Multigenerational Caregiving and Its Effect on Human Capital: Insights from a Human Resource Development Perspective

Abstract

A multigenerational caregiving crisis is emerging at the interface of family and work, and human resource development (HRD) should pay attention. This perspective considers the impact of multigenerational caregiving-induced responsibilities on human capital frameworks, and their implications for HRD. We believe traditional models often neglect the unique challenges multigenerational caregivers face—such as stress, absenteeism, and constrained opportunities for self-development—which contribute to the erosion of human capital. This paper uses quantitative models to show that multigenerational caregiving is a critical driver of human capital depreciation. Integrating multigenerational caregivers into human capital discourse foregrounds the need for adaptive HRD strategies. These strategies should prioritize both human capital sustainability and workforce well-being, empowering organizations to support multigenerational caregivers and build a more inclusive, resilient workforce.

Keywords

multigenerational caregiving human capital depreciation elder care work-life balance sandwich generation

There are only four kinds of people in the world. Those who have been caregivers. Those who are currently caregivers. Those who will be caregivers, and those who will need a caregiver.—Rosalyn Carter

The recent observance of National Caregivers Day (February 21, 2025), offered a timely opportunity to recognize the vital contributions caregivers make to families, communities, and society at large. Of particular importance are multigenerational caregivers (MGCs; Patterson & Margolis, 2019)—individuals who provide care across generational boundaries, such as for young children and aging parents. Often referred to as the “sandwich generation” (Miller, 1981, p. 419), these caregivers face competing role demands that can radically disorder their professional and personal lives (Griggs et al., 2020; Pashazade et al., 2024).

While precise estimates vary, recent data suggest that 18%–23% of Americans are considered MGCs, caring for both elderly family members and children under 18 (Burke, 2017; Pew Research Center, 2022). This growing demographic provokes the need for recognition to move beyond acknowledgment and critically address a pressing yet underexplored issue in human resource development (HRD): the impact of multigenerational caregiving (MGC) on human capital.

This paper presents a perspective on reevaluating human capital frameworks to address the competing demands of MGCs. We advance the central proposition that MGC constitutes a significant yet underrecognized source of human capital depreciation in contemporary labor markets. The intensity and duration of MGC duties impose psychosocial and temporal constraints that clearly impact capacity for professional development, health maintenance, and continuous skill acquisition (Bauer & Sousa-Poza, 2015). These constraints generate opportunity costs—such as reduced participation, absenteeism, and limited reskilling—that are rarely captured in traditional models of human capital. By extending human capital theory to account for MGC-induced depreciation factors, we offer an economic lens that links MGC burdens to macro-level workforce outcomes. This reframing foregrounds the need for HRD to adopt adaptive strategies that prioritize human capital sustainability and workforce well-being by addressing the fundamental pressures experienced by MGC employees. To anchor our perspective, we begin by revisiting the foundational concept of human capital and identifying its theoretical limitations in accounting for the caregiving realities faced by MGCs.

Human Capital

The concept of human capital, first introduced by Becker (1964 [2009]), provides an economic concept for the productive attributes of individuals—such as education, technical expertise, and workplace-relevant skills—that underpin productivity within industrial-capitalist societies. Although this model has traditionally served as a basis for understanding workforce dynamics, its limitations are becoming increasingly evident in the context of shifting societal structures, often referred to as “late modernity” (Côté, 2005, p. 224). For instance, though human capital models effectively describe the economic utility of workplace skills, their scope becomes limited when addressing the broader socio-economic challenges associated with caregiving.

Recent scholarship has offered important insights into the challenges MGCs face within the labor force. For example, elder caregiving has been shown to directly impact labor force participation, with caregivers often reducing work hours or withdrawing from the labor market entirely due to caregiving responsibilities (Lilly et al., 2007; Moussa, 2019). These effects are further nuanced by caregiving intensity, which disproportionately affect blue-collar workers who experience physical demands and limited flexibility, compared to white-collar workers, who struggle with balancing work-life integration (Cheng et al., 2020). And the implications extend beyond workforce participation, touching on caregivers’ psychological and physical health. Studies have documented the significant stress and health challenges associated with caregiving, which directly influence productivity and career longevity (Bauer & Sousa-Poza, 2015). Moreover, while organizational support mechanisms, such as supervisor encouragement and diversity management, have been identified as critical enablers of work-family policy utilization (Kim & Mullins, 2016), many organizations lack comprehensive policies to address caregiving needs (Matuszek & Bandow, 2016).

