KDI - Korea Development Institute - RESEARCH - Research Areas

Summary

Policy Study KOR A Study on Structural Changes in the Unemployment Rate

This study examines the recent divergence between unemployment rates and labor market conditions in South Korea from the perspective of changes in matching efficiency.

Prior to the COVID-19 pandemic, the unemployment rate in South Korea remained in the mid-to-high 3 percent range, before rising above 4 percent during the pandemic. It then declined sharply and, as of 2025, has stayed in the mid-to-high 2 percent range, a level significantly lower than its pre-pandemic level. These movements in the unemployment rate cannot be explained simply by changes in labor demand. The unemployment rate continued to decline even during periods when growth in labor demand stagnated, and it remained low even after labor demand began to decline.

These movements in labor market indicators suggest an improvement in matching efficiency. This study examines this possibility using actual data and analyzes the determinants of changes in matching efficiency.

This study first estimates a labor market matching function that incorporates heterogeneity in industries and job seekers’ characteristics. Incorporating multiple dimensions of heterogeneity allows us to examine how changes in the composition of the job seeker pool and cross-industry differences in labor market tightness affect changes in matching efficiency. Based on the estimated matching function, the matching efficiency of the South Korean labor market is found to have increased by approximately 14 percent over the analysis period (2015-2025). A substantial portion of this improvement is trend growth driven by advances in matching technology and the expansion of job intermediation services. However, even after accounting for this trend growth, matching efficiency is estimated to have increased by about 5 percent over the same period, largely due to the effects of demographic changes.

To examine this more closely, this study decomposes changes in matching efficiency - after accounting for trend improvements driven by factors such as technological progress - into job seeker characteristic composition effects, job seeker distribution composition effects, and a variance effect. The results indicate that improvements in matching efficiency during the 2015-2020 period were driven primarily by the job seeker distribution composition effect. As population aging increased the share of older job seekers and reduced the share of younger job seekers, job-search activity became increasingly concentrated in relatively efficient industries such as construction, while declining in less efficient sectors such as retail, accommodation, and food services. This reallocation of job-search activity contributed to an improvement in aggregate matching efficiency in the labor market.

After 2020, a reduction in cross-industry disparities in labor market tightness contributed to improvements in aggregate matching efficiency(variance effect). As the number of younger job seekers declined, relatively slack sectors such as retail, accommodation, and food services became tighter. In contrast, relatively tight sectors such as health and social services became slacker as the number of older female job seekers increased.

Improvements in matching efficiency are estimated to have reduced the structural unemployment rate in South Korea by approximately 0.5 percentage points, and to account for about 60 percent of the decline in the unemployment rate since 2015. These findings suggest that recent low unemployment rate is more likely to reflect structural changes rather than a temporary cyclical phenomenon. Accordingly, unemployment is likely to remain at levels substantially below its historical average going forward. Therefore, when assessing labor market conditions based on unemployment indicators, it is important to distinguish between structural and cyclical factors.

Summary

Research Monograph KOR Structural Changes in Korea’s Retail Markets and Their Economic Impacts

This report examines structural changes in Korea’s retail markets and their economic impacts, focusing on the interactions among market structure, regulatory policy, and demand-side transformation. Rapid growth in online retail channels, adjustments to offline retail regulations, and long-term demographic shifts have jointly reshaped retail market outcomes in ways that differ across regions and retail formats. The study aims to provide an integrated empirical assessment of these changes and to clarify the mechanisms through which they affect retail performance.

The analysis draws on large-scale administrative and transaction-level data, including nationwide credit card transaction panels at the sub-district level, online platform payment information, detailed records on local regulatory changes, and official population statistics. A combination of panel regression models and quasi-experimental designs is employed to identify the effects of online retail expansion, regulatory adjustment, and demographic change on offline retail sales, store counts, and market structure, while accounting for regional and format-specific heterogeneity.

