The study examines methodologies for quantitatively analyzing the impact of global supply chain fragmentation and applies these approaches to scenarios involving critical minerals. It identifies two primary analytical approaches: microeconomic and macroeconomic.

Microeconomic methods provide detailed insights at the item or firm level but face challenges due to limited access to specific supply chain data. Macroeconomic methods, while suitable for industry- or national-level analysis, often rely on unrealistic assumptions when applied to item-level fragmentation. Despite the significant macroeconomic effects of disruptions in critical supply chains, existing item-level analysis techniques struggle to capture these impacts accurately. For instance, efforts to link item-level analysis with GDP using linear programming or inoperability input-output analysis often encounter limitations due to rigid assumptions about input-output structures. High-tech items, in particular, pose challenges due to their complex supply chain interdependencies and their significant influence on final production.

To address these issues, the study proposes an integrated methodology combining machine learning techniques for microeconomic analysis with the OECD METRO model for macroeconomic evaluation. This approach considers key issues and transmission channels identified in previous research. The study also reviews critical mineral management policies in major economies such as the United States, European Union, China, and Korea. The United States identifies critical minerals essential for economic and national security through legislative measures like the 2020 Energy Act and has implemented strategies to strengthen North American supply chain resilience. The European Union has updated its critical raw materials list every three years since 2008 and enacted the Critical Raw Materials Act in 2024 to expand production capacity and enhance international cooperation. China, despite lacking a clear legal definition of critical minerals, strengthens its resource management through export controls and cooperation with resource-rich countries. Korea designated 33 minerals as critical through its 2023 Critical Minerals Securing Strategy, prioritizing 10 strategic minerals essential for industries like electric vehicles and semiconductors. However, Korea’s reliance on imports for most critical minerals highlights its vulnerability.

The study conducts a vulnerability analysis of Korea’s critical mineral supply chains using indicators such as the Trade Specialization Index (TSI) and Herfindahl-Hirschman Index (HHI). It identifies high global supply chain concentration in minerals like cobalt, lithium, and neodymium, which are crucial for secondary batteries and electric vehicles. To assess geopolitical risks, it examines import trends from China across seven countries from 2017 to 2023. Sharp declines in imports of gallium, graphite, and rare earth elements suggest potential disruptions due to trade conflicts or export controls.

The study employs a Dual-Stage Attention-Based Recurrent Neural Network (DA-RNN) model to predict the impact of critical mineral fragmentation on Korea’s exports of key items like batteries and semiconductors under three scenarios involving germanium, graphite, and rare earth elements. The results show significant decreases in export values across all scenarios. For example, restrictions on germanium imports led to a 3.9% decline in battery exports, while rare earth element shortages caused a 10.8% drop.

Using the OECD METRO model, the study evaluates the macroeconomic impact of critical mineral fragmentation under two approaches: direct analysis of import disruptions (Approach 1) and integration of microeconomic results into macroeconomic simulations (Approach 2). The findings indicate that germanium fragmentation could reduce Korea’s real GDP by 0.15%, while graphite and rare earth element disruptions could lead to decreases of 0.14% and 0.89%, respectively.

Based on these findings, the study recommends strengthening supply chain monitoring systems by integrating fragmented platforms across government agencies and establishing a centralized control tower. It also suggests diversifying procurement strategies, promoting R&D for substitute materials, and supporting SMEs through digital-based supply chain management platforms. Additionally, it emphasizes harmonizing policies with major economies to prevent over-securitization and redundant investments while expanding international cooperation for joint mineral exploration and development projects.

This study examines Japan’s labor shortage, tracing it from cyclical tightness in the early 1970s and the late-1980s/early-1990s bubble to a structural shortfall since the mid-2010s driven by the sustained contraction of the working-age population. Earlier episodes were demand-led and policy-induced (for example, the transition to a 40-hour work week), whereas today’s tightness is demographic in origin and therefore persistent. Chapter 2 details these dynamics and the underlying structural constraints.

