In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an autoregressive benchmark model in many practically relevant cases. Then, we applied GRNN to forecast quarterly German GDP growth by extending univariate GRNN to multivariate and mixed-frequency settings. We could distinguish between “normal” times and situations where the time-series behavior is very different from “normal” times such as during the COVID-19 recession and recovery. GRNN was superior in terms of root mean forecast errors compared to an autoregressive model and to more sophisticated approaches such as dynamic factor models if applied appropriately.

This paper contributes to a better understanding of the important role that credit demand plays for credit markets and aggregate macroeconomic developments as both a source and transmitter of economic shocks. I am the first to identify a structural credit demand equation together with credit supply, aggregate supply, demand and monetary policy in a Bayesian structural VAR. The model combines informative priors on structural coefficients and multiple external instruments to achieve identification. In order to improve identification of the credit demand shocks, I construct a new granular instrument from regional mortgage origination.
I find that credit demand is quite elastic with respect to contemporaneous macroeconomic conditions, while credit supply is relatively inelastic. I show that credit supply and demand shocks matter for aggregate fluctuations, albeit at different times: credit demand shocks mostly drove the boom prior to the financial crisis, while credit supply shocks were responsible during and after the crisis itself. In an out-of-sample exercise, I find that the Covid pandemic induced a large expansion of credit demand in 2020Q2, which pushed the US economy towards a sustained recovery and helped to avoid a stagflationary scenario in 2022.

In this article, we investigate the divergence between credit ratings (CRs) and Moody's market-implied ratings (MIRs). Our evidence shows that rating gaps provide incremental information to the market regarding issuers' default risk over CRs alone in the short horizon and outperform CRs over extended horizons. The predictive ability of rating gaps is greater for more opaque and volatile issuers. Such predictability was more pronounced during the 2008 financial crisis but weakened in the post-Dodd-Frank Act period. This finding is consistent with credit rating agencies' efforts to improve their performance when facing regulatory pressure. Moreover, our analysis identifies rating-gap signals that do (do not) lead to subsequent Moody's actions to place issuers on negative outlook and watchlists. We find that negative signals from MIR gaps have a real economic impact on issuers' fundamentals such as profitability, leverage, investment, and default risk, thus supporting the recovery-efforts hypothesis.

In her 2021 State of the Union address, European Commission’s President Ursula von der Leyen announced that “[the EU] will invest in 5G and fiber. But equally important is the investment in digital skills.” Indeed, the EU Recovery and Resilience Facility, which runs until 2026, has earmarked substantial funds to tackle the digital divide, in acknowledgment of the fact that the EU is not only missing ICT specialists but also that many Europeans do not have sufficient digital skills to thrive in today’s society and labor market. Many observers argue that older workers in particular lack digital skills, suffering more often from computer anxiety and showing lower computer self-efficacy (Czaja et al. 2006). This lack of skills hampers their employability and productivity in a technologically fast-changing world.

The bank recovery and resolution directive (BRRD) regulates the bail-in hierarchy to resolve distressed banks in the European Union (EU). Using the staggered BRRD implementation across 15 member states, we identify banks’ capital cost responses and subsequent pass-through to borrowers towards surprise elements due to national transposition details. Average bank capital costs increase heterogeneously across countries with strongest funding cost hikes observed for banks located in GIIPS and non-EMU countries. Only banks in core E(M)U countries that exhibit higher funding costs increase credit spreads for corporate borrowers and contract credit supply. Tighter credit conditions are only passed on to more levered and less profitable firms. On balance, the national implementation of BRRD appears to have strengthened financial system resilience without a pervasive hike in borrowing costs.

This paper investigates whether managers’ personal connections help corporate productivity to recover after a negative economic shock. Leveraging the heterogeneity in the severity of the financial crisis across different sectors, the paper reports that (i) the financial crisis had a negative effect on within-firm productivity, (ii) the effect was long-lasting and persistent, supporting a productivity-hysteresis hypothesis, and (iii) managers’ personal connections allowed corporations to recover from this productivity slowdown. Among the possible mechanisms, we show that connected managers operating in affected sectors foster productivity recovery through higher input cost efficiency and better access to the credit market, as well as more efficient use of labour and capital.

Studies find that during the 2007–2009 global financial crisis, loan spreads rose and corporate lending tightened, especially for foreign borrowers (a flight-home effect). We find that banks in countries with explicit deposit insurance (DI) made smaller reductions in total lending and foreign lending, experienced smaller increases in loan spreads, and had quicker post-crisis recoveries. These effects are more pronounced for banks heavily relying on deposit funding. Evidence also reveals that more generous or credible DI design is associated with a stronger stabilization effect on bank lending during the crisis, confirmed by the difference-in-differences analysis based on expansion of DI coverage during the crisis. The stabilization effect is robust to the use of country-specific crisis measures and control of temporary government guarantees.