Institutional Quality and High-Tech Investment in the EU

 The provided sources examine the widening productivity growth gap between the European Union (EU) and the United States (US), tracing its roots to differences in high-tech investment and the quality of institutional and regulatory frameworks.

The EU-US Productivity and Innovation Gap

Since the mid-1990s, EU countries have experienced slower productivity growth compared to the US, a divergence closely linked to an "innovation gap". The sources highlight several key differences in investment patterns:

• Sectoral Focus: The US prioritizes investment in high-tech sectors such as ICT, Artificial Intelligence (AI), cloud computing, and biotechnology. In contrast, Europe remains concentrated in mature, mid-tech sectors, leading to what some researchers call a "middle-technology trap".
• Investment Shares: In 2021, high-tech sectors accounted for approximately 33% of market sector gross fixed capital formation in the US, nearly double the 17% share in the EU.
• ICT Contribution: The ICT sector alone explains about 48% of the average annual hourly productivity growth gap between the EU and the US from 2000 to 2019.
• Spillover Effects: High-tech innovation provides broader productivity spillovers across the economy, whereas the incremental innovation typical of the EU's mid-tech focus has more limited benefits.

The Role of Institutions and Regulation

The sources argue that the EU's lag in high-tech is deeply rooted in its institutional and regulatory environment. High-tech sectors are inherently risky, characterized by trial-and-error and higher rates of project failure. Consequently, the cost of failure—influenced by regulations—is a critical determinant of investment.

• Labor Market Rigidity: Restrictive Employment Protection Legislation (EPL), which increases the costs of dismissing workers, can deter firms from pursuing high-risk, high-reward disruptive innovation. While some argue EPL fosters trust, the sources suggest it often increases operational rigidity and reduces the incentive to adjust workforces in response to technological shifts.
• Administrative Burdens: High costs and complex procedures for starting a business and resolving insolvency act as barriers to entry and exit, further discouraging investment in volatile high-tech sectors.
• Governance Quality: Broader institutional factors, including the rule of law, control of corruption, and government effectiveness, create the "level playing field" necessary for economic actors to invest and innovate.

Impact on High-Tech and AI Investment

Empirical analysis in the sources indicates a strong correlation between high-quality institutions and investment in innovative sectors.

• Closing the Gap: Raising the institutional and regulatory quality of all EU countries to the level of the current "EU frontier" (the best-performing member states) could increase the share of investment in high-tech sectors by as much as 50%. This reform would effectively close the investment gap with the US by approximately half.
• Artificial Intelligence: AI-intensive sectors are particularly sensitive to these frameworks. Enhancing institutional governance could boost investment in AI-intensive sectors by over 7 percentage points.
• Economic Size: Beyond investment shares, more efficient institutions are associated with a larger relative economic size (value added) of innovative sectors compared to traditional ones.

Policy Implications

The findings suggest that for the EU to increase its competitiveness and productivity growth, it must move beyond industrial composition and address fundamental structural factors. Key recommendations include:

• Simplifying business procedures and reducing administrative burdens for entrepreneurs.
• Making labor markets more flexible to lower the costs of failure and restructuring in risky sectors.
• Strengthening governance and the rule of law to provide a more stable environment for long-term investment.
• Improving insolvency frameworks to lower the costs associated with project failures and firm exits.

The provided sources identify institutional and regulatory quality as the fundamental drivers behind the widening productivity and investment gap between the European Union and the United States. While the US has successfully pivoted toward high-growth, high-tech sectors, the EU remains caught in a "middle-technology trap," largely due to frameworks that increase the costs of innovation and failure.

Core Institutional and Regulatory Indicators

The sources evaluate institutional quality through three primary lenses, noting that higher scores in these areas are directly correlated with increased high-tech investment:

• Institutional Delivery Index: This broad measure encompasses the rule of law, control of corruption, government effectiveness, and regulatory quality. It reflects the extent to which a country provides a "level playing field" and sound economic incentives for actors to invest and innovate.
• Employment Protection Legislation (EPL): This index measures the stringency of regulations regarding worker dismissals. While some argue EPL fosters trust, the sources suggest that for high-tech sectors, strict EPL increases labor market rigidity and operational costs, making it difficult for firms to adjust their workforces in response to rapid technological shifts.
• Business Entry and Exit Frameworks: This includes the Starting a Business score (administrative burdens on entrepreneurs) and the Resolving Insolvency score (the ease and cost of firm exit).

The Mechanism: Risk and the "Cost of Failure"

The sources argue that institutional quality is more critical for high-tech sectors (e.g., AI, ICT, biotech) than for traditional mid-tech sectors because high-tech innovation is inherently disruptive and risky.

