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A Review of the Research on Financial Performance and Its Determinants

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• First Online: 30 May 2020
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• Mihaela Brindusa Tudose 5 &
• Silvia Avasilcai 5  

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• International Symposium in Management Innovation for Sustainable Management and Entrepreneurship

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To carry out the review, the study was designed in such a manner as to enable us to: (a) identify the degree of interest that researchers displayed for scientific grounding of concepts they operate with and (b) identify the degree to which new lines of research have been shaped on determinants of financial performance. Based on a sample of 45 articles which analyzed the corporate financial performance, published during 2014–2019, was established a database which details: the researches’ topic; dependent and independent analyzed variables (and the indicators used for their assessment); samples; sources of data and periods in which they have been collected; results of the research; and authors’ contributions in defining the concept of performance. In terms of study’s first aim, we have shown that authors are concerned with grounding concepts with which they operate, but they mostly focus on the determinants and not on the financial performance. In terms of determinants of the financial performance, the study reveals that the research is more detailed and they extend the analyses with new variables (such as ethics of stakeholders, corporate lobbying, corporate culture, green credit or non-financial reporting) for explaining the dynamics of the financial performance.

• Performance
• Financial performance
• Determinants
• Authors’ contributions

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Tudose, M.B., Avasilcai, S. (2020). A Review of the Research on Financial Performance and Its Determinants. In: Prostean, G., Lavios Villahoz, J., Brancu, L., Bakacsi, G. (eds) Innovation in Sustainable Management and Entrepreneurship. SIM 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-44711-3_17

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The main goal of my article is to provide students with valuable information and practical guidance on how to navigate the world of financial research papers. Drawing on my knowledge and experience as a researcher, I will share tips, techniques, and best practices that will help students improve their research skills, master the art of writing a compelling paper, and present their findings effectively.

• The Importance of Research Papers in the Study of Finance

I believe that research papers are of great importance in the field of financial studies. They serve as a platform for students to contribute to existing knowledge, challenge prevailing theories, and offer innovative ideas.

Through research papers, students have the opportunity to critically analyze complex financial concepts, conduct empirical research, and provide evidence-based findings that can be used in policy and practice.

Research papers allow students to develop important skills such as critical thinking, data analysis, literature review, and effective communication. These skills are highly valued in the financial industry, where professionals must make informed decisions, evaluate financial strategies, and communicate their findings to various stakeholders.

• Understanding the Structure of Finance Research Papers

In order to effectively navigate the world of financial research papers, it is crucial to understand the standard structure that underlies these research papers. Specific requirements may vary from institution to institution and discipline to discipline. But trust me, there are common components that you will definitely find in many finance research papers.

• Components of a Finance Research Paper

The abstract is a concise summary of your research paper that provides an overview of the objectives, methodology, key findings, and conclusions of the study. Although it appears at the beginning of the paper, it is usually written after the entire research process is completed.

The abstract plays a vital role in keeping the reader interested and conveying the essence of your research.

Introduction

The introduction sets the stage for your research paper by introducing the research problem, emphasizing its importance, and providing necessary background information. It should clearly state the research question or objective and provide a rationale for its importance.

The introduction should provide a brief review of the literature relevant to your research and explain how your research contributes to existing knowledge in the field.

Literature Review

The literature review section critically examines the existing body of knowledge and research related to your topic. This involves conducting a thorough review of relevant academic articles, books, reports, and other scholarly sources.

The literature review should identify key theories, concepts, and debates in the field. You can highlight gaps in research or unresolved issues, and lay the groundwork for your research by defining its context and significance.

Methodology

The Methodology section describes the research design, data collection methods, and analytical techniques used in your study. It should include a clear and detailed explanation of how you collected and analyzed data to address your research question.

Depending on the nature of your research, the methodology may include quantitative or qualitative approaches, surveys, interviews, experiments, or archival research. Transparency and accuracy in describing your methodology is crucial to ensure the accuracy and reproducibility of your research.

Data Analysis and Results

In the Data Analysis and Results section, you present the conclusions of your research based on the data you have collected. This section involves organizing, analyzing, and interpreting the data using appropriate statistical or qualitative methods.

It is important to present the results in an objective and concise manner, using tables, charts, or graphs to increase clarity and understanding. I advise you to provide sufficient context and explanation of the results so that readers can interpret them correctly.

Discussion and Interpretation

The Discussion and Interpretation section allows you to delve into the meaning of your results and relate them to existing theories, concepts, or practical applications. Here you can analyze the significance of your results, assess their consistency with previous research.

Be sure to discuss limitations or problems you encountered during your research and offer possible explanations or recommendations. This section provides an opportunity for critical thinking, reflection, and synthesis of your research findings.

Conclusions

The conclusion is the final section of your research paper that summarizes the main findings, restates the research question or objective, and discusses the broader implications of your research. It should provide a concise summary of the main issues addressed in the paper and conclude the description of the research.

In conclusion, I often highlight areas for future research. In this way, I emphasize the policy or practical implications and also emphasize the significance of my work.

• Choosing a Relevant Research Topic in Finance

I always spend my time choosing an interesting and relevant research topic. This is the first important step on the way to writing a research paper in finance.

A well-chosen topic will not only sustain your interest throughout the research process, but will also contribute to the existing body of knowledge in the field.

• The Importance of Choosing an Interesting Research Topic

An interesting research topic in the field of finance serves as the basis for a successful research paper. It should be relevant, meaningful, and intellectually stimulating. When choosing a topic, I take into account its potential for gaining new knowledge, filling gaps in the existing literature, or offering innovative solutions to financial problems. One of my recent studies was about the costs of helping schools in the wake of the pandemic , which I prepared for Forbes.com.

Fascinating topics not only attract the attention of readers, but also inspire your own curiosity and passion, making the research process more enjoyable and rewarding.

An interesting research topic can raise your academic and professional profile. It demonstrates your knowledge and interests in specific areas of finance, allowing you to establish yourself as a knowledgeable and competent researcher. It can also open doors for collaboration, networking, and future research opportunities.

• Strategies for Identifying Research Gaps

Identifying research gaps is an important step in selecting an appropriate research topic. Research gaps are areas in the existing literature where knowledge is limited, contradictory, or outdated.

By identifying these gaps, you can contribute to the field by filling in the missing pieces of the puzzle or questioning existing assumptions.

Use the following strategies to identify research gaps in finance:

• Literature review: Conduct a thorough review of relevant research articles, journals, books, and reports to identify areas where the literature is insufficient, contradictory, or outdated. Look for unanswered questions, unresolved debates, or emerging trends that have not been explored in detail.
• Industry reviews: Stay up to date on the latest developments, challenges, and emerging trends in the financial industry. Network with professionals, attend conferences and webinars, and follow industry publications to gain insight into potential research gaps that need further exploration.
• Consult with experts: Seek advice from professors, mentors, or experts in the field of finance. They can provide valuable insights into current research gaps and suggest potential research topics based on their experience and knowledge.
• Analyze policies and practices: Examine financial policies, regulations, or practices and identify areas where research can contribute to improved financial decision-making, risk management, or efficiency. Look for gaps between theory and practice that require further research.
• Explore interdisciplinary connections: Consider interdisciplinary approaches by exploring the connections between finance and other fields such as economics, psychology, sociology, or technology. These intersections often create unique opportunities for innovative research.
• Narrowing and Refining the Research Topic

Once you have identified the broad research area and potential research gaps, it is important to narrow and refine your research topic. In my opinion, this process involves focusing on your research question, clarifying the scope of your research, and ensuring that it is feasible within the resources and timeframe available.

Narrowing and refining the research topic:

• Define the research question: Clearly articulate the specific research question or objective that your research aims to address. Make sure it is specific, concise, and measurable. This will help guide your research and keep it focused.
• Conduct preliminary research: Conduct initial investigations and exploratory research to gain a deeper understanding of your chosen topic. This will help you refine your research questions and identify any specific sub-topics or aspects you want to explore.
• Consider feasibility: Assess the feasibility of your research topic in terms of data availability, resources, and time constraints. Ensure that you have access to the necessary data sources, research tools, and expertise needed to conduct the research effectively.
• Conducting Thorough Literature Reviews in Finance

The purpose of a literature review is to identify and analyze relevant research sources, synthesize key findings, and set the context for your own research. By conducting a thorough literature review, you demonstrate your familiarity with previous work, identify gaps in the existing literature, and build a solid foundation for your research.

• Effective Strategies for Collecting Relevant Literature

To collect the necessary literature for your finance research paper, use the following strategies:

Use Academic Databases

Access reputable academic databases such as JSTOR, Google Scholar, or specialized finance journals to find relevant research articles, books, conference proceedings, and reports. Use keywords, subject headings, and advanced search functions to refine your search results.

Keep Track of Citations

Study the reference lists of articles and books that you think are relevant to your research topic. Follow the “citation trails” to find additional sources that are frequently cited or considered seminal works in the field.

Search for Citations

Identify influential articles or books related to your research topic and use citation databases such as Web of Science or Scopus to find more recent articles that cite these influential works. This method will help you identify recent research that builds on or challenges existing theories.

Consult with Experts in Your Field

Ask your professors, mentors, or experts in finance for recommendations on the primary literature or seminal works in your research area. They can provide valuable insight into the most current and influential literature in the field.

• Evaluating and Analyzing Existing Research in Finance

When evaluating and analyzing existing research in finance, consider the following aspects:

Assess the relevance of each source to your research topic and research question. Look for studies that directly address your research objectives or provide insights that are applicable to your study.

Credibility and Quality

Evaluate the credibility and quality of the sources by considering factors such as the reputation of the authors, the rigor of the research methodology employed, the peer-review process, and the publication venue. Focus on peer-reviewed academic journals and reputable publishers.

Strengths and Limitations

Analyze the strengths and limitations of each study to understand its contributions and potential shortcomings. Consider the research design, sample size, data collection methods, and analytical techniques used.

Consistency and Contradictions

Identify consistent findings across multiple studies and note any contradictions or discrepancies. These inconsistencies may indicate areas where further research is needed or potential research gaps.

• Identifying Key Debates and Research Gaps in the Literature

As you analyze the existing literature in finance, pay attention to key debates, unresolved questions, and research gaps. Note any conflicting findings, theoretical disagreements, or emerging trends that require further investigation. Identifying these gaps and debates will help you position your own research within the broader context of the field and contribute to knowledge expansion.

