POPULATION AND SOCIAL CONDITIONS 12/2005 Hans-Joachim MITTAG Contents Differences in hourly earnings between economic activities are less pronounced… [600589]

Statistics
in focus

POPULATION AND SOCIAL CONDITIONS
12/2005
Hans-Joachim MITTAG
Contents

Differences in hourly earnings between economic activities are
less pronounced than between
countries….. …………………….1
Earnings in “Services” tend to
be above those in “Industry”
……………………………………..5

Number of hours paid per
month tends to be higher in the
NMS …………………………………….. 7
A first glance at the gender pay
gap………………………………………. 9

Gross Earnings in Europe
Main results of the
Structure of Earnings Survey 2002
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The European Structure of Earnings Surv ey (SES) provides detailed information on
the level and structure of rem uneration of employees, their individual characteristics
and the enterprise or local unit to which they belong. It is a 4-yearly survey conducted
under Council Regulation 530/1999 and Commission Regulation 1916/2000. The SES
outcome represents an uniquely rich data source on gross earnings in Europe which is
increasingly important for evidence-based policy making, in particular for monitoring
economic growth and social cohesion. Furthermore, the SES data are indispensable
for employers and employees as regards the demand and supply of labour.
This Statistics in Focus opens a series dealing with re sults for the recent SES carried
out for the reference year 2002. The SES 2002 micro data are available for
approximately 7.9 millions employees in enterprises with at least 10 employees in
“Industry and services” (sections C to K of the economic activity classification scheme
NACE 1.1). By April 2005 Eurostat had receiv ed data from 28 countrie s: 24 out of the
current 25 Member States (all except Ma lta), the Acceding Countries Bulgaria and
Romania as well as from Iceland and Norway. The latter belong to the European
Economic Area (EEA). The data were collected by the national statistical offices in
2003 and processed during 2004. The only ex ception are the German data which refer
to 2001 and were processed in 2003. The averages referring to EU-25, EU-15 and the
NMS (today’s EU, “old” EU and new Member States, respectively) as well as to the
euro-zone EZ (EU-15 except Denmark, Sweden and the United Kingdom) are
weighted averages including only those countries for which national data are available.
More information on coverage of the survey, methods, definitions or abbreviations of
countries and NACE sections is presented in the Methodological Notes at the end.
This publication aims at taking a first glan ce at the SES 2002 results available in
Eurostat’s freely accessible database Ne w Cronos. It presents selected tables and
graphs with core results on gross hourly, monthly and annual earnings as well as on
hours paid. A multitude of additional graphs are offered through an interactive
visualisation tool1 which provides immediate access to a graphical display of user-
defined views on the data, including earni ngs data expressed in Purchasing Power
Standards (PPS).2
Differences in hourly earnings between economic activities
are less pronounced than between countries
Figure 1 presents bar charts for average gross hourly earnings related to employees in “Industry and services” (NACE aggregate C-K) and in the economic activities “Hotels
and restaurants” (NACE section H) and “Financial intermediation” (section J) where
particularly low and high earnings, respectively, are observed. In each graph, the
countries are ordered by decreasing numerical values.3
The graph for “Industry and services” shows t hat average gross hourly earnings in the
NMS (2.83 €) and the EU-15 (14.18 €) diffe r considerably, ranging from 1.52 € in
Latvia and 1.77 € in Lithuania to 19.75 € in Denmark and 22.41 € in Norway. 4 The
lowest earnings are observed in Bulgaria (0.80 €) and Romania (1.04 €). The graph
shows furthermore that average gross hourly earnings for every individual NMS,
except Cyprus, are plainly below those observed in any EU-15 country (see also
Figure 2a). In C-K, Cyprus ranks above Po rtugal, Greece and Spain. Slovenia ranks
second-best among the NMS, not only for C- K but also for any of the individual
economic activities.

1 The tool is accessible via http://forum.europa.eu.int/irc/dsis/wages/info/data/index.htm . This
address leads to a virtual library containing an item “Gross earnings in Europe 2002”.

2 Due to space restrictions, th is publication predominantly deals with earnings data expressed in
euro. PPS represent an artificial currency unit which reflects differences in national price levels
that are not taken into account by exchange rates.
3 The following Table 1 (page 3) covers all 28 co untries participating in the SES 2002. As the
Islandic data on earnings only refer to the NACE se ctions D, F and G, the NACE aggregates C-F,
G-K and C-K are not available for Iceland. This expl ains why Iceland is neither included in Tables
2-4 nor in the graphs of this publication.

