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Published in: Mengerian Economics, edited by A. Sielska, Ł. Jasiński, K. Turowski.
Cheltenham: Edward Elgar, pp. 155-167: https://www.e-elgar.com/shop/gbp/mengerian-
economics-9781035302888.html
Alicja Sielska
Assistant Professor, Institute of Economic Sciences, Faculty of Law, Administration and
Economics, University of Wrocław, Poland and Researcher, University of New York, Prague,
Czech Republic
alicja.sielska@uwr.edu.pl
PERFECT COMPETITION AND AN IMPERFECT WORLD.
CONSIDERATIONS ON THE GENDER WAGE GAP IN THE LIGHT OF CARL
MENGER’S THEORY
It seems that in an ideal world there should be no wars, diseases, pathologies, and every
person, regardless of race, religion, or gender, should be equal. Some believe that under such
conditions women and men will earn the same, and the World Bank’s estimates that due to the
gender wage gap, we lose twice as much as the world’s gross product (World Bank 2018) will
be forgotten. In economics, such a model image of wages is suggested by the neoclassical model
of perfect competition
i
. According to this theory, there must be an infinite number of
entrepreneurs in the economy, each of whom has a negligible share in the production of the
entire branch; the product is homogeneous; there is perfect information on the market and no
barriers to entry and exit (Begg, Vernasca, Fischer, Dornbusch 2014, p. 311). Similarly, in a
perfectly competitive labour market, employers and employees have full knowledge of wages
and available jobs; employers strive to maximize profit, and employees to maximize
satisfaction with real wages. There are no obstacles to labour mobility; employees and
employers make employment and wage decisions individually, and there is perfect
substitutability of employees (Kalinowska-Nawrotek 2005, p. 12). Thus, a perfect labour
market excludes discrimination based on gender.
The most popular neoclassical theories of discrimination based on the assumption of a
competitive market include Becker’s theory of taste-based discrimination (Becker 1971) and
Becker’s (Becker 1962) or Mincer’s and Polachek’s (Mincer, Polachek 1974) theory of human
capital. According to the former, women can potentially earn less than men due to employers’
prejudices. However, those who hold such beliefs about women will be driven out of the market
in the long run by competitors without such tendencies, who will start to make more profits by
employing an underestimated factor of production - in this case, women's work. Ultimately,
non-discriminatory entrepreneurs will raise women’s salaries to the level achieved by men.
According to the second of these theories, the same will happen with employers believing in a
lower human capital (inferior skills) of women. Thus, according to the neoclassical vision,
discrimination will not only be eliminated but will disappear completely (Sielska 2007, pp. 31–
46).
Gary Becker is credited with disseminating the theory of human capital with his book
titled Human Capital, published in 1964. On its basis, the difference between employees’
salaries was explained due to their investments in acquired characteristics that directly affect
the productivity of the individual. It was explained that women, due to their lower level of
human capital
ii
, can generate lower incomes than men (Sielska 2017, pp. 24–25). Thus, each
gender can achieve a different level of pay not due to discrimination, but because we are dealing
with workers with a different set of skills.
Therefore, it can be assumed that in the neoclassical world, women and men with the
same qualifications should earn the same wages, and discrimination will be a short-term
phenomenon. However, in this optimistic scenario there is a serious problem to be faced - the
assumptions of the model of perfect competition are far from reality. It is difficult to imagine a
world in which there is full knowledge on the labour market or perfect substitutability of
employees, etc. Of course, some will argue that mainstream economists are aware of the
limitations of their model, and that the assumptions they make are merely some kind of
simplification. However, without entering a discussion about the legitimacy of this argument,
it is worth noting that similar conclusions about the gender wage gap can be drawn on the basis
of the theory created by the founder of the Austrian School, Carl Menger.
In his opus magnum Principles of Economics (Grundsätze der Volkswirtschaftslehre,
1871), Menger explains that certain goods have a different price because of their characteristics
and market situation (supply/demand ratio), and that discrimination on the input market under
competitive conditions is unprofitable. Although he indirectly referred to the labour market, he
emphasized that the valuation mechanism is the same for all factors. As he wrote:
(…) the price of a good is a consequence of its value to economizing men, and the magnitude of its price
is always determined by the magnitude of its value. It is also evident, therefore, that rent, interest, and
wages are all regulated according to the same general principles (Menger 2007, p. 173).
