The Political Impact of Others' Job Loss: Personifying the Enemy

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Principal investigator:

Diana Mutz

University of Pennsylvania

Email: mutz@sas.upenn.edu

Homepage: https://www.sas.upenn.edu/polisci/people/standing-faculty/diana-mutz


Field period: 07/11/2017-11/01/2017

Abstract
Using two treatment conditions and a control condition, five hypotheses are tested that differentiate between Americans' reactions to job loss per se, as opposed to job loss attributed specifically to trade. Results suggest that over-attributing job loss to trade in the absence of knowledge about actual causes results in scapegoating foreigners and lowering support for international trade.

Hypotheses

H1: Attributing job loss to trade will produce greater negative emotional reactions than when job loss is attributed to automation.

H2: Job loss attributed to trade will produce more negative attitudes toward international trade relative to job loss attributed to automation.

H3: Job loss attributed to trade will increase belief that manufacturing jobs can be recovered relative to job loss attributed to automation.

H4: Job loss attributed to trade will increase the acceptability of negative stereotypes about people ethnically similar to those in the trading country.

H5: People in the control condition will assume that job loss in manufacturing is due to trade, even when there is no information provided.

Experimental Manipulations
Job loss attributed to either trade, automation or unspecified cause.

Outcomes
1) attitudes toward international trade; 2) negative emotions; 3) believe that manufacturing jobs can be brought back to US; 4) normative acceptability of negative stereotypes about foreigners.

Summary of Results
Trade support diminishes and negative emotions increase when an article attributes one man's job loss to trade. Job loss due to automation reduces beliefs that manufacturing jobs can return. Job loss attributed to trade increases the normative acceptability of negative Chinese stereotypes.