While these studies highlight the potential impact of MGCs on organizational outcomes, they do not explicitly address the need to reevaluate human capital frameworks to integrate caregiving demands as a central element of HRD. Pressures are faced by MGCs that extend beyond measurable workplace skills, imposing opportunity costs that are rarely accounted for in conventional frameworks. For example, the straightforward equation for quantifying the invisible overtime burden ( $O T$ ) associated with caregiving (Lerner, 2022) provides a simple perspective. $O T$ can be calculated as follows:

O T = T_{c} \cdot w_{h}

(1)

Where:

$T_{c}$ : time spent caregiving.

$w_{h}$ : equivalent hourly wage.

This equation considers that MGCs face heightened opportunity costs due to this unpaid caregiving labor, which directly limits their ability to invest in professional growth and exacerbates human capital depreciation. Expanding human capital models to reflect the nuanced realities of MGCs is critical to advancing HRD scholarship and practice, ensuring both the sustainability of organizations and the well-being of their workforce.

While this overview outlines MGC-related pressures on workforce participation, a more detailed perspective requires modeling how these pressures quantitatively affect human capital depreciation. In the next section, we extend this logic by embedding caregiving variables into established human capital and production models.

Integrating Multigenerational Caregiving into Human Capital Depreciation Models

Côté (2005) proposed narrowing human capital to workplace-specific skills, while introducing “identity capital” to capture broader identity-negotiation tasks like personal values, affiliations, and life planning—especially relevant in late modernity. Caregiving-induced responsibilities often intersect with these identity tasks, creating a complex dynamic that disrupts the balance between occupational and personal development. This interplay stresses the importance of modeling human capital depreciation as a function of caregiving duration and the intensity of caregiving demands.

The relationship between MGC and human capital investment further complicates the dynamics between such investments and their returns. While education, training, and health improvements traditionally enhance human capital, caregiving introduces depreciation factors—such as stress, absenteeism, and reduced opportunities for self-development—that diminish these gains. This heightened depreciation not only reduces the projected human capital but also impacts the return on human capital investment (R) by increasing opportunity costs (C) associated with caregiving. The dual burden of caregiving and professional responsibilities creates a compounded challenge, affecting both immediate productivity and the longer-term value derived from human capital investments. This relationship can be quantitatively represented as follows:

R = \frac{(w_{2} - w_{1})}{w_{1}} - \frac{C}{w_{1}}

(2)

Where:

$R$ : return on capital investment.

$w_{2}$ : wage with investment.

w₁: wage without investment.

$C$ opportunity cost of caregiving time.

Caregiving-induced responsibilities increase challenges by limiting opportunities for further education, training, or self-care, thereby reducing resources. These compounded challenges hinder personal and professional growth. And they also directly influence productivity. The burden of MGC introduces depreciation factors into the human capital equation, potentially accelerating the erosion of skills and capacity over time, and can be represented mathematically as follows:

H C_{t + 1} = H C_{t} + Δ E_{t} + Δ H_{t} - D_{t}

(3)

Where:

$H C_{t}$ human capital at time t.

$∆ E_{t} :$ incremental gains from education and training.

$∆ H_{t} :$ incremental gains from health improvements.

$D_{t} :$ depreciation due to intensity of caregiving (stress, absenteeism, and limited time for self-development exacerbated for MGC).

Caregiving-induced responsibilities lead to a higher D_t, reducing HCt+1 and contributes to human capital depreciation. This phenomenon extends beyond individual productivity, influencing productivity spillovers that shape organizational performance (Carpenter, 2020). As MGCs navigate their dual roles, their diminished capacity indirectly affects workplace outcomes, necessitating an examination of these dynamics through an aggregate production function:

Q = A \cdot F (K, H C, L)

(4)

Where:

Q: output.

A: technology level.

K: physical capital.

HC: human capital.

L: labor.

F: Represents the production function, which combines the inputs K, HC, and $L$ in a specific mathematical way to produce the output Q. The exact form of F depends on the assumptions or model being used. For example, F might take a linear form, a multiplicative form with diminishing returns, or another structure that defines how the inputs combine to produce output.