Therefore, his argument regarding the consumer market can be applied to the labour market.
Thus, the problem in the form of unrealistic assumptions of the model of perfect competition is
avoided. For Menger, competition is a dynamic process and not an isolated, static case.
The main objective of this chapter is to analyse the gender wage gap in the context of
the possibility of equal pay for both genders. Based on the considerations on the theories of
Carl Menger, it has been demonstrated that equal pay is possible, i.e., it is not just a theoretical
phenomenon created by the model of perfect competition. The presented analysis was carried
out in two ways. On the one hand, the supply side was considered, i.e., employees with a
specific set of skills and experience. On the other hand, the demand side, i.e., employers
reporting a demand for work were accounted for (Jackson 1989).
Comparing the incomparable – the supply side of the gender wage gap
Generally, the gender wage gap is defined as the percentage difference between the average
wages of both genders. Simply put, it can be calculated based on the difference in average
wages of the logarithm of natural wages in the male and female population. Thus, if the
logarithm of a person's salary is marked as Yi and the binary variable determining the person’s
gender is marked as Mi (if Mi = 1 for men and Mi = 0 for women), then the gender wage gap can
be represented with the use of the following equation (Słoczyński 2012):
!
"
#$% &
'
( !
"
#$% )
'
% )
*
It is believed that the positive value of the wage gap thus expressed speaks in favour of
discrimination against women. The problem, however, is that the comparison of average
salaries of women to men (which is currently done by, e.g., the European Union
iii
) is not
correct
iv
. This raw, non-adjusted, uncorrected gap is a statistical way of comparison that does
not consider the fact that women and men are ‘different’ and, e.g., do ‘different’ work.
Menger stressed that in the consumer market, the exchange of goods does not take place
because of their equality for the persons participating in the transaction but is based on their
different valuations. An individual e.g., exchanges a horse for a hundred units of grain only
because he values that grain more highly than the animal he owns (similarly, for the owner of
the grain, it is of less value than the horse offered) (Menger 2007, p. 194). Thus, the subjective
perception of goods determines their final price. If one good has a higher price than another, it
means that it satisfies the needs of the individual in a different way. In other words, it is simply
a different good. Therefore, we perfectly understand why we pay more for a kilogram of organic
apples in contrast to those fertilized which are considered less healthy (because they are not
‘exactly the same’ fruits, differences occur both in the production process and in the final
product itself). The situation is similar in the labour market, e.g., men graduating from
secondary school, compared to women with higher education, are different, i.e., in this case
inferior workers
v
. Furthermore, different professions are characterized by a different level of
pay, e.g., a nurse earns less than a doctor.
Thus, estimating the unadjusted wage gap, without considering the components
affecting the remuneration, i.e., differences between employees, is an attempt to distort the
picture, ignoring the role of mechanisms for valuing factors of production. The price of land,
capital, and labour depends on productivity. Therefore, possible comparisons are justified when
talking about the same factors of production, i.e., identical apples or workers.
In the 1960s, Gary Becker conducted his ground-breaking study, explaining that human
capital is related to the worker’s productivity (Becker 1962). Since then, the number of studies
on discrimination against women in the labour market has started to grow dynamically in
economics (Weichselbaumer, Winter-Ebmer 2005). It was noted that the comparison of wages
between men and women is correct when we consider the differentiating factors that affect
wages, e.g., education level, sector, working time, etc. The wage gap, which would possibly
remain, would argue for a worse position of women in the labour market. Therefore,
homogenization theories have been developed, considering the adjusted gender wage gap. The
first method of this type is the Blinder-Oaxaca decomposition technique for the independent
double hurdle model.