To manage this challenge, Japan’s policy response combines mobilization of domestic labor—most notably rising participation by women and older workers—with an expanded intake of foreign workers. The foreign-resident population grew from roughly 2.09 million in 2014 to about 3.59 million in 2024, with rapid increases in Technical Intern Trainees and Specified Skilled Workers. These increases reflect domestic drivers—population aging and acute shortages in care, hospitality, construction, etc.—as well as international forces, including a surge in Asia-centered labor migration and policy shifts. Chapter 3 assesses Japan's policy efforts to engage women and older workers into the labor market, while Chapter 4 reviews the theory, history, and practice of international labor migration in Asia. Chapter 5 disaggregates Japan’s foreign-worker regime into three pillars—high-skilled channels, the Technical Intern Training Program, and the Specified Skilled Worker system—and evaluates their policy design, outcomes, and outstanding issues. Chapter 6 assesses integration through wages and social-insurance coverage as indicators of how well foreign workers are settling into Japanese labor markets and society.

This study sets out the following policy implications for Korea. For older workers, Japan’s experience shows the effectiveness of gradual, sequenced reform—phased extensions of employment guarantees—backed by targeted subsidies, sustained social dialogue, and flexible compliance options for firms. Firm-level transparency and action plans, combined with workplace redesign, childcare provision, and well-targeted grants, have helped lift women’s participation. On foreign workers, Japan and Korea should streamline its fragmented governance and build a more efficient architecture for lower-skilled pathways, with clear skill-progression ladders that link training and language support to advancement in wages and roles. Korea should also better leverage international students by smoothing school-to-work transitions and strengthening settlement support. Finally, Japan and Korea could co-lead rules-based cooperation with major sending countries to stabilize flows and alleviate persistent shortages.

Foreword

Part 1 Key Policies for Open Strategic Autonomy
01. The Evolution of South Korea’s Economic Security Strategy | Seungjoo Lee |
02. Partners Under Pressure: Strengthening Dutch-South Korean Economic Security Amid a Fractious Indo-Pacific | Richard Ghiasy |
03. Toward a Strategic Partnership in Science and Technology between Korea and the Netherlands | Myong Hwa Lee |
04. Cooperation on Control Points is Needed for Strategic Autonomy | Joris Vierhout, Amber Geurts |

Part 2 Key Technologies for Open Strategic Autonomy
01. Korea–Netherlands Cooperation Agenda for Advanced AI Semiconductor R&D | Seokjoon Kwon |
02. Quantum Technology as a New Frontier of Cooperation: NL-ROK Partnership Opportunities | Anna Grashuis, Ingrid Romijn, Ulrich Mans, Mayra van Houts |
03. ROK-NL Strategic Cooperation in Energy Security | Sunghun Cho |
04. Key technologies for Open Strategic Autonomy in Korea and the Netherlands: Critical Raw Materials for Defense | Irina Patrahau, Benedetta Girardi |

Conclusion and Policy Recommendations

As has recently been observed, the global economic order is undergoing a profound transformation. The intensifying geopolitical rivalry among great powers, the retreat from multilateralism, the resurgence of protectionist policies, and the weaponization of trade and technology have shaken the foundation of the open and inclusive global economic order, which has been around for a long period. These changes underscore the growing importance of technological leadership, secure supply chains, and resilient industrial ecosystems in shaping the economic security and strategic autonomy of individual nations. However, pursuing security and autonomy does not mean isolation. Ironically, the necessity for like-minded countries to cooperate has never been greater, as no single nation can cope alone with the shift in the global economic order.