4 The corresponding PPS values are 3.02 and 3.60 for Latvia and Lithuania and 15.34 and 14.95
for Denmark and Norway, respectively. A PPS-bas ed comparison reduces the differences in
earnings between the EU-15 and the NMS. 

Manuscript completed on: 15.09.2005
Data extracted on: 27.06.2005
ISSN 1024-4352 Catalogue number: KS-NK-05-012-EN-N
© European Communities, 2005

2 Statistics in focus — Population and social conditions — 12/2005 ________________________________________
"

The full numerical information on gross hourly earnings in
Europe is given in Table 1. The table contains data for all 9
individual NACE sections C to K as well as for the 3 NACE
aggregates “Industry” (C – F), “Services” (G – K) and “Industry
and services” (C – K). The rows containing figures for the
NMS are highlighted by using a shadowed background. The
figures for the two Candidate Countries and the EEA countries
are displayed separately. In each row of Table 1, the
maximum and minimum values are in bold. The distribution of
extreme earnings shows very similar patterns in European
countries. The lowest earnings are in all countries, except the Czech
Republic and Cyprus, observed in NACE section H, the
highest usually in NACE section J (exceptions for Belgium,
Denmark, the Netherlands and Austria, see also Figure 3a).
The second-lowest earnings are predominantly linked to
“Wholesale and retail trade, repair of motor vehicles, personal
and household goods” (section G), the second-highest usually
either to “Electricity, gas and water supply” (section E) or to
“Mining and quarrying” (section C). Figure 1: Gross hourly earnings for 3 economic activities
(countries ranked by descending order)
a) Industry and services (NACE aggregate C – K)
b) Financial intermediation (NACE section J)
c) Hotels and restaurants ( NACE section H)

—————————————————————— 12/2005 — Populat ion and social conditions — Statistics in focus 3 "#
Table 1: Gross hourly earnings, in euro

Figures in bold / bold Italic: maximum / mi nimum (per row without missing data)
NACE or country codes in Italic: The corresponding columns and rows are visualized in Figure 1 – 2
Data with shadowed background refer to the NMS.
Source: Eurostat, SES 2002.

While Figure 1 visualizes selected columns of Table 1, the
following Figure 2 presents another view on the same data by
graphically displaying selected rows . Figure 2a refers to a
comparison of gross hourly earnings in the EU-15 and NMS.
The ratio “Hourly earnings in the EU-15 / hourly earnings in
the NMS” which results by dividing the corresponding rows in
Table 1 varies between economic activities from
approximately 3.6 in NACE sect ion C to 5.4 for section D1.
Figure 2b illustrates that the le vel of this earnings ratio may
even be much higher when comparing individual countries.
When comparing gross hourly earnings for Denmark and
Latvia (EU Member States with particularly high and low levels
of earnings, respectively), it va ries for example from 7.0 in
NACE section J to 16.2 in section H. 2


