Multilingualism and Optimal
Language Policy in the EU
Jan Fidrmuc
Brunel University
Stylized Facts





6,912 living languages on Earth
Most countries linguistically diverse.
A few countries monolingual -- mostly small,
remote and sparsely populated islands (e.g.
Falkland islands, Saint Helena, Pitcairn), and.
North Korea.
Most European countries linguistically
diverse.
Most European countries: only a single
official language.
Worldwide
Country
European Union
Languages
Diversity
Population
Country
Languages
Diversity
Population
P.N. Guinea
820
0.99
5.8
Germany
69
0.189
82.5
Indonesia
742
0.85
234.7
France
66
0.272
60.6
Nigeria
516
0.87
135
UK
55
0.139
60.0
India
427
0.93
1129.9
Italy
42
0.593
58.5
USA
311
0.35
301.1
Netherlands
38
0.389
16.3
Mexico
297
0.14
108.7
Sweden
32
0.167
9.0
Cameroon
280
0.94
18.1
Belgium
28
0.734
10.4
Australia
275
0.13
20.4
Greece
24
0.175
11.1
China
241
0.49
1321.8
Finland
23
0.14
5.2
D.R. Congo
216
0.95
65.8
Romania
23
0.168
21.7
Brazil
200
0.03
190
Hungary
21
0.158
10.1
Philippines
180
0.85
91.1
Spain
20
0.438
43.0
Malaysia
147
0.76
24.8
Austria
19
0.54
8.2
Canada
145
0.55
33.4
Poland
17
0.06
38.2
Sudan
134
0.59
39.4
Bulgaria
16
0.224
7.8
Chad
133
0.95
9.9
Estonia
16
0.476
1.3
Russia
129
0.28
141.4
Denmark
14
0.051
5.4
Tanzania
128
0.97
39.4
Latvia
12
0.595
2.3
Nepal
125
0.74
28.9
Slovak Rep.
12
0.307
5.4
Vanuatu
115
0.97
0.2
Lithuania
11
0.339
3.4
Myanmar
113
0.52
47.4
Slovenia
10
0.174
2.0
Viet Nam
104
0.23
85.3
Czech Rep.
9
0.069
10.2
South Korea
4
0.00
49
Portugal
8
0.022
10.5
Cuba
4
0.00
11.4
Cyprus
6
0.366
0.7
Haiti
2
0.00
8.7
Luxemburg
6
0.498
0.5
Bermuda
1
0.00
0.07
Ireland
5
0.223
4.1
North Korea
1
0.00
23.3
Malta
3
0.016
0.4
Stylized Facts



2% EU citizens multilingual
39% speak at least one foreign language
14% speak two or more foreign languages


