Publications

Wernerfelt N, Tuchman A, Shapiro B, & Moakler R. "Estimating the Value of Offsite Data to Advertisers on Meta" Marketing Science, forthcoming.

Alekseev G, Amer S, Gopal M, Kuchler T, Schneider JW, Stroebel J, & Wernerfelt N (2023). “The Effects of COVID-19 on US Small Businesses: Evidence from Owners, Managers, and Employees.” Management Science.

Athey S, Grabarz K, Luca M, & Wernerfelt N. (2023). “Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines.” Proceedings of the National Academy of Sciences.

Chetty R, Jackson MO, Stroebel J, Kuchler T, Hendren N, Fluegge R, Gong S, Gonzalez F, Grondin A, Jacob M, Koenen M, Laguna-Muggenburg E, Mudekereza F, Rutter T, Thor N, Townsend W, Zhang R, Bailey M, Barbera P, Bhole M, & Wernerfelt N. (2022). “Social Capital in the United States II: Exposure, Friending Bias, and the Determinants of Economic Connectedness.” Nature.

Chetty R, Jackson MO, Stroebel J, Kuchler T, Hendren N, Fluegge R, Gong S, Gonzalez F, Grondin A, Jacob M, Koenen M, Laguna-Muggenburg E, Mudekereza F, Rutter T, Thor N, Townsend W, Zhang R, Bailey M, Barbera P, Bhole M, & Wernerfelt N. (2022). “Social Capital in the United States I: Measurement and Associations with Economic Mobility.” Nature.

Working Papers

“Learning, Sophistication, and the Returns to Advertising: Implications for Differences in Firm Performance” [with Steven Tadelis, Christopher Hooton, Utsav Manjeer, Daniel Deisenroth, Nick Dadson and Lindsay Greenbaum.] 

Abstract: Why do establishments exhibit wide variation in their productivity and profitability? Can variation in returns to advertising help answer this question? We present results from a large field experiment on Facebook and Instagram that documents variance in advertisers’ ability to generate returns to advertising. We focus on campaigns aimed at boosting sales and tie advertising expenses to revenues for each advertiser. We find that spending on advertising led to significant increases in revenues, number of purchases, number of purchasers, and number of conversions. The heterogeneity in these results by expenditure, age, and engagement documents patterns consistent with learning by doing and variance in how sophisticated advertisers are. Advertisers who engage in more learning activities and more sophisticated data collection exhibit the highest returns and are more likely to continue their activities over time, suggesting that differences in advertising effectiveness may account for some of the variance in productivity across firms.

"Reducing misinformation sharing at scale using digital accuracy prompt ads" [with Hause Lin, Haritz Garro, Jesse Shore, Adam Hughes, Daniel Deisenroth, Nathaniel Barr, Adam Berinsky, Dean Eckles, Gordon Pennycook, and David G. Rand]

Abstract: Interventions to reduce misinformation sharing have been a major focus in recent years. Developing “content-neutral” interventions that do not require specific fact-checks or warnings related to individual false claims is particularly important in developing scalable solutions. Here, we provide the first evaluations of a content-neutral intervention to reduce misinformation sharing conducted at scale in the field. Specifically, across two on-platform randomized controlled trials, one on Meta’s Facebook (N=33,043,471) and the other on Twitter (N=75,763), we find that simple messages reminding people to think about accuracy—delivered to large numbers of users using digital advertisements—reduce misinformation sharing, with effect sizes on par with what is typically observed in digital advertising experiments. On Facebook, in the hour after receiving an accuracy prompt ad, we found a 2.6% reduction in the probability of being a misinformation sharer among users who had shared misinformation the week prior to the experiment. On Twitter, over more than a week of receiving 3 accuracy prompt ads per day, we similarly found a 3.7% to 6.3% decrease in the probability of sharing low-quality content among active users who shared misinformation pre-treatment. These findings suggest that content-neutral interventions that prompt users to consider accuracy have the potential to complement existing content-specific interventions in reducing the spread of misinformation online. 

“The Digital Welfare of Nations: New Measures of Welfare Gains and Inequality” [with Erik Brynjolfsson, Avinash Collis, Asad Liaqat, Daley Kutzman, Haritz Garro, Daniel Deisenroth, and Jae Joon Lee.] NBER Digest

Abstract: Digital goods can generate large benefits for consumers, but these benefits are largely unmeasured in the national accounts, including GDP and productivity. In this paper, we measure welfare gains from 10 popular digital goods across 13 countries by conducting large-scale incentivized online choice experiments on representative samples of nearly 40,000 people. We estimate that these goods – many of which are free to users – generate over $2.5 trillion in aggregate consumer welfare across these countries per year, which is roughly equivalent to 6% of their combined GDP. We find that lower-income individuals and lower-income countries obtain relatively larger welfare gains from these goods compared to higher-income individuals and countries. This suggests that digital goods may reduce inequality in welfare within and across countries by disproportionately benefiting lower-income groups.

“Designing Experiments with Synthetic Controls” [with Nick Doudchenko, Dave Gilinson, and Sean Taylor]

Abstract: Synthetic controls have become a powerful and standard component of the applied researcher’s toolkit. Research to date often takes the treated unit as fixed and conducts post-hoc analyses of different interventions. A common problem that has become increasingly relevant in applied work, however, is given a set of possible test units, how can a researcher select the best one(s) to experiment on? This paper develops an approach for answering this question with synthetic controls, leveraging simulated interventions and permutation tests across candidate test units. We also discuss frequent implementation issues that may arise in practice and how they can be addressed. Finally, using historical data from Facebook, we demonstrate the design and analysis of a country-level experiment and show the substantial gains from utilizing this approach. Our methodology is implemented in the open source R package countrytestr.

Earlier Publications

Wernerfelt N, Slusky DJG, & Zeckhauser R. (2017). “Second Trimester Sunlight and Asthma: Evidence from Two Independent Studies.” American Journal of Health Economics. 3(2): 227-253.

Dreber A, Rand DG, Wernerfelt N, Garcia JR, Lum JK, & Zeckhauser R. (2011). “Dopamine and Risk Choices in Different Domains: Findings Among Serious Tournament Bridge Players.” Journal of Risk and Uncertainty. 43: 19-38.

Rand DG, Pfeiffer T, Dreber A, Sheketoff R, Wernerfelt N, & Benkler Y. (2009). “Dynamic Remodeling of In-group Bias During the 2008 Presidential Election.” Proceedings of the National Academy of Sciences. 106 (15): 6187-6191.

Non-Refereed Publications

Amsden Z, et al. (2019) “The Libra Blockchain.” Technical White Paper.

Wernerfelt N, & Zeckhauser R. (2010). “Denying the Temptation to GRAB.” Chapter in The Natural Resources Trap. Ed. W Hogan and F Sturzenegger. Cambridge, MA: MIT Press.

Wernerfelt N, Tarnita C, Rand DG, & Nowak M. (2009) “A Modular Approach for Analyzing Evolutionary Games in Networked Populations.” Harvard College Mathematics Thesis.