The Republic of Korea and the Netherlands, as middle powers and trading nations, share a deep interest in preserving the stability, openness, and resilience of the global economy, which ultimately contribute to the prosperity of all participating countries. South Korea, for example, has long been a globalized manufacturing power house, heavily relying on global value chains to support its growth. However, a series of shocks, including China’s economic retaliation over THAAD, Japan’s export controls, the COVID-19 pandemic, and US–China technology competition, revealed structural vulnerabilities of Korea’s export-oriented economy. Korea’s new economic security strategy, as detailed in this volume, reflects efforts to reconcile its position as an export leader and an import-dependent economy. Similarly, the Netherlands, one of Europe’s most open trading nations, faces the challenge of mitigating risks while preserving openness. The country positions itself as a logistics hub, a high-tech innovator, and a host of globally competitive firms such as ASML. As the European Union attempts to lower its external dependencies in strategic sectors, the Netherlands plays a significant role in shaping Europe’s economic security agenda.

Against this backdrop, Korea and the Netherlands emerge as natural partners. Their complementary strengths in semiconductors, advanced manufacturing, quantum technology, and clean energy transition can create opportunities for them to build resilient supply chains and shape global standards jointly. Their partnership also aligns with broader Indo-Pacific regional frameworks, including the EU–Korea Strategic Partnership and the international component of Horizon Europe, positioning both countries to contribute to a stable, rules-based global order.

This edited volume, “Industrial Open Strategic Autonomy in the Indo-Pacific: Focusing on High-tech Industrial Innovation and Supply Chain Security”, examines how Korea and the Netherlands can deepen their cooperation across key policy areas and critical technologies to advance open strategic autonomy. Drawing on contributions from leading experts, the volume is organized into two parts. Part I analyzes the policy foundations of economic security and strategic autonomy and Part II explores the technological domains essential to achieving these goals. Based on the authors’ in-depth analyses, three main recommendations for ROK-Netherlands cooperaion on open strategic autonomy are suggested: first, establish a shared economic security foresight mechanism. Third, coordinate sustainable supply chain resilience. Third, coordinate sustainable supply chain resilience.

Executive Summary

1. Introduction

2. Model

3. Data and Calibration

4. Assessing Debt Sustainability in the APEC Economies

5. Conclusion

References

Appendix
A. OLG Model and Calibration
B. Dynamics of the Debt-to-GDP Ratio
C. Additional Tables

In this paper, we estimate additional government expenditure used to reduce AI’s existential risk and assess public debt sustainability. Our most important policy-relevant finding is that even under the conservative assumption that government expenditure equals the maximum amount society is willing to sacrifice to mitigate AI risk, and that all such expenditure is financed by issuing sovereign bonds rather than raising taxes, government debt does not necessarily become explosive. Instead, in our benchmark scenario—where the growth-enhancing effect of AI is calibrated to the average of prior studies—the debt ratio remains sustainable for most APEC economies. We also find that, except for Russia, an additional AI-driven growth effect of 3.4–6.1% would suffice for debt financing to remain sustainable for many APEC economies. In particular, for the United States, the required effect is 3.8% or 4.6%, depending on parameter assumptions. For faster growing economies such as China and Korea, the required additional effect is even smaller than for the United States.

Executive Summary

1. Introduction

2. Informal Economy and Composition of ODA in the Philippines

3. Model

4. Macroeconomic Equilibrium

5. Results

6. Conclusion

References

We analyze how the size and composition of official development assistance (ODA) shape aggregate performance and informality in the Philippines using a small open-economy dynamic general equilibrium model with a formal and informal sector. Two main scenarios are considered: (i) an increase in total ODA and (ii) a higher share of tied aid, given a fixed amount of ODA. Both scenarios raise capital, output, and consumption in steady state, but through distinct mechanisms. The first scenario primarily increases demand and appreciates the relative price of informal goods, expanding informality. By contrast, the second scenario expands public capital, crowds in formal investment, lowers the relative price of informal good, and shifts resources toward the formal sector, despite short-run reallocation costs.

