A note on the gender wage gap among managerial positions using a counterfactual decomposition approach: sticky floor or glass ceiling?
Post on 16-Mar-2017
This article was downloaded by: [University of California Santa Cruz]On: 14 November 2014, At: 21:25Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK
Applied Economics LettersPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/rael20
A note on the gender wage gap among managerialpositions using a counterfactual decompositionapproach: sticky floor or glass ceiling?Marco Biagetti a & Sergio Scicchitano a ba Department of Development and Cohesion Policies , Ministry of Economic Development ,Via Sicilia 162c, Rome, 00168, Italyb Department of Public Economics , University of Rome , Via del Castro Laurenziano n. 9,Rome, 00161, ItalyPublished online: 24 Jan 2011.
To cite this article: Marco Biagetti & Sergio Scicchitano (2011) A note on the gender wage gap among managerial positionsusing a counterfactual decomposition approach: sticky floor or glass ceiling?, Applied Economics Letters, 18:10, 939-943, DOI:10.1080/13504851.2010.518944
To link to this article: http://dx.doi.org/10.1080/13504851.2010.518944
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the Content) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions
A note on the gender wage gap
among managerial positions using
a counterfactual decomposition
approach: sticky floor or glass
Marco Biagettia and Sergio Scicchitanoa,b,*
aDepartment of Development and Cohesion Policies, Ministry of EconomicDevelopment, Via Sicilia 162c, Rome, 00168 ItalybDepartment of Public Economics, University of Rome, Via del CastroLaurenziano n. 9, Rome, 00161 Italy
In this article, we apply a counterfactual decomposition approach usingQuantile Regression (QR) to the wage distribution of managerial workforcein Italy. We find evidence of both significant sticky floor and glass ceilingeffects for the Gender Wage Gap (GWG). Furthermore, the U-shapedfigure of the pay gap is mostly due to the difference in rewards that thetwo genders receive for their characteristics, whose relative incidence is alsocontinuously increasing as we move to upper quantiles.
In this article, we apply a counterfactual decomposition
approach using Quantile Regression (QR) to the wage
distribution of the managerial workforce in Italy. The
aim is twofold: firstly, to understand whether in the
Gender Wage Gap (GWG) there exists a sticky floor
or a glass ceiling effect; secondly, to investigate whether
that GWG may be attributed more to difference in
labour market characteristics between the genders or
to difference in rewards that the two sexes receive for
their characteristics in the managerial labour market.Despite the fact that generalGWGhas become awide-
spread research topic in the empirical economic literature,
only a few papers analyse the wage differentials across
managerial workers.1 Furthermore, much lesser regard is
devoted to investigate the existence of sticky floor (higher
GWG at the bottom of the wage distribution) or glass
ceiling (higher GWG at the top of the wage distribution)
effects using QR. Yurtoglu and Zulehner (2009) find that
the estimated pay gaps for top executive officers of pub-
licly listed US firms are larger at the bottom than at the
top of the distribution, that is, they find evidence of a
However, to the best of our knowledge, despite the
very large use of counterfactual decomposition using
QR done by the applied research inGWGwhen study-
ing the sticky floor and glass ceiling effects along the
*Corresponding author. E-mail: firstname.lastname@example.org See Bertrand and Hallock (2001) and Jurajda and Paligorova (2009).2 Smith et al. (2010), bymeans of a different procedure, demonstrate that inDenmark there is still a considerable glass ceiling butalso evidence of sticky floors.
Applied Economics Letters ISSN 13504851 print/ISSN 14664291 online # 2011 Taylor & Francishttp://www.informaworld.com
Applied Economics Letters, 2011, 18, 939943
wage distribution,3 there is no empirical survey apply-
ing this approach to supervisory works. In particular,
such method could be particularly useful in this con-
text, because it decomposes the difference between the
supervisor male and female log wage distributions into
one component that is based on the difference in coef-
ficients and another based on the difference in char-
acteristics. Hence, different values of the GWG at
each of the estimated points along the log wage dis-
tribution could be better explained.In this article, we fill this gap of economic literature,
using the last European dataset, the Community
Statistics on Income and Living Conditions survey
(EU-SILC).We find that along the whole wage distribu-
tion of the Italian managerial labour market, there are
both significant sticky floor and glass ceiling effects for
the GWG. Furthermore, the U-shaped figure of the pay
gap is mostly due to the difference in rewards that the
two genders receive for their characteristics, whereas the
characteristic effect is monotonically decreasing along
the whole wage distribution.This article is organized as follows. In Section II
we quickly describe the econometric methodology
adopted. Section III deals with the data used. Section
IV presents the results obtained from splitting the
differences in distribution using QR. In the last section
we conclude with a possible explanation.
