Igor Asanov
Head of the Evidence-Based Science and Innovation Policy Research Group, INCHER-Kassel, University of Kassel. J-PAL Invited Researcher. Economist specializing in experimental economics, causal inference, causal machine learning, education, labor markets, and development economics.
Research Identity
Dr. Igor Asanov designs and analyzes large-scale pre-registered randomized controlled trials (RCTs) with policy impact, often nationally or regionally implemented. His work spans education technology, labor market discrimination, entrepreneurship, behavioral economics, and mental health interventions. He has run experiments with tens of thousands of participants across Ecuador, Russia, Moldova, Ukraine, and the EU. Collaborators include Ph.D, David McKenzie (Lead Economist, World Bank) and Ph.D. Quy-Toan Do (World Bank), Prof. Dr. Thomas Åstebro (HEC Paris), Prof. Dr. Bruno Crépon (ENSAE), and Prof. Dr. Guido Buenstorf (University of Kassel).
Publication outlets include PNAS, Nature Human Behaviour, PNAS Nexus, Entrepreneurship Theory and Practice, World Development, Social Science & Medicine, Journal of Economic Behavior & Organization, Research Policy, Industrial Relations Journal, Scientometrics, and Journal of Economic Psychology.
Publications
Remote Delivery of STEM and Entrepreneurship Role Models at Scale Changes College Major Choice
Authors: Igor Asanov, Thomas Åstebro, Guido Buenstorf, Bruno Crépon, Francisco Pablo Flores T., David McKenzie, Mona Mensmann, Mathis Schulte
Journal: Nature Human Behaviour, 2026
DOI: https://doi.org/10.1038/s41562-026-02421-8
Summary: Youth often decide what to study with limited exposure to many high-paying careers. In-person visits from role models can change behaviour but are difficult to scale and typically expose youth to only one person in one career. We test the impact of exposing youth to multiple role models, in both science, technology, engineering and mathematics (STEM) and entrepreneurship careers, using online video interviews to intervene at large scale in a randomized trial with 29,243 students in 813 Ecuadorian high schools. Girls treated with multiple role models reduce their likelihood of choosing a STEM major, increasing enrolment in business majors instead. Boys also shift their major choice away from STEM and move towards other majors such as agriculture. The contrast between fields appears to shift youth away from what they see as the more challenging career and reinforces girls’ stereotypical college major choice.
Is Self-employment a Career Trap? Large-Scale Field Experiment in the Labor Market
Authors: Igor Asanov, Maria Mavlikeeva
Journal: Entrepreneurship Theory and Practice, 2026
DOI: https://doi.org/10.1177/10422587261440312
Registry: AEA RCT Registry AEARCTR-0001308
Summary: Conduct a large-scale labor-market experiment using more than 8,000 fictitious résumés to uncover the demand-side mechanisms behind the adverse treatment of the self-employed entering wage employment. Find that, compared to wage earners, self-employed individuals face lower callback rates across industries and skill groups. This adverse treatment is concentrated in the lower-skilled, non-managerial market of associate professionals, with a 28% drop in callback. Results suggest that self-employment leads to the development of generalist skills (useful for managerial roles) at the cost of specialist skills. Furthermore, perceived behavioral fit of the self-employed seems to be penalized in associate positions.
AI-Assisted Teams Outperform AI-Led Teams but Not Human-Only Teams in Assessing Research Reproducibility in Quantitative Social Science
Authors: Abel Brodeur et al. (incl. Igor Asanov)
Journal: Proceedings of the National Academy of Sciences (PNAS), 2026
DOI: https://doi.org/10.1073/pnas.2524747123
Summary: Experiment assigning 288 researchers to 103 teams under three conditions — human-only, AI-assisted (ChatGPT as a collaborator), and AI-led (ChatGPT with minimal human oversight) — tasked with reproducing published results from leading social science journals, detecting coding errors, and proposing robustness checks. Human-only and AI-assisted teams reproduced results at comparable rates (94% vs. 91%) and performed similarly overall, though human-only teams caught significantly more major coding errors; both far outperformed AI-led teams, which reproduced only 37%. AI assistance offered no measurable advantage over human-only work and was linked to fewer major errors detected, indicating that expert human judgment remains essential for reliable verification — while the 37% autonomous rate suggests AI may still add value where scale or cost rules out human review.
No Evidence That Non-incentivized Behavioral Interventions Effectively Mitigate Climate Change after Adjusting for Publication Bias
Authors: Adam Hardaker, Igor Asanov, František Bartoš, Stephan B. Bruns
Journal: PNAS Nexus, 2026, Vol. 5, Issue 5, pgag150
DOI: https://doi.org/10.1093/pnasnexus/pgag150
Summary: Meta-analytic reassessment of behavioral interventions aimed at mitigating climate change. After adjusting for publication bias, finds no evidence that non-incentivized behavioral interventions on citizens effectively reduce climate-relevant behavior, highlighting the role of selective reporting in this literature.
