Cyclicality of job and worker flows: New data and a new set of stylized facts

We study the relationship between cyclical job and worker flows at the plant level using a new data set spanning from 1976-2006. We find that procyclical labor demand explains relatively little of procyclical worker flows. Instead, all plants in the employment growth distribution increase their worker turnover during booms. We also find that cyclical changes in the employment growth distribution are mostly driven by plants moving from inactivity to a growing labor force during booms. Consequently, increased labor turnover at growing plants is the main quantitative driver behind increased labor turnover during booms. We argue that on the job search models are able to capture non-parallel shifts in the employment growth distribution and procyclical conditional worker flows for a range of the growth distribution. Yet, they fail to rationalize procyclical accession rates for all shrinking and procylical separation rates for all growing plants

Cyclicality of Job and Worker Flows: New Data and a New Set of Stylized Facts

We study the relationship between cyclical job and worker flows at the plant level using a new data set spanning from 1976-2006. We find that procyclical labor demand explains relatively little of procyclical worker flows. Instead, all plants in the employment growth distribution increase their worker turnover during booms. We also find that cyclical changes in the employment growth distribution are mostly driven by plants moving from inactivity to a growing labor force during booms. Consequently, increased labor turnover at growing plants is the main quantitative driver behind increased labor turnover during booms. We argue that on the job search models are able to capture non-parallel shifts in the employment growth distribution and procyclical conditional worker flows for a range of the growth distribution. Yet, they fail to rationalize procyclical accession rates for all shrinking and procylical separation rates for all growing plants

A fully adaptive interpolated stochastic sampling method for random PDEs

A numerical method for the fully adaptive sampling and interpolation of PDE with random data is presented. It is based on the idea that the solution of the PDE with stochastic data can be represented as conditional expectation of a functional of a corresponding stochastic differential equation (SDE). The physical domain is decomposed subject to a non-uniform grid and a classical Euler scheme is employed to approximately solve the SDE at grid vertices. Interpolation with a conforming finite element basis is employed to reconstruct a global solution of the problem. An a posteriori error estimator is introduced which provides a measure of the different error contributions. This facilitates the formulation of an adaptive algorithm to control the overall error by either reducing the stochastic error by locally evaluating more samples, or the approximation error by locally refining the underlying mesh. Numerical examples illustrate the performance of the presented novel method

Heterobimetallic Gold/Ruthenium Complexes Synthesized via Post‐functionalization and Applied in Dual Photoredox Gold Catalysis

The synthesis of heterobimetallic AuI/RuII complexes of the general formula syn- and anti-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ is reported. The ditopic bridging ligand L1∩L2 refers to a P,N hybrid ligand composed of phosphine and bipyridine substructures, which was obtained via a post-functionalization strategy based on Diels-Alder reaction between a phosphole and a maleimide moiety. It was found that the stereochemistry at the phosphorus atom of the resulting 7-phosphanorbornene backbone can be controlled by executing the metal coordination and the cycloaddition reaction in a different order. All precursors, as well as the mono- and multimetallic complexes, were isolated and fully characterized by various spectroscopic methods such as NMR, IR, and UV-vis spectroscopy as well as cyclic voltammetry. Photophysical measurements show efficient phosphorescence for the investigated monometallic complex anti-[(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ and the bimetallic analogue syn-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$, thus indicating a small influence of the {AuCl} fragment on the photoluminescence properties. The heterobimetallic Au$^{I}$/Ru$^{II}$ complexes syn- and anti-[{AuCl}(L1∩L2){Ru(bpy)$_{2}$}][PF$_{6}$]$_{2}$ are both active catalysts in the P-arylation of aryldiazonium salts promoted by visible light with H-phosphonate affording arylphosphonates in yields of up to 91 %. Both dinuclear complexes outperform their monometallic counterparts

Worker Churn and Employment Growth at the Establishment Level

We find that worker turnover is more procyclical than job turnover. Procyclical worker churn result almost exclusively from job-to-job transitions. The size and cyclical properties of churn are close to uniform along the entire employment growth distribution of establishments. Even shrinking firms churn, i.e., they hire while separating from workers. The cyclical movements in the source of hiring, from employment vs non-employment, are close to uniform across the employment growth distribution

Job and worker flows: New stylized facts for Germany

We study the relationship between cyclical job and worker flows at the establishment level using the new German AWFP dataset spanning from 1975-2014. We find that worker turnover moves more procyclical than job turnover. This procyclical worker churn takes place along the entire employment growth distribution of establishments. We show that these procyclical conditional worker flows result almost exclusively from job-tojob transitions. Growing establishments fuel their employment growth by poaching workers from other establishments as the boom matures. At the same time, non-growing establishments replace these workers by hiring from other establishments and non-employment

Adaptive SDE based interpolation for random PDEs

A numerical method for the fully adaptive sampling and interpolation of PDE with random data is presented. It is based on the idea that the solution of the PDE with stochastic data can be represented as conditional expectation of a functional of a corresponding stochastic differential equation (SDE). The physical domain is decomposed subject to a non-uniform grid and a classical Euler scheme is employed to approximately solve the SDE at grid vertices. Interpolation with a conforming finite element basis is employed to reconstruct a global solution of the problem. An a posteriori error estimator is introduced which provides a measure of the different error contributions. This facilitates the formulation of an adaptive algorithm to control the overall error by either reducing the stochastic error by locally evaluating more samples, or the approximation error by locally refining the underlying mesh. Numerical examples illustrate the performance of the presented novel method

Multistimuli‐Responsive [3]Dioxaphosphaferrocenophanes with Orthogonal Switches

Novel multistimuli-responsive phosphine ligands comprising a redox-active [3]dioxaphosphaferrocenophane backbone and a P-bound imidazolin-2-ylidenamino entity that allows switching by protonation are reported. Investigation of the corresponding metal complexes and their redox behaviour are reported and show the sensitivity of the system towards protonation and metal coordination. The experimental findings are supported by DFT calculations. Protonation and oxidation events are applied in Rh-catalysed hydrosilylations and demonstrate a remarkable influence on reactivity and/or selectivity

SDE based regression for random PDEs

A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour