Content uploaded by Arturo Cancio
Author content
All content in this area was uploaded by Arturo Cancio on Nov 23, 2017
Content may be subject to copyright.
ISSN (Online): 2367-6957 ISSN (Print): 2367-6361
Izvestiya Journal of Varna University of Economics 3 (2017)
I ZVESTIY A
Journal of Varna University of Economics
http://journal.ue-varna.bg
236
PRECARIOUSNESS AND ARTISTS: THE SPANISH CASE
Jabier Martínez LÓPEZ
1
, Arturo Cancio FERRUZ
2
________________________
1
PhD Economics and Business Administration, Deusto Business School (DBS), University of Deusto, Bilbao,
Bizkaia, Spain. E-mail: jabier.martinez@deusto.es
2
PhD candidate, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain. E-mail: arturo.cancio@ehu.eus
JEL
E24, J31, J41, Z11
Abstract
Keywords:
precariousness, labour
market, artists, Spain
.
Our research focuses on the labour conditions of the artistic sector, based on the surveys
the Spanish National Institute of Statistics (INE) publishes on a periodical basis,
informing about socio-
economic data regarding the type of contracts, economic activity
and earned incomes in the general labour market. We analyse the distribution of sal
a-
ries, the number of working hours and the kind of contracts for the sector of activity of
the artists through a series of statistics and use of web microdata
forms as defined by the
2014 Wage Structure Poll (EES-14) as a primary unit of analysis.
We obtain empirical
evidence of an actual precarious artistic life and demonstrate that the values
characterising the right to lead a life with dignity are substantially lower in the so-
called
creative industries than the ones in other professional fields..
© 2017 University of Economics
–
Varna
Citation: LÓPEZ, J., FERRUZ, A. (2017). Precariousness and Artists: the Spanish Case. Izvestiya Journal of Varna
University of Economics. 61 (3). p. 236 –.251
Acknowledgements
This work is included in the research labours of Prekariart team at the University
of the Basque Country UPV/EHU financially supported by the Spanish Ministry of
Economy and Competitiveness (MINECO) – more specifically from the State I+D+i
Programme Oriented to the Challenges of Society, ref. HAR2016-77767-R
(AEI/FEDER, UE) – that we gratefully want to acknowledge. Besides, the authors
presented a summarised version of this article in the 8
th
International Conference The
Economy in a Changing World: National, Regional and Global Aspects (ECW-2017)
organised by the University of Economics – Varna, together with the Economic
Research Institute at the Bulgarian Academy of Sciences and Varna Chamber of
Commerce and Industries. We are sincerely grateful that the Scientific Committee se-
lected our research to be presented at this conference. We would also like to thank the
two anonymous reviewers for their suggestions and comments.
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
237
Introduction
Notwithstanding the fact that determining the perimeter of cultural activity or
establishing professional criteria to “consider the artist” (Benhamou, 2011) is a difficult
task, the working conditions of an artist accurately mirror the main features of
precarious labour. At the very least, the artist’s job seems to be more precarious than
that of other professionals (Alper and Wassal, 2006; Girsburg and Throsby, 2006). The
empiric evidence endorses this circumstance: the artist as a precarious worker is prone
to be self-employed, part-timer, and temporary contracts are more frequent in this field
of economic activity than in other occupations (Benhamou, 2000). Besides, the
distribution of incomes among artists tends to be highly assymetrical (Thorsby, 2010).
Moreover, in a recent study, Pérez and López-Aparicio (2017) demonstrate that pre-
cariousness is a feature characterising the economic life of most Spanish artists. They
claim that the income of 50% of more than 1000 Spanish artists surveyed is below the
minimum wage. They also affirm that less than 15% can make a living from the earnings
they get from their artistic activities, whereas only 3% of the artists see their economic ac-
tivity a satisfactory one and the only source of income. Regardless of the accuracy and
interest of these findings, this socio-economic research based on an anonymous online
published poll is not the most reliable source of information to obtain objective results.
