## 1. Definition of the High-Tech Sector

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---

### Overview and statistical definition
- Uses Eurostat’s sectoral-level classification of high- and medium-high-tech manufacturing and high-tech knowledge-intensive services (see Appendix I).
- Covers advanced export-oriented activities—semiconductors, pharmaceuticals, photonics, aerospace—alongside knowledge-intensive services in ICT, software, and professional and scientific activities.
- Statistical scope includes NACE Rev. 2 codes for high and medium-high tech industries and high-tech knowledge-intensive services (Appendix I note).

### Importance, composition, and performance
- Sectoral composition and concentration:
  - High-tech sectors together account for about 11 percent of total gross value added and 6 percent of employment.
  - High-tech manufacturing concentrated in machinery and equipment, led by lithography machines production and its supplier network.
  - Computing, programming, and IT consulting dominate high-tech knowledge-intensive services.
- Growth and market valuation:
  - High-tech subsectors—especially pharmaceuticals, machinery and equipment, and advanced manufacturing—have recorded stronger growth in gross value added (GVA) and labor productivity than the overall economy (Figure 2).
  - Between 2014 and 2025, the market capitalization of listed Dutch high-tech firms grew faster than in the U.S. and China, albeit from a much smaller base.
  - Market data covers 33 listed companies for the Netherlands, 2,251 for China, and 1,036 for US (as of 2025).
  - One leading semiconductor equipment company accounted for about 60 percent of listed Dutch high-tech market capitalization at end-2025.

### Deep integration in global value chains (GVCs) and intangibles
- Netherlands ranks high among leading EU economies in domestic value added embodied in foreign high-tech exports; this share has risen faster than in peers over time.
- Netherlands' global exporter rank for high-tech value added: 14th.
- High-tech GVA relative to the U.S. recovered after 2015 and has been broadly stable; the post-2015 recovery was mainly driven by medium-high tech manufacturing.
- Intangible assets:
  - Medium-high-tech industries, notably electrical and machinery equipment, exhibit a relative advantage in intangible assets; intangible assets in high-tech KIS remain broadly in line with peers.

### GVC-related vulnerabilities and exposure channels
- Two-sided vulnerabilities from foreign-input and foreign-demand exposures:
  - Backward linkages:
    - Foreign value added has exceeded one-third of high-tech exports in recent years and remains above the EU median.
    - Chemicals and pharmaceuticals show the highest foreign value added in exports; machinery, equipment, and electronics display meaningful backward linkages; high-tech KIS have lower direct foreign-input exposure but remain indirectly exposed through links to manufacturing.
    - A decomposition for 2010–2022: services remain largely domestic while manufacturing relies more heavily on foreign inputs; computer, electronic, and electrical equipment show a marked decline in domestic value-added share with a rising share of China.
  - Forward linkages:
    - Exposure to foreign final demand is high—60 percent of sectoral value added—and concentrated in a few markets.
    - Key downstream markets: Germany, the U.S., and China; Germany is a key downstream market for machinery, semiconductors, and lithography-related inputs; the U.S. and China are major markets for electronics and other high-tech goods.
- Channels of vulnerability:
  - Geoeconomic fragmentation and trade restrictions (export controls, subsidies, security-driven policies).
  - Strategic input chokepoints in advanced materials, chemical technology, electronics, energy technologies, and defense.
  - Production relocation risk induced by foreign subsidies, faster permitting, lower energy costs, or targeted industrial-policy packages.
  - Dependence on non-EU capital and acquisition-led exits risking relocation of control, IP, and production.
- Since COVID-19, supply disruptions have become larger, more persistent, and more frequent.

### Assessment framework and methodology (illustrative simulations)
- Two GVC-related vulnerability channels examined: disruptions to access to foreign inputs and to external demand.
- Critical product categories mapped to high-tech manufacturing sectors and weighed by supplier concentration using the Herfindahl–Hirschman Index.
- Linkages traced through input–output relationships to estimate structural output at risk under a stylized two-sided disruption involving key partners.
- Model specifics and caveats:
  - Uses a tractable input–output model augmented with international trade data and inter-country input–output tables (Appendix III).
  - Broadly consistent with Bonam et al. (2026) and related literature.
  - Results are illustrative structural output at risk, not forecasts or point estimates; framework abstracts from behavioral relationships, substitution, inventories, price responses, policy adjustment, and broader macroeconomic effects.
  - Scope distinctions: direct supply exposures assessed for goods trade; high-tech services captured through foreign-demand channels and indirect links to goods-producing sectors.

### Domestic policy implications highlighted
- Sustaining high-tech leadership will require:
  - Easing domestic bottlenecks (labor, grid capacity, permitting, scale-up finance).
  - Leveraging deeper EU integration to support scaling.
  - Strengthening resilience to GVC disruptions and geoeconomic fragmentation.

---

### Illustrative simulations of a 50 percent bilateral trade disruption shock

### Simulations — headline results
- Vulnerability measured as total loss as a percent of gross output under a 50 percent disruption of bilateral trade.
- Sizable output at risk, especially in chemicals, machinery and electronics and electrical equipment (Figure 4, left chart).
- Exposure is best read as a ranking of relative exposure across sectors and partners, rather than as estimates of likely output losses.
- Model type: partial-equilibrium, open-economy input–output framework measuring structural exposure of Dutch high-tech sectors to bilateral (not global) supply and demand disruptions with key partners without any consideration for global macro-economic effects.

### Exposure channels and quantitative contributions
- Exposure is largely supply-driven (almost half of total vulnerability), reflecting reliance on foreign inputs and concentrated supplier bases for specialized components including semiconductor-related inputs, lithography equipment components, and rare earth elements.
- Demand-side exposure contributes around 30 percentage points to risks in most manufacturing sectors.
- Indirect input–output linkages amplify initial shocks by slightly more than 20 percentage points in the most exposed sectors.
- Exception: Other transport equipment is more closely associated with demand concentration and a narrower set of export markets.
- No direct supply effects identified for sectors C29 (motor vehicles) and C30 (other transport equipment), as none of the critical inputs used in the analysis are sourced from these sectors.

### Sectoral and partner concentration
- High-tech KIS show limited direct vulnerability but remain exposed through indirect effects from domestic production linkages.
- U.S. is the single largest source of exposure for electrical equipment and electronics, chemicals and machinery.
- China is the second-largest contributor in most manufacturing sectors, particularly electronics and chemicals.
- Germany contributes notably in machinery, motor vehicles, and aerospace.
- South Korea's contribution concentrated in electronics; France mainly present in aerospace value-chain links.
- Key trading partners identified: China, U.S., Germany, Korea, and France.

### Nonfinancial bottlenecks — overview
- Structural bottlenecks constrain investment, scaling, and diffusion: labor and skill shortages, grid congestion, regulatory constraints, and later-stage scale-up finance frictions.
- Constraints most binding for capital- and infrastructure-intensive activities; knowledge-based activities are less directly affected.