So, in the context of MCG on human capital, the production function F (K, HC, L) serves as a conceptual “black box,” encapsulating how physical capital (K), human capital (HC), and labor ( $L$ ) interact to determine organizational output (Q). These dynamics are uniquely shaped by the dual burden MGCs carry, which limits both the availability and effectiveness of their human capital. Different formulations of the production function (F) reflect varying assumptions about how MGC impacts these inputs, offering diverse perspectives on productivity. And these variations can provide valuable insights into the interplay between caregiving, human capital, and organizational performance, as illustrated in the various models below. Note: In the following models, the output variable (Q) is implied rather than explicitly stated in each equation. Readers should interpret each formulation as a specific instantiation of the production function (F), which still yields organizational output $(Q)$ .

Linear Model

F (K, H C, L) = a K + b H C + c L

(5)

In this model, the contribution of each input is additive and independent, suggesting that physical capital ( $K$ ), human capital (HC), and labor ( $L$ ) individually contribute to organizational output (Q) without direct interaction effects. For MGCs, caregiving imposes distinct constraints that diminish both the availability and effectiveness of their human capital. The coefficients a, b, and c represent the respective weights or marginal productivity of each input, indicating their proportional contributions to the overall output. As a result, the weight assigned to HC may be lower, reflecting the diminished capacity of MGCs to fully engage in workplace activities. This reduction can be attributed to stress, absenteeism, and limited opportunities for skill development, which act as depreciation factors for human capital.

Interaction Model

F (K, H C, L) = a K + b H C + c L + d (K \cdot H C)

(6)

In the interaction model, the contribution of each input (K, HC, and $L$ ) is primarily additive, but it also includes an interaction term $d (K \cdot H C)$ to account for the synergistic effects between physical capital ( $K$ ) and human capital (HC). This interaction reflects the idea that the productivity of physical capital is enhanced when paired with well-functioning human capital. However, caregiving-induced responsibilities can lower the weight of HC due to reduced availability and productivity caused by externalities that constrain opportunities for skill development. The inclusion of the interaction term highlights the compounding impact of MGC on organizational performance. When HC declines, its synergy with physical capital (K) weakens, further reducing overall productivity (Q).

Cobb–Douglas Production Model

F (K, H C, L) = K^{α} H C^{β} L^{γ}

(7)

In the Cobb–Douglas production model, the inputs of physical capital ( $K$ ), human capital ( $H C$ ), and labor ( $L$ ) contribute to organizational output (Q) with diminishing returns, as reflected in the exponents α, β, and γ, respectively. These exponents indicate the elasticity of each input, measuring its proportional contribution to output. Caregiving-induced responsibilities often lead to a depreciation of human capital, manifested in reduced availability, productivity, and prospects for skill enhancement. This depreciation may lower the value of β, reflecting the diminished impact of $H C$ on organizational output.

Threshold Model

F (K, H C, L) = if H C > H C_{m i n,} then; a K + b H C + c L, else 0

(8)

In the Threshold Model, the production function $F (K, H C, L)$ assumes that organizational output ( $Q$ ) only occurs when human capital (HC) exceeds a critical minimum threshold ( $H C_{m i n}$ ). This reflects the premise that certain levels of human capital are indispensable for initiating and sustaining productive activities, as insufficient HC renders the other inputs (K and L) ineffective. For organizations with many MGCs, caregiving demands can drop $H C$ below $H C_{m i n}$ , resulting in reduced productivity—or even halting output entirely.

Dynamic Model

F (K, H C, L, t) = K_{t}^{α} H C_{t}^{β} L_{t}^{γ}

(9)

In the Dynamic Model, the production function $F (K, H C, L, t)$ incorporates a time dimension, recognizing that the inputs of physical capital (K), human capital (HC), and labor (L) evolve over time (t). This formulation accounts for changes in productivity influenced by time-dependent factors such as technological advancements, skill development, and depreciation. Human capital ( $H C_{t}$ ) in particular evolves as a function of education, health improvements, and the depreciation factors that diminish its value. Caregiving-induced responsibilities routinely amplify depreciation ( $D_{t}$ ), leading to a gradual erosion of $H C_{t}$ unless offset by incremental gains from targeted interventions. The time-dependent nature of this model highlights how prolonged MGC can have cumulative negative effects, further constraining organizational productivity.

Policy-Sensitive Model

F (K, H C, L) = a K + b (H C + P) + c L

(10)

In the Policy-Sensitive Model, the production function $F (K, H C, L)$ incorporates an additional policy factor (P) to account for organizational or governmental support mechanisms. The inclusion of $P$ modifies the contribution of human capital ( $H C$ ) to organizational output ( $Q$ ) by enhancing its effectiveness. Policies such as flexible work arrangements, subsidized caregiving, mental health resources, and professional development opportunities directly mitigate the constraints faced by MGCs, thereby boosting $H C$ .

