Human capital space: a spatial perspective of the dynamics of people and economic relationships

The paper addresses how people grow by using space and how spatial development should be structured around human development rather than solely economic production. It notes a deficit in spatial investments directly serving human development (e.g., schools, healthcare) and argues that human capital (HC)—encompassing education, skills, health, experience, and mobility—is both a driver and outcome of spatial development. Against backdrops of demographic change (ageing, shrinking cities) and knowledge-based economies, the study asks why some places accumulate more HC, how places can attract, cultivate, and retain HC, and how space reciprocally shapes people–economy relations (PERs). The purpose is to extend HC into a spatial discourse by introducing the concept of human capital space (HCS) to analyse the spatial representations, mechanisms, and policy implications of PERs.

The article synthesizes strands from population geography (distribution/mobility focusing on quantities), labour geography (workers’ agency and employment contexts), and economic geography (knowledge economy, creative class, amenities, clustering) to argue HC better integrates qualitative human attributes with spatial economic dynamics. Prior work has emphasized talent attraction, creative classes, amenities, clustering, and knowledge spillovers, but has paid less attention to the spatial formation and heterogeneity of HC itself and the spaces that cultivate, employ, and refresh it. Measures of HC commonly use educational attainment or the Jorgenson–Fraumeni lifetime income approach; both have limitations for geographical application. The literature also documents amenity-driven migration, university–industry relations, studentification, and housing market effects near good schools, but lacks a unifying spatial framework linking investment in human development to spatial outcomes. This synthesis motivates the HCS framework to capture spatial externalities, selection–sorting–matching mechanisms, and endogenous drivers of development.

Conceptual and theoretical framework development. The study does not collect or analyse empirical datasets; rather, it constructs the concept of Human Capital Space (HCS) through synthesis of multidisciplinary literature and deductive reasoning. It develops: (1) a typology of HCS—HC employment space (HCES), HC cultivation space (HCCS), and HC refreshing space (HCRS)—mapped to physical entities (firms/industry districts; schools/universities; amenities/healthcare); (2) mechanisms linking people and space via reciprocity of investment and rewards across the human lifecycle; (3) spatial externalities and endogenous growth pathways; (4) a selection–sorting–matching framework explaining spatial heterogeneity of HC; and (5) implications for dynamic capabilities and spatial investment strategies. The approach is normative–analytical, drawing illustrative empirical references from prior studies.

- Introduces Human Capital Space (HCS) as a spatial framework to analyse people–economy relationships (PERs), positing reciprocal investment–reward dynamics between people and space that operate across education, work, consumption, and health. - Defines three interlinked HCS types: (1) HCES—spaces where HC is utilised and augmented through work and on-the-job learning (e.g., industry clusters, business districts); (2) HCCS—spaces cultivating HC (schools, universities, research institutes), with impacts such as jiaoyufication and studentification; (3) HCRS—spaces meeting social and health needs (amenities, recreation, neighbourhood quality, healthcare) that attract and retain HC. - Articulates spatial externalities: HCS shapes place identity and quality-of-place; generates housing and land premiums near jobs and schools; produces positive wage externalities through local skill concentrations; scales local effects to city/regional attraction; and risks reinforcing spatial inequalities, necessitating inclusive growth considerations. - Positions HC as an endogenous driver of spatial development, vital to innovation, productivity, and technology adoption; its accumulation underpins regional competitiveness and transitions to knowledge-based economies. - Proposes a selection–sorting–matching mechanism: individuals self-select into places based on HC and opportunities; spatial sorting by skills follows due to costs, opportunities, and institutions; thicker labour markets enhance matching efficiency between skills and firms, reinforcing agglomeration. - Links HC to regional dynamic capabilities: higher HC enhances places’ abilities to integrate, reconfigure, and leverage resources under changing conditions, attracting external capital and opportunities. - Highlights investment implications: calls for “patient capital” in education and healthcare, intergenerational financing, and coordinated spatial investments across HCES, HCCS, and HCRS to build endogenous growth capacity. - Illustrative data points: in 2019, the global population over 65 exceeded under-5s for the first time; in Beijing, the share of Peking and Tsinghua graduates staying fell from 72%/31% (2013) to 16%/18% (2019); microgeographic knowledge spillovers can operate at 50–250 m scales in Berlin; high housing premiums cluster in large cities due to proximity to HC-related spaces.

By reframing HC as inherently spatial, the HCS concept addresses why and how some places accumulate and retain human capital while others lose it. It integrates population, labour, and economic geographies, moving beyond debates like “do jobs follow people or people follow jobs” by emphasising the design of spaces for cultivation, employment, and refreshing of HC across the life course. The typology clarifies how education, work-based learning, amenities, and healthcare jointly shape migration, agglomeration, and urban form. Recognizing spatial externalities and matching dynamics explains observed wage and housing patterns, city branding, and regional disparities, and situates HC as an endogenous force in urban/regional competitiveness and resilience. The framework suggests policy should balance attraction with cultivation and retention, connect HCES–HCCS–HCRS strategically, and focus on inclusive access to mitigate inequality reinforced by HC agglomeration.

The paper contributes a people-centred spatial framework—Human Capital Space (HCS)—that bridges population, labour, and economic geographies and guides human-oriented spatial development. It (1) conceptualises a typology of HC spaces (HCES, HCCS, HCRS) and their synergies; (2) explicates spatial externalities and the selection–sorting–matching mechanism as drivers of HC heterogeneity; (3) positions HC as an endogenous source of dynamic capabilities for places; and (4) argues for deliberate, long-term investment in education, healthcare, and amenities to build sustainable spatial development capacity. Future research directions include operationalising HCS measurement at multiple scales, integrating non-educational HC dimensions (e.g., health), examining contextual variations (economic stage, social/cultural factors), expanding network/accessibility analyses of HCS, and exploring interactions between HC and other capital forms while addressing equity and inclusion.

- Data and measurement: Lack of systematic, multi-scalar data on HC and HCS; overreliance on education proxies; Jorgenson–Fraumeni methods demand micro + macro data and are hard to scale; skills-adjusted HC indicates bias when using education alone. - Concept scope and context: HCS types and their relative importance are context-dependent (economic stage, social environment, presence/absence of universities); HCS evolves with societal change and is not exhaustive. - Integration with other capitals: Need to analyse interplay between HC and social, natural, and physical capital and extend analyses to broader physical spaces (e.g., employment areas, networks, accessibility). - Inequality and inclusivity: HC agglomeration can exacerbate spatial inequality and segregation; requires ‘patient’ investment and inclusive policies; spatial matching is imperfect and investment is costly.