Wage Dispersion and Decentralization of Wage Bargaining

This paper studies how decentralization of wage bargaining from sector to firm-level influences wage levels and wage dispersion. We use detailed panel data covering a period of decentralization in the Danish labor market. The decentralization process provides variation in the individual worker's wage-setting system that facilitates identification of the effects of decentralization. We find a wage premium associated with firm-level bargaining relative to sector-level bargaining, and that the return to skills is higher under the more decentralized wage-setting systems. Using quantile regression, we also find that wages are more dispersed under firm-level bargaining compared to more centralized wage-setting systems.wage bargaining, decentralization, wage dispersion

Wage Dispersion and Decentralization of Wage Bargaining

This paper studies how decentralization of wage bargaining from sector to firm level influences wage levels and wage dispersion. We use a detailed panel data set covering a period of decentralization in the Danish labor market. The decentralization process provides exogenous variation in the individual worker's wage-setting system that facilitates identification of the effects of decentralization. Consistent with predictions we find that wages are more dispersed under firm-level bargaining compared to more centralized wage-setting systems. However, the differences across wage-setting systems are reduced substantially when controlling for unobserved individual level heterogeneity.Wage bargaining; decentralization; panel data quantile regression

Context and Aggregation: An Experimental Study of Bias and Discrimination in Organizational Decisions

This paper addresses a notable gap at the intersection of organizational economics and organization science: how does organizational context influence aggregation of individual behavior in organizational decisions? Using basic centralized versus decentralized organizational structures as building blocks for our experimental design, we examine whether assignment of organizational positions, incentive schemes, and structural configuration induce endogenous adaptation in the form of change in reservation levels (bias) or modified discrimination capability in subjects' behavior. We found that evaluators adapted their reservation and discrimination levels in centralized structures, whereas they did not generally adapt their reservation and discrimination levels when placed in decentralized structures. We identify mechanisms that explain these findings; explain how they influence aggregate, organizational behavior; and discuss implications for research and practice

HANA: A HAndwritten NAme Database for Offline Handwritten Text Recognition

Methods for linking individuals across historical data sets, typically in combination with AI based transcription models, are developing rapidly. Probably the single most important identifier for linking is personal names. However, personal names are prone to enumeration and transcription errors and although modern linking methods are designed to handle such challenges these sources of errors are critical and should be minimized. For this purpose, improved transcription methods and large-scale databases are crucial components. This paper describes and provides documentation for HANA, a newly constructed large-scale database which consists of more than 1.1 million images of handwritten word-groups. The database is a collection of personal names, containing more than 105 thousand unique names with a total of more than 3.3 million examples. In addition, we present benchmark results for deep learning models that automatically can transcribe the personal names from the scanned documents. Focusing mainly on personal names, due to its vital role in linking, we hope to foster more sophisticated, accurate, and robust models for handwritten text recognition through making more challenging large-scale databases publicly available. This paper describes the data source, the collection process, and the image-processing procedures and methods that are involved in extracting the handwritten personal names and handwritten text in general from the forms

Panel Data Evidence on Europe

What has been the quantitative effect on productivity growth of information and communication technology (ICT) in Europe after 1995? Based on a multi-country sectoral panel data set, we provide econometric evidence of positive and significant productivity effects of ICT in Europe, mainly due to advances in total factor productivity. In contrast to the US, this impact of ICT has happened against a negative macro economic shock not related to ICT. Our main result is in contrast to the established consensus in the growth accounting literature that there has been no acceleration of productivity growth in Europe, mainly due to the performance of ICT-using sectors. One important advantage of using econometric methods is that we can distinguish between growth effects from ICT and macro economic shocks; a feature that growth accounting methods cannot handle

Hybrid Lattice-Boltzmann-Potential Flow Simulations of Turbulent Flow around Submerged Structures

We report on the development and validation of a 3D hybrid Lattice Boltzmann Model (LBM), with Large Eddy Simulation (LES), to simulate the interactions of incompressible turbulent flows with ocean structures. The LBM is based on a perturbation method, in which the velocity and pressure are expressed as the sum of an inviscid flow and a viscous perturbation. The far- to near-field flow is assumed to be inviscid and represented by potential flow theory, which can be efficiently modeled with a Boundary Element Method (BEM). The near-field perturbation flow around structures is modeled by the Navier–Stokes (NS) equations, based on a Lattice Boltzmann Method (LBM) with a Large Eddy Simulation (LES) of the turbulence. In the paper, we present the hybrid model formulation, in which a modified LBM collision operator is introduced to simulate the viscous perturbation flow, resulting in a novel perturbation LBM (pLBM) approach. The pLBM is then extended for the simulation of turbulence using the LES and a wall model to represent the viscous/turbulent sub-layer near solid boundaries. The hybrid model is first validated by simulating turbulent flows over a flat plate, for moderate to large Reynolds number values, Re ∈ [3.7×104;1.2×106]; the plate friction coefficient and near-field turbulence properties computed with the model are found to agree well with both experiments and direct NS simulations. We then simulate the flow past a NACA-0012 foil using a regular LBM-LES and the new hybrid pLBM-LES models with the wall model, for Re = 1.44 x 106. A good agreement is found for the computed lift and drag forces, and pressure distribution on the foil, with experiments and results of other numerical methods. Results obtained with the pLBM model are either nearly identical or slightly improved, relative to those of the standard LBM, but are obtained in a significantly smaller computational domain and hence at a much reduced computational cost, thus demonstrating the benefits of the new hybrid approach