Publications:
"Transaction Fee Economics in the Ethereum Blockchain" (with Alex Karaivanov, 2021, Economic Inquiry, 13025, p.1-28.)
(Available from: https://doi.org/10.1111/ecin.13025)
We study the economic determinants and dynamics of transaction fees in the Ethereum blockchain. The transaction fee is an endogenous price for service, paid when a direct transfer or smart-contract transaction is recorded on the blockchain. We estimate an empirical model based on queueing theory and analyze the factors determining the Ethereum ``gas price", i.e., transaction cost per unit of service, ``gas''. Using detailed block-level and transaction-level data obtained directly from the Ethereum blockchain, we show that changes in network service demand significantly affect the marginal and median gas price -- when there is high block utilization, per-unit transaction fees increase on average, with a strong non-linear threshold effect above 90% utilization. We additionally find that the transaction type is an important factor -- a larger fraction of regular transactions (direct transfers between users, as opposed to smart contract calls), is associated with higher gas price.
"Individual Evolutionary Learning and Zero-Intelligence in the Continuous Double Auction" (with Jasmina Arifovic and John Ledyard, 2022, Handbook of Experimental Finance, 20035, p. 225-249)
(Available from: https://ideas.repec.org/h/elg/eechap/20035_19.html)
We study behavior in a Continuous Double Auction. In this paper we report on two models, ZI and IEL, which we tested against each other using two very different data sets: a large, uncontrolled set from classroom experiments using the Moblab interface and a small, controlled set from experiments at SFU. We found that drawing subjects from a pool composed of 70% IEL agent and 30% NI agents, who randomly order from [0,250], generated results that were a very good fit to the 2090 observations from Moblab. That mixture outperformed a pool composed only of ZI agents. We found that a pool composed of only IEL agents was a good fit to the 25 observations from SFU. With respect to the distribution of efficiency, that IEL model dominated the ZI model. But, with respect to the distribution of average prices, the ZI model does a little better than IEL. Weighing the efficiency and price fits equally, IEL seems to be a better overall fit to the SFU data than ZI.
Working Papers:
"Excluded at the Top: Racial Differences in Senior Executives' Access to Information" (with Deniz Anginer, Nejat Seyhun, and Ray Zhang, 2022)
We document that African-American executives, on average, earn zero abnormal profits from insider trades, in contrast to Asian-American and Caucasian executives who earn significantly positive abnormal profits. We also find that these differences cannot be attributed to differences in industry, firm or insider characteristics. These race differences are less profound in firms that emphasize diversity and employee equity. Our results imply that African-American executives are disadvantaged relative to non-African-American executives in access to insider information. Our findings suggest that executives who make corporate decisions based on a subset of all available information are likely to make suboptimal decisions.
"Global Economic Impact of Covid-19: Evidence from Insider Traders" (with Deniz Anginer, Nejat Seyhun, and Ray Zhang, 2020)
We examine insider trades around the onset of the COVID-19 pandemic. Insiders purchased shares in record numbers after the stock market decline that began in late February 2020. We find that insider purchases were more pronounced for larger firms, value firms, firms with high levels of leverage as well as firms in the finance, energy and consumer nondurable sectors. These results suggest that insiders believe the impact of COVID-19 on global economic activity and the stock prices of their companies to be temporary. We also find some evidence of opportunistic insider selling in January and February 2020 prior to the stock market decline, suggesting that some insiders anticipated the decline. Finally, we find similar patterns in insider trading in Canada, Italy, Spain and South Korea, but a more muted response in China. Our results indicate that insiders’ private information became especially valuable during this period of significant market disruption.
"Exchange Rates and Export Behaviour: Firm-Level Evidence from Turkey" (with Nihan Akhan, Refik Erzan, and Tolga Kuzubas, 2018)
This paper investigates the heterogeneity in the responses of export volumes to real exchange rate changes using firm-level data from Turkey for the period 2007-2014. We find that, consistent with the literature, high productivity firms were also large exporters and importers. Our results confirmed the positive effect of a depreciation on export volumes for Turkey, on average. However, firms with relatively high import intensities, measured as the ratio of imports to total trade at the firm-level, reacted significantly differently compared to low import intensity firms. Our empirical analysis suggested that for firms relying predominantly on imported inputs, the positive effect of a depreciation could be offset by the corresponding negative effect through the cost channel and might even lead to a reduction in exports. Our results are consistent with the conventional belief that exchange rate depreciation benefits exporters, but this average effect might be misleading as it hides a significant amount of heterogeneity.
Conferences/Seminars/Workshops:
-The Second Conference on Zero/Minimal Intelligence Agents, 2021 (virtual/attendee)
-SFU Beedie School of Business Brown Bag Seminar, 2021 (virtual/presenter)
-Canadian Economic Association Annual Conference, 2021 (virtual/presenter)
-The First Conference on Zero/Minimal Intelligence Agents, 2020 (virtual/attendee)
-Istanbul Finance Seminar Series, 2020-2021 (virtual/attendee)
-Virtual Experimental Finance Workshop, 2021 (virtual/attendee)
-Virtual Finance Theory Seminar, 2020 (virtual/attendee)
-SFU Department of Economics Brown Bag Seminar, 2020 (virtual/presenter)
-SFU Computing Science - Machine Learning Poster Session, 2018 (Vancouver/presenter)
-Center for Economics and Econometrics (CEE) Conference, Bogazici University, 2016 (Istanbul/attendee)