Source: Special Eurobarometer 243: Europeans
and their Languages, November-December 2005.
Except English, French, German, Spanish
and Russian, most languages only spoken in
their own countries
Mother’s Tongues
English
German
French
Italian
Spanish
Polish
Dutch
Russian
Turkish
Multiling
Austria
0
96
0
0
0
0
0
0
0
0
Belgium
0
0
35
2
1
1
59
0
1
1
Bulgaria
0
0
0
0
0
0
0
0
9
1
Cyprus
1
0
1
0
0
0
0
0
0
1
Czech Rep.
0
0
0
0
0
0
0
0
0
1
Denmark
0
0
0
0
0
0
0
0
0
1
Estonia
0
0
0
0
0
0
0
16
0
1
Finland
0
0
0
0
0
0
0
0
0
0
France
1
0
93
2
1
0
0
0
0
2
Germany
0
91
0
0
0
1
0
3
2
1
Greece
0
0
0
0
0
0
0
0
0
0
Hungary
0
1
0
0
0
0
0
0
0
1
Ireland
95
0
0
0
0
1
0
0
0
8
Italy
3
2
0
96
1
0
0
0
0
2
Latvia
0
0
0
0
0
0
0
25
0
1
Lithuania
0
0
0
0
0
5
0
7
0
1
Luxemburg
1
4
6
2
1
0
1
0
0
2
Malta
3
0
0
0
0
0
0
0
0
0
Netherlands
1
1
0
0
0
0
96
0
0
1
Poland
0
1
0
0
0
98
0
0
0
0
Portugal
0
0
0
0
0
0
0
0
0
0
Romania
0
1
0
0
0
0
0
0
0
2
Slovak Rep.
0
0
0
0
0
0
0
1
0
2
Slovenia
0
0
0
0
0
0
0
0
0
1
Spain
0
0
0
1
89
0
0
0
0
8
Sweden
0
1
0
0
0
0
0
0
0
1
UK
93
0
0
0
0
0
0
0
0
2
EU27
13
17
12
12
8
8
5
1
0
2
Foreign Lang
English
German
French
Italian
Spanish
Polish
Dutch
Russian
Turkish
1+
2+
Austria
45
3
6
5
2
0
0
1
1
48
17
Belgium
41
13
36
1
2
0
9
0
0
63
40
Bulgaria
16
6
4
1
1
0
0
25
1
47
14
Cyprus
50
2
4
1
1
0
0
1
0
52
8
Czech Rep.
16
19
2
0
0
2
0
15
0
50
19
Denmark
66
27
3
1
2
0
0
0
0
71
34
Estonia
25
8
0
0
0
0
0
52
0
73
28
Finland
31
5
1
0
0
0
0
1
0
37
18
France
19
5
6
3
6
0
0
0
0
34
10
Germany
38
8
8
1
2
1
0
5
0
49
14
Greece
32
6
5
2
0
0
0
2
1
41
10
Hungary
8
8
0
1
0
0
0
1
0
17
5
Ireland
4
2
9
0
1
0
0
0
0
18
4
Italy
22
2
10
1
2
0
0
0
0
34
10
Latvia
15
3
0
0
0
1
0
60
0
78
18
Lithuania
14
4
1
0
0
8
0
67
0
79
25
Luxemburg
38
84
83
3
0
0
0
0
0
97
84
Malta
65
1
5
35
1
0
0
0
0
69
35
Netherlands
76
56
19
0
3
0
3
0
0
83
60
Poland
18
9
1
1
0
0
0
12
0
35
12
Portugal
15
2
9
1
4
0
0
0
0
21
8
Romania
14
2
10
2
1
0
0
2
0
26
10
Slovak Rep.
17
18
1
0
0
2
0
19
0
62
25
Slovenia
41
21
2
9
1
0
0
0
0
75
41
Spain
16
2
6
0
9
0
0
0
0
32
9
Sweden
67
11
3
1
1
0
0
0
0
70
20
6
2
9
1
2
0
0
0
0
18
6
24.4
7.9
7.9
1.3
3.1
0.4
0
3.6
0.5
39
14
UK
EU27
All Speakers
English
German
French
Italian
Spanish
Polish
Dutch
Russian
Turkish
Austria
45
99
6
5
2
0
0
1
1
Belgium
41
13
71
3
3
1
68
0
1
Bulgaria
16
6
4
1
1
0
0
25
10
Cyprus
51
2
5
1
1
0
0
1
0
Czech Rep.
16
19
2
0
0
2
0
15
0
Denmark
66
27
3
1
2
0
0
0
0
Estonia
25
8
0
0
0
0
0
68
0
Finland
31
5
1
0
0
0
0
1
0
France
20
5
99
5
7
0
0
0
0
Germany
38
99
8
1
2
2
0
8
2
Greece
32
6
5
2
0
0
0
2
1
Hungary
8
9
0
1
0
0
0
1
0
Ireland
99
2
9
0
1
1
0
0
0
Italy
25
4
10
97
3
0
0
0
0
Latvia
15
3
0
0
0
1
0
85
0
Lithuania
14
4
1
0
0
13
0
74
0
Luxemburg
39
88
89
5
1
0
1
0
0
Malta
68
1
5
35
1
0
0
0
0
Netherlands
77
57
19
0
3
0
99
0
0
Poland
18
10
1
1
0
98
0
12
0
Portugal
15
2
9
1
4
0
0
0
0
Romania
14
3
10
2
1
0
0
2
0
Slovak Rep.
17
18
1
0
0
2
0
20
0
Slovenia
41
21
2
9
1
0
0
0
0
Spain
16
2
6
1
98
0
0
0
0
Sweden
67
12
3
1
1
0
0
0
0
UK
99
2
9
1
2
0
0
0
0
37.4
24.9
19.9
13.3
11.1
8.4
4.9
4.6
0.5
EU27
English
French
German
Russian
Stylized Facts


Large differences across age cohorts
Only English seems to improve its relative
standing over time
All
15-29
30-44
45-60
> 60
English
37
55
41
32
24
German
25
26
25
24
25
French
20
22
19
20
19
Italian
13
13
13
13
13
Spanish
11
13
11
10
11
Polish
8
8
8
8
8
Dutch
5
5
5
5
5
Turkish
0
1
1
0
0
Russian
5
4
5
5
4
Stylized Facts: Attitudes

67% Europeans think English is a useful
language for one's personal development and
career



22-25% think so of German or French
10% think no language is useful
The opinions on which languages children
should learn are very similar

2% think children should learn no foreign
language
Useful Language
Children Should Learn
English
German
French
Spanish
English
German
French
Spanish
Austria
73
2
15
8
85
2
29
10
Belgium
83
9
54
6
88
7
52
10
Bulgaria
65
34
11
5
87
49
13
6
Cyprus
93
17
34
3
98
18
50
2
Czech Rep.
68
56
5
2
90
68
8
4
Denmark
92
56
7
10
94
64
12
13
Estonia
71
14
2
1
93
23
7
1
Finland
86
18
8
4
84
24
11
3
France
81
19
2
36
90
25
2
45
Germany
81
5
27
13
89
3
44
17
Greece
74
30
21
4
96
50
34
3
Hungary
57
52
3
1
83
73
4
2
Ireland
4
37
58
34
3
42
65
34
Italy
82
15
25
15
85
17
34
18
Latvia
70
17
3
1
94
28
6
1
Lithuania
85
27
4
1
91
34
6
2
Luxemburg
37
60
82
2
61
41
81
3
Malta
88
5
12
2
89
12
23
2
Netherlands
93
48
19
16
90
40
22
22
Poland
70
45
5
2
89
69
7
1
Portugal
51
5
31
6
87
8
58
7
Romania
63
18
33
7
63
18
33
7
Slovak Rep.
70
60
4
1
87
74
7
3
Slovenia
79
61
4
2
97
69
7
3
Spain
72
11
32
5
85
14
44
3
Sweden
96
39
12
21
99
37
17
30
UK
4
29
63
33
4
36
72
38
EU27
67
22
25
15
76
28
33
19
EU Multilingualism and Optimal
Language Policy

