Evidence concerning inequality in ability to realize aspirations is prevalent: overall, in specialized segments of the labor market, in self-employment and high-aspirations environments. Empirical literature and public debate are full of case studies and comprehensive empirical studies documenting the paramount gap between successful individuals (typically ethnic majority men) and those who are less likely to “make it” (typically ethnic minority and women). So far the drivers of these disparities and their consequences have been studied much less intensively, due to methodological constraints and shortage of appropriate data. This project proposes significant innovations to overcome both types of barriers and push the frontier of the research agenda on equality in reaching aspirations. Overall, project is interdisciplinary, combining four fields: management, economics, quantitative methods and psychology. An important feature of this project is that it offers a diversified methodological perspective, combining applied microeconometrics, as well as experimental methods.

1. EARHART: EquAl in ReacHing AspiRaTions
University of Warsaw FAME | GRAPE NHH
General info about the project
EARHART, Project no. 2019/34/H/HS4/00481
Abstract: Evidence concerning inequality in ability to realize aspirations is prevalent:
overall, in specialized segments of the labor market, in self-employment and high-
aspirations environments. Empirical literature and public debate are full of case stud-
ies and comprehensive empirical studies documenting the paramount gap between
successful individuals (typically ethnic majority men) and those who are less likely to
“make it” (typically ethnic minority and women). So far the drivers of these disparities
and their consequences have been studied much less intensively, due to methodolog-
ical constraints and shortage of appropriate data. This project proposes significant
innovations to overcome both types of barriers and push the frontier of the research
agenda on equality in reaching aspirations.
Overall, project is interdisciplinary, combining four fields: management, economics,
quantitative methods and psychology. An important feature of this project is that it
offers a diversified methodological perspective, combining applied microeconomet-
rics, as well as experimental methods.
The team
University of Warsaw: Joanna Tyrowicz (PI), Adrian Chadi (University of
Konstanz), Sebastian Zalas;
FAME | GRAPE: Magdalena Smyk-Szymańska (co-PI), Katarzyna Bech-Wysocka,
Lucas van der Velde, Hubert Drążkowski
NHH: Siri Terjesen, Bram Timmermans, Astrid Kunze
WP1 Inequality as a driver of entrepreneurship
Research question: Does labor market inequality drive take-up of (necessity) self-
employment (SE) among women?
Theoretical framework: A woman decides to become SE when:
(α − w)V − K > U(1 − GWG)
α - entrepreneurial ability; w - cost of being self-employed women; V - expected
payoff from being an entrepreneur; K - start-up costs; U - expected payoff from
being a worker; GWG - gender wage gap
Hypothesis: The higher the GWG ⇒the higher probability for women to become SE.
Data: Global Entrepreneurship Monitor and various Labor Market Microdata to esti-
mate Gender Wage Gaps
Pushed into necessity self-employment?
We find a positive & robust correlation between gender wage gaps and women’s
entrepreneurship, but... even larger for men!
We propose a new theoretical framework: including possibility that the model of the
decision to become self-employed is gender specific not only due to external factors
(GWG) but also internal (education, age, access to capital, entrepreneurial network).
Empirical test: We estimated parameters (β’s) of the model of probability to become
self-employed among men and provided a counterfactual decision of each woman in
the sample, as she decided like an average man.
Actual women vs. counterfactual
Women are in general more likely to be NECESSITY self-employed, but there is no
additional increase due to the gender wage gap. However, the correlation is ob-
servable for a counterfactual scenario - which means that the lack of correlation
between GWG and the probability of being SE is not due to differences in char-
acteristics, but different dependencies between personal characteristics and the
decision to become SE.
WP 2 Corporate boards diversity
Paper 1 Gender board diversity across Europe throughout four decades
Research task: building a Gender Board Diversity Dataset (GBDD) that includes also
private (not listed) companies - unlike BoardEx, which includes only public (listed)
companies [minority of board seats]
Data: Orbis records of 2+ million firms in Europe from 1986 to 2020 (originally with
no harmonisation)
Most challenging harmonisation:
Type of boards: Management Boards (MB), Supervisory Boards and Other Boards
(OB) - executive versus non-executive role
Gender of a board member: from names, based on linguistic rules across languages
Time trends in gender board diversity in Europe
Still, majority of firms have NO WOMEN on boards in 2020.
Paper 2 Do women help women? Mechanisms of diversity spillovers
Research question: Do women in other (non-executive) boards help women to get
to management boards if:
there is no public eye scrutiny (stock-listed versus private companies)
there is a token woman in ”other” board
Data: Harmonised GBDD data (from Paper 1)
woman in MBt (1) (2) (3) (4)
woman in OBt−1 -0.01*** 0.138*** 0.001 0.006***
(0.001) (0.019) (0.001) (0.001)
no public eyet 0.027
(0.009)
woman in OBt−1 # no public eyet -0.149***
(0.009)
token woman in OBt−1 -0.006***
(0.001)
Firms with women 0.21 0.25 0.22 0.22
Observations 9 913 051 13 903 488 5 023 962 5 023 962
Firms 1 631 081 2 214 249 954 670 954 670
Clustered SE YES YES YES YES
Fixed effects Firm Firm Firm Firm
MB - Management Board; OB - Other (non-executive) Board
no public eye scrutiny ⇒no help
one women ⇒no help
spillovers under the public scrutiny ⇒not if a token woman
Paper 3 (ONGOING STUDY): Women in boards and firm performance
Research question: Does more genderboard diversityaffect performance of the firm?
Challenge: Causal Identification Solution: Shift-Share instrument
Research task: Estimation of the equation:
log(sales)i,t = β0 + γGBDi,t + βk log(total assetsi,t) + βllog(employmenti,t) + ηi + i,t
where GBD - gender board diversity (share of women or share of boards with no
women in boards in the sector)
WP3 Biases against minorities in high aspiration positions
ONGOING STUDY: Confirmation bias in evaluating minority applicants
Research question: Do binding Equal Opportunity (EO) clauses backfire?
Research idea: An online experiment (correspondence test) with scholars from all
over the world - 10 000 e-mails with a request to advice in recruitment process -
evaluating CV’s.
between-subject variation: binding and non-binding EO clause;
between-subject variation: gender composition of the pool of candidates
(minority women versus equal shares);
random assignment of CV’s to evaluate
Available articles
Smyk, Magdalena Tyrowicz, Joanna, ”Pushed into necessity? Labor market
inequality and entreprenurship of disadvantaged group”, GRAPE WP6
Zalas, Sebastian Drążkowski, Hubert, 2023, ”The Evolution of the Labour Share in
Poland: New Evidence from Firm-Level Data”, Gospodarka Narodowa. The Polish
Journal of Economics
EARHART, Project no. 2019/34/H/HS4/00481