COSTING BABEL: THE CONTRIBUTION OF LANGUAGE
SKILLS TO EXPORTING AND PRODUCTIVITY
James Foreman-Peck
‘…they have all one language; and this [the city
and the tower] they begin to do: and now nothing
will be restrained from them, which they have
imagined to do. Go to, let us go down, and there
confound their language’…. Genesis II 11
pertinent. This ‘network externality’ can give rise to
underinvestment in languages.1
Another realistic modification to the model for business
purposes is suggested by an incident in David Lodge’s
novel Nice Work.2 There a bilingual academic shadowing
a monolingual businessman is able to achieve an
advantage by overhearing and translating a discussion
among the foreign language negotiators with whom a
deal is to be struck. The commercial benefits to each
negotiating, or potentially negotiating, party depend on
whether they can both understand each other’s language
or not. Languages are not always perfect substitutes in
transactions. To be dependent on the other party
communicating in your language when you require is a
handicap that it is worth investing to overcome.
T
he tower of Babel story illustrates the contribution a
common language makes to trade. Also the drama
shows that different languages are barriers reducing
productivity — unless language skills are widespread.
Yet as early as the 1890s, a keen observer bemoaned the
unwillingness of British businessmen to make any
linguistic concessions in overseas markets, thereby losing
customers to the more accommodating foreign
competitors (Gaskell 1897).
The English-speaking nations’ lack of language skills
might be explained by the fact that at present they belong
to the largest economic group measured by spending
power (not by population). A simple model explains
(Church and King 1993). Consider two languages that are
merely communications technologies and perfect
substitutes for each other. The (positive) cost of learning
each language is the same. Assuming these costs are not
too high, then the efficient language learning solution is
for the smaller language group to learn the language of
the larger group. This maximises the excess of
communication benefits over learning costs. The
communication benefits are the same whichever group
becomes bilingual, and the costs are lowest if the fewest
possible acquire the extra language skills.
Despite these theoretical possibilities, studies of the
private return to individual acquisition of language skills
in Britain show few signs of underinvestment. The
following section therefore suggests why such results
nonetheless may be consistent with inadequate resources
devoted to languages. Section 2 examines more
fundamental reasons for underinvestment, an excess of
social over private returns, and outlines some possible
evidence for the impact on international trade. The third
section analyses evidence from a survey of SMEs. Larger
firms and those with language skills are more likely to
export, while the proportions of enterprises claiming
language skills, language plans and using translators in
the rest of Europe are at least three times higher than in
the UK sample. Section 4 explains why exporting tends
to be particularly socially beneficial, the wider market
allowing a spreading of fixed costs and giving a once and
for all boost to productivity. The fifth section shows that
the language effect for British bilateral trade is stronger
than for the world average. It offers some illustrations of
the size of the social gain from more investment in
language expertise, in particular from raising British
linguistic skills to those of the world average.
European language investment is then probably covered
by this model. To explain the English-speaking
economies’ language investment stance on say Mandarin
or Hindi, it is necessary to note that the value of time
spent acquiring language skills is less the lower the
earning power that constitutes the opportunity cost. The
opportunity cost to a member of a rich nation of learning
say Mandarin is much higher than that for a Chinese
citizen learning English — leaving aside intrinsic
difficulty. Asian economic growth may well change this
opportunity cost in a couple of decades though.
Even in this simple model, language learning costs can be
so high that the socially ideal arrangement of the
minority learning the majority language does not come
about. When deciding whether to invest in language
skills, individual learners do not take into account the
benefit conferred upon those they will be able to
communicate with. Only their own payoff enters the
private calculation. But for the world as a whole the gains
to both parties relative to the investment costs are
1
In a different framework Konya (2006) develops this idea further,
concluding that in some circumstances it may be optimal for small
countries to subsidise language learning in actual or potential trading
partners.
