Discussion Paper No. 589
Oktober 28, 2026
The Good, the Bad, and the Bayesian: Self-Confidence and Algorithmic Advice
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Understanding how decision makers incorporate external information is increasingly important as algorithmic predictions become a common source of advice. The literature on advice-taking suggests that people discount others' advice, especially when they feel competent. We experimentally study how self-confidence affects advice utilization and how algorithmic advice shapes confidence in final judgments. In our online experiment, participants make age predictions and assess the prediction accuracy before and after receiving algorithmic advice. We exogenously vary self-confidence through (perceived) task difficulty and vary the (observable) quality of the algorithmic advisor. While participants generally put more weight on high-quality ("good") advice, we find, contrary to the existing advice-taking literature, that they are less influenced by advice when they perceive the task as difficult. By contrasting age and accuracy predictions, we show that advice can influence beliefs without substantially changing point predictions: people who feel proficient at a task barely adjust their predictions toward high-quality advice but become more confident in them. When people feel less proficient, they are more reluctant to adjust their predictions toward low-quality ("bad") advice. Our design shows that prediction and confidence updating respond differently to perceived task difficulty and advice quality, implying that measures based solely on changes in point predictions can misstate the influence of advice. Comparing observed updating with a Bayesian benchmark further reveals systematic underutilization of advice, driven in particular by insufficient confidence updating following high-quality advice in tasks perceived as easy.
Keywords:
algorithmic advice; algorithm appreciation; confidence; online experiment;
JEL-Classification:
C91; D83; D91;
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Discussion Paper No. 588
Oktober 14, 2026
Integrated vs. Separated Schooling for Refugee Children: Long-Term Effects on Education and Assimilation
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Does direct integration into native schools or temporary placement in separate schools better promote the education and cultural assimilation of refugee children? In the Netherlands, primary-school-aged refugee children are placed in either integrated or separated schools depending on their randomly assigned municipality. By contrast, all secondary-school-aged arrivals are initially separated. We exploit this institutional setting in two-way fixed-effects models with age-at-arrival and municipality fixed effects. Using rich administrative data, we find that integrated schooling reduces educational attainment at age 18, particularly for children of lower-educated parents. At the same time, integrated schooling increases cultural assimilation, measured by hormonal-contraceptive usage among teenage women, particularly for children from non-Muslim-majority countries. A distinctive feature of separated schooling that may account for its positive educational effect is that it allows employing teachers specialized in native-language teaching for non-native speakers.
Keywords:
refugee children; schools; integration; educational attainment; contraceptives;
JEL-Classification:
I24; I21; J13; J15; O15;
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Discussion Paper No. 587
Repression, Exit, and Dissent in an Autocracy
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Does repression silence dissent or push people to leave? We study the arrest of protesters during East Germany's Peaceful Revolution, using novel micro-data from Leipzig. Residents of streets and houses with an arrested protester were more likely to have left their address once the Berlin Wall fell, and exit visa applications rose in the months after an arrest. Nearby protest activity and support for the opposition show no visible decline after an arrest. Our results suggest that repression raised the demand for exit without a visible retreat of voice, and that residents acted on this demand once leaving became possible.
Keywords:
protest; repression; emigration; exit visas; east germany; autocratic breakdown;
JEL-Classification:
H10; N44; P20;
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Discussion Paper No. 586
September 23, 2026
The Stories We Tell: Societal Narratives and Support for the Far Right
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In two studies using AI-assisted qualitative interviews, we ask a representative sample of the German electorate (N = 1, 013) to reflect on the most important societal events of the last 15 years. We document that far-right supporters construct systematically different narratives about the recent past. First, they recall different events—with a strong focus on migration-related issues. Second, even when they do consider the same events, they are more likely to blame the establishment and describe events more negatively and with greater emotional intensity. We further document that these narratives are associated with policy preferences, and that far right supporters are more inclined than supporters of other parties to prioritize cultural over economic issues. Together, our findings reveal that partisan divides extend to how citizens remember and interpret shared national experiences.
Keywords:
polarization; narratives; ai-assisted qualitative interviews; explanations; mental models;
JEL-Classification:
D01; C90; D84;
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Discussion Paper No. 585
September 9, 2026
The Supply-Side Effect of Immigration on Prices: Evidence from Nursing Homes
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We study how immigration affects prices through changes in labor supply. Using policy-driven increases in immigration to Germany and administrative data covering the universe of nursing homes, we find that one additional foreign-born woman per 100 residents reduces nursing-home care prices by 2.6 percent. The price effects are concentrated in more competitive markets. Examining potential mechanisms, we find that immigration lowers labor costs as nursing homes shift toward lower-paid foreign-born workers. We find no evidence of declines in inspection-based measures of quality or of scale effects. Finally, immigration increases the use of informal care, potentially strengthening competitive pressure from the broader care market.
