working papers

Abstract: We explore the economics of edible insects. We describe in detail how the biology of insects makes them a remarkable source of nutrition that can be produced with less resources and a lesser environmental impact than alternatives (e.g., meat). Thus, edible insects have the potential to play a key role in a more sustainable food system, thereby mitigating climate change and biodiversity loss. Furthermore, we highlight that a tropical climate and an abundance of endemic insect species in much of Latin America gives the region a competitive advantage in developing the industry to integrate edible insects into the food system.


Coauthored with Capitán

Abstract: This paper studies whether simple informational interventions can increase consumerwillingness to try insect-based foods. Using a randomized survey experiment in the Nordic countries, participants received either a control message or one emphasizing the environmental or nutritional benefits of edible insects. Neither intervention had a significant effect on willingness to try, suggesting that attitudes toward entomophagy are largely pre-determined. These results imply that firmsshouldprioritizeaccessibility and product developmentoverpersuasivemessaging. Policymakers seeking to promote insect consumption should consider structural incentives rather than relying on awareness campaigns.


Sole author

Abstract: Calorie labeling is a popular policy to address the obesity epidemic, but it has had little empirical success. Under the premise that willful avoidance of information plays a role in this result, we propose a novel approach—pre-nudges—to make consumers more receptive to calorie information. Unlike nudges, which are used to directly influence a choice, pre-nudges are used to directly influence how consumers react to the nudge itself (the calorie label). In line with predictions from our theoretical analysis, we test two pre-nudges in the context of menu labeling: one aims to increase self-efficacy, and the other one highlights the long-term health risks of overeating. In a large-scale laboratory experiment, we find that both pre-nudges reduce calorie information avoidance. Overall, our paper suggests a possible role for pre-nudges in addressing the obesity epidemic—one of the largest public health issues globally—and illustrates the potential usefulness of pre-nudges more generally.


Coauthored with Thunström, Van ’t Veld, Nordström, and Shogren (submitted) 📄

Abstract: We introduce the endowment effect for information: A tendency to value information more when expecting it, independently of its content. This result follows from a standard belief-based model of reference-dependent preferences and it is driven by gain-loss utility, though the information’s instrumentality can modulate the effect. Results from a laboratory experiment align with the theoretical results. Thus, we contribute to further understanding information avoidance beyond content or timing effects. Additionally, we discuss three experimental observations from a sequential manipulation of beliefs in our experimental design, laying groundwork for a theory of referent formation.


Coauthored with Thunström, Van ’t Veld, and Nordström

Abstract: Coming soon.


Coauthored with Méndez

Abstract: The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts’ choices. To explore this question, we took a sample of 100 studies published between 2009 and 2018 in criminology, demography, economics and finance, management, marketing and organisational behaviour, political science, psychology, and sociology. For one claim of each study, at least five re-analysts were invited to independently re-analyze the original data. The statistical appropriateness of the re-analyses was assessed in peer evaluations and the robustness indicators were inspected along a range of research characteristics and study designs. Only 31% of the independent re-analyses yielded the same result (within a tolerance region of +/- 0.05 Cohen’s d) as the original report. Even with a four times broader tolerance region, this indicator did not go above 56%. Regarding the conclusions drawn, only 34% of the studies remained analytically robust, meaning that all re-analysts reported evidence for the originally reported claim. Using a more liberal definition of robustness produced comparable result (39% when >80% re-analysis agreement with the original conclusion defined analytical robustness). This explorative study suggests that the common single-path analyses in social and behavioural research cannot be assumed to be robust to alternative — similarly justifiable — analyses. Therefore, we recommend the development and use of practices to explore and communicate this neglected source of uncertainty.


Coauthored with many others (revision requested, Nature)

Abstract: Published claims should be reproducible, yielding the same result when applying the same analysis to the same data. In a stratified random sample of 600 papers published from 2009 to 2018 in 62 journals spanning the social and behavioral sciences, authors of 146 (24.3% [95% CI 21.1 - 27.9%]) papers made data available to assess reproducibility. We assessed whether originally reported claims could be reproduced using the same data and analysis for papers in which authors made data available or we obtained source data to reconstruct the dataset. 76.2 (52.6% [95% CI 45.2 - 59.9%]) papers were rated as precisely reproducible and 104.4 (72.1% [95% CI 65.1 - 78.8%]) papers as at least approximately reproducible (within 15% of the original effects or within .05 of original p-values) after weighting 553 claims from 144.9 papers. We observed higher reproducibility for papers from Political Science and Economics than other disciplines, and for more recent than older papers.


