Academic Publications:

Country Reputation and Corporate Activity, 2022, Management Science, Forthcoming, with Alper Darendeli.
Replication Files: https://github.com/mehmetcanayaz/countryreputation

Fake Products, Real Effects: Evidence from Special 301 Actions, 2021, Journal of Financial and Quantitative Analysis, Forthcoming, with Umit Gurun.

Papers Undergoing Revision:

[1] Choose Your Battles Wisely: The Consequences of Protesting Government Procurement Contracts (2022)
with Jess Cornaggia and Kimberly Cornaggia

We examine the relation between a firm’s successful protest of a government agency’s conduct or terms of a procurement contract and the amount of business the firm conducts with the government going forward. We find firms receive fewer and less valuable government contracts, face more contract cancellations, and experience significant reductions in sales growth and employee growth. Despite widespread belief, successful bid protesters do not delay government procurement due to lengthy dispute resolutions. Overall, we provide the first analysis of corporate interactions with the United States government bid-protest system. 

Presentations: 2020 American Finance Association Meetings (San Diego),  MFA 2020 Annual Meeting in Chicago, 2020 American Law and Economics Association (ALEA) Annual Meeting in Chicago, Clemson University*,  Emory University*, Pennsylvania State University (Smeal College of Business and Harrisburg),  Emory University*, and Temple University (Fox School of Business)*.

* denotes presentation by co-author

Working Papers:

[1] When Protectionism Kills Talent (2024)
with Umit Gurun and Isil Erel

We examine the repercussions of protectionist policies implemented in the United States since 2018 on the composition of workforce and career choices within the semiconductor industry. Using a unique dataset of 1.6 million active engineers and scientists working in the chip manufacturing industry worldwide, we find that the shift towards protectionism, aimed at reviving domestic manufacturing and employment, paradoxically resulted in a significant drop in hiring domestic talent. The effect is stronger for entry-level and junior positions, indicating a disproportionate impact on newcomers to the workforce. Additionally, we trace the trajectories of undergraduate and graduate cohorts possessing chip-related skills over time, and document significant shifts away from the chip industry. Our findings highlight the challenges in achieving the goals of initiatives like the 2022 CHIPS and Science Act, emphasizing the need to address talent shortages to sustain the semiconductor industry's intended growth. 

Presentations:  2024 CSEF-RCFS Conference on Finance, Labor and Inequality.

[2] Financial Consequences of the Belt and Road Initiative (2024)

China's Belt and Road Initiative (BRI) aims to reshape the global economy by creating economic corridors that encompass two-thirds of the world's population and 40% of global GDP. This paper provides the first analysis of BRI's unintended financial consequences for countries along its corridors. Utilizing the inauguration of a railway tunnel between Europe and Asia as a quasi-natural experiment, it demonstrates that countries gaining access to BRI corridors issue significant amounts of high-yield public debt. This debt, mainly absorbed domestically, diverts capital from firms and finances collective consumption instead of essential infrastructure projects required to harness BRI's promised efficiency gains. 

Presentations: Fifth Conference on Law and Macroeconomics, 2022 New Zealand Finance Meeting,  CMU-PSU-Pitt Finance Conference, MFA 2023 Annual Meeting, 2023 FMA Annual Meeting, Federal Reserve Board, Center for Global Business Studies.

[3] Crafting an AI Compass: The Influence of Global AI Standards on Firms (2023)
with Zhe Wang

The adoption and commercialization of new technologies rely heavily on universally accepted principles, known as standards. Surprisingly, the role of standards in shaping business outcomes is largely unexplored. This paper provides a first examination of how  standardization of artificial intelligence (AI) influences business outcomes. By leveraging hand-collected data on global AI standards, we provide insights into their creation, content, and shed light on the countries leading or lagging in global AI standardization efforts. Our findings reveal that establishing universal rules and guidelines for AI has a first order impact on corporate investment. Standardization of machine learning methods, programming languages, protocols for big data,  guidelines for data interchange, and interoperability of industrial data fuel capital and R&D investments. Conversely, frameworks for ethical, societal, and privacy considerations in AI have distortionary effects. Overall, AI standards have a positive 'ripple effect' on firm value, gradually amplifying as the standards mature and their impact on firms deepens. 

Presentations: 2024 Next Generation of Antitrust, Data Privacy & Data Protection Scholars Conference, Asian Bureau of Finance and Economic Research 11th Annual Conference.