Thus, in the 1970s, two economists working independently of each other, Ronald
Oaxaca (Oaxaca 1973) and Alan Blinder (Blinder 1973), used a method consisting in estimating
separate linear regressions of the logarithm of remuneration for women and men due to the
vector of explanatory variables. This can be written as follows (Słoczyński 2012):
+
$% , -$.$/, 01$ ,,,,,,,,,,,,,,234,#$% &5
,
+
$% , -$.6/ , 06$,,,,,,,,,,,,,,234,#$% )5
,
where, as before, Mi = 1 for men and Mi = 0 for women, in addition Yi is remuneration, Xi are
explanatory variables,
.7
and
.1
are parameters, and
8
"
01$9-$
'
% 8
"
06$9-$
'
% )*
Thus, the
difference between the remuneration of men and women is recorded as:
8
"
+
$9#$% &
'
( ,8
"
+
$9#$% )
'
% 8
"
-$9#$% &
'
.1( ,8
"
-$9#$% )
'
.7%
,
8
"
-$9#$% &
'
.1( ,8
"
-$9#$% )
'
.7/ 8
"
-$9#$% )
'
.1( ,8
"
-$9#$% )
'
.1%
,
8
"
-$9#$% )
'
.1( 8
"
-$9#$% )
'
.7/ 8
"
-$9#$% &
'
.1( ,8
"
-$9#$% )
'
.1%
!
"
-$9#$% )
'
,:.1( .7; / :!
"
-$9#$% &
'
( ,!
"
-$9#$% )
'
;.1*
,
As can be observed in the described method, the difference in the remuneration of men and
women can be presented as the sum of the explained component and the unexplained
component. The explained component, simply put, tells us how much of the observed wage gap
is because women and men are different (as explanatory variables we consider, e.g., age, marital
status, education, experience, profession, position held, etc.). Its individual components are
explained part
unexplained part
differences in the average values of individual variables multiplied by the corresponding
parameters from the regression. Then, from the difference between the average values of the
natural logarithm of remuneration in the male and female population, we subtract the estimated
explanatory component which consists of all explanatory variables, and as a result we obtain
the value of the unexplained component. The unexplained component informs about how much
of the observed wage gap results from the fact that women and men receive different wages
even when they are the same (for this reason it is interpreted as the result of discrimination). Its
elements are differences in parameters from regression for women and men multiplied by the
average value of a given variable in the respective group, i.e., women or men
vi
. For example:
Blinder in his pioneering paper studied, i.a., the wage gap between white men and white women
based on data from the Michigan Survey Research Centre in 1967. Based on calculations, he
explained that white men earn on average 45.8% more than women. 15.7% of this difference is
the explained component (to which Blinder included, i.a., components such as age, place of
residence, apprenticeships, profession, trade union membership, veteran status, time of work,
etc.), which means that if women had the same endowments, the gender wage gap would be
reduced by 15.7%. Women, among the observed variables, lost the most from the fact that their
wages did not increase over the life cycle, and men earned more primarily due to higher
education and less sensitivity to local working conditions (Blinder 1973). However, it follows
that still about 2/3 (the unexplained part in this case is 30.1%) of the wage gap remains
unexplained, which can be attributed to the effect of discrimination (women still earn less, even
though they have the same endowment as men). Why is this taking place?
First, it is worth drawing attention to the imperfection of the measurement tools. The
explained component depends on the variables that have been considered by the researcher, i.e.,
the value of the unexplained component may depend on variables that have not been considered,
and this does not mean per se the effect of discrimination. The authors of the described method
were aware of its specific weakness. Oaxaca, for example, noted that:
It is clear that the magnitude of the estimated effects of discrimination crucially depends upon the choice
of control variables for the wage regressions. A researcher’s choice of control variables implicitly reveals
his or her attitude toward what constitutes discrimination in the labour market (Oaxaca 1973, p. 699).
In addition, two economists, Doris Weichselbaumer and Rudolf Winter-Ebmer, performed a
meta-analysis of all English-language publications on the gender wage gap that appeared
between 1960 and 1990. Having studied 260 items covering different methods of calculating
the gap in more than 60 countries, they noticed that the limitations and choice of variables were
the most important for the result achieved. For example, in studies using subgroup datasets
(e.g., unmarried workers, workers entering the market, etc.), which allows for a better
comparison of employee productivity, the wage gap between men and women was narrowing.
On the other hand, in measurements that lacked key features related to human capital such as
e.g., work experience, the wage gap was usually overstated. A similar problem occurred when
the considerations did not use hourly rates but were based on monthly or annual salaries which
considered breaks in work, and their comparison gave an erroneous picture of the situation of
women (Weichselbaumer, Winter-Ebmer 2005). Interestingly, Oaxaca also writes that:
If it were possible to control for virtually all sources of variation in wages, one could pretty well eliminate
labour market discrimination as a significant factor in determining wage differentials by sex (or race)
(Oaxaca 1973, p. 699).