The first set of results shows that increases in online retail spending are, on average, associated with declines in offline retail sales. The magnitude and direction of the effects, however, vary considerably across retail formats. Large discount stores exhibit the strongest substitution effects; meanwhile, super supermarkets (SSMs) and other mid-sized offline retailers also experience adjustment pressures in the form of declining sales and store counts. In contrast, convenience stores and certain proximity-based specialty retailers display weaker substitution effects, with some evidence of complementary outcomes at the local level. The expansion of rapid delivery services, such as same-day or next-day shipping, exerts an additional negative effect on offline sales, particularly in food and daily necessities segments, indicating that logistics innovation constitutes an independent channel of competitive pressure.

The second set of results evaluates the economic effects of policy changes that allowed large retail stores and SSMs to shift mandatory closure days from weekends to weekdays. Exploiting variation in policy timing across local governments, the analysis finds that weekday conversion is associated with a statistically significant increase in sales for large discount stores―a pattern that is robust across alternative specifications and that persists after controlling for COVID-19-related disruptions. The effects on SSMs and convenience stores are more heterogeneous and appear to depend on local market structure and consumption patterns. Notably, no systematic decline in traditional market sales is detected on average, suggesting that the regulatory adjustment does not uniformly disadvantage such formats.

The final set of results highlights the role of demographic structure in shaping long-term retail market outcomes. While population decline generally leads to market contraction, the adjustment mechanisms differ significantly across retail formats. While small-scale, proximity-based retailers (e.g., convenience stores) have shown consistent growth, they primarily respond to demand shocks through store exits, suggesting structural fragility often associated with excess entry. In contrast, corporate-type retailers, such as SSMs and supermarkets, tend to buffer the shock through adjustments in sales per store, potentially benefiting from product differentiation capabilities. Furthermore, population aging―specifically the rising share of the elderly and the shrinking baby boomer generation―is found to structurally dampen overall retail vitality. These findings suggest that policy frameworks need to move beyond uniform protection to support fundamental competitiveness, accounting for format-specific adjustment paths and the qualitative shift in demand.

Overall, these findings indicate that structural changes in Korea’s retail markets arise from the combined influence of market-driven forces, regulatory design, and demographic trends, generating heterogeneous adjustment paths across regions and retail formats. The results imply that uniform, format-based retail regulation may be increasingly misaligned with evolving market conditions, and that policy frameworks incorporating regional characteristics, retail heterogeneity, and long-term demand shifts are more likely to prove effective.

Summary

Research Monograph KOR Macroeconomic Impact of AI Diffusion

This report examines how artificial intelligence (AI), particularly modern, data-driven, and increasingly generative systems, is likely to affect Korea’s productivity, growth, employment, and wages over the next decade or two. Three layers of evidence are integrated within a unified task-based framework: (i) micro-level measures of AI exposure and economic viability at the task and occupation levels, (ii) firm-level panel evidence on AI adoption and productivity, and (iii) a macroeconomic general-equilibrium model that aggregates task-level shocks into total factor productivity (TFP) and long-run labor market outcomes. The study defines AI as software systems that replicate human capabilities in learning, prediction, pattern recognition, perception, and natural language processing―a definition consistent with that used in the underlying firm survey and broad enough to encompass both earlier, narrow algorithms and more recent foundation models and AI agents.

Chapter 2 offers an accessible overview of the technological evolution of AI from traditional machine learning to transformer-based large language models and emerging agent-like systems. It emphasizes two features of particular macroeconomic relevance. First, advances in general-purpose and multimodal models have greatly expanded the range of tasks technically exposed to AI. Second, effective deployment requires complementary investments in data, organizational capacity, and human capital, suggesting that technical feasibility alone is a poor predictor of short-run economic impact.