1 For a PPS-based earnings comparison, th is ratio shrinks to 2.0 for section C and to 2.9 for section D.
2 For a PPS-based earnings comparison, the ratio reduces to 2.7 for section J and to 6.3 for section H.
Economic activity
C D E F G H I J K C-F G- K C-K
EU-25 10.78 12.42 13. 39 11.12 11.04 9.01 11.92 19.17 14.41 12.20 12.85 12.56
EU-15 15.70 14.36 17. 47 12.53 12.23 9.50 14.14 20.49 15.64 14.14 14.21 14.18
NMS 4.34 2.64 3.47 2.50 2.47 2.32 2.87 5.08 3.13 2.75 2.93 2.83
EZ 13.68 13.46 16. 78 11.10 11.37 8.86 12.75 17.85 13.31 13.15 12.68 12.90
BE 13.80 14.18 19.69 12.51 12.43 9.26 12.98 17.68 14.76 14.01 13.55 13.75
CZ 3.20 2.65 3.06 2.57 2.46 2.91 3.00 4.89 2.94 2.68 3.00 2.82
DK 27.90 21.02 23.78 21.19 16.52 16.07 21.87 24.27 21.05 21.18 18.95 19.76
DE 15.90 16.60 18. 79 13.41 13.49 9.53 14.17 19.00 14.78 16.18 14.51 15.40
EE 2.88 2.06 2.40 2.09 1.95 1.33 2.27 4.33 2.26 2.12 2.14 2.13
EL 9.51 6.70 13.63 7.21 5.91 5.48 9.16 10.44 6.83 7.38 7.06 7.19
ES 10.96 8.63 12.71 7.15 7.87 6.19 9.56 14.53 7.46 8.28 8.43 8.36
FR 15.27 14.62 17. 33 12.25 12.48 10.91 14.11 18.61 16.44 14.42 14.40 14.41
IE 18.02 16.36 23. 54 17.06 12.33 10.76 17.18 23.02 16.99 16.77 15.76 16.20
IT 9.51 9.93 12.84 9.45 9.59 8.02 10.80 17.14 10.10 9.97 10.85 10.38
CY 9.52 7.44 10.80 9.15 6.80 6.96 11.23 12.77 9.83 8.57 10.30 9.67
LV 1.80 1.48 2.30 1.40 1.13 0.99 1.80 3.49 1.68 1.53 1.51 1.52
LT 2.20 1.70 2.48 1.64 1.62 1.13 1.81 3.29 1.85 1.76 1.78 1.77
LU 15.91 15.34 23. 13 13.13 12.91 10.26 17.47 24.09 14.34 14.44 16.38 15.88
HU 2.78 2.45 3.03 1.96 2.12 1.82 2.72 4.67 2.80 2.44 2.60 2.51
NL 23.26 15.03 20.83 14.49 11.96 11.43 14.64 19.00 15.00 15.06 13.86 14.22
AT 13.15 12.67 16.51 11.60 10.26 7.46 12.13 16.13 12.95 12.54 11.59 12.01
PL 5.00 2.85 3.88 2.75 2.75 2.52 3.56 5.08 3.44 3.06 3.33 3.18
PT 4.87 4.37 10.06 4.45 5.07 3.73 7.38 10.72 6.64 4.48 6.12 5.26
SI 7.26 4.83 6.77 4.33 4.79 3.93 5.40 8.44 6.26 4.85 5.44 5.10
SK 2.45 1.94 2.84 1.73 2.42 1.34 1.86 4.29 2.38 1.97 2.18 2.08
FI 13.41 14.07 15. 31 13.06 12.72 10.89 13.27 16.32 14.97 13.94 13.65 13.80
SE 15.49 14.69 16. 72 14.65 14.39 11.16 14.09 20.21 16.39 14.74 15.20 15.00
UK 24.10 17.99 21. 43 17.50 13.61 10.14 17.66 26.76 20.42 18.06 17.46 17.64
BG 1.30 0.73 1.29 0.71 0.56 0.53 1.01 1.59 0.71 0.80 0.81 0.80
RO 1.68 0.88 1.47 0.86 0.88 0.75 1.34 2.57 1.03 0.98 1.16 1.04
IS : 12.92 : 14.01 13.48 : : : : : : :
NO 34.95 21.66 23.23 21.20 19.60 16.05 21.56 26.81 24.92 22.41 21.53 21.83

4 Statistics in focus — Population and social conditions — 12/2005 ________________________________________
"

A more comprehensive presentatio n of the variability of gross
hourly earnings is shown in Figure 3 which uses boxplots1
instead of bar charts. Figure 3a vi sualizes for all countries the
dispersion of gross hourly earnings between economic
activities, i.e. it displays the information contained in the rows
of Table 1 referring to all individual countries (except Iceland).
On the one hand, the graph shows again that gross hourly
earnings differs considerably as regards its mean level. The
highest level of earnings withi n the set of NMS, except
Cyprus, belongs to Slovenia. The median for Slovenia is very
close to that of Portugal (see the highlighted boxplot referring
to Slovenia). For Cyprus, the medi an lies slightly above that of
Spain and slightly below that of Italy. On the other hand, the
graph shows that the distribut ion of earnings also differs
considerably from country to country. The medians for
Belgium (13.80 €) and for Finland (13.41 €) are, for example,
very close but the variability of earnings between different economic activities, represented by the total length of the
boxplot, is higher in Belgium.
Figure 3b displays for all NACE categories the variability of
gross hourly earnings between countries, i. e. it summarizes
the information contained in the columns of Table 1. The
variability is particularly high for “Mining and quarrying” (NACE
section C) and low for “Hotels and restaurants” (section H).
The highest median is connected with “Financial
intermediation” (section J) as the highlighted boxplot shows. A
comparative glance at both part s of Figure 3 shows that the
overall picture of Figure 3b is more homogeneous, i.e. the
influence of the country on earn ings tends to be stronger than
that of the economic activity. The boxplots in Figure 3b for the
economic activities H and J are, for example, much more
similar than those in Figure 3a belonging to Bulgaria and
Norway. a) NMS (left-hand bars) and EU-15 (right-hand bars)
b) Latvia (left-hand bars) and Denmark (right-hand bars) Figure 2: Gross hourly earnings for 2 countries or country sets, in euro


1 A boxplot summarizes the information contained in a data set by displaying 5 characteristics of the set. It is defined by a box of length
x0.75 – x 0.25 (difference between upper and lower quartile, the so-called in terquartile range, defining the “inner 50%” of the data ordered by
increasing size), the median x 0.5 (marked inside the box) and the extreme values x min and x max. The latter are connected with the box via
lines. The total length of a boxplot represents the range of the data set.

