KDI Korea Development Institute

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 Renewable Energy Deployment in Korea: Economic Drivers, Barriers, and Policy Implications

Despite the rapid global decline in the levelized cost of electricity (LCOE) for solar and wind power, Korea's renewable energy generation share remains markedly low. This study examines the economic drivers and impacts of renewable energy deployment in Korea through four complementary analyses: firm-level decomposition of industrial greenhouse gas emissions, cross-country panel estimation of deployment correlates, country-level learning-by-doing (LBD) estimation, and a public expenditure efficiency assessment using the Marginal Value of Public Funds (MVPF) framework.

The firm-level analysis finds that emission reductions in Korea have been driven primarily by energy efficiency improvements, while fuel switching and process-level reductions remain limited; technological lock-in among large firms suggests a heavier potential burden from carbon pricing. The cross-country analysis finds that LCOE is not significantly associated with deployment shares on average, but a negative correlation emerges among low-deployment countries; non-cost factors ― including grid quality, financial access, and revenue certainty ― are each significant on average. LBD estimates reveal that cumulative capacity and cost reductions co-move on average, but global technology spillovers account for much of this pattern; onshore wind, however, exhibits a statistically robust inverted-U-shaped learning path that persists after controlling for common trends, with learning pathways that vary across countries and are amplified by revenue certainty and technological proximity. Applying the MVPF framework to Korea's Renewable Energy Certificate (REC) scheme yields estimates of 1.33 for solar and 1.18 for wind, with learning effects accounting for 21-50% of total benefits. Taken together, the evidence points to a policy agenda extending beyond price signals: accelerating renewable deployment requires targeted interventions in grid infrastructure, financing conditions, and institutional design ― investments that the MVPF estimates confirm to be economically justified.

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 Government Forms and Economic Security

This report explores the relationship between government forms and economic security, analyzing how political systems in democratic countries influence economic development. Unlike previous studies that focus on dichotomous comparisons between democracy and authoritarianism, this research empirically identifies the conditional effects of micro-institutional combinations in OECD high-income democracies―such as government type, electoral rules, and power structures―on long-term economic levels through government capacity. It emphasizes that beyond the polar extremes of the Washington Consensus and the Beijing Consensus, the economic conversion efficiency of government capacity within democratic institutions is the key determinant.

The literature review examines contrasting views on the impact of democracy on economic growth. Some studies argue that democracy promotes growth by strengthening property rights and investment incentives, while others point out that it can hinder growth due to policy delays and populism. Presidential systems are praised for long-term stability and executive power, whereas parliamentary systems are noted for flexibility and consensus, though empirical results are mixed. Recent analyses, like Acemoglu et al. (2019), confirm positive effects of democracy when using income levels rather than growth rates as the dependent variable, as this captures long-term cumulative effects while controlling for short-term volatility.

For the analytical method, panel data from 38 OECD countries (1995-2023) is utilized with the Arellano-Bover/Blundell-Bond System GMM. The dependent variable is ln(GDP per capita) to measure economic development levels, with political system dummies (presidential, semi-presidential, parliamentary; single-member district, multi-member district; separation of powers, fusion of powers) and their interactions with government capacity indicators (government effectiveness, control of corruption, political stability, regulatory quality, rule of law) as key explanatory variables. Control variables include historical legacies (Spanish colony, former USSR, Scandinavian legal origin), economic structures (trade dependence, inflation, FDI, oil rents), and demographic factors (aging) to mitigate endogeneity.

Empirical results show that the combination of presidential system + single-member district + separation of powers yields the greatest increase in income levels from improvements in government capacity. A 1-unit improvement in government effectiveness leads to a 47.1% rise (real 60.2%) in presidential systems (ps), but is nearly insignificant in parliamentary systems (cm). Similar patterns hold for control of corruption and rule of law, with regulatory quality showing 4-7% uplift effects. Political stability is positive in presidential systems but has reverse effects in parliamentary ones. This is interpreted as the fixed terms and separate survival in presidential systems enhancing incentives for long-term reforms, while bottom-up nominations in single-member districts ensure political stability.