Our research focuses on labour conditions based on the surveys the Spanish Na-
tional Institute of Statistics (INE) publishes on a periodical basis, informing about so-
cio-economic data regarding the type of contracts, the economic activity and the
earned income in the general labour market. We aim to get empirical evidence of an
actual precarious artistic life, to demonstrate that the values that characterise the right
to lead a life with dignity in the so-called creative industries are substantially lower
than the ones in other professional areas.
We have structured the present article in three sections: after this short
introduction, we are to delve into the concept of labour precariousness and how it ap-
plies to the professional activity of artists. In the section that follows, we shall de-
scribe the methodology and data employed to carry out our study. Finally, we shall
present some basic results and conclusions.
Artists and Precarious Work
Culture Statistics 2016 is the latest report the statistical office of the EU
(Eurostat) has published about the cultural activity within the EU. This report can be
considered a third edition of the Eurostat publication on culture statistics. Previous
editions of the pocketbook Cultural Statistics were released in 2007 and 2011. The
Izvestiya
2017 • Volume 61 • №3
238
current edition has based its results on information that corresponds to the year 2014.
It presents a selection of indicators and data on certain cultural topics that include
cultural employment. In this regard, the report intends to give an overview of cultural
employment by comparing it with the employment rates in the general labour market.
The chapter on cultural employment presents data derived from the EU Labour
Force Survey and the methodology used to obtain the statistics followed an algorithm
which takes into account the Statistical Classification of Economic Activities (NACE
Rev. 2) and the International Standard Classification of Occupations (ISCO-08)
classifications. It features a brief section that specifically addresses the particular
characteristics of the cultural occupations of writers and artists as a whole (ISCO 264
and 265 classifications). Said section focuses on the the following aspects: self-
employment status; working time (full-time versus part-time), multiple job-holding
and, for employees, contractual status (permanent versus temporary contracts).
The results of this study are displayed in Figure 1 and Table 1 dispalyed below.
Creative and performing artists, authors, journalists and linguists (ISCO 264 +265)
Total
(1) Data for Estonia, Lithuania and Romania is extremely unreliable and therefore not
published.
(2) Lack of reliability of data on cultural occupations (ISCO 264+265).
Source: Eurostat.
Fig. 1. Share of self-employed among ‘creative and performing artists,
authors, journalists and linguists’ (ISCO 264-265),
compared with total employment, 2014 (¹) (%)
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
239
Table 1
Employment characteristics of ‘creative and performing artists,
authors, journalists and linguists’ (ISCO 264-265)
compared with total employment, 2014 (%)
Full-time job Single job holder
Permanent contract
(employees)
ISCO
264
-
265
(1)
Total
ISCO
264
-
265
Total
ISCO
264
-
265
(2)
Total
EU
-
28
70
80
90
96
76
86
Belgium
74
76
95
96
78
91
Bulgaria
91
97
96
99
93
95
Czech Republic
87
94
95
98
89
90
Denmark
76
75
88
92
84
91
Germany
68
72
90
95
82
87
Estonia
84
90
77
95
97
97
Ireland
67
76
96
98
79
91
Greece
73
91
99
98
78
88
Spain
80
84
95
98
67
76
France
64
81
82
96
56
84
Croatia
80
94
90
98
63
83
Italy
73
82
97
99
82
86
Cyprus
64
86
86
96
78
81
Latvia
76
93
86
95
96
97
Lithuania
87
91
89
94
100
97
Luxembourg
82
81
92
97
94
92
Hungary
85
94
94
98
87
89
Malta
61
83
97
95
92
92
Netherlands
42
50
79
92
74
79
Austria
56
72
88
96
84
91
Poland
75
92
87
94
66
72
Portugal
77
87
89
96
61
79
Romania
88
90
99
98
100
99
Slovenia
83
89
94
96
67
83
Slovakia
94
95
94
99
94
91
Finland
71
85
88
95
80
84
Sweden
69
74
85
91
66
83
United Kingdom
69
73
92
96
88
94
Iceland
78
76
75
90
81
87
Norway
69
73
85
91
90
92
Izvestiya
2017 • Volume 61 • №3
240
Switzerland
43
62
85
93
86
87
FYR of Macedonia
89
94
97
99
86
85
Turkey
74
88
98
97
88
87
(1) Low reliability for Croatia and Malta.