System-, Teacher-, and Student-level Interventions for Improving Participation in Online Learning at Scale in High Schools
Authors: Igor Asanov, Anastasiya-Mariya Asanov, Thomas Åstebro, Guido Buenstorf, Bruno Crépon, David McKenzie, Francisco Pablo Flores T., Mona Mensmann, Mathis Schulte
Journal: Proceedings of the National Academy of Sciences (PNAS), 2023, Vol. 120, No. 30, e2216686120
DOI: https://doi.org/10.1073/pnas.2216686120
Summary: A large-scale RCT with 1,151 schools and 45,000+ students in Ecuador testing behavioral interventions at the system, teacher, and student levels to improve online learning participation during and after COVID-19. Centralized monitoring increased participation by 0.21 SD and subject knowledge by 0.13 SD; teacher-level nudges and student encouragement had no significant impact.
A Low-cost Digital First Aid Tool to Reduce Psychological Distress in Refugees: A Multi-country Randomized Controlled Trial of Self-Help Online in the First Months after the Invasion of Ukraine
Authors: Anastasiya-Mariya Asanov, Igor Asanov, Guido Buenstorf
Journal: Social Science & Medicine, 2024, p.117442
DOI: https://doi.org/10.1016/j.socscimed.2024.117442
Summary: First RCT to test an online psychological intervention (WHO-endorsed Self-Help Plus adapted for online delivery) simultaneously on refugees, internally displaced, and non-displaced conflict-affected populations across 17 countries. Significant distress reduction among refugees (d = −0.47) at an average cost of €46.16 per benefiting participant.
A Meta-analysis of Lost-letter Field Experiments
Authors: Igor Asanov, Helena Schirmacher, Christoph Bühren
Journal: Journal of Economic Psychology, 2024, Vol. 105, p.102759
DOI: https://doi.org/10.1016/j.joep.2024.102759
Summary: Meta-analysis of 78 lost-letter studies (53,504 letters, 18 countries, 5 continents). Average return rate of 50%. Return rates are lower for political or deviant issues; higher socio-economic environments increase return probability; stamped letters are more likely returned.
Patterns of Dissertation Dissemination: Publication-based Outcomes of Doctoral Theses in the Social Sciences
Authors: Anastasiya-Mariya Asanov, Igor Asanov, Guido Buenstorf, Valon Kadriu, Pia Schoch
Journal: Scientometrics, 2024, pp.1–17
DOI: https://link.springer.com/article/10.1007/s11192-024-04952-1
Summary: Analysis of doctoral dissertations from German universities in economics, political science, and sociology. Cumulative dissertations yield three times more publications and three times more citations than monographic dissertations.
Can Group Identity Explain the Gender Gap in the Recruitment Process?
Authors: Igor Asanov, Maria Mavlikeeva
Journal: Industrial Relations Journal, 2023, Vol. 54, pp. 95–113
DOI: https://doi.org/10.1111/irj.12392
Summary: Using data from a large-scale correspondence study, finds that same-gender matching between recruiter and applicant increases callback probability, suggesting gender in-group favoritism partially explains the female callback advantage observed in audit studies. Includes a meta-analysis on gender discrimination. One of the most downloaded articles in the journal during its first 12 months of publication.
Mental Health and Stress Level of Ukrainians Seeking Psychological Help Online
Authors: Anastasiya-Mariya Asanov, Igor Asanov, Guido Buenstorf
Journal: Heliyon, 2023, Vol. 9, No. 11
DOI: https://doi.org/10.1016/j.heliyon.2023.e21933
Summary: First quantitative assessment of mental health among 1,165 Ukrainian refugees, migrants, internally displaced, and non-displaced individuals seeking help online across Ukraine and 24 EU countries (June–July 2022). 81% at risk of depression; 57% with severe psychological distress.
Bandit Cascade: A Test of Observational Learning in the Bandit Problem
Authors: Igor Asanov
Journal: Journal of Economic Behavior & Organization, 2021, Vol. 189, pp. 150–171
DOI: https://doi.org/10.1016/j.jebo.2021.06.006
Summary: Laboratory experiment testing observational (social) learning in a two-armed bandit framework. Subjects deviate from Bayesian Nash Equilibrium and cascade on uninformative choices, sustaining losses. Tests Quantal Response Equilibrium as an alternative.