Executive Summary

1. Introduction

2. Theoretical Framework

3. Data

4. Methodology

5. Results

6. Discussion

7. Conclusion

References

Appendix

This paper investigates how environmental, social, and governance (ESG) conditions, together with economic factors, shape fertility dynamics in APEC economies. Using World Development Indicators from 1996 to 2021 and assembling more than 1,400 indicators, we predict annual changes in the crude birth rate. Models are trained on non-APEC economies and tested out of sample on APEC economies. Random Forest achieves the lowest RMSE at 0.397, and models that combine ESG and economic variables outperform those relying on economic indicators alone, with RMSE values of 0.271 and 0.298 respectively. SHapley Additive Explanations (SHAP) reveal that environmental factors are the most influential predictors of fertility in APEC, followed by governance, while social factors are smaller in magnitude but show increasing importance over time. Lag analysis indicates short-run effects for social and governance variables at one-year lags and medium- term cumulative effects for environmental variables, peaking around four years. Country-level profiles highlight clear heterogeneity: environmental drivers dominate in China and Russia, governance factors are most important in Korea and the United States, and social influences are stronger in Canada and Japan. The study provides a comprehensive, externally validated, and interpretable framework for fertility prediction, while emphasizing that the analysis remains predictive and associational rather than causal. We regard this as a first step toward more rigorous causal evaluation of the highlighted drivers.

The importance of tariff measures in recent international trade has been highlighted again with the universal tariffs and reciprocal tariffs of the second Trump administration in the United States, as well as the retaliatory tariffs from trade partners. Interest in their economic effects is growing day by day. To properly analyze these economic effects, it is essential to accurately estimate the tariff elasticity of trade. This study comprehensively analyzes the main content of previous researches on the tariff elasticity of trade through a literature review, presenting various theoretical grounds and analytical methodologies. We applied these to Korea’s 2014 import clearance data to empirically estimate tariff elasticity. The main contents and analysis results of this study are as follows.

First, this study introduces the basic theoretical model of Fontagné et al. (2022) and derives an equation to estimate tariff elasticity. According to this, the tariff elasticity of trade can be estimated by the elasticity of substitution between items. If a consumer can easily substitute another product when the tariff of a specific product rises, the import of that product is expected to decrease more actively.

Second, this study suggests the possibility of developing a more realistic model based on the basic theoretical model of Fontagné et al. (2022). Particularly, the development of theoretical models and empirical analysis strategies that appropriately reflect other factors affecting tariff elasticity in addition to the elasticity of substitution between items is necessary. These suggestions can be categorized into 1) the level of hierarchy in the CES utility function, 2) consideration of the export supply function, 3) the possibility of partial pass-through, 4) consideration of other trade costs, 5) resolution of endogeneity issues, and 6) consideration of the customs valuation.

Third, this study investigated several empirical analysis studies on the tariff elasticity of trade. The results showed that the estimated value of tariff elasticity of trade ranged from an absolute value of 2.5 to 5.1 on average, but the variance was quite large depending on the sample, data characteristics, and analysis methodology. By country characteristics, it was confirmed that the greater the market dominance of the importing country, and when the exporting country is a developed country, the smaller the tariff elasticity of trade. Also, tariff elasticity was relatively large when there was a bilateral trade agreement, but smaller in cases of past colonial relationships, large price gaps, or great geographical distances. By industry and item characteristics, homogeneous and standardized products such as agricultural and mineral products had higher tariff elasticity, while heterogeneous products like machinery and textiles had lower tariff elasticity. In terms of industrial structure, the higher the use and diversity of intermediate goods, the greater the productivity differences between items within the industry, and the more products traded on regular exchanges, the higher the tariff elasticity of trade. Regarding market competitiveness and structure, the more intense the market competitiveness, the higher the tariff elasticity, but items with larger profit margins had lower tariff elasticity. It was also confirmed that various non-price competitive factors such as technological advantages and brand awareness were important. By firm characteristics, tariff elasticity of trade was greater when strategic complementarity between firms was high but smaller when firm productivity was high. Regarding data characteristics, the finer the aggregation level of item classification, the greater the tariff elasticity appeared. It was also confirmed that the analysis period and scope, data source, and consideration of proxy variables could also affect changes in estimated tariff elasticity.