This thesis can be confirmed by, i.a., the research conducted in 2018 in the financial planning
industry on a sample of 710 people. It clearly demonstrates that the gender wage gap amounted
to 19%, of which as much as 91% can be explained by the differences between women and
men. Only 9% of the estimated difference (provided that all variables are considered) can be
attributed to the effect of discrimination, and this means that women in this industry would earn
on average 1.8% less than men if they were actually ‘exactly the same workers’ as men.
According to the authors of that text, the greatest impact on the wage was the degree of
motivation in the system of remuneration for results and generated income, as well as the role
played, team structure, etc. (Tharp, Lurtz, Mielitz, Kitces, Ammerman 2019).
Therefore, it can be concluded that the choice of explanatory variables has the greatest
impact on the size of the wage gap. On the other hand, it turns out that in sectors where the
factors determining the wage gap can be largely isolated, the gap is small
vii
.
Demand-side discrimination
The component explained in the Blinder-Oaxaca double decomposition, as mentioned, helps to
answer the question: “How much would women’s pay increase if there were no differences in
factors affecting the wages.” The problem, however, is that with its help we only see why in
certain situations women perform worse. However, we do not know the exact cause of this
situation (Madden, 2012). It can be assumed that, on the one hand, these are human choices,
e.g., women are looking for work closer to their place of residence or taking up part-time
employment
viii
. They also work in generally lower-paid industries, such as nursing and
education
ix
, and in general their human capital (which is influenced not only by education but
also by experience, often outdated due to maternity leave) may be lower than that of men. In
addition, it should be noted that some variables in the explained component may be affected by
employers’ preferences, e.g., women take up lower positions due to business owners’ or
executives’ biases
x
. It is thus argued that the explained component is not exempt from
discrimination and that, therefore, its possible magnitude cannot be attributed solely to an
unexplained component.
Employers’ prejudices are difficult to consider in static models. Even by introducing a
binary variable (0 - employers without prejudice, 1 – prejudiced employers), we will not avoid
the problem of obtaining reliable data (e.g., employers will not admit to their preferences, and
employees may overestimate or underestimate the beliefs of their superiors). However, Gary
Becker (Becker 1971) tried to show that employers’ preferences could impact the size of the
gender pay gap. The utility function of such employers can be written with the following
formula:
< % =>
:
?@/ ?A
;
(, B@?@(BA?A(C?A
*,
,
where: p - the general price level; F - production function for the employer; Nw - number of
women employed; Nm – number of men employed; ww - the salary offered to women; wm - the
wage offered to men; d – a coefficient of discrimination equal to the utility loss in relation to
the employment of one woman
xi
.
Therefore, it can be concluded that prejudices against women generate for the employer
a unit cost of work in an equal form (ww – d). Therefore, if wm – ww
≥ d
, then the employer will
decide to hire a woman. In addition, the optimal number of employees employed in the
company depends on the assumption:
pF’ (Nm) = wm, for men
and
pF’ (Nw) = ww + d, for women.
Assuming that p is constant and constitutes the sum for all employers, the demand
function for men can be written as: Nmd (wm; ww; d) = Nms (wm) and for women: Nwd (wm; ww;
d) = Nws (ww), where Ns denotes respectively the supply function (Nms - supply function for
men; Nws - supply function for women). Hence, it is reasonable to claim that the difference
satisfying the assumption: ww < wm will increase in the case of increasing the number of
employers with prejudices, when the demand for employees who are women (while ww = wm)
will be lower than their respective supply. Therefore, increasing the number of discriminatory
employers will lead to an increase in the wage gap. In addition, it can be concluded from the
model that women can be employed by employers who have no prejudice against them, which
will lead to segregation in the labour market (Altonji, Blank 1991, pp. 3170-3171).
Nevertheless, Becker points out that with an increase in the number of employers with
prejudices, women will obtain lower wages. However, in the long run, competitive
entrepreneurs who want to make as much profit as possible, noticing such a situation, will begin
to hire women doing the same work for a lower wage than men in other companies. Thus,
discriminatory employers will begin to suffer economic losses until they are eventually driven
out of the market. This means that it is not profitable for employers to treat women worse, as
these are purely uneconomical behaviours and should be eliminated on the labour market
(Sielska 2017, p. 21; Słoczyński 2008).