• Developing a Strong Methodology for Finance Research

Research methodologies in finance encompass a range of approaches that enable researchers to investigate financial phenomena, test hypotheses, and analyze data. It is essential to understand the various methodologies available to select the most suitable one for your research. Common research methodologies in finance include quantitative methods, qualitative methods, and mixed-methods approaches.

• Selecting the Appropriate Research Methodology

Selecting the appropriate research methodology in finance is crucial for addressing your research question and achieving your research objectives. Consider the following factors when choosing a methodology:

Research Question

Assess whether your research question requires a quantitative analysis, qualitative exploration, or a combination of both. Quantitative methods involve collecting and analyzing numerical data, while qualitative methods focus on understanding the meaning and context of phenomena through interviews, observations, or textual analysis.

Data Availability

Evaluate the availability and accessibility of relevant data sources. Some research questions may require existing datasets, while others may necessitate primary data collection through surveys, interviews, or experiments.

Research Design

Determine the most appropriate research design for your study. This involves deciding whether your research will be cross-sectional, longitudinal, experimental, or case-based. Each design offers unique advantages and suits different research objectives.

Resource Constraints

Consider the available resources, such as time, budget, and expertise, that impact your choice of methodology. Some methodologies may require more extensive data collection efforts, advanced statistical analysis, or specialized software.

• Data Collection Techniques and Sources in Finance Research

Once you have selected a research methodology, you need to determine the most suitable data collection techniques and sources. The choice of data collection methods depends on the research objectives, available resources, and the type of data required.

In finance research, common data collection techniques include:

Surveys involve administering structured questionnaires to collect data from a sample of respondents. Surveys can provide valuable insights into financial behaviors, attitudes, and preferences.

Interviews allow for in-depth exploration of topics and enable researchers to gather qualitative data through direct conversations with individuals or groups. Interviews can provide rich insights into financial decision-making processes and subjective experiences.

Document Analysis

Document analysis involves examining financial reports, policy documents, company filings, or other relevant documents to gather data and insights. This technique is often used to analyze financial statements, market reports, or policy documents.

Observations

Observations involve systematically observing financial behaviors, market activities, or organizational processes. This technique can provide valuable insights into real-time financial phenomena and behaviors.

When selecting data sources for finance research, consider both primary and secondary sources. Primary sources include original data collected specifically for your study, such as surveys or interviews.

Secondary sources comprise existing data from academic journals, government reports, financial databases, or company records. My choice of data sources depends on the research objectives, data availability, and the level of detail required.

• Ensuring Research Validity and Reliability

Ensuring research validity and reliability is crucial for producing trustworthy and credible findings in finance research. Validity refers to the extent to which your research accurately measures what it aims to measure, while reliability refers to the consistency and repeatability of your research results. To enhance research validity and reliability in finance:

• Define and Operationalize Variables – Clearly define and operationalize your variables to ensure that you are measuring the intended constructs accurately. Clearly specify the measurement scales, indicators, and operational definitions.
• Use Appropriate Sampling Techniques – Select appropriate sampling techniques to ensure that your sample represents the target population. Random sampling, stratified sampling, or purposive sampling can be employed based on your research objectives and available resources.
• Employ Robust Data Analysis Techniques – Use appropriate data analysis techniques that align with your research methodology and research questions. For quantitative research, statistical methods such as regression analysis, hypothesis testing, or time series analysis may be applicable. Qualitative research may involve thematic analysis, content analysis, or discourse analysis. Ensure that your chosen analysis techniques are reliable and provide meaningful insights.
• Maintain Data Integrity – Pay attention to data quality and integrity throughout the research process. Implement data validation measures, check for outliers or inconsistencies, and ensure accurate data entry and coding. Document your data collection and management processes to facilitate transparency and reproducibility.
• Address Potential Bias – Identify and address potential sources of bias in your research. Common types of bias in finance research include selection bias, response bias, and measurement bias. Implement strategies such as randomization, control groups, or multiple data sources to mitigate bias and enhance research validity.
• Triangulation of Findings – Consider triangulation by combining multiple methods, data sources, or researchers’ perspectives to strengthen the validity and reliability of your findings. Triangulation helps validate and confirm research results through different lenses and reduces the impact of individual biases.
• Peer Review and Expert Feedback – Seek peer review and expert feedback on your research design, analysis, and findings. Engage with colleagues, mentors, or subject matter experts who can provide valuable insights and constructive criticism to improve the rigor and validity of your research.
• Transparent Reporting – Clearly document and report your research methods, data collection procedures, and analysis techniques. Provide sufficient detail to allow other researchers to replicate your study or verify your findings. Transparent reporting enhances the trustworthiness and replicability of your research.
• Continuous Reflection and Iteration – Engage in continuous reflection on the strengths and limitations of your research. Acknowledge any potential shortcomings, discuss the implications, and suggest areas for further research. Emphasize the need for ongoing improvement and learning in the field of finance.
• Ethical Considerations – Ensure that your research adheres to ethical guidelines and standards. Protect the confidentiality and privacy of research participants, obtain informed consent, and handle sensitive financial information responsibly. Ethical conduct strengthens the credibility and trustworthiness of your research.
• Analyzing Data and Presenting Results

In finance research, essential data analysis techniques include descriptive statistics, inferential statistics, regression analysis, financial modeling, and econometric analysis.

These techniques help researchers uncover patterns, relationships, and insights within the data and provide a foundation for drawing meaningful conclusions.

• Effective Visualization and Presentation of Findings

Effective visualization and presentation of findings are crucial for conveying research results in a clear and concise manner. Utilize charts, graphs, tables, and visual representations to present data and key findings.

Choose appropriate visual formats that align with the nature of your data and research objectives. Clear and visually appealing presentations enhance understanding and facilitate communication of complex financial information.

• Interpreting Results and Drawing Conclusions

Interpreting the results of data analysis is an important step in finance research. Carefully examine the statistical significance, magnitude, and direction of relationships or differences observed in the data. Relate the findings back to your research objectives and research question.

Draw meaningful conclusions that contribute to the existing knowledge base in finance. Discuss the implications of your findings and highlight areas for future research and exploration.

• Writing and Structuring a Finance Research Paper
• Crafting a Clear and Coherent Introduction

A clear and coherent introduction sets the stage for your finance research paper. It should provide context, state the research problem, outline the research objectives, and highlight the significance of your study.

Engage the reader by clearly stating the purpose of your research and conveying the research question or hypotheses you aim to address.

• Organizing and Presenting Literature Review

Organize and present the literature review section in a logical and coherent manner. Summarize relevant studies, identify key theories or frameworks, and highlight research gaps and debates.

Analyze the literature critically and establish the need for your research. Provide a synthesis of existing knowledge that supports the rationale for your study.

• Writing a Robust Methodology Section

The methodology section describes your research design, data collection methods, and analysis techniques. Clearly explain how you collected and analyzed data, ensuring that others can replicate your study.

Justify your chosen methodology and discuss any limitations or potential sources of bias. A well-written methodology section enhances the credibility and rigor of your research.

• Structuring the Results and Discussion Section

Structure the results and discussion section in a coherent and logical manner. Present your findings objectively and clearly, using tables, graphs, or visual aids to support your results.

Interpret the results and discuss their implications, relating them back to your research question and relevant literature. Address any unexpected findings or limitations and offer possible explanations.

• Concluding the Paper with Impactful Takeaways

The conclusion should provide a concise summary of your research findings and their implications. Emphasize the significance of your study and its contribution to the field of finance. Recapitulate your research objectives and answer the research question.

Discuss the practical and theoretical implications of your findings and suggest avenues for future research. Leave the reader with impactful takeaways that reinforce the importance of your work.

• Citing Sources and Avoiding Plagiarism in Finance Research Papers

Proper citations are crucial in finance research papers to acknowledge the contributions of other scholars and uphold academic integrity.

Citations provide evidence of your research’s foundation and demonstrate your engagement with existing literature. They also allow readers to locate and verify the sources you have referenced.

• Formatting Citations in Finance Papers

Follow the appropriate citation style guide (such as APA, MLA, or Chicago) to ensure consistent and accurate formatting of citations in your finance research paper.

Pay attention to in-text citations, reference lists, and footnotes, adhering to the specific guidelines for citing books, journal articles, websites, and other relevant sources.

• Avoiding Plagiarism: Best Practices and Tools

Plagiarism, the unauthorized use of others’ work or ideas, is a serious ethical offense. To avoid plagiarism in finance research papers, practice these best practices: always attribute sources, paraphrase information in your own words, and use quotation marks when directly quoting.

Additionally, utilize plagiarism detection tools like Turnitin or Grammarly to check your work for unintentional plagiarism before submission.

• Proofreading and Editing Strategies for Finance Research Papers

Proofreading and editing are essential steps in the writing process to enhance the clarity, coherence, and professionalism of your finance research paper. These processes ensure that your paper is free from grammatical errors, typos, and inconsistencies, allowing your ideas to shine through effectively.

• Common Errors to Look Out for in Finance Papers

When proofreading and editing your finance research paper, be vigilant for common errors such as spelling mistakes, punctuation errors, improper sentence structure, unclear or ambiguous language, and inconsistent formatting. Pay particular attention to technical finance terms and ensure their correct usage.

• Helpful Tips for Effective Proofreading and Editing

To effectively proofread and edit your finance research paper, consider the following tips:

• Take a break: Step away from your paper for a while before proofreading to gain a fresh perspective and approach it with a critical eye.
• Read aloud: Read your paper aloud to identify any awkward phrasing, grammatical errors, or areas that require revision. This technique helps you catch errors that may be missed when reading silently.
• Use a checklist: Create a checklist of common errors or areas to review, such as grammar, spelling, punctuation, formatting, and logical flow. Systematically go through each item on the checklist to ensure thorough proofreading.
• Seek feedback: Ask a colleague, mentor, or peer to review your paper and provide constructive feedback. A fresh pair of eyes can catch errors or inconsistencies you may have overlooked.
• Review for clarity and coherence: Ensure that your ideas are presented in a logical and organized manner. Check for clarity of expression, coherence of arguments, and smooth transitions between paragraphs and sections.
• Key Takeaways and Recap of Tips and Techniques

Navigating the world of financial research requires a combination of knowledge, skills, and effective strategies. We have covered various aspects of financial research, from understanding the structure of research papers to selecting relevant topics, conducting literature reviews, developing sound methodologies, analyzing data, and presenting results.