1.
2.
3.
4.
5.
Outline
Multilingualism in the EU
Simple model of linguistic-policy choice
Cost per language per person: average cost
vs cost per disenfranchised person
Optimal sequence of official languages
Political economy of a linguistic reform
EU Multilingualism



EU in 1957: 6 members and 4 languages
EU in 2007: 27 members and 23 languages
Some official languages are spoken by many


Some official languages are not


German (85 mn), English (62 mn), French (61mn)
Maltese, Irish (0.4-0.6 mn)
Some non-official languages spoken by many

Catalan (4.1 mn), Russian (4.2), Turkish (2.2 mn),
Arabic (1.6 mn)
EU Multilingualism: Implications



EU treaties, regulations and decisions must
be translated into all official languages
Most documents are prepared in English
(62%), French (26%) or German (3%)
Translation: 1.3 million pages per year (2002)


2710 translators and additional 1900 other staff
Interpretation: 50-60 meetings per day with 160 interpreters per meeting

962 interpreters, plus 200 other staff
EU Multilingualism: Implications



Long backlog of documents to be translated
Relay translations increasingly used
MEPs are asked to use simple sentences
and to avoid making jokes
EU Multilingualism: Future Prospects



Official status requested for Catalan, Valencian,
Galician and Basque.
Future enlargements: Croatian and Turkish.
Alternatives:






English only;
English, French and German only;
Esperanto;
English (for everyone except English native speakers)
and French (for English native speakers);
Those whose languages are used should compensate
the others;
Self financing.
EU Multilingualism





Language policy should facilitate
communication effectively and efficiently
Most nation-states implement restrictive
language policy: single language typical
EU: extensive multilingualism
This is effective but is it also efficient?
Costs and benefits need to be considered
Costs


EU25 at ‘full speed’: € 1,045 million per year
(17% of the administrative budget)
Erroneous and/or confusing translations



MEPs are asked to use simple sentences and to
avoid making jokes
Potential for disagreements about
interpretation of legal documents
Delays in implementation of legal/regulatory
decisions
Benefits: Preventing Linguistic
Disenfranchisement


A person is linguistically disenfranchised
(excluded) if the EU does not use a language
that they understand
Not all languages are equal: some are more
popular than others


Special Eurobaromenter 255: Europeans and their
Languages, 2005
Optimal language policy needs to reflect this
Model of Language Policy Choice

Union with n linguistic groups



Public good 





Language-dependent
Provided in a core language
Subsequently translated into other languages.
Translation can be full or partial


Population of group j is Nj
Population of the union is N= Nj.
j ranges between 0 and 1
Utility from receiving  in one’s own language:
U(j), U’(j)>0 and U’’(j)<0
Translation is costly: Cj=cj, c>0
Model of Language Policy Choice

Individual utility from translation of  under self-financing
U ( j ) 

c
Nj
Utility from translation of  under centralization
U () 

Nj
Optimal extent of translation, j, is chosen according to
U ' (*j ) 

c j
(n  1)c
N
and optimal extent of translation, , is chosen according to
(n  1)c
U ' ( ) 
N
*
Model of Language Policy Choice
1. If all groups are equally sized, full sharing is preferred by
all (except the core-language group):
c
nc (n  1)c


Nj N
N
2. Optimal extent of translation regime depends on group
size: full sharing results in over-provision of translation
for small groups and under-provision for large groups.
3. Groups of below-average size prefer full-sharing while
above-average ones prefer self-financing.
Data on Language Proficiency





Eurobaromenter 54: Special survey on
languages, 2000.
Candidate Countries Eurobarometer, 2001.
Special Eurobaromenter 255: Europeans and
their Languages, 2005
Respondents asked about mother’s tongue
and other languages that they speak well
Nationally representative surveys

we can extrapolate to get the number of speakers
of different languages in EU countries
Not All Languages Equal
Native
(1)
All
(2)
All (G/VG)
(3)
Multiplier
(3)/(1)
English
62.4
238.0
182.6
2.93
German
85.3
147.9
121.7
1.43
French
60.7
128.0
97.2
1.60
Italian
57.7
71.6
64.8
1.12
Spanish
39.7
67.2
54.1
1.36
Polish
39.2
41.9
40.9
1.04
Romanian
21.0
22.5
22.2
1.06
Dutch
21.9
25.2
24.0
1.10
4.2
35.3
22.4
5.33
Russian
Disenfranchisement



People are disenfranchised if the EU does
not use a language that they understand.
Only preventing disenfranchisement
considered
National pride, patriotism and international
recognition are ignored.
Disenfranchisement (EB 2000-01)
EU15
AC10
EU25
English only
45%
79%
50%
English-French
30%
77%
38%
English-German
32%
65%
37%
English-French-German
19%
64%
26%
Disenfranchisement corrected for
proficiency (EB 2005)
English
63
English-German
49
German
75
English-French
51
French
80
English-French-German
38
Italian
87
Spanish
89
Polish
92
Dutch
95
Russian
95
Cost per Language