### Labor shortages and skills
- Labor shortages remain one of the main obstacles in high-tech sectors, especially high-tech KIS, and rank second in medium-high-tech manufacturing after insufficient demand (Figure 5).
- Firms responding by adopting automation (robotization and AI-based solutions), particularly in high-tech KIS.
- STEM enrollment remains below peer levels.
- Analysis based on ESJS wave 2 (2021) with sample covering eight countries (AT, BE, DE, DK, FI, FR, NL, and SE).

### Electricity grid congestion and nitrogen constraints
- Electricity grid congestion is becoming a binding constraint on high-tech investment, electrification, and industrial expansion, particularly in Noord‑Brabant and Limburg.
- Long connection queues and uncertainty over future access are delaying factory expansions, electricity-intensive production lines, and on-site renewable generation and battery storage.
- Policy efforts should prioritize accelerating permitting and delivery of network upgrades, greater demand flexibility, storage, and energy-efficiency measures to ease near-term pressures.
- Nitrogen deposition exceeded critical loads across about 70 percent of Natura 2000 area as of 2023, leaving little room for new projects without breaching environmental thresholds.
- A 2024 Council of State ruling further limited the use of nitrogen headroom within existing permits.
- Fragmented responsibilities across municipal, provincial, and national authorities add delays and uncertainty for projects requiring multiple permits or located near protected areas.

### Permitting, regulation, and EU fragmentation
- Obtaining an industrial building permit can take an estimated 20–39 months from preparation through appeals, with objection and appeal procedures alone accounting for 10–23 months.
- Pending spatial-planning cases before the Council of State have more than doubled since 2020.
- Example of rapid delivery: Eemshaven LNG terminal permitting and construction took only 200 days when prioritized and coordinated across government levels.
- EU internal market fragmentation is structural for some ecosystems (medical and biotech, digital and ICT, defense and security) and can limit scaling within Europe.
- Regulatory fragmentation examples:
  - Overlapping EU frameworks (AI Act, GDPR, Data Act, DSA/DMA, NIS2) increase compliance costs for digital and AI activities.
  - 27 (divergent) export-control and dual-use regimes in EU raise costs and complicate semiconductor and dual-use exports within EU.
  - 27 national reimbursement regimes in EU restrict Dutch pharma market access.

### Gaps in access to finance for high-tech firms
- Startup funding ecosystem: strong but fragmented.
- Early-stage funding:
  - Seed and other early-stage VC investment was 0.07 percent of GDP in 2025, twice as high as in France, Germany, and Belgium, and on par with Sweden (0.1 percent of GDP).
  - Seed and other early-stage funding was 4 times higher in the US, at 0.29 percent of GDP.
- Later-stage funding:
  - Later-stage VC investment is 0.03 percent of GDP in the Netherlands in 2025, nearly four times lower than Sweden (0.1 percent of GDP) and ten times lower than the US (0.33 percent of GDP).
  - Share of insurance sector assets invested into equity is 13 percent in the Netherlands compared to 50 percent in Sweden.
- Financing needs by round:
  - Series B/C+ (growth/later-stage) firms seek €10–100+ million per round.
  - Series A typical needs are €3–15 million.
  - Pre-seed and seed typical needs are €10k–2 million per round.
- Market structure:
  - The Netherlands has the second lowest number of SME IPOs per 1,000 firms in the EU.
  - IPOs make up only about 10 percent of high-tech sector exits and 1.2 percent of all exits.

### Policy measures and interim financing options
- Policy recommendations and reforms highlighted:
  - Implement savings and investment union reforms to raise market liquidity and valuations.
  - Promote automatic enrollment in private pensions and review frameworks for pan-European private pension products and occupational pension funds to allow more VC investment domestically and EU-wide.
  - Implement the EU Listing Act by mid-2026 as planned to improve listing processes on regulated markets and public offerings of shares.
  - Complementary domestic reforms to the Bankruptcy Act and securities laws to shorten settlement cycles and reallocate capital from failed startups more quickly.
  - Standardize and simplify procedures for smaller-denomination corporate debt securities issuance; lower the minimum denomination currently set at €100,000; increase pricing transparency and leverage online platforms to increase retail investor participation.
- Interim and EU-level financing sources:
  - EIB venture debt typically €15 to 50 million offers patient funding with very limited equity dilution.
  - European Tech Champions Initiative (ETCI), a fund-of-funds managed by the EIF under InvestEU, is a significant source for Dutch scale-ups.
  - European Innovation Council (EIC) grants and equity investments of up to €30 million support deep tech startups.
  - EC plans a market-based, privately-managed and privately co-financed Scaleup Europe Fund as part of the EIC Fund and complementary to ETCI 2.0.

---

### Proposed National Investment Institution (NII) and policy priorities

### NII: functions and rationale
- Could standardize funding processes, improve coordination, provide “bridge” patient series B equity capital, and help better leverage EU financing.
- Invest-NL and the Ministry of Economic Affairs expanded initiatives to support capital-intensive ventures, including via the €610 million Dutch Deep Tech Fund.
- NII potential roles:
  - Design patient equity products to “bridge” the funding gap from lab proof-of-concept to commercial deployment.
  - Reduce funding fragmentation across sectors and regions, simplify funding processes, and improve coordination at the national level.
  - Better leverage series C+ EIB co-financing and EU instruments, and ease compliance with EU state‑aid rules.

### Delivery requirements and sizing
- NII will need:
  - Clear mandates and guidelines to ensure focus on addressing market failures (not substituting for private investors).
  - Arms-length governance to guarantee independence from political pressure and signal intent to deliver value for money to markets.
  - Ability to crowd in private finance.
- Current funding plans suggest total initial capital of the institution would be in the €3–5 billion range.
- Funding scale challenge:
  - Many scale-ups require €100–300 million in total funding across multiple rounds; an initial capital of €3–5 billion is likely too small to provide significant equity capital to scale-ups without crowding in private capital.

### Overarching priorities: execution, scale, resilience
- Execution: close implementation gaps by easing binding non-financial constraints—skills, grid capacity, nitrogen limits, and permitting delays—through stronger coordination, faster delivery, and clearer accountability.
- Scale: improve demand-side conditions by deepening the EU Single Market, strengthening EU policy coordination, reducing cross-border barriers, and expanding scale-up funding.
- Resilience: deploy industrial policy carefully by targeting clear market failures, avoiding Single Market fragmentation, ensuring additionality; strengthen supply-chain resilience by identifying and managing critical dependencies, leveraging strategic interdependencies, and broadening R&D diffusion.