By following my advice and the methods we have discussed, students can increase their ability to produce high-quality financial research papers. Creating a clear and coherent introduction, organizing and presenting a comprehensive literature review, and developing a sound methodology are important steps in conducting successful research.

In addition, effective data analysis, presentation of results through visualization, and formulation of meaningful conclusions contribute to the value and impact of the study.

I also emphasized the importance of proper citation and avoiding plagiarism, ensuring academic integrity, and recognizing the contributions of other researchers. The importance of proofreading and editing strategies was emphasized as they help to eliminate errors and improve the overall clarity, coherence, and professionalism of a financial research paper.

By applying the knowledge and techniques presented in my article, students can confidently navigate the world of financial research papers and succeed in their academic pursuits. By continuing to develop their skills in financial research, they will contribute to the advancement of knowledge in this field, making a valuable contribution to the ever-evolving world of finance.

Marguerite Roza, Ph.D., is a renowned expert in education finance policy and practice. She currently holds the position of Research Professor and Director of the Edunomics Lab, a research center focused on exploring and modeling education finance policy and its implications. Her work covers a wide range of topics, including state and school district finance policy, financial equity, pensions, compensation, higher education finance, and more.

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White paper: Financial institutions should refine their cybersecurity amid AI boom

Implementing cutting-edge AI tools to detect and respond to threats is imperative, according to FSSCC. However, it is equally vital to maintain skilled human oversight to interpret AI data accurately and mitigate potential AI inaccuracies or biases, it added. The sector must continue to prioritize the adoption of AI models for fraud prevention, but it also must not forget the human element and prepare for complex phishing and social engineering tactics enabled by AI.

Aligning with approaches like the National Institute of Standards and Technology’s AI Risk Management Framework is critical, according to FSSCC. “Financial institutions must strengthen their risk management protocols, focusing on emerging risks from the increased availability of AI, especially GenAI models, which includes data positioning and model biases,” it said. At the same time, the financial sector should collaborate to develop standardized strategies for managing AI-related risk. Individually, financial institutions should recognize the value of human judgment in AI models and invest in thier workforces.

Regulators also have a role to play, according to FSSCC. “Regulators should identify clear regulatory outcomes and objectives, while enabling regulated entities the ability to deploy effective risk management techniques based on common standards and best practices,” it said.

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International Paper Co (IP) Gets a Buy from Truist Financial

Truist Financial analyst Michael Roxland maintained a Buy rating on International Paper Co ( IP – Research Report ) today. The company’s shares closed yesterday at $38.77.

Roxland covers the Consumer Cyclical sector, focusing on stocks such as Avery Dennison, International Paper Co, and O-I Glass. According to TipRanks , Roxland has an average return of 8.3% and a 63.27% success rate on recommended stocks.

In addition to Truist Financial, International Paper Co also received a Buy from Citi’s Anthony Pettinari in a report issued yesterday. However, on the same day, Wells Fargo maintained a Hold rating on International Paper Co (NYSE: IP).

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Based on International Paper Co’s latest earnings release for the quarter ending December 31, the company reported a quarterly revenue of $4.6 billion and a GAAP net loss of $284 million. In comparison, last year the company earned a revenue of $5.13 billion and had a GAAP net loss of $318 million

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International Paper Co (IP) Company Description:

International Paper Co. engages in the manufacture of paper and packaging products. It operates through the following segments: Industrial Packaging, Global Cellulose Fibers, and Printing Papers. The Industrial Packaging segment involves in the manufacturing of containerboards, which include linerboard, medium, whitetop, recycled linerboard, recycled medium, and saturating kraft. The Global Cellulose Fibers segment offers cellulose fibers product portfolio includes fluff, market, and specialty pulps. The Printing Papers segment includes manufacturing of the printing and writing papers. The company was founded by Hugh J. Chisholm in 1898 and is headquartered in Memphis, TN.

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April 20, 2023 | By Jean-Paul L’Huillier and Gregory Phelan

Can Supply Shocks be Inflationary with a Flat Phillips Curve?

Empirical estimates find that the relationship between inflation and the output gap is close to nonexistent—a so-called flat Phillips curve. We show that standard pricing frictions cannot simultaneously produce a flat Phillips curve and meaningful inflation from plausible supply shocks. This is because imposing a flat Phillips curve immediately implies that the price level is also rigid with respect to supply shocks. In quantitative versions of the New Keynesian model, price markup shocks need to be several orders of magnitude bigger than other shocks in order to fit the data, leading to unreasonable assessments of the magnitude of the increase in costs during inflationary episodes. Hence, we propose a strategic microfoundation of price stickiness in which prices are sticky with respect to demand shocks but flexible with respect to supply shocks (Working Paper no. 23-03).

April 3, 2023 | By Thomas M. Eisenbach and Gregory Phelan

Fragility of Safe Assets

The market for U.S. Treasury securities experienced extreme stress in March 2020, when prices dropped precipitously (yields spiked) over a period of about two weeks. This was highly unusual, as Treasury prices typically increase during times of stress. Using a theoretical model, we show that markets for safe assets can be fragile due to strategic interactions among investors who hold Treasury securities for their liquidity characteristics. Worried about having to sell at potentially worse prices in the future, such investors may sell preemptively, leading to self-fulfilling “market runs” that are similar to traditional bank runs in some respects. Our results motivate potential policy interventions to stabilize the market during times of stress and disruption (Working Paper no. 23-02).

March 22, 2023 | By William Chen and Gregory Phelan

Digital Currency and Banking-Sector Stability

Digital currencies provide a potential form of liquidity competing with bank deposits. We introduce digital currency into a macro model with a financial sector in which financial frictions generate endogenous systemic risk and instability. In the model, digital currency is fully integrated into the financial system and depresses bank deposit spreads, particularly during crises, which limits banks’ ability to recapitalize following losses. The probability of the banking sector being in crisis states can grow significantly with the introduction of digital currency. While banking-sector stability suffers, household welfare can improve significantly. Financial frictions may limit the potential benefits of digital currencies (Working Paper no. 23-01).

September 22, 2022 | By Andrew Ellul and Dasol Kim

Counterparty Choice, Bank Interconnectedness, and Bank Risk-taking

We investigate whether banks’ counterparty choices in OTC derivative markets contribute to network fragility. We use novel confidential regulatory data and show that banks are more likely to choose densely connected non-bank counterparties and do not hedge such exposures. Banks are also more likely to connect with riskier counterparties for their most material exposures, suggesting the existence of moral hazard behavior in network formation. Finally, we show that these exposures are correlated with systemic risk measures despite greater regulatory oversight after the crisis. (Working Paper no. 22-06).

August 23, 2022 | By Ron Alquist and Ram Yamarthy

Hedge Funds and Treasury Market Price Impact: Evidence from Direct Exposures

The increasing importance of non-bank financial intermediaries has raised new questions about the risks that hedge funds pose to the financial system. The OFR examined how changes in hedge fund exposures affect U.S. Treasury prices and the yield curve. Using confidential hedge fund data from the SEC's Form Private Fund (PF), OFR analysts calculated hedge funds' aggregate, net Treasury exposures, and their fluctuations over time. This revealed economically significant and consistent evidence that changes in hedge fund exposures are related to Treasury yield changes. Furthermore, particular strategy groups and lower-levered hedge funds were seen to have a larger estimated price impact on Treasuries. Finally, asset pricing tests show that U.S. Treasury investors demand additional return compensation due to the risks associated with hedge fund demand (Working Paper no. 22-05).

July 11, 2022 | By Todd Keister and Cyril Monnet

Central Bank Digital Currency: Stability and Information

One often cited concern about central bank digital currency (CBDC) is that it could make runs on banks and other financial intermediaries more common. This working paper identifies two ways a CBDC may enhance rather than weaken financial stability. First, banks do less maturity transformation when depositors have access to CBDC, reducing their exposure to depositor runs. Second, monitoring the flow of funds into CBDC allows policymakers to react more quickly to periods of stress, which lessens the incentive for depositors and other short-term creditors to withdraw assets (Working Paper no. 22-04).

June 28, 2022 | By Chase P. Ross, Landon J. Ross, and Sharon Y. Ross

Cash-Hedged Stock Returns

This paper studies firms’ cash holdings and the implications for asset prices and financial stability. Corporate cash piles vary across companies and over time, and cash holdings are important for financial stability because of their value in crises. Firms’ cash holdings earn low returns that are correlated across firms. Thus, the asset pricing results are important both for investors who are managing a portfolio’s risk and policymakers concerned about sources of vulnerability. We show how investors can hedge out the cash on firms’ balance sheets when making portfolio choices. Cash generates variation in beta estimates, and we decompose stock betas into components that depend on the firm’s cash holding, return on cash, and cash-hedged return. Common asset pricing premia have large implicit cash positions, and portfolios of cash-hedged premia often have higher Sharpe ratios because of the correlation between firms’ cash returns. We show the value of a dollar increased in 2020, and firms hold cash because they are riskier. (Working Paper no. 22-03).

April 14, 2022 | By Johannes Poeschl and Ram Yamarthy

Aggregate Risk in the Term Structure of Corporate Credit

Higher rates of default can occur when corporations have difficulty accessing short- and long- term credit markets, increasing risks to financial stability. This paper uses credit spread data across different maturities to study what the shape and risk sensitivity of a firm's term structure can tell us about its fragility. Firms that are more financially constrained display a negatively sloped credit spread curve, have short-term spreads that are more sensitive to aggregate conditions, and face heightened rollover risks. Such financing fragility at the short end of the curve can harm a firm's ability to take advantage of investment opportunities (Working Paper no. 22-02).

February 10, 2022 | By Samuel J. Hempel, Dasol Kim, and Russ Wermers

Financial Intermediary Funding Constraints and Segmented Markets

This working paper examines the role of financial intermediaries, namely authorized participants (APs), in the propagation of shocks across funds that they support and the underlying assets held by those funds. Corporate bond ETF trades by the Federal Reserve through the Secondary Market Corporate Credit Facility (SMCCF) beginning in May 2020 were extremely large and likely alleviated inventory capacity constraints for APs that were counterparties to those transactions. ETFs that were not traded by the Federal Reserve, but overlap in their bond holdings with those traded, exhibit a positive and significant price reaction within minutes of the transaction. Consistent evidence is found for the prices of their underlying bonds. The paper's findings support the view that the inclusion of ETFs in the SMCCF had broader "spillover" effects in stabilizing markets beyond the ETFs directly targeted by the program (Working Paper no. 22-01).