(2) Low reliability for Croatia, Cyprus and Malta.
Source: Eurostat.
Figure 1 shows that nearly half (49%) of all artists and writers in the EU are
self-employed. This percentage is much higher than that reported for total
employment (15%). The difference between these rates however is not so pronounced
in Spain: 37% versus 17%. Besides, as shown in Table 1, 70% of artists and writers
said they had a full-time job, which is lower than the corresponding proportion of the
total workforce: 80%. 80% versus 84% in Spain. EU-wide, 96% of employed people
held one job, whereas the figure for artists and writers was 90%. 98% versus 95% in
Spain.
According to this study, time spent at work is an important determinant of the
worker’s position in the labour market and, in most cases, of his or her financial
resources. Full-time employment often comes with benefits that part-timers do not
enjoy. Part-time employment may lead workers to consider getting a second job.
‘Full-time part-timers’ sometimes seek to complement their main part-time job with
another part-time occupation, to increase their income. Holding a second job may
thus be an indication of (self-perceived) precarious employment.
However, the assumption that precarious labour is a subjective perception finds
a rejoinder in the work of Rodgers and Rodgers (1989) or more recently Olsthoorn
(2014) who identify some distinctive features of precarious labour:
•
insecure employment (e.g. temporal employment);
•
low level of protection (e.g. social protection, protection against unemplo-
yment or against discrimination);
•
insufficient income or economic vulnerability and
•
no individual and collective control over work (working conditions, income,
working hours).
The above authors arrive at similar conclusions by deploying different metho-
dologies. On the one hand, Rodgers and Rodgers’ study has a discursive and
multidisciplinary character. They observe that despite the efforts of many occidental
countries to regulate the labour market, the debate on precarious labour re-emerges in
the late 1960’s. In fact, Barattini (2009) states the International Labour Organization
(ILO) used this concept for the first time in 1974 to define the instability in the
workplace, either by the absence of a contract or by fixed-term contracts. Since then,
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
241
there has been an increasing concern about job insecurity, but always as an unwanted
or necessary effect of productive restructuring, technological change in the labour
process, transformations in the labour market and new forms of work organisation as
Aguiar (2008) explains.
On the other hand, Olsthoorn observes that the concept of precarious
employment is very ambiguous, lending itself to multiple interpretations that can lead
to confusion. He also states that due to the existence of different and imprecise
definitions and the use of non-integrated variables and statistical indicators that use
different dimensions, labour precariousness is elusive to its quantitative evaluation.
Taking Kalleberg's (2009, 2011) empirical studies as a starting point, which he
questions and criticises for the reasons explained above, he proposes an improved
method for measuring precarious work that is consistent with theoretical discourse
and provides valid and reliable results (Idem). To achieve this, in addition to
conceptualising precarious employment based on a review of relevant theoretical
perspectives, Olsthoorn proposes and integrates two indicators to test several
validated hypotheses, using data from the Dutch labour market.
The conceptual framework suggested by Olsthoorn is a useful starting point
when trying to conceptualise precarious work as asserted in the study for the
European Parliament’s Committee on Employment and Social Affairs (EMPL)
entitled Precarious Employment in Europe: Patterns, Trends and Policy Strategies
(2016) and Duell study (2004) is a valuable antecedent. The EMPL study describes
and analyses the development of precarious work in Europe, focusing on its
underlying causes and assessment of policy answers at European and national level.
The research carried out in this study is based on existing available data, studies and
analyses from various sources, complemented by independent data and expertise and
documents from national and international institutions. It specifically addresses the
argumentation of certain themes linked to labour precariousness and it provides
specific discussions of the issues associated with the risk of precariousness and
ground its findings on detailed quantitative and qualitative evidence.
The above study examines works with two analytical axes of employment
relations and individual risk of precariousness with a conceptual link to quality of
work. The types of employment relationships examined are ‘standard’ open-ended,
full-time contracts, part-time work, self-employment, temporary work (including
fixed-term contracts, temporary agency work, seasonal and casual work, posted work
and outsourced or subcontracted work), zero hours contracts, internships, and
informal or undeclared work. In-work poverty and low pay are among the most
important indicators of individual exposure to precariousness. The analysis concludes
Izvestiya
2017 • Volume 61 • №3
242
that: “(…) all employment relationships are at some risk of precariousness. However,
the level of risk varies” (DGIP, 2016: 168).