• Trial-and-Error: Innovative sectors involve significant trial-and-error and higher rates of project failure.
• Cost of Failure: The expected profitability of investing in high-tech depends heavily on the costs associated with failure and restructuring.
• Barriers to Innovation: Burdensome regulations and rigid labor laws disproportionately increase these costs, deterring firms from pursuing "primary innovation" (creating new products) and pushing them toward "secondary innovation" (improving existing products).

Empirical Impact on High-Tech and AI Investment

The research demonstrates a causal link between these factors and sectoral investment shares:

• Closing the Investment Gap: Raising the institutional and regulatory quality of all EU countries to the level of the "EU frontier" (the best-performing member states) could increase the share of investment in high-tech sectors by up to 50%. This reform alone would close the EU-US high-tech investment gap by approximately half.
• Sensitivity of AI: AI-intensive sectors are particularly sensitive to these frameworks. Improving institutional governance could boost investment in AI-intensive sectors by over 7 percentage points.
• Economic Size: More efficient institutions are associated not just with higher investment shares, but with a larger relative economic size (value added) of innovative sectors compared to traditional ones.

Institutional Origins and Policy Implications

To address potential bias, the study uses legal origins (e.g., English common law vs. French civil law) as instruments, finding that historical legal ideologies continue to influence modern regulatory stringency and, consequently, investment patterns.

The sources conclude that to escape the "middle-technology trap" and enhance competitiveness, the EU must prioritize structural reforms. These include:

1. Reducing administrative burdens for starting and managing businesses.
2. Increasing labor market flexibility to lower the costs of restructuring in risky sectors.
3. Strengthening the rule of law and governance to reduce uncertainty for long-term investors.
4. Improving insolvency frameworks to facilitate the efficient reallocation of resources from failing projects to new opportunities.

The provided sources demonstrate that institutional and regulatory quality are decisive factors in determining the size and success of high-tech sectors within the European Union. While the United States has successfully pivoted toward high-growth, high-tech industries, the EU remains largely confined to a "middle-technology trap," focusing on mature, mid-tech sectors with limited productivity spillovers.

The High-Tech Investment Disparity

The sources quantify a significant gap in high-tech investment between the two regions:

• Sectoral Concentration: In 2021, high-tech sectors accounted for 33% of market sector gross fixed capital formation in the US, nearly double the 17% share observed in the EU.
• Productivity Growth: This investment gap directly translates to slower productivity growth; the ICT sector alone explains roughly 48% of the average annual hourly productivity growth gap between the EU and the US from 2000 to 2019.
• Innovation Style: US high-tech sectors drive "primary innovation" (introducing new products), whereas the EU’s mid-tech focus results in "secondary innovation" (incremental improvements to existing products).

Vulnerability of High-Tech to Institutional Quality

High-tech sectors are uniquely sensitive to institutional and regulatory frameworks because they are inherently disruptive and risky.

• The Cost of Failure: Innovation in fields like AI, ICT, and biotechnology involves significant trial-and-error and high rates of project failure. Burdensome regulations disproportionately increase the "costs of failure and restructuring," deterring firms from investing in these volatile sectors.
• Labor Market Rigidity: Stringent Employment Protection Legislation (EPL)—regulations governing worker dismissals—increases labor market rigidity. In high-tech sectors that require frequent workforce reallocation and high mobility, strict EPL acts as a significant barrier to investment and scaling.
• Entry and Exit Barriers: Administrative burdens for starting a business and inefficient insolvency frameworks (exit costs) further discourage entrepreneurial risk-taking in cutting-edge industries.

Empirical Impact of Reform

The research indicates that improving the quality of EU institutions could dramatically reshape its high-tech landscape:

• Closing the Gap: Raising the institutional and regulatory quality of all EU countries to the level of the "EU frontier" (the best-performing member states) could increase high-tech investment shares by as much as 50%. This reform alone would close approximately half of the investment gap with the US.
• Impact on AI: Artificial Intelligence-intensive sectors are particularly responsive to these factors. Enhancing institutional governance is estimated to boost investment in AI-intensive sectors by over 7 percentage points.
• Economic Size: Beyond investment, efficient institutions are associated with a larger relative economic size (value added) of innovative and disruptive sectors compared to traditional ones.

Broader Institutional Context

The sources use legal origins (e.g., French civil law vs. English common law) as a lens to explain why these regulatory differences exist, noting that historical legal ideologies continue to influence modern state intervention and regulatory stringency. To escape the middle-technology trap, the sources conclude that the EU must prioritize structural reforms—specifically reducing administrative burdens, increasing labor market flexibility, and strengthening the rule of law—to create a dynamic environment where high-tech sectors can flourish.