2
1
Pages 276–281 of the Penguin 1989 edition.
into account implies a 6–13% ‘social’ return, probably
within the range obtainable on other investments, and
therefore consistent with Swiss optimum investment in
language skills. But this does not include network
externalities, nor explain persistence, because private
investment decisions will not take into consideration state
funding. So perhaps there is a language ability constraint
that keeps private returns high, for those possessing it.
1. What Do We Earn from Knowing More
Languages? Gross and Net Private Returns
to Language Investment
A market approach to language skills investment
suggests we should ask whether the earnings of those
with specific skills or qualifications are higher than
others (and if so, what does it mean?). For this is how the
market encourages investment in skills.
What about native English-speakers? English is a world
language so there is no perceived need for the US, the
UK, Ireland and other native English-speakers to invest
in language skills? Certainly there is no evidence for a
significant UK wage premium for language degrees
(Dolton and Vignoles 2002 Table 1 p123). But this is not
the same as a premium to skill (occupation-dependent).
‘A’ levels are grouped in this study so that it is
apparently impossible to separate languages from
humanities to estimate a skill effect. The research was
concerned primarily to show the excess returns to
mathematics, which might give a clue to the
interpretation of the findings. If mathematics teaching in
English schools was particularly poor or painful or
simply adequate teaching scarce, compared with other
subjects, then the wage premium identified would be
necessary to induce students to pursue the subject. Such
scarce students would attract a scarcity premium. By a
similar argument it follows that the absence of a wage
premium for languages could indicate that A-level
language teaching is about right. Language teaching is
sufficiently effective that students do not require
financial compensation for the pain of learning.
One of the most widely studied relationships in human
capital investment is the Mincer equation (Rosen 1992).
In this model individuals’ earnings are explained by their
years of schooling and subsequent work experience. The
idea is that individuals undertake schooling until the
expected foregone earnings, and additional costs of
school and from not working, equal expected future
increased pay. An additional assumption is that on
average their earnings expectations are correct.
Individuals make different schooling choices (and
achieve different earnings) because of their varied
abilities, dispositions, financial constraints and time
preferences.
Private costs (such as the pain or pleasure of studying)
are included in the Mincer model. Gross and net returns
therefore diverge only if the public sector pays the costs
of education, and/or if there are spillover effects — such
as the network externality discussed above for language
acquisition.
Other human capital measures, (such as language skills)
have been added to this model subsequently. But if there
are ‘excess returns’, why are they not eliminated by
more, profit-seeking, investment in human capital? One
answer could be in the time necessary for supply to adjust
to the change in demand for skills — a plausible
explanation for the Welsh language premium in Wales in
1999 (Henley and Eleri Jones 2005). In the case of years
of schooling financial constraints might be compelling
and keep up returns for those less constrained. But the
same would not apply to the choice of subjects — maths
or French say — while being schooled (assuming a
choice was available).
A US high school curriculum study found that ‘two years
of foreign language would raise wages by 4%.’ (Altonji
1995). The language effect was apparently stronger than
those for maths and science. The interpretation offered of
the result is that ‘languages may play a role in the
development of general cognitive and communication
skills.’3 This is an alternative explanation for the maths
result above as well. Conversely the language finding
might reflect on the position of language teaching in the
US.
Analysis of a representative sample of U.S. college
graduates, with controls for cognitive ability, suggests a
2–3% wage premium for college graduates who can
speak a second language (Saiz and Zoido, 2005). Note
that the premium compares poorly to returns to an extra
year of education, 8–14%. If private returns to languages
were higher, then a fault would be signalled in either the
US labour market or education industry. In the case of an
extra year at college the explanation could well be a
financial constraint or time preference but this does not
apply to choice of subject. In short the absence of a wage
premium or excess return to language skills is no
Turning to language acquisition by non-English speakers,
investment in English as a second language in
Switzerland yields a 25% earnings differential for fluent
skills, controlling for education and experience (Grin
2003). But returns depend on whether employment is in a
trade-orientated sector. In French-speaking Switzerland
German skills are rewarded more highly than English.
