KDI - Korea Development Institute - RESEARCH - Research Areas

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 Energy Market Design with Local Content Requirements

As governments accelerate the push toward carbon neutrality―while advancing strategies for emerging industries, responding to tighter protectionism, and adapting to shifting supply chains―pressures to build domestic industrial capacity, strengthen energy security, and secure technological autonomy have intensified. Although support for renewables and low-carbon processes is expanding, preferential measures for domestic producers risk distorting price signals, weakening allocative efficiency, and increasing exposure to trade disputes. This report examines how such industrial support interacts with energy-market design and assesses the implications for market participation, competitive dynamics, and overall efficiency.

We develop an asymmetric auction model that reflects cost and capability gaps between domestic and foreign firms and incorporates a lower-bound constraint on domestic firms’ ex-ante winning probability. Within this setting, we compare three instruments: (i) horizontal measures that reduce entry costs (e.g., grid and other infrastructure investment, market and regulatory reform); (ii) conditional, flat subsidies paid when a domestic bidder wins; and (iii) market-based, multi-dimensional (scoring) auctions that award non-price premiums for domestic content. When entry costs are significant, conditional subsidies tend to dampen participation less than scoring-based linkage and can deliver higher allocative efficiency. Combining horizontal and vertical tools helps meet domestic-content objectives while limiting distortions and widening competition relative to reliance on vertical measures alone.

Building on these results, the report recommends: defining measurable short- and long-term objectives; prioritising sectors with meaningful yet bridgeable capability gaps; translating non-price scores into “equivalent subsidies” for transparent calibration; embedding regular evaluation and sunset provisions; and continuously ensuring consistency with international trade disciplines.

Summary

Research Monograph KOR Empirical Study on the Growth of Korea’s Cultural Content Industry and Policy Implications

This study conducts a comprehensive analysis of the growth dynamics of South Korea's cultural content industry to enhance its competitiveness and support sustainable development. Employing a multifaceted empirical approach, it examines quantitative metrics―such as the number of businesses, employment levels, revenue, and trade flows―across the industry and its subsectors to identify growth trajectories and structural characteristics (Chapters 3 and 4).

Given the industry's complex interdependence with other sectors, this study combines data from the "Special Classification of the Content Industry" (Statistics Korea, Ministry of Culture, Sports and Tourism), the "Korean Standard Industrial Classification (KSIC)" (Statistics Korea), and the "Input-Output Tables" (Bank of Korea). This integration creates a new input-output table that captures 12 subsectors of the cultural content industry (Chapter 5).

The study uses the new input-output table to examine supply, demand, and input structures to illuminate the industry's economic roles and inter-industry linkages. Key metrics―including total output ratio, import dependency, intermediate input structure, and value-added ratio―are compared with other sectors to highlight the distinctive characteristics (Chapter 6). The study further investigates the sector's effects on the broader economy, calculating coefficients for input, production induction, and sensitivity, assessing the sector's overall impact via inter-industry ties and interactions (Chapter 7).

In recognition that individual businesses drive the industry's growth, this study identifies business growth enablers within the CPND framework (Content, Platform, Network, and Device). They include intellectual property ownership, workforce size, operational tenure, market diversification, and digital infrastructure. This analysis highlights the critical impact of IP rights―especially utility patents and copyrights―on competitiveness and revenue growth (Chapter 8).

Moreover, the study systematically evaluates relevant policies through a descriptive statistical analysis of 149 support programs managed by the Ministry of Culture, Sports and Tourism and the Korea Creative Content Agency (KOCCA), focusing on their primary functions and target groups (Chapter 9). Finally, building on the study's findings, key policy directions are proposed: fostering digital adaptability among small and medium-sized enterprises (SMEs), enhancing IP protection in the digital era, diversifying export markets, and addressing regional disparities to ensure balanced development across Korea (Chapters 10).

Summary

KDI FOCUS Path to National Champions: Transforming Support Policies for Small- and Medium-Sized Enterprises (SMEs)

South Korea’s ‘national champion policy,’ designed to foster global enterprises, has yet to deliver measurable outcomes in sales and productivity, suggesting inefficiencies in resource allocation linked to ‘the risk of picking winners.’ Accordingly, the incentive structure of growth policies for Small- and Medium-Sized Enterprises (SMEs) needs an operational shift, moving away from conventional subsidy assistance toward a bespoke model that integrates private investment, consulting, and networks to address their business challenges collaboratively. Furthermore, in order to enhance policy accountability and effectiveness, it is crucial to consolidate support details and performance outcomes while ensuring transparency through public disclosure.

- Amid intensifying competition for technological dominance, advanced countries are stepping up the reintroduction of targeted industrial policy to concentrate support in specific industries or firms.

