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Bauer, Anja & Enzo Weber (2026): Decomposing Variations in Labor Market Mismatch. (IAB-Discussion Paper 03/2026), Nürnberg, 19 S. DOI:10.48720/IAB.DP.2603

Abstract

"Dieses Diskussionspapier zeigt, wie Veränderungen des Arbeitsmarkt-Mismatch auf die Komponenten Arbeitslosigkeit, offene Stellen und Matchingeffizienz zurückgeführt werden können. Wir stellen fest, dass die Arbeitslosigkeit der wichtigste Faktor ist und auch die zyklischen Schwankungen bestimmt, während die Beiträge der offenen Stellen geringer und antizyklisch sind. Wir unterscheiden nach der Ursache der Arbeitslosigkeit und zeigen, dass Ströme gegenüber der Beschäftigung den Mismatch verstärken, während dies für Nichtbeschäftigung und Ausbildung / Weiterbildung nicht der Fall ist." (Autorenreferat, IAB-Doku)

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Bossler, Mario & Martin Popp (2026): Labor Demand on a Tight Leash (im Erscheinen). In: ILR review, 2025-10-21.

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Galos, Diana Roxana & Joris Frese (2026): Online social class cues and employability: Experimental evidence from Germany. In: Social science research, Jg. 133. DOI:10.1016/j.ssresearch.2025.103258

Abstract

"Social media platforms, such as Twitter or Instagram, offer easily accessible information – relevant or not – for employers when evaluating candidates for a position. In particular, they tend to be sources of information about individuals’ interests and leisure activities.Because interests are highly stratified by social class (e.g., engagement in highbrow and lowbrow activities), this represents a new way for class to potentially manifest itself in the hiring process. To study discrimination in hiring based on online social class cues, we conducted a pre-registered survey experiment in Germany with samples of employers and non-employers, manipulating job applicants’ class cues on social media(highbrow versus lowbrow). Overall, we found no difference in preferences for the candidates displaying highbrow and lowbrow activities on their social media profiles. However, this masks important differences in the specific activities proxying for class. When these activities have no relevance for the jobs in question, higher-class candidates are preferred. Exploratory analyses show that respondents are more likely to express positive sentiments toward the higher-class profiles, with highbrow activities being positively associated with work-related traits. Our findings highlight the need to consider how digital environments and, more specifically, online social class cues, may contribute to class bias in hiring." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier Inc.) ((en))

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Loewy, Michael B. (2026): Teaching two-sided labor search theory to undergraduates: A model and some exercises. In: The journal of economic education, Jg. 57, H. 1, S. 27-38. DOI:10.1080/00220485.2025.2549718

Abstract

"Although the Diamond-Mortensen-Pissarides (DMP) model originated roughly 40 years ago and its authors shared the 2010 Nobel Memorial Prize in Economic Sciences, their work is still absent from several recent editions of popular intermediate macroeconomics textbooks. In contrast, Stephen Williamson's textbook (2014, 2018) presents an early static version of the DMP model accessible to undergraduates. This article's author compensates for the topic's omission in some intermediate-level textbooks by discussing Williamson's static DMP model and presenting four additional exercises not covered in his main text: (1) a change in a vacancy's posting price; (2) an increase in workers' relative bargaining power; (3) the introduction of a minimum wage; and (4) the introduction of an endogenous unemployment insurance benefit. The latter exercise yields an interesting neutrality result." (Author's abstract, IAB-Doku) ((en))

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Mühlbauer, Sabrina & Enzo Weber (2026): Machine learning for labor market matching. In: Machine learning with applications, Jg. 23, 2026-02-03. DOI:10.1016/j.mlwa.2026.100861

Abstract

"This paper develops a large-scale machine learning framework to improve labor market matching using rich administrative data. Matching is defined as a job seeker entering employment in a specific occupational field. We exploit comprehensive employment biographies from Germany, covering individual characteristics and job-related information, to estimate employment probabilities across occupations and generate personalized job recommendations. The contribution lies in demonstrating why machine learning methods are particularly well suited for administrative labor market data and outperform traditional statistical approaches. We compare logit, ordinary least squares (OLS), k-nearest neighbors, and random forest (RF). RF consistently achieves the highest predictive performance. Its advantage is rooted in key methodological properties: RF builds an ensemble of decision trees trained on bootstrap samples, introduces random feature selection at each split, and aggregates predictions through majority voting. This enables RF to capture nonlinear relationships and complex interactions, remain robust in high-dimensional settings, and reduce overfitting — features that are particularly relevant for heterogeneous and imbalanced administrative data. Compared to conventional models, RF better exploits the full informational content of employment histories, especially when estimating on all employment spells rather than restricting the sample to unemployment-to-employment transitions. The sample comprises approximately 55 million spells, representing about 6 percent of the German workforce from 2012 to 2018. Our results suggest that ML-based matching, relative to standard statistical approaches, could hypothetically reduce the unemployment rate by up to 0.3 percentage points, highlighting the practical relevance of RF-based decision support for labor market policy." (Author's abstract, IAB-Doku, © Elsevier) ((en))