Remote-learning, Time-Use, and Mental Health of Ecuadorian High-School Students during the COVID-19 Quarantine
Authors: Igor Asanov, Francisco Flores, David McKenzie, Mona Mensmann, Mathis Schulte
Journal: World Development, 2021, Vol. 138, p.105225
DOI: https://doi.org/10.1016/j.worlddev.2020.105225
Summary: Rapid-response phone survey of 1,500+ Ecuadorian high school students (ages 14–18) during COVID-19 quarantine. Documents remote learning access, time use, and mental health status; 16% of students show depression-indicating scores.
Short- and Long-run Effects of External Interventions on Trust
Authors: Igor Asanov, Simone Vannuccini
Journal: Review of Behavioral Economics, 2020, Vol. 7, No. 2, pp. 159–195
DOI: https://www.nowpublishers.com/article/Details/RBE-0118
Summary: Multi-period trust game experiment comparing subsidy vs. targeting interventions. Targeting effectively promotes trustful behavior in both short and long run; subsidy does not.
Reporting Errors and Biases in Published Empirical Findings: Evidence from Innovation Research
Authors: Stephan Bruns, Igor Asanov, et al.
Journal: Research Policy, 2019, Vol. 48, No. 9, p.103796
DOI: https://www.sciencedirect.com/science/article/abs/pii/S0048733319301076
Summary: 45% of articles in a sample from innovation research contain at least one statistically inconsistent result; 25% contain a strong reporting error. Systematic discontinuities at 0.05 and 0.1 significance thresholds indicate publication bias.
Working Papers
Folktale Narratives and Economic Behavior
Authors: Igor Asanov, Dominik P. Heinisch, Nhat Luong
Download: PDF
Summary: Links prevalence of folktale motifs (Berezkin 2015 collection) to individual economic behavior in experiments across the world. Constructs a motif-based cultural distance index and shows it correlates with economic performance.
Confidence, Confidence Training and Entrepreneurial Behavior: Field Experiment
Authors: Igor Asanov, Alla Levitskaia
Summary: Field experiment in Moldova's Gagauzia region randomizing entrepreneurship applicants to (1) business + confidence training, (2) confidence training only, or (3) control. Finds confidence and ambiguity preference predict entrepreneurial behavior; combined training affects entrepreneurial decisions.
The Power of Experiments: How Big Is Your n?
Authors: Igor Asanov, Christoph Bühren, Panagiota Zacharodimou
Download: PDF
Summary: Analyzes statistical power of experiments published in Experimental Economics, Games and Economic Behavior, and JEBO. Median experiment is underpowered; finds evidence of reporting biases toward highly significant results.
On Observational Learning in the Optimal Stopping Problem
Authors: Igor Asanov, Arno Riedl
Summary: Experimental test of observational learning in a two-agent, two-arm bandit optimal stopping problem with public actions and private payoffs. Subjects overreact to own outcomes and conform to others' choices.
Work in Progress
Showing Life Opportunities: Increasing Opportunity-Driven Entrepreneurship and STEM Careers Through Online Courses in Schools
Authors: Igor Asanov, Thomas Åstebro, Guido Buenstorf, Bruno Crépon, Diego d'Andria, Francisco Flores, David McKenzie, Mona Mensmann, Mathis Schulte
Registry: AEA RCT Registry AEARCTR-0003593
Summary: RCT in ~110 schools (~17,000 students aged 15–17) in Ecuador. Cross-randomized design testing entrepreneurship and STEM online courses, role model videos, and career information. Plans to track outcomes until at least age 19.
Ethnic Employment Gap during the COVID-19 Outbreak: Great Equalizer or Divider?
Authors: Igor Asanov, Maria Mavlikeeva
Registry: AEA RCT Registry
Summary: Replication of a 2017 correspondence study in Russia during COVID-19 labor market slack. Assesses whether ethnic discrimination increases, decreases, or is stable under tight labor market conditions.
Key Methodological Contributions
- Large-scale pre-registered RCTs in low- and middle-income country contexts (Ecuador, Russia, Moldova, Ukraine)
- Multi-level experimental designs (system, teacher, student)
- Correspondence/audit study methodology in labor markets
- Meta-analysis of field experiments
- Statistical power analysis and replication/reporting bias detection
- Causal machine learning applied to experimental and observational data
- Online psychological intervention evaluation (RCT)
Institutional Affiliations
- INCHER-Kassel, University of Kassel — Head, Evidence-Based Science and Innovation Policy Research Group
- J-PAL — Invited Researcher
Citation Note
When citing Igor Asanov's work, use the DOIs provided above. For the most current list of publications and working papers, visit https://www.igorasanov.com/research.