—————————————————————— 12/2005 — Populat ion and social conditions — Statistics in focus 5 "#
Figure 3: Dispersion of gross hourly earnings, in euro
b) Comparison by economic activity (highlighted: financial intermediation)

Earnings in “Services” tend to be above those in “Industry”
It is of interest to investigate whether the main findings related
to gross hourly earnings also apply to gross monthly and
annual earnings for which the ranking of countries might be
different, due to different working hours or differences in
annual bonuses. Furthermore, it is worth comparing earnings
in “Industry” (C-F) and “Services” (G-K)“ where the
composition of annual earnings is not necessarily identical.
Table 2 displays average gross hourly, monthly and annual
earnings for the aggregates “Industry” and “Services” as well
as for “Industry and services” (C-K). A comparison of earnings
for C-F and G-K shows that average gross earnings in
“Services” tend to be above those observed for “Industry”. In
Table 2 earnings in “Services” are highlighted if they exceed
the corresponding values observed in “Industry” by at least
10%. By far the highest differences are reported from Portugal
where, for example, annual earnings in “Services” amount to
137.6% of annual earnings in “I ndustry”. For the country sets
EU-15 and EU-25 the same perc entages are 102.6 and 106.7,
respectively. The lowest level for gross annual earnings in
“Services”, expressed as a percentage of gross annual earnings in “Industry”, is 92.7 for Germany and 93.3 for
Ireland.
Gross earnings in “Services” or in “Industry” crucially depend
on the number of employees workin g in the individual sections
and thus defining the composit ion of these NACE aggregates.
The aggregate “Services” includes for example “Hotels and
restaurants” (section H) with low average earnings as well as
“Financial intermediation” (section J) with high average
earnings. It is obvious that a high number of employees
working in section H tends to decrease the average for the
service sector whereas a high number of employees attributed
to section J has the opposite e ffect. In Luxembourg, 21.9 % of
employees working in “Services” are linked to section J and
only 6.2 % to section H, i. e. the ratio of the size of these
sections is 3.5 to 1. This partly explains the high
Luxembourgish figure for gross annual earnings in “Services”.
In Ireland, the shares for section J and section H in “Services”
are 19.6 % and 14.2 %, respectively, corresponding to a ratio
of only 1.4 to1. a) Country-by-country comparison (highlighted: Slovenia)
Maximum: NACE section J (exceptions: section C for DK, NL and NO, section E for BE, EL, IE and AT),
Minimum: NACE section H (except ions: section G for CZ and CY)
Maximum: value for NO (exceptions: DK for NACE secti ons E, H and I), minimum: value for BG (no exceptions)

6 Statistics in focus — Population and social conditions — 12/2005 ________________________________________
"

A closer look at Table 2 shows that the ranking of earnings
between countries is not identical for hourly earnings, monthly
earnings and annual earnings, respectively, but the overall picture
does not alter a lot. Figure 4 illus trates this by means of the
NACE aggregate “Industry and serv ices”. As explained in more
detail in the following, the observed changes of rank positions from Figure 4a to Figure 4b are mainly due to differences in
hours paid in the reference month whereas the changes from
Figure 4b to Figure 4c are mainly caused by differences in
payments which do not not occur in each pay period (13th
month payment, non-regular allowances or holiday bonuses). Table 2: Earnings, in euro (NACE aggregates C-F, G-K and C-K)

Figures in bold: Hourly, monthly and annual earnings, respectively , in “Services” exceed those in “Industry” by more than 10 %.
NACE codes in Italic: The corresponding rows are visualized in Figure 4.
Source: Eurostat, SES 2002.
Gross hourly
earnings Gross earnings
in the reference
month Gross annual
earnings