Fourth, this study applied these discussions to the quarterly HS 6-digit import clearance data of Korea in 2014 to estimate tariff elasticity. The empirical analysis methodology mainly considered the Poisson Pseudo- Maximum Likelihood (PPML) estimation based on the structural gravity equation. The empirical analysis results estimated the absolute value of tariff elasticity to be about 5 to 10, confirming it to be similar to existing previous studies. However, it was found that the estimated tariff elasticity significantly differed statistically depending on the aggregation unit of the product, and the pattern of difference varied according to the setting of fixed effects. By product characteristics, the tariff elasticity of consumer goods was the highest, followed by intermediate goods and capital goods. By product group, the tariff elasticity of homogeneous items such as mineral products was estimated to be very large with an absolute value of 10 or more, but statistically significant elasticity was not observed in some product groups such as stone and ceramics. To verify the robustness of the main analysis results, both the log-linear equation and asymptotic bias-corrected PPML estimation method were applied, but the analysis results were qualitatively similar and statistically significant consistently.

Based on these analysis results, this study draws the following implications. First, the government should manage and pay close attention to the elasticity of substitution between similar products when establishing tariff policies. In particular, since the elasticity of substitution varies by industry and item, tailored tariff policies that consider the characteristics and substitutability of each industry and item are necessary. Especially for homogeneous products like agricultural and mineral products, meticulous policy design is required as they are sensitive to tariff changes. Second, the government should consider various factors in addition to the elasticity of substitution when establishing tariff policies, including economic and political relations with trade partners, strategic behavior of related firms, and market competition structure. Comprehensive consideration of these variables becomes a prerequisite for the government to design more effective and sustainable tariff and response measures. Third, when estimating tariff elasticity as a basis for policy, the aggregation method of data is crucial. In particular, it is important to divide the data in detail by item rather than total data to design the correct policy. Fourth, in analysis methodology, appropriate fixed effects should be selected by fully considering the analysis purpose and data characteristics. Fifth, when establishing and evaluating trade policies, careful consideration of other trade costs, such as freight insurance rates, in addition to tariffs is necessary. Lastly, regarding empirical analysis techniques for estimating tariff elasticity of trade, it is proposed that the general PPML estimation method is a sufficiently reliable and valid approach for analyzing tariff elasticity.

Since the inauguration of Trump’s second term, U.S. trade policy has triggered profound changes in the global trading order. The United States, prioritizing the prevention of illegal immigration and drug trafficking as matters of national security, has implemented stringent trade measures such as the imposition of high tariffs and the renegotiation of bilateral agreements. These policies have amplified uncertainty across the external environment of Latin America, including Mexico and Brazil. The recent U.S. decision to impose a 50 percent retaliatory tariff on Brazilian products starkly illustrates the vulnerability of Latin American trade to policy volatility. Against this backdrop, the upcoming USMCA renegotiation in July 2026 is likely to become another critical variable for the region’s external relations and supply chain configuration.

Despite the rising geopolitical and geoeconomic importance of Latin America, the region remains relatively marginal within Korea’s trade strategy. Yet, the ascent of the Global South, the restructuring of supply chains, and the diversification of trade partners underscore Latin America’s growing strategic value and the urgency for Korea to pursue proactive and long-term policy responses.

In this context, Japan’s experience in Latin America provides meaningful insights for Korea. Japan has consolidated its presence by focusing on traditional manufacturing sectors such as automobiles, machinery, and chemicals, establishing dual hubs in Mexico and Brazil while simultaneously diversifying into markets such as Argentina and Chile. Japanese firms have strengthened localization strategies by responding proactively to policy changes, including Brazil’s “Mover” program and Mexico’s environmental regulations. In the resource sector, Japan has sought stable access to critical minerals such as lithium and copper through close government–business collaboration, supported by financial and policy instruments that helped mitigate risks.