Why do these differentials persist? Possibly there are
barriers to employment in Swiss trade-orientated sectors.
Alternatively it could be because the focus is on gross
returns whereas the individual is concerned with the net
payoff. The direct financial investment in Swiss human
capital pattern is largely a state decision. Around 10% of
Swiss total education spending is devoted to second
language teaching, according to Grin (2003). Taking this
3
2
A bigger effect was found for the ‘non-academic’ sample.
indication of whether there is or is not adequate
investment.
interpreted, on international trade have often turned to the
49th parallel (for instance McCallum 1995). Analysis of
the role of language differences in these border effects
has estimated the impact of common language variables
on trade and immigration between Quebec and foreign
countries on the one hand, and other Canadian provinces
and foreign countries on the other (for example Wagner,
Head and Ries 2002).
2. Why Might the Market Under-Invest in
Languages? Social Returns
Earnings returns to languages depend upon the demand
for these skills by firms.4 If firms incorrectly do not
perceive profit opportunities from exploiting language
skills then they will not demand them, and private returns
— primarily wages — will be lower in the short run. In
the longer term, when people have time to adjust to these
price signals, the proportion of national resources
devoted to language skills will be lower than ideal.
Commonly, language effects on trade have been
identified simply with a binary variable, but more
sensitive approaches have been adopted. For example
Melitz (2002) distinguishes between an open circuit
language and direct communication. An open circuit
language is widely spoken (20% or more) or official in
both bilateral trading countries (maximum of two per
country). He finds 15 languages in this category. Direct
communication depends on the percentage of speakers in
each country; in this category he identifies 29 languages.
The measure is found by summing the products of the
respective percentages of speakers over all the relevant
languages (at least four percent) in the two trading
countries. The impact of the sum of these two is about the
same as the Frankel-Rose (2002) binary measure
(doubles trade or trade/GDP) (Table 3. Melitz 2002).5
What then might prevent businesses from identifying
such opportunities, triggering this divergence between
private and social returns? A plausible possibility is
complementarity between general (language) and specific
(e.g. marketing) training. Returns to general training are
likely to be higher when combined with specific training
and, conversely, returns to specific training are probably
greater in conjunction with general. Employers will not
invest enough in specific training if workers do not have
the right general educational background. Equally
workers will invest insufficiently in general training if
they think that inadequate specific training will follow.
Without labour turnover workers and employers could
negotiate contracts whereby employers paid a part of the
general training costs. But if workers may leave before
employers recoup the cost of their training then
employers will be loath to pay for the investment. Labour
turnover then encourages under-investment in both
general and specific training when the one enhances the
productivity of the other.
In a recent survey, the language effects on the trade of
industrialised countries was suggested to be equivalent to
about a 7% tax (Anderson and van Wincoop 2004), This
nation-based analysis could breakdown when large
multinational companies choose to communicate across
borders in the language of their headquarters country, as
Siemens insists on German. But even for large businesses
there will be pressures to use the language native to the
majority of participants in transactions (Loos 2007).
The greater the proportion of the population that speaks
English, as either a first or second language, the higher
the volume of trade, both exports and imports, between
the US and that country (Hutchinson 2002). Moreover
the difficulty of learning a language has an impact.
Linguistic difference from English reduces trade with the
US, controlling for migrants and networks (Hutchinson
2005). The significance of these types of results is
brought out forcefully by the second stage of Frankel and
Rose’s (2002) analysis; not only does a common
language cause trade, but trade causes economic growth,
and therefore so does the lack of a language barrier.
That there also may be an information-based market
failure in language investment is suggested by a study of
export managers of British SMEs (Williams and Chaston
2004). The research found that linguistic ability was a
major stimulus for the positive use of export information.
Experience of living and/or working overseas
significantly affected both information-gathering and
decision-making. Without this experience it would be
difficult to judge what was being missed.
