then in case of the series of industrial production. Also the production cycles are much more synchronized across countries compared to the credit.