This study investigates Japan’s industry- and period-specific entry cases and government support policies to derive policy implications for Korea’s Latin America strategy. The key recommendations are as follows:
First, strengthen government–business linkages to institutionalize supply chain restructuring support.

Second, emphasize reference-building at the initial stage of entry to establish a foundation for long-term growth.

Third, respond proactively to environmental and regulatory changes to build trust with local governments and turn compliance into a source of competitive advantage.

Fourth, maintain a Brazil–Mexico-centered strategy while expanding into Argentina, Chile, and Colombia to diversify regional risks.

Fifth, explore opportunities for joint ventures with Japan, particularly in strategic sectors such as minerals.

In sum, Japan’s experience highlights essential lessons for Korea to achieve stable and sustainable outcomes in Latin America under conditions of global trade uncertainty. Rather than merely replicating Japan’s approach, Korea should design tailored strategies that reflect the specific characteristics of Korean firms and the diverse demands of Latin American economies.

This study comprehensively analyzes cross-border investment and spillover effects of artificial intelligence (AI) technology in the era of the 21st century’s paradigm shift toward an intangible asset-centered economy, and proposes policy directions for enhancing Korea’s AI industrial competitiveness. The research particularly focuses on exploring effective response strategies that technology-follower countries like Korea can adopt in a situation where global AI investment is extremely concentrated in the United States and China.

Examining the research background, the proportion of intangible assets in the market value of major global companies has surged from 17% in 1975 to 90% in 2020, with global AI investment reaching approximately $252.3 billion in 2024, a 17-fold increase from 2013. However, while the United States accounts for over 60% of global AI investment, Korea represents merely 1.5-2.0%, revealing an extreme polarization of technological hegemony with 93% of AI-related patents concentrated in the US and China. In this context, although Korea possesses successful technology catch-up experience in manufacturing sectors from the past, the AI era’s technological competition presents fundamentally different challenges due to the characteristics of intangible assets—high initial development costs and near-zero marginal production costs.

Starting from this problem awareness, this study systematically conducted historical experience analysis, global AI investment status surveys, theoretical model construction, and empirical analysis using the GVAR model. Analysis of Korea’s past technology spillover experiences revealed that Samsung Electronics’ case of overcoming a 5.5-year technology gap in the memory semiconductor sector demonstrated the importance of systematic technology partnerships and continuous R&D investment. In the IT hardware sector, economic benefits related to productivity improvement increased approximately 3.7-fold from 76.4 trillion won to 286.4 trillion won during the 2000-2005 period.

Through theoretical model analysis, the study confirmed that when intangible asset investment spillovers occur from technology-leading countries to technology-adopting countries, the adopting countries can achieve higher utility while investing less. Furthermore, under an appropriate spillover royalty system, benefits can accrue to both leading and adopting countries; however, the findings suggest that adopting countries need to maintain continuous intangible asset investment to prepare for potential spillover cessation by leading countries due to narrowing technology gaps.

The empirical analysis using the GVAR model yielded particularly noteworthy results. When Korea experienced an AI-related FDI outflow shock, domestic real GDP increased by 0.33%, while FDI inflow shocks resulted in only a 0.19% increase, confirming that technology acquisition through overseas investment may show stronger economic correlations. Stock indices showed a positive response of 0.75% to FDI outflow shocks and a negative response of -1.61% to FDI inflow shocks, indicating that markets tend to positively evaluate overseas AI investment from the perspective of securing future competitiveness.