In the next section of our study we will try to establish to what extent the labour of
artists in Spain can be considered precarious or at least, more precarious than other
professional activities.
Methodology and data
We obtain the data from the Wage Structure Poll (Encuesta de Estructura Salari-
al - EES) a statistic operation with standard methodological and content criteria with-
in the EU, firstly implemented in 1995. This poll aims to obtain comparable results
about the level, structure and distribution of the salaries in the EU. Therefore, the
member states of the EU draw on the same period of reference, scope of coverage,
required information, representativity, processing and transmission of results. The
EES is a quadrennial research which, besides the individual information about
salaries, considers a high number of variables such as sex, occupation, activity and
career of the employees, or the size of the enterprises surveyed. These features allow
establishing some relationships among the salaries and the variables that contribute to
determining their amount such as the level of education of workers, their career, type
of contracts or occupations, to name but a few.
Further on, the EES relates the wage tiers with other variables that affect the
workers in an establishment or an enterprise: the target market of its production, the
existence of collective bargaining agreements and their scope or whether its activity is
concerned with a public or private property. The EES not only provides average earn-
ing values, but also the distribution of salaries and as a consequence, a measurement
of their inequality. We can summarise two fundamental objectives of the EES:
• The knowledge on wage tiers, not only at the average level but also about
their distribution.
• The determination of the structure of salaries, regarding both the composition
of the conditioning variables and their scope.
We study the latest EES data from the 2014 poll (EES-2014) which the Spanish
National Institute of Statistics (INE) published on October 28th, 2016. It incorporates
209.436 employees who provide their services in quotation centres, regardless of their
size and registered in the Social Security system during the whole month of October
of the reference year. Presidents, members of boards of directors and, in general, all
personnel whose remuneration is not mainly in the form of a salary, but as commis-
sions or benefits, are excluded.
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
243
Regarding the sectoral coverage, the EES examines the economic activities in
the sectors of industry, construction and services. It excludes the agricultural, live-
stock and fishing activities, domestic staff, extraterritorial organisations and, partially,
the Public Administration, Defense and compulsory Social Security.
We use the total yearly wage definition according to EES-14 as the basic unit of
analysis. The methodology can be found in the INE EES-14 manual. We analyse the
distribution of salaries, the number of working hours and the kind of contracts for the
sector of activity of the artists (R0) through a series of statistics. Furthermore, we
compare them to the ones of other activities included in the 2009 Spanish National
Classification of Economic Activities (CNAE-2009) shown in Table 2, to evaluate the
real degree of precariousness present in each of them. Section ‘R’ includes recreation
and entertainment activities alongside artistic activities. It is not currently possible to
separate the latter from the former. In any case, we believe that this fact does not dis-
tort our analysis, as we also believe that it does not introduce significant biases. If it
does, the conclusions we would obtain from our analysis would be even more solid;
the artistic activity would be even more precarious.
Table 2
2009 Spanish National Classification of Economic Activities (CNAE-2009)
CNAE-2009
BRANCHES OF
ACTIVITY
DESCRIPTION
'B0' '05','06','07','08','09'
Mining and quarrying
'C1' '10','11','12','13','14','15'
Manufacture of food products, beverages and t
o-
bacco products, textiles, apparel, leather and relat-
ed products
'C2' '16','17'
Manufacture
of cork, wood and paper products
(except furniture)
'C3' '18'
Printing and reproduction
'C4' '19','20','21','22'
Manufacture of coke, and refined petroleum pro
d-
ucts, chemicals and chemical products, pharma-
ce
u
ticals products, rubber and plastics products
'C5' '23'
Manufacture of non
-
metallic mineral products
'C6' '24','25'
Manufacture of
basic metals and fabricated metal
products, except machinery and equipment
'C7' '26','27','28'
Manufacture of computer, electronic and optical
products, electrical equipment, machinery and
equipment n.e.c.