It must be emphasised that what Becker managed to explain about discrimination had
already been noticed more than a century earlier by the precursor of the Austrian school.
Menger, in the Principles of Economics, in chapter five entitled “Price Theory,” as has been
said before, did not consider competition within the framework of the model of perfect
competition. Therefore, he did not refer to unrealistic assumptions. Competition was a dynamic
process in his view. He believed that in the consumer market under competitive conditions, a
seller
xii
who excludes a certain number of customers from the purchase of a particular product
limits his earning opportunities. This customer will probably go to another seller and acquire
the good anyway. In addition, unlike monopoly (where the lack of competition makes it
possible to raise the price of a good within the limits acceptable to the demand side), not using
the available factors of production (which affects the higher price of the good) will also result
in a worse position on the market in relation to other entrepreneurs (Menger 2007, pp. 220-
225). The same mechanism can be applied to the labour market. Let us imagine a discriminatory
employer who, due to his stereotypical thinking about women, does not want to promote a
female worker and thus offer her a higher salary. If indeed this woman’s wage is too low in
relation to her productivity, then any other entrepreneur who wants to generate as much profit
as possible will be interested in employing her. If the work sold on the market is below its value,
it is worth hiring such an employee, and then entrepreneurs competing for an underestimated
factor of production (a female employee, in this case) will increase its value.
Conclusion
Perfect competition offers a picture of an ideal world without a gender wage gap. The problem,
however, is that this idealistic analysis is based on assumptions detached from reality. However,
considering the theories of Carl Menger described in this chapter, it can be assumed that in the
world around us it can also be perfect, i.e., there is a chance to significantly reduce the wage
gap between genders. First, on the supply side, workers with the same endowments should earn
equal wages. Secondly, in competitive markets, employers’ prejudices against women will be
marginalised. Reality does not have to be imperfect. For this to happen, however, it is necessary
to understand the fundamental laws of economics, including issues concerning the valuation of
factors of production which were emphasized by the founder of the Austrian School.
Is the gender substitution of workers, i.e., equalization of the level of education, a break
with the division into feminized and masculinized professions, equality in the issue of care
work, etc. the only solution to the problem? Perhaps our perception of the ‘ideal world’ ignores
the freedom and preferences of the individual. Angus Deaton notes that in the 1960s, the
demographic explosion in poor countries kept people in rich countries awake. This anxiety was
mainly on humanitarian grounds, as many poor countries already struggled to feed their
residents Therefore, the policy of the developed part of the world began to deal with help in
controlling the number of children (international organizations borrowed money for this
purpose, foundations collected appropriate funds). What the poor themselves, that is, people
with children thought about it, whom it was about, was of nobody’s interest. However, the
African and Asian children who contributed the most to the demographic explosion were, in
most cases, wanted children (Deaton 2013, pp. 241–242). Further, the same author writes:
Certainly, not everyone everywhere has access to convenient modern contraception at low cost, but there
is over-whelming evidence—if indeed evidence is required—that on average, if not family by family,
people want the children they have, with their own good reasons for having them. The story of unbridled
passion provided a convenient rationale for what “we” wanted to do, which was to “help” poor people
have fewer children that “they” wanted but “we” did not. No one presented evidence that people wanted
such help or that having fewer children would improve their lives. Quite the contrary (Deaton 2013, p.
241).
Similarly, nowadays the need for both genders to receive the same earnings is emphasized.
Equal opportunities should be ensured in this regard, but this does not mean that everyone will
want to use them equally. If there are no symptoms in every case that ‘we want’ and ‘women
do not,’ then the world will still be perfect in our imperfect way of thinking.
Bibliography
Autor D. (2003). Lecture Note the Economics of Discrimination,
https://economics.mit.edu/files/4095 [Available at 12.02.2021].
Altonji J.G., Blank R.M. (1991). Race and Gender in the Labour Market, in Ashenfelter
O., Card D. (eds.), Handbook of Labour Economics, 1st edition, vol. 3. Amsterdam: North
Holland.
Becker G. (1962). Investment in human capital: A theoretical analysis. The Journal of
Political Economy, 70(5), pp. 9–49.
Becker, G. (1971). The Economics of discrimination, 2nd edition. Chicago, IL:
University of Chicago Press.
Begg D., Vernasca G., Fischer S., Dornbusch R. (2014). Economics, 11th edition.