June 9, 2021 | By Mark Paddrik and H. Peyton Young

Assessing the Safety of Central Counterparties

Under central clearing, parties to a financial contract enter into two matched contracts with the central counterparty that offset one another. Central clearing protects against defaults among counterparties that could threaten financial stability, but also concentrates the risk of default at the central counterparty. This working paper shows how to estimate the probability that a central counterparty could cover any specified fraction of payment defaults by its members using public disclosure data. The framework supplements conventional risk management approaches predicated on a specific number of member defaults. The paper applies the approach to assessing the safety of a wide range of central counterparties located in different geographical regions and specializing in different asset classes (Working Paper no. 21-02).

April 1, 2021 | By Daniel Barth and R. Jay Kahn

Hedge Funds and the Treasury Cash-Futures Disconnect

This paper examines the potential financial stability risks of the Treasury cash-futures basis trade, an arbitrage of pricing differences between the two Treasury markets. Using regulatory data on hedge fund exposures and repurchase agreement (repo) transactions, the paper provides evidence that at its peak the trade was associated with more than half of hedge funds' Treasury positions and a quarter of dealers' repo lending. The trade exposes hedge funds to rollover risk on repo financing and margin risk on the futures, both of which materialized in March 2020. While Treasury market disruptions spurred hedge funds to sell Treasuries, the unwinding of the basis trade was likely a consequence rather than the primary cause of the stress. We present evidence suggesting prompt intervention by the Federal Reserve prevented larger spillovers from the trade into broader Treasury market functioning. (Working Paper no. 21-01)

December 3, 2020 | By Berardino Palazzo and Ram Yamarthy

Credit Risk and the Transmission of Interest Rate Shocks

Unexpected changes in interest rates, often observed through the course of monetary policy, can have a significant effect on corporate credit risk. Using high frequency measures of interest rate surprises surrounding Federal Open Market Committee announcements and daily credit default swap (CDS) spreads, this paper finds a positive, significant relationship between monetary policy shocks and corporate credit risk over the last two decades. One component of the spread affected is compensation related to expected losses in default. The other affected component is the credit risk premium, which measures additional compensation for default risk. Riskier firms, with higher CDS spreads or leverage, or lower market capitalization, are much more sensitive to monetary policy shocks. Among the three measures of firm risk, CDS spreads appear to capture this sensitivity best. High frequency and daily equity returns also exhibit a significant and asymmetric response to policy announcements. (Working Paper no. 20-05)

June 18, 2020 | By Mark Paddrik and Simpson Zhang

Central Counterparty Default Waterfalls and Systemic Loss

This paper examines how a central counterparty (CCP) uses a default waterfall to manage and allocate resources to cover defaults of clearing members and clients. A resilient waterfall ensures cleared payments are paid in full and on-time, reducing the threat to financial stability from losses and their spillovers. However, the amount of resources collected and their allocation affect clearing incentives. This paper models and evaluates the trade-offs between resiliency and participation in a credit default swaps market. It finds that the benefits of greater central clearing rates generally dominate the benefits of increased waterfall resources. (Working Paper no. 20-4)

February 25, 2020 | By Daniel Barth and Phillip Monin

Illiquidity in Intermediate Portfolios: Evidence from Large Hedge Funds

This paper examines whether hedge funds’ returns include a premium that compensates investors for accepting the risk from illiquid asset holdings. It finds that the premium is large and a significant share of risk-adjusted returns. The size of the premium matters for financial stability because it signals investors’ view of the importance of illiquidity risk. (Working Paper no. 20-03)

February 25, 2020 | By Daniel Barth, Laurel Hammond, and Phillip Monin

Leverage and Risk in Hedge Funds

This paper examines the relationship between hedge funds’ use of leverage and their portfolio risk. It finds that more leveraged funds tend to have less volatile returns and less chance of an extreme negative return. More leveraged funds also tend to hold higher quality and more liquid assets. (Working Paper no. 20-02)

February 25, 2020 | By Daniel Barth, Juha Joenvaara, Mikko Kauppila, and Russ Wermers

The Hedge Fund Industry is Bigger (and has Performed Better) Than You Think

This paper shows that hedge fund industry gross assets exceeded $8.3 trillion, and net assets were at least $5.0 trillion, at year-end 2016. This estimate is around 37 percent larger than the next largest estimate. This paper also shows that funds reporting publicly available data have much lower returns, and much higher net flows, than funds reporting only non-public regulatory data. The outperformance of the non-publicly reporting funds appears to arise entirely from alpha rather than greater exposure to systematic risk factors. (Working Paper no. 20-01)

October 23, 2019 | By Robert Garrison, Pankaj Jain, and Mark Paddrik

Cross-Asset Market Order Flow, Liquidity, and Price Discovery

This paper examines the complex intra-day linkages between the U.S. equity securities market and the equity derivatives market. The paper finds a positive, but short-lived, relationship between the two markets’ order flow activities, which relate to the supply, demand, and withdrawal of liquidity between the two markets. The paper also finds that cross-asset market order flow is a key component of liquidity and price discovery, particularly during periods of market volatility. (Working Paper no. 19-04)

October 1, 2019 | By Mathias S. Kruttli, Phillip J. Monin, and Sumudu W. Watugala

The Life of the Counterparty: Shock Propagation in Hedge Fund-Prime Broker Credit Networks

This paper shows the post-crisis hedge fund-prime broker credit network is concentrated among 10 percent of participants. The average fund borrows from three brokers, and the brokers lending the most are highly connected. The paper finds that a liquidity shock to a prime broker results in reduced borrowing by hedge funds due to the broker reducing its supply of credit. Larger, more connected, and better-performing funds, and those that do less over-the-counter trading, are better able to compensate for the reduction in credit from the broker. (Working Paper no. 19-03)

August 6, 2019 | By Meraj Allahrakha, Jill Cetina, Benjamin Munyan, and Sumudu Watugala

The Effects of the Volcker Rule on Corporate Bond Trading: Evidence from the Underwriting Exemption

This paper examines the impact of the Volcker rule, which bans proprietary trading by commercial banks and their affiliates, with some exceptions. It finds evidence that the rule has increased the cost of liquidity provided by firms it covers, but not decreased the firms’ exposure to liquidity risk. It also finds that the rule has decreased the market share of covered firms. Customers appear to be trading more with non-bank dealers, who are exempt from the Volcker rule but also cannot borrow at the Federal Reserve's discount window. (Working Paper no. 19-02)

March 12, 2019 | By Mark Paddrik and Stathis Tompaidis

Market-Making Costs and Liquidity: Evidence from CDS Markets

This paper examines whether liquidity deteriorated in the single-name credit default swaps market due to regulatory reforms after the 2007-09 financial crisis. It finds evidence of both increased spreads and lower volumes, consistent with the reforms increasing the cost of market-making for bank-dealers. It also finds that transaction prices between dealers and clients have become more dependent on the inventories of individual dealers as interdealer trade has declined. (Working Paper no. 19-01)

October 9, 2018 | By Haelim Anderson, Daniel Barth, and Dong Beom Choi

Reducing Moral Hazard at the Expense of Market Discipline: The Effectiveness of Double Liability Before and During the Great Depression

This paper examines the impact of double liability on bank risks and depositor safety before and during the Great Depression. Under double liability, shareholders of failing banks lost their initial investments and had to pay up to the par value of their stock to compensate depositors. The paper finds that double liability did not reduce bank risk before the Great Depression, but that deposits were less susceptible to runs. (Working Paper no. 18-06)

August 29, 2018 | By Andrea L. Eisfeldt, Bernard Herskovic, Sriram Rajan, and Emil Siriwardane

OTC Intermediaries

This paper estimates the systemic effects of exit by a key over-the-counter (OTC) intermediary. In the model, risk-averse traders are connected by a core-periphery network. If traders are also averse to concentrated bilateral exposures, then the incomplete network prevents full risk sharing. The impact of the network structure on prices is quantified using proprietary data on all credit default swap transactions in the United States from 2010 to 2013. There are a small number of key OTC intermediaries whose exit can move markets dramatically. Eliminating one of these intermediaries leads to over a 20 percent increase in credit spreads. The Internet Appendix includes extensions of the model. (Working Paper no. 18-05)

August 28, 2018 | By Agostino Capponi, Paul Glasserman, and Marko Weber

Swing Pricing for Mutual Funds: Breaking the Feedback Loop Between Fire Sales and Fund Runs

This paper develops a model of a downward spiral of falling prices and increasing redemptions that can lead to the failure of a mutual fund. It shows how mutual funds can best design swing pricing for effectiveness at preventing runs, even under extreme market stress. (Working Paper no. 18-04)

April 19, 2018 | By Simpson Zhang and Mihaela van der Schaar

Reputational Dynamics in Financial Networks During a Crisis

This paper studies the role of learning and reputation in economic networks, such as interbank lending and derivatives trading networks, in times of market distress or financial crisis. The model demonstrates the importance of maintaining firm anonymity and identifies network structures that offer increased resilience. (Working Paper no. 18-03)

April 10, 2018 | By Jen-Wen Chang and Simpson Zhang

Competitive Pay and Excessive Manager Risk-taking

This paper assesses whether compensation plans can drive excessive risk-taking. It develops a model showing that principals offer contracts incentivizing less risky behavior when the market for managers is sluggish. But hot labor markets result in contracts that incentivize risk-taking. The market for executive talent heats up for larger projects and during financial bubbles, when debt funding increases. The results suggest policymakers should consider the impacts of compensation and corporate governance policies on competition for managers. (Working Paper no. 18-02)

March 28, 2018 | By Joe McLaughlin, Adam Minson, Nathan Palmer, and Eric Parolin

The OFR Financial System Vulnerabilities Monitor

This paper describes the purpose, construction, interpretation, and use of the OFR Financial System Vulnerabilities Monitor. The monitor, a heat map of 58 quantitative indicators, is a starting point for assessing vulnerabilities in the U.S. financial system. The OFR launched the monitor in 2017 to help fulfill its mandate to measure and monitor risks to U.S. financial stability. (Working Paper no. 18-01)

December 15, 2017 | By Mathias S. Kruttli, Phillip J. Monin, and Sumudu W. Watugala

Investor Concentration, Flows, and Cash Holdings: Evidence from Hedge Funds

Some hedge funds have a few large investors. Such a concentrated investor base can make a fund vulnerable to unexpected requests for large redemptions. This paper shows that U.S. hedge funds in part account for that risk by holding more cash and liquid assets. These holdings help funds accommodate large outflows, but also result in lower risk-adjusted returns. The Internet Appendix includes methodology details. (Working Paper no. 17-07)

November 2, 2017 | By Mark Paddrik and H. Peyton Young

How Safe are Central Counterparties in Derivatives Markets?