C-F G- K C-K C-F G- K C-K C-F G- K C-K
EU-25 12.20 12.85 12.56 2075 2172 2129 27018 28881 28024
EU-15 14.14 14.21 14.18 2399 2398 2399 31218 32045 31675
NMS 2.75 2.93 2.83 498 526 511 6508 6941 6710
EZ 13.15 12.68 12.90 2211 2139 2173 29613 29365 29485
BE 14.01 13.55 13.75 2506 2390 2441 29823 31378 30694
CZ 2.68 3.00 2.82 457 518 483 6861 7680 7212
DK 21.18 18.95 19.76 3522 3093 3250 41547 41884 41736
DE 16.18 14.51 15.40 2714 2503 2616 35842 33211 34622
EE 2.12 2.14 2.13 393 397 395 4732 5101 4934
EL 7.38 7.06 7.19 1345 1210 1264 19444 18263 18751
ES 8.28 8.43 8.36 1518 1528 1524 20907 21194 21063
FR 14.42 14.40 14.41 2184 2219 2204 28778 29437 29139
IE 16.77 15.76 16.20 2708 2445 2559 34188 31898 32912
IT 9.97 10.85 10.38 1829 1938 1880 24470 27354 25808
CY 8.57 10.30 9.67 1484 1770 1666 19940 23681 22316
LV 1.53 1.51 1.52 284 279 281 3580 3641 3616
LT 1.76 1.78 1.77 323 327 325 3993 4209 4097
LU 14.44 16.38 15.88 2610 2878 2809 33218 39918 38103
HU 2.44 2.60 2.51 454 481 467 5685 6165 5906
NL 15.06 13.86 14.22 2483 2326 2372 33990 33541 33683
AT 12.54 11.59 12.01 2268 2078 2162 33028 31941 32434
PL 3.06 3.33 3.18 573 608 589 6879 7290 7065
PT 4.48 6.12 5.26 762 1032 891 11563 15911 13609
SI 4.85 5.44 5.10 863 968 908 10661 12102 11275
SK 1.97 2.18 2.08 336 378 359 5338 6022 5708
FI 13.94 13.65 13.80 2341 2250 2297 30968 30963 30965
SE 14.74 15.20 15.00 2552 2620 2590 30628 33248 32056
UK 18.06 17.46 17.64 3167 2951 3018 38668 38477 38538
BG 0.80 0.81 0.80 147 149 147 1867 1914 1884
RO 0.98 1.16 1.04 183 211 192 2176 2647 2321
NO 22.41 21.53 21.83 3733 3545 3611 43974 41676 42475

________________________________________ 12/2005 — Population and social conditions — Statistics in focus 7 "#

+1 +1 +1 -3 +3 -3 +1 -1 ← rank position changes (compared to part a)

+3 +4 -3 -3 -1 +1 -1 +1 -1 +1 -1 ← rank position changes (compared to b)
Number of hours paid per month tends to be higher in the NMS
Table 3 presents the numerical information on hours paid in
the reference month for “Industry and services” and, in
addition, separately for “Industry” and “Services”. Furthermore,
Table 3 displays data on annual bonuses and, to provide a
more complete picture of working conditions in Europe, on
annual days of paid holiday leave. The data on annual
bonuses contribute to explaining the change of rank positions from Figure 4b to Figure 4c. In Sweden, for example, the non-
regular payments in “Industry and services” are remarkably
low (only 1.4 % of total annual earnings) whereas the
corresponding values amount in the Netherlands to 9.5 %, in
Ireland to 12.3 % and in Austria to 14.7 %. Sweden’s rank
position in Figure 4c hence declines whereas the rank of
Austria considerably improves. Figure 4: Gross earnings, NACE aggregate C-K, in euro
(countries ranked by descending order)
a) Hourly earnings
b) Earnings in the reference month
c) Annual earnings