II. Econometric Specification
The use of Ordinary Least Squares (OLS) provides
estimates for the conditional mean only, whereas we
are interested in analysing wage gender differentials
across the whole wage distribution for Italian man-
agers. A useful tool to achieve this purpose is the QR
method (Koenker and Bassett, 1978), where the thquantile of a variable conditional on some covariates
can be estimated and the effect of those covariates at
the bottom, at the median or at the top of the distribu-
tion can be accounted for.Let yi be the dependent variable and xi the vector of
the chosen covariates. The relation is given by
yi xib ei with F 1e jX 0 1
where F 1e jX represents the th quantile of e con-ditional on x. The estimated th quantile is obtainedby solving the following equation:
q; xf; bf q; xm; bm q; xf; bf q; xf; bm q; xf; bm ; xm; bm
The right-hand term in the first set of bracketsconstitutes the difference in coefficients (i.e. thecounterfactual distribution), whereas that in the sec-ond set of brackets is the effect of differencescharacteristics.
We used the latest (2007) wave of the EU-SILC data-base, available since March 2009. Our analysis wasperformed on the log hourly gross wage of Italianindividuals between 25 and 65 years of age whodeclared to be employed in a managerial position.EU-SILC identifies that position with a supervisoryrole where supervisory responsibility includes formalresponsibility for coordinating a group of otheremployees (other than apprentices). Students, peopleserving in the Armed Forces and self-employed werealso excluded. After doing so 3064 individualsremained, 1025 females and 2039 males. The covari-ates considered were (i) citizenship with three cate-gories: citizenship of the same country as that ofresidence (the base category), of any other EU countryand of any other country; (ii) marital status (threecategories: single individuals the base category union without legal basis, union with legal basis);(iii) limitation of activity because of health problemswhose categories are strongly limited (base category),limited, not limited; (iv) level of education with threecategories: the base is for pre-primary, primary andlower secondary school; the second for upper second-ary and post-secondary nontertiary education; the lastonly includes people with at least tertiary education;(v) working experience and its squared; (vi) whether ornot the individual works part-time (of course twocategories); (vii) type of contract (temporary or per-manent); (viii) the size of the unit where a worker isemployed, split into three categories (1119, 2049and more than 50 employees) other than the base (upto 10 employees) and (ix) sector (13 categories). Thesummary statistics for the sample of men and womenused in this article are reported in Table 1.
The results from the counterfactual decomposition aredisplayed in Table 2.We also report the OLS estimatesand the observed wage gap for comparison. All the
coefficients are significant at 1%. Figure 1 plots thedecomposition results at each of the 99%. We findthat women earn less than men, also after control formany personal, human capital and labour marketcharacteristics, along the whole wage distribution.The observed GWG, as reported in the first row ofthe Table 2, is U-shaped and shows the lowest value atthe median ( = .50) quantile.By taking into account the effects of all covariates,
the counterfactual analysis confirms a more linearU-shaped pattern, thus showing both sticky floor defined as the difference between 10th and 50th quan-tiles and glass ceiling computed with the differencebetween 90th and 50th quantiles effects. Moreover,the pay gap at the two extreme 10th and 90th quantilesis now higher. By decomposing the effect of its determi-nants, the GWG is mainly due to the difference inrewards along the entire distribution, whose relativeincidence is also monotonically increasing as we moveto upper quantiles. Such component, then, evidences aJ-shaped pattern, that is, a glass ceiling effect muchmore pronounced than the sticky floor. Conversely,the characteristic effect is continuously decreasingover the whole distribution.