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Stans, Renske, Laura Ehrmantraut, Malin Siemers & Pia Pinger (2026): The Impact of Higher Education on Employer Perceptions. In: The Economic Journal, Jg. 136, H. 674, S. 602-625. DOI:10.1093/ej/ueaf061

Abstract

"Do employers seek to attract individuals with more education because it enhances human capital or because it signals higher levels of pre-existing traits? We experimentally vary master’s degree completion rates on applicant résumés and examine how this influences candidates’ desirability and employer perceptions of their productive characteristics. Our findings show that while a completed master’s degree increases desirability, an incomplete master’s degree is perceived by human resource managers as less favorable than a bachelor’s degree. This suggests that employersprefer candidates with higher education mainly because they view the degree as a signal of pre-existing productive traits. Consistent with this, employers perceive both cognitive and non-cognitive traits as stronger in master graduates but non-cognitive traits as weaker in master dropouts compared to bachelor’s degree holders. Overall, perceived cognitiveand non-cognitive traits play a larger role in determining a candidate ’s attractiveness than expertise. This paper thus provides causal evidence on the origins of the education premium." (Author's abstract, IAB-Doku) ((en))

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Yeo, Hyesu (2026): Older Worker’s Job Search Activities and Employment Transition. In: Research on Aging, Jg. 48, H. 1, S. 28-43. DOI:10.1177/01640275251343107

Abstract

"This study investigated job search patterns among American older workers. Data from the 2016-2018 Health and Retirement Study included 1501 individuals aged 50+ who were looking for jobs in 2016. Latent Class Analysis (LCA) was conducted to identify job search patterns based on nine types of job search activities. Multinomial logistic regression was then used to examine membership in each class. Five job search patterns emerged from the LCA analysis, including No Ads, Ads only, Friends & Ads, Phone & Ads, and Agencies & Ads. Employment transitions were related to job search patterns. Unemployed older workers, despite utilizing more diverse job search methods, were less likely to secure new jobs compared to their employed peers. These findings highlight the need for workforce development programs to focus on workplace skill-building training and educational opportunities before becoming unemployed and age-friendly workforce development tailored to older workers with low-skilled and low income." (Author's abstract, IAB-Doku) ((en))

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Zimmermann, Florian & Matthias Collischon (2026): Women use Social Networks for Job Search more often than Men, but Men use them more intensely. In: Economics Letters, Jg. 259, 2025-12-18. DOI:10.1016/j.econlet.2025.112795

Abstract

"Research has long highlighted the role of social capital for labor market outcomes, but gendered processes received surprisingly little attention. Employing representative German survey data, we analyze differences in job search via social networks. Contrary to expectations, we find that women report using social networks more often at the extensive margin compared to men, but men are more likely utilize networks in ways requiring more effort, such as being introduced to employers. Thus, we highlight the importance of investigating social networks in detail to understand the role of social networks for generating or sustaining gender inequalities in the labor market." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))

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Arndt, Franziska, Philip Herzer & Paula Risius (2025): Auszubildende über Social Media finden. (KOFA kompakt / Kompetenzzentrum Fachkräftesicherung 2025,01), Köln, 6 S.

