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Attribution Bias by Gender: Evidence from a Laboratory Experiment

YSI Webinar with Professor James Fenske

Start time:

May 18, 2020 @ 4:00 pm - 5:30 pm

Virtual Project Virtual Project

EDT

Location:

Online

Type:

Other

Virtual Project Virtual Project

Speakers

Speaker Image
James Fenske

Professor

Description

It is well understood that achieving gender parity matters for economic development. However, despite substantial progress in recent decades, gender inequality in the areas of well-being, rights, opportunities, and economic and political empowerment persists in many developing countries. A vast literature shows that discrimination leads to differences in men and women’s labour market outcomes at several stages, including screening, hiring, and promotion. A key mechanism that explains the differences in economic outcomes of men and women is that of attribution bias. Attribution bias by gender is understood as the tendency of observers to attribute good performance of males to skill and females to luck in certain tasks and vice versa. For example, physicians increase their referrals more to a male surgeon than to a female surgeon after a good patient outcome but lower their referrals more to a female surgeon than a male surgeon after a bad outcome. Such attribution bias has also been shown to be present among teachers who attribute boys' successes in mathematics to ability and girls' successes to effort.

In order to get a deeper understanding of the underlying mechanism that explains gender gap, the Economic Development WG is launching a webinar on one of the topical areas of research – gender. In this meeting, we will host Professor James Fenske who will discuss his recent paper on attribution bias by gender. The study presents evidence from a laboratory experiment by testing for the presence of attribution bias by gender through a principal-agent approach. It sheds light on whether a person’s gender has an effect on the way we interpret information about his or her ability. A lab experiment provides a controlled setting in which other factors are unlikely to influence participants’ behaviour.

Professor James Fenske is currently affiliated with the Department of Economics at the University of Warwick and is also a Research Associate at the Centre for Competitive Advantage in the Global Economy (CAGE). Previously, he held position as an Associate Professor at the University of Oxford. He has vast expertise in Economic History and Development Economics and is the recipient of several awards, including the Philip Leverhulme Prize in Economics.

Paper: Fenske, J., Castagnetti, A., & Sharma, K. (2020). Attribution Bias by Gender: Evidence from a Laboratory Experiment (No. 452). Competitive Advantage in the Global Economy (CAGE).

Link to the paper: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/452-2020_fenske.pdf

Hosted by Working Group(s):

Organizers

Attendees

Mandem Jim

Anika Muzib Suchi

Michael Cosh

Cicero Braga

Sophie Eales-White

Jheelum Sarkar

Md Labib Sadbin Hasan

Ruchira Bhattacharya

Ajibola Akanji

umesh moramudali

Mayuri Chaturvedi

Marcelo Gantier Mita

Joana Vaccarezza

Luisa Scarcella

Avinno Faruk

farhad gohardani

Ajwad Hossain

Ezebuilo Ukwueze

Elvis Avenyo

Khushboo Bhanushali

Kavitha Srikanth

Judith Derndorfer

Marta Musso

Sawsan Abdul-Jalil

supraja parthasarathy

Farjana Tonny

Giuliano Toshiro Yajima

Jay Pocklington

GEORGE SICHINGA

Tarik Imamović

Camila Alvarenga

Bijun Qin

Alice LIN

TANISHA GHOSAL

Soyra Gune

srikanth velijala

通 方

YANHUI WANG

Anisha Sawhney

Henry Faulkner-Ellis

Larissa Simões

Ana Peixoto

YANGFEI LIN

Dheeraj Tulsani

Santiago José Gahn

Nicholas Lacourse

SRINJAY CHANDRASEKAR

giuseppe simone

jiawei wu

Shizhuo Wang

Nur Batrisya Fathima

Adam Nowakowski

Oliver Hanney

Aishwarya Atluri

Becky zhu

Akanksha Soni

Alexandros Kordas

Arjo Shrestho

Guylaine Nouwoue

Eric Decker

Md. Al-Hasan

Mariana Ramírez

Md Jahurul Islam

Valentina San Martino

Minh Tam Bui

Achmad Kautsar

Eshrat Sharmin

Sazeda Akter

xinran liu

Amitoj Singh

Karmini Sharma

Tafsia Muzib

annesha muzib

Khaleda Yemin

Kanak Chanpa

Shirooa Purna

Ibshar Khan

anjali sharma