This paper assesses the extent to which common factors underlie indicators of vulnerability to financial crises in emerging market economies (EMEs) and whether this link is changing over time. We use a Bayesian dynamic common factor model to estimate their common component in a sample of up to 41 countries including both developed as well as emerging economies. This permits us to interpret the component in common to both of them as a global factor. We introduce time variation into the model to investigate whether indicators are decoupling from global factors over time. While decoupling can be observed in a few cases, the exposure to global factors in most countries tends to fluctuate around the mean. Broadly speaking then, the answer is no.

We examine how changes in capital requirements and monetary policy shocks affect corporate investment during a credit boom. Our empirical analysis uses data on SMEs in the UK between 1998 and 2006, a period when monetary policy and microprudential regulation were set by independent institutions. We find that an increase in bank-specific capital requirements led to a contraction in corporate debt and investment, but only for firms with short bank relationships. This suggests that relationships between firms and banks are crucial for the transmission of regulatory shocks. Long relationships also attenuate the impact of monetary policy shocks, but to a smaller degree than for capital requirement changes. We also find that the two policies do not dampen or amplify the effect of each other, but their effects vary with the size of banks’ capital buffers and the creditworthiness of firms.

Fabo et al. (2021) use OLS regression to show that central bankers report quantitatively larger effects of QE on output and inflation than do academic researchers. We reject the null hypothesis of a Gaussian distribution of the residuals in many of these specifications, except for the language regressions. We then repeat the analysis with regression estimators that are robust to a non-Gaussian residual distribution where this is feasible. We use the median regression and the MS regression estimator. With these robust regression approaches, the null hypothesis that central bank and academic researchers report the same quantitative effect of QE on output and inflation cannot be rejected, with point estimates which are less than half as large. This statistical challenge suggests that more research is required to understand better whether central bank researchers report different QE multipliers or not.