Foreign Languages and Trade

Technical University Košice, Herl’any, October 14-15, 2010

Jarko Fidrmuc OeNB Vienna, Comenius University Bratislava,

CESifo Munich, OEI Regensburg

Jan Fidrmuc Brunel University London, CEPR, and CESifo

The research was largely completed during Jarko Fidrmuc’s stay at the University of Munich. The opinions are those of the author and do not necessarily reflect the official viewpoint of the Oesterreichische

Nationalbank or of the Eurosystem. We acknowledge CESIUK support from the Operational Program of Research and Development (OP VaV) in the framework of the European Regional Development Fund (ERDF).

- 2 -

Literature Review – I

• Gravity models usually include also dummies for

common languages as a control variables.

• Helpman, Melitz and Rubinstein (2008) derive the

gravity equation by in a model with heterogenous firms

which stresses the link between productivity and

export performance of firms.

• Their empirical results indicate that common

languages are an important part of fixed costs related

to market entry.

- 3 -

Literature Review – II

Mélitz (2008)

• Official and non-official indigenous languages

• Language impact measured using dummy

variables

(if official or spoken by more than 20%) or

communicative probability

• Only indigenous languages (Ethnologue

database)

- 4 -

Literature Review – III

Rauch (1999, 2001),

Rauch and Trindade (2002),

Bandyopadhyay, Coughlin and Wall (2008)

• Ethnic-networks increase trade

• Rauch and Trindade (2002): ethnic Chinese

networks in SE Asia increase trade by at least

60%

- 5 -

Our Contribution

• First to study effect of native and foreign

(learned) languages alike

- Trade often relies on communication in non-

native languages

• Unique extensive dataset on language

proficiency

in the EU

- 6 -

Data–Foreign Languages

• Special Eurobarometer 255: Europeans and their

Languages, November - December 05.

• Nationally representative surveys; only EU nationals

included.

• Respondents were asked on their language skills:

- Native language(s),

- up to 3 other languages that they speak well enough

to have a conversation,

- Self-assessed proficiency of foreign languages:

basic (not used here), good, and very good.

- 7 -

English (good/very good skills) French (good/very good skills)

Foreign Languages in Europe – I

- 8 -

Foreign Languages in Europe – II

German (good/very good skills) Russian (good/very good skills)

- 9 -

Communicative Probability

• Probability that two randomly selected individuals from two different countries can speak sufficiently well the same language

- English• Languages spoken by at least 10% of population

in at least 3 countries- German - French - Russian (only in Eastern Europe)

• We compute the overall communication probability based of possible multiple knowledge of English, French, and German.

- 10 -

Communicative Probability

EU15 NMS/ACs EU29

English 22 6 13

German 7 1 3

French 5 0 1

Russian 0 4 1

Cumulative 30 6 16

- 11 -

Average Cumulative Com. Probabilities–EU15 (English, German, and French)

0

5

10

15

20

25

30

35

40

45

50

- 12 -

Average Cumulative Com. Probabilities–EUROPA29(English, German, and French)

0

5

10

15

20

25

30

35

- 13 -

Data–Further Variables

• Trade and GDP data are taken from the IMF (IFS and DOT)

• All variables are converted to euro.

• PISA test results in 2006 (because of country availability),

• Public and private expenditures on education in 2000.

• We cover EU15, new member states, and the candidate

countries.

- 14 -

Gravity Model–Core Variables

• Trade (in logs) between countries i and j, Tijt,

• Log of output of i and j, yit and yjt,, measured in

nominal EUR,

• Distance between i and j, dij

• Common border dummy, bij.

• A dummy for former federations in CESEE, fij.

ijijijjtitijt

fbdyyT4321

- 15 -

Gravity Model–Languages

• Communication probabilities: Pfij - English, - English, French, German- Cumulative cummulative probability for English,

French and German

• In this version we do not include dummies for

common languages.

F

fijffijijijjtitijt

PfbdyyT,4321

- 16 -

Gravity Model–Panel Structure

ijtjtit

F

fijffijijijjtitijt

PfbdyyT ,4321

• Time-varying country dummies following Baldwin

and Taglioni (2006): - Country-specific time-invariant and

time-varying omitted variables- Country-specific measurement problems- This lowers the possible endogeneity problems.