The sources describe Classification of Innovativeness as a central methodological tool used to distinguish how different sectors respond to institutional and regulatory environments. By categorizing sectors based on their level of technological advancement, the researchers demonstrate that high-tech and disruptive industries are disproportionately sensitive to the quality of governance and the "cost of failure" compared to traditional, mid-tech industries.

The sources employ three distinct methods to classify sectoral innovativeness:

1. Eurostat High-Tech Taxonomy

This approach uses a binary classification (dummy variable) based on the Eurostat high-tech aggregation of NACE Rev. 2 codes at the 2-digit level.

• High-Tech Manufacturing: Includes sectors such as C21 (Pharmaceuticals) and C26 (Computers, electronic, and optical products).
• High-Tech Knowledge-Intensive Services: Includes J58–J60 (Publishing and media), J61 (Telecommunications), and J62–J63 (Computer programming and information services).
• Context: This classification helps illustrate the "middle-technology trap," where the EU remains focused on mature, mid-tech sectors while the US dominates these high-tech categories.

2. Patent Intensity

To provide a more granular, continuous measure of innovativeness, the researchers classify sectors based on their patenting activity.

• Methodology: They match International Patent Classification (IPC) codes from over 18 million US patent applications to NACE codes. US data is used specifically to mitigate endogeneity issues, ensuring that the measure of innovativeness is not biased by the EU's own institutional frameworks.
• Finding: The sources find that improvements in institutional frameworks have a disproportionately stronger effect on sectors with higher patenting activity, such as computer manufacturing (C26), compared to the lowest-ranking sectors.

3. Artificial Intelligence (AI) Intensity

This method focuses on the most modern and disruptive technological frontier using a taxonomy developed by Calvino et al. (2024). Sectors are ranked based on four dimensions of AI intensity:

• AI Human Capital Demand: Demand for AI-related skills.
• AI Innovation: Sector-specific AI-related patents.
• AI Use: The actual adoption of AI by firms.
• AI Exposure: The extent to which AI can perform tasks associated with occupations in that sector.
• Adjustment for Bias: The researchers specifically exclude regulatory barriers from the AI exposure measure to avoid "circularity," ensuring the classification isn't defined by the very regulations they are trying to study.
• Highly AI-Intensive Sectors: Beyond typical tech, this includes K (Financial and Insurance) and M (Professional, Scientific, and Technical Activities).

Significance within the Institutional Context

The classification of sectors is vital because it reveals that not all industries are affected equally by regulation.

• Risk and Uncertainty: Innovative sectors involve significant trial-and-error and higher failure rates. Therefore, high costs associated with Employment Protection Legislation (EPL), business entry, and insolvency proceedings deter investment specifically in high-tech sectors while having less impact on stable, mid-tech industries.
• Primary vs. Secondary Innovation: The sources cite research suggesting that rigid labor markets (high firing costs) lead countries to specialize in "secondary innovation" (incremental improvements), whereas flexible markets foster "primary innovation" (introducing entirely new products).
• Policy Impact: By using these classifications, the sources estimate that raising EU institutional quality to the "frontier" would boost investment in these specific high-tech and AI-intensive sectors by up to 50%, whereas traditional sectors would see a much smaller marginal impact.

The key empirical findings in the sources demonstrate a strong causal link between the quality of institutional and regulatory frameworks and the level of investment in high-tech, innovative, and AI-intensive sectors across the European Union,. These findings suggest that the EU's persistent productivity lag behind the United States is deeply rooted in governance structures that inadvertently deter investment in risky, cutting-edge industries,.

Core Findings on Investment and the EU-US Gap

The primary finding of the study is that raising the institutional and regulatory quality of all EU countries to the level of the current "EU frontier" (the best-performing member states) would have a transformative effect on the economy:

• 50% Increase in High-Tech Investment: Such reforms could increase the share of investment in high-technology sectors by as much as 50%,.
• Closing the Gap with the US: This increase would effectively close approximately half of the existing high-tech investment gap between the EU and the US,,. For context, in 2021, high-tech sectors accounted for 33% of market sector investment in the US, compared to only 17% in the EU.
• AI-Specific Gains: Enhancing institutional governance alone could boost investment in AI-intensive sectors by over 7 percentage points,.

Impact Across Different Sector Classifications

The sources used three distinct methods to classify "innovativeness," finding that better institutions consistently benefited more advanced sectors:

• High-Tech Taxonomy: More efficient institutional frameworks were positively associated with higher investment shares in sectors classified as high-tech by Eurostat.
• Patent Intensity: Improvements in institutional frameworks had a disproportionately stronger effect on sectors with higher patenting activity compared to low-innovation sectors.
• AI Intensity: Sectors with high AI intensity were found to be more sensitive to institutional conditions than traditional sectors. This effect was particularly pronounced in a more recent sample (2019–2023), reflecting AI's growing economic prominence.