- Korea provides substantial subsidies to firms through its national champion policy, but studies on its effectiveness remain limited.

- This study analyzes the effectiveness of Korea’s national champion policy and offers recommendations for improvement by comparing its operational approach with those of other countries.

- Korea’s flagship national champion policy program, World Class 300, provided targeted annual subsidies to 30~56 firms selected through a government-led process.

- The declining share of high-growth firms led to a large drop in the number of firms satisfying WC300’s sales growth criterion, making it harder to identify eligible firms.

- An analysis of WC300 outcomes reveals no significant impact on sales, value-added, or productivity, suggesting that resources may have been allocated to firms misaligned with the project’s objectives.

- Korea’s national champion policy aims to foster innovation and promote exports among SMEs to drive growth and job creation.

- However, concentrating resources on less competitive firms through selective support risks undermining economic efficiency and distorting market dynamics.

- Relational support is likely more effective than transactional support for high-potential firms.

- Effective business growth support requires tailored assistance that meets the diverse needs across the growth stages of individual firms rather than focusing on a single activity.

- The time has come for Korea to shift gears in its national champion

- To enhance the effectiveness of the national champion policy, its framework―including firm selection and support measures―should transition to a private-sector-led approach.

- Enhancing policy accountability and effectiveness requires centralized management of support details and performance data alongside transparent public disclosure.

- Given the low incentives for actively restructuring government support projects, institutionalizing independent evaluations is crucial for improving future outcomes.

- New policy initiatives should operate systematic pilot programs to enhance effectiveness.

Summary

Research Monograph KOR Economic Security and Strategies to Strengthen Supply Chains

On top of the US-China strategic competition, the COVID-19 pandemic, climate crisis, and rising geopolitical risks have pushed economic security and supply chain policies to the forefront of policy dialogue in South Korea. This study examines the factors behind the growing importance of economic security and response measures from geo-economic and traditional economics perspectives, along with analyses of case studies in key sectors. The primary aim of this research is to identify strategies to enhance Korea's economic security.

The policy directions regarding Korea’s economic security presented in this study are as follows: First, Korea should build upon its manufacturing capabilities in advanced industries and actively foster related cutting-edge technologies to secure strategic advantages. To achieve this, industrial policies should be more closely integrated, and supply chain vulnerabilities should be mitigated particularly by reducing dependence on China.

Second, simple localization or domestication of intermediate goods suppliers should be avoided. Instead, the Korean government should actively participate in international joint investment and R&D cooperation to support private-sector investments for diversifying supply chains.

Third, the strategy of large enterprises sharing technological know-how with small and medium-sized enterprises (SMEs) with similar technological development goals has been a key driver of Korea’s high localization rate and international competitiveness in the display industry. Therefore, in promoting the localization of advanced strategic sectors, the government should enhance support for improving the technological capabilities of domestic supply chain firms. Moreover, industry associations should establish various mechanisms and channels to strengthen collaboration between advanced industries firms and supply chain firms.

Fourth, a stable supply of mineral resources urgently requires investment in R&D, international cooperation, and the mobilization of financial resources for large-scale investments. Expanding R&D in mineral resource development technologies and leveraging these efforts as a platform for international cooperation should be prioritized. Additionally, concrete strategies for securing financial resources to support large-scale investments should be explored.

Fifth, when supply chain crises in advanced strategic industries pose risks that can potentially escalate to national crisis level, it is critical to consider adopting the 'emergency acquisition flexibilities' strategy used in defense material procurement. To this end, existing systems should be restructured to enable rapid procurement and response, ensuring greater resilience in times of crisis.

Sixth, to enhance the competitiveness of advanced strategic industries, priority should be placed on expanding power generation capacity through targeted investments in energy infrastructure. Simultaneously, measures such as connecting and expanding power grids, developing smart grids, and diversifying energy resources to improve efficiency should be pursued. As for water resource infrastructure, ensuring quantitative stability requires the multipurpose use of existing infrastructure, the activation of alternative water resources, and the construction of new water resource infrastructure. Additionally, strengthening technological capabilities through localization efforts is essential to securing a stable supply of ultrapure water.

Last but not least, prompt establishment and implementation of a national logistics strategy is required to adapt to changes in the global logistics network. This strategy should focus on securing overseas networks and global logistics hubs, as well as fostering globally competitive logistics companies, and enhancing adaptability to shifts in the logistics environment.

Summary

Research Monograph KOR Policy Strategies for Sustainable Regional Development

Rapid aging and low birth rates have sparked concerns over population extinction in some provinces, and fundamental questions have been raised over the sustainability of basic local governments and effectiveness of regional development systems. In particular, amid the swift progress in digital and new technologies, the accelerating pace of low growth has precipitated the need to enhance regional industrial competitiveness and build innovative growth engines more than ever before. Therefore, the research in this paper was conducted with the following in mind: ① determinants of the transfer of industries or companies; ② effects of the transfer of public regional development institutions; ③ differential factors of regional industrial diversification and innovation systems; ④ sustainability of local government finances; ⑤ measures to resolve the inconsistency between the administration and daily life, and strengthening the connectivity between cities and their surroundings; ⑥ housing policy measures for regional development.