- 17 -

OLS-Results for EU15

Variable OLS1 OLS2 OLS3

Intercept 15.705 *** 15.568 *** 15.659 *** (63.338) (59.522) (60.502)

GDP 0.915 *** 0.920 *** 0.923 *** (65.436) (65.426) (64.564)

Distance -0.767 *** -0.757 *** -0.759 *** (-31.489) (-29.496) (-29.934)

Contiguity 0.541 *** 0.519 *** 0.466 *** (15.831) (14.848) (13.152)

EMU 0.460 *** 0.454 *** 0.408 *** (11.991) (11.814) (10.541)

English 1.078 *** 1.101 ***

(11.231) (11.377)

French 0.048

(0.467)

German 0.241 ***

(3.466)

Cumulative 0.573 *** (8.760)

N 1470 1470 1470

Adjusted R2 0.965 0.966 0.964

- 18 -

OLS-Results for EUROPA29Variable OLS1 OLS2 OLS3

Intercept 18.027 *** 17.981 *** 18.016 *** (101.297) (100.013) (100.553)

GDP 0.916 *** 0.924 *** 0.916 *** (79.985) (80.472) (79.903)

Distance -1.047 *** -1.051 *** -1.043 *** (-50.708) (-50.409) (-50.162)

Contiguity 0.384 *** 0.405 *** 0.361 *** (9.902) (10.231) (9.190)

Federations 2.401 *** 1.880 *** 2.426 *** (26.099) (15.301) (26.252)

EU 0.038 0.031 0.058

(0.813) (0.664) (1.236)

EMU 0.188 *** 0.193 *** 0.165 *** (4.925) (4.935) (4.292)

English 0.653 *** 0.622 ***

(5.523) (5.280)

French -0.479 **

(-2.759)

German 0.051

(0.411)

Russian 1.642 ***

(6.159)

Cumulative 0.336 *** (3.739)

N 5634 5634 5634

Adjusted R2 0.923 0.924 0.923

- 19 -

Controlling for Endogeneity

• Proficiency in foreign languages and trade may be

endogenous:

- People learn foreign languages of their main

economic partners (e.g. the rise of interest in

Chinese courses in the last decade)

- People forget languages which are not frequently

used

(e.g. Russian in CEECs)

• OLS results may be biased.

- 20 -

Instrumental Strategy

We compare several sets of instrumental variables:

• Language groups are our preferred instruments

- We use dummies for countries with Germanic and

Romanic languages.

- Unlike common languages, language groups are not

correlated with free trade areas (e.g. Germany and

Norway, France and Spain).

• Pisa tests results are valid but weak instruments.

• Public expenditures on education are invalid instruments.

• All instruments work worse for the CESEE.

- 21 -

IV-Results for EU15: Language Groups

Variable GRP1 GRP2 GRP3

Intercept 15.647 *** 14.132 *** 15.151 *** (58.735) (24.909) (46.572)

GDP 0.916 *** 0.944 *** 0.932 *** (67.546) (45.501) (64.578)

Distance -0.763 *** -0.610 *** -0.716 *** (-30.266) (-11.349) (-23.783)

Contiguity 0.542 *** 0.430 *** 0.425 *** (16.368) (5.164) (11.099)

EMU 0.464 *** 0.403 *** 0.408 *** (12.215) (6.987) (10.760)

English 1.165 *** 1.423 ***

(5.926) (6.392)

French 1.950 ***

(3.346)

German 0.241

(0.409)

Cumulative 0.953 *** (5.762)

N 1470 1470 1470

Adjusted R2 0.965 0.957 0.963

Sargan statistics 1.429 2.440 1.322

[0.232] [0.486] [0.250]

- 22 -

English English French German Cumul.

GRP1 GRP2 GRP2 GRP2 GRP3

Germanic (country 1) 0.179 0.062 *** 0.015 *** 0.011 0.201 ***

(20.572) *** (7.591) (4.356) (1.032) (21.840)

Germanic (country 2) 0.179 0.062 *** 0.015 *** 0.011 0.201 ***

(20.533) *** (7.589) (4.310) (1.017) (21.780)

Germanic (country 1 & 2) 0.142 *** -0.018 *** 0.069 ***

(21.245) (-6.094) (7.968)

Romance (country 1) -0.135 *** 0.027 *** -0.013

(-17.529) (8.035) (-1.335)

Romance (country 2) -0.135 *** 0.027 *** -0.013

(-17.530) (8.038) (-1.334)

Romance (country 1 & 2) 0.095 *** 0.007 ** -0.010

(14.010) (2.239) (-1.171)

F-test of excluded instruments 233.17 301.77 23.63 18.95 262.57

[0.000] [0.000] [0.000] [0.000] [0.000]

First Stage Equation for EU15: Lang. Groups

- 23 -

IV-Results for EU15: PISA Variables

Variable PISA1 PISA2 PISA3

Intercept 14.569 *** 8.864 *** 11.255 *** (43.416) (3.714) (11.129)

GDP 0.924 *** 1.031 *** 0.999 *** (61.338) (19.890) (35.436)

