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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 European Union

Country 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

UK 6 2 9 1 2 0 0 0 0 18 6

EU27 24.4 7.9 7.9 1.3 3.1 0.4 0 3.6 0.5 39 14

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

EU27 37.4 24.9 19.9 13.3 11.1 8.4 4.9 4.6 0.5

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 Outline

1. Multilingualism in the EU

2. Simple model of linguistic-policy choice

3. Cost per language per person: average cost vs cost per disenfranchised person

4. Optimal sequence of official languages

5. 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

German (85 mn), English (62 mn), French (61mn) Some official languages are not

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 1-

60 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

Population of group j is Nj Population of the union is N= Nj.

Public good Language-dependent Provided in a core language Subsequently translated into other languages.

Translation can be full or partial 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=cj, c>0

Model of Language Policy Choice

Individual utility from translation of under self-financing

j

jj N

cU

)(

Optimal extent of translation, j, is chosen according to

Utility from translation of under centralization

N

cnU

)1()(

and optimal extent of translation, , is chosen according to

N

cnU

)1()(' *

jj N

cU )(' *

Model of Language Policy Choice

1. If all groups are equally sized, full sharing is preferred by all (except the core-language group):

N

cn

N

nc

N

c

j

)1(

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

Russian 4.2 35.3 22.4 5.33

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 Pop Cost Pop Cost German 90.1 0.6 Hungarian 10.1 5.4 French 64.5 0.9 Swedish 8.9 6.2 English 62.3 0.9 Slovak 5.4 10.2 Italian 57.6 1.0 Danish 5.3 10.4 Spanish 39.4 1.4 Finish 5.1 10.8 Polish 38.6 1.4 Lithuanian 3.6 15.3 Dutch 21.9 2.5 Latvian 2.4 22.9 Greek 11.3 4.9 Slovene 2.0 27.5 Portuguese 10.8 5.1 Estonian 1.4 39.3 Czech 10.3 5.3 Maltese 0.4 137.5

Cost per Disenfranchised Person Average cost misleading

Calculation assumes that all speakers of non-official 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 Disenfranchised Population

(millions) Cost per person disenfranchised

(EUR) E EF EG EFG E EF EG EFG

English 62.3 0 0 0 0 0 0 0 0

French 64.5 37.5 0 36.6 0 1.5 0 1.5 0 German 90.1 42.1 40.3 0 0 1.3 1.4 0 0 Italian 57.6 35.1 27.7 34.0 27.1 1.6 2.0 1.6 1.9

Polish 38.6 30.9 30.1 25.9 25.5 1.8 1.8 2.1 2.2 Spanish 39.4 25.2 22.5 24.8 22.1 2.2 2.4 2.2 2.5 Hungarian 10.1 8.6 8.5 7.6 7.5 6.4 6.5 7.3 7.3

Portuguese 10.8 7.0 6.4 6.9 6.3 7.8 8.6 8.0 8.8 Greek 11.3 5.9 5.9 5.8 5.7 9.4 9.4 9.5 9.7

Czech 10.3 7.8 7.8 5.6 5.5 7.0 7.1 9.9 10.0

Cost per Disenfranchised Person

Total

Population Disenfranchised Population

(millions) Cost per person disenfranchised

(EUR) E EF EG EFG E EF EG EFG

Slovak 5.4 4.7 4.6 3.9 3.8 11.7 11.8 14.1 14.3 Dutch 21.9 8.4 4.3 5.6 3.3 6.5 12.9 9.8 16.9 Lithuanian 3.6 2.9 2.8 2.6 2.5 19.1 19.3 21.2 21.7 Finnish 5.1 2.0 2.0 1.9 1.8 27.7 27.7 29.1 30.0 Latvian 2.4 1.8 1.8 1.6 1.6 29.8 30.2 33.7 34.2 Swedish 8.9 1.9 1.8 1.7 1.6 29.4 30.9 32.5 34.3 Estonian 1.4 1.0 1.0 0.9 0.9 56.9 56.9 63.4 63.7 Danish 5.3 1.3 1.3 0.9 0.9 41.5 43.2 64.9 64.9 Slovene 2.0 0.9 0.9 0.6 0.5 58.5 59.8 98.2 102.2 Maltese 0.4 0.07 0.07 0.07 0.07 808.8 808.8 808.8 831.3

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 (1m23), 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

EN1 + GE

2 + FR

3 + IT

4 + SP

5 + PL

6 + RO

7 + HU

8 + PT

9 + CZ

9 + GR

9 + RU

62.6 49.337.8

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 16b 17 18a 18b 19

10a+ GR

11 + BG

12 + NL

13 + FI

13 +

SW

14a+

SW

15 + LT

15 + SK

15a+ SK

17 + LV

17 + DK

18a+ 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 301 2 3 4 5 6 7 8 9 10 11a 11b