Coauthored with many others (submitted)

Abstract: We attempted replications of 274 claims of positive results from 164 papers published from 2009 to 2018 in 54 journals in the social and behavioral sciences. Replications were high-powered on average to detect the original effect size (Median = 99.1%), used original materials when relevant and available, and were peer-reviewed in advance through a standardized internal protocol. Replications showed statistically significant results in the same pattern as the original study for 151 of 274 claims (55.1% [95% CI 49.2 - 60.9%]) and for 80.8 of 164 papers (49.3% [95% CI 43.8 - 54.7%]) weighed for replicating multiple claims per paper. Some decline is expected based on power to detect original effects and regression to the mean due to replicating only positive results. For claims where effect sizes could be converted to Pearson’s r, the median effect size was 0.23 [95% CI 0.21 - 0.28] for original studies and 0.11 [95% CI 0.08 - 0.13] for replication studies, a 53.4% [95% CI 42.3 - 65.2%] reduction in correlation and a 78.3% [95% CI 66.7 - 87.8%] reduction in shared variance. Thirteen methods for evaluating replication success provided estimates ranging from 31.1% to 77.1% (median = 49.9%), though most methods could only be applied to a subset of the replicated papers (median = 89.3%; range 63.3% to 100.0%). The conditions that promote or inhibit replicability are worthy of additional investigation.


Coauthored with many others (submitted)

published papers

Abstract: Replication is an important “credibility control” mechanism for clarifying the reliability of published findings. However, replication is costly, and it is infeasible to replicate everything. Accurate, fast, lower cost alternatives such as eliciting predictions from experts or novices could accelerate credibility assessment and improve allocation of replication resources for important and uncertain findings. We elicited judgments from experts and novices on 100 claims from preprints about an emerging area of research (COVID-19 pandemic) using a new interactive structured elicitation protocol and we conducted 35 new replications. Participants’ average estimates were similar to the observed replication rate of 60%. After interacting with their peers, novices updated both their estimates and confidence in their judgements significantly more than experts and their accuracy improved more between elicitation rounds. Experts’ average accuracy was 0.54 (95% CI: [0.454, 0.628]) after interaction and they correctly classified 55% of claims; novices’ average accuracy was 0.55 (95% CI: [0.455, 0.628]), correctly classifying 61% of claims. The difference in accuracy between experts and novices was not significant and their judgments on the full set of claims were strongly correlated (r=.48). These results are consistent with prior investigations eliciting predictions about the replicability of published findings in established areas of research and suggest that expertise may not be required for credibility assessment of some research findings.


Coauthored with many others (Nature Human Behavior, 2024) 📄 🔗

Abstract: We tested whether large language models (LLMs) can help predict results from a complex behavioural science experiment. In study 1, we investigated the performance of the widely used LLMs GPT-3.5 and GPT-4 in forecasting the empirical findings of a large-scale experimental study of emotions, gender, and social perceptions. We found that GPT-4, but not GPT-3.5, matched the performance of a cohort of 119 human experts, with correlations of 0.89 (GPT-4), 0.07 (GPT-3.5) and 0.87 (human experts) between aggregated forecasts and realized effect sizes. In study 2, providing participants from a university subject pool the opportunity to query a GPT-4 powered chatbot significantly increased the accuracy of their forecasts. Results indicate promise for artificial intelligence (AI) to help anticipate—at scale and minimal cost—which claims about human behaviour will find empirical support and which ones will not. Our discussion focuses on avenues for human–AI collaboration in science.


Coauthored with many others (Royal Society Open Science, 2024) 🔗

Abstract: A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as male-stereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.


Coauthored as part of an author-consortium with many others (Organizational Behavior and Human Decision Processes, 2023) 🔗

Abstract: We study the implementation of a time-varying pricing (TVP) program by a major electricity utility in Costa Rica. Because of particular features of the data, we use recently developed understanding of the two-way fixed effects differences-in-differences estimator along with event-study specifications to interpret our results. Similar to previous research, we find that the program reduces consumption during peak-hours. However, in contrast with previous research, we find that the program increases total consumption. With a stylized economic model, we show how these seemingly conflicted results may not be at odds. The key element of the model is that previous research used data from rich countries, in which the use of heating and cooling devices drives electricity consumption, but we use data from a tropical middle-income country, where very few households have heating or cooling devices. Since there is not much room for technological changes (which might reduce consumption at all times), behavioral changes to reduce consumption during peak hours are not enough to offset the increased consumption during off-peak hours (when electricity is cheaper). Our results serve as a cautionary piece of evidence for policy makers interested in reducing consumption during peak hours—the goal can potentially be achieved with TVP, but the cost is increased total consumption.


Coauthored with Alpízar, Madrigal-Ballestero, and Pattanayak (Resource and Energy Economics, 2021) 📄 💾 🔗

Abstract: Using a spatially explicit framework with low/middle-income country coastal characteristics, we explore whether aspatial policies augment the impact of marine protected areas (MPAs) and identify when MPAs create income burdens on communities. When MPAs are small and budget-constrained, they cannot resolve all of the marinescape’s open-access issues, but they can create win-win opportunities for ecological and economic goals at lower levels of enforcement. Aspatial policies—taxes, gear restrictions, license restrictions, and livelihood programs—improve the MPA’s ability to generate ecological gains, and licenses and livelihood policies can mitigate MPA-induced income burdens. Managers can use MPA location and enforcement level, in conjunction with the MPA’s impact on fish dispersal, to induce exit from fishing and to direct the spatial leakage of effort. Our framework provides further insights for conservation-development policy in coastal settings, and we explore stylized examples in Costa Rica and Tanzania.


