Claudia Cigagna and Giovanni Sulis
The purpose of this paper is to analyse the effect of unemployment and labour institutions such as employment protection legislation, coverage of unemployment benefits, minimum…
Abstract
Purpose
The purpose of this paper is to analyse the effect of unemployment and labour institutions such as employment protection legislation, coverage of unemployment benefits, minimum wages (MW), union power and tax wedge on migration flows. The authors allow for interactions of these institutions with migration entry laws, as both affect equilibrium wages and employment in destination countries, influencing mobility decisions of immigrants.
Design/methodology/approach
The authors use data on migration flows for a sample of 15 OECD countries over the period 1980-2006. The relationship between flows and labour institutions is analysed using OLS techniques and including destination and origin-by-year fixed effects. The coefficients of interest are identified through within country variation. The authors test the robustness of the results to different specifications using, among others, dynamic models for panel data.
Findings
The authors find strong and negative effects of unemployment, employment protection and migration policy on flows. The negative effect of migration policy on flows is larger in countries with high than in countries with low employment protection. The authors find positive effects for MW, unemployment benefits and union power. The authors show heterogeneous effects depending on the group of countries of origin and destination.
Research limitations/implications
While the identification strategy allows us to estimate the effects of interest, the baseline estimates may suffer from endogeneity problems in terms of omitted variable bias and reverse causality. The sensitivity checks provide mixed results and show that baseline estimates are not always robust to different specifications. Further work is needed to better address the problem of endogeneity.
Originality/value
The paper adds to the previous literature on the determinants of immigration flows by explicitly considering the labour market environment in destination countries. The results provide insights into potential interaction effects and coordination of reforms in labour markets and immigration policies.
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This paper seeks to study gender wage differentials in Italy using first‐order predictions of monopsony‐search models. It compares empirical predictions of these models against…
Abstract
Purpose
This paper seeks to study gender wage differentials in Italy using first‐order predictions of monopsony‐search models. It compares empirical predictions of these models against other competing ones of wage determination in non‐competitive settings.
Design/methodology/approach
The paper looks at the empirical relevance of the model in terms of third degree wage discrimination among men and women by estimating the labour supply elasticity to the individual firm. It also tests the monopsony model using a “natural” experiment. Italian administrative longitudinal data from INPS are used.
Findings
Women have lower elasticity of labour supply to the individual firm: employer size regressions indicate larger effects (and consequently lower elasticity) for women as predicted by the monopsony model. Using the theoretical dynamic monopsony‐search model of Burdett and Mortensen, wage elasticity of separations and recruits confirm this result. Using relative men/women employment effects resulting from institutional changes in wage indexation mechanism (Scala Mobile), it is found that relative male employment responded differently in the two periods to the exogenous relative increase in the wage differential, as predicted by the monopsony model. Search frictions explain about 50 per cent of the gender differential.
Research limitations/implications
No role for discrimination. Better controls for rents and union status would be needed. More rich firm data would be needed.
Originality/value
The paper is one of the few attempts of testing implications of monopsony models in unionised labour markets, such as Italy, after some important reforms in wage bargaining agreements. The change in institutional agreements is an interesting test for different theories of wage determination.
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Fabio Berton, Stefano Dughera and Andrea Ricci
In this chapter, we propose a theoretical assessment of the relationship between unions and investments. We develop a simple model where a firm chooses its investment level…
Abstract
In this chapter, we propose a theoretical assessment of the relationship between unions and investments. We develop a simple model where a firm chooses its investment level anticipating the employee's effort choice and the outcome of wage bargaining. First, and consistently with the holdup view, we find that the union's bargaining power has a negative effect on the accumulation of fixed capital. Second, we show that this negative effect is mitigated by the voice ability of unions to ease the displeasure of exerting effort. Hence, when the voice ability of unions is strong vis-à-vis their bargaining power, the holdup view does not necessarily survive, and unionized firms invest more than their nonunionized competitors.
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Alex Bryson and Harald Dale-Olsen
We present theoretical and empirical evidence challenging early studies that found unions were detrimental to workplace innovation. Under our theoretical model, unions prefer…
Abstract
We present theoretical and empirical evidence challenging early studies that found unions were detrimental to workplace innovation. Under our theoretical model, unions prefer product innovation to labor-saving technological process innovation, thus making union wage bargaining regimes more conducive to product innovation than competitive pay setting. We test the theory with population-representative workplace data for Britain and Norway. We find strong support for the notion that local bargaining leads to product innovation, either alone or together with technological innovation.
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Angelo Rosa, Alessandro Massaro, Giustina Secundo and Giovanni Schiuma
This study aims to provide a methodology and tools to design new organizational processes and artificial intelligence (AI)-based scoring to optimize the resources management in…
Abstract
Purpose
This study aims to provide a methodology and tools to design new organizational processes and artificial intelligence (AI)-based scoring to optimize the resources management in healthcare units.
Design/methodology/approach
Process design and process data-driven simulation: the processes are designed by the business process modeling and notation and the unified modeling language standards. Data processing is performed by Correlation matrix analysis and by Fuzzy c-Means data clustering. The matching between the two methods provides the most indicated final corrective actions of the “TO BE” organizational model.
Findings
This proposed method, experimentally applied in this work merging the lean management model (LMM), process mining (PM) and AI methods, named process mining organization (PMO) model (Rosa et al., 2023 (b)), is able to improve organizational processes of a hospitalization unit (HU) by developing three propaedeutic phases: (1) analysis of the current state of the processes (“AS IS”) by identifying the critical issues as bottlenecks of processes, (2) AI data processing able to provide additional classified and predicted information allowing the “TO BE” workflow process and (3) implementation of corrective actions suggested by the PMO in order to support strategic decision-making processes in the short, medium and long term by classifying an order of priority about the healthcare procedures/protocols to perform.
Research limitations/implications
The main limitation of the proposed case study is in the limited number of available digital data to process. This aspect reduces the capability to interpret result. In any case, the proposed methodology is a “launch” work to define a new approach to integrate organizational processes including workflow design and AI scoring. Future work will be focused on managerial implications due to use of the discussed method: design and development of new human resource (HR) organizational protocols following data analysis to optimize costs and care services and to decrease injury compensation claims.
Practical implications
Main implications are in healthcare managerial scenarios: design and development of new HR organizational protocols following data analysis to optimize costs and care services and to decrease injury compensation claims.
Social implications
Care services optimization is addressed on HUs.
Originality/value
The design of HR organizational processes integrates AI-driven data decision-making processes. This case study examines AI-based innovation analytics addressed on resource efficiency.