How likely is a central counterparty, or CCP, to default after a severe credit shock? This working paper uses credit default swap data to estimate the direct and indirect impacts of a default by CCP counterparties in derivatives trades. It finds that a CCP could be more vulnerable to failure than conventional stress tests have shown. (Working Paper no. 17-06)

October 31, 2017 | By Kenechukwu Anadu and Viktoria Baklanova

The Intersection of U.S. Money Market Mutual Fund Reforms, Bank Liquidity Requirements, and the Federal Home Loan Bank System

After the financial crisis, reforms of money market funds and changes to banks’ liquidity requirements had an unintended consequence of increased Federal Home Loan Banks’ reliance on short-term funding from money market funds to finance longer-term loans and other assets. This increase could make the financial system more vulnerable and pose risks to financial stability. (Working Paper no. 17-05)

October 25, 2017 | By Phillip Monin

The OFR Financial Stress Index

The 2007-09 financial crisis showed that stress in the financial system can have devastating effects on the economy. To measure such stress, the OFR has developed a Financial Stress Index. This working paper describes how the index is constructed and how the OFR uses it to monitor financial stability. (Working Paper no. 17-04)

September 29, 2017 | By Mark D. Flood, Dror Y. Kenett, Robin L. Lumsdaine, and Jonathan K. Simon

The Complexity of Bank Holding Companies: A New Measurement Approach

Some bank holding companies are very complex, with hundreds or thousands of subsidiaries. This complexity complicates the job of unwinding a failed bank holding company. In this working paper, OFR researchers propose a new way to measure complexity that can support the resolution process after a bank holding company fails. (Working Paper no. 17-03)

April 5, 2017 | By Katherine Gleason, Steve Bright, Francis Martinez, and Charles Taylor

Europe’s CoCos Provide a Lesson on Uncertainty

European banks issue contingent convertible bonds. These bonds can force investors to absorb losses when a bank is under stress. The authors find that heightened uncertainty about discretion by banks on when to make payments to investors and by regulators on when to trigger a loss absorption mechanism worsened price declines in a stressed market. (Working Paper no. 17-02)

February 21, 2017 | By Paul Glasserman and Qi Wu

Persistence and Procyclicality in Margin Requirements

This paper describes how to set margin levels for derivatives contracts so that margin calls do not add to market stress during times of instability. Price volatility varies by asset class. Certain qualities of volatility should be taken into account to set the most effective margin levels without adding to market stress. (Working Paper no. 17-01)

December 20, 2016 | By Anqi Liu, Mark Paddrik, Steve Yang, and Xingjia Zhang

Interbank Contagion: An Agent-based Model Approach to Endogenously Formed Networks

The authors create an agent-based model that can help regulators understand risk in the interbank funding market. Tests of the model against actual bank failures before, during, and after the 2007-09 financial crisis suggest that the market has become more resilient to asset write-downs and liquidity shocks. The model uses balance sheet data from more than 6,600 U.S. banks. (Working Paper no. 16-14)

December 6, 2016 | By Mark Paddrik, Haelim Park, and Jessie Jiaxu Wang

Bank Networks and Systemic Risk: Evidence from the National Banking Acts

This paper uses unique data to analyze how the national banking acts in 1863 and 1864 reshaped the U.S. bank network in the 1860s. The laws concentrated reserves in New York and regional cities, creating systemically important banks. The paper shows this concentration made contagion more likely if big banks faced economic shocks. (Working Paper no. 16-13)

December 1, 2016 | By Mark Paddrik, Sriram Rajan, and H. Peyton Young

Contagion in the CDS Market

This paper assesses the risk of contagion in the credit default swap (CDS) market. This risk emerges through the inability of CDS counterparties to make payments during systemic stress. The authors find that the central counterparty contributes significantly less to network contagion than do several peripheral firms that are large net sellers of CDS protection. (Working Paper no. 16-12)

November 10, 2016 | By Meraj Allahrakha, Jill Cetina, and Benjamin Munyan

Do Higher Capital Standards Always Reduce Bank Risk? The Impact of the Basel Leverage Ratio on the U.S. Triparty Repo Market

This paper examines how risk-taking in the repurchase agreement, or repo, market changed after regulators introduced the supplementary leverage ratio for banks. The paper finds that broker-dealers owned by U.S. bank holding companies now borrow less in the repo market overall after the change, but a larger percentage of the borrowing is backed by more risky collateral. (Working Paper no. 16-11)

October 11, 2016 | By Richard Neuberg, Paul Glasserman, Benjamin Kay, and Sriram Rajan

The Market-implied Probability of European Government Intervention in Distressed Banks

This paper assesses the likelihood of European government support in distressed banks. To measure market expectations of these events, the authors study the credit spread between old credit default swap contracts and new ones with a definition of default linked to government intervention. (Working Paper no. 16-10)

September 27, 2016 | By Matthias Raddant and Dror Y. Kenett

Interconnectedness in the Global Financial Market

This working paper shows how network analysis can facilitate the monitoring of movements by stocks in the global financial system over time. The paper analyzes nearly 4,000 stocks in 15 countries. It concludes that stock returns tend to move together within regions — but not across them — in times of stability, but move in sync globally in times of crisis. (Working Paper no. 16-09)

August 23, 2016 | By Viktoria Baklanova, Cecilia Caglio, Frank Keane, and Burt Porter

A Pilot Survey of Agent Securities Lending Activity

A new securities lending survey sheds light on these transactions that help underpin smooth-functioning capital markets. The pilot project by the OFR, Federal Reserve, and staff of the Securities and Exchange Commission shows that participating agents facilitated about $1 trillion in daily securities loans during a three-day period in 2015. Collecting these data on a permanent basis could help regulators identify potential vulnerabilities in a key component of our financial system. (Working Paper no. 16-08)

July 26, 2016 | By Samim Ghamami and Paul Glasserman

Does OTC Derivatives Reform Incentivize Central Clearing?

The requirement that standardized over-the-counter derivatives be cleared through central counterparties, or CCPs, is intended in part to create a cost incentive favoring central clearing. This working paper shows that the cost incentive does not necessarily favor central clearing, and when it does, it might be because of insufficient levels of guarantee funds, which banks provide to protect CCPs in the event of CCP member default. (Working Paper no. 16-07)

May 26, 2016 | By Andrea Aguiar, Richard Bookstaber, Dror Y. Kenett, and Thomas Wipf

A Map of Collateral Uses and Flows

Collateral is exchanged among market participants to support financial activities, including secured funding, securities lending, securities exchanges, margin lending, derivatives, and clearing. This working paper creates a collateral map to show how collateral moves among bilateral counterparties, triparty banks, and central counterparties, and can spread stress through the financial system. The paper also discusses the recent increase in collateral demand, effects of post-crisis regulation, and collateral-related stress scenarios. (Working Paper no. 16-06)

May 11, 2016 | By Cindy M. Vojtech, Benjamin S. Kay, and John C. Driscoll

The Real Consequences of Bank Mortgage Lending Standards.

This paper describes how mortgage lending standards, as measured by responses to the Federal Reserve's quarterly Senior Loan Officer Opinion Survey, relate to changes in the availability of mortgage loans at banks from 1990 to 2013. The research suggests that the survey's reported changes in credit standards are a leading indicator of the financial industry's vulnerability to shocks. (Working Paper no. 16-05)

April 20, 2016 | By Harry Mamaysky and Paul Glasserman

Does Unusual News Forecast Market Stress?

This paper investigates the use of automated text analysis by computers as a tool for monitoring financial stability. The authors find negative sentiment extracted from tens of thousands of news articles about 50 large financial services companies is useful in forecasting volatility in the stock market. The method, which also considers the "unusualness" of news, may help anticipate stress in the financial system. (Working Paper no. 16-04)

March 30, 2016 | By John Bluedorn and Haelim Park

Stopping Contagion with Bailouts: Microevidence from Pennsylvania Bank Networks During the Panic of 1884

This working paper examines how a bailout orchestrated by New York Clearinghouse member banks stopped financial contagion during the Panic of 1884. The private-sector assistance to Metropolitan National Bank, an important correspondent bank for many banks outside New York City, prevented a minor financial crisis in New York from becoming a broad, systemic event, according to the authors' analysis. (Working Paper no. 16-03)

March 23, 2016 | By Mark D. Flood and Phillip Monin

Form PF and Hedge Funds: Risk-measurement Precision for Option Portfolios

This paper examines the precision of Form PF in measuring the risk hedge funds pose to the financial system. Hedge funds and other private funds now file Form PF with the Securities and Exchange Commission. The paper extends the methodology of a 2015 OFR working paper and finds that options significantly weaken the risk-measurement tolerances in Form PF. (Working Paper no. 16-02)

March 8, 2016 | By Jill Cetina, Mark Paddrik, and Sriram Rajan

Stressed to the Core: Counterparty Concentrations and Systemic Losses in CDS Markets

This paper applies the Federal Reserve's supervisory stress test scenarios to examine the impacts on banks — and the banking system as a whole — from default of their largest counterparties in the credit derivatives markets. The authors find higher loss concentrations for the banking system than for individual firms and potential for large indirect losses when a major counterparty defaults. (Working Paper no. 16-01)

November 25, 2015 | By Maya Eden and Benjamin Kay

Safe Assets as Commodity Money

This paper examines the systemic implications of the supply of liquid safe assets, such as Treasury bills. The paper explores how liquid safe assets facilitate the trades of risky assets. The paper finds that financial markets may be remarkably resilient to changes in the stock of liquid assets. (Working Paper no. 15-23)

