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Jan Fidrmuc Jarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and 2 nd FIW-Research Conference „International Economics“ Vienna University of Economics December 12, 2008 Foreign Languages and Trade
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Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Dec 21, 2015

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Page 1: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Jan Fidrmuc Jarko Fidrmuc

Brunel University, CEDI, CEPR and WDI

University of Munich, Comenius University and CESifo

2nd FIW-Research Conference „International Economics“Vienna University of EconomicsDecember 12, 2008

Foreign Languages and Trade

Page 2: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Introduction

Do languages affect trade? Easier communication lower

transaction costs greater trade Trade analysis (gravity model)

typically accounts for common official languageE.g. Rose (2000): common

language increases trade by 50%

Page 3: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Introduction (cont’d)

Gravity models: official languages only

Dummy variables, not proficiency Proficiency varies across countries

E.g. French in France, Belgium, Luxembourg, Switzerland, Canada,…

Other languages besides official ones matter tooNon-official indigenous languagesForeign languages

Page 4: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Introduction (cont’d)

Rauch (1999, 2001), Rauch and Trindade (2002), Bandyopadhyay, Coughlin and Wall (2008)Ethnic-networks increase tradeRauch and Trindade (2002):

ethnic Chinese networks in SE Asia increase trade by at least 60%

Page 5: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Introduction (cont’d)

Mélitz (2008)Official and non-official

indigenous languagesLanguage impact measured using

dummy variables (if official or spoken by more than 20%) or communicative probability

Only indigenous languages (Ethnologue database)

Page 6: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Our Contribution

First to study effect of native and foreign (learned) languages alikeTrade often relies on

communication in non-native languages

Unique extensive dataset on language proficiency in the EU

Non-linearity Old vs new Europe Role of English

Page 7: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Data

Special Eurobarometer 255: Europeans and their Languages, November - December 2005

Nationally representative surveys; only EU nationals included

Mother’s tongue(s) and up to 3 other languages that they speak well enough to have a conversation

Self-assessed proficiency: basic, good, very good

Trade flows: 2001-07

Page 8: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

English (good/very good skills)

French (good/very good skills)

Page 9: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

German (good/very good skills)

Russian (good/very good skills)

Page 10: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Spanish (good/very good skills)

Italian (good/very good skills)

Page 11: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Gravity Model

Gravity model methodology following Baldwin and Taglioni (2006)

Trade between i and j, Tijt, and output of i and j, yit and yjt,, measured in nominal US$

Distance between i and j: dij Common border and common

history dummies: bij and fij

ijt

F

fijff

D

dijddijijijjtitjtitijt PLfbdyyT ,,4321

Page 12: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Gravity Model (cont’d)

Common official-language dummies: Ldij

Communication probabilities: Pfij Time-varying country dummies:

Country-specific time-invariant and time-varying omitted variables

Country-specific measurement problems

ijt

F

fijff

D

dijddijijijjtitjtitijt PLfbdyyT ,,4321

Page 13: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Communicative Probability

Probability that two random individuals from two different countries speak the same language

1. English2. Languages spoken by at least 10%

of population in at least 3 countries German, French, Russian

3. Languages spoken by at least 4% of population in at least 3 countries

Italian, Spanish, Hungarian, Swedish

Page 14: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Communicative Probability

EU15 NMS/ACs EU29

English 22 11 17

German 7 2 5

French 5 1 3

Page 15: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU15

Common official language and communicative probability raise trade

English especially important Accounting for proficiency in English

lowers official-language effect French/German: weak/mixed results Spanish/Italian/Swedish: seemingly

strong effects Most country pairs’ at/close to zero

Page 16: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU 15Variable (1) (2) (3) (4) (5) (6) GDP 1.004 *** 0.897 *** 0.885 *** 0.880 *** 0.895 *** 1.007 ***