'C8' '29','30','31','32','33'
Manufacture of
transport equipment
'D0' '35'
Electricity, gas, steam and air
-
conditioning supply
Izvestiya
2017 • Volume 61 • №3
244
'E0' '36','37','38','39'
Water supply, sewerage, waste management and
remediation
'F0' '41','42','43'
Construction
'G1' '45','46'
Wholesale, repair of motor vehicles and
motorc
y-
cles
'G2' '47'
Retail trade, except motor vehicles and motorc
y-
cles
'H1' '49','50','51'
Terrestrial, piping, maritime, air and fluvial tran
s-
portation.
Activities related to transport
'H2' '52','53'
Storage and activities related to transport.
Postal
and
mail
services
'I0' '55','56'
Accommodation and food service activities
'J0' '58','59','60','61','62','63'
Telecommunication, IT and other information se
r-
vices
'K0' '64','65','66'
Financial and insurance activities
'L0' '68'
Real estate
activities
'M0' '69','70','71','72','73','74','75'
Professional, scientific and technical activities
'N0' '77','78','79','80','81','82'
Administrative and support service activities
'O0' '84'
Public administration and defence, compulsory s
o-
cial security
'P0' '85'
Education
'Q0' '86','87','88'
Human health services and social work activities
'R0' '90','91','92','93'
Arts, entertainment and recreation
'S0' '94','95','96'
Other services
Source: Own elaboration from data of the CNAE extracted from http://www.empleo.
gob.es/ stadisticas/hue/hue11/ANE/cnae09.htm [Accessed: 12/04/2017].
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
245
Reference/Source: Own elaboration (INE, 2016).
Fig. 2. Log (Wages) Probability Density Function
(for ALL economic activities, R0 and D0)
We use web microdata forms as defined by the EES-14 as a primary unit of
analysis. As we can appreciate in the distribution of salaries – presented in logarith-
mic terms in order to compare them – the salary of artists (R0) presents the highest
density for the lowest salaries. Simultaneously, it includes workers who earn the
highest salaries. Figure 3 below shows a summary of the statistics calculated. R0 pre-
sents the highest variation coefficient, the highest positive asymmetry and kurtosis.
6 8 10 12 14
0.0 0.5 1.0 1.5
log (wages)
density
6 8 10 12 14
0.0 0.5 1.0 1.5
6 8 10 12 14
0.0 0.5 1.0 1.5
PDF
D0
R0
ALL
Izvestiya
2017 • Volume 61 • №3
246
Reference/Source: Own elaboration (INE, 2016). (x-axis wages (euros), y-axis (pdfs)).
Fig. 3. Distribution of salaries by economic activity
The statistics we calculate are: 1) average 2) standard deviation 3) coefficient of
variation 4) coefficient of skewness 5) coefficient of kurtosis; 6) Gini index 7) distri-
bution by percentiles 8) % full-contract and 9) % open-ended contracts. We intend to
obtain empirical evidence to corroborate that the labour of artists in Spain is precari-
ous.
-
-
-
0 200000 500000
0.0 0.2
B0
0 400000 800000
0.0 0.4 0.8
C1
0 100000 250000
0.00 0.10 0.20
C2
0 100000 250000
0.00 0.10 0.20
C3
0 400000 800000
0.0 0.2 0.4
C4
0 100000 250000
0.00 0.10 0.20
C5
0 100000 250000
0.00 0.10 0.20
C6
0 100000 250000
0.00 0.10 0.20
C7
0 200000 500000
0.00 0.10 0.20
C8
0 200000
400000
0.00 0.06 0.12
D0
0 100000 200000
0.00 0.10
E0
0 100000 250000
0.00 0.15 0.30
F0
0 200000 500000
0.0 0.2 0.4
G1
0 200000 400000
0.00 0.15 0.30
G2
0 100000 200000
0.00 0.10
H1
0 200000 400000
0.00 0.15 0.30
H2
0 100000 250000
0.00 0.10 0.20
I0
0 400000 1000000
0.0 0.2 0.4
J0
0 200000 500000
0.00 0.10
K0
0 200000 400000
0.00 0.15 0.30
L0
0 400000 800000
0.0 0.2 0.4
M0
0 200000 500000
0.0 0.2
N0
0 40000 80000
0.00 0.03 0.06
O0
0 50000 150000
0.00 0.04 0.08
P0
0 100000 200000
0.00 0.06 0.12
Q0
0 400000 1000000
0.0 0.2 0.4 0.6
R0
0 200000 500000
0.0 0.2 0.4 0.6
S0
0 400000 1000000
0.0 0.2 0.4 0.6
ALL
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
247
-
-
-
; a measure of the symmetry of the probability
distribution about its average.