Identifying the social rate of return to investment in
language skills has been facilitated by two strands of
recent research; on the trade impact of common
currencies and borders and on the productivity boost
derived from international trade. Those seeking to
understand the impact of national borders, broadly
5
Melitz (2002) builds on the same data base as constructed by
Frankel and Rose (2002). Results from this data are not used in
the present report although experiments show large British and
whole world language effects. This is because the trade data
appear to have been deflated twice so that the values tend to
decline in successive periods when real trade volumes rose
substantially.
4
Usually by firms, but in the case of Welsh, by government
through regulation. Hence the findings of an 8-10 percent
Welsh language premium (Henley and Eleri Jones 2005).
3
Table 1. Proportions of SMEs with Language
Investments and Planning (Elan Sample)
UK
Rest of Europe
Skills
0.131
0.487
Plan
0.020
0.474
National
0.160
0.209
Translator
0.150
0.440
Agent
0.280
0.292
3. How do Language Skills Affect Smaller
Firms’ Exports?
Information failure about possibilities in foreign language
markets is likely to be greatest for smaller businesses,
with fewer resources to invest in search. The matter is
here probed with the European Commission’s Elan
survey of European SMEs (Hagen et al 2006).6 This is
the most ambitious survey of language use by business,
in that all European countries were included, and up to
100 SMEs (up to 250 employees) were sampled in each
country. The sample was stratified for each country to
match the national export profile as closely as possible.
The export profile was identified as the pattern of trade
destinations and sectors by country for exports of goods
and services based on official trade figures. A crosssection of company sizes was selected that also reflected
national rather than regional patterns.
the Managing Agency system in India, and was often
accused of contributing to Britain’s export shortcomings
in the face of foreign competition. In most other respects
British firms do not compare at all. The proportions of
enterprises claiming language skills, language plans and
using translators in the rest of Europe are at least three
times higher than in the UK sample.
British SMEs are likely to rely on everyone else using
English. This ‘common language network’ logic might
suggest greater UK employment of foreign nationals than
continental Europe. European members of this network
can more easily migrate to Britain for jobs than the
British can migrate to Europe. Moreover to the extent
that Britain is a more open economy than most of the rest
of Europe, British SME’s will be more likely to employ
foreign nationals than the rest of Europe. These will be
self-selected by their language skills, and British
businesses will be saved from investing in language
acquisition. Yet Table 1 shows the proportion of SMEs
employing foreign nationals is lower in Britain than in
the rest of Europe.
The language investment questions employed in the
analysis below are;

‘Plan’. In order to deal with customers abroad
does your company have a formal language
strategy?

‘Skills’. Have you acquired staff with specific
language skills due to export needs?

‘Nationals’. Have you ever employed native
speakers full time in your company who support
your foreign trade?

‘Agents’. Have you ever used local agents
and/or distributors who speak your own native
language in your foreign markets?

‘Translator’. Have you ever employed external
translators/interpreters for foreign trade?
This lower UK demand for language services might
simply reflect a lower need relative to the continent; the
British can export without language skills. But, in this
sample, UK SMEs export a lower proportion (37%) than
the rest of Europe (45%),8 consistent with
underinvestment in the language skills that are associated
with exports.
The small firms survey shows that the larger the turnover,
the higher the proportion of sales abroad 7. Regardless of
whether turnover is included in the statistical model
though, language skills are a good predictor of a higher
proportion of export sales for the whole sample.
To examine whether these descriptive statistics reflect a
genuine and significant pattern, multivariate analysis is
used. British businesses are expected to demand fewer
language skills than the rest of Europe. But there is no
reason why this should be associated with lower British
exports, if other nationals have adequately acquired
English. So a test of a UK language shortfall in export
model (1) is whether the UK ‘country effect’ is positive,
to offset the lower language skills input. If this country
effect is zero or negative, then being English-speaking is
not sufficient to counterbalance the impact on exports of
lower language resources.9
Consistent with English as a world or ‘open circuit’
language, British SMEs in the ELAN sample in general
behave very differently from the European average. They
only broadly compare with the rest of Europe in the
employment of agents (Table 1), which has been a long
standing feature of British export organisation. It spilled
over to the 19th century Comprador system in China and
6
We are grateful to the Commission for permission to use the
survey results.