Abstract

"Die Lage am Ausbildungsmarkt ist angespannt: Viele Unternehmen können ihre Ausbildungsplätze nicht besetzen, während gleichzeitig zahlreiche Jugendliche ohne Ausbildungsplatz bleiben. Um diese Passungsprobleme zu überwinden, ist es wichtig, dass Unternehmen ihre Ausbildungsplätze dort bewerben, wo Jugendliche suchen. Besonders wichtig sind für Jugendliche Online-Stellenanzeigen und die Vermittlungsangebote der Bundesagentur für Arbeit. An dritter Stelle stehen Social-Media-Kanäle. Die passgenaue Auswahl von Social-Media-Kanälen und -Inhalten kann Unternehmen somit näher an Jugendliche bringen. Doch: Während Jugendliche vor allem über Instagram, YouTube und WhatsApp suchen, nutzen Unternehmen neben Instagram eher Facebook, LinkedIn und Xing. Gerade Facebook ist für Jugendliche jedoch kaum relevant. Die direkte Ansprache von Jugendlichen mit Haupt- und Realschulabschluss bietet besonders großes Potenzial, denn es zeigt sich, dass Haupt- und Realschüler:innen anders suchen als Abiturient:innen: Haupt- und Realschüler:innen nutzen neben Online-Stellenanzeigen besonders analoge Formate. In den sozialen Medien nutzen sie vorwiegend Instagram, WhatsApp und YouTube." (Autorenreferat, IAB-Doku)

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Baktash, Mehrzad B. (2025): Overeducation, performance pay and wages: evidence from Germany. In: Education Economics, S. 1-21. DOI:10.1080/09645292.2025.2546445

Abstract

"Overeducated workers are more productive and have higher wages in comparison to their adequately educated coworkers in the same jobs. However, they have lower wages than their similarly educated peers who are in correctly matched jobs. This study examines the hypotheses that overeducated workers sort into performance pay jobs as an adjustment mechanism and that performance pay enhances their wages. Using the SOEP, I show that overeducation associates with a higher likelihood of sorting into performance pay jobs and that performance pay significantly improves the wages of overeducated workers. The findings hold in endogenous switching regressions and several robustness checks." (Author's abstract, IAB-Doku) ((en))

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Basbug, Gokce & Roberto M. Fernandez (2025): Gendered Job Search: An Analysis of Gender Differences in Reservation Wages and Job Applications. In: ILR review, Jg. 78, H. 1, S. 217-239. DOI:10.1177/00197939241298623

Abstract

"Using a weekly survey of unemployed workers, this study examines gender differences in reservation wages and applied-for occupational categories. The analysis shows that a large portion of the gender difference in reservation wages is attributable to the fact that women and men search for different occupations. Findings further demonstrate that women are more likely to apply to occupations with higher percentages of female incumbents, and they target these occupations from the earlier stages of their job search, rather than adjusting their preferences over the course of unemployment. Further analysis shows that women are more likely to apply for occupational categories that offer greater flexibility in working hours, more opportunities for interpersonal interactions, less critical decision-making, and a less competitive environment. Finally, the analysis reveals that household responsibilities, particularly the number of children, and willingness to take risks are important factors influencing women’s decisions to pursue occupations with less demanding work hours." (Author's abstract, IAB-Doku) ((en))

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Benanav, Aaron (2025): When an Accountant Becomes a Taxi Driver: Unemployment, Labor Market Institutions, and Economic Theory. In: History of political economy, Jg. 57, H. S1, S. 81-110. DOI:10.1215/00182702-12134470

Abstract

"This article reconstructs the history of how economists came to understand unemployment as a distinct category and how that understanding transformed over time. In the early twentieth century, governments regulated access to unemployment benefits and established labor market protections, drawing sharper boundaries between employment and unemployment. Historians have shown that these boundaries were politically constructed, but economic theory largely treated them as given. Postwar Keynesian models assumed that unemployment was a temporary and measurable condition between spells of stable, high-wage work. However, that assumption rested on a historically specific labor market structure that began to unravel in the 1970s and 1980s. As stable jobs contracted, more workers cycled through precarious employment rather than remaining fully unemployed or finding new stable work. Economic theory responded with new models focused on individual incentives and firm behavior, but these also tended to treat emerging patterns as evidence of how unemployment had always functioned, rather than as signs of a shifting institutional landscape. By tracing how the category of unemployment was constructed and transformed—and how economists responded to those shifts—this article shows how changes in institutional context shape the development of economic thought itself." (Author's abstract, IAB-Doku) ((en))

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Birinci, Serdar, Kurt See & Shu Lin Wee (2025): Job Applications and Labor Market Flows. In: The Review of Economic Studies, Jg. 92, H. 3, S. 1438-1496. DOI:10.1093/restud/rdae064