-
; a measure of “taledness” of the probability distribution.
-
;
-. Lorenz curve (Figure 4) plots the proportion of the wages of the workers (y-
axis) that is cumulatively earned by the bottom x% of the workers (workers are sorted
from the one who has the lowest wage to the one who has the highest one).
Gini index: it is a measure of statistical dispersion intended to represent inequali-
ty of the distribution of a variable (wages in our case). A value of 0 represents total
inequality and a value of 1 total equality. It stands for two times the area between the
Lorenz curve and the line of total equality (45-degree line).
Results and conclusions
Table 3 shows the results. We use a grayscale background to differentiate the
progression of precariousness on the statistics; from the highest level of precarious-
ness (dark grey) to the lowest (light grey).
As we can appreciate in Table 3, the artistic sector shows a higher variation co-
efficient and more asymmetrical distribution, a higher and unbalanced kurtosis and
Gini index that evidence the idea of an unequal distribution of the salaries, in particu-
lar on the lowest sections. The median shows the wages of the 50% of the workers.
The average salary is among the lowest five of all of them and presents the second
lowest median. Moreover, the presence of full-time contracts is the second lower rate
and indefinite contracts the fifth lower rate among all the activities considered.
These data reveal that the distribution of wages in the Spanish artistic sector is
the more extreme and asymmetrical of the activities considered in this study. It pre-
sents the highest concentration and shows how the majority of the workers in this sec-
tor receive the lowest salaries. Besides, it includes a small group with the highest sal-
aries. Somehow, these results confirm one of the issues linked to precariousness
Alper and Wassal (2006: 858) consider: “(…) the existence of unusual earnings pat-
terns in the artistic labour market, such as greater earnings uncertainty and variability,
relative to other occupations”.
Izvestiya
2017 • Volume 61 • №3
248
The empirical evidence found in our work support the consideration of the artis-
tic activities as precarious. The data from the 2014 INE’s wage distribution survey by
economic activity leaves no room for doubt. We do get empirical evidence of an actu-
al precarious artistic life in Spain and open the way to demonstrate that the values
characterising the right to lead a life with dignity in the so-called creative industries
are substantially lower than the ones in other professional fields.
Reference/Source: Own elaboration (INE, 2016).
Fig. 4. Lorenz Curve (ALL economic activities, R0 and D0)
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
x100% workers
x100% wages
Lorenz Curve
D0
R0
ALL
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
249
Table 3
Wages and contracts distribution in Spain
Reference: Own elaboration form the data obtained at INE [Online] https://goo.gl
/HCpRuS [Accessed: 12/04/2017]
References
1. Alper, N. & Wassall, G. (2006) “Artists’ careers and their labour markets,” in
Ginburgh & Throsby [eds.], 813-864.
2. Aguiar, S. (2008) “Inquisiciones sobre la economía del tiempo: la conformación
de la figura del trabajo precario”. Cuadernos de Estudios de Trabajo, 5, s.p. Ex-
tracted from https://goo.gl/u4h250
3. Barattini, M. (2009) “El trabajo precario en la era de la globalización; ¿es posible
la organización?”. Polis, Revista de la Universidad Bolivariana, (8), 24, 17-37.