### Execution / Scale / Resilience — summary findings and gaps
- Execution priorities and gaps:
  - Priorities: reskilling and scaling STEM and international talent pipelines; fast-track grid expansion; resolve nitrogen and spatial planning constraints; priority permitting lanes; expand housing in high-tech clusters.
  - Gaps: centralized high‑tech reskilling scheme missing; slow progress on grid congestion; no dedicated fast-track permitting for strategic projects; fragmented permitting across government levels.
- Scale priorities and gaps:
  - Priorities: address later-stage financing gap; strengthen defense-adjacent supply chains; crowd in private capital including Dutch institutional investors and EU capital.
  - Gaps: domestic private equity and institutional investor participation limited (especially at TRL5-6); no one-stop shop for financing; incomplete Capital Markets Union and Single Market.
- Resilience priorities and gaps:
  - Priorities: deepen university–industry collaboration; diversify supply chains; complete energy transition.
  - Gaps: R&D and adoption concentrated in large firms; slow grid expansion and high energy costs; incomplete Single Market and regulatory fragmentation; fragmented energy market and volatile electricity prices.

### Concluding policy recommendations (summary)
- Execution: ease binding non-financial constraints—skills, grid, nitrogen, permitting—through stronger coordination, faster delivery, and clearer accountability.
- Scale: deepen EU Single Market, strengthen EU policy coordination, reduce cross-border barriers, expand scale-up funding.
- Resilience: target market failures carefully to avoid Single Market fragmentation; identify and manage critical dependencies; broaden R&D diffusion.

---

### Measuring direct supply exposure — model mechanics and limitations

### Key methodological elements (direct supply and demand exposure)
- Direct supply loss for sector s under disruption magnitude 휆∈[0,1]:
  - d_s_supply(휆) = min(휆 ⋅ ∑_{h∈H_s} v_h ⋅ w_h , f_s_shock)
  - H_s: set of HS codes mapped to sector s via the bridge table.
  - v_h: Dutch imports of product h from critical suppliers (in millions of USD, from UN Comtrade).
  - w_h: non-substitutability weight (expert-weight range from 0.25 to 0.90).
  - f_s_shock: total foreign intermediate inputs consumed by Dutch sector s from identified shock countries (from ICIO intermediate-use matrix Z).
- Demand-side direct loss:
  - E_s_shock = ∑_{j∈shock} Z_{s,j} + ∑_{j∈shock} Y_{s,j}
  - Demand-diversion difficulty coefficient φ_s ∈ [0,1], calibrated empirically: φ_s = export_to_shock_s / total_export_s
  - d_s_demand(휆) = 휆 ⋅ E_s_shock ⋅ φ_s
- Combined direct loss with sector cap x_s (gross output):
  - d_s(휆) = min(d_s_supply(휆) + d_s_demand(휆), x_s)
- Vulnerability indicator:
  - V_s(0.5) = Δx_s(0.5) / x_s  (total loss from 50% disruption as share of gross output)

### Propagation via Leontief inverse
- Technical coefficients: A = Z x̂^{-1} (x̂ is diagonal matrix of gross output).
- Leontief inverse: L = (I − A)^{-1}; L_{i,j} gives total output required from sector i to deliver one unit of final output from sector j.
- Total output loss vector for disruption intensity 휆:
  - Δx(휆) = L × d(휆)
  - d(휆) has d_s>0 only for Dutch high-tech sectors and zero elsewhere.
- Leontief multiplier for group G:
  - μ_G(휆) = ∑_{s∈G} Δx_s(휆) / ∑_{s∈G} d_s(휆)

### Functional properties and limitations
- Supply-channel saturation threshold for sector s:
  - λ_s* = f_s_shock / ∑_h v_h w_h
  - Below λ_s*: supply losses grow proportionally with λ; above λ_s*: additional disruption intensity has no further supply-side effect.
- Model limitations explicitly stated:
  - Fixed technical coefficients: no input substitution, supplier switching, inventory drawdown, or price responses.
  - Static comparison: does not model transition path, duration, or timing of adjustments.
  - No services in product-to-sector bridge table: HS-to-sector mapping covers goods only; KIS have zero direct supply exposure by construction and incur losses only via demand and indirect channels.
  - No re-routing of imports; non-substitutability weight w_h partially captures rerouting difficulty.
  - Simulation results are illustrative vulnerability measures, not forecasts; omission of general equilibrium feedback, price adjustments, and spillovers likely understates full economic impact of prolonged disruption.

### Appendix III — selected critical inputs and example weights (HS 4-digit → weight w1)
- C26 — Electronics (examples): 8542 — 0.14; 8541 — 0.27; 8534 — 0.33; 8517 — 0.33; 8471 — 0.31; 8473 — 0.28; 8523 — 0.10; 9001 — 0.10; 9002 — 0.18; 9013 — 0.16.
- C27 — Electrical Equipment (examples): 8507 — 0.25; 8504 — 0.22; 8506 — 0.19; 8516 — 0.19; 8532 — 0.18; 8533 — 0.17.
- C28 — Machinery & Equipment (examples): 8457 — 0.20; 8486 — 0.16; 8456 — 0.15; 8460 — 0.12; 8483 — 0.10.
- C20 — Chemicals (examples): 3707 — 0.37; 2805 — 0.32; 2846 — 0.18; 2836 — 0.25; 2818 — 0.18; 2903 — 0.15; 2901 — 0.15; 2804 — 0.10.
- C301 — Aerospace (examples): 8803 — 0.34; 8802 — 0.26; 8407 — 0.11.
- Note: Weight w1 reflects empirical HHI of Dutch import sourcing for each HS code; example interpretation given in text.

### Appendix IV — top suppliers and markets (selected figures)
- Top suppliers by vulnerability-weighted imports (examples):
  - China: Imports (USD mn) 100,388 — Weighted imports* 22,403
  - USA: Imports (USD mn) 36,112 — Weighted imports* 6,547
  - South Korea: Imports (USD mn) 30,785 — Weighted imports* 5,188
  - Japan: Imports (USD mn) 21,546 — Weighted imports* 4,345
  - Germany: Imports (USD mn) 24,065 — Weighted imports* 8,321
- Top markets by concentration-weighted exports (examples):
  - Germany: Export (USD mn) 256,583 — Weighted export** 31,313
  - France: Export (USD mn) 193,531 — Weighted export** 18,885
  - USA: Export (USD mn) 149,611 — Weighted export** 11,126
  - Belgium: Export (USD mn) 140,429 — Weighted export** 2,992
  - Italy: Export (USD mn) 104,305 — Weighted export** 47

### Policy context — selected instruments supporting high-tech sector
- National and EU instruments cited (summaries and exact parameters preserved):
  - Research and Development Promotion Act (WBSO): payroll tax relief for R&D labor costs (32–40% first tranche; 16% thereafter); used by 20,000 firms last year.
  - Innovation Box: reduced effective CIT rate (9%) on profits from qualifying self-developed IP.
  - Innovation Credit (Netherlands Enterprise Agency): maximum of €50 mn for 2026, and maximum funding of €10 mn per project.
  - Seed Capital Scheme: Maximum of €42 mn for 2026, and maximum funding of €12 mn per project.
  - Project Beethoven: multi-year public investment in Brainport Eindhoven (€2.5 bn, public-private).
  - Invest-NL Deep Tech Fund: Deep Tech: €610 million fund.
  - 3% R&D Action Plan: target of investing 3% of GDP in R&D by 2030.
  - 30% Expat Tax Exemption: preferential PIT treatment for eligible workers (up to 30% of gross salary tax-free).
  - European Chips Act (EU): framework to support semiconductor R&D, pilot lines, manufacturing, and skills.
  - Horizon Europe / EIC, InvestEU / EIB financing, EU AI Act, Digital Single Market, EU Skills Agenda, Green Deal industrial policies.