8 Statistics in focus — Population and social conditions — 12/2005 ________________________________________
"
Table 3: Paid time and annual bonuses, NACE aggregates C-F, G-K and C-K
Figures in bold / bold Italic: maximum / minimum per column
NACE code in Italic: The data in this column are visualized in Figure 5.
Source: Eurostat, SES 2002
Hours paid in the
reference month Annual bonuses (in % of
total annual earnings) Annual days of paid
holiday leave
C-F G- K C-K C-F G- K C-K C-F G- K C- K
EU-25 174 173 173 8.5 9.5 9. 0 26.2 24.2 25.1
EU-15 172 171 172 8.6 9.6 9. 1 26.6 24.3 25.4
NMS 181 181 181 6.8 6.9 6.8 23.8 23.5 23.7
EZ 171 171 171 10.0 10.4 10. 2 27.3 25.8 26.5
BE 179 179 179 10.5 11.5 11. 1 19.8 19.3 19.5
CZ 171 174 172 18.0 16.8 17.5 22.3 24.0 23.1
DK 166 163 164 2.3 2.1 2. 2 25.1 24.8 24.9
DE 169 174 171 9.1 8.6 8. 9 29.2 28.3 28.8
EE 186 185 185 3.0 4.4 3.8 20.6 17.3 18.8
EL 181 172 176 15.4 16.0 15.7 22.7 21.5 22.0
ES 184 183 183 15.9 18.2 17.2 23.7 22.1 22.8
FR 152 154 153 12.1 12.4 12.3 31.5 30.3 30.9
IE 162 155 158 4.3 4.2 4. 3 21.7 21.1 21.4
IT 184 180 182 6.1 6.2 6. 1 26.5 26.0 26.3
CY 173 172 173 10.5 8.4 9.1 21.2 23.0 22.4
LV 185 185 185 4.5 6.2 5.5 15.6 14.3 14.8
LT 183 184 184 1.5 3.1 2.3 16.2 13.6 15.0
LU 181 176 178 6.7 10.7 9. 8 27.7 27.2 27.3
HU 187 185 186 2.8 2.5 2.7 26.7 26.4 26.6
NL 165 168 167 9.8 9.3 9. 5 24.6 20.6 21.9
AT 181 180 180 14.8 14.6 14. 7 25.5 24.0 24.7
PL 188 185 186 0.3 0.8 0.5 25.1 25.0 25.0
PT 170 170 170 14.3 16.1 15.3 21.2 20.7 21.0
SI 179 179 179 11.2 11.4 11.3 23.9 22.9 23.5
SK 173 174 174 14.3 14.8 14.6 25.5 24.4 24.9
FI 168 165 167 7.2 5.7 6. 5 23.2 23.1 23.2
SE 174 173 173 1.2 1.6 1.4 : : :
UK 178 174 175 4.4 9.0 7. 5 23.1 20.2 21.1
BG 184 184 184 3.2 4.7 3. 8 25.3 23.9 24.7
RO 188 187 188 6.0 7.8 6.6 25.1 23.5 24.6
NO 166 164 165 1.1 2.1 1. 7 23.5 20.3 21.4

Figure 5 visualizes the data in Table 3 referring to hours paid
in NACE sections C-K. The graph shows that the number of
hours paid in the reference month for “Industry and services”
varies considerably across countries. The range goes from
153 in France and 158 in Ireland to 186 in Hungary or Poland
and 188 in Bulgaria. In particular, Figure 5 provides an
explanation why for France and Irel and, the countries with the
lowest figures for monthly hours paid, the rank positions in
Figure 4b have declined by 3 rank positions compared to Figure 4a. Contrary to the situation in Figure 4a, Belgium
ranks in Figure 4b not only bef ore France, but also before
Finland and the Netherlands and this is coherent with the
ranking order displayed in Figur e 5. The number of monthly
hours paid in Belgium (179) is above the EU-25 average (173)
and much higher than in Finland and the Netherlands (both
167). The average hours paid in NACE aggregate C-K
amounts to 172 in the EU-15 and to 181 in the NMS.

Figure 5: Hours paid in the reference month, NACE aggregate C – K

________________________________________ 12/2005 — Population and social conditions — Statistics in focus 9 "#
A first glance at the gender pay gap
European employment policy is committed to promoting equal
opportunities in work for men and women. The SES 2002 data
combine detailed information on local units as well as on
personal characteristics of employees and hence represent an
empirical basis for monitoring political strategies aiming at
eliminating gender pay gaps.
Table 4 presents a breakdown of hourly earnings for the
NACE aggregates C-F, G-K and C-K by sex. The average hourly earnings for woman are in all three NACE categories
uniformly below male’s earnings. For the gender pay gap,
expressed as women’s earnings in percentages of men’s
earnings, the lowest percentages observed in “Industry” are
63.9 (Cyprus) and 71.0 (Slovakia) , the highest amount to 88.0
(Sweden) and 89.0 (Luxembourg). In “Services”, the
corresponding extremes are 67.0 (United Kingdom) and 67.5
(Slovakia) on the lower end and 94.1 (Romania) and 94.9
(Bulgaria) on the upper end of the scale.
Table 4: Gross hourly earnings by sex, NACE aggregates C-F, G-K and C-K
Percentages in bold / bold Italic: maximum / minimum (per column)
NACE code in Italic: The data in this column are visu alized in Figure 6a.
Source: Eurostat , SES 2002.
Men’s hourly
earnings (in Euro) Women’s hourly
earnings (in Euro) Women’s hourly earnings
(in % of men’s earnings)