4. Benhamou, F. (2000) “The Opposition of Two Models of Labour Market Adjust-
ment. The Case of the Audio-visual and Performing Arts in France and in the
United Kingdom”. Journal of Cultural Economics, 24, p. 301–19.
avg. st. dev. cv skew.
kurt. gini quartiles % full-
contract
% open-
ended
contract
0% 25% 50% 75% 100%
B0 32,905.60
20,302.74
0.62 5.82 100.09 0.29 327.39 20,101.05
27,789.03
40,846.65
574,130.91 96.73% 83.91%
C1 21,538.88
15,353.65
0.71 7.78 183.60 0.30 327.39 14,003.85
17,947.16
25,311.76
978,372.30 82.62% 85.59%
C2 24,710.10
14,551.61
0.59 2.58 15.62 0.29 916.46 15,879.86
20,304.46
29,361.23
289,778.34 91.11% 88.03%
C3 22,082.08
11,792.76
0.53 2.59 26.54 0.27 1,122.32
14,725.93
19,929.40
27,233.36
354,904.84 85.06% 90.88%
C4 32,035.96
19,705.40
0.62 4.80 78.39 0.29 461.35 19,377.77
27,605.51
40,065.85
978,372.30 93.65% 89.85%
C5 26,506.21
13,528.09
0.51 2.61 27.76 0.26 1,885.85
17,865.58
23,930.70
31,668.92
354,904.84 92.01% 87.06%
C6 26,655.44
12,823.03
0.48 1.65 8.64 0.25 343.24 18,339.83
24,294.60
33,022.55
342,322.83 91.31% 81.70%
C7 29,049.85
14,678.48
0.51 2.37 14.33 0.25 1,121.64
20,067.30
25,915.00
34,861.40
346,567.68 93.47% 86.71%
C8 29,305.84
15,372.78
0.52 2.43 31.26 0.27 384.88 18,786.27
26,641.09
36,953.34
525,442.37 90.81% 83.71%
D0 51,034.62
22,263.14
0.44 0.93 9.01 0.24 1,470.73
35,614.80
52,438.85
64,185.81
395,439.16 97.13% 95.22%
E0 25,959.29
12,462.37
0.48 1.55 6.68 0.25 532.29 18,141.73
23,934.42
31,448.67
250,273.56 88.80% 82.83%
F0 22,608.06
12,619.56
0.56 3.05 20.38 0.26 333.92 16,327.86
19,597.00
25,625.13
354,904.84 89.47% 64.40%
G1 24,482.48
18,363.39
0.75 4.12 34.67 0.33 323.81 14,825.13
19,234.88
28,216.92
610,329.00 85.10% 88.97%
G2 16,264.78
9,462.45 0.58 2.67 15.87 0.28 179.15 10,874.85
14,809.84
19,253.84
397,749.16 65.05% 85.79%
H1 22,942.75
13,234.43
0.58 1.51 6.42 0.31 118.19 14,327.45
20,462.28
29,833.45
234,420.26 85.11% 80.35%
H2 24,822.53
14,261.58
0.57 3.57 44.71 0.28 409.20 16,490.72
21,750.58
30,333.96
478,645.63 86.89% 86.76%
I0 13,636.05
8,442.03 0.62 1.81 9.41 0.32 277.05 7,254.47 13,722.87
17,976.00
256,419.90 47.71% 74.52%
J0 32,755.83
20,052.93
0.61 4.19 85.23 0.30 118.19 19,460.04
28,996.36
42,022.05
1,252,723.92
91.89% 86.41%
K0 40,697.64
19,823.78
0.49 2.36 32.72 0.26 118.19 27,599.12
38,749.83
51,284.19
594,602.45 93.18% 96.40%
L0 20,619.76
21,117.26
1.02 6.07 64.24 0.39 601.59 11,038.94
15,376.32
22,930.78
420,000.00 75.05% 86.40%
M0 26,265.16
21,689.44
0.83 7.68 153.12 0.36 179.15 14,390.82
21,580.46
32,498.64
978,372.31 81.54% 83.08%
N0 15,766.08
14,159.71
0.90 13.53
375.27 0.35 118.19 8,740.92 14,093.51
19,607.00
607,400.03 56.65% 68.80%
O0 27,568.54
11,904.19
0.43 0.82 1.63 0.24 1,835.10
19,627.08
26,160.93
34,201.31
114,339.84 90.64% 77.57%
P0 20,925.84
12,847.61
0.61 1.35 9.85 0.33 342.12 10,513.20
20,944.57
29,388.94
182,592.36 59.29% 67.16%
Q0 24,826.40
15,870.44
0.64 1.53 3.23 0.33 179.15 14,325.55
20,741.00
31,166.64
241,548.67 78.25% 73.00%
R0 16,957.35
22,211.25
1.31 28.56
1369.46
0.42 179.15 7, 373.40 13,659.20
21,919.85
1,252,723.93
54.80% 73.27%
S0 16,214.00
12,987.76
0.80 6.95 180.82 0.36 118.19 9,201.94 12,600.00
20,097.68
574,130.91 65.21% 79.85%
ALL
22,858.16
16,136.92
0.71 5.23 148.20 0.34 118.19 13,217.84
19,263.78
28,782.70
1,252,723.93
76.08% 79.17%
Izvestiya
2017 • Volume 61 • №3
250
5. Benhamou, F. (2011) “Artist Labour Market”. Chapter 7 in T. Towse (ed.), A
Handbook of Cultural Economics. Edward Elgar Publishing, p. 69-75.