Abstract

"Job applications have risen over time, yet job-finding rates remain unchanged. Meanwhile, separations have declined. We argue that increased applications raise the probability of a good match rather than the probability of job-finding. Using a search model with multiple applications and costly information, we show that when applications increase, firms invest in identifying good matches, reducing separations. Concurrently, increased congestion and selectivity over which offer to accept temper increases in job-finding rates. Our framework contains testable implications for changes in offers, acceptances, reservation wages, applicants per vacancy, and tenure, objects that enable it to generate the trends in unemployment flows." (Author's abstract, IAB-Doku) ((en))

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Brixy, Udo & Martin Murmann (2025): Hiring opportunities for new firms and the business cycle. In: Small business economics, Jg. 64, H. 3, S. 1387-1413., 2024-06-24. DOI:10.1007/s11187-024-00948-6

Abstract

"Whether firms founded during or outside economic crises have greater growth potential is an important question for both prospective entrepreneurs and policy makers. Existing research offers conflicting answers, and mostly either focuses on aggregate cohort-level effects or selectively excludes small new firms from the analyses. Using extensive linked employer-employee data on young German firms around and during the Global Financial Crisis, a period of sharply reduced access to external capital and recession, we show that young firms respond to cyclical conditions in highly heterogeneous ways. Our firm-level results reveal that the average new firm found it easier to hire its first employees when it was founded during the crisis. These firms achieved countercyclical growth by hiring career entrants. More specifically, hiring in very young (<1.5 years) and small to medium-sized (below the 90th percentile) young firms was countercyclical, while this was not the case for older and larger young firms. Thus, the firm-specific effects for young entrepreneurial firms may be very different from those reported in previous research. Our results suggest that market entry during a crisis may facilitate hiring and that policies that promote entrepreneurship may usefully complement policies that encourage labor hoarding by incumbents during recessions." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))

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Bryson, Alex & Harald Dale-Olsen (2025): Job search under changing labour taxes. In: Labour Economics, Jg. 95. DOI:10.1016/j.labeco.2025.102750

Abstract

"Workers’ job mobility decisions are related to firms’ wage policies but also depend on tax schedules. Using Norwegian population-wide administrative linked employer-employee data for 2010–2019, we study how the job-to-job turnover of employees is affected by marginal taxes and firms’ pay policies, thus drawing inferences on job search behaviour. By paying higher wages, job-to-job separation rates drop, but this negative relationship is weakened when income taxes increase, consistent with higher taxes reducing search activity. However, consistent with theory, the tax effect is smaller where workers receive performance bonuses." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))

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Busch, Anne, Fabienne-Agnes Baumann, Benedikt Krieger, Kerstin Goluchowicz & Sebastian Krusee (2025): Analysepotenziale von OnlineStellenanzeigen und Methoden Maschinellen Lernens am Beispiel der Mindestlohnforschung. Hat der Mindestlohn die Nachfrage von Kompetenzen durch Arbeitgeber verändert? (iit Perspektive / Institut für Innovation und Technik 80), Berlin, 17 S. DOI:10.23776/2025_09

Abstract

"Diese iit-perspektive beleuchtet das Potenzial innovativer Datenzugänge (Online-Stellenanzeigen) und Analysemethoden (Methoden des maschinellen Lernens) für sozialwissenschaftliche Fragestellungen am Beispiel der Mindestlohnforschung. So ist es mit Online-Stellenanzeigen als Datengrundlage beispielsweise möglich zu untersuchen, inwieweit die Einführung bzw. Erhöhung des Mindestlohns die von Arbeitgebern geforderten beruflichen Kompetenzen verändert hat." (Autorenreferat, IAB-Doku)

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Börschlein, Erik-Benjamin (2025): Essays on Wages and Minimum Wages in Frictional Labor Markets. 237 S. DOI:10.5283/epub.76880