8
Although there is a wide dispersion around these averages.
9
Ireland is not included in the present sample.
7
The UK sample was unusually unwilling or unable to provide
turnover figures and the UK seems to have larger firms.
4
Exportsi = f(language skillsi, countryi, sectori,
national trade opennessi, turnoveri)
impact is equivalent to increasing the number of
customers. In turn this lowers fixed costs per capita, and
raises profit, which may encourage entry to the market by
other firms. If so, more competing firms lower the markup of price on costs, so that output is higher and wellbeing increases. Even without such entry, fixed costs per
capita still decrease and well-being rises.
(1)
….UK effect>0 for no language failure
Exports of the ith SME are normalised by turnover,10 so
the dependent variable can range only from zero to unity.
This restriction also requires logit type estimation or
transformation of the variable.
The drawback is that a firm must be large to make the
shift from the home market to exporting and here there
may be a market failure. The benefits of exporting are
rather like agglomeration economies in this model; a
larger market brings down costs for everybody. Language
skills are the way in which the market is extended.
Cooperation or collaboration between firms to share a
fixed cost, such as an Arabic-speaking switchboard
operator, could in principle go some way to address the
problem. But the difficulty of finding a group of firms
with the same needs that is willing to cooperate in this
respect, while presumably competing in others, is likely
to be very considerable. The findings of this section are
consistent with this obstacle indeed being substantial for
the UK, and with significant associated underinvestment
in language skills.
A number of other controls are needed in the model to
ensure that other peculiarities of the British economy,
such as industrial structure, do not give rise to SME’s
lower export propensities. The British sample does
indeed have different sector characteristics from the
European average.11 Individual country effects are
included as well as a measure of national trade openness.
The logic of the last control is that a typical SME of an
economy that trades 160% of its output is likely to be
more export-intensive than that of a country that trades
only 60%. But openness probably stems primarily from
the size and prosperity of the economy, rather than from
investment in language human assets.
Whatever the specification it is not possible to obtain a
positive and significant UK country effect. If native
English language-speaker conferred an export advantage,
then the data would show a stronger tendency of UK
firms to export, controlling for other influences. They do
not. Equally robust is the result that firms with language
skills and a language plan are likely to export a higher
proportion of their output.
4. How Does Exporting Boost Productivity?
SME language skills influence their trade performance,
on the basis of the foregoing analysis. Investment in
languages improves access to foreign markets.
Exporting firms tend to be more productive than those
that only supply the home market (Greenaway and
Kneller 2004, Greenaway and Yu 2004, Girma, Kneller
and Pisu 2005). The principle of comparative advantage
— that specialisation is the basis of the gains from trade
— is consistent with this association. Countries and
economies that specialise in what they do better,
exporting these goods and services, while importing
products which they cannot make so cheaply, will have
higher living standards than those that restrict trade.
Exporters will be more productive because of this
specialisation.
It is apparent from these results that British SME’s lower
investment in language skills is not compensated by the
advantages of being native English-speakers, as far as
export intensity is concerned. Indeed the best estimate is
that there is a substantial negative effect on exports that
must be attributed to language complacency. This model
cannot calculate, but only suggest, the extent of exports
forgone by those SMEs that do not export at all, because
these are not included in the sample.
The model underlying these findings is that foreign
language skills boosts the firm’s sales opportunities,
permitting either or both of a higher price for the same
volume of sales and higher sales at the same price,
because of the wider market permitted by exports. The
downside is that the firm must invest in the fixed costs of
acquiring these skills. If the investment pays off, the
For good empirical reasons, analysis now more
commonly focuses on the fixed and sunk costs associated
with exporting. These include establishing distribution
and service networks in foreign markets, which can be
barriers for less productive firms (Helpman, Meltiz and
Yeaple, 2004). Exporting, on one interpretation then,
identifies those firms with sufficiently good products, or
which are productive enough, to overcome the sunk
costs. The expansion of these more efficient and effective
firms must improve the productivity of the economy as a
whole.