Policy implications suggest that for countries like Korea, with vulnerabilities in single-term presidencies and top-down nominations, reforms are needed. Introducing a four-year re-election system to secure long-term vision, midterm elections to turn divided governments into negotiation opportunities, and bottom-up nominations to strengthen legislative independence are recommended. Constitutional amendments should exclude incumbent politicians and emphasize citizen participation to block agency problems. This forms an "institutional trinity" to complete economic security within democracy, providing a roadmap for the post-Washington-Beijing world.

Research limitations include its restriction to OECD high-income democracies, making generalization to developing countries or authoritarian regimes difficult. The low institutional heterogeneity limits identification of regime effects themselves, and it fails to capture advantages of authoritarian models. However, it provides empirical evidence for optimizing efficiency through fine-tuning in high-institutional environments.

Summary

Other Research KOR Whole-of-Government Coordination in ODA: Comparative Cases of Donor Countries

Amid rapidly changing global conditions, complex and interconnected challenges have become increasingly prominent, highlighting the importance of whole-of-government approaches in international development cooperation. The significance of such approaches is reflected in the OECD DAC peer review framework, which assesses whether member countries have coherent and coordinated government-level systems for effective development and humanitarian assistance. Key evaluation criteria include leadership, accountability, complementarity, and inter-agency responsibilities.

Implementing whole-of-government approaches in practice presents multiple challenges. While global issues such as supply chains, climate change, health, and food security emphasize the need for coordinated action, the specialized expertise of individual ministries has become increasingly important. Whole-of-government coordination requires horizontal collaboration across agencies, often involving substantial costs and efforts, and raises questions about balancing individual agency accountability with collective action.

This study examines the theoretical background, concepts, and scope of whole-of-government coordination in development cooperation. It also reviews analytical criteria for evaluating coordination frameworks, focusing on legal and institutional foundations, inter-ministrial coordination mechanisms, and evaluation and performance management measures, which function as unintended, indirect coordination tools. Using these criteria, the study compares the development cooperation systems of selected donor countries, including Japan, France, the United Kingdom, Germany, and Spain, to explore how whole-of-government coordination is structured and implemented.

The research provides a foundation for understanding the design and assessment of government-wide coordination mechanisms in development cooperation, contributing to the discussion on policy coherence, accountability, and effectiveness in international development policy.

Summary

Research Monograph KOR Korean Real Estate Project Finance: Structure, Problems, and Policy Recommendations

Since the 2022 Legoland crisis, real estate Project Finance (PF) has emerged as a significant risk factor for the entire South Korean economy, particularly within the financial and construction sectors. These crises are not isolated events but a phenomenon that recurs roughly every decade; for instance, the massive savings bank run of 2011 was also primarily driven by non-performing PF loans. The study addresses a set of fundamental questions: What are the root causes of these recurring PF crises, and how can they be resolved? What policy measures are available, what are their projected economic effects, and what are the key points of contention considering global precedents and Korea's unique institutional and industrial context? By conducting comprehensive institutional and empirical research, the study proposes structural improvements for real estate PF in Korea.
The study is organized into four chapters.

Chapter 1 explains the structure of real estate PF, diagnosing the "low-capital, high-guarantee" structure as the primary cause of these recurring crises, and discusses various policy measures to reform this structure. In major advanced economies, developers typically raise 20-40% of the total project cost as equity, but Korea's equity ratio stands at a mere 3%. Consequently, financial institutions rely on completion or payment guarantees from construction companies instead of rigorous project feasibility assessments. This chapter argues that this structure transfers risk to the entire society by encouraging reckless investment and system-wide instability. It then discusses policy recommendations such as tax deferrals on land contributions in kind to encourage equity expansion. Other related issues are examined, including equity loans―where developers borrow cash to fund their equity contribution―which critics argue can nullify the effect of equity increases. Policymakers may need to determine what constitutes qualified equity and what does not.

Drawing on a proprietary dataset of approximately 800 PF sites evaluated between 2013 and January 2025, Chapter 2 provides an in-depth empirical analysis of how low equity affects the soundness of PF projects. The analysis reveals that higher equity ratios significantly reduce pre-sale, financial, and construction risks. Furthermore, it demonstrates that higher equity ratios lead to lower total project costs, specifically in construction, financial, and miscellaneous expenses, suggesting that resolving the low-capital structure can improve both the stability of projects and the affordability of housing supply.