Abstract

"In Deutschland ist das Zusammenspiel zwischen Löhnen und institutionellen sowie marktbedingten Friktionen ein zentrales Thema wirtschaftspolitischer Debatten. Diese Dissertation untersucht in drei empirischen Studien kausale Zusammenhänge zwischen Löhnen und Mindestlöhnen, Matchingfriktionen und Arbeitsmarktanspannung. Die Analysen basieren auf umfangreichen administrativen Daten der Bundesagentur für Arbeit und nutzen fortgeschrittene ökonometrische Methoden zur kausalen Inferenz. Die ersten beiden Kapitel betrachten institutionelle Effekte – insbesondere die Einführung des gesetzlichen Mindestlohns im Jahr 2015 – während das dritte Kapitel den Fokus auf veränderte Marktbedingungen legt, insbesondere den zunehmenden Fachkräftemangel. Ziel ist es, die Wirkungsmechanismen zwischen Löhnen und Arbeitsmarktfriktionen differenziert darzustellen. Kapitel 1 Dieses Kapitel entwickelt einen innovativen Machine-Learning-Ansatz zur verbesserten Schätzung langfristiger Lohneffekte des Mindestlohns. Übliche Studien basieren auf einem fixen Pre-Treatment-Indikator („Bite“), basierend auf Löhnen vor der Politikmaßnahme, der die Betroffenheit von der Mindestlohneinführung nur kurzfristig akkurat abbildet. Um langfristige dynamische Veränderungen zu erfassen, werden hier ein zeitvariable Bite-Indikatoren mittels LASSO-basierter Vorhersagemodelle konstruiert, welche die Inzidenz und die Intensität der Mindestlohnbetroffenheit abbilden. Basierend auf administrativen Daten der Jahre 2010–2014 wird die Mindestlohnbetroffenheit für den Zeitraum 2015–2020 vorhergesagt. In der anschließenden Differenz-von-Differenzen-Analyse zeigen sich signifikant positive Lohneffekte, die im Vergleich zu herkömmlichen Methoden jedoch geringer ausfallen und über die Zeit konstant bleiben. Die Ergebnisse deuten darauf hin, dass traditionelle Evaluierungen die Effekte überschätzen könnten, da sie dynamische Selektionseffekte und mindestlohnunabhängige Lohnentwicklungen nicht ausreichend berücksichtigen. Kapitel 2 In diesem Kapitel wird untersucht, wie sich die Einführung des Mindestlohns auf offene Stellen und damit verbundene Friktionen im Matching-Prozess ausgewirkt hat. Die Analyse basiert auf administrativen Vakanzdaten und Erwerbsbiographien. Die Analyse erfolgt auf der Berufsebenen für den Zeitraum 2013–2019 und nutzt ein Differenz-von-Differenzen-Design. Die Ergebnisse zeigen, dass die Anzahl neu gemeldeter Stellen durch die Mindestlohneinführung insgesamt nicht zurückging. Jedoch stieg der Anteil stornierter Vakanzen um 4–9 Prozent, und die Dauer erfolgreicher Besetzungsprozesse erhöhte sich um 5–6 Prozent. Dies deutet auf verstärkte Such- und Matchingfriktionen hin, etwa durch höhere Einstellungsstandards oder reduzierte berufliche Mobilität. Ergänzende Analysen zeigen geringere Übergänge zwischen Arbeitgebern, insbesondere bei Berufswechseln. Somit wird deutlich, dass die Mindestlohneinführung zwar nur geringe Auswirkungen auf die Beschäftigung hatte, aber dennoch Matchingprozesse erheblich beeinflusst hat. Kapitel 3 Dieses Kapitel wechselt die Perspektive und untersucht, wie zunehmende Arbeitsmarktanspannung – gemessen als Verhältnis von offenen Stellen zu Arbeitssuchenden – die Lohnentwicklung beeinflusst hat. Mithilfe eines Leave-One-Out-Instruments wird der kausale Effekt lokaler Arbeitsmarktanspannung in beruflichen Arbeitsmärkten auf Löhne geschätzt. Die Ergebnisse zeigen moderate, aber signifikant positive Lohneffekte, die etwa 7–19 Prozent des realen Lohnwachstums in Deutschland zwischen 2012 und 2022 erklären. Besonders stark profitieren neu Eingestellte, Hochqualifizierte, Beschäftigte im Dienstleistungssektor und Arbeitnehmer in Ostdeutschland. Zudem steigt der Lohn in Niedriglohnunternehmen überdurchschnittlich stark, was auf eine Verringerung der Lohnungleichheit hindeutet. Im Gesamtfazit werden die Erkenntnisse der drei Studien zusammengeführt. Die Arbeit zeigt, wie institutionelle Eingriffe wie der Mindestlohn einerseits Löhne anheben, gleichzeitig aber neue Friktionen erzeugen können. Andererseits können veränderte Marktbedingungen auch ohne staatliche Eingriffe Löhne steigern – wie etwa bei hoher Arbeitsmarktanspannung. Methodisch hebt die Dissertation die Bedeutung administrativer Mikrodaten und robuster kausaler Analyseverfahren in der Arbeitsmarktforschung hervor." (Autorenreferat, IAB-Doku)