Coauthored with Albers, Ashworth, Madrigal-Ballestero, and Preonas (Marine Resource Economics, 2021) 📄 🔗

Abstract: The design of protected areas, whether marine or terrestrial, rarely considers how people respond to the imposition of no-take sites with complete or incomplete enforcement. Consequently, these protected areas may fail to achieve their intended goal. We present and solve a spatial bio-economic model in which a manager chooses the optimal location, size, and enforcement level of a marine protected area (MPA). This manager acts as a Stackelberg leader, and her choices consider villagers’ best response to the MPA in a spatial Nash equilibrium of fishing site and effort decisions. Relevant to lower income country settings but general to other settings, we incorporate limited enforcement budgets, distance costs of traveling to fishing sites, and labor allocation to onshore wage opportunities. The optimal MPA varies markedly across alternative manager goals and budget sizes, but always induce changes in villagers’ decisions as a function of distance, dispersal, and wage. We consider MPA managers with ecological conservation goals and with economic goals, and identify the shortcomings of several common manager decision rules, including those focused on: (1) fishery outcomes rather than broader economic goals, (2) fish stocks at MPA sites rather than across the full marinescape, (3) absolute levels rather than additional values, and (4) costless enforcement. Our results demonstrate that such naïve or overly narrow decision rules can lead to inefficient MPA designs that miss economic and conservation opportunities.


Coauthored with Albers, Preonas, Robinson, and Madrigal-Ballestero (Environmental and Resource Economics, 2020) 🔗

Abstract: To ensure food security among rural communities under a changing climate, policymakers need information on the prevalence and determinants of food insecurity, the role of extreme weather events in exacerbating food insecurity, and the strategies that farmers use to cope with food insecurity. Using household surveys in Guatemala and Honduras, we explore the prevalence of food insecurity among smallholder farmers on both a recurrent (seasonal) and episodic (resulting from extreme weather events) basis, analyze the factors associated with both types of food insecurity, and document farmer coping strategies. Of the 439 households surveyed, 56% experienced recurrent food insecurity, 36% experienced episodic food insecurity due to extreme weather events, and 24% experienced both types. Food insecurity among smallholder farmers was correlated with sociodemographic factors (e.g., age, education, migration) and asset ownership. The factors affecting food insecurity differed between type and prevalence of food insecurity. Our results highlight the urgent need for policies and programs to help smallholder farmers improve their overall food security and resilience to extreme weather shocks. Such policies should focus on enhancing farmer education levels, securing land tenure, empowering women, promoting generational knowledge exchange, and providing emergency food support in the lean season or following extreme weather events.


Coauthored with many others (Regional Environmental Change, 2020) 🔗

Abstract: This paper describes the adaptive responses of rural households and community-based drinking water organizations (CWOs) during seasonal droughts in Costa Rica. It empirically characterizes the adaptive measures used by 3,410 households and 81 CWOs in the driest area of the country. Volumetric pricing is a powerful adaptation option for managing water scarcity during these periods. However, these pricing schemes are not properly set to recover costs for adequate investment in water infrastructure. As a result, many CWOs rely on external financial support to cover these investments. The financial and governance restrictions characterizing most CWOs must be overcome in order to implement most of the adaptation measures identified for preparedness against seasonal drought. On the other hand, some rural households use water sources in addition to the tap water provided by CWOs (e.g. bottled water), as well as water-storing devices (e.g. buckets). The lack of effective adaptation of CWOs to water scarcity, expressed by unreliable piped-water systems, would probably lead to a higher use of these alternatives. This would entail higher costs to households, due to the time and resources invested in these activities. These costs and the potential additional costs on health represent the social costs of community failures to adapt to drier scenarios in existing piped-water systems.


Coauthored with Madrigal-Ballestero, Salas, and Córdoba (Waterlines, 2019) 📄 🔗

Abstract: Costa Rica is considering expanding their marine protected areas (MPAs) to conserve marine resources. Due to the importance of households’ responses to an MPA in defining the MPA’s ecological and economic outcomes, this paper uses an economic decision framework to interpret data from near-MPA household surveys to inform this policy discussion. The model and data suggest that the impact of expanding MPAs relies on levels of enforcement and on-shore wages. If larger near-shore MPAs can produce high wages through increased tourism, MPA expansions could provide ecological benefits with low burdens to communities. Due to distance costs and gear investments, however, MPAs farther off-shore may place high burdens on off-shore fishers.


Coauthored with Madrigal-Ballestero, Albers, and Salas (Ambio, 2017) 📄 🔗