Total cost: € 686 million in EU15, € 1,045
million in EU25.
Average cost per language per year:
€ 68.6 million in EU15 and € 55 million in
EU25.
Average cost per person:
€ 1.8 in EU15 and € 2.30 in EU25.
There are important differences across
languages.
Average Cost per Person/Language
German
French
English
Italian
Spanish
Polish
Dutch
Greek
Portuguese
Czech
Pop
90.1
64.5
62.3
57.6
39.4
38.6
21.9
11.3
10.8
10.3
Cost
0.6
0.9
0.9
1.0
1.4
1.4
2.5
4.9
5.1
5.3
Hungarian
Swedish
Slovak
Danish
Finish
Lithuanian
Latvian
Slovene
Estonian
Maltese
Pop
10.1
8.9
5.4
5.3
5.1
3.6
2.4
2.0
1.4
0.4
Cost
5.4
6.2
10.2
10.4
10.8
15.3
22.9
27.5
39.3
137.5
Cost per Disenfranchised Person

Average cost misleading




Calculation assumes that all speakers of nonofficial languages are disenfranchised
Alternative: cost per language (€ 55 million)
divided by the number of those who would be
disenfranchised if their language was left out
Alternative scenarios: from English only to
English-French-German
Static analysis, bargaining or sequencing not
taken into account
Cost per Disenfranchised Person
Total
Population
English
French
German
Italian
Polish
Spanish
Hungarian
Portuguese
Greek
Czech
62.3
64.5
90.1
57.6
38.6
39.4
10.1
10.8
11.3
10.3
Disenfranchised Population
(millions)
E
EF
EG
EFG
0
0
0
0
37.5
0
36.6
0
42.1
40.3
0
0
35.1
27.7
34.0
27.1
30.9
30.1
25.9
25.5
25.2
22.5
24.8
22.1
8.6
8.5
7.6
7.5
7.0
6.4
6.9
6.3
5.9
5.9
5.8
5.7
7.8
7.8
5.6
5.5
Cost per person disenfranchised
(EUR)
E
EF
EG
EFG
0
0
0
0
1.5
0
1.5
0
1.3
1.4
0
0
1.6
2.0
1.6
1.9
1.8
1.8
2.1
2.2
2.2
2.4
2.2
2.5
6.4
6.5
7.3
7.3
7.8
8.6
8.0
8.8
9.4
9.4
9.5
9.7
7.0
7.1
9.9
10.0
Cost per Disenfranchised Person
Total
Population
Slovak
Dutch
Lithuanian
Finnish
Latvian
Swedish
Estonian
Danish
Slovene
Maltese
5.4
21.9
3.6
5.1
2.4
8.9
1.4
5.3
2.0
0.4
Disenfranchised Population
(millions)
E
EF
EG
EFG
4.7
4.6
3.9
3.8
8.4
4.3
5.6
3.3
2.9
2.8
2.6
2.5
2.0
2.0
1.9
1.8
1.8
1.8
1.6
1.6
1.9
1.8
1.7
1.6
1.0
1.0
0.9
0.9
1.3
1.3
0.9
0.9
0.9
0.9
0.6
0.5
0.07
0.07
0.07
0.07
Cost per person disenfranchised
(EUR)
E
EF
EG
EFG
11.7
11.8
14.1
14.3
6.5
12.9
9.8
16.9
19.1
19.3
21.2
21.7
27.7
27.7
29.1
30.0
29.8
30.2
33.7
34.2
29.4
30.9
32.5
34.3
56.9
56.9
63.4
63.7
41.5
43.2
64.9
64.9
58.5
59.8
98.2
102.2
808.8 808.8 808.8
831.3
Optimal Sets of Official Languages

Selecting the optimal set of official languages




How many?
Which ones?
The optimal set of official languages should
maximize welfare (facilitate communication)
and minimize cost
For every m (1m23), we find the set of m
languages that minimizes disenfranchisement
( minimizes welfare loss)
Optimal Sets of Official Languages:
All Respondents
1
2
3
4
5
6
7
8
9
10a
10b
10c
EN
1+
GE
2+
FR
3+
IT
4+
SP
5+
PL
6+
RO
7+
HU
8+
PT
9+
CZ
9+
GR
9+
RU
62.6
49.3
37.8
29.5
22.4
16.4
12.9 10.9
9.2
7.7
7.7
7.7
11
12
13
14a
14b
15
16a
17
18a
18b
19
16b
10a+ 11 + 12 + 13 + 13 + 14a+ 15 + 15 + 15a 17 + 17 + 18a+
GR
BG
NL
FI
SW
SW
LT
SK + SK LV
DK
DK
6.2
5.0
4.0
3.3
3.3
2.7
2.2
2.2
1.7
1.3
1.3
1
Optimal Sets of Official Languages:
Respondents under 30
1
2
3
4
5
6
7
8
9
10 11a
EN
1+
FR
2+
GE
3+
IT
4+
SP
5+
PL
6+
RO
7+
HU
8+
PT
9+
CZ
44.6
34.5
25.8 19.9
14.4
10.4
7.8
6.3
5.1
3.9
14c
14d
12
13 14a
14b
14e
18
11a+ 12 + 13 + 13 + 13 + 13 + 13 +
BG
NL
RU
FI
SK
LT
LV
13 + FI/SK/LT/LV
2.3
1.8
1.4
1.5
1.5
1.5
1.5
0.7
11b
10 + 10 +
GR
BG
3.1
3.1
Optimal Sets of Official Languages