C-F G- K C-K C-F G- K C-K C-F G- K C-K
EU-25 13.08 14.58 13.79 9.62 10. 75 10.40 73.6 73.7 75.4
EU-15 14.90 16.06 15.46 11.72 11. 93 11.87 78.7 74.3 76.8
NMS 2.98 3.22 3.08 2.27 2.61 2.46 76.0 81.0 79.8
EZ 13.85 14.10 13.96 10.95 10. 87 10.90 79.1 77.1 78.1
BE 14.45 14.63 14.54 12.08 12. 03 12.05 83.6 82.3 82.9
CZ 2.96 3.37 3.12 2.17 2.54 2.35 73.3 75.5 75.5
DK 22.08 20.89 21.42 18.59 16. 65 17.13 84.2 79.7 80.0
DE 17.17 16.48 16.91 13.09 12. 28 12.58 76.2 74.6 74.4
EE 2.34 2.52 2.43 1.78 1.78 1.78 76.2 70.7 73.4
EL 7.98 7.96 7.97 5.94 5.94 5.94 74.4 74.6 74.5
ES 8.62 9.65 9.09 6.80 6.83 6.82 78.8 70.8 75.0
FR 14.89 15.74 15.31 12.98 12. 68 12.77 87.1 80.6 83.4
IE 18.09 18.50 18.29 13.81 13. 32 13.47 76.4 72.0 73.7
IT 10.50 11.80 11.06 8.53 9. 33 8.97 81.2 79.1 81.2
CY 9.40 11.88 10.80 6.01 8.32 7.76 63.9 70.0 71.9
LV 1.62 1.75 1.69 1.38 1.31 1.34 85.3 75.1 79.2
LT 1.90 1.93 1.91 1.54 1.61 1.58 80.9 83.7 82.5
LU 14.67 18.06 16.94 13.06 13.82 13.73 89.0 76.5 81.1
HU 2.62 2.74 2.67 2.11 2.43 2.28 80.6 88.7 85.5
NL 15.40 15.56 15.50 13.38 11. 58 11.84 86.9 74.5 76.4
AT 13.24 13.29 13.26 10.04 9. 66 9.76 75.9 72.7 73.6
PL 3.26 3.51 3.35 2.57 3.12 2.88 79.0 89.0 86.0
PT 4.98 6.65 5.71 3.56 5.47 4.59 71.4 82.4 80.3
SI 5.07 5.80 5.34 4.39 5.06 4.75 86.6 87.2 89.0
SK 2.20 2.63 2.40 1.56 1.78 1.70 71.0 67.5 70.9
FI 14.49 15.30 14.80 12.37 11. 99 12.13 85.3 78.4 82.0
SE 15.14 16.58 15.82 13.33 13. 43 13.40 88.0 81.0 84.7
UK 19.07 20.62 20.01 14. 55 13.82 13.95 76.3 67.0 69.7
BG 0.91 0.83 0.88 0. 66 0.78 0.70 72.0 94.9 79.9
RO 1.10 1.19 1.13 0.80 1. 12 0.90 72.9 94.1 80.2
NO 23.04 23.73 23.44 19.86 18. 54 18.80 86.2 78.1 80.2

10 Statistics in focus — Population and social conditions — 12/2005 ________________________________________
"
b) Construction (NACE section F)
Figure 6a visualizes the gender pay gap data presented in
Table 4 for “Industry and services” (NACE category C-K).
Figure 6b, referring to “Construction” (section F, not covered
by Table 4), shows that gender-specific pay differences may even be more accentuated for individual economic activities1.
The lowest percentages for section F refer to Ireland (77.7)
and the United Kingdom (80.4), the highest to Slovenia
(118.6) and Romania (110.6).

It should be stressed, however, that Table 4 and Figure 6 do
not include any breakdown by personal characteristics of men
and women or by variables related to the enterprise. The data
in Table 4 only represent a first starting-point for a deeper
analysis of gender pay gaps. Figure 6b makes very clear that
gender pay data non-adjusted for employee’s characteristics
need to be interpreted with great caution. In “Construction”, for
example, females are strongly under-represented2 and usually
not involved in manual work. Women’s typical occupations in section F therefore differ from thos e of men. This explains that
in several countries women’s gross hourly earnings for section
F lie above that of men. Di fferences observed in average
earnings do not necessarily reflect a gap in pay between
women and men occupying the same job with the same level of seniority. Hence, one has to take a closer look at key
determinants of earnings, such as occupation, educational
level, work experience or size of the enterprise. Earnings
comparisons for men and women working in comparable “job
cells” (same or comparable occupation, educational level,
working-time arrangements, age, same enterprise) lead to
more meaningful adjusted measures for gender-specific
earnings inequalities.
Figure 6: Gender pa y gap for gross hourl y earnin gs
(countries ranked by descending order)
a) Industry and services (NACE aggregate C-K)


1 The reader may access data on hourly earnings by sex for all NACE sections C to K by using an interactive version of this Stati stics in
Focus edition ( http:/forum.europa.eu.int/irc/dsis/wages/info/data/interactive.htm ).