*Source: sipea2026087 - 1. Definition of the High-Tech Sector, June 29, 2026 (KINGDOM OF THE NETHERLANDS—THE NETHERLANDS, INTERNATIONAL MONETARY FUND).*

### 1. Definition of the High-Tech Sector ___________________________________________________ 4

### 1. Definition of the High-Tech Sector ___________________________________________________ 4

### Overview and Statistical Definition
- Uses Eurostat’s sectoral-level classification of high- and medium-high-tech manufacturing and high-tech knowledge-intensive services (see Appendix I).
- Covers advanced export-oriented activities—semiconductors, pharmaceuticals, photonics, aerospace—alongside knowledge-intensive services in ICT, software, and professional and scientific activities.
- Statistical scope includes NACE Rev. 2 codes for high and medium-high tech industries and high-tech knowledge-intensive services (Appendix I note).

### Importance and Strategic Role
- The high-tech sector is anchored in innovation ecosystems that link frontier firms, specialized suppliers, universities, and local authorities, combining capability networks (semiconductors, photonics, precision mechatronics, advanced materials) with mission-oriented networks (medical and biotech, energy and climate, defense, digital/ICT).
- Ecosystems translate research into commercial applications and support diffusion across firms, underpinning the Netherlands’ strong innovation performance.
- Sectoral composition and concentration:
  - High-tech sectors together account for about 11 percent of total gross value added and 6 percent of employment.
  - High-tech manufacturing is concentrated in machinery and equipment, led by lithography machines production and its supplier network.
  - Computing, programming, and IT consulting dominate the high-tech knowledge-intensive services side.
- Growth and market valuation:
  - High-tech subsectors—especially pharmaceuticals, machinery and equipment, and advanced manufacturing—have recorded stronger growth in gross value added (GVA) and labor productivity than the overall economy (Figure 2).
  - Between 2014 and 2025, the market capitalization of listed Dutch high-tech firms grew faster than in the U.S. and China, albeit from a much smaller base.
  - Market data covers 33 listed companies for the Netherlands, 2,251 for China, and 1,036 for US (as of 2025).
  - One leading semiconductor equipment company accounted for about 60 percent of listed Dutch high-tech market capitalization at end-2025.

### Deep Integration in Global Value Chains (GVCs)
- The Netherlands ranks high among leading EU economies in domestic value added embodied in foreign high-tech exports; this share has risen faster than in peers over time.
- The Netherlands is among the top 15 global exporters of high-tech value added (Netherlands' rank: 14th).
- High-tech GVA relative to the U.S. recovered after 2015 and has been broadly stable; the post-2015 recovery was mainly driven by medium-high tech manufacturing.
- Intangible assets:
  - Medium-high-tech industries, notably electrical and machinery equipment, exhibit a relative advantage in intangible assets; intangible assets in high-tech KIS remain broadly in line with peers.

### GVC-Related Vulnerabilities and Exposure Channels
- Foreign-input and foreign-demand exposures create two-sided vulnerabilities:
  - Backward linkages: reliance on imported inputs, specialized components, and foreign technology embedded in production networks.
    - Foreign value added has exceeded one-third of high-tech exports in recent years and remains above the EU median.
    - Foreign-input exposure varies across sectors: chemicals and pharmaceuticals show the highest foreign value added in exports; machinery, equipment, and electronics display meaningful backward linkages; high-tech KIS have lower direct foreign-input exposure but remain indirectly exposed through links to manufacturing.
    - A decomposition of value added in high-tech domestic final demand between 2010 and 2022 shows services remain largely domestic while manufacturing relies more heavily on foreign inputs; computer, electronic, and electrical equipment show a marked decline in domestic value-added share with a rising share of China.
  - Forward linkages: exposure to foreign final demand is high—60 percent of sectoral value added—and concentrated in a few markets.
    - Key downstream markets: Germany, the U.S., and China. Germany is a key downstream market for machinery, semiconductors, and lithography-related inputs; the U.S. and China are major markets for electronics and other high-tech goods.
- Channels of GVC-related vulnerabilities:
  - Geoeconomic fragmentation and trade restrictions: export controls, subsidies, security-driven policies can disrupt trade and technology flows, affecting both forward and backward linkages.
  - Strategic input chokepoints and external dependencies: reliance on critical raw materials, energy inputs, specialty components, and specific production stages creates chokepoints, especially in advanced materials, chemical technology, electronics, energy technologies, and defense.
  - Production relocation risk: foreign subsidies, faster permitting, lower energy costs, or targeted industrial-policy packages may incentivize firms to relocate production abroad, especially capital-intensive deep-tech activities (semiconductors, photonics, advanced materials, energy technologies).
  - Dependence on non-EU capital and exit channels: foreign investors and acquisition-led exits can risk relocation of control, intellectual property, and production even when early-stage research originates domestically.
- Since COVID-19, supply disruptions have become larger, more persistent, and more frequent.

### Assessment Framework and Methodology (Illustrative Simulations)
- Two GVC-related vulnerability channels are examined: disruptions to access to foreign inputs and to external demand.
- Critical product categories are mapped to high-tech manufacturing sectors and weighed by supplier concentration using the Herfindahl–Hirschman Index.
- Linkages are traced through input–output relationships to estimate structural output at risk under a stylized two-sided disruption involving key partners.
- Framework specifics:
  - Uses a tractable input–output model augmented with international trade data and inter-country input–output tables (Appendix III).
  - Broadly consistent with Bonam et al. (2026) and related literature.
  - Results are illustrative structural output at risk, not forecasts or point estimates; the framework abstracts from behavioral relationships, substitution, inventories, price responses, policy adjustment, and broader macroeconomic effects.
- Scope distinctions:
  - Direct supply exposures assessed for goods trade.
  - High-tech services are captured through foreign-demand channels and indirect links to goods-producing sectors.

### Domestic Policy Implications Highlighted
- Sustaining high-tech leadership will require:
  - Easing domestic bottlenecks (labor, grid capacity, permitting, scale-up finance).
  - Leveraging deeper EU integration to support scaling.
  - Strengthening resilience to GVC disruptions and geoeconomic fragmentation.