Collectively, these models illustrate how MGC-induced responsibilities can act as depreciation forces that erode individual capacity and organizational productivity. These insights form the basis for practical implications in HRD. Strategic interventions have the potential to preserve human capital (Park et al., 2021) by mitigating the long-term effects of MGC-induced capital loss.

Brief Implications for HRD

Including MGC factors in human capital models uncovers vital yet often overlooked implications for HRD. Especially when considering the compounded losses experienced by both employees striving to balance care and career, and organizations struggling to retain and support them. Traditional skill-based frameworks overlook the competing demands of MGCs, highlighting the need for a broader view of human capital depreciation. MGC-induced factors—such as mental strain, absenteeism, and reduced opportunities for self-development directly impact individual productivity. They also alter how human capital interacts with physical capital and labor, thereby affecting broader organizational outcomes. Quantitative models like Cobb–Douglas and Threshold frameworks highlight how MGC can reduce the elasticity or availability of human capital. In contrast, policy-sensitive and dynamic models emphasize the importance of targeted interventions in mitigating these effects.

It is critical for HRD to incorporate strategies to address the challenges. These strategies help preserve human capital while strengthening commitment, reducing turnover, and fostering a more inclusive, supportive workplace culture. Table 1 presents targeted HRD strategies—like flexible scheduling, caregiver-aware leadership, and tailored upskilling—that address MGC constraints and offer practical approaches to reduce human capital loss while boosting retention, engagement, and productivity.

Table 1.

HRD Strategies to Mitigate Human Capital Depreciation Among Multigenerational Caregivers.

HRD strategy	Description	Intended outcome
Flexible work arrangements	Compressed workweeks, remote/hybrid options, and adaptive scheduling tailored to caregiver needs	Enhances time autonomy, reduces absenteeism, and improves engagement
Caregiver-focused leadership training	Empathy-building, individualized goal-setting, and inclusive evaluation practices	Increases managerial support, improves retention, and fosters inclusive culture
Targeted upskilling opportunities	Microlearning, asynchronous modules, or subsidized training tailored for limited availability	Preserves skill development, supports career progression, and sustains productivity
Caregiving resource navigation	Internal caregiver support portals, peer networks, or access to external caregiving services	Reduces cognitive load, facilitates access to support, and enhances well-being
Leave policy enhancements	Paid or protected caregiving leave beyond federal mandates	Prevents burnout, reduces turnover, and signals organizational commitment to equity

Integrating MGC realities into human capital models is not only strategic—it is a step toward equity. Women, who disproportionately shoulder caregiving roles, often face systemic barriers that quietly stall their careers (Patterson & Margolis, 2019). When HRD practices align with MGC realities, organizations foster inclusion, strengthen retention, and elevate engagement. This alignment enables HRD to address the evolving challenges of MGCs while sustaining organizational vitality amid changing workforce and demographic trends.

Conclusion

This perspective emphasizes the need to reimagine human capital frameworks to account for the unique and complex challenges faced by MGCs. Incorporating MGC into HRD discourse calls for a shift toward human capital models that enable organizations to better support caregivers and build a more inclusive, resilient workforce. To advance this agenda, HRD should embed MGC priorities into leadership training, performance evaluations, and workforce development planning. And organizations are encouraged to audit existing policies—such as leave structures, flexible work options, and training access—for their responsiveness to caregiving demands. Future research should explore the longitudinal effects of MGC on skill depreciation and career progression, as well as the impact of targeted interventions. HRD has the power to redefine the workplace by ensuring that those who care for others across generations are no longer invisible—but are seen, supported, and empowered to thrive.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Rob E. Carpenter

Author Biographies

Rob E. Carpenter holds a PhD in Human Resource Development from the University of Texas at Tyler where he currently serves as Executive in Residence. His professional concentration is in the healthcare sector while his academic pursuits include teaching and conducting interdisciplinary research in both the physical and social sciences.

Brandy Dial is a PhD student in Human Resource Development at the University of Texas at Tyler. With a master’s in industrial and organizational psychology from the University of West Florida, she has extensive experience in organizational management and psychology. Her research interests focus on the impact of multigenerational caregiving on workplace dynamics, particularly its psychosocial implications for self and others.

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