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G23-2 Labour Markets in the Transition Era: Future of Work, AI, Unemployment, Gig Economy and Digital Nomads

Tracks
Track 2
Friday, August 28, 2026
11:00 - 13:00
Auditorium 245A - North Building - Faculty of Geology and Geography

Details

Chair: Michael Moritz The discussant for each presentation is the presenter of the next paper in the session. The first presenter is the discussant of the last paper.


Speaker

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Prof. Annekatrin Niebuhr
Senior Researcher
Institute for Employment Research, Kiel University

Spatial disparities in hiring problems: The role of firm characteristics, job features, and search channel

Author(s) - Presenters are indicated with (p)

Prof. Annekatrin Niebuhr (p), Dr. Michaela Fuchs, Dr. Jan Cornelius Peters, Georg Sieglen

Abstract

Against the backdrop of discussions about growing regional labour shortages, this study investigates spatial disparities in hiring problems using representative micro data on vacancies and establishments in Germany. Our results point to significant disparities that vary along the urban-rural hierarchy depending on indicator. While establishments in rural areas receive less suitable applications and more often abandon hiring plans, firms in cities more often report problems related to the applicants’ qualification and wage expectations. Prevailing types of establishments and jobs explain an important part, but not all of the disparities. Evidence on concessions suggests, moreover, that employer responses to
labour shortages differ depending on the location type. While establishments in urban areas are more likely to compromise on wages, concessions on qualification are more frequent outside big cities. However, rural establishments report problems related to applicants’ insufficient qualifications less
often. Heterogenous hiring problems indicate that there is need for place-sensitive policies rather than place-based policies that focus on specific locations.

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Dr. Michael Moritz
Senior Researcher
Institute for Employment Research (IAB)

Worker Sorting, Industry Sorting, and Agglomeration Effects

Author(s) - Presenters are indicated with (p)

Dr. Michael Moritz (p), Prof. Dr. Wolfgang Dauth, Dr. Anja Rossen

Abstract

Significant spatial wage disparities can be observed in virtually all countries with free market economies. In particular, larger cities offer higher wages compared to more rural areas. There are at least two major explanations for this observation: (1) people with characteristics that are related to higher wages prefer to live in larger cities and (2) the same worker becomes more productive if she or he is located in a larger rather than a smaller city. In this paper, we shed light on the relative importance of those explanations and demonstrate that, after controlling for worker and firm sorting, there is still a significant agglomeration effect, which we call the true urban wage premium, that makes wages increase with the size of population. Following Card, Rothstein, and Yi (2024, 2025), we find a so-called hierarchy effect, i.e. the mobility of workers between cities of different sizes is usually not between representative firms. Furthermore, we demonstrate how the wage decomposition by Abowd, Kramarz, and Margolis (1999) can be adapted to identify the true urban wage premium. We split the AKM plant effects into an industry-specific component and a region-specific component. Those premia reveal the various sources of wage disparities and are informative to (local) policymakers. We come to the conclusion that on the one hand the decomposition is nearly fully absorbed by the regional component. On the other hand, bigger cities do not offer a more favorable industry mix.

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Mr Emilio Becker
Ph.D. Student
Pucrs

Spatial spillovers in local labour markets: tourism employment and wage bills across Chilean municipalities

Author(s) - Presenters are indicated with (p)

Mr Emilio Becker (p), Dr Stephan Brunow, Dr Eduardo Sanguinet,

Abstract

Spatial location shapes how labour market opportunities and inequalities evolve, because economic outcomes in one place may be influenced by what happens next door. Tourism provides a particularly informative lens for studying these mechanisms: it is employment-intensive, relies on territorially embedded assets, and can generate both positive spillovers across neighbouring municipalities and competitive displacement.

Chile is a revealing setting. Between 2000 and 2020, the Metropolitan Region of Santiago consistently concentrated more than 40% of national GDP, while regional and municipal per capita income gaps remained persistent. At the same time, the country has undergone a gradual structural transformation toward service-based employment, which today accounts for roughly 70% of national employment. Within this transformation, tourism is far from marginal: between 2012 and 2022, employment linked to tourism-related activities increased by approximately 57%, while total national employment expanded by about 10% during the same period. Yet national aggregates conceal where these gains materialise, and whether tourism growth has been spatially diffuse or concentrated in already advantaged territories.

A key step is to look beyond job counts. Municipalities with similar tourism employment can generate very different tourism-related wage bills due to differences in occupational composition, seasonality, productivity, firm structure and specialization. Jointly analysing tourism employment and wage bills therefore allows an assessment of whether spatial concentration in jobs coincides with concentration in labour income, or whether job creation and income capture diverge across space.

Preliminary descriptive evidence based on municipal location quotients for 2007, 2012, 2017 and 2022 shows pronounced and persistent specialization: several municipalities display values above 2 and, in some cases, above 4, while many remain underrepresented.

The formal analysis focuses on two benchmark years, 2013 and 2023, covering all 345 municipalities. Spatial autocorrelation is assessed using global Moran’s I and LISA, and spatial econometric models (SAR, SEM and SDM) are estimated using explanatory variables capturing tourism capacity, accessibility, labour-market scale and density, human capital, and natural and cultural amenities, allowing the identification of direct and indirect spatial spillover effects.

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