*Source: sipea2026087 - 1. Definition of the High-Tech Sector, June 29, 2026 (KINGDOM OF THE NETHERLANDS—THE NETHERLANDS, INTERNATIONAL MONETARY FUND).*

### 13.      Illustrative simulations of a 50 percent bilateral trade disruption shock suggest

### 13.      Illustrative simulations of a 50 percent bilateral trade disruption shock suggest 

### Simulations — headline results
- Vulnerability measured as total loss as a percent of gross output under a 50 percent disruption of bilateral trade.
- Sizable output at risk, especially in chemicals, machinery and electronics and electrical equipment (Figure 4, left chart).
- Exposure is best read as a ranking of relative exposure across sectors and partners, rather than as estimates of likely output losses.
- The model is a partial-equilibrium, open-economy input–output framework that measures structural exposure of Dutch high-tech sectors to bilateral (not global) supply and demand disruptions with key partners without any consideration for global macro-economic effects.  

### Exposure channels and quantitative contributions
- Exposure is largely supply-driven (almost half of total vulnerability), reflecting reliance on foreign inputs and concentrated supplier bases for specialized components including semiconductor-related inputs, lithography equipment components, and rare earth elements.
- Demand-side exposure contributes around 30 percentage points to risks in most manufacturing sectors.
- Indirect input–output linkages amplify initial shocks by slightly more than 20 percentage points in the most exposed sectors.
- Exception: Other transport equipment is more closely associated with demand concentration and a narrower set of export markets.
- No direct supply effects are identified for sectors C29 (motor vehicles) and C30 (other transport equipment), as none of the critical inputs used in the analysis are sourced from these sectors.

### Sectoral and partner concentration
- High-tech knowledge-intensive services show limited direct vulnerability but remain exposed through indirect effects from domestic production linkages (goods-based supply-shock design captures direct supply disruptions only for goods producing sectors).
- U.S. is the single largest source of exposure for electrical equipment and electronics, chemicals and machinery.
- China ranks as the second-largest contributor in most manufacturing sectors, particularly electronics and chemicals.
- Germany adds a comparatively smaller layer of exposure, most notably in machinery, motor vehicles, and aerospace.
- South Korea's contribution is concentrated in electronics.
- France is mainly present in aerospace value-chain links.
- Key trading partners identified include China, U.S., Germany, Korea and France.

### Nonfinancial bottlenecks — overview
- Structural bottlenecks constrain investment, scaling, and diffusion: labor and skill shortages, grid congestion, regulatory constraints, and later-stage scale-up finance frictions.
- Constraints are most binding for capital- and infrastructure-intensive activities; knowledge-based activities are less directly affected.

### Labor shortages and skills
- Labor shortages remain one of the main obstacles in high-tech sectors, especially high-tech KIS, and rank second in medium-high-tech manufacturing after insufficient demand (Figure 5).
- Firms are responding by adopting automation (robotization and AI-based solutions), particularly in high-tech KIS.
- Skill enhancement needs are high among workers in high-tech sectors, especially high-tech KIS.
- STEM enrollment remains below peer levels.
- Analysis based on ESJS wave 2 (2021) with sample covering eight countries (AT, BE, DE, DK, FI, FR, NL, and SE).

### Electricity grid congestion and nitrogen constraints
- Electricity grid congestion is becoming a binding constraint on high-tech investment, electrification, and industrial expansion, particularly in Noord‑Brabant and Limburg.
- Long connection queues and uncertainty over future access are delaying factory expansions, electricity-intensive production lines, and on-site renewable generation and battery storage.
- While major grid investment is underway, expansion has so far lagged demand; policy efforts should prioritize accelerating permitting and delivery of network upgrades, greater demand flexibility, storage, and energy-efficiency measures to ease near-term pressures.
- Nitrogen deposition exceeded critical loads across about 70 percent of Natura 2000 area as of 2023, leaving little room for new projects without breaching environmental thresholds.
- A 2024 Council of State ruling further limited the use of nitrogen headroom within existing permits.
- Fragmented responsibilities across municipal, provincial, and national authorities add delays and uncertainty for projects requiring multiple permits or located near protected areas.

### Permitting, regulation, and EU fragmentation
- Obtaining an industrial building permit can take an estimated 20–39 months from preparation through appeals, with objection and appeal procedures alone accounting for 10–23 months.
- Pending spatial-planning cases before the Council of State have more than doubled since 2020.
- Example of rapid delivery: Eemshaven LNG terminal permitting and construction took only 200 days when prioritized and coordinated across government levels.
- EU internal market fragmentation is structural for some ecosystems (medical and biotech, digital and ICT, defense and security) and can limit scaling within Europe.
- Table examples of regulatory fragmentation:
  - Overlapping EU frameworks (AI Act, GDPR, Data Act, DSA/DMA, NIS2) increase compliance costs for digital and AI activities.
  - 27 (divergent) export-control and dual-use regimes in EU raise costs and complicate semiconductor and dual-use exports within EU.
  - 27 national reimbursement regimes in EU restrict Dutch pharma market access.

### Gaps in access to finance for high-tech firms
- Netherlands has a strong but fragmented startup funding ecosystem; pre-seed, seed, and series A startups supported by public grants, VC, and angel investors.
- Seed and other early-stage VC investment was 0.07 percent of GDP in 2025, twice as high as in France, Germany, and Belgium, and on par with Sweden (0.1 percent of GDP).
- Seed and other early-stage funding was 4 times higher in the US, at 0.29 percent of GDP.
- Later-stage VC investment is 0.03 percent of GDP in the Netherlands in 2025, nearly four times lower than Sweden (0.1 percent of GDP) and ten times lower than the US (0.33 percent of GDP).
- The share of insurance sector assets invested into equity is 13 percent in the Netherlands compared to 50 percent in Sweden.
- Series B/C+ (growth/later-stage) firms seek €10–100+ million per round; Series A typical needs are €3–15 million; pre-seed and seed typical needs are €10k–2 million per round.
- The Netherlands has the second lowest number of SME IPOs per 1,000 firms in the EU.
- IPOs make up only about 10 percent of high-tech sector exits and 1.2 percent of all exits.

### Policy measures and interim financing options
- Policy recommendations and reforms highlighted:
  - Implement savings and investment union reforms to raise market liquidity and valuations.
  - Promote automatic enrollment in private pensions and review frameworks for pan-European private pension products and occupational pension funds to allow more VC investment domestically and EU-wide.
  - Implement the EU Listing Act by mid-2026 as planned to improve listing processes on regulated markets and public offerings of shares.
  - Complementary domestic reforms to the Bankruptcy Act and securities laws to shorten settlement cycles and reallocate capital from failed startups more quickly.
  - Standardize and simplify procedures for smaller-denomination corporate debt securities issuance; lower the minimum denomination currently set at €100,000; increase pricing transparency and leverage online platforms to increase retail investor participation.
- Interim and EU-level financing sources:
  - EIB venture debt typically €15 to 50 million offers patient funding with very limited equity dilution.
  - European Tech Champions Initiative (ETCI), a fund-of-funds managed by the EIF under InvestEU, is a significant source for Dutch scale-ups.
  - European Innovation Council (EIC) grants and equity investments of up to €30 million support deep tech startups.
  - EC plans a market-based, privately-managed and privately co-financed Scaleup Europe Fund as part of the EIC Fund and complementary to ETCI 2.0.