Synthesizing these analytical results, this study presents the following policy implications. First, considering that overseas AI investment shows stronger economic correlations than domestic investment attraction, it is necessary to establish an institutional foundation that supports Korean companies’ investments and joint ventures with global AI companies and facilitates the return of acquired technology and talent to Korea. Second, given the 83-fold investment gap with the United States, rather than competing in all AI fields, a strategy of selection and concentration in specific areas such as AI hardware-software convergence that leverages Korea’s strengths in manufacturing and IT hardware capabilities is required. Third, while effectively utilizing technology spillovers, Korea must maintain an appropriate level of independent intangible asset investment to prepare for potential technology blockades by leading countries. Fourth, Korea should pursue a balance between international cooperation and independent innovation by strengthening partnerships with the United States while also participating in the establishment of AI technology cooperation networks within the Northeast Asian region.

In conclusion, this study suggests that for Korea to bridge the technology gap in the AI era and secure sustainable competitiveness, it needs to reinterpret past success patterns to fit the characteristics of the AI era and adopt a differentiated approach through selection and concentration. Particularly, an integrated strategy linking technology acquisition through overseas investment with the construction of a domestic innovation ecosystem is required, along with the establishment of a flexible policy framework capable of responding to the rapidly changing global AI technology environment.

Executive Summary

1. Introduction

2. Data

3. The Model

4. Qualitative properties

5. Numerical Simulation

6. Conclusion

Appendix

References

Digital platforms have become central to modern economies, as consumers increasingly spend leisure time online and platform firms transform user engagement into economic value. This study develops a multi-country, multi-industry open economy general equilibrium model to analyze how web traffic—measured as visits to platform domains—can be converted into “data capital” through big data and AI algorithms and then used as a non-rival input for production and innovation.

To ground the analysis, we construct a new dataset that links domain-level web traffic to corporate ownership across countries. The evidence reveals sharp cross country differences in the geographic origin of users. U.S. platforms attract a strongly international audience, with domestic users accounting for less than one-third of visits on average. Chinese platforms are more domestically concentrated, though TikTok stands out as a global exception with a highly international user base. Korean platforms, by contrast, rely overwhelmingly on domestic users, with less than ten percent of traffic originating abroad. Comparing these patterns with international service trade statistics, we find that countries with higher shares of foreign users are systematically more active in exporting online services.

Qualitative analysis provides further insight into user behavior. Consumers allocate more time to a platform when they experience greater content satisfaction, which depends on both technological quality and country-specific content preferences. When the quality of foreign platform content improves, consumers reallocate time away from domestic platforms toward foreign ones. The extent of this shift is influenced by the elasticity of leisure demand, the substitutability across platforms, and the share of time already devoted to foreign platforms.

The general equilibrium model allows us to simulate counterfactual scenarios and evaluate policy-relevant outcomes. Reducing cross-border frictions to foreign content raises welfare in all countries, primarily through the expansion of content variety and the reallocation of consumer time, while leaving the broader industrial structure largely unchanged. Lowering barriers faced by foreign platforms, such as discriminatory digital services taxes, increases platform revenues, encourages consumers to spend more leisure time online, and strengthens investment incentives for domestic platforms. Although the immediate welfare gains are modest, the longer-run effects on intangible investment and innovation are more significant. Enhancing the productivity of platform R&D generates asymmetric effects by expanding platform activity in the innovating country and reducing it in the non innovating country, yet global welfare increases because users everywhere benefit from improved content quality and diversity.

Taken together, the findings highlight that the accumulation of web-traffic-based data capital is a central driver of platform growth. Policies that improve access to foreign content, the taxation of digital services, and foster innovation in platform R&D directly influence how consumer time is allocated and how platform firms invest in data-driven growth. For policymakers, the results suggest that lowering barriers to cross-border online activity can deliver substantial welfare gains, that digital taxation should be carefully designed to balance fiscal and innovation objectives, and that investment in platform R&D is essential for competitiveness in the global digital economy.

In sum, this study demonstrates that digital platforms thrive not only on technological progress but also on the ability to accumulate and deploy data capital derived from web traffic. Recognizing the economic role of data capital is crucial for designing effective policies in the digital era, where market access, taxation, and innovation shape the international competitiveness of platform industries.