portrait

Markus Eyting

Postdoctoral Researcher in Economics at the Chair of Digital Economics at the JGU Mainz and at Heidelberg Institute of Global Health & Stanford Medicine. To learn more about me, please see my CV or click the icons below.

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Research

I am an applied microeconomist, using experimental methods as well as survey and administrative data to study the interplay of beliefs and individual decision-making with applications to health, discrimination, and machine learning.


Publications


Belief Elicitation with Multiple Point Predictions

with Patrick Schmidt

European Economic Review, 2021, Vol. 135

We propose a simple, incentive compatible procedure based on binarized linear scoring rules to elicit beliefs about real-valued outcomes - multiple point predictions. Simultaneously eliciting multiple point predictions with linear incentives reveals the subjective probability distribution without pre-defined intervals or probabilistic statements. We show that the approach is theoretically as robust as existing methods, while adapting flexibly to different beliefs. In a laboratory experiment, we compare our procedure to the standard approach of eliciting discrete probabilities on pre-defined intervals. We find that elicitation with multiple point predictions is faster, perceived as less difficult and more consistent with a subsequent decision. We further find that multiple point predictions are more accurate if beliefs vary between participants. Finally, we provide experimental evidence that pre-defined intervals anchor reports.


Can monetary incentives increase organ donations?

with Arne Hosemann & Magnus Johannesson

Economics Letters, 2016, Vol. 142, 56-58.

We test in an experiment if a monetary incentive or a charity incentive can motivate people to fill in the German organ donor card and thereby increase the number of organ donors. We find that a monetary incentive significantly increases the number of organ donors whereas the charity incentive does not.




Working Papers


Why do we Discriminate? The Role of Motivated Reasoning

Winner of the EEA 2023 Best Young Economist Award

Identifying the cause of discrimination is crucial to design effective policies and to understand discrimination dynamics. Building on traditional models, this paper introduces a new explanation for discrimination: discrimination based on motivated reasoning. By systematically acquiring and processing information, individuals form motivated beliefs and consequentially discriminate based on these beliefs. Through a series of experiments, I show the existence of discrimination based on motivated reasoning and demonstrate important differences to statistical discrimination and taste-based discrimination. Finally, I demonstrate how this form of discrimination can be alleviated by limiting individuals’ scope to interpret information.


A Random Forest A Day Keeps the Doctor Away

Using a unique dataset from a German health check-up provider including detailed individual questionnaire data as well as medical test data, I apply a random forest to predict several health risk factors. I evaluate the prediction performance using various metrics and find decent prediction qualities across all outcomes. By identifying the most relevant predictor variables, I compile concise and validated questionnaire tools to identify individuals’ blood pressure, blood glucose, and cholesterol levels, their risk of a coronary heart disease, whether or not they suffer from plaque or a metabolic syndrome as well as their relative fitness levels. In a second step, I compare the prediction results to physician predictions of the same patient observations. I find that the random forest outperforms the physicians if predictions are based on the same information set. When additionally providing the physicians with the random forest predictions for a particular patient observation, the physicians align with the random forest predictions. Finally, while the random forest considers various psychological scales, the physicians focus on family health history information instead.


Herpes zoster vaccination and new diagnoses of dementia: A quasi-randomized study

with Min Xie, Felix Michalik, Simon Heß, Seunghun Chung & Pascal Geldsetzer

There is increasing consensus that neuroinflammation plays an important role in the pathophysiology of dementia. Herpes zoster vaccination may, thus, have a beneficial effect on the dementia disease process because it reduces neuroinflammatory reactivations of the varicella zoster virus. In addition, live-attenuated vaccines appear to induce broader immune mechanisms that have important off-target health effects, with these effects often being far stronger among female than male individuals. This study, therefore, aims to determine the effect of live-attenuated herpes zoster vaccination on the incidence of dementia diagnoses. To reduce the chance of confounding, we take advantage of the fact that in Wales eligibility for the zoster vaccine was determined based on an individual’s exact date of birth. Those born before September 2 1933 were ineligible and remained ineligible for life, while those born on or after September 2 1933 were eligible to receive the vaccine for one year. Using country-wide data on all vaccinations received, primary and secondary care encounters, death certificates, and patients’ date of birth in weeks, we first show that the percentage of adults who received the vaccine increased from 0.01% among patients who were merely one week too old to be eligible, to 47.2% among those who were just one week younger. Apart from this large difference in the probability of ever receiving the zoster vaccine, individuals born just one week prior to September 2 1933 are unlikely to differ systematically from those born one week later. We test this empirically by showing that there were no differences in pre-existing conditions or uptake of other preventive interventions between adults across the date-of-birth eligibility cutoff, and that there do not appear to have been other interventions that used the exact same date-of-birth eligibility cutoff as was used for the zoster vaccine program. Using this unique quasi-randomization, we first replicate the vaccine’s known effect from clinical trials of reducing the occurrence of shingles. We then show that receiving the zoster vaccine reduced the probability of a new dementia diagnosis over a follow-up period of seven years by 3.5 percentage points (95% CI: 0.6 – 7.1, p=0.019), corresponding to a 20.0% (95% CI: 6.5 – 33.4) relative reduction. This protective effect was stronger among women than men. The zoster vaccine had no effects on any other common causes of morbidity and mortality. We triangulate our findings using i) a difference-in-differences instrumental variable approach, and ii) propensity score matching. Lastly, we successfully replicate our findings in a different population, type of data, and using an outcome that is closely related to dementia, but less reliant on a timely diagnosis of dementia by the healthcare system. Specifically, we used population-wide mortality data by month of birth for all of England and Wales (whereby England constitutes approximately 95% of England’s and Wales’s combined population) and the same quasi-randomization approach as in our main analyses. We show that eligibility for zoster vaccination based on one’s date of birth reduced the percentage of the population with a death whose primary cause was dementia by 0.38 (95% CI: 0.08 to 0.68, p=0.012) percentage points over a nine-year follow-up period, corresponding to a relative reduction of 4.8% (95% CI: 1.6% to 8.0%). As in our main analysis, this effect was stronger among women than men.

Coverage: Nature News, Washington Post, Spektrum der Wissenschaft [German], Deutsches Ärzteblatt Post [German], Der Tagesspiegel Post [German], Focus Online [German], La Repubblica [Italian], El Tiempo Latino [Spanish]


Contact

Room: 01-112, Q
Johann-Joachim-Becher-Weg 31
55128 Mainz, Germany
+49-6131-39-22166
meyting@stanford.edu