*Source: KINGDOM OF THE NETHERLANDS—THE NETHERLANDS (Selected Issues Paper content provided).*

### 27.      The proposed National Investment Institution could standardize funding processes,

### 27.      The proposed National Investment Institution could standardize funding processes,

### Proposed National Investment Institution (NII): functions and rationale
- Could standardize funding processes, improve coordination, provide “bridge” patient series B equity capital, and help better leverage EU financing.
- Invest-NL and the Ministry of Economic Affairs expanded initiatives to support capital-intensive ventures (e.g., in the semiconductors, photonics, quantum computing sectors), including via the €610 million Dutch Deep Tech Fund.
- The proposed NII could:
  - Design patient equity products to “bridge” the funding gap as firms progress from lab proof-of-concept to commercial deployment.
  - Help reduce funding fragmentation across sectors and regions, simplify funding processes, and improve coordination at the national level.
  - Better leverage series C+ EIB co-financing and EU instruments, and ease compliance with EU state‑aid rules.

### Delivery requirements and sizing
- NII will need:
  - Clear mandates and guidelines to ensure focus on addressing market failures (not substituting for private investors).
  - Arms-length governance to guarantee independence from political pressure and signal intent to deliver value for money to markets.
  - Ability to crowd in private finance.
- Current funding plans suggest total initial capital of the institution would be in the €3–5 billion range.
- Funding scale challenge:
  - Many scale-ups require €100–300 million in total funding across multiple rounds; an initial capital of €3–5 billion is likely too small to provide significant equity capital to scale-ups without crowding in private capital.

### Policy considerations: overarching priorities
- Sustaining high-tech leadership requires a policy agenda focusing on execution, scale, and resilience, with coordinated domestic and EU-wide efforts.
- The Netherlands excels at innovation but faces domestic bottlenecks that slow investment and scaling; external risks (geoeconomic fragmentation, concentrated GVC exposures, high energy costs) underscore the need to strengthen resilience.
- Policies should address domestic execution bottlenecks while leveraging EU-level policies for scale and resilience. These priorities reinforce each other.

### Execution: findings, policies, and gaps (Table 3 summary)
- Priorities:
  - Address skill shortage through reskilling and scaling STEM and international talent pipelines.
  - Fast-track grid expansion in key clusters.
  - Resolve nitrogen and spatial planning constraints.
  - Priority permitting lanes for strategic projects.
  - Expand housing availability in high-tech growth clusters.
- Existing policies:
  - STEM & Reskilling: Technology Pact (Techniekpact), Lifelong Learning framework.
  - Talent attraction: 30% Expat Tax Exemption; Kennismigranten (fast-track residence permits for high-skilled migration).
  - Infrastructure: Climate Agreement (Klimaatakkoord) & SDE++ subsidies for low-carbon energy to expand electricity grid capacity.
  - Ecosystem Projects: e.g., Project Beethoven to improve local infrastructure, talent, and housing.
- Gaps:
  - Skill shortage remains: A centralized high‑tech reskilling scheme is missing. STEM pipeline expansion remains limited.
  - Infrastructure bottlenecks: Progress addressing grid congestion is slow, no dedicated fast-track permitting for strategic projects or housing near tech hubs.
  - Regulatory hurdles: Fragmented permitting across government levels. Nitrogen rules delaying permits for housing/facilities are acute and only partially resolved by current measures.

### Scale: findings, policies, and gaps (Table 4 summary)
- Priorities:
  - Address potential later-stage financing gap for scale-ups.
  - Strengthen defense-adjacent supply chains.
  - Crowd in private capital, including from Dutch institutional investors and EU capital for larger tickets and more patient investing.
- Existing policies:
  - Public Funding: National Growth Fund, Deep Tech Fund via Invest-NL.
  - Innovation Box: Innovation Credit (NEA), ROMs (9 Regional Agencies).
  - Proposed NII.
- Gaps:
  - Financing gaps remain: Domestic private equity capital and institutional investor participation are limited (especially at TRL5-6). No one-stop shop to advise on financing.
  - Deepening Single Market, cross-border value chains and market depth matter for scaling beyond NL demand.
  - Capital Markets Union remains incomplete, hindering cross-border financing at scale. Incomplete Single Market.

### Resilience: findings, policies, and gaps (Table 5 summary)
- Priorities:
  - Strengthen Innovation: deepen university–industry collaboration.
  - Diversify Supply Chains and reduce choke point vulnerabilities.
  - Complete Energy transition and enhance competitiveness.
- Existing policies:
  - National Technology Strategy.
  - New Industrial Policy 2025.
  - 3% R&D Action Plan.
  - Climate Agreement.
  - SDE++ subsidies for decarbonization.
  - TNO Mega clusters.
  - IP targets 6 strategic markets.
  - EU-level instruments: EU Critical Raw Materials Act; Important projects of common European interest (PCEIs); European Defense Industrial Strategy (EDIS); European Economic Security Strategy and EU Dual Use Export Control Framework.
- Gaps:
  - Need to identify market failures and critical dependencies to avoid fragmentation risks.
  - Innovation diffusion/collab: R&D and adoption of new tech still concentrated in large companies.
  - Energy transition lags: Slow grid expansion. High energy costs due to heavy gas reliance.
  - GVC resilience: incomplete Single Market and regulatory fragmentation due to diverging rules and “Gold-plating”.
  - Fragmented Energy Market: Electricity prices are highly volatile and differ across EU countries due to weak interconnectivity.

### Concluding remarks and policy recommendations
- Role of high-tech sector:
  - Central to growth in the Netherlands; underpins productivity growth, export strength, and technological specialization across advanced manufacturing and knowledge-intensive services.
  - Strength rests on deep global integration, which also creates vulnerabilities (foreign-input disruptions, external demand shocks).
- Key vulnerabilities:
  - Supply chains increasingly reliant on non-EU partners; export demand concentrated in key markets.
  - Vulnerabilities concentrated in electronics, electrical equipment, chemicals, and machinery, with exposure to a small set of key trading partners.
  - Domestic constraints: skill shortages, grid congestion, nitrogen and permitting constraints, and scale-up finance frictions.
  - High energy costs risk eroding competitiveness in energy-intensive segments; EU market fragmentation limits firms’ ability to scale within Europe.
- Policy priorities (summary):
  - Execution: close implementation gaps by easing binding non-financial constraints—skills, grid capacity, nitrogen limits, and permitting delays—through stronger coordination, faster delivery, and clearer accountability.
  - Scale: improve demand-side conditions by deepening the EU Single Market, strengthening EU policy coordination, reducing cross-border barriers, and expanding the scale-up funding.
  - Resilience: deploy industrial policy carefully by targeting clear market failures, avoiding Single Market fragmentation, and ensuring additionality; strengthen supply-chain resilience by identifying and managing critical dependencies, leveraging strategic interdependencies, and broadening R&D diffusion.