Chapter 3 develops a task-based measure of AI automation potential tailored to the Korean labor market. Using detailed work descriptions from the Korean Employment Classification of Occupations (KECO) and Workpedia, the study decomposes 537 occupations into 6,824 unit tasks and scores each task along five dimensions: measurability of outcomes, data availability and quality, context dependence, required human judgment necessity, and agentability (the ease with which an AI agent can execute a given task). These components are combined into a task-level AI score that captures effective automation potential rather than mere technical exposure. A cost-benefit framework inspired by recent work on computer vision and AI costs is then applied to identify tasks and task·firm combinations for which automation is economically viable, given realistic assumptions about data, development, inference, integration, and maintenance costs relative to labor savings. The findings are conservative by design. Under a naive exposure-only criterion, AI could potentially affect roughly 8-12% of current employment and 10-11% of current sales, concentrated in finance, insurance, R&D, ICT, and certain transport and business services. Narrowing the focus to tasks that are both technically automatable and economically viable reduces these shares to about 1-3% of employment and 1-2% of sales. This suggests that, in the near term, AI will likely induce selective and partial automation in specific occupations and industries, rather than a broad-based, immediate displacement of labor.

Chapter 4 analyzes firm-level evidence using the nationally representative Korean Survey of Business Activities for 2017-2023, which asks firms whether they use AI―defined in the questionnaire as software that replicates human learning, reasoning, perception, and natural language understanding―and other fourth industrial revolution (IR4) technologies. To address the endogenous timing of AI adoption, the analysis employs panel IV (2SLS) models with firm and year fixed effects, instrumenting AI adoption with industry-level economic viability measures from Chapter 3. In the preferred specifications, firms that adopt AI and related IR4 technologies exhibit statistically significant increases in log sales per employee on the order of 5-20%, driven primarily by higher sales rather than systematic employment cuts. Pure “AI only” effects, net of broader digitalization, are estimated with less precision, consistent with AI operating as a general-purpose technology that must be embedded in a broader digital and organizational transformation. As a robustness check, propensity-score matching and difference-in-differences estimates for AI first movers suggest modest but positive short-run effects on labor productivity, with limited evidence of strong dynamic effects within the short observation window.

Chapter 5 incorporates these micro-level estimates into a task-based general-equilibrium model following the approach of Acemoglu and Restrepo to simulate AI-induced TFP paths over the next 10-15 years. Hulten’s theorem implies that, under certain assumptions, aggregate TFP change can be approximated by a Domar-weighted sum of task-level cost savings. The model therefore combines (i) the economically viable task shares by industry, (ii) firm-level productivity effects of AI, and (iii) alternative adoption scenarios―baseline, optimistic, and pessimistic―to trace out possible TFP trajectories. Under baseline assumptions, AI contributes a cumulative TFP gain of about 2.3% over a decade, nontrivial but below some of the more optimistic global projections. These simulations focus on the task automation channel and treat parameters as exogenous. They abstract from structural transformation, intangible capital accumulation, idea-generation effects, and potential discontinuities in AI capabilities. Then the analysis turns to long-run employment and wage effects across occupations. Using a cross-section of Korean 2-digit occupational categories over 2014-2024, the analysis estimates reduced-form relationships between changes in employment and real hourly wages and measures of routine and structured task content, while instrumenting for endogenous employment changes with leave-one-out labor-demand shocks. Occupations with higher routine task shares experience lower employment growth and somewhat lower wage growth over the decade, consistent with international evidence that automation pressure exerts downward pressure on labor demand and wage growth in exposed jobs. Combined with the AI exposure metrics presented earlier, these estimates imply that, under realistic adoption scenarios, the annual displacement and wage-drag effects attributable to AI are likely modest relative to existing demographic and structural trends, but non-negligible for specific groups.

Chapter 6 synthesizes these findings and discusses their implications for policy and business. For policymakers, the central message is that AI is unlikely to trigger an immediate, economy-wide employment collapse, but will require active management of selective automation, task restructuring, and skill upgrading in exposed sectors. The study argues for a market-friendly policy mix: clarifying AI-related regulation and liability, investing in data and compute infrastructure, strengthening education, training, and retraining systems, and fostering complementary innovations and organizational change. For firms, the key insight is that productivity gains derive less from AI in isolation and more from integrating AI into workflows, data pipelines, and human capital strategies.