2 The percentage of women working in “Industry and services” amounts to 35.7 in the EU-1 5 and 39.9 in the NMS. For “Construction” , the
corresponding percentages are 10.7 and 12.7.

________________________________________ 12/2005 — Population and social conditions — Statistics in focus 11 
¾ ESSENTIAL INFORMATION – METHODOLOGICAL NOTES
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EU-wide harmonised structural data on gross earnings, hours paid and
annual days of paid holiday leave are collected every four years in the European Structure of Earnings Survey under Council Regulation (EC) No
530/1999 and Commission Regulation (EC) No 1916/2000. The latest refer
to the year 2002, encompassing information from more than 7.9 Mio employees in all Member States of the EU (except Malta) as well as in the
Candidate Countries Bulgaria and Romania and the EEA countries Iceland and Norway. The data for Germany refer to the year 2001. The national
surveys were generally conducted on the basis of a two-stage random
sampling approach of enterprises or local units (first stage) and employees (second stage).
Official codes for countries included in this publication
Coverage of the survey and codes for economic activities
The codes below are as defined in the General Industrial Classification of
Economic Activities, NACE, Rev 1.1. For the SES 2002, data for NACE sections C to K were mandatory and optional for the sections L to O. Nine countries provided data for all optional NACE sections. These data are not
covered by this publication.
Economic activity
C Mining and quarrying J Financial intermediation
D Manufacturing K Real estate, renting, business activities
E Electricity, gas, water supply L Public administration and defense; compulsory social
security
F Construction M Education
G
Wholesale and retail trade, repair of motor vehicles,
personal and household goods N Health and social work
H Hotels and restaurants O Other community, social and personal service activities
I Transport, storage, communication
The SES 2002 data refer to enterprises with at least 10 employees. The
inclusion of small enterprises was optional and 14 countries made use of this option. The national averages on earnings for all economic activities presented in
this publication include all sizes of enterprises for which data are available.
Useful definitions
Employees are all persons who a have a direct employment contract with
the enterprise or local unit and receive remuneration, irrespective of the type
of work performed or the number of hours worked.
Gross earnings cover remuneration in cash paid directly by the employer,
before deductions of tax and social security contributions. All data on earnings presented in this publication cover full-time employees as well as part-time employees. The data for part-time employees are grossed-up to those for full-time employees.

Monthly earnings are restricted to gross earnings which are paid in each pay
period. Annual earnings also include allowances and bonuses which are not
paid in each pay period, such as 13
th month payments or holiday bonuses.
Severance payments and payment in kind are not included. G ross hourly
earnings are defined as gross monthly earnings divided by the number of
hours paid in the same month.
Hours paid cover normal and overtime hours. Hours not worked but
nevertheless paid are also counted as hours paid. Examples are annual holidays or sick leave.
EU Member States Acceding Countries
BE Belgium IE Ireland AT Austria BG Bulgaria
CZ Czech Republic IT Italy PL Poland RO Romania
DK Denmark CY Cyprus PT Portugal DE Germany LV Latvia SI Slovenia EEA Countries
EE Estonia LT Lithuania SK Slovakia IS Iceland
EL Greece LU Luxembourg FI Finland NO Norway ES Spain HU Hungary SE Sweden
FR France NL Netherlands UK United Kingdom

Further information:
Databases and weblinks
SES 2002 data on Eurostat’s freely accessible database :
Population and social conditions
Population
Health
Education and training
Labour marke t
Employment and unemployment
Job vacancy statistics
Earnings and labour costs
Minimum wages
Labour costs
Gross earnings
Structure of earnings survey 200 2
Number of employees
Hourly earnings
Monthly earnings
Annual earnings
Hours pai d
Annual holidays

Interactive visualisation of SES 2002 data:
http://forum.europa.eu.int/irc/dsi s/wages/info/data/index.htm (item “Gross earnings in Europe 2002”)
http://forum.europa.eu.int/irc/dsis/w ages/info/data/interactive.htm (interactive version of this publication)

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