Keywords:
immigration; labor supply; prices; nursing homes;
JEL-Classification:
J61; F22; J30;
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Discussion Paper No. 582
Gambling for Retirement: The Hidden Costs of Savings Lotteries in a Nationwide Experiment
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Governments increasingly encourage socially desirable behavior with probabilistic incentives. We study such “Pigouvian lotteries” in a retirement-savings field experiment with 387,000 workers in Colombia’s public pension system. The lotteries induce sharp bunching at qualification thresholds, but workers mostly meet them by retiming rather than increasing deposits, leaving overall savings largely unaffected. Lotteries further crowd out valuable life and disability insurance and disproportionately reward wealthier savers. A welfare analysis shows that, once we account for these unintended consequences, lotteries reduce welfare. Our findings illustrate that behavioral spillovers across time and choice domains can reverse the verdict on behavioral public policies.
Keywords:
retirement savings; prize-linked savings; paternalism; informality; household finance;
JEL-Classification:
D14; D91; H55; C93; G52;
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Discussion Paper No. 584
Fairness Views and Beliefs about the International Distribution of Climate Change Costs
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International climate negotiations focus on three distinct climate change costs: mitigation, adaptation and loss and damage. This paper measures voters' fairness views about how these costs should be allocated between nations, and investigates whether fairness views and beliefs about a country's responsibility matter for policy support. In an online survey experiment, the paper finds that fairness views vary with the type of cost, that voters underestimate their country responsibility, and that fairness views and beliefs jointly predict voters' climate policy preferences. The paper also implements tailored treatments to test whether fairness views and beliefs causally affect policy support, but it finds no evidence of a causal link. The results highlight that, to be consistent with citizens' fairness ideals, the international distribution of mitigation costs should differ from the one of adaptation and loss and damage.
Keywords:
climate change; international negotiations; policy support; fairness; misperceptions;
JEL-Classification:
D63; D91; F53; H41; Q54;
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Discussion Paper No. 583
Re-fielding Replicability of Silicon Sample-based Marketing Research
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Large language models are increasingly used to generate silicon samples, synthetic respondents that stand in for human participants in behavioral research. As silicon samples enter the methodological mainstream, the question of their re-fielding replicability becomes critical: when researchers regenerate a silicon sample under the same procedure at a later point in time, how stable are the resulting data? Existing validation studies have compared LLM-generated responses to human responses at a single point in time, but the temporal consistency of silicon samples themselves (whether independent reapplications of the same generation procedure yield comparable samples) has not been examined systematically, especially under sparse-conditioning, re-fielded sample-generation settings. We address this gap by generating silicon samples across three weekly waves, permitting a re-fielding consistency assessment. We benchmark this assessment with a human reference sample recruited via Prolific. Moreover, we systematically compare three structurally distinct generation paradigms that try to increase response variability: single-prompt batch generation, iterative generation with cumulative memory, and two-stage seed-and-expand generation. We find that re-fielding consistency is reasonably high in aggregate and comparable to the human benchmark for the strongest paradigm (two-stage seed-and-expand) but markedly lower for single-prompt batch generation. In contrast, alignment with the human reference is generally low, so that silicon samples reproduce their own outputs more faithfully than they reproduce human data. This means that silicon samples can be internally reproducible without being externally valid.
Keywords:
silicon samples; synthetic data; replicability; consistency; sustainability; plant-based meat;
JEL-Classification:
C83; C52; C45; M31; Q56; D12;
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Discussion Paper No. 581
The Making of the German Model of Industrial Relations
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This paper studies how collective bargaining institutions emerged from competition within the labor movement. We draw on newly assembled data on strikes, union membership, and bargaining agreements at the county-occupation level in Imperial Germany around 1900. Three rival factions competed for control of the labor movement: the social-democratic Free Trade Unions, the radical unions, and the moderate unions, divided over whether to confront employers, negotiate with them, or both. The Free Trade Unions struck more effectively than the radical unions and bargained far more than the moderate ones. Instrumenting Free Trade Union strength with distance to their headquarters, we show that stronger organization raised the likelihood that agreements emerged. Strike activity rose ahead of first agreements and fell thereafter. The effect is concentrated in multi-employer agreements with peace obligations, the bargaining form that later defined the German model. Organized employers played little part in this process. Durable bargaining institutions emerged where a movement could both sustain conflict and commit to settling it.
Keywords:
labor conflict; collective bargaining agreement; unions; endogenous institutions;
JEL-Classification:
N33; J51; J52; D72;
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Discussion Paper No. 580
Juli 31, 2026
Perceived Teammate Identity and Cooperative Behavior in Hybrid Human–Artificial Agent Teams
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We study how perceived teammate identity shapes effort allocation in hybrid human–artificial agent teams in collaborative environments. In a real-effort online experiment and under different incentive schemes, fixed payment and team competition, participants work in a team where each team member is responsible for their own segment but can observe and intervene in teammates’ segments. Teammates are algorithmically controlled agents, framed as either artificial or human-like, with their actual behavior held constant across treatments. Participants exert approximately one-third less compensatory effort when teammates are presented with human-like cues than when they are transparently labeled as artificial, and this difference is robust across both incentive schemes. The pattern is consistent with a model in which perceived human identity reduces the non-monetary benefit of helping. The result highlights that in hybrid teams, the labeling and presentation of artificial collaborators have economically meaningful consequences for cooperative effort and the organization of team production.
Keywords:
human–ai collaboration; online experiment; team incentives; teamwork; tournaments;
JEL-Classification:
C91; D29; D83; D89;