Summary

Policy Study KOR A Study on the Economic Impact of Foreign Worker Inflows and Determinants of Migration Decisions

Korea’s declining potential growth due to demographic change has elevated immigration policy as a central economic strategy, yet effective design is hindered by limited evidence on labor-market impacts and growing reliance on non-employment residence statuses that still permit work.

Traditional employment-visa-based forecasting no longer captures the true scale or composition of foreign labor.

This study addresses this gap by providing rigorous evidence on how foreign worker inflows affect labor-market outcomes and by identifying key determinants of migrants’ decisions to move to Korea.

Using a causal framework with shift-share instruments for 229 municipalities (2016-2023), the study shows that an increase in employment-visa foreign inflows raises natives’ days worked slightly but substantially reduces foreign workers’ days worked and incomes.

Income effects on natives are, on average, statistically insignificant, while foreign workers’ incomes decline markedly, indicating strong substitution and competition among foreign workers and more pronounced adverse effects for foreigners than for natives.

The effects vary by period and visa type.

In the post-COVID-19 period, inflows under employment visas reduced native incomes, and the adverse income effects become more pronounced when non-employment visa holders (e.g., overseas Koreans, international students, and permanent residents) are included.

These findings underscore that mismeasurement of labor inflows ― particularly the exclusion of non-employment statuses ― can bias impact estimates and lead to misguided policy conclusions.

Beyond labor outcomes, the analysis documents migration determinants ― income, finance, and migration costs ― showing a consistent native income premium, limited financial inclusion for foreigners reliant on high-interest loans, and high migration costs relative to expected income, especially under short-term stay regimes.

Taken together, the findings indicate that immigration policy in Korea should move away from a narrow, employment-visa-centered approach and toward an integrated framework that explicitly accounts for all labor-supplying residence statuses and their heterogeneous effects over time and space.

These patterns underscore the necessity of evidence-based visa quota setting, careful monitoring of regional and sectoral impacts, and policy instruments that prevent unintended harm to vulnerable groups.

By grounding immigration policy in precise measurement and causal analysis rather than aggregate labor-shortage narratives, Korea can better align foreign labor utilization with sustainable growth and labor-market stability.

Summary

Policy Study KOR Intergenerational Mobilty in Korea: Insights from Educational Mobilty

This study examines intergenerational educational mobility in South Korea to provide a comprehensive analysis of social mobility and its underlying factors. By assessing both absolute and relative educational mobility, the study aims to highlight disparities in access to higher education and the influence of parental background. The findings indicate that while South Korea exhibits high intergenerational educational mobility, the trend of upward mobility has weakened in recent birth cohorts, with parental education and income playing a growing role in shaping children’s educational outcomes. In particular, the analysis reveals that income disparities increasingly translate into differences in access to top-tier universities, reinforcing intergenerational inequality. Moreover, structural changes, such as rising university enrollment rates, necessitate a nuanced approach to measuring educational mobility. To enhance equal opportunities, policy efforts should focus on expanding educational access for disadvantaged groups and preventing income inequality from perpetuating educational disparities. Reforming university admissions to incorporate diverse selection criteria beyond standardized test scores can help ensure that academic achievement is determined by individual ability and effort rather than socioeconomic background.

Summary

Research Monograph KOR The Effects of Serious Accidents Punishment Act on Labor Market Outcomes

This study examines the effects of the Serious Accidents Punishment Act (SAPA) on labor market outcomes to derive policy implications. SAPA was enacted in January 2021 and implemented in January 2022.

Chapter 2 summarizes the institutional structure and introduces key research questions. Specifically, this chapter reviews the legislative background, the structure of the law, early judicial trends, and existing literature on SAPA. Based on this review, I provide theoretical predictions regarding the effects of SAPA using a simple model where firms choose their level of safety investment and labor demand. The model predicts that while SAPA is likely to reduce accidents by increasing safety investment, it may simultaneously lead to a reduction in labor demand.