Selecting the optimal m:




Costs and benefits not expressed in the
same unit
23 (or more) official languages inefficient


Marginal benefits  lowering disenfranchisement
Marginal costs  monetary and non-monetary
High costs and large negative externalities
1-3 languages  excessive
disenfranchisement


63% with English only
38% with English-French-German
Optimal Sets of Official Languages
40
35
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Optimal Sets of Official Languages

6 languages: good intermediate solution



Modest disenfranchisement: 16%
Adding further languages brings only limited gains
However, political constraints crucial
Political Economy of Language-policy
Reform
At present, linguistic policies decided by
unanimity
Small countries benefit from crosssubsidization of translation costs by large
countries
Two possible scenarios for reform:



1.
2.
Reform designed so as to compensate losers
Decision-making rule changes  qualified
majority voting (QMV) instead of unanimity
Political Economy of Language-policy
Reform

Centralization:





Under-provision of translation for large countries
Over-provision for small countries
Majority of EU population would benefit from
moving from centralization to self-financing
Majority of EU countries would oppose such
reform
Reducing the number of official languages:
similar case
Political Economy of Language-policy
Reform
Countries
better off
under selffinancing
Countries
Population (%)
Groups (%)
Countries (%)
UK, IRL,
F, BE,
LUX, D,
AT, IT,
ES, PL
78
30
40
Countries with majority of population proficient in
core languages
E
UK, IRL,
D, NL,
FIN, S,
DK, SLO,
CY, MT
50
40
40
EF
UK, IRL,
D, F, BE,
LUX, IT,
NL, FIN,
S, DK,
SLO, CY,
MT
62
50
46
EG
UK, IRL,
D, AT,
NL, LUX,
FIN, S,
DK, SLO,
CY, MT
63
40
48
EFG
UK, IRL,
D, AT, F,
BE, LUX,
IT, NL,
FIN, S,
DK, SLO,
CY, MT
74
50
60
Language-policy Reform with
Compensation of Losers




Decentralization: countries get control over
funds earmarked for linguistic services
Giving countries discretion makes them
internalize the costs of the linguistic regime
EU budget unchanged but funds spent in a
way that maximizes aggregate welfare
Countries can keep the rents that they are
currently enjoying  politically feasible
Language-policy Reform under QMV

1.
2.
Alternative QMV scenarios:
Nice Treaty (min 14 states, 255/345 votes,
62% of EU population)
Lisbon Treaty (55% states, 65% pop)
Language-policy Reform under QMV
Acceptable
Disenfranchisement
Nice Treaty QMV
Lisbon Treaty QMV
All Respondents
10
11
11
20
10
10
30
9
10
40
9
8
50
7
5
Respondents under 30
10
9
9
20
7
5
30
7
5
40
5
3
50
4
2
Language-policy Reform under QMV

Six-language scenario not possible at present
and under present (NT) rules


Not even when assuming that relatively high
disenfranchisement rate is tolerable
May be feasible in the future or if QMV rules
change
Conclusions


Six-language scenario (EGFISP): 16%
disenfranchisement (10% for under 30s)
The same set results if we only consider
native speakers (i.e. if only pride is being
considered)


Includes languages of all ‘large countries’
Adding more languages : gains small and
typically limited to a single country
Conclusions



Political constraints likely to be crucial
In a generation of two (or if voting procedures
change), linguistic regime with 3-6 official
languages will be possible
Linguistic reform will change incentives for
acquiring linguistic skills.



If reform undertaken, adjustment will be temporary
Linguistic dynamics will be influenced by today’s
choice
Challenge of future enlargements (especially
Turkish)
Further Questions
1 Which languages should be used where?

EP, EU institutions, legal texts
Different rules may be necessary for different
areas or institutions
2 What happens to the remaining languages?
 Savings up to €55 mn per language
 Kept by the EU?
 …or transferred to member countries as
compensation?

Language and Communicative Benefits
Language serves three functions:

1.
2.
3.
Medium of exchange (communicate with others)
Store of value (to store useful information in
written/recorded form)
Tool of discrimination (exclude others by using a
language that they do not understand)
Economics of Languages literature focuses
mainly on the first two functions:


Communicative/economic benefits of speaking a
language
Communicative Benefits
Communicative benefits of languages
similar to other aspects of human capital
Costly investment



Monetary cost, time & effort, foregone earnings
Positive return


Ability to communicate and engage in economic
transactions with others
Spillover:


Return accrues also to the other party who has
not learned your language
Communicative Benefits
Formal modelling:
Selten and Pool (1991)

1.




Seminal contribution
Multiple languages, including artificial languages
Communicative benefits depend on the number
of people with whom one can communicate
Costs vary across individuals and langauges
Gabszewicz, Ginsburgh and Weber (2005)
2.