Regional development policies must consider both fiscal efficiency and economic growth at the national level, and connect and cooperate with the central and local governments to narrow regional gaps and bolster uniqueness while enhancing the effectiveness of policies. This highlights a crucial point in Korea's regional development policy. Indeed, when the issues of low growth, aging, and regional gaps facing Korean society and economy are considered, an examination of the sustainability of regional development must first be conducted followed by a guarantee of sustainable growth in which finances are managed.

Accordingly, this study first identifies a strategy for industrial diversification that is effective for regional economic growth, and provides implications by dividing the local environment into the dimensions of industrial diversity and innovation capability. It is found that the diversity of industries can have a positive effect on regional development but the economic impact can vary according to industry. As such, the industrial characteristics and conditions of a region should be considered. Secondly, it is also shown that while the relocation of a company can positively effect employment and investment in the short-term, it can diminish its soundness and profitability in the long-term, and the possibility of survival and growth decreases; which has negative repercussions for regional development. Thirdly, the relocation of public institutions is found to have boosted employment in local manufacturing and services which relates to the improvement of settlement conditions. However, no significant effects were observed in the employment in knowledge-based industries suggesting that the main industry must be nurtured for the region to continue growing. Fourthly, an examination of the financial conditions of local governments confirms that, with the exception of Seoul, unsustainable fiscal operations were implemented in 2013-2018. Fifthly, a direction for the reorganization of administrative districts is suggested as metropolitanization could accelerate the decline of non-capital cities. Besides the linkage between administrative districts, it is also recommended that areas with declining populations identify the living area system and strengthen their connections with neighboring areas. And lastly, a direction for housing policy is also presented since an inflow into and concentration of the metropolitan area can exacerbate the polarization of asset prices and income by region. In particular, this paper proposes a shift from the jeonse-centered lease policy to a guaranteed monthly rent and in the policy direction to respond to the increase in vacant homes in the non-metropolitan area.

Summary

KDI Policy Forum Can Artificial Intelligence Improve the Effectiveness of Government Support Policies?

■ Despite high hopes for artificial intelligence (AI) to generate powerful innovations across the public sphere backed by its strong prediction skills, Korea has not fully brought the technologies into the public sector in tasks like identifying policy target groups and managing follow-up tasks in line with its policy objectives.

- Recent cases of AI-applied public services in Korea show limited usage, mainly replacing simple repetitive tasks.

- Few leading countries are trying to apply AI-based analysis to select promising policy target groups to effectively achieve policy goals and follow up on the performance of public projects.

- While the existing management system for policy performance is mostly about ex-post assessment of project outcomes, the application of AI technologies signifies a shift to data-driven decision-making that uses ex-ante forecasts of policy effects.

■ An analysis of AI-applied recipient selection of small and medium enterprise (SME) policy support programs demonstrated the efficiency of AI in predicting the performance of beneficiary firms after the program and AI's potential to significantly improve the effectiveness of public support by providing helpful information in screening out unfit SMEs.

- Using firm-level data, this study applies machine learning to various public financing programs (subsidies or loans for SMEs) funded by the Ministry of SMEs and Startups and finds that AI helps predict the growth of recipient firms in the years following policy support.

- The application of AI in identifying fitting recipients likely to achieve intended objectives may increase project effectiveness.

■ In a KDI survey in 2020, respondents pointed out that what hinders transitioning into a system of AI-applied, data-driven policymaking in the public sector are: 1) incomplete standardization and linkage of policy information between governmental ministries and 2) lack of expertise in technology utilization in the public sector.

■ By developing a strategy to propel a transition into data-driven policymaking in the public sector, coordinated national-level efforts must be made to heighten policy effectiveness across different public fields, including education, health care, public safety, national defense, and business support.

- One way to adopt AI technologies in the public sector is by designing a policy to support technology adoption for competent public institutions. Support measures may cover system, data platform, security, organizational consulting, training, etc.

- Detailed strategies are: 1) unifying existing data management systems into one single platform, 2) reorganizing the way government work gets done to enable efficient exchange of policy information, and 3) building a trust-based public-private partnership.

- By examining the policy cycle from planning and implementation to evaluation, it is important to clarify areas for AI to contribute to policy decision-making. Also, the government needs step-by-step strategies toward data-driven policymaking, such as setting clear project objectives, selecting and sharing data, establishing system and security, and promoting operational transparency.

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