Our counterfactual distribution of wages among Italianworkers in a supervisory position demonstrates that theGWG exhibits a U-shaped pattern, that is, it showsboth significant sticky floor and glass ceiling effects.The decomposition results for a selected grid of quan-tiles indicate that the contribution of differences inrewards has been quantitatively much more importantthan that of different covariates at each of the estimatedpoints along the log wage distribution. Furthermore,
Table 1. Summary statistics for sample
Variable Mean SD Mean SD
Log gross hourly wage 2.39 0.45 2.66 0.44Citizenship 2.00 0.12 2.01 0.11Marital status 1.24 0.93 1.44 0.86Limitation because of health
problems2.81 0.43 2.88 0.37
Education attained 1.16 0.66 1.01 0.68Work experience 18.02 9.79 20.05 10.07Part time 0.15 0.35 0.18 0.13Permanent 0.91 0.28 0.95 0.22Firm size 1.68 1.26 1.84 1.23Sectors 7.28 3.49 5.40 3.49
A note on the gender wage gap among managerial positions 941
although the effect of the difference in rewards is
J-shaped, with a much more pronounced glass ceiling
effect than that of sticky floor, its relative incidence is
also continuously increasing along the distribution.We can now briefly speculate on the possible expla-
nations of such findings. On the one hand, it is well
known that in Italy the workfamily composite recon-
ciliation index is quite low, comparedwith that of many
other industrial countries (OECD, 2001). Moreover,
there is also evidence that countries with less generous
workfamily policies have a wider wage gap at the
bottom of the wage distribution and a lower gap at
the top, suggesting that the positive effect of family-
friendly policies dominates at the bottom of the distri-
bution (Arulampalam et al., 2007). Thus, following
Yurtoglu and Zulehner (2009), the lack of an adequate
workfamily reconciliation package may also induce
managerial women to prefer family to career than
compared with men, especially at the bottom of the
wage distribution. On the other hand, it is also well
documented that idiosyncratic, sociological and cul-
tural reasons may have a major role in discriminating
against women, particularly for the high hierarchical
levels, because the supervisory positions are tradition-
ally considered as mens prerogative (OECD, 2002). In
this framework, as we move up the wage distribution,
although other reasons may be also called, gender
stereotypes may be much likely to considerably influ-
ence the increasing incidence of the coefficient effect,
especially at the top of the wage distribution.
We thankMarcoMarini for invaluable suggestions and
comments. The views expressed in this article are those
of the authors and, in particular, do not necessarily
Table 2. Decompositions of changes in gender wage gap using quantile regression
OLS = .10 = .20 = .30 = .40 = .50 = .60 = .70 = .80 = .90
Raw 0.269 0.303 0.208 0.216 0.223 0.201 0.254 0.251 0.288 0.288(0.017) (0.048) (0.004) (0.037) (0.0112) (0.032) (0.027) (0.021) (0.022) (0.016)
0.273 0.323 0.239 0.212 0.207 0.214 0.230 0.256 0.294 0.331
(0.017) (0.006) (0.005) (0.005) (0.006) (0.007) (0.009) (0.009) (0.012) (0.024)Characteristics 0.071 0.158 0.096 0.072 0.062 0.057 0.051 0.049 0.048 0.048
(0.013) (0.020) (0.016) (0.015) (0.014) (0.014) (0.014) (0.015) (0.017) (0.023)26% 49% 40% 34% 30% 26% 22% 19% 16% 15%
Coefficients 0.202 0.165 0.143 0.140 0.145 0.158 0.179 0.207 0.246 0.282(0.015) (0.032) (0.022) (0.019) (0.015) (0.013) (0.012) (0.011) (0.011) (0.014)74% 51% 60% 66% 70% 74% 78% 81% 84% 85%
Note: Bootstrap SEs with 100 replications are given in parentheses. All coefficients are significant at 1%. Percentages are in italics.
Total differential Characteristics Coefficients Raw
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Fig. 1. Decomposition of differences in distribution using quantile regression
Note: Results obtained by applying decomposition at each of the 99%. Bootstrap SE with 100 replications.
942 M. Biagetti and S. Scicchitano
reflect those of theMinistry of EconomicDevelopment.
The usual disclaimer applies.
Arulampalam, W., Booth, A. L. and Bryan, M. L. (2007) Isthere a glass ceiling over Europe? Exploring the genderpay gap across the wage distribution, Industrial andLabor Relations Review, 60, 16386.
Bertrand, M. and Hallock, K. (2001) The gender gap in topcorporate jobs, Industrial and Labor Relations Review,55, 121.
Jurajda, S. and Paligorova, T. (2009) Czech female man-agers and their wages, Labour Economics, 16, 34251.
Koenker, R. and Bassett, G. (1978) Regression quantiles,Econometrica, 46, 3350.
Melly, B. (2005) Decomposition of differences in distributionusing quantile regression,Labour Economics, 12, 57790.
OECD (2001) Employment Outook, OECD, Paris.OECD (2002) Employment Outook, OECD, Paris.Smith, N., Smith, V. and Verner, M. (2010) The gender
pay gap in top corporate jobs in Denmark: glassceilings, sticky floors or both?, IZA DiscussionPapers 4848, Institute for the Study of Labor (IZA),Germany.
Wahlberg, R. (2010) The gender wage gap across thewage distribution in the private and publicsectors in Sweden, Applied Economic Letters,DOI: 10.1080/13504850903035915.
Yurtoglu, B. and Zulehner, C. (2009) Sticky floors and glassceilings in top corporate jobs. Available at http://ssrn.com/abstract=1470860 (accessed 9 September2009).
A note on the gender wage gap among managerial positions 943