Simpler model: two languages/countries only
Communicative Benefits: Model




Gabszewicz, Ginsburgh and Weber (2005)
Two countries: i and j with Ni and Nj citizens
Heterogenous learning cost, θ, uniformly
distributed over [0,1] in each country
Learning another language is costly:
Ci(θ)=ciθ and Cj(θ)=cjθ; ci≠ cj

Communicative benefits proportional to
number of people with whom one can
communicate
Communicative Benefits: Model

Utility of unilingual citizen of i:
B(Ni+αjNj)=Ni+αjNj

Utility of bilingual citizen of i:
B(Ni+Nj)-ciθ =Ni+Nj-ciθ

Condition for learning language j:
Nj-ciθ ≥ αjNj

Highest-θ individual in i who learns j:
Nj-ciθ = αjNj
θ(αj)=min[(1-αj)Nj/ci, 1]
Communicative Benefits: Model

θ is uniformly distributed over [0,1]  share
of country i population who learn language j:
θ(αj)=αi

For country j
θ(αi)=αj


Define cost-adjusted communicative benefit
of country i citizen from learning j: bij = Nj/ci
Equilibrium given by:
αi = min[(1-αj)bij,1]
αj = min[(1- αi)bji,1]
Communicative Benefits: Model
Interior equilibrium:

αi = (1-αj)bij
αj = (1- αi)bji
Solution

αi* = [bij(1-bji)]/[1-bijbji]
αj* = [bji(1-bij)]/[1-bijbji]
Unique interior equilibrium exists when



bji,bji<1 (stable equilibrium)
or bji,bji>1 (unstable equilibrium)
Communicative Benefits:
Comparative Statics
The fraction of those learning the other
language is






decreasing in the learning cost of the other
language;
increasing in the learning cost of own language;
increasing in the population of the other country;
decreasing in own population size.
These predictions that can be tested
empirically
αj
αi
1
bij
bij
1
α*i
α*i
α*j
bji
1
αi
Figure 1. bij, bji < 1. Stable interior
equilibrium. No corner equilibria.
α*j
1
bji
αj
Figure 2. bij, bji > 1. Unstable interior
equilibrium. Two corner equilibria
(1,0) and (0,1).
Communicative Benefits:
Empirical Analysis
Ginsburgh, Ortuño-Ortín and Weber
(forthcoming):





Aggregate data proficiency in English, French,
German and Spanish in EU15 countries
log(αi)=β₀+β1log(Ni)+β2log(Nj)+β3log(dij)+uij
where dij is linguistic distance between
languages i and j
Own population: negative effect (except French)
Other country's population: positive effect
Linguistic distance (proxy for the cost of
learning): negative effect
Communicative Benefits:
Empirical Analysis
Population speaking language i (β1)
English
French
German
Spanish
-0.153∗
(0.021)
0.355∗
(0.138)
-0.361∗
(0.072)
0.032
(0.168)
All four
-0.058
(0.069)
0.625∗
(0.057)
Population speaking language j (β2)
Distance between i and j (β3)
-0.408∗
(0.082)
-0.512
(0.416)
-1.362∗
(0.214)
-0.560
(0.385)
-0.954∗
(0.200)
Intercept(β0)
0.733∗
(0.016)
0.193
(0.121)
0.586∗
(0.077)
0.091
(0.109)
0.080
(0.100)
French speaking population (β0F )
-0.112
(0.062)
German speaking population (β0G)
-0.233∗
(0.061)
Spanish speaking population (β0S)
-0.514∗
(0.050)
R2
0.919
0.599
0.910
0.232
0.758
No. of observations
11
12
11
12
46
Communicative Benefits:
Empirical Analysis




Individual data: Special Eurobarometer 243:
Females learn languages more often than
males
Propensity to learn foreign languages falls
with age – but increases again for retirees
Right-wing people more likely to speak
English, left-wing people more likely to
speak French
Communicative Benefits:
Empirical Analysis
Education, being self-employed, managerial
or white-collar worker, living in urban area
and being tall increase propensity to learn
languages
Large differences across countries:



positive correlation between the country-specific
intercepts and linguistic proximity: 0.43 for
English, 0.54 for French and 0.33 for German.
English
French
German
Italian
0.236***
(0.059)
0.457***
(0.084)
-0.045
(0.073)
0.368***
(0.162)
Age
-0.065***
(0.009)
0.005
(0.013)
-0.048***
(0.010)
0.007
(0.023)
Age sqrd
0.0003***
(0.0001)
0.0001
(0.0001)
0.0005***
(0.0001)
-0.0001
(0.0002)
Married
-0.065***
(0.047)
-0.048
(0.072)
-0.039
(0.057)
-0.361***
(0.131)
Left-Right
0.031***
(0.010)
-0.033**
(0.015)
0.017
(0.012)
-0.031
(0.025)
Sec. education
1.272***
(0.085)
1.014***
(0.118)
0.874
(0.104)
0.888***
(0.224)
Tert. Education
2.321***
(0.088)
1.831***
(0.126)
1.492***
(0.108)
1.377***
(0.248)
Still student
2.758***
(0.123)
2.437***
(0.187)
1.493***
(0.163)
1.394***
(0.343)
Self-employed
0.460***
(0.086)
0.507***
(0.130)
0.300***
(0.119)
0.347
(0.243)
Manager
1.118***
(0.073)
0.578***
(0.115)
0.725***
(0.094)
0.607***
(0.207)
White collar
0.520***
(0.071)
0.210*
(0.116)
0.402***
(0.096)
0.108
(0.224)
House person
0.059
(0.096)
-0.117
(0.149)
0.259**
(0.130)
-0.512*
(0.294)
Unemployed
0.128
(0.103)
0.089
(0.180)
0.032
(0.144)
0.024
(0.307)
Retired
0.177**
(0.090)
0.190
(0.135)
0.235**
(0.107)
0.184
(0.256)
Height
0.022***
(0.003)
0.013***
(0.005)
0.003
(0.004)
0.008
(0.009)
-0.091***
(0.026)
0.014
(0.057)
-0.032**
(0.015)
-0.052*
(0.031)
BMI sqrd
0.001***
(0.000)
-0.001
(0.001)
0.0003
(0.0002)
0.0005
(0.0004)
Small/medium town
0.305***
(0.050)
0.296***
(0.077)
0.101*
(0.062)
0.172
(0.140)
Large town
0.730***
(0.055)
0.376***
(0.084)
0.184***
(0.068)
0.183
(0.141)
Female
BMI
Spanish
Russian
Dutch
Female
0.202
(0.151)
0.102
(0.095)
-0.365
(0.268)
Age
0.011
(0.022)
0.153***
(0.016)
0.022
(0.037)
Age sqrd
-0.0002
(0.0002)
-0.0014***
(0.0002)
-0.0003
(0.0004)
Married
-0.293***
(0.122)
0.096
(0.076)
-0.264
(0.216)
0.007
(0.028)
0.023
(0.015)
0.067
(0.052)
Sec. education
0.313*
(0.180)
0.788***
(0.137)
0.459
(0.350)
Tert. Education
0.692***
(0.196)
1.430***
(0.145)
0.988***
(0.364)
Still student
1.363***
(0.289)
1.205***
(0.240)
1.281**
(0.541)
Self-employed
0.947***
(0.215)
-0.130
(0.144)
0.231
(0.414)
Manager
0.575***
(0.211)
0.355***
(0.121)
0.072
(0.373)
White collar
0.086
(0.221)
-0.052
(0.117)
0.253
(0.323)
House person
0.386
(0.242)
-0.190
(0.194)
0.608
(0.414)
Unemployed
0.234
(0.301)
-0.042
(0.161)
0.651
(0.401)
Retired
0.581***
(0.233)
-0.246*
(0.130)
0.228
(0.430)
Height
0.003
(0.008)
0.006
(0.005)
-0.023
(0.015)
BMI
-0.071*
(0.040)
-0.044**
(0.018)
0.016
(0.048)
BMI sqrd
0.0004
(0.0007)
0.0007***
(0.0002)
-0.0003
(0.0005)
0.104
(0.135)
0.135*
(0.081)
0.148
(0.220)
0.381***
(0.137)
0.190**
(0.088)
0.515**
(0.248)
Left-Right
Small/medium town
Large town
Languages and Discrimination
Speakers of foreign languages are excluded
from communication


Example: Cockney rhyming slang
Can be recognized by their speech/accent
Can be subject to discrimination





Bigotry: taste for discrimination
Price discrimination: eg foreigners pay higher
prices than locals
Cost-motivated discrimination
Languages and Discrimination
Lang (1986): model of wage discrimination
based on language





White employers
White or black workers who speak different
languages
Employer who hires blacks them needs to be
compensated for the cost of learning blacks’
language or for hiring bilingual supervisors
Wage discrimination occurs without bigotry or
employers having a taste for discrimination
Languages and Discrimination
Puzzle: different languages/dialects persist
despite strong incentives for harmonization
Akerlof and Kranton (2000): model of
identity




People behavior shaped by identity-specific
social norms (race, ethnicity, gender)
Deviation are punished by social sanctions
Languages and Discrimination
Berman (2000): model of religious sect
membership (Ultra-Othodox Jews)



Costly observable behavior demonstrates
commitment
This eliminates free-riding on club goods (eg
community support networks and insurance)
Native language skills  group identification




Favorable treatment from group members
Avoidance of discrimination or predation
Language skills acquired easily in childhood and
costly in adult life  free-riding difficult
Returns to Linguistic Skills
Linguistic skills make transactions easier
and less costly
Implications for labor-market returns, trade
flows, investment, migration, growth, etc.
Alesina and La Ferrara (2005 JEL):
linguistically diverse countries grow more
slowly





Exception: developed countries
Slower growth may be due to inter-ethnic conflict
rather than linguistic diversity
Labor Market Returns
Similar to return to other aspects of human
capital such as education
Most studies consider immigrants



Immigrants who speak the destination-country
language earn up to 20% more than immigrants
who do not (Chiswick and Miller, 2002, JPopE;
Chiswick and Miller, 2007, IZA DP 2664)
Labor Market Returns
Ginsburgh and Prieto-Rodriguez (2006):
returns to language use for European
workers (not immigrants)




2001 wave of the European Community
Household Panel (ECHP)
Survey asked about languages that
respondents use at their workplace (up to 2)
Returns to English, French, German, Italian
and Spanish in A, DK, FIN, F, D, GR, IT, P,
ES
Labor Market Returns
Relative scarcity of languages: linguistic
disenfranchisement rate




0 if the respondent does not use the language at
work
Labor-market return dependent on how many
other people speak the language in the same
country
instrumented with lagged disenfranchisement
rate (2000)
Labor Market Returns
Return to speaking English