October 29, 2015 | By Benjamin Munyan

Regulatory Arbitrage in Repo Markets

This paper documents a pattern of foreign-owned broker-dealers reducing their borrowing in the U.S. triparty repo market, a key source of short-term funding in the financial system, at quarter end and immediately returning to the market when a new quarter begins. This activity reduces their capital requirements under the leverage ratio. (Working Paper no. 15-22)

October 20, 2015 | By Paul Glasserman and H. Peyton Young

Contagion in Financial Networks

This paper surveys the rapidly growing literature about interconnectedness and financial stability. The paper focuses on insights in the literature on the relationship between network structure and the vulnerability of the financial system to contagion. (Working Paper no. 15-21)

October 7, 2015 | By Jill Cetina and Katherine Gleason

The Difficult Business of Measuring Banks' Liquidity: Understanding the Liquidity Coverage Ratio

Bank regulators adopted a new requirement called the Liquidity Coverage Ratio after the financial crisis to help ensure banks maintain enough liquid assets to cover their financial obligations during times of stress. This paper uses a series of increasingly complex examples to demonstrate issues in analyzing this new liquidity metric. (Working Paper no. 15-20)

October 1, 2015 | By Jingnan Chen, Mark D. Flood, and Richard B. Sowers

Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios

Uncertainty is a crucial factor in financial stability, but it is notoriously difficult to measure. This working paper extends techniques from engineering to quantify fundamental economic uncertainty, and applies the method to an example of portfolio stress testing. By this measure, uncertainty peaked in late 2008. (Working Paper no. 15-19)

September 16, 2015 | By Richard Bookstaber and Mark Paddrik

An Agent-based Model for Crisis Liquidity Dynamics

This paper presents an agent-based model for examining price impacts and liquidity dynamics during financial crises, which are often characterized by sharp reductions in liquidity followed by cascades of falling prices. The model highlights the implications of changes in market makers' ability to provide intermediation services and the decision cycles of liquidity demanders versus liquidity suppliers during a crisis. (Working Paper no. 15-18)

September 9, 2015 | By Viktoria Baklanova, Adam Copeland, and Rebecca McCaughrin

Reference Guide to U.S. Repo and Securities Lending Markets

This paper is a reference guide on U.S. repo and securities lending markets. It discusses the main institutional features of these markets, their vulnerabilities, and data gaps that prevent market participants and regulators from addressing known vulnerabilities. (Working Paper no. 15-17)

August 19, 2015 | By Paul Glasserman and Linan Yang

Bounding Wrong-Way Risk in Measuring Counterparty Risk

This paper proposes a new method for bounding the impact of "wrong-way risk" on counterparty credit risk measurement for a portfolio of derivatives. Wrong-way risk refers to the possibility that a counterparty's default risk increases with the market value of the exposure. (Working Paper no. 15-16)

August 13, 2015 | By Chester Curme, Rosario N. Mantegna, Dror Y. Kenett, Michele Tumminello, and H. Eugene Stanley

How Lead-Lag Correlations Affect the Intraday Pattern of Collective Stock Dynamics

This paper explores how the increasing correlation among intraday stock returns affects the possibility to diversify investment risk and potentially may affect market stability. (Working Paper no. 15-15)

August 6, 2015 | By Sumudu W. Watugala

Economic Uncertainty and Commodity Futures Volatility

This paper investigates the dynamics of commodity futures volatility and analyzes the impact of increased emerging market demand on commodity markets. (Working Paper no. 15-14)

July 30, 2015 | By Mark D. Flood, Phillip Monin, and Lina Bandyopadhyay

Gauging Form PF: Data Tolerances in Regulatory Reporting on Hedge Fund Risk Exposures

This paper examines the precision of Form PF, a regulatory filing introduced after the financial crisis to measure risk exposures for private funds, including hedge funds. The paper finds that Form PF's measurement tolerances are large enough to allow private funds with dissimilar risk profiles to report similar risk measurements to regulators. (Working Paper no. 15-13)

June 18, 2015 | By Dror Y. Kenett, Sary Levy-Carciente, Adam Avakian, H. Eugene Stanley, and Shlomo Havlin

Dynamical Macroprudential Stress Testing Using Network Theory

This paper presents a dynamic bipartite network model for a stress test of a banking system's sensitivity to external shocks in individual asset classes. As a case study, the model is applied to investigate the Venezuelan banking system from 1998 to 2013. The model quantifies the sensitivity of bank portfolios to different shock scenarios and identifies systemic vulnerabilities that stem from connectivity and network effects, and their time evolution. The model provides a framework for dynamical macroprudential stress testing. (Working Paper no. 15-12)

May 28, 2015 | By Mark D. Flood, John C. Liechty, and Thomas Piontek

Systemwide Commonalities in Market Liquidity

This paper identifies hidden liquidity regimes (high, medium and low) across a broad range of financial markets that can be used for characterizing periods of market stress and identifying underlying predictors of liquidity shocks. This regime could have provided meaningful predictions of liquidity disruptions up to 15 trading days in advance of the 2008 financial crisis. These methods offer a potential framework for monitoring and predicting a systemwide collapse in market liquidity, which could signal a collapse of liquidity in the funding markets as experienced in the financial crisis. (Working Paper no. 15-11)

May 13, 2015 | By Javed Ahmed, Christopher Anderson, and Rebecca Zarutskie

Are the Borrowing Costs of Large Financial Firms Unusual?

This paper examines evidence of a too-big-to-fail subsidy for large financial firms by comparing borrowing costs of large and small firms across industries. The paper finds that larger firms borrow more cheaply in many industries, and this size effect is often largest in nonfinancial industries. These results challenge the notion that expected government bailouts are behind borrowing cost advantages enjoyed by the largest financial firms. (Working Paper no. 15-10)

May 13, 2015 | By Jill Cetina and Bert Loudis

The Influence of Systemic Importance Indicators on Banks' Credit Default Swap Spreads

This paper examines credit default swap (CDS) spreads in a sample of international banks for evidence of a benefit related to possible measures of systemic importance. The authors find a consistent, statistically significant negative relationship between five-year CDS spreads of banks and nine different systemic importance indicators. The paper shows that the benefit is most pronounced for banks within a certain asset range. Such evidence is weaker for banks identified by regulators as global systemically important banks. (Working Paper no. 15-09)

May 7, 2015 | By Agostino Capponi, W. Allen Cheng, and Sriram Rajan

Systemic Risk: The Dynamics under Central Clearing

This paper develops a model for concentration risks that clearing members pose to central counterparties. Over time, larger clearing members crowd out smaller clearing members. Systemic risk is created because high clearing member concentration results in relatively lower lending, higher cost of capital, and increasingly costly hedging. To address this risk, the paper proposes a self-funding systemic risk charge. (Working Paper no. 15-08)

May 7, 2015 | By Paul Glasserman, Ciamac C. Moallemi, and Kai Yuan

Hidden Illiquidity with Multiple Central Counterparties

This paper focuses on the systemic risks in markets cleared by multiple central counterparties (CCPs). Each CCP charges margins based on the potential impact from the default of a clearing member and subsequent liquidation of a large position. Swaps dealers can split their positions among multiple CCPs, effectively "hiding" potential liquidation costs. A lack of coordination among CCPs can lead to a "race to the bottom" because CCPs with lower perceived liquidation costs can drive competitors out of the market. (Working Paper no. 15-07)

May 7, 2015 | By Therese C. Scharlemann and Stephen H. Shore

The Effect of Negative Equity on Mortgage Default: Evidence from HAMP PRA

This paper uses data from the Home Affordable Modification Program to examine the impact of principal forgiveness on mortgage default. On average 3.1 percent of loans become delinquent and exit the program each quarter. The authors estimate that the rate would have been 3.8 percent absent principal forgiveness, which averaged 28 percent of the initial mortgage balance. (Working Paper no. 15-06)

April 2, 2015 | By Charles W. Calomiris, Matthew Jaremski, Haelim Park, and Gary Richardson

Liquidity Risk, Bank Networks, and the Value of Joining the Federal Reserve System

The Federal Reserve System was created to reduce risks related to seasonal swings in loan demand and to stabilize fluctuations in interest rates. Many state-chartered banks chose not to join the system because of the cost of the Federal Reserve's reserve requirements. The inability to attract many state-chartered banks created indirect access to government protection (lender of last resort) without federal regulation. (Working Paper no. 15-05)

March 26, 2015 | By Mark D. Flood and Oliver R. Goodenough

Contract as Automaton: The Computational Representation of Financial Agreements

This paper shows that the fundamental legal structure of a well-written financial contract follows a logic that can be formalized mathematically as a "deterministic finite automaton." This allows, for example, automated reasoning to determine whether a contract is internally coherent and complete. The paper illustrates the process by representing a simple loan agreement as an automaton. (Working Paper no. 15-04)

March 10, 2015 | By Richard Bookstaber, Michael D. Foley, and Brian F. Tivnan

Market Liquidity and Heterogeneity in the Investor Decision Cycle

This paper presents a model of market liquidity in which those who need to sell come into the market with a greater need for immediacy than those who are willing to buy. This is a critical market dynamic behind the illiquidity that arises during market dislocations and crises, when some are in forced-selling mode while others are hesitant to come in and take the other side of the trade. (Working Paper no. 15-03)

March 3, 2015 | By Paul Glasserman and Gowtham Tangirala

Are the Federal Reserve's Stress Test Results Predictable?

