Arbeitspapier

Causal misperceptions of the part-time pay gap

This paper studies if workers infer from correlation about causal effects in the context of the part-time wage penalty. Differences in hourly pay between full-time and part-time workers are strongly driven by worker selection and systematic sorting. Ignoring these selection effects can lead to biased expectations about the consequences of working part-time on wages ('selection neglect bias'). Based on representative survey data from Germany, I document substantial misperceptions of the part-time wage gap. Workers strongly overestimate how much part-time workers in their occupation earn per hour, whereas they are approximately informed of mean full-time wage rates. Consistent with selection neglect, those who perceive large hourly pay differences between full-time and part-time workers also predict large changes in hourly wages when a given worker switches between full-time and part-time employment. Causal analyses using a survey experiment reveal that providing information about the raw part-time pay gap increases expectations about the full-time wage premium by factor 1.7, suggesting that individuals draw causal conclusions from observed correlations. De-biasing respondents by informing them about the influence of worker characteristics on observed pay gaps mitigates selection neglect. Subjective beliefs about the part-time/full-time wage gap are predictive of planned and actual transitions between full-time and part-time employment, necessitating the prevention of causal misperceptions.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 2031

Classification
Wirtschaft
Wage Level and Structure; Wage Differentials
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Expectations; Speculations
Subject
part-time pay gap
wage expectations
selection neglect
causal misperceptions

Event
Geistige Schöpfung
(who)
Schrenker, Annekatrin
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2023

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Schrenker, Annekatrin
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2023

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