Research

This paper investigates how the monetary policy transmis sion changes once the economy is in a low interest rate environment. We estimate a nonlinear model for the euro area and a panel of 10 euro-area countries over the period 1999–2019 and allow for the effects of monetary policy shocks to be state-dependent. Using smooth transition local projections (STLPs), we examine the impulse responses of investment, savings, consumption, and the output gap to an expansionary monetary policy shock under normal and low interest rate regimes. We find evidence for changes in the monetary policy transmission across the two interest rate regimes. Expansionary monetary policy shocks are either less effective in stimulating aggregate demand or their impact reverses the sign in a low interest rate regime.

We estimate the impact of tax shocks on output across different stages of the business cycle. We do so for a panel of advanced economies using a harmonized dataset of narrative-identified exogenous tax changes and a smooth transition local projection model. The output response to an exogenous tax change is significant, but only during economic expansions—in recessions, the tax multiplier is insignificant, both in the short- and medium term. A unique panel of disaggregated tax changes reveals that the state dependence of the tax multiplier is predominantly driven by income and indirect taxes. Our results exhibit no asymmetry in the direction of the tax change and are robust to a number of alternative model specifications and definitions of the business cycle. We rationalize our empirical findings in a model with an occasionally binding borrowing constraint that generates a state-dependent response of hours worked to tax changes, with different tax types producing output patterns consistent with the data.

We propose a new application of quantile regressions to corporate sectoral default probabilities for scenario analysis (QPD). Our model relies on unconditional quantile regressions and a balance sheet based measure of corporate defaults in conjunction with scenario-relevant macro-and sectoral variables. The paper fills a gap in the corporate default modeling and stress-testing literature as it allows to analyze scenario driven sectoral heterogeneity and non-linearity in default probabilities. We evaluate the performance of our model with various tools and demonstrate its abilities with an application to a current scenario concerned with increasing geopolitical and trade tensions and find that the model projects heterogeneous sensitivities across the sectors that are expected to be most vulnerable.