Lowest: 5% in Denmark
Highest: 39% in Spain
Return to speaking French: up to 49% (in
Spain)
Return to speaking German up to 60% (also
in Spain)
Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez)
Austria
Denmark
Finland
France
Germany
Greece
Italy
Portugal
Spain
English
0.15
0.05
0.20
0.29
0.23
0.15
0.18
0.31
0.39
French
0.25
0.18
0.50
0.00
0.42
0.24
0.21
0.34
0.49
German
0.00
0.17
0.47
0.46
0.00
0.24
0.28
0.46
0.60
Italian
0.26
0.18
0.50
0.48
0.49
0.25
0.00
0.47
0.60
Spanish
0.28
0.18
0.50
0.43
0.49
0.26
0.28
0.45
0.00
Dutch
0.28
0.19
0.50
0.51
0.49
0.26
0.29
0.47
0.61
Languages and Migration



Parsons, Skeldon, Walmsley and Winters
(2007, World Bank Policy Research Paper
4165): data on migration flow
Over half of global migration flows is
between countries sharing a common
language (Arabic, Chinese, English, French,
Portuguese or Spanish)
Over a quarter of global migration flows is
between English-speaking countries
Languages and Trade





Fidrmuc and Fidrmuc (2009):
Gravity-model of trade flows
Control for probability that two randomly
chosen people from two different countries
are able to communicate in the same
language
Both native and non-native speakers
considered
Effect on trade strongly significant and large
Results: EU 15
Variable`
(1)
(2)
(3)
(4)
(5)
(6)
OLS
2SLS
OLS
2SLS
OLS
2SLS
15.175
***
15.049
***
15.415
***
9.652
***
14.573
***
13.925
***
0.897
***
0.904
***
0.885
***
0.888
***
1.007
***
1.013
***
-0.748
***
-0.741
***
-0.761
***
-0.345
**
-0.754
***
-0.710
***
0.471
***
0.463
***
0.491
***
0.566
***
0.478
***
0.427
***
English
0.543
***
0.449
***
0.570
***
0.558
**
0.786
***
0.492
***
German
0.581
***
0.587
***
0.853
***
-0.137
0.336
***
-0.197
*
French
0.186
**
0.196
**
0.101
-0.474
***
Swedish
0.279
***
0.310
***
0.235
**
-0.263
***
-0.242
***
-0.340
1.152
***
1.449
***
1.074
Intercept
GDP
Distance
Contiguity
Official languages
Dutch
***
-0.033
0.442
**
0.218
**
0.362
***
***
-1.188
***
-0.287
***
-0.149
**
***
2.015
***
19.552
***
0.396
***
1.349
***
-11.652
Proficiency
English
French
0.080
German
-0.408
***
1.271
Cumulativea
N
1470
1470
1470
1470
1470
1470
Adjusted R2
0.974
0.974
0.974
0.906
0.973
0.971
Results: NMS/AC
Variable
(1)
(2)
(3)
(4)
(5)
(6)
OLS
2SLS
OLS
2SLS
OLS
2SLS
19.372
***
18.866
0.573
***
0.576
-1.024
***
Former Fed.
2.292
Contiguity
Intercept
GDP
Distance
***
17.119
***
11.993
**
0.566
***
0.561
-1.007
***
-0.817
***
-0.314
***
2.306
***
1.478
***
0.765
0.531
***
0.519
***
0.650
***
5.074
***
10.566
***
5.182
***
***
**
19.176
***
18.581
***
0.574
**
0.576
**
-1.001
***
-0.967
***
***
2.299
***
2.317
***
0.861
***
0.538
***
0.533
***
8.667
***
82.753
***
7.330
***
4.978
***
9.442
***
Proficiency
English
German
13.381
Russian
3.748
*
***
Cumulative
N
1254
1254
1254
1254
1254
1254
Adjusted R2
0.850
0.847
0.858
0.844
0.850
0.848
Results: All Countries
Variable
(1)
(2)
(3)
(4)
(5)
(6)
OLS
2SLS
OLS
2SLS
OLS
2SLS
Official languages
English
0.715
***
0.886
***
0.739
***
0.638
***
0.802
***
0.888
***
German
0.571
***
0.567
***
0.910
***
7.400
***
0.337
***
0.490
***
French
0.056
-4.529
***
-0.160
Greek
2.333
***
2.322
***
2.316
***
2.289
***
2.333
***
2.324
***
Swedish
0.162
***
0.144
**
0.134
**
-0.128
0.162
**
0.147
**
-0.622
***
-0.621
***
-0.638
***
-1.827
***
-0.614
***
-0.619
***
0.664
***
0.139
0.569
***
1.525
**
6.387
**
0.386
***
0.128
Dutch
0.041
0.230
-0.028
Proficiency
English
French
-0.315
German
-0.470
***
-9.597
***
Russian
1.603
***
2.147
***
Cumulativea
N
5634
5634
5634
5634
5634
5634
Adjusted R2
0.930
0.930
0.931
0.904
0.930
0.930
Languages and Trade


Increasing English proficiency in all EU15
countries by 10 percentage points
(keeping UK and Irish proficiency levels
constant)  15% increase in intra-EU15
trade
Bringing all countries to level of English
proficiency of the Netherlands  70%
increase in EU15 trade by 70%.
Conclusions
Communicative benefits an important
determinant of language learning
Choice to learn another language reflects
rational consideration (costs and benefits)
Language skills have positive returns






Individual level (labor-market returns)
Aggregate level (trade)
Social returns: language helps shape
ethnic identity
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Economics of Migration