Chapter 3 analyzes data from an original firm-level survey to examine current situation of the Safety and Health Management Systems. I find that firms increased their safety investment following the implementation of SAPA. However, despite the quantitative expansion of safety investment, I find that the qualitative improvement of the Safety and Health Management Systems remains limited.

Chapters 4 through 6 present causal analyses of SAPA’s effects. In Chapter 4, I study the effects on the labor market for safety experts, a key input for safety investment. By applying Synthetic Difference-in-Differences (SDID) to observations from the Regional Employment Survey, I find that SAPA increased the employment of safety experts, with the effect growing from 2022 to 2024. However, the effect on wages was pronounced only in the short run; while SAPA increased wages in the second half of 2022, the effect became smaller and statistically insignificant by the second half of 2024, implying a highly elastic supply of safety experts.

Chapter 5 examines effects on workplace accident fatalities, the primary policy objective of SAPA. Using a Difference-in-Differences (DID) framework that exploits industry-level variation in exposure to SAPA, I find that the Act reduced three "traditional" types of workplace accidents: falls, crushes, and collisions. However, there is no evidence of significant effects on other accident types.

Chapter 6 investigates the effects of SAPA on labor demand for high-risk occupations. I combine information on occupation-level risk exposure and labor market outcomes using an empirical strategy in Continuous Treatment Difference-in-Differences framework. The results indicate that following the implementation of SAPA, employment levels in higher-risk occupations decreased relative to those with lower risk exposure.

Chapter 7 concludes the study by synthesizing the empirical findings and deriving policy implications.

Summary

KDI FOCUS Eldercare Workforce: Projections and Policy Implications

Operating beyond the super-aged threshold, Korea faces deepening shortages in its eldercare workforce as the sector struggles to attract workers. While better job quality is imperative to expand this workforce and maintain the quality of life for older adults, incentives for domestic workers alone will not close the gap. Visa policy needs to change to bring in foreign care workers, and care robot technologies should be actively deployed to raise labor productivity in the sector.

- Demand for formal eldercare services is expected to rise sharply, with workforce shortages deepening in step.

- Demand for LTC services is projected to increase by more than 2.4 times between 2023 and 2043.

- Health improvements offset demand only modestly. The growing 85+ population will drive faster growth in high-intensity care (Grades 13).

- The supply of LTC workers is projected to peak at 806,000 in 2034 before declining.

- The share of care workers aged 60 and over is expected to rise from 63.1% in 2023 to 72.6% in 2043, reflecting an increasingly aged workforce.

- Holding the 2023 caseload per care worker constant would require an additional 990,000 workers by 2043.

- Differences in the pace of aging across regions will widen disparities in the number of beneficiaries per care worker.

- Foreign care workers comprised just 0.9% of the total workforce in 2023, a marginal presence in the sector.

- With 56.6% of foreign care workers aged 60 or over and 77% concentrated in the SMA, their capacity to mitigate workforce aging and regional supply disparities remains highly constrained.

- Visa policy for foreign care workers should shift to occupation-specific visas with managed aggregate inflows, guided by the extent to which better job quality can expand the domestic workforce.

- Applying current EPS service-sector quotas to care facilities would permit up to 63,000 foreign workers.

- The E-7 care worker visa pilot should be expanded in scale, alongside efforts to secure sufficient enrollment for the associated training program.

- Attracting domestic workers and retaining recruited foreign careworkers both require better job quality.

- Targeted incentives are needed to encourage employment in underserved regions and ease supply-demand imbalances.

- Care robot uptake in Korea remains low, with just 6.4% of surveyed facilities deploying them.

- The main reason for deploying care robots is to ease the physical burden on care workers; adopters report workload reductions of more than half in some cases.

- Cost is a key barrier to adoption: 51.8% of care facilities would deploy care robots if cost subsidies were provided.

- Care robot policy should expand beyond its developer-centered focus to include support for care facilities, promoting wider adoption in frontline care settings.

