Multilingualism and Optimal Language Policy in the EU

1
Multilingualism and Optimal Language Policy in
the EU

• Jan Fidrmuc
• Brunel University

2
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.

3
Worldwide Worldwide Worldwide Worldwide European Union European Union European Union 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
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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

5
Mothers 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
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 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
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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
8
English
9
French
10
German
11
Russian
12
Stylized Facts

• Large differences across age cohorts
• Only English seems to improve its relative
  standing over time

13

All 15-29 30-44 45-60 gt 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
           
14
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

15
Useful Language Useful Language Useful Language Useful Language Children Should Learn Children Should Learn Children Should Learn 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
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EU Multilingualism and Optimal Language Policy

• 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

18
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)

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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

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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

23
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.

24
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

25
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

26
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

27
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 ones own language
  U(?j), U(?j)gt0 and U(?j)lt0
• Translation is costly Cjc?j, cgt0

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Model of Language Policy Choice

• Individual utility from translation of ? under
  self-financing

• Optimal extent of translation, ?j, is chosen
  according to

• Utility from translation of ? under
  centralization

• and optimal extent of translation, ?, is chosen
  according to

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Model of Language Policy Choice

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

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.
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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 mothers 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

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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
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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.

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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
34
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
35
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.

36
Average Cost per Person/Language
37
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

38
Cost per Disenfranchised Person
39
Cost per Disenfranchised Person
40
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)

41
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 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
42
Optimal Sets of Official Languages Respondents
under 30
1 2 3 4 5 6 7 8 9 10 11a 11b
EN 1 FR 2 GE 3 IT 4 SP 5 PL 6 RO 7 HU 8 PT 9 CZ 10 GR 10 BG
44.6 34.5 25.8 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 13 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
43
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

44
Optimal Sets of Official Languages
45
Optimal Sets of Official Languages

• 6 languages good intermediate solution
• Modest disenfranchisement 16
• Adding further languages brings only limited
  gains
• However, political constraints crucial

46
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
• Reform designed so as to compensate losers
• Decision-making rule changes ? qualified majority
  voting (QMV) instead of unanimity

47
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

48
Political Economy of Language-policy Reform
49
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

50
Language-policy Reform under QMV

• Alternative QMV scenarios
• Nice Treaty (min 14 states, 255/345 votes, 62 of
  EU population)
• Lisbon Treaty (55 states, 65 pop)

51
Language-policy Reform under QMV
Acceptable Disenfranchisement Nice Treaty QMV Lisbon Treaty QMV
All Respondents All Respondents
10 11 11
20 10 10
30 9 10
40 9 8
50 7 5
Respondents under 30 Respondents under 30
10 9 9
20 7 5
30 7 5
40 5 3
50 4 2
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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

53
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

54
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 todays
  choice
• Challenge of future enlargements (especially
  Turkish)

55
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?

56
Language and Communicative Benefits

• Language serves three functions
• 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

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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

59
Communicative Benefits

• Formal modelling
• 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
• Gabszewicz, Ginsburgh and Weber (2005)
• Simpler model two languages/countries only

60
Communicative Benefits Model

• Gabszewicz, Ginsburgh and Weber (2005)
• Two countries i and j with Ni and Nj citizens
• Heterogenous learning cost, ?, uniformly
  distributed over 0,1 in each country
• Learning another language is costly
• Ci(?)ci? and Cj(?)cj? ci? cj
• Communicative benefits proportional to number of
  people with whom one can communicate

61
Communicative Benefits Model

• Utility of unilingual citizen of i
• B(NiajNj)NiajNj
• Utility of bilingual citizen of i
• B(NiNj)-ci? NiNj-ci?
• Condition for learning language j
• Nj-ci? ajNj
• Highest-? individual in i who learns j
• Nj-ci? ajNj
• ?(aj)min(1-aj)Nj/ci, 1

62
Communicative Benefits Model

• ? is uniformly distributed over 0,1 ? share of
  country i population who learn language j
• ?(aj)ai
• For country j
• ?(ai)aj
• Define cost-adjusted communicative benefit of
  country i citizen from learning j bij Nj/ci
• Equilibrium given by
• ai min(1-aj)bij,1
• aj min(1- ai)bji,1

63
Communicative Benefits Model

• Interior equilibrium
• ai (1-aj)bij
• aj (1- ai)bji
• Solution
• ai bij(1-bji)/1-bijbji
• aj bji(1-bij)/1-bijbji
• Unique interior equilibrium exists when
• bji,bjilt1 (stable equilibrium)
• or bji,bjigt1 (unstable equilibrium)

64
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

65
ai
aj
1
bij
1
bij
ai
ai

ai
aj bji 1
aj
aj 1 bji
Figure 1. bij, bji lt 1. Stable interior equilibrium. No corner equilibria.
Figure 2. bij, bji gt 1. Unstable interior equilibrium. Two corner equilibria (1,0) and (0,1).
66
Communicative Benefits Empirical Analysis

• Ginsburgh, Ortuño-Ortín and Weber (forthcoming)
• Aggregate data proficiency in English, French,
  German and Spanish in EU15 countries
• log(ai)ß0ß1log(Ni)ß2log(Nj)ß3log(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

67
Communicative Benefits Empirical Analysis
English French German Spanish All four
Population speaking language i (ß1) -0.153 (0.021) 0.355 (0.138) -0.361 (0.072) 0.032 (0.168) -0.058 (0.069)
Population speaking language j (ß2) 0.625 (0.057)
Distance between i and j (ß3) -0.408 (0.082) -0.512 (0.416) -1.362 (0.214) -0.560 (0.385) -0.954 (0.200)
Intercept(ß0) 0.733 (0.016) 0.193 (0.121) 0.586 (0.077) 0.091 (0.109) 0.080 (0.100)
French speaking population (ß0F ) -0.112 (0.062)
German speaking population (ß0G) -0.233 (0.061)
Spanish speaking population (ß0S) -0.514 (0.050)
R2 0.919 0.599 0.910 0.232 0.758
No. of observations 11 12 11 12 46
68
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

69
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.

70
English English French French German German Italian 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)
71
Spanish Spanish Russian Russian Dutch 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)
72
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

73
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

74
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

75
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

76
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

77
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)

78
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

79
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)

80
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)

81
Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) Returns to using languages in the workplace (Ginsburgh and Prieto-Rodriguez) 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
82
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

83
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

84
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 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
85
Results NMS/AC
Variable (1) (2) (3) (4) (5) (6)
OLS 2SLS OLS 2SLS OLS 2SLS
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
86
Results All Countries
Variable (1) (2) (3) (4) (5) (6)
OLS 2SLS OLS 2SLS OLS 2SLS
Official languages 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
87
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.

88
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