The Mechanism: Risk and the "Cost of Failure"

The empirical evidence supports the theory that institutions matter most for high-tech because these sectors are inherently characterized by trial-and-error and high failure rates,.

• Sensitivity to Costs: The expected profitability of high-tech investment depends heavily on the costs of failure and restructuring.
• Burdensome Regulations: Rigid labor laws (Employment Protection Legislation) and complex administrative procedures for starting or closing a business act as "costs of failure" that deter firms from pursuing disruptive, primary innovation,,.
• Relative Success of Mid-Tech: In contrast, the sources found that mid-tech sectors, which involve lower risk and incremental innovation, are less sensitive to these regulatory constraints.

Robustness and Broader Economic Impacts

The researchers employed an Instrumental Variable (IV) approach using legal origins to establish that these findings are causal rather than just correlations,. The results remained robust even when:

• Controlling for GDP per capita and corporate tax rates,.
• Excluding financial hubs like Ireland and Luxembourg.
• Using Value Added Share as a dependent variable, which showed that better institutions are associated with a larger relative economic size for innovative sectors,.
• Using Insolvency Frameworks as an indicator; efficient insolvency procedures were found to be highly important for investment in innovative sectors.

Policy Implications

The empirical results suggest that to escape the "middle-technology trap," the EU must prioritize structural reforms that lower the barriers to entry and the costs of failure,. Specifically, the sources recommend easing labor market rigidities, reducing administrative burdens for startups, and improving insolvency frameworks to allow for a more dynamic reallocation of resources toward frontier technologies,.

The provided sources suggest that the European Union’s productivity lag is not merely a result of industrial preference but is deeply rooted in the quality of its governance and regulatory frameworks. To bridge the investment gap with the United States and escape the "middle-technology trap," the sources propose several critical policy shifts focused on lowering the costs of innovation and failure.

1. Strengthening Institutional Governance and the Rule of Law

The sources emphasize that high-quality institutions are the foundation of a competitive high-tech economy.

• Effective Governance: Policies should aim to improve "Institutional Delivery," which includes strengthening the rule of law, controlling corruption, and enhancing government effectiveness.
• Reducing Uncertainty: Sound institutions provide a "level playing field" and reduce the economic uncertainty that often discourages long-term, high-risk investments in disruptive technologies.
• Economic Impact: The sources estimate that elevating institutional quality to the level of the "EU frontier" (the highest-performing member states) could increase the high-tech investment share by roughly 30%.

2. Enhancing Labor Market Flexibility (EPL Reform)

A major policy implication involves the reform of Employment Protection Legislation (EPL), which governs the strictness of worker dismissals.

• Lowering Reallocation Costs: Disruptive innovation requires frequent workforce reallocation and rapid scaling. Current rigidities increase operational costs and deter firms from pursuing high-risk, primary innovation (introducing new products) in favor of safer, secondary innovation (improving existing products).
• Targeted Flexicurity: Policymakers are encouraged to ease firing costs, which would incentivize firms to enter sectors characterized by risky technology and trial-and-error processes.

3. Reducing Administrative and Exit Burdens

The sources identify business entry and exit barriers as significant deterrents to high-tech dynamism.

• Simplifying Start-ups: Reducing the administrative burden on entrepreneurs (as measured by the "Starting a Business score") is one of the most effective ways to boost investment; reforms in this area alone could increase high-tech investment shares by up to 50%.
• Insolvency Frameworks: Efficient insolvency procedures are critical because they lower the "cost of failure". Policies that make it easier and cheaper to resolve insolvency allow resources to be reallocated more dynamically from failing projects to frontier technologies.

4. Fostering AI and Frontier Technology Adoption

Given that AI-intensive sectors are particularly sensitive to regulatory environments, the sources suggest that general institutional improvements will have a disproportionately positive effect on the AI landscape.

• Recent Relevance: Analysis of the 2019–2023 period shows that as AI technology has matured, the importance of institutional quality in fostering its adoption has increased.
• Sensitivity: Enhancing governance could boost investment in AI-intensive sectors by over 7 percentage points.

5. Integrating Complementary Enablers

While structural and regulatory reforms are central, the sources conclude they must be part of a broader, integrated strategy.

• Beyond Regulation: Reforms to labor markets and administrative procedures need to be complemented by access to finance, robust digital infrastructure, and education/skill-upgrading systems.
• Global Competitiveness: Combining these structural improvements with innovation enablers is seen as the only viable path to closing the productivity and investment gap with the US.