Distance -0.680 *** -0.132 -0.390 *** (-22.279) (-0.576) (-4.472)

Contiguity 0.562 *** 0.137 0.114

(15.281) (0.724) (1.217)

EMU 0.540 *** 0.362 *** 0.404 *** (12.401) (3.342) (6.412)

English 2.774 *** 4.420 ***

(8.590) (5.206)

French 6.101 **

(2.401)

German 1.832 *

(1.749)

Cumulative 3.861 *** (5.559)

N 1470 1470 1470

Adjusted R2 0.958 0.860 0.899

Sargan statistics 0.100 5.533 0.017

[0.752] [0.137] [0.895]

- 24 -

First Stage Eq. for EU15: PISA Instruments

English English French German Cumul.

PISA1 PISA2 PISA2 PISA2 PISA3

Reading performance 0.257 *** 0.499 *** 0.012 -0.468 *** 0.184 ***

(country 1) (11.771) (8.910) (0.216) (-5.670) (5.419)

Reading performance 0.256 *** 0.498 *** 0.018 -0.457 *** 0.185 ***

(country 2) (11.739) (8.895) (0.321) (-5.535) (5.454)

Mathematic performance -0.034 0.087 0.210 ***

(country 1) (-0.651) (1.619) (2.693)

Mathematic performance -0.036 0.085 0.210 ***

(country 2) (-0.681) (1.587) (2.701)

Science scale -0.223 *** -0.170 ** 0.274 ***

(country 1) (-3.385) (-2.536) (2.817)

Science scale -0.221 *** -0.174 *** 0.262 ***

(country 2) (-3.348) (-2.600) (2.697)

F-test of excluded instruments 77.40 30.27 2.85 6.78 16.55

[0.000] [0.000] [0.009] [0.000] [0.000]

- 25 -

IV-Results for EUROPA29: Language GroupsVariable GRP1 GRP2 GRP3

Intercept 17.830 *** 18.526 *** 17.171 *** (87.713) (62.796) (45.300)

GDP 0.910 *** 0.920 *** 0.901 *** (76.705) (51.200) (64.632)

Distance -1.040 *** -1.131 *** -0.961 *** (-48.162) (-27.348) (-24.371)

Contiguity 0.371 *** 0.736 *** 0.131

(9.428) (4.903) (1.532)

Former Federations 2.416 *** 2.053 *** 2.702 *** (25.955) (2.851) (19.193)

EU -0.101 -0.023 -0.192 * (-1.412) (-0.335) (-1.850)

EMU 0.220 *** 0.535 *** 0.019

(5.506) (3.947) (0.269)

English 2.702 *** 2.921 ***

(3.326) (3.401)

French -1.996

(-1.599)

German -7.137 ***

(-3.126)

Russian -0.121

(-0.059)

Cumulative 3.796 *** (3.011)

N 5634 5634 5634

Adjusted R2 0.919 0.871 0.902

Sargan statistics 3.747 49.251 3.200

[0.053] [0.000] [0.074]

- 26 -

First Stage Eq. for EUROPA29: Lang. Groups

English English French Germ. Russian Cumul.

GRP1 GRP2 GRP2 GRP2 GRP2 GRP3

Germanic (country 1) 0.097 *** 0.007 *** 0.019 *** -0.012 ***

(30.475) (7.090) (7.057) (-5.415)

Germanic (country 2) 0.097 *** 0.007 *** 0.019 *** -0.012 ***

(30.417) (7.178) (7.063) (-5.597)

Germanic (country 1 & 2) 0.166 *** 0.002 ** 0.037 *** 0.012 ***

(50.895) (2.240) (13.067) (5.394)

Romance (country 1) -0.051 *** -0.039 *** 0.014 *** -0.008 *** -0.009 *** -0.038 *** (-10.91) (-11.02) (12.90) (-2.66) (-3.860) (-5.54)

Romance (country 2) -0.052 *** -0.039 *** 0.014 *** -0.008 *** -0.009 *** -0.037 *** (-10.90) (-11.00) (13.03) (-2.71) (-3.93) (-5.52)

Romance (country 1 & 2) 0.029 *** 0.023 *** -0.007 ** 0.009 ***

(7.089) (17.788) (-2.045) (3.133)

Slavonic (country 1) 0.020 *** 0.001 0.006 * 0.000

(4.876) (0.528) (1.828) (0.019)

Slavonic (country 2) 0.020 *** 0.001 0.007 ** -0.001

(4.983) (0.532) (2.094) (-0.280)

Slavonic (country 1 & 2) -0.015 *** -0.001 -0.021 *** -0.042 ***

(-2.96) (-0.59) (-4.63) (-11.95)