This paper examines the results of four rounds of stress testing of the largest U.S. bank holding companies, starting in 2009. The data reveal a growing correlation in results from one year to the next, highlighting whether the stress tests in their current form may be losing some of their information value over time. The authors discuss the implications of these patterns and recommend greater diversity in the stress scenarios analyzed. (Working Paper no. 15-02)

February 11, 2015 | By Richard Bookstaber, Paul Glasserman, Garud Iyengar, Yu Luo, Venkat Venkatasubramanian, and Zhizun Zhang

Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks

This paper demonstrates the value of signed directional graphs, a modeling methodology used for risk detection in process engineering, in tracing the path of potential instabilities and feedback loops within the financial system. This approach expands the usefulness of network models of the financial system by including critical information on the direction of influence and the points of control between the various nodes of the network. (Working Paper no. 15-01)

December 22, 2014 | By Emil Siriwardane

Concentrated Capital Losses and the Pricing of Corporate Credit Risk

This paper uses proprietary credit default swap (CDS) data for 2010 to 2014 to show that capital fluctuations for sellers of CDS protection are an important determinant of CDS spread movements. (Working Paper no. 14-10)

November 25, 2014 | By Mark Paddrik, Roy Hayes, William Scherer, and Peter Beling

Effects of Limit Order Book Information Level on Market Stability Metrics

This paper uses an agent-based model of the limit order book to explore how the levels of information available to participants, exchanges, and regulators can be used for insights on the stability and resiliency of a market. (Working Paper no. 14-09)

November 13, 2014 | By Phillip Monin

Hedging Market Risk in Optimal Liquidation

This paper discusses optimal strategies for financial institutions in selling large blocks of securities and in hedging the resulting market risk. (Working Paper no. 14-08)

October 23, 2014 | By Robert Engle and Emil Siriwardane

Structural GARCH: The Volatility-Leverage Connection

This paper proposes a new model of volatility featuring a "leverage multiplier" by which financial leverage amplifies equity volatility. The model estimates daily asset returns and asset volatility. (Working Paper no. 14-07)

August 19, 2014 | By Paul Glasserman and Wanmo Kang

Design of Risk Weights

This paper investigates the design of risk weights used in setting minimum levels of regulatory capital for banks and presents a formula for regulators to set those weights by analyzing bank portfolios. (Working Paper no. 14-06)

July 29, 2014 | By Rick Bookstaber, Mark Paddrik, and Brian Tivnan

An Agent-based Model for Financial Vulnerability

This paper develops an agent-based model that uses a map of funding and collateral flows to analyze the financial system's vulnerability to fire sales and runs. (Working Paper no. 14-05)

July 2, 2014 | By Zoltan Pozsar

Shadow Banking: The Money View

This paper presents an accounting framework for measuring the sources and uses of short-term funding in the global financial system and introduces a dynamic map of global funding flows. (Working Paper no. 14-04)

May 29, 2014 | By Andrea Aguiar, Rick Bookstaber, and Thomas Wipf

A Map of Funding Durability and Risk

This paper features a funding map to illustrate the flow of funding from its initial providers through the bank/dealers to the end-users. In addition to showing the plumbing of the system, the paper also shows the processes for transforming funding liquidity, credit quality, and tenor. The paper then applies the funding map to track risk through various types of financial institutions, and to identify gaps in data needed for financial stability monitoring. (Working Paper no. 14-03)

May 9, 2014 | By Mark D. Flood, Victoria L. Lemieux, Margaret Varga, and B.L. William Wong

The Application of Visual Analytics to Financial Stability Monitoring

This paper provides an overview of visual analytics - the science of analytical reasoning enhanced by interactive visualizations produced by data analytics software - and discusses potential benefits in monitoring financial stability. (Working Paper no. 14-02)

April 16, 2014 | By Javed I. Ahmed

Competition in Lending and Credit Ratings

This paper explores the relationship between the quality of corporate credit ratings and competition in lending between the public bond market and banks. It finds that the quality of credit ratings plays a role in financial stability because the behavior of rating agencies can reduce the impact of macroeconomic shocks. (Working Paper no. 14-01)

December 5, 2013 | By Matthew McCormick and Lynn Calahan

Common Ground: The Need for a Universal Mortgage Loan Identifier

The U.S. mortgage finance system is a critical part of our nation's financial system, representing 70 percent of U.S. household liabilities. The establishment of a single, cradle‐to‐grave, universal mortgage identifier that cannot be linked to individuals using publicly‐available data would significantly benefit regulators and researchers. (Working Paper no. 13-12)

September 4, 2013 | By Mark Flood, Jonathan Katz, Stephen Ong, and Adam Smith

Cryptography and the Economics of Supervisory Information: Balancing Transparency and Confidentiality

This paper explores tradeoffs between transparency and confidentiality in financial regulation and discusses new techniques from the fields of secure computation and statistical data privacy that can facilitate the secure sharing of financial information. (Working Paper no. 13-11)

July 18, 2013 | By Rick Bookstaber, Jill Cetina, Greg Feldberg, Mark Flood, and Paul Glasserman

Stress Tests to Promote Financial Stability: Assessing Progress and Looking to the Future

Stress testing of large bank holding companies in the United States - a valuable exercise used to determine regulatory capital and liquidity planning at these institutions - should be adapted to be made more useful for financial stability monitoring. (Working Paper no. 13-10)

June 21, 2013 | By Paul Glasserman and H. Peyton Young

How Likely is Contagion in Financial Networks?

This paper estimates how much interconnections among financial institutions - potential channels for contagion and amplification of shocks to the financial system - can increase expected losses from a wide range of shocks. (Working Paper no. 13-09)

May 15, 2013 | By Douglas J. Elliot, Greg Feldberg, and Andreas Lehnert

The History of Cyclical Macroprudential Policy in the United States

This paper presents a survey and historical narrative of policies to smooth the credit cycle in light of their potential future application as "macroprudential" policies to reduce the build-up of risks in U.S. financial markets. (Working Paper no. 13-08)

April 9, 2013 | By Paul Glasserman, Chulmin Kang, and Wanmo Kang

Stress Scenario Selection by Empirical Likelihood

This paper develops a method for selecting and analyzing stress-testing scenarios for financial risk assessment. (Working Paper no. 13-07)

March 13, 2013 | By Ozgur (Ozzy) Akay, Zeynep Senyuz, and Emre Yoldas

Hedge Fund Contagion and Risk-adjusted Returns: A Markov-switching Dynamic Factor Approach

This paper uses a flexible framework to analyze two important phenomena influencing the hedge fund industry - contagion and time variation in risk-adjusted return. (Working Paper no. 13-06)

February 7, 2013 | By Mark D. Flood and George G. Korenko

Systematic Scenario Selection: Stress Testing and the Nature of Uncertainty

This paper offers a technique for selecting multidimensional shock scenarios for use in financial stress testing. The technique uses a grid search of sparse, well distributed stress-test scenarios that are considered a middle ground between traditional stress testing and reverse stress testing. (Working Paper no. 13-05)

January 23, 2013 | By Nan Chen, Paul Glasserman, Behzad Nouri, and Markus Pelger

CoCos, Bail-in, and Tail Risk

This paper develops a capital structure model of a bank to analyze the incentives created by contingent convertibles (CoCos) and bail-in debt, which convert to equity when a bank approaches insolvency. These two forms of contingent capital have been proposed as potential mechanisms to enhance financial stability. (Working Paper no. 13-04)

December 21, 2012 | By Richard Bookstaber

Using Agent-Based Models for Analyzing Threats to Financial Stability

This paper discusses the concepts and research related to agent-based models and explores how the dynamics of a flock of birds in flight, a group of drivers in a traffic jam, or a panicked crowd of stampeding people might inform our analysis of threats to financial stability. (Working Paper no. 12-03)

March 26, 2012 | By Mark J. Flannery, Paul Glasserman, David K.A. Mordecai, and Cliff Rossi

Forging Best Practices in Risk Management

This paper assesses risk management practices and how risk management can be improved. The paper approaches risk management from three perspectives: (1) risk measurement by individual firms, (2) governance and incentives, and (3) systemic concerns. The paper evaluates each approach separately and also discusses the importance of considering them as interrelated. (Working Paper no. 12-02)

January 5, 2012 | By Dimitrios Bisias, Mark Flood, Andrew W. Lo, and Stavros Valavanis

A Survey of Systemic Risk Analytics

The paper focuses on quantitative tools to assess threats to financial stability. It gives a broad overview of the state of the art in measuring systemic risk by focusing on a key set of 31 specific measurements outlined elsewhere in peer-reviewed articles or working papers. (Working Paper no. 12-01)

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AI has moved into its era of deployment; throughout 2022 and the beginning of 2023, new large-scale AI models have been released every month. These models, such as ChatGPT, Stable Diffusion, Whisper, and DALL-E 2, are capable of an increasingly broad range of tasks, from text manipulation and analysis, to image generation, to unprecedentedly good speech recognition. These systems demonstrate capabilities in question answering, and the generation of text, image, and code unimagined a decade ago, and they outperform the state of the art on many benchmarks, old and new. However, they are prone to hallucination, routinely biased, and can be tricked into serving nefarious aims, highlighting the complicated ethical challenges associated with their deployment.

Although 2022 was the first year in a decade where private AI investment decreased, AI is still a topic of great interest to policymakers, industry leaders, researchers, and the public. Policymakers are talking about AI more than ever before. Industry leaders that have integrated AI into their businesses are seeing tangible cost and revenue benefits. The number of AI publications and collaborations continues to increase. And the public is forming sharper opinions about AI and which elements they like or dislike.

AI will continue to improve and, as such, become a greater part of all our lives. Given the increased presence of this technology and its potential for massive disruption, we should all begin thinking more critically about how exactly we want AI to be developed and deployed. We should also ask questions about who is deploying it—as our analysis shows, AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors. This year’s AI Index paints a picture of where we are so far with AI, in order to highlight what might await us in the future.

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• 28 NOVEMBER 2023 · RESEARCH BULLETIN NO. 113

Reports of AI ending human labour may be greatly exaggerated

by Stefania Albanesi , António Dias da Silva , Juan Francisco Jimeno , Ana Lamo and Alena Wabitsch [ 1 ]

Recent advances in artificial intelligence (AI) have revived the debate about the impact of new technologies on jobs (e.g. Frey and Osborne, 2017; Susskind, 2020; and Acemoglu, 2021). Waves of innovation have usually been accompanied by anxiety about the future of jobs. This apprehension persists, even though history suggests that previous fears about labour becoming redundant were exaggerated (e.g. Autor, 2015; Bessen, 2019). In fact, in this article we show that during the deep learning boom of the 2010s, occupations potentially more exposed to AI-enabled technologies actually increased their employment share in Europe. However, the jury is still out on whether the same can be expected from new developments in AI-enabled technologies. When the verdict comes in, it could be win or lose – not only for jobs, but also for equality and prosperity in Europe.

The evidence so far on AI and employment

AI breakthroughs have come in many fields. These include advances in robotics, supervised and unsupervised learning, natural language processing, machine translation and image recognition, to name but a few. AI has applications among masses of other activities that enable automation of human labour in non-routine tasks, both in manufacturing and also in services – from providing medical advice to writing code. AI is thus a general-purpose technology that can automate work in virtually every occupation. It stands in contrast to other technologies such as computerisation and industrial robotics, which only allow a limited set of tasks to be automated by implementing manually specified rules.