EN1 + FR

2 + GE

3 + IT

4 + SP

5 + PL

6 + RO

7 + HU

8 + PT

9 + CZ

10 + GR

10 + BG

44.6 34.525.8

19.9 14.4 10.4 7.8 6.3 5.1 3.9 3.1 3.1

12 13 14a 14b 14c 14d 14e 18

11a+ BG

12 + NL

13 + RU

13 + FI

13 + SK

13 + LT

13 + LV

13 + FI/SK/LT/LV

2.3 1.8 1.4 1.5 1.5 1.5 1.5 0.7

Optimal Sets of Official Languages Selecting the optimal m:

Marginal benefits lowering disenfranchisement Marginal costs monetary and non-monetary

Costs and benefits not expressed in the same unit

23 (or more) official languages inefficient 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

0

5

10

15

20

25

30

35

40

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 cross-

subsidization of translation costs by large countries

Two possible scenarios for reform: 1. Reform designed so as to compensate losers2. 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 with majority of population proficient in core languages

Countries better off under self-financing

E EF EG EFG

Countries

UK, IRL, F, BE, LUX, D, AT, IT, ES, PL

UK, IRL, D, NL, FIN, S, DK, SLO, CY, MT

UK, IRL, D, F, BE, LUX, IT, NL, FIN, S, DK, SLO, CY, MT

UK, IRL, D, AT, NL, LUX, FIN, S, DK, SLO, CY, MT

UK, IRL, D, AT, F, BE, LUX, IT, NL, FIN, S, DK, SLO, CY, MT

Population (%) 78 50 62 63 74 Groups (%) 30 40 50 40 50 Countries (%) 40 40 46 48 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 Alternative QMV scenarios:1. Nice Treaty (min 14 states, 255/345 votes,

62% of EU population)2. 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. Medium of exchange (communicate with others)2. Store of value (to store useful information in

written/recorded form)3. 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:

1. Selten and Pool (1991) 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

2. Gabszewicz, Ginsburgh and Weber (2005) 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

Solutionαi* = [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

αi

bij

1

α*i

α*j bji 1

αj

Figure 1. bij, bji < 1. Stable interior

equilibrium. No corner equilibria.

αi

bij

1

α*i

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

English French German SpanishAll four

Population speaking language i (β1) -0.153∗(0.021)

0.355∗(0.138)

-0.361∗(0.072)

0.032(0.168)

-0.058(0.069)

Population speaking language j (β2) 0.625∗(0.057)

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

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

Female 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)

BMI -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)

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)

Left-Right 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)

Small/medium town 0.104 (0.135) 0.135* (0.081) 0.148 (0.220)

Large town 0.381*** (0.137) 0.190** (0.088) 0.515** (0.248)

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)


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


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)


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

Intercept 15.175 *** 15.049 *** 15.415 *** 9.652 *** 14.573 *** 13.925 ***

GDP 0.897 *** 0.904 *** 0.885 *** 0.888 *** 1.007 *** 1.013 ***

Distance -0.748 *** -0.741 *** -0.761 *** -0.345 ** -0.754 *** -0.710 ***

Contiguity 0.471 *** 0.463 *** 0.491 *** 0.566 *** 0.478 *** 0.427 ***

Official languages

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 -11.652 *** -0.033 -0.474 ***

Swedish 0.279 *** 0.310 *** 0.235 ** 0.442 ** 0.218 ** 0.362 ***

Dutch -0.263 *** -0.242 *** -0.340 *** -1.188 *** -0.287 *** -0.149 **

Proficiency

English 1.152 *** 1.449 *** 1.074 *** 2.015 ***

French 0.080 19.552 ***

German -0.408 *** 1.271

Cumulativea 0.396 *** 1.349 ***

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)


Intercept 19.372 *** 18.866 *** 17.119 *** 11.993 *** 19.176 *** 18.581 ***

GDP 0.573 *** 0.576 ** 0.566 *** 0.561 ** 0.574 ** 0.576 **

Distance -1.024 *** -1.007 *** -0.817 *** -0.314 -1.001 *** -0.967 ***

Former Fed. 2.292 *** 2.306 *** 1.478 *** 0.765 *** 2.299 *** 2.317 ***

Contiguity 0.531 *** 0.519 *** 0.650 *** 0.861 *** 0.538 *** 0.533 ***

Proficiency

English 5.074 *** 10.566 *** 5.182 *** 8.667 ***

German 13.381 * 82.753 ***

Russian 3.748 *** 7.330 ***

Cumulative 4.978 *** 9.442 ***

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)


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 0.041 0.230 -4.529 *** -0.160 -0.028

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 **

Dutch -0.622 *** -0.621 *** -0.638 *** -1.827 *** -0.614 *** -0.619 ***

Proficiency

English 0.664 *** 0.139 0.569 *** 1.525 **

French -0.315 6.387 **

German -0.470 *** -9.597 ***

Russian 1.603 *** 2.147 ***

Cumulativea 0.386 *** 0.128

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