Distance -0.772 *** -0.748 *** -0.761 *** -0.750 *** -0.668 *** -0.754 ***

Contiguity 0.499 *** 0.471 *** 0.491 *** 0.364 *** 0.157 *** 0.478 ***

Official Languages

English 0.908 *** 0.543 *** 0.570 *** 0.662 *** 0.775 *** 0.786 ***

German 0.556 *** 0.581 *** 0.853 *** 0.841 *** 0.667 *** 0.336 ***

French 0.150 ** 0.186 ** 0.101 0.295 0.788 *** -0.033

Swedish 0.158 0.279 *** 0.235 ** 0.323 *** -2.974 *** 0.218 **

Dutch -0.344 *** -0.263 *** -0.340 *** -0.180 ** 0.150 *** -0.287 ***

Proficiency English 1.152 *** 1.074 *** 0.944 *** 1.022 *** French 0.080 0.065 -0.321 German -0.408 *** -0.274 *** 0.102 Italian 8.724 *** 11.687 *** Spanish 8.938 *** 12.071 *** Swedish 19.793 *** Cumulative EFG 0.396 ***

N 1470 1470 1470 1470 1470 1470 Adjusted R2 0.972 0.974 0.974 0.975 0.980 0.973

Page 17: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU15, magnitude Consider column (5)

Average effect in EU15: 25% increase due to English proficiency (22% average communicative probability)

UK-IRL trade increased 2.2 times because English is official language and 2.7 times because of English proficiency 5.8 fold increase overall

NL-S trade increased 1.7 times and NL-UK trade more than doubled

Page 18: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: NMS/AC

English proficiency raises trade Large coefficient estimate but

proficiency is relatively low Average impact: 77% increase

(11% average communicative probability)

German and Russian also significant Average impact of German: 30%

Page 19: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: NMS/AC

Variable (1) (2) (3) (4) (5)

GDP 0.571 *** 0.573 *** 0.566 *** 0.566 *** 0.574 **

Distance -1.039 *** -1.024 *** -0.817 *** -0.820 *** -1.001 ***

Former Federations 2.278 *** 2.292 *** 1.478 *** 1.471 *** 2.299 ***

Contiguity 0.543 *** 0.531 *** 0.650 *** 0.654 *** 0.538 ***

Proficiency:

English 5.074 *** 5.182 *** 5.188 ***

German 13.381 * 13.239 *

Russian 3.748 *** 3.745 ***

Hungarian -0.309

Cumulative 4.978 ***

N 1254 1254 1254 1254 1254

Adjusted R2 0.847 0.850 0.858 0.858 0.850

Page 20: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU29

Weaker results English significant but impact less

powerful than in either EU15 or NMS/ACAverage English proficiency (17%)

raises trade by 11% French not significant and German

negative impact Remaining languages significant

Page 21: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU29

Variable (1) (2) (3) (4) (5) (6)

GDP 0.987 *** 0.767 *** 0.769 *** 0.773 *** 0.773 *** 0.843 ***

Distance -1.038 *** -1.029 *** -1.035 *** -1.025 *** -1.019 *** -1.028 ***

Former Federations 2.460 *** 2.455 *** 1.961 *** 1.988 *** 2.043 *** 2.466 ***

Contiguity 0.320 *** 0.325 *** 0.339 *** 0.328 *** 0.270 *** 0.317 ***

EU 0.263 *** 0.235 *** 0.216 *** 0.218 *** 0.210 *** 0.246 ***

Official languages

English 0.931 *** 0.715 *** 0.739 *** 0.752 *** 0.786 *** 0.802 ***

German 0.566 *** 0.571 *** 0.910 *** 0.893 *** 0.838 *** 0.337 ***

French 0.037 0.056 0.230 0.240 0.295 -0.160

Greek 2.319 *** 2.333 *** 2.316 *** 2.330 *** 2.359 *** 2.333 ***

Swedish 0.140 ** 0.162 *** 0.134 ** 0.153 ** -2.156 *** 0.162 **

Dutch -0.621 *** -0.622 *** -0.638 *** -0.610 *** -0.543 *** -0.614 ***

Proficiency:

English 0.664 *** 0.569 *** 0.595 *** 0.508 ***

French -0.315 -0.283 -0.276

German -0.470 *** -0.436 *** -0.330 **

Russian 1.603 *** 1.559 *** 1.557 ***

Italian 1.637 *** 1.706 ***

Spanish 2.645 ** 3.444 ***

Swedish 12.635 ***

Hungarian 3.577 ***

Cumulative 0.386 ***

N 5634 5634 5634 5634 5634 5634

Adjusted R2 0.930 0.930 0.931 0.931 0.931 0.930

Page 22: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: Discussion

Possible explanations for weaker EU29 results:

1. Heterogeneity: EU15 vs NMS/AC Trade between EU15 and NMS/AC

still below potential Different political, economic and

linguistic legacy NMS/AC have not yet reached

their new linguistic equilibrium

2. Effect of languages not linear

Page 23: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: Non-linear Effect

Add squared communicative probability Hump-shaped effect of English

diminishing returns Peak at around 70% probability Quadratic term not significant in

NMS/AC and EU29 French/German: weaker/negative effect Other languages: quadratic terms not

significant in NMS/AC and EU29Except Russian: U-shaped in NMS/AC

Page 24: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: Non-linear Effect EU15Variable (1) (2) (3) (4) (5)

Intercept GDP Distance Contiguity included but not reported

Official languages

English 0.908 *** 1.369 *** 1.672 *** 1.749 *** 1.601 ***

German 0.556 *** 0.661 *** 0.030 0.015 0.325 ***

French 0.150 * 0.292 *** 0.400 0.514 1.003 ***

Swedish 0.158 ** 0.362 *** 0.256 *** 0.279 *** 17.057 ***

Dutch -0.344 *** -0.283 *** -0.404 *** -0.286 *** 0.030

Proficiency:

English 5.157 *** 6.005 *** 6.008 *** 5.178 ***

French 1.119 *** 1.220 *** 0.040 **

German -2.633 *** -2.499 *** -1.108 **

Italian 46.564 *** 33.852 ***

Spanish 10.856 *** 11.446 ***

Swedish 80.606 ***

Proficiency (Quadratic):

English -3.580 *** -4.481 *** -4.580 *** -3.690 ***

French -1.552 *** -1.712 *** -0.872 **

German 3.230 *** 3.172 *** 1.571 ***

Italian -748.687 *** -461.089 ***

Spanish -75.874 ** -52.094

Swedish -857.98 ***

N 1470 1470 1470 1470 1470

Adjusted R2 0.972 0.975 0.977 0.978 0.983

Page 25: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Non-linear Effect: EU15

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

english

french

german

Page 26: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Robustness: EU15

Results potentially driven by outliersCountry pairs with especially

high/low trade Effect of English proficiency

highest around 50th percentile (median regression)

Effect of foreign languages not due to outliers

Page 27: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU 15, Quantile Regressions

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Q5 Q15 Q25 Q35 Q45 Q55 Q65 Q75 Q85 Q95

Quantile Regression

OLS

Page 28: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Results: EU 15, Quantile Regressions

OLS Q10 Q25 Q50 Q75 Q90 Test

Income 0.895 *** 0.962 *** 0.931 *** 0.874 *** 0.836 *** 0.795 *** 26.15

Distance -0.694 *** -0.464 *** -0.695 *** -0.709 *** -0.787 *** -0.852 *** 0.94

Contiguity 0.643 *** 0.673 *** 0.483 *** 0.687 *** 0.591 *** 0.319 *** 7.06

Eng. off. lang. 0.488 *** 1.088 *** 0.890 *** 0.433 ** 0.426 *** 0.400 *** 5.10

Eng. proff. 0.549 *** 0.304 0.340 *** 0.697 *** 0.426 *** 0.272 *** 9.46

Intercept -21.313 *** -27.083 *** -23.557 *** -20.109 *** -17.209 *** -14.193 *** 22.42

N 1800 1800 1800 1800 1800 1800 1800

Pseudo R2 0.918 0.738 0.735 0.722 0.716 0.714 ND

Page 29: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Conclusions

Language has a strong effect on trade

Countries with common official language trade more with each other

Proficiency in foreign languages also increases trade

Effects of languages different in EU15 and NMS/AC

Effect of languages seems non-linear (diminishing returns)

Page 30: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Conclusions (cont’d)

Universal proficiency in English could raise trade up to 2.7 times (EU15)

Rose: monetary unions 2-3 fold increase in tradeCommon currency costly (OCA

theory) Improving English proficiency does

not require abandoning national languages

Large gains possible at little cost

Page 31: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.
Page 32: Jan FidrmucJarko Fidrmuc Brunel University, CEDI, CEPR and WDI University of Munich, Comenius University and CESifo 2 nd FIW-Research Conference „International.

Position of German in CEECs?