Monitoring Harassment in Organizations

Working Paper: CEPR ID: DP18423

Authors: Laura Boudreau; Sylvain Chassang; Ada Gonzlez Torres; Rachel Heath

Abstract: We evaluate secure survey methods designed for the ongoing monitoring of harassment in organizations. To do so, we partner with a large Bangladeshi garment manufacturer and experiment with different designs of phone-based worker surveys. “Hard” garbling (HG) responses to sensitive questions, i.e., automatically recording a random subset as complaints, increases reporting of physical harassment by 290%, sexual harassment by 271%, and threatening behavior by 45%, from reporting rates of 1.5%, 1.8%, and 9.9%, respectively, under the status quo of direct elicitation. Rapport-building and removing team identifiers from responses do not significantly increase reporting. We show that garbled reports can be used to consistently estimate policy-relevant statistics of harassment, including: How prevalent is it? What share of managers is responsible for the misbehavior? and, How isolated are its victims? In our data, harassment is widespread, the problem is not restricted to a minority of managers, and victims are often isolated within teams.

Keywords: harassment; whistleblowing; garbling; survey design; gender; readymade garments; bangladesh

JEL Codes: J81; P00; J16; D82


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
rapport building (RB) (R20)reporting rates of harassment (J81)
low personally identifiable information (low PII) (C81)reporting rates of harassment (J81)
hard garbling (HG) + rapport building (RB) + low PII (Z00)enhanced reporting rates (E01)
hard garbling (HG) (D50)reporting rates of physical harassment (J81)
hard garbling (HG) (D50)reporting rates of sexual harassment (J81)
hard garbling (HG) (D50)reporting rates of threatening behavior (K42)

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