Maidenhead : McGraw-Hill Education.
Bisom-Rapp S., Sargeant M. (2016). Lifetime Disadvantage, Discrimination and the
Gender Workforce. Cambridge: Cambridge University Press.
Blinder A.S. (1973). Wage Discrimination: Reduced Form and Structural Estimates.
Journal of Human Resources, 8(4), pp. 436–455.
Criado Perez C. (2019). Invisible Women. Data Bias in a World Designed for Men. New
York: Abrams Press.
D’Amico T. (1987). The Conceit of Labour Market Discrimination. American
Economic Review, 77(2), pp. 310–315.
Deaton A. (2013). The Great Escape: Health, Wealth, and the Origins of Inequality.
Princeton and Oxford: Princeton University Press.
Eurostat (2020). Gender Pay gap statistics. Available at
https://ec.europa.eu/eurostat/statistics-explained/index.php/Gender_pay_gap_statistics
[Accessed 2.01.2021].
Jackson L. (1989). Relative deprivation and the gender wage gap. Journal of Social
Issues, 45(4), pp. 117–134.
Kalinowska-Nawrotek B. (2005). Dyskryminacja kobiet na polskim rynku pracy.
Poznań: Akademia Ekonomiczna w Poznaniu.
Knight F. (1921). Risk, Uncertainty, and Profit. Chicago, IL: University of Chicago.
Madden J. (2012). Performance-support bias and the gender pay gap among
stockbrokers. Gender & Society, 26(3), pp. 488–518.
Menger C. (2007). Principles of Economics. Translated by J. Dingwall, B. Hoselitz.
Auburn, AL: Ludwig von Mises Institute.
Mincer J., Polachek S. (1974). Family investments in human capital: Earning of women.
Journal of Political Economy, 82(2), pp. 76–108.
Nelson J.A. (1995). Economic Theory and Feminist Theory. W: E. Kuiper, J. Sop (eds),
Out of the Margin: Feminist Perspectives on Economics. New York: Routledge.
Obama B. (2014). Remarks by the President on Equal Pay for Equal Work. The White
House. Available at https://obamawhitehouse.archives.gov/the-press-
office/2014/04/08/remarks-president-equal-pay-equal-work [Accessed 14.06.2021].
Oaxaca R. (1973). Male-Female Wage Differentials in Urban Labour Markets.
International Economic Review, 14(3), pp. 693–709.
Rothbard M. (2010). Economists and Competition, in Gordon D. (ed.), Strictly
Confidential: The Private Volker Fund Memos of Murray N. Rothbard. Auburn, AL: Ludwig
von Mises Institute, pp. 307–320.
Sielska A. (2017). Dyskryminacja instytucjonalna kobiet na polskim rynku pracy.
Warszawa: CeDeWu.
Słoczyński T. (2008). Indywidualistyczne teorie dyskryminacji kobiet na rynku pracy.
Mishellanea, 4(8), pp. 79–87.
Słoczyński T. (2012). Wokół międzynarodowego zróżnicowania międzypłciowej luki
płacowej. International Journal of Management and Economics, 34, pp. 169–185.
Tharp D., Lurtz M., Mielitz K., Kitces M., Ammerman D. (2019). Examining the gender
pay gap among financial planning professionals: A Blinder-Oaxaca decomposition. Financial
Planning Review, 2(3–4), e1061.
Weichselbaumer D., Winter-Ebmer R. (2005). A meta-analysis of the international
gender wage gap. Journal of Economic Surveys, 19(3), pp. 479–511.
World Bank. (2018). Globally, Countries Lose $160 Trillion in Wealth Due to Earning
Gaps Between Women and Men. Available at https://www.worldbank.org/en/news/press-
release/2018/05/30/globally-countries-lose-160-trillion-in-wealth-due-to-earnings-gaps-
between-women-and-men [Accessed 11.01.2021].
World Bank. (2020). Girls’ education. Available at
https://www.worldbank.org/en/topic/girlseducation [Accessed 13.02.2021].