6. Directorate General For Internal Policies (2016) Precarious Employment in Eu-
rope: Patterns, Trends and Policy Strategies (Study). Policy Department A: Eco-
nomic and Scientific Policy (IP/A/EMPL/2014-14). PE 587.285. July, 2016.
7. Duell, N. (2004) “Defining and Assessing Precarious Employment in Europe: A
Review of Main Studies and Surveys”. Economics Research & Consulting. Mu-
nich, December.
8. Ginsburg, V. & Throsby, D. (eds.) (2006) Handbook of the Economics of Art
and Culture. Amsterdam: Elsevier.
9. Handcock, m. S. & morris, M. (1999) Relative Distribution Methods in the So-
cial Sciences. Springer, New York, ISBN 0-387-98778- 11. URL http://www.
stat.ucla.edu/~handcock/RelDist
10. Handcock, M. S. (2016), Relative Distribution Methods. Version 1.6-6. Project
home page at http://www.stat.ucla.edu/~handcock/RelDist. URL https://CRAN.
R-project.org/package=reldist
11. Ine (2016). Encuesta de estructura salarial 2014 (EES-14) [Wage Structure Poll
2014], [online] Available at: http://www.ine.es/prensa/np996.pdf [Accesed 20
May 2017].
12. Kalleberg, A. L. (2009). “Precarious work, insecure workers: Employment rela-
tions in transition”. American Sociological Review, 74(1), 1–22.
13. Kalleberg, A. L. (2011). “Good jobs, bad jobs: The rise of polarized and precari-
ous employment in the United States, 1970s to 2000s”. New York: Russel Sage
Foundation.
14. Olsthoorn, M. (2014) “Measuring Precarious Employment: A Proposal for Two
Indicators of Precarious Employment Based on Set-Theory and Tested with
Dutch Labour Market-Data”. Social Indicators Research, 119(1), p. 421-441.
15. Parchami, A. (2016). Weighted.Desc.Stat: Weighted Descriptive Statistics. R
package version 1.0. https://CRAN.R-project.org/package=Weighted.Desc.Stat
16. Pasek, J., with some assistance from Alex Tahk, some code modified from R-
core; Additional contributions by Gene Culter and Marcus Schwemmle. (2016).
weights: Weighting and Weighted Statistics. R package version 0.85.
https://CRAN.R-project.org/package=weights
17. Pérez, M. & López-Aparicio, I. (2017) La Actividad Económica de los/las
Artistas en España (Estudio y Análisis). Fundación Antonio Nebrija.
18. Plat, D. (2012). IC2: Inequality and Concentration Indices and Curves. R pack-
age version 1.0-1. https://CRAN.R-project.org/package=IC2
J. M. López, A. C. Ferruz.
Precariousness and Artists: the Spanish Case
251
19. Rodgers, G. & Rodgers, J. (eds.) (1989) Labour Market Regulation: The Growth
of Atypical Employment in Western Europe. ILO. Geneva.
20. R Core Team (2013) R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. http://www.R-
project.org/.
21. Throsby, D. (2010) “Economic Analysis of Artists’ Behaviour: Some Current
Issues”. Revue d'économie politique. 2010/1 Vol. 120, p. 47-56.