[4] An Anatomy of Cryptocurrency Sentiment (2023)
with Charles Cao, Giang Nguyen, and Qiang Wang

In this paper, we investigate the impact of market sentiment on cryptocurrency returns. To accomplish this, we use a novel dataset that captures a multitude of attitudes, moods, and emotions extracted from a vast amount of news and social media content. Our findings indicate that social media sentiment significantly predicts crypto returns, while sentiment from news media does not. Additionally, we observe that fundamental events play a role in shaping sentiment, but market exuberance---sentiment unrelated to fundamental events---is a strong and robust predictor of returns. Furthermore, we find that market exuberance is positively related to momentum return but does not positively predict volatility. This suggests that sentiment influences returns through price perception and demand shocks rather than the risk premium channel. Overall, our research highlights the importance of sentiment in understanding and predicting cryptocurrency market dynamics.

Presentations:  Penn State University*, CMU-PSU-Pitt Finance Conference*, 2023 Early Career Women in Finance Conference*, 2023 FMA Annual Meeting*, 2024 WFA Meeting.

* denotes presentation by co-author

Media: Les Affaires.

[5] Macro sentiment and hedge fund returns (2023)
with Mustafa Caglayan, Tim Simin, and Le Zhao

In heterogeneous agent models, systematic excess demand for risky assets, generated by sentiment, can lead to a sentiment risk premium for sophisticated arbitrageurs. Utilizing media-based sentiment on economic growth, inflation, unemployment, and sociopolitical conditions, we create a macro sentiment index (MSI) and show that hedge funds with negative exposure to MSI generate higher returns than funds with positive exposure to MSI. The predictive power of MSI betas remains after controlling for various hedge fund characteristics and other risk and uncertainty factors proven to impact hedge fund returns. The negative relation is most pronounced among directional and semi-directional hedge fund strategies and remains for up to four months. We show that a tradable version of the MSI meets the necessary criteria to be considered a state variable in the ICAPM for hedge funds and actively managed mutual funds but not for unmanaged passive industry portfolios or individual stocks. Overall, our results suggest that the expected returns of hedge fund portfolios and actively managed mutual fund portfolios reflect a sentiment risk premium. 

Presentations: 2022 FMA Annual Meeting in Atlanta*,  EFA 2024 Annual Meeting*.

* denotes presentation by co-author

[6]  Judicial Ideology and Business Dynamics (2023)
with Matthew T. Gustafson 

Using staggered changes in U.S. circuit court ideology and counties along circuit borders, we examine the effect of judicial ideology on the business start-up decision. We find evidence that shifts toward more liberal courts, which are commonly viewed as less pro-business, are followed by immediate reductions in the number of firm and business establishments in an area. This reduction is largest in the year after the ideology change and driven primarily by fewer entries from de novo firms. An industry decomposition reveals that retail firms, which are traditionally viewed as litigation sensitive, are the primarily drivers of our results. Overall, our study shows that start-ups weigh an area's judicial risk when deciding to open a business.  

Presentations: Iowa State University*, Third Annual Conference on Law and Macroeconomics, University of Miami*,  MFA 2021 Annual Meeting, University of Bath*, Vrije Universiteit Amsterdam, 2021 American Law and Economics Association (ALEA) Annual Meeting in Chicago, 2023 FMA Annual Meeting, 15th Florida State University Truist Beach Conference.

* denotes presentation by co-author

[7] Privacy Laws and Value of Personal Data (2022)
with Ilja Kantorovitch and Roxana Mihet

We analyze how the adoption of the California Consumer Privacy Act (CCPA), which limits consumer personal data acquisition, processing, and trade, affects voice-AI firms. To derive theoretical predictions, we use a general equilibrium model where firms produce intermediate goods using labor and data in the form of intangible capital, which can be traded subject to a cost representing regulatory and technical challenges. Firms differ in their ability to collect data internally, driven by the size of their customer base and reliance on data. When the introduction of the CCPA increases the cost of trading data, sophisticated firms with small customer bases are hit the hardest. Such firms have a low ability to collect in-house data and high reliance on data and cannot adequately substitute the previously externally purchased data. We utilize novel and hand-collected data on voice-AI firms to provide empirical support for our theoretical predictions. We empirically show that sophisticated firms with voice-AI products experience lower returns on assets than their industry peers after the introduction of the CCPA, and firms with weak customer bases experience the strongest distortionary effects. 

Presentations: University of Lausanne*, ESSEC*, 2022 Next Generation of Antitrust, Data Privacy and Data Protection Scholars Conference (NYU), 15th Digital Economics Conference at Toulouse School of Economics*, NBER Economics of Privacy Conference, AEA 2023.

Slides: NBER Slides can be found here.

* denotes presentation by co-author