Zachorowska-Mazurkiewicz A. (2016). Praca kobiet w teorii ekonomii. Perspektywa
ekonomii głównego nurtu i ekonomii feministycznej. Kraków: Wydawnictwo Uniwersytetu
Jagiellońskiego.
i
From Cournot, Jevons, Edgeworth, i.a., to Clark, the fate of perfect competition was shaped (these economists
participated in the creation of individual assumptions of the model, e.g., Cournot, using calculus, noticed the
possibility of distinguishing different forms of the market depending on the number of sellers, and Clark added
elements of resource mobility and the concept of a stationary economy to the modern concept of perfect
competition). For more on this topic, see Rothbard (2010). The researcher to have collected all the conditions of
perfect competition and combined them into an analytical whole is considered to be Frank Knight (Knight 1921).
ii
It has also been pointed out that women may have a level of human capital similar to men. However, even in
this case, they will receive lower wage because it is a different type of capital, which: 1) more often contributes
to non-monetary returns, 2) is less specialized, 3) is lost as a result of career breaks and 4) increases satisfaction
with both paid, unpaid work and rest, when men invest in human capital contributing only to high cash returns
(Zachorowska-Mazurkiewicz 2016, pp. 100–101).
iii
The unadjusted gender wage gap is calculated by the European Union as the difference between the average
gross hourly earnings of men and women expressed as a percentage of men’s average gross hourly earnings. It is
estimated for enterprises with 10 or more employees (Eurostat 2020).
iv
Often, the media use the unadjusted gender pay gap in an attempt to illustrate the inferior position of women in
the labour market. Barack Obama used similarly calculated data during his speech in April 2014: “Now, here's the
challenge: Today, the average full-time working woman earns just 77 cents for every dollar a man earns; for
African American women, Latinas, it's even less. And in 2014, that's an embarrassment. It is wrong” (Obama
2014).
v
Provided that we recognize that an individual’s productivity depends on human capital, the amount of which is
influenced by, i.a., level of education.
vi
The author thanks Dr Tymon Słoczyński for his time and explanation of the Blinder-Oaxaca decomposition.
vii
Speaking of discrimination against women in the labour market, it is pointed out that this phenomenon must be
considered in two ways. On the one hand, women may receive worse treatment after entering the labour market,
and on the other hand, before entering it, when they have limited access to education or other forms related to
investing in human capital (D’Amico 1987). This also means that the analysis of the wage gap alone does not
exhaust the problem of discrimination. According to Angus Deaton, global education levels have improved
significantly since World War II, and women are better educated today; e.g., between 1986 and 1996, the
proportion of girls attending school in the Indian countryside increased from 43 to 62% (Deaton 2013, p. 105).
However, according to UNESCO, 32 million girls are still out of school worldwide (including 34.3 million in
primary school, 30 million in middle school and 67.4 million in high school). In countries affected by armed
conflict, girls are more than twice as likely to be out of school as in non-conflict countries. In addition, in many
countries, a small number of girls entering primary school will complete it, and far fewer will graduate from
secondary school (World Bank 2020). For more on this topic, see e.g.: Bisom-Rapp, Sargeant (2016), pp. 19–32.
viii
However, this does not mean that women are less hardworking. In general, a smaller number of hours devoted
to paid work is associated with having more household duties. It is estimated that “on a global scale, 75% of unpaid
work is done by women. They devote three to six hours a day to it, while the average for men is from thirty minutes
to two hours” (Criado Perez 2019, p. 68).
ix
It should be pointed out that professions considered to be feminised are often strongly influenced by the state.
For example, health care or education are characterized by constant appeals for raises for employees. Their work
is inadequately valued, which is the result of maintaining non-market health care systems or education.
x
Nelson observes that companies are not closed boxes irrelevant to the situation of women. If we look inside these
‘black boxes,’ we find certain practices, social constructs of skills, policies, and behaviours that affect the position
of women (Nelson 1995, p. 21).
xi
Those indications have been adjusted for the purposes of this chapter on the basis of: Author 2003. In the original
version, the index w is the discriminated group, and the index m – the favoured group.
xii
It should also be noted that, on the consumer market, subjective discrimination is a natural phenomenon. Each
person, due to the limited number of resources, must allocate them to specific, most preferred needs. Thus, they
reject – discriminate against - less desirable needs and goals in favour of those that will satisfy their requirements
to a greater extent, e.g. a thirsty man will drink the obtained water first, and only then will he water the flowers.
This means that at a given moment he rejects watering flowers in favour of satisfying his thirst (Sielska 2017, p.
48).