The empirical evidence on the effect of AI-enabled technologies on jobs and wages is still evolving. For example, both Felten et al. (2019) and Acemoglu et al. (2022) conclude that occupations more exposed to AI experience no significant impact on employment. However, Acemoglu et al. (2022) also find that AI-exposed establishments reduced non-AI and overall hiring. That would imply that while new tasks are being created, AI is also replacing human labour in a subset of tasks. Moreover, Felten et al. (2019) find that occupations impacted by AI actually experience a small rise in wages. On a different note, Webb (2020) argues that, compared with either software or robots, AI-enabled technologies are likely to have a greater impact on high-skilled workers in particular. Meanwhile, the literature to date focuses mostly on the United States.

New evidence for Europe

In a recent paper (Albanesi et al. 2023), we examine the link between AI-enabled technologies and employment shares in 16 European countries over the period 2011-19 [ 2 ] . These years saw the rise of deep learning applications such as language processing, image recognition, algorithm-based recommendations or fraud detection. Though more limited in scope than the current generative AI models such as ChatGPT, deep learning applications are nonetheless revolutionary – and still trigger concerns about the impact on jobs. We use data at three-digit occupation level (according to the International Standard Classification of Occupations) from Eurostat’s Labour Force Survey, as well as two proxies for potential AI-enabled automation borrowed from the literature. The first proxy is the AI Occupational Impact created by Felten et al. (2018) and Felten et al. (2019), which links advances in specific applications of AI to abilities required for each occupation as described in O*NET [ 3 ] . The second one is a measure of the exposure of tasks and occupations to AI, constructed by Webb (2020) by quantifying the text overlap between AI patent descriptions and job descriptions from O*NET. In addition, we compare the exposure to AI-enabled technologies with exposure to software by using a software exposure measured as constructed by Webb (2020).

These data reveal that around 25% of all jobs in these European countries were in occupations highly exposed to AI-enabled automation – specifically, in the upper third of the exposure measure. The degree of exposure is as much an opportunity as it is a risk. The outcome for jobs depends on whether the AI-enabled technologies will substitute or complement labour. Compared with occupations more exposed to advances in software, those more exposed to AI employ a larger proportion of high-skilled workers (Chart 1). This supports the case that AI-enabled technologies could be in competition with high-skilled jobs. While the exposure to technology varies for different levels of skills, it is relatively uniform across age groups (not shown in the chart).

Exposure to technology by education level

average percentile

Source: Albanesi et al. (2023).

Notes: The chart reflects how exposed different “education groups” of workers are on average to the three technology measures. Education groups are defined as the subsample of occupation-sector cells whose average educational attainment is in the lower, middle, and upper third (tercile) respectively of the national education distribution.

What do the results say about the impact of AI on employment?

We find a positive association between AI-enabled automation and changes in employment shares in our sample of 16 European countries, regardless of which proxy we used. According to the AI exposure indicator proposed by Webb (2020), moving 25 centiles up along the distribution of exposure to AI is associated with a 2.6% increase in sector-occupation employment share, while using the measure provided by Felten et al. (2018, 2019) the estimated increase in the sector-occupation employment share is 4.3%. The estimated coefficients are displayed by the horizontal line in the left-hand and middle columns of Charts 2 and 3.

Technology-enabled automation might also affect the relative shares of employment at different skill levels and thus impact earnings inequality. The literature on job polarisation shows that medium-skilled workers in routine-intensive jobs tended to be replaced by computerisation (e.g. Autor et al, 2003; Goos et al, 2009). In contrast, it is often argued that AI-enabled automation is more likely to complement or replace jobs in occupations that employ high-skilled labour.

Panels (a) and (b) in Chart 2 show the estimated coefficients of the association between changes in employment and AI-enabled automation by level of education (broken down into terciles, i.e. the lower, middle and upper thirds of the population). Statistically significant coefficients are plotted in dark blue. For occupations where average educational attainment is in the low and medium-skill groups, AI exposure does not seem to shake things up significantly. However, for the high-skill group we find a positive and significant association: moving 25 centiles up along the distribution of exposure to AI appears to boost the sector-occupation employment share by 3.1% using Webb’s AI exposure indicator, and by 6.7% using the measure of Felten et al.

Exposure to technology and changes in employment shares by skill level

a) AI, Webb b) AI, Felten et al. c) Software, Webb

percentage changes

Notes: Regression coefficients measuring the effect of exposure to technology on changes in employment share. Each observation is a ISCO 3-digit occupation times sector cell. Observations are weighted by cells’ average labour supply. Sector and country dummies are included. The sample consists in data for 16 European countries, from 2011 to 2019. The coefficient for the whole sample is shown by the horizontal line. The bars display the coefficient estimated for the subsample of cells for average educational attainment in the lower, middle and upper tercile respectively of the within-country education distribution. Coefficients that are statistically significant at least at the 10% level are plotted in dark blue.

Panels (a) and (b) in Chart 3 report the estimates by age group (again broken down by terciles, i.e. youngest, middle and oldest third of the population). AI-enabled automation appears to be more favourable for those occupations that employ relatively younger workers. Regardless of the AI indicator used, the estimated benefit for the younger group seems to be double that for the other age groups.

AI-enabled automation is thus associated with employment increases in Europe – mostly for high-skill occupations and younger workers. This is at odds with the evidence from previous technology waves, when computerisation decreased the relative share of employment of medium-skilled workers, resulting in polarisation. However, we do not find evidence of this polarisation pattern for our sample, e ven when examining the impact of software-enabled automation, proxied by the software exposure by Webb (2020). Panel (c) in Charts 2 and 3 displays the results. The relationship between software exposure and employment changes is null for the pooled sample, and there is no evidence of software replacing routine medium-skill jobs.

Exposure to technology and changes in employment shares by age

a) AI, Webb b) AI, Felten et al. C) Software, Webb

Notes: Regression coefficients measuring the effect of exposure to technology on changes in employment share. Each observation is an ISCO 3-digit occupation times sector cell. Observations are weighted by cells’ average labour supply. Sector and country dummies are included. The sample consists in data for 16 European countries, from 2011 to 2019. The coefficient for the whole sample is shown by the horizontal line. The bars display the coefficient estimated for the subsample of cells of workers with an average age in the lower, middle and upper tercile respectively of workers’ age distribution. Coefficients that are statistically significant at least at the 10% level are plotted in dark blue.

Despite the results for employment shares, neither AI or software exposure showed statistically significant effects on wages, except when using the Felten et al. measure, which indicates that occupations more exposed to AI have slightly worse wage growth.

Our results show a mixed picture across the 16 European countries. The positive impact of AI-enabled automation on employment holds true for most countries, with only a few exceptions. However, the scale of the impact varies substantially across countries. This might reflect differences in underlying economic factors, such as the pace of technology diffusion and education, or the level of regulation – and therefore competition – in product and labour markets.

Too soon to reach a verdict

During the deep learning boom of the 2010s, occupations potentially more exposed to AI-enabled technologies actually increased their employment share in Europe. Occupations with a relatively higher proportion of younger and skilled workers gained the most. For wages, the evidence is less clear and suggests neutral to slightly negative impacts. These results do not amount to an acquittal: AI-enabled technologies continue to be developed and adopted. Most of their impact on employment and wages – and therefore on growth and equality – has yet to be seen.

Acemoglu, D (2022), “Harms of AI”, Oxford Handbook of AI Governance .

Acemoglu, D., Autor, D., Hazell, J. and Restrepo, P. (2022), “Artificial intelligence and jobs: Evidence from online vacancies”, Journal of Labor Economics, Vol. 40(S1), pp. S293-S340.

Acemoglu, D. and Restrepo, P. (2018), “The race between man and machine: implications of technology for growth, factor shares, and employment”, American Economic Review , Vol. 108, pp. 1488-1542.

Albanesi, S., Dias da Silva, A., Jimeno, J. F., Lamo, A. and Wabitsch, A. (2023), “ New Technologies and Jobs in Europe ”, Working Paper Series, No 2831, ECB.

Autor, D. (2015), “Why are there still so many jobs? The history and future of workplace automation”, Journal of Economic Perspectives , Vol.29(3), pp. 3-30.

Autor, D., Levy, F. and Murnane, R. (2003), “The skill content of recent technological change: An empirical exploration”, Quarterly Journal of Economics, Vol. 118(4), pp. 1279-1333.

Bessen, J. (2019), “Automation and jobs: when technology boosts employment” , Economic Policy , October, pp. 589-626.

Felten, E. W., Raj, M. and Seamans, R. (2018), “A method to link advances in artificial intelligence to occupational abilities”, AEA Papers and Proceedings, Vol. 108, pp. 54–57.

Felten, E. W., Raj, M. and Seamans, R. (2019), “The effect of artificial intelligence on human labor: An ability-based approach”, Academy of Management Proceedings .

Frey, C. B. and Osborne M. A. (2017), “The future of employment: How susceptible are jobs to computerisation?”, Technological Forecasting and Social Change , Vol. 114, pp. 254-280.

Goos, M., Manning, A. and Salomons, A. (2009), “Job polarization in Europe”, American Economic Review , Vol. 99(2), pp. 58-63.

Susskind, D. (2020), A world without work: Technology, automation and how we should respond , London: Penguin.

Webb, M. (2020), The impact of artificial intelligence on the labor market, mimeo.

This article was written by Stefania Albanesi (University of Pittsburg, NBER and CEPS), António Dias da Silva (Directorate General Economics, European Central Bank), Juan Francisco Jimeno (Banco de España, Universidad de Alcalá, CEMFI, CEPR and IZA), Ana Lamo (Directorate General Research, European Central Bank) and Alena Wabitsch (University of Oxford). It is based on the paper entitled “New technologies and jobs in Europe” by the same authors. The authors would like to thank Gareth Budden, Michael Ehrmann, Alex Popov and Zoë Sprokel for their comments. The views expressed here are those of the authors and do not necessarily represent the views of the European Central Bank and the Eurosystem.

Belgium, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Austria, Portugal, Finland and the United Kingdom.

The Occupational Information Network (O*NET) is an online database that contains hundreds of job definitions in the United States. Every occupation requires a different mix of knowledge, skills and abilities, and is performed using a variety of activities and tasks.

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