Contributions in Merlin

null

null

null

We examine how U.S. monetary policy affects the international activities of U.S. banks. We access a rarely studied U.S. bank-level regulatory dataset to assess at a quarterly frequency how changes in the U.S. Federal funds rate (before the crisis) and quantitative easing (after the onset of the crisis) affect changes in cross-border claims by U.S. banks across countries, maturities and sectors, and also affect changes in claims by their foreign affiliates. We find robust evidence consistent with the existence of a potent global bank lending channel. In response to changes in U.S. monetary conditions, U.S. banks strongly adjust their cross-border claims in both the pre- and post-crisis period. However, we also find that U.S. bank affiliate claims respond mainly to host country monetary conditions.

Prosocial work behaviors in a globalized environment do not operate in a cultural vacuum. We assess to what extent voice and helping organizational citizenship behaviors (OCBs) vary across cultures, depending on employees’ perceived level of organizational formalization and national uncertainty. We predict that in contexts of uncertainty, cognitive resources are engaged in coping with this uncertainty. Organizational formalization can provide structure that frees up cognitive resources to engage in OCB. In contrast, in contexts of low uncertainty, organizational formalization is not necessary for providing structure and may increase constraints on discretionary behavior. A three-level hierarchical linear modeling analysis of data from 7,537 employees in 267 organizations across 17 countries provides broad support for our hypothesis: perceived organizational formalization is weakly related to OCB, but where uncertainty is high; formalization facilitates voice significantly, helping OCB to a lesser extent. Our findings contribute to clarifying the dynamics between perceptions of norms at organizational and national levels for understanding when employees may engage in helping and voice behaviors. The key implication is that managers can foster OCB through organizational formalization interventions in uncertain environments that are cognitively demanding.

null

We propose a massively parallelized and optimized framework to solve high-dimensional dynamic stochastic economic models on modern GPU- and MIC-based clusters. First, we introduce a novel approach for adaptive sparse grid index compression alongside a surplus matrix reordering, which significantly reduces the global memory throughput of the compute kernels and maps randomly accessed data onto cache or fast shared memory. Second, we fully vectorize the compute kernels for AVX, AVX2 and AVX512 CPUs, respectively. Third, we develop a hybrid cluster oriented work-preempting scheduler based on TBB, which evenly distributes the time iteration workload onto available CPU cores and accelerators. Numerical experiments on Cray XC40 KNL “Grand Tave” and on Cray XC50 “Piz Daint” systems at the Swiss National Supercomputer Centre (CSCS) show that our framework scales nicely to at least 4,096 compute nodes, resulting in an overall speedup of more than four orders of magnitude compared to a single, optimized CPU thread. As an economic application, we compute global solutions to an annually calibrated stochastic public finance model with sixteen discrete, stochastic states with unprecedented performance. Index Terms—High-Performance Computing, Macroeconomics, Public Finance, Adaptive Sparse Grids, Heterogeneous Systems, CUDA, GPU, MIC

The concept of second-order risk operationalizes the estimation risk in portfolio construction induced by model uncertainty. We study its contribution to the realized volatility of recently developed risk parity strategies. For each strategy, we derive closed-form solutions for the second-order risk, subsequently illustrated in empirical analysis based on real market data. The results suggest a relation between the contribution of second-order risk and the sensitivity of a portfolio to single eigenvectors of the covariance matrix of assets' returns. Among the strategies considered, we find the principal risk parity strategy, that invests equally in each eigenvector underlying the variance-covariance matrix, to be immune to second-order risk. For the other strategies, second-order risk can be partially mitigated by means of statistical methods.

null