*Source: IMF staff assessment based on discussions with stakeholders, from the chapter "KINGDOM OF THE NETHERLANDS—THE NETHERLANDS" (selected issues paper).*

### 8. Measuring Direct Supply Exposure. For each high-tech sector 푠, we compute the direct

### 8. Measuring Direct Supply Exposure

### Methodology: Direct supply loss (high-tech sector s)
- Direct loss of hard-to-replace imports from shock countries under disruption magnitude 휆∈[0,1]:
  - 푑푠푠푢푝푝푙푦(휆)=푚푖푛(휆⋅∑ℎ∈퐻푠 푣ℎ⋅푤ℎ , 푓푠푠ℎ표푐푘)
- Definitions:
  - 퐻푠 is the set of HS codes mapped to sector 푠 via the bridge table.
  - 푣ℎ denotes Dutch imports of product ℎ from critical suppliers (in millions of USD, from UN Comtrade).
  - 푤ℎ is the non-substitutability weight.
  - 푓푠푠ℎ표푐푘 is the total foreign intermediate inputs consumed by Dutch sector 푠, sourced from the identified shock countries, taken from the ICIO intermediate-use matrix 푍.
- Expert-weight range for 푤ℎ noted in text:
  - range from 0.25 (easily substitutable) to 0.90 (near-irreplaceable in the short run).

### Bilateral cap rationale
- The minimum operator caps Comtrade-based exposure at the bilateral ICIO intermediate input level to:
  - Net out re-exports (Netherlands is a large re-export hub).
  - Exclude final goods recorded in Comtrade that do not enter production as intermediate inputs.
- Ensures estimated supply losses reflect actual production dependencies rather than gross trade flows.

### Measuring demand-side direct exposure
- Total exports at risk from Dutch sector 푠 to shock-country sectors:
  - 퐸푠푠ℎ표푐푘 = ∑푗∈푠ℎ표푐푘 푍푠,푗 + ∑푗∈푠ℎ표푐푘 푌푠,푗
- Demand-diversion difficulty coefficient 휙푠∈[0,1]:
  - Calibrated empirically: 휙푠 = export_to_shock_s / total_export_s
  - total_export_s = sum of all foreign intermediate and final-demand deliveries by Dutch sector 푠.
- Demand-side direct loss:
  - 푑푠푑푒푚푎푛푑(휆)=휆⋅퐸푠푠ℎ표푐푘⋅휙푠

### Combined direct shock and sector cap
- Combined direct loss:
  - 푑푠(휆)=푚푖푛(푑푠푠푢푝푝푙푦(휆)+푑푠푑푒푚푎푛푑(휆), 푥푠)
  - 푥푠 is the gross output of sector 푠.
- Cap ensures estimated losses cannot exceed sector total production.

### Functional properties of losses
- Supply-channel saturation threshold for sector 푠:
  - 휆푠∗ = 푓푠푠ℎ표푐푘 / ∑ℎ 푣ℎ푤ℎ
- Behaviour:
  - Below 휆푠∗: supply losses grow proportionally with 휆.
  - Above 휆푠∗: additional disruption intensity has no further supply-side effect.
  - Demand channel remains linear in 휆.
  - Leontief multipliers vary across scenarios and depend on composition of the shock vector.

### Supply-chain propagation via Leontief inverse
- Technical coefficients matrix from ICIO intermediate-use matrix:
  - 퐴 = 푍푥̂−1 (where 푥̂ is diagonal matrix of gross output).
- Leontief inverse:
  - 퐿 = (퐼 − 퐴)−1
  - Element 퐿푖,푗 gives total output required from sector 푖 to deliver one unit of final output from sector 푗.
- Total output loss vector for disruption intensity 휆:
  - Δ푥(휆) = 퐿 × 푑(휆)
  - 푑(휆) has 푑푠>0 only for Dutch high-tech sectors and zero elsewhere.
  - Total loss for Dutch high-tech sector 푠 is the 푠-th element of Δ푥(휆) restricted to Dutch sectors.
- Leontief multiplier for group of sectors 퐺:
  - 휇퐺(휆) = ∑푠∈퐺 Δ푥푠(휆) / ∑푠∈퐺 푑푠(휆)

### Vulnerability indicator
- Vulnerability of sector 푠 defined as total loss from 50% disruption as share of gross output:
  - 푉푠(0.5) = Δ푥푠(0.5) / 푥푠

### Model limitations (as stated)
- Fixed technical coefficients: no input substitution, supplier switching, inventory drawdown, or price responses.
- Static comparison: compares pre-disruption equilibrium with post-disruption counterfactual; does not model transition path, duration, inventory depletion, or timing of adjustments.
- No services in product-to-sector bridge table: HS-to-sector mapping covers goods trade only; knowledge-intensive service sectors have zero direct supply exposure by construction and can only incur losses via demand and indirect channels.
- No re-routing of imports: imports from shock countries are lost in proportion to 휆; non-substitutability weight 푤ℎ partially captures rerouting difficulty.
- Simulation results are illustrative vulnerability measures, not forecasts; omission of general equilibrium feedback, price adjustments, and spillovers likely understates full economic impact of prolonged disruption.

### Appendix III — Selected identified critical inputs and weights (HS 4-digit → weight w1)
- C26 — Electronics (examples):
  - 8542 Electronic integrated circuits (chips, processors) — 0.14
  - 8541 Diodes, transistors, semiconductors — 0.27
  - 8534 Printed circuits (PCBs) — 0.33
  - 8517 Telecom equipment (incl. smartphones, transmission apparatus) — 0.33
  - 8471 Computers & data-processing machines — 0.31
  - 8473 Parts for computers & office machines — 0.28
  - 8523 Storage media (optical, magnetic, semiconductor) — 0.10
  - 9001 Optical fibres, lenses, prisms (unmounted) — 0.10
  - 9002 Mounted lenses, prisms, mirrors (for instruments) — 0.18
  - 9013 Liquid crystal devices, lasers, optical appliances — 0.16
- C27 — Electrical Equipment (examples):
  - 8507 Electric accumulators (batteries, Li-ion) — 0.25
  - 8504 Transformers & static converters — 0.22
  - 8506 Primary cells & batteries — 0.19
  - 8516 Electric heating apparatus (industrial/consumer) — 0.19
  - 8532 Electrical capacitors — 0.18
  - 8533 Electrical resistors — 0.17
- C28 — Machinery & Equipment (examples):
  - 8457 Machining centres & unit construction machines — 0.20
  - 8486 Semiconductor manufacturing machinery — 0.16
  - 8456 Laser/ultrasonic/plasma machine tools — 0.15
  - 8460 Grinding, sharpening & polishing machines — 0.12
  - 8483 Transmission shafts, gears, bearings — 0.10
- C20 — Chemicals (examples):
  - 3707 Photographic chemical preparations — 0.37
  - 2805 Alkali/alkaline-earth/rare-earth metals — 0.32
  - 2846 Rare-earth compounds — 0.18
  - 2836 Carbonates (sodium, lithium, etc.) — 0.25
  - 2818 Aluminium oxide (corundum, alumina) — 0.18
  - 2903 Halogenated hydrocarbons — 0.15
  - 2901 Acyclic hydrocarbons (ethylene, propylene) — 0.15
  - 2804 Hydrogen, noble gases, other non-metals — 0.10
- C301 — Aerospace (examples):
  - 8803 Parts of aircraft & spacecraft — 0.34
  - 8802 Powered aircraft & helicopters — 0.26
  - 8407 Spark-ignition engines (piston) — 0.11
- Note on weight w1:
  - Weight reflects empirical HHI of Dutch import sourcing for each HS code. Example: w = 0.37 indicates concentrated suppliers; w = 0.07 indicates diversified sourcing.

