John List

Misinformation represents a vital threat to the societal fabric of modern economies. While the supply side of the misinformation market has begun to receive increased scrutiny, the demand side has received scant attention. We explore the demand for misinformation through the lens of augmenting critical thinking skills in a field experiment during the 2022 Presidential election in Colombia. Data from roughly 2.000 individuals suggest that our treatments enhance critical thinking, causing subjects to more carefully consider the truthfulness of potential misinformation. We furthermore provide evidence that reducing the demand of fake news can deliver on the dual goal of reducing the spread of fake news by encouraging reporting of misinformation.

Social scientists have increasingly turned to the experimental method to understand human behaviour. One critical issue that makes solving social problems difficult is scaling up the idea from a small group to a larger group in more diverse situations. The urgency of scaling policies impacts us every day, whether it is protecting the health and safety of a community or enhancing the opportunities of future generations. Yet, a common result is that, when we scale up ideas, most experience a ‘voltage drop’—that is, on scaling, the cost–benefit profile depreciates considerably. Here I argue that, to reduce voltage drops, we must optimally generate policy-based evidence. Optimality requires answering two crucial questions: what information should be generated and in what sequence. The economics underlying the science of scaling provides insights into these questions, which are in some cases at odds with …

In 2019 I put together a summary of data from my field experiments website that pertained to framed field experiments (see List 2024). Several people have asked me if I have an update. In this document I update all figures and numbers to show the details for 2023. I also include the description from the 2019 paper below.

In 2019, I put together a summary of data from my field experiments website that pertained to artefactual field experiments. Several people have asked me if I have an update. In this document I update all figures and numbers to show the details for the year 2023. I also include the description from the 2019 paper below. The definition of artefactual field experiments comes originally from Harrison and List (2004) and is advanced in List (2024).

Businesses, governments, and individuals have dealt with bringing ideas to scale, sometimes successfully, but all too often unsuccessfully. Scaling is at the core of my book The Voltage Effect (List, ) In both the book and this paper, I aim to elucidate what I have learned from using economics to understand the world. I begin this paper by discussing the meaning of the NABE Adam Smith Award. The rest of the papertalk proceeds first by describing the origins of my work on scaling and The Voltage Effect. Scaling has long been considered an art, but there was clearly a need for a scientific understanding. Following the origins, is an overview of some of the key takeaways from The Voltage Effect (List, ): identifying ideas with the potential to scale and the tools to take ideas to scale.

A Course in Experimental Economics John A. List Page 1 A Course in Experimental Economics John A. List Page 2 IF YOU WANT TO CITE OR GIVE ATTRIBUTION TO THIS SLIDE DECK, PLEASE CITE THE FORTHCOMING BOOK: List, John A. “A Course in Experimental Economics,” University of Chicago Press, forthcoming. Page 3 Some Tips for “Start-Ups” to do Better Field Experiments and Getting Your Work Published JA List U. Chicago, ANU, & NBER Page 4 Some Tips for Doing Better Field Experiments and Getting Your Work Published Page 5 Some Tips for “Start-Ups” to do Better Field Experiments and Getting Your Work Published JA List U. Chicago, ANU, & NBER SR Goal: Induce you to go into your AFE slides and your working papers and make changes to improve the work LR Goal: Induce you to change the way you design, examine, interpret, and/or write-up your future studies Human Capital Goals: …

While behavioral non-price interventions (“nudges”) have grown from academic curiosity to a bona fide policy tool, their relative economic efficiency remains under-researched. We develop a unified framework to estimate welfare effects of both nudges and taxes. We showcase our approach by creating a database of more than 300 carefully hand-coded point estimates of nonprice and price interventions in the markets for cigarettes, influenza vaccinations, and household energy. While nudges are effective in changing behavior in all three markets, they are not necessarily the most efficient policy. We find that nudges are more efficient in the market for cigarettes, while taxes are more efficient in the energy market. For influenza vaccinations, optimal subsidies likely outperform nudges. Importantly, two key factors govern the difference in results across markets: i) an elasticity-weighted standard deviation of the behavioral bias, and ii) the magnitude of the average externality. Nudges dominate taxes whenever i) exceeds ii). Combining nudges and taxes does not always provide quantitatively significant improvements to implementing one policy tool alone.

In this paper, we provide a suite of tools for empirical market design, including optimal nonlinear pricing in intensive-margin consumer demand, as well as a broad class of related adverseselection models. Despite significant data limitations, we are able to derive informative bounds on demand under counterfactual price changes. These bounds arise because empirically plausible DGPs must respect the Law of Demand and the observed shift (s) in aggregate demand resulting from a known exogenous price change (s). These bounds facilitate robust policy prescriptions using rich, internal data sources similar to those available in many real-world applications. Our partial identification approach enables viable nonlinear pricing design while achieving robustness against worst-case deviations from baseline model assumptions. As a side benefit, our identification results also provide useful, novel insights into optimal experimental design for pricing RCTs.