Summary

Research Monograph KOR Who Cares for Us?: Policies on Eldercare Workers

South Korea reached the super-aged mark in December 2024, with over 20% of its population aged 65 and older. Eldercare jobs, labor-intensive and emotionally demanding yet accessible to low-skilled workers at low wages, are globally undesirable, leading to labor shortages in advanced economies. As baby boomers (born 1955-1963) enter the late elderly (75 and older) after 2030, demand for eldercare services is projected to surge, worsening supply-demand imbalances.

This study examines the current state and limitations of Korea’s eldercare workforce to propose policy improvements. It estimates eldercare labor supply and demand to forecast the scale of labor shortage and discusses strategies for workforce expansion. Additionally, an empirical analysis assesses how quantitative and qualitative workforce expansion impacts the quality of life for residents in long-term care facilities, providing policy insights.

Chapter 2 forecasts demand for eldercare services and estimates the eldercare labor supply to assess the scale of labor shortage and analyze supply-demand imbalances at the national and metropolitan/provincial levels. The findings indicate that the rapid rise in the super-aged population will sharply increase demand, outpacing the growth of care worker supply and deepening supply-demand imbalances. Regional variations in aging and available workforce are expected to widen the regional supply disparities, suggesting the need for proactive and region-specific workforce expansion policies. This chapter also estimates demand for services that reflect improvements in elderly health in the past decade, highlighting that workforce expansion alone is insufficient to resolve the supply-demand gap amid sustained demand growth. Managing demand for long-term care services through elderly health promotion and functional improvements is essential.

Chapter 3 investigates how expanding the eldercare workforce in long-term facilities affects health outcomes for care recipients. Using health insurance claims and long-term care insurance data, it examines the impact of the 2018 minimum wage increase and the 2022 staffing requirement changes on facility employment and recipients’ medical service utilization. The results indicate that workforce expansion is associated with reduced medical service use, leading to positive health outcomes, suggesting investment in care worker expansion can be a cost-effective policy measure.

Chapter 4 empirically analyzes the impact of enhancing nursing functions in eldercare workers on care recipients and discusses the need for improving their expertise. This chapter examines how changes in nursing staff skill composition following the 2018 minimum wage increase and the specialized nursing care unit pilot program launched in 2019 affected recipients' medical service utilization. The analysis shows that strengthening medical functions in long-term care facilities significantly reduces residents' use of high-cost inpatient services, leading to lower overall healthcare expenditures. While the increased costs of long-term care services partially offset these savings, the results suggest that the specialized nursing care unit program aligns with policy goals of optimizing healthcare utilization among facility residents.

Chapter 5 identifies the characteristics of foreign care workers using administrative data, albeit to a limited extent, aiming to enhance understanding of migrant labor in the eldercare sector. With restricted foreign worker employment in eldercare roles in Korea, this chapter assesses the potential impacts of their integration through existing literature. Furthermore, it reviews specific policy responses from countries utilizing migrant worker policies to mitigate eldercare labor shortages and discusses implications for Korea's eldercare sector.

Chapter 6 proposes future policy directions for eldercare workforce expansion based on the findings from the preceding chapters. First, quantitative workforce expansion enhances job quality, reduces workload through care technology, and utilizes migrant labor. Second, elevating the professional competence of the eldercare workforce involves strengthening nursing functions in long-term care facilities, clarifying the scope of nursing care that can be provided within such facilities, and enhancing education and training in geriatric medicine for facility staff. Third, managing care demand through health promotion entails implementing mental health and chronic disease management strategies to delay the need for eldercare. By addressing these areas, this study aims to contribute to the development of sustainable policies that ensure adequate workforce supply while improving the quality of eldercare services in Korea.

Summary

Policy Study KOR Income Support in Response to Labor Market Shocks: Korea‘s Basic Livelihood Security System

This study examines how labor market conditions and labor policy changes affect benefit receipt under Korea’s National Basic Livelihood Security (NBLS) system. Given the substantial coverage gaps in employment insurance, NBLS serves as the last-resort safety net for low-income individuals who are able to work. Assessing its responsiveness to economic shocks and policy changes is essential for evaluating the effectiveness and limitations of the current income support system.