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Cai, Xiaoming, Pieter Gautier & Ronald Wolthoff (2025): Search, Screening, and Sorting. In: American Economic Journal. Macroeconomics, Jg. 17, H. 3, S. 205-236. DOI:10.1257/mac.20240026

Abstract

"We examine how search frictions impact labor market sorting by constructing a model consistent with evidence that employers interview a subset of a pool of applicants. We derive necessary and sufficient conditions for sorting in applications and matches. Positive sorting is obtained when production complementarities outweigh a counterforce measured by a (novel) quality-quantity elasticity. Interestingly, the threshold for the complementarities depends on the fraction of high-type workers and can be increasing in the number of interviews. Our model shows how policies like Ban the Box can backfire because when screening workers becomes harder, firms may discourage certain workers from applying." (Author's abstract, IAB-Doku) ((en))

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Caldwell, Sydnee, Ingrid Haegele & Jörg Heining (2025): Firm Pay and Worker Search. (IAB-Discussion Paper 04/2025), Nürnberg, 141 S. DOI:10.48720/IAB.DP.2504

Abstract

"Ob und wie Arbeitnehmer am Arbeitsplatz suchen, hängt von ihren Vorstellungen über die Bezahlung und die Arbeitsbedingungen in anderen Unternehmen ab. Dennoch ist wenig darüber bekannt, wie viel Arbeitnehmer tatsächlich über die Arbeitsentgelte außerhalb ihrer aktuellen Beschäftigung Bescheid wissen. Wir nutzen eine groß angelegte Umfrage unter deutschen Vollzeitbeschäftigten, welche mit Sozialversicherungsdaten verknüpft wurde, um Gehaltserwartungen und Präferenzen gegenüber bestimmten externen Unternehmen zu ermitteln. Arbeitnehmer glauben, dass sie mit erheblicher Heterogenität hinsichtlich der Vergütung bei anderen Unternehmen konfrontiert sind und richten ihre Suche nach einem neuen Arbeitsplatz auf Unternehmen aus, von denen sie ausgehen, dass diese mehr bezahlen. Die von den Arbeitnehmern erwarteten unternehmensspezifischen Lohnaufschläge korrelieren sowohl stark mit den Vergütungsschemata, die sich anhand von administrativen Daten zeigen, als auch mit der Würdigung von firmenspezifischer Annehmlichkeiten. Die meisten Arbeiter sind auch bei einer erheblichen Erhöhung des Gehalts nicht bereit, sich einen neuen Job zu suchen – oder ihr derzeitiges Unternehmen zu verlassen. Die Kosten eines Jobwechsel betragen zwischen 7 und 18 Prozent des Jahreslohns eines Arbeitnehmers. Die Zugehörigkeit zu einem Arbeitgeber variiert je nach Arbeitgeber und kann nicht anhand von Unterschieden in firmenspezifischen Annehmlichkeiten oder den Kosten des Jobwechsels erklärt werden." (Autorenreferat, IAB-Doku)

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Carlini, Giacomo (2025): Essays in Macroeconomics and Labor Economics. 147 S.

Abstract

"The first chapter investigates why assortative matching between workers and firms is stronger in large cities than in small cities. I develop a search and matching model with heterogeneous workers and firms to examine how worker composition and labor market frictions affect sorting. Calibrating the model to German employer-employee data, I find that matching efficiency is key to explaining differences in assortative matching across cities. This effect is amplified by a more dispersed worker productivity dispersion. The model shows that around 5% of the GDP gap between large and small cities is attributable to differences in assortative matching, underscoring the role of local labor market frictions and productivity distributions in spatial inequality. The second chapter explores how task-biased technological adoption affects GDP gaps across countries. We introduce a country-specific measure of task intensity and document that as GDP increases, routine work declines while cognitive work rises. Moreover, differences in task content within occupations explain over half of the cross-country differences in routine work. Using a production framework where technology is task-specific and occupations are aggregates of tasks, we estimate task-specific productivities across countries. A counterfactual exercise suggests that reducing dispersion in task-biased technology adoption could shrink the average GDP gap with the United States by 25%. The third chapter examines sectoral labor productivity growth in the U.S. over 50 years, highlighting routine- and skill-biased technical change. I show that routine labor productivity has grown fastest, with skill-biased technical change benefiting skilled workers while unskilled productivity declined, especially in services. Finally, to disentangle the role of different labor-augmenting technological change, I extend the framework to account for heterogeneity in both occupations and skills." (Author's abstract, IAB-Doku) ((en))