The Macroeconomics of Managers

Projektinformationen

MACROMGR

ID Finanzhilfevereinbarung: 101097789

DOI

10.3030/101097789

EK-Unterschriftsdatum 27 Oktober 2023

Startdatum 1 November 2023

Enddatum 31 Oktober 2028

Finanziert unter

• European Research Council (ERC)

Gesamtkosten

€ 1 782 794,00

EU-Beitrag

€ 1 782 794,00

Koordiniert durch

CEU GMBH
Austria

Periodic Reporting for period 1 - MACROMGR (The Macroeconomics of Managers)

Berichtszeitraum: 2023-11-01 bis 2026-04-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Management practices matter for firm performance, and trainings can improve these practices with lasting effects. CEOs matter for firm performance, as shown by studies of CEO mobility and characteristics. Yet the two literatures on what managers do versus who they are have remained largely separate. Understanding the availability, elasticity of supply, and allocation of manager skills is crucial for development accounting and explaining productivity differences across countries.

The MACROMGR project introduces manager skills into development accounting with a macroeconomic approach. Manager skills enter the production function as an input, potentially complementary with firm productivity. The project studies three core questions: (1) How transferable is manager knowledge between firms? (2) How elastic is the supply of good managers over time? (3) How efficient is the allocation of managers to firms within and across countries?

The project's expected impact includes uncovering aggregate productivity losses from manager misallocation across firms, space, and time; understanding how management can be improved in the aggregate and quantifying potential spillovers from business training; explaining why countries not at the technological frontier are slow to catch up; and quantifying benefits of high-skilled migration through better cross-border allocation of managerial talent. Results can inform better targeting of management interventions and training programs.

The quantitative analysis relies on newly collected longitudinal data on the universe of firms and top managers in Germany (1991-2021) and Hungary (1980-2021), creating a completely novel dataset that follows managers for several decades as they move across firms and between two tightly integrated countries.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

During the reporting period (November 2023 - October 2025), the project made substantial progress across all research objectives.

# Data Infrastructure Development

Acquired and integrated the German manager and firm database (December 2023) to complement the Hungarian Manager Database. Established restricted data access at the Hungarian Statistical Office for VAT, trade, and innovation data. Linked multiple Hungarian administrative datasets spanning 30+ years. Processed historical "Who's Who" almanac data using large language models for historical elite analysis. Developed project website (macromanagers.eu) with comprehensive metadata repository.

# Novel Methodologies

Developed new approaches to estimate CEO fixed effects in production functions for privately held businesses, adapting Abowd-Kramarz-Margolis methods to sparse mobility networks. Implemented LLM-based approach for manager nationality classification from names, replacing originally proposed name embedding methods. Applied successfully to Hungarian manager database; German database classification in progress.

# Research Studies Completed or Advanced

- "Managers, Entrepreneurs, and the Allocation of Talent: Evidence from Hungary's Transition" (with Krisztina Orban) - presented at major international workshops and conferences
- "Expatriate CEOs and Firm Performance: The Role of General Skills, Investment and Exporting Ability" (with Almos Telegdy) - major revision completed with new theoretical model, undergoing peer review
- "Estimating the Value of CEOs in Privately Held Businesses" - novel methodology for sparse networks
- "Broken Ladders: AI, Teamwork and the Dynamics of Skill Formation" (with Zsófia Bárány) - new paper on organizational learning
- "Managerial Talent Selection and Institutions" (with Amanda De Pirro and Mihaly Laki) - historical elite analysis using "Who's Who" data

# Tools and Software Development

Created research data analysis tools using Julia and Python, presented at JuliaCon 2024 and RSE Conference Warwick 2025.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The project has advanced beyond the state of the art in three key areas:

# Methodological Innovation

Adapted CEO valuation methods to contexts with sparse mobility networks, addressing fundamental challenges in measuring managerial contribution in privately held firms. This is the first application of worker fixed effects methods to the universe of managers in privately held businesses, where traditional methods fail due to limited CEO mobility.

# Data Integration at Unprecedented Scale

Successfully linked 30+ years of administrative data across multiple restricted sources, creating novel research infrastructure for studying manager-firm dynamics.

# AI-Enhanced Research Methods

Pioneered use of large language models for historical data processing, including nationality classification and almanac processing, significantly improving on originally proposed embedding approaches. This methodology can be applied to other contexts requiring entity classification from sparse text data.