This paper presents a global model linking individual country vector error-correcting models in which the domestic variables are related to the country-specific variables as an approximate solution to a global common factor model. This global VAR is estimated for 26 countries, the euro area...

This paper links granular data of financial institutions to global macroeconomic variables using an infinite-dimensional vector autoregressive (IVAR) model framework. The approach taken allows for an assessment of the two-way links between the financial system and the macroeconomy, while...

This paper links granular data of financial institutions to global macroeconomic variables using an infinite-dimensional vector autoregressive (IVAR) model framework. The approach taken allows for an assessment of the two-way links between the financial system and the macroeconomy, while...

This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of insights from the multiple testing literature. The method tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not...

This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under...

This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under...