Keywords: confirmation bias, media market, media bias
This paper develops a theoretical model where individuals with limited attention select a portfolio of news sources to learn about the true state of the world. Confirmation bias naturally arises as individuals favor sources reinforcing their prior beliefs; however, I identify conditions where they instead seek neutral or contradictory sources. This occurs among those with weak priors, for whom a mix of the contradictory source with the neutral source is optimal. The model further examines the relationship between source error and polarization, showing an inverse-U pattern. However, endogenous switching to biased sources can disrupt this pattern, influencing overall polarization dynamics.
The Impact of Sentencing Ranges Design on Sentencing Decisions: An Empirical Analysis
This paper examines how sentencing range design influences sentencing decisions in the Czech legal system, leveraging a recent reform affecting theft and property offenses. Using differences-in-differences and regression discontinuity, I identify causal effects of sentencing ranges on outcomes. I find evidence of a severity effect, where harsher sentences result from placement in higher ranges, and a reference effect, where cases within the same range serve as benchmarks. These findings provide court-based evidence for phenomena previously studied only experimentally. The results contribute to the discussion on optimal sentencing range design by shedding light on the mechanisms shaping judicial decisions.
This paper is an extended version of my Master's thesis submitted to Charles University, Faculty of Law in September 2024 under the supervision of Michal Šoltés.
Discrimination, Design, and Behavior in Secondary Markets: Evidence from a Natural Experiment on Vinted.cz
In this paper, I model the behavior of buyers on the Vinted.cz platform. Buyers know that the quality of items sold varies more within one seller nationality group, but the nationality of the seller is uncertain for any given item. Buyers can pay a certain cost to acquire different types of information. I model several scenarios regarding information availability, including rational inattention. The aim is to derive the implications of each scenario for discrimination, buyer welfare, and the platform’s profit.
Team Composition and Productivity in Constitutional Courts: Evidence from Judge Rotation in the Czech Republic
This study examines the impact of various team characteristics on work efficiency. To identify this effect, we exploit a quasi-exogenous mechanism that assigns constitutional court judges to three-member panels. Using a newly compiled dataset of panel decisions from [years], we find that panel composition—particularly its diversity—significantly influences decision-making outcomes, such as the duration of proceedings, the success rate of proposals, and the frequency of citations. We further analyze the effects of judges’ professional background, education, age, and gender on these outcomes.
Selected Biases in the Quasi-Induced Exposure Approach to Relative Risk: Identification, Directions and Magnitudes
with Peter Bolcha, submitted to European Transport
This paper addresses the challenge of heterogeneity in risk exposure when estimating the relative risk (RR) of causing road traffic crashes (RTCs) for different driver types. Quasi-induced exposure is a well-established alternative to direct data collection for exposure estimation. We investigate biases imposed on RR estimates caused by errors in fault assignment and unequal driver mix. Simulations reveal the directions and magnitudes of the possible biases and empirical tests of these biases are performed on a Czech dataset (1.2 million RTCs). Results show that errors in responsibility assignment work in opposite directions, with magnitude of bias depending on the size of the error and the target group proportion. Bias caused by unequal mixing depends on the target group proportion and the extent of the heterogeneity of not-at-fault drivers. Empirical tests confirm the discussed biases and underline their importance while interpreting RR estimates, so far mostly ignored by the literature.