First, the study analyzes the responsiveness of NBLS benefit receipt and expenditures to key labor market indicators, such as the unemployment rate and the employment rate. The results show that, overall, NBLS has not exhibited meaningful counter-cyclical responsiveness to labor market fluctuations. Although a modest increase in benefit responsiveness to the unemployment rate is observed following the 2015 reform, responsiveness remains broadly limited ― even during the COVID-19 period. However, in contrast to the weak correlation with the aggregate employment rate, declines in the employment rate of middle-aged unpaid family workers show a clear association with increases in NBLS receipt. These findings suggest that NBLS has limited responsiveness to labor market fluctuations among the working population, though it appears responsive for specific vulnerable groups such as unpaid family workers.

Second, the study examines the effects of minimum wage increases ― a key labor policy targeting vulnerable workers ― on NBLS benefit receipt. The analysis shows that sharp minimum wage hikes increased both overall NBLS receipt and livelihood benefit receipt, particularly among middle-aged individuals. Monthly analyses that control for other NBLS reform effects also confirm that minimum wage increases raised benefit receipt among the working-age population. Moreover, this increase was driven primarily by new entrants to NBLS rather than by a slowdown in exits.

These findings align with the earlier results showing that NBLS receipt is particularly responsive to labor market shocks among certain vulnerable groups, such as middle-aged unpaid family workers. Previous studies have shown that minimum wage increases reduce employment rates among vulnerable groups in the labor market, including the self-employed and unpaid family workers. Taken together, the analysis suggests that employment shocks experienced by unpaid family workers may constitute a key channel through which NBLS benefit uptake rises ― particularly among the middle-aged population.

This paper emphasizes the importance of establishing and strengthening an income support system that is responsive to labor market dynamics, especially in light of anticipated structural changes and labor policy reforms. Moreover, because labor and welfare policies often target overlapping populations and interact in practice, it is essential to carefully consider these interconnections in the design and implementation of related policies.

Summary

KDI FOCUS Declining Cognitive Skills among Korean Workers: Drivers and Improvement Measures

Strengthening workforce competencies and labor productivity has become increasingly important amid rapid advances in automation and industrial transformation. However, international comparative findings show that the cognitive skills of Korean workers decline steeply with age, raising concerns about labor productivity. While multiple factors contribute to this decline, the primary driver appears to be a wage structure that provides insufficient incentives for skills development. To promote labor productivity growth, wage systems based on skills and performance need to be expanded, alongside the provision of broader opportunities for upskilling and reskilling.

- Adapting to advances in AI and evolving job tasks requires raising labor productivity through broad-based improvements in workers’ cognitive skills.

- The cognitive skills of Korean workers have not only declined over the past decade but also exhibit an unusually rapid depreciation with age, raising concerns regarding both labor productivity and the effective utilization of older workers.

- Skill depreciation among Korean workers is marked by (1) an early onset in young adulthood and (2) an exceptionally rapid decline with age.

- Factors contributing to the rapid age-related decline in cognitive skills appear to include limited opportunities for skill development in adulthood: long and rigid working hours, ineffective learning and training programs, and workplace environments that prevent workers from developing skills.

- The absence of wage systems that incentivize voluntary skill development is suggested as a key factor behind Korea’s rapid skill decline.

- For Korean workers, the expected wage return to cognitive skills is roughly half the level observed in OECD peers such as Germany, Japan, and the United States, leaving weak incentives for voluntary upskilling.

- Korea’s wage structure (1) places substantially greater weight on tenure than on competencies and (2) exhibits large wage differentials by firm size.

- This wage structure weakens incentives for post-entry skill development while intensifying inefficient credential competition for early-career entry into large firms.

- Broader adoption of skill- and job-based pay systems is needed to strengthen incentives for workers to develop their skills.

- Workers should be given meaningful opportunities to build their skills through greater autonomy over working hours, more effective learning and training programs, and workplace environments that enable full use of their competencies.

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