F-test of excl. instr. 60.42 603.63 87.12 59.81 21.98 17.18

[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]

- 27 -

IV-Results for EUROP29: PISA TestsVariable PISA1 PISA2 PISA3

Intercept 18.427 *** 15.148 18.369

(109.943) (0.688) (89.785)

GDP 0.918 *** 1.157 0.918

(76.026) (0.704) (74.720)

Distance -1.106 *** -1.003 -1.099

(-51.901) (-1.497) (-40.568)

Contiguity 0.294 *** 0.056 0.264

(8.802) (0.162) (6.690)

Former Federations 2.371 *** -7.612 2.404

(32.038) (-0.104) (28.169)

EU 0.056 -0.321 0.055

(0.985) (-0.117) (0.960)

EMU 0.236 *** -0.397 0.211

(7.248) (-0.124) (5.654)

English 0.466 0.549

(0.891) (0.065)

French 1.006

(0.214)

German 6.891

(0.617)

Russian 34.414

(0.140)

Cumulative 0.443

(0.879)

N 4870 4870 4870

Adjusted R2 0.936 0.570 0.935

Sargan statistics 0.911 1.744 0.921

[0.340] [0.418] [0.337]

- 28 -

First Stage Eq. for EUROPA29: PISA Tests

English English French Germ. Russian Cumul.

PISA1 PISA2 PISA2 PISA2 PISA2 PISA3

Reading performance 0.098 *** 0.259 *** 0.030 ** -0.064 *** -0.007 0.103 ***

(country 1) (13.782) (16.399) (2.314) (-3.606) (-0.790) (10.179)

Reading performance 0.099 *** 0.255 *** 0.028 ** -0.064 *** -0.006 0.103 ***

(country 2) (13.851) (16.171) (2.209) (-3.618) (-0.730) (10.160)

Mathematic perf. -0.125 *** 0.070 *** 0.123 *** -0.002

(country 1) (-5.629) (3.896) (4.949) (-0.210)

Mathematic perf. -0.130 *** 0.071 *** 0.118 *** -0.001

(country 2) (-5.860) (3.950) (4.767) (-0.100)

Science scale -0.045 * -0.115 *** -0.035 0.005

(country 1) (-1.942) (-6.131) (-1.334) (0.420)

Science scale -0.035 -0.115 *** -0.030 0.003

(country 2) (-1.498) (-6.133) (-1.164) (0.270)

F-test of excl. instr. 106.910 62.640 8.180 9.200 0.270 57.950

[0.000] [0.000] [0.000] [0.000] [0.951] [0.000]

- 29 -

Economic Significance (EU15)

Consider the OLS and IV (Group) results:

• Coefficients for English communication probability is 1.1-

1.4.

• Average effect in EU15: 27%-36% increase due to English

proficiency (22% average communicative probability).

• UK-IRL trade is increased 3 to four times because of

English proficiency (97% communicative probability).

• Furthermore, NL-UK trade is higher by factor 2.3 to 2.9

(76% com. prob.).

• But also NL-S trade is increased 1.7-2.1 times (52% com.

prob.).

- 30 -

Extensions and Sensitivity Analysis

• The foreign language effects may be non-linear, but

the effects are not robust.

• Hump-shaped effect of English diminishing

returns to language skills.

• Median regression confirms the robustness to

outliers.

• Quantile regression shows that the effects are

highest for the lowest and highest quantiles (5th &

90th).

• The results are largely confirmed also East Europe

and EU27 despite a different language education

history.

- 31 -

Non-linear Effect for EU15

Variable NL1 NL2 NL3

Intercept 14.860 *** 14.749 *** 14.264 ***

GDP 0.900 *** 0.917 *** 1.011 ***

Distance -0.781 *** -0.798 *** -0.787 ***

Contiguity 0.474 *** 0.383 *** 0.405 ***

EMU 0.469 *** 0.419 *** 0.533 ***

English (official language) 1.237 *** 1.792 *** 1.077 ***

French (official language) 0.813 *** 0.116

German (official language) -0.012 0.522 ***

English 3.156 *** 5.431 ***

French -0.206

German -2.472 ***

English squared -2.173 *** -4.264 ***

French squared -0.795 *

German squared 3.116 ***

Cumulative 0.580

Cumulative squared -0.418

N 1470 1470 1470

Adjusted R2 0.975 0.979 0.976

- 32 -

Conclusions

• Language proficiency has a strong effect on trade.

• Large trade gains are possible through better foreign

language education.

• The gains are comparable to those of a monetary

integration.

• Improving English proficiency does not require

abandoning national languages.

• Large gains are possible at little cost.