Low fare public transport as social policy? A study of Germany’s 9-Euro-Ticket and Deutschlandticket via propensity score matching

Abstract This study uses Propensity Score Matching (PSM) to evaluate the impact of two public transportation fare innovations in Germany—the 9-Euro-Ticket and the Deutschlandticket ( 49-Euro-Ticket )—on travel behavior and related outcomes focusing on economically marginalized individuals. Both tickets have drastically reduced the complexity of the fare system in Germany and lowered the cost of public transportation, in the case of the 9-Euro-Ticket , to almost zero. The goal of the study is to estimate causal effects in a quasi-experimental setting, as the tickets were not randomly assigned. PSM aims to reduce self-selection bias by creating a balanced sample of ticket-holders and non-ticket-holders, simulating the conditions of a Randomized Controlled Trial. After matching on key variables, weighted regression models were applied to produce doubly robust estimates of the Average Treatment Effect on the Treated. The study analyzes four main areas: activity participation, mode use, financial relief, and attitudes. Both tickets significantly increased the use of public transportation, with stronger effects for the 9-Euro-Ticket , especially among economically marginalized individuals. The tickets also led to a slight reduction in car use. The Deutschlandticket increased the probability of substituting car trips with public transportation. Both tickets increased agreement with positive statements about the ticket, with economically marginalized individuals emphasizing the social dimension of the policy. The application of the method demonstrates the usefulness of PSM for policy evaluation in transportation research.

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Publication Details

Journal
Transportation
Published
2025-07-12
DOI
https://doi.org/10.1007/s11116-025-10640-7
Citations
2
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
5.26

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article

Low fare public transport as social policy? A study of Germany’s 9-Euro-Ticket and Deutschlandticket via propensity score matching

Allister Loder, Klaus Bogenberger, Stefan Wurster, Isabella Waldorf
2 citations
Transportation
Advanced Causal Inference Techniques
5.26
article

Low fare public transport as social policy? A study of Germany’s 9-Euro-Ticket and Deutschlandticket via propensity score matching

Allister Loder, Klaus Bogenberger, Stefan Wurster, Isabella Waldorf
article en
2 citations

Abstract

Abstract This study uses Propensity Score Matching (PSM) to evaluate the impact of two public transportation fare innovations in Germany—the 9-Euro-Ticket and the Deutschlandticket ( 49-Euro-Ticket )—on travel behavior and related outcomes focusing on economically marginalized individuals. Both tickets have drastically reduced the complexity of the fare system in Germany and lowered the cost of public transportation, in the case of the 9-Euro-Ticket , to almost zero. The goal of the study is to estimate causal effects in a quasi-experimental setting, as the tickets were not randomly assigned. PSM aims to reduce self-selection bias by creating a balanced sample of ticket-holders and non-ticket-holders, simulating the conditions of a Randomized Controlled Trial. After matching on key variables, weighted regression models were applied to produce doubly robust estimates of the Average Treatment Effect on the Treated. The study analyzes four main areas: activity participation, mode use, financial relief, and attitudes. Both tickets significantly increased the use of public transportation, with stronger effects for the 9-Euro-Ticket , especially among economically marginalized individuals. The tickets also led to a slight reduction in car use. The Deutschlandticket increased the probability of substituting car trips with public transportation. Both tickets increased agreement with positive statements about the ticket, with economically marginalized individuals emphasizing the social dimension of the policy. The application of the method demonstrates the usefulness of PSM for policy evaluation in transportation research.

Transportation
Technical University of Munich (DE)
Technische Universität München
Openalex Percentile: Top 5%
Advanced Causal Inference Techniques
5.26
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