### Appendix IV — Top suppliers, key markets (selected figures)
- Top suppliers by vulnerability-weighted imports (examples):
  - China: Imports (USD mn) 100,388 — Weighted imports* 22,403
  - USA: Imports (USD mn) 36,112 — Weighted imports* 6,547
  - South Korea: Imports (USD mn) 30,785 — Weighted imports* 5,188
  - Japan: Imports (USD mn) 21,546 — Weighted imports* 4,345
  - Germany: Imports (USD mn) 24,065 — Weighted imports* 8,321
- Top markets by concentration-weighted exports (examples):
  - Germany: Export (USD mn) 256,583 — Weighted export** 31,313
  - France: Export (USD mn) 193,531 — Weighted export** 18,885
  - USA: Export (USD mn) 149,611 — Weighted export** 11,126
  - Belgium: Export (USD mn) 140,429 — Weighted export** 2,992
  - Italy: Export (USD mn) 104,305 — Weighted export** 47

### Policy context (selected initiatives supporting high-tech sector)
- National and EU-level instruments listed (summaries):
  - Research and Development Promotion Act (WBSO): payroll tax relief for R&D labor costs (32–40% first tranche; 16% thereafter); used by 20,000 firms last year.
  - Innovation Box: reduced effective CIT rate (9%) on profits from qualifying self-developed IP.
  - Innovation Credit (Netherlands Enterprise Agency): maximum of €50 mn for 2026, and maximum funding of €10 mn per project.
  - Seed Capital Scheme: Maximum of €42 mn for 2026, and maximum funding of €12 mn per project.
  - Project Beethoven: multi-year public investment in Brainport Eindhoven (€2.5 bn, public-private).
  - Invest-NL Deep Tech Fund: Deep Tech: €610 million fund.
  - 3% R&D Action Plan: target of investing 3% of GDP in R&D by 2030.
  - 30% Expat Tax Exemption: preferential PIT treatment for eligible workers (up to 30% of gross salary tax-free).
  - European Chips Act (EU): framework to support semiconductor R&D, pilot lines, manufacturing, and skills.
  - Horizon Europe / EIC, InvestEU / EIB financing, EU AI Act, Digital Single Market, EU Skills Agenda, Green Deal industrial policies (described as supporting R&D, scale-up finance, regulatory integration, and green/industrial incentives).

*Source: IMF staff compilation from the provided chapter content.*

### References

### sipea2026087 - References

### Geoeconomic fragmentation and multilateralism
- Aiyar, S., J. Chen, C. Ebeke, R. Garcia-Saltos, T. Gudmundsson, A. Ilyina, A. Kangur, T. Kunaratskul, S. Rodriguez, M. Ruta, T. Schulze, G. Soderberg, and J. P. Trevino (2023), Geoeconomic Fragmentation and the Future of Multilateralism, IMF Staff Discussion Note No. 2023/001, International Monetary Fund, Washington, DC, Geo-Economic Fragmentation and the Future of Multilateralism; Staff Discussion Note No: 2023/001; January 15, 2023.
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### European Commission, Parliament, and EU policy documents
- European Commission (2026), Country Report — Netherlands, Directorate-General for Economic and Financial Affairs, https://economy-finance.ec.europa.eu/economic-surveillance-eu-member-states/country-pages-including-country-reports/country-report-netherlands_en.
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### Netherlands-focused research, strategies, and analyses
- Bonam D., J. Demmers, G. Goy, J. de Grip, B. Heerma van Voss, D. de Leeuw, C. Mehlbaum, A. Smadu, R. Swierstra (2026) “Global supply chains and European economic vulnerabilities”, DeNederlandscheBank, https://www.dnb.nl/media/d5xopy4u/dnb-analysis-global-supply-chains-and-european-economic-vulnerabilities-1.pdf.
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- TNO (2025c), R&D Top 50: The Netherlands' Top Research and Development Spenders, rapport-2025-r&d-top50-eng.pdf.
- Wennink, P. (2025), The Route to Future Prosperity: A Strong Netherlands in a Relevant Europe, independent advisory report, https://www.rapportwennink.nl/en/.
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- Ru J. and L. Gan (2025), "Analysis on the Economic Growth Effects of Industrial Clustering in High-Tech Manufacturing and Knowledge-Intensive Service Industries," Sustainable Economies, 3(1).

### Innovation, technology, and industry initiatives
- Brainport Eindhoven (2024), Project Beethoven 2024: Strengthening the Microchip Industry and Quality of Life, https://brainporteindhoven.com/en/strategy-organisation/agenda-with-the-government/project-beethoven-2024.
- Brainport Eindhoven (2026), Innovation Campuses in Brainport Eindhoven, brochure, https://brainporteindhoven.com/fileadmin/user_upload/Campussen/Innovation-campuses_in_Brainport_Eindhoven_brochure-2026.pdf.
- Holland High Tech (2026), Innovation Domains, https://www.hollandhightech.nl/en/innovation/innovation-domains.
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- Pietrobelli C., M. Delera and N. Geri (2026) “Navigating a fragmenting global economy: What GVC reconfiguration means for future industrial development”, UNIDO policy brief No. 28/2026.

### Sectoral vulnerability and competitiveness analyses
- Attinasi M.-G., L. Boeckelmann, R. Gerinovics and B. Meunier (2025). “Unveiling the hidden costs of critical dependencies”, ECB Economic Bulletin, Issue 5/2025, https://www.ecb.europa.eu/press/economic-bulletin/articles/2025/html/ecb.ebart202505_01~c93c71e372.en.html.
- Bonam D., J. Demmers, G. Goy, J. de Grip, B. Heerma van Voss, D. de Leeuw, C. Mehlbaum, A. Smadu, R. Swierstra (2026) “Global supply chains and European economic vulnerabilities”, DeNederlandscheBank, https://www.dnb.nl/media/d5xopy4u/dnb-analysis-global-supply-chains-and-european-economic-vulnerabilities-1.pdf.
- Ru J. and L. Gan (2025), "Analysis on the Economic Growth Effects of Industrial Clustering in High-Tech Manufacturing and Knowledge-Intensive Service Industries," Sustainable Economies, 3(1).

*Source: sipea2026087 - References*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2026/english/sipea2026087.pdf_