Will Gender Parity Break the Glass Ceiling? Evidence from a Randomized

Experiment

Preliminary

Manuel F. Bagüés & Berta Esteve-Volart

(Universidad Carlos III) (York University)

Motivation• Gender parity or gender quotas imposed

or considered in many countries– France: electoral party lists– Norway: public enterprises’ boards– Spain: cabinet, considering all public sector

recruitment committees (legislation project approved by Government in March 8)

• No previous evidence of gender quota effectiveness

• We use data on public exams in Spain

Why?• Few women in top positions

– Politics: women occupy at least 30% parliamentary seats in 12 out of 179 countries

– Boards of large private companies: women are 2% in Spain, 3% in Italy, 4% in France

• Policy: from equal opportunities to gender parity– The failure of the pipeline theory

How?

• Directly: women hire more women

• Indirectly:

- Role model transmission

- Women in top positions can choose policy more adequate for women,

- Private sector: flexible working hours- Politics: public expenditure more useful to

women (Duflo and Chattopadhyay 2004)

Will it work?

Empirical evidence• Data on individual productivity

– General: evidence of wage gap (Blau & Kahn 1994)– Top management: Bertrand & Hallock (1999)– Researchers: CSIC (2003), Veugelers (2006), Long

(1993), Mairesse & Turner (2002)

• Data on firm productivity (Wolfers 2006)• Experimental data

– Blind Evaluation vs Non-Blind Evaluation• Blank (1990), Goldin & Rouse (2000), Lavy (2005)

– Randomization• Lab Experiments (Gneezy et al 2003)

Background Information

• We use data from public examinations in Spain• They determine the access to public positions

(judiciary, diplomacy, notaries, economists, tax inspectors, and many others)

• Every year 175,000 young university graduates take public exams

• Only a small number of candidates pass exams• Elite formation: many political figures had to

pass public exam (e.g. Aznar)

Characteristics of public exams

• Each committee examines 500 candidates• Random allocation of candidates to

evaluating committees• Evaluation

– Oral– Two or three stages, all qualifying– Voting by majority basis– Multiple choice test introduced in 2003 for

some exams

Data

• All results are published in the state official bulletin (BOE)

• We examine public exams to the judiciary, years 1995-2004 (new data: 1985-2005)

• Type of exams: judge, prosecutor, court secretary• 150 committees• 75,000 candidates involved• About 1,700 judges, prosecutors and court

secretaries recruited

Data: what do we know?

• Characteristics of evaluators– Gender, age, age of entry, rank

• Characteristics of successful candidates for all years– Gender, age, age of entry, rank

• Characteristics of all candidates for 2003 and 2004

• We do NOT know the individual vote of each committee member

Empirical strategy

1) Committee-level information:

where y is an outcome variable, s is female share in committee, X are committee characteristics

cetetcetcetcet Xsy

Interpretation

1. Female evaluators are tougher with female candidates

2. Male evaluators are more generous with female candidates

• Possible non-linearities?

2) Candidate-level information for years 2003 and 2004 (multiple choice test):

Quantitatively

• A female candidate’s chances to pass the public exam are 5.5% greater if evaluated by a committee with fewer women than the median committee, than if evaluated by a committee with more women that the median committee

Caveats• What is the motivation of the evaluators?

1) Evaluators have ‘irrational taste’

2) Evaluators behave according to rational choice but:- Women think women are worse (lack of

confidence) - Since the men in committees discriminated in the

past, men in committees now are more generous with female candidates (past discrimination)

- Women want to increase their group’s average quality (statistical discrimination)

Next step

• Evolution over time of the observed gender bias

– What happened since the first committee with a female member?

• Data before 1995