Chapter 3 complements the preceding chapter by analyzing site-specific PF data from the United States (via MSCI) to examine the relationship between financial structure and final project performance. The findings indicate that: (1) higher Loan-to-Value (LTV) ratios increase the probability of default; (2) higher LTV ratios reduce the likelihood of recovery after a default occurs; and (3) higher LTV ratios hinder post-completion transactions, such as refinancing into permanent loans or successful divestment (exit). Taken together, these results underscore that high debt dependency creates multifaceted risks throughout the project lifecycle.

Chapter 4 employs a Dynamic Stochastic General Equilibrium (DSGE) model to analyze the macroeconomic implications of PF regulatory changes. The model reflects Korea's unique "finance-real economy cross-structure," where non-bank financial institutions (NBFIs) provide about 70% of PF loans due to regulatory asymmetries. The analysis shows that while temporary tightening of capital requirements primarily causes credit reallocation between institutions, a permanent increase in NBFI capital requirements leads to long-term benefits. Although it may cause a temporary dip in housing supply, the accumulation of capital eventually improves credit supply capacity, leading to increased housing stock, stabilized prices, and higher total national output. In contrast, "cost-based" regulations that impose continuous costs on leverage were found to suppress credit supply and reduce aggregate production in both the short and long term.

Summary

Policy Study KOR Analysis of Commuting Efficiency based on Urban Spatial Development and Transport Infrastructure Supply Policies

Commuting, which bridges residences and workplaces, is a fundamental trip that supports daily life and economic activities, while maintaining close ties to labor market accessibility, productivity, and social quality of life. The government has made continuous efforts to reduce commuting distances and times by alleviating the spatial imbalance between residential and employment facilities and expanding the housing supply for diverse social classes near job-dense areas.

The purpose of this study is to empirically analyze the impact of urban spatial development and transport infrastructure supply policies on commuting efficiency. To this end, we established commuting efficiency indicators―including average and external commute times, external commute ratios, and car usage rates for external commutes―at the level of cities (si), counties (gun), and districts (gu) (hereafter si-gun-gu). By constructing a staggered Difference-in-Differences (DiD) model that accounts for the varying implementation timelines of urban development and rail projects across different regions, this research analyzes the heterogeneity of commuting efficiency improvements according to the timing of development and supply.

Based on the staggered DiD model, which considers the interaction effects between rail and housing land supply, the results reveal that despite the steady expansion of physical infrastructure―such as urban development, transport expansion, and public transit improvements―over the past 20 years, the actual effects on improving commuting efficiency have been limited. The average commute time across nationwide si-gun-gu slightly increased from 23.02 minutes in 2000 to 24.18 minutes in 2020. Furthermore, the car usage rate for external commutes across these si-gun-gu regions rose significantly from 54.61% to 69.69%, and the external commuting ratio also saw a slight increase from 23.18% to 24.75% during the same period.

The empirical findings suggest that to enhance commuting efficiency in the future, a policy shift is required: moving away from the traditional focus on expanding transport and land supply toward Transportation Demand Management (TDM) and the refinement of urban spatial structures. Specifically, car demand management policies―such as congestion charging, adjusting parking fees to realistic levels, and expanding bus-only lanes―should be strengthened. Concurrently, public transit service quality, including fare systems, transfer convenience, accessibility, and reliability, must be improved to actively encourage transit use. Additionally, strategies to distribute transport demand through mixed-use urban developments that promote jobs-housing proximity are essential.

Furthermore, to improve commuting efficiency, policies should focus on creating polycentric urban structures to alleviate commute concentration in specific areas, establishing walkable and bikeable communities through mixed-use development, and strengthening jobs-housing proximity via Transit-Oriented Development (TOD). Moreover, "soft" policies such as telecommuting, flexible work hours, decentralized office spaces, and staggered commuting should be implemented in parallel to reduce the necessity of travel or mitigate peak-hour congestion.

Commuting efficiency cannot be improved solely by the supply of land and transport facilities. This is because commute times are influenced by a complex interplay of factors, including induced demand, jobs-housing imbalances, and individual mobility behaviors. Therefore, the policy focus must shift fundamentally toward improving spatial accessibility between housing and employment opportunities, prioritizing demand management and structural urban improvements over simple infrastructure expansion.

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.

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