The variable is the answer to the question ‘What is the
percentage of your sales abroad of goods or services as a
proportion of your total sales?’
10
More importantly, the higher productivity of exporters is,
in part, caused by exporting. Through international
buyers and competitors, exporters may learn about new
processes, products or management practices. Export
11
In particular, 17 percent of the UK sample was classified as
‘manufacture of machinery and equipment nes’ compared with
a European sample average of 8 percent, and 11 percent ‘land
transport’ compared with one percent.
5
markets allow firms to exploit economies of scale,
thereby enhancing productivity. By gaining access to
bigger markets, they may simply be in a better position to
spread their overheads over more sales, increasing their
productivity in this way. There is a good deal of evidence
that unit costs fall with the scale of production for many
enterprises, and exporting often allows access to greater
scale. Exporters may also face greater competitive
pressures in international markets, which could more
strongly encourage efficiency.12
Consequently inadequate investment in language skills
could lose SMEs profitable opportunities.
A second, not mutually exclusive, possibility is that SME
management are averse to risk. Their limited resources
and reserves must often encourage such an attitude, with
the consequence that they are likely to invest less in the
acquisition of information of uncertain value (before they
have acquired it) than would a risk-neutral organisation.
Yet there is a strong case that society as a whole, and
public authorities representing society, should be riskneutral, because they can diversify away project-specific
risk, and take the long view of economic affairs. If this
premise is accepted, there is, in principle, scope for
productive public intervention to offset this
underinvestment in information.
Are exporters in fact more productive because
productivity causes exports, or because exporting boosts
their productivity. Both effects are likely to be at work.
Only the second is pertinent for the present study
however. Selling more abroad does not necessarily
improve economic performance — if for instance there is
no difference from the consequences of selling more at
home. For example switching more resources into foreign
languages for a firm could require a reduction of
investment in domestic marketing. In such a case, only if
the additional linguistic resources generated more sales
than were lost from the diversion away from marketing at
home would there be a gain to the firm and to the
economy. This is where the contribution of scale
economies or learning in the wider export market is
critical.
The net productivity effect of exporting greatly enhances
the returns to language investment by SMEs, primarily
for those not yet engaged in exporting.
5. What Are the Trade Effects of Language
Skills for the United Kingdom?
To complement the evidence at the individual firm level,
another approach to testing for British underinvestment
in languages is through national aggregate trade effects.
Here the principal challenge is to model international
trade flows so that the impact of language knowledge or
ignorance can be isolated from other influences.
Industry groups do gain from ‘learning-by-exporting’
(Harris and Li 2007 Table 3.6). But experiences differ for
entrants, exiting firms, and those that enter and exit
overseas markets. Harris and Li (2007) show that firms
new to exporting experienced substantial productivity
effects; a 34% long-run increase in Total Factor
Productivity in the year these firms began exporting. This
was a once and for all boost for, in the year after
beginning exporting, a productivity increase of only
about 5% was found. Because the ‘follow on’ effect is
small compared with the initial stimulus, the fixed cost
explanation for exporting permitting greater productivity
is of greater significance than learning by exporting.
Isaac Newton proposed that the attractive force between
two objects depended on the product of their masses
divided by the square of the distance between them.
Some centuries later it was found that the gravity model
also provided a good explanation for international trade
flows.13 The attractive force is replaced by trade between
two countries and the ‘mass’ of the countries is their
GDP, or GDP per capita, or both. Distance and other
barriers such as language also have been found to
influence trade flows in this type of model. Gravity
models are by far the most widely used means of
empirically studying trade because they fit the data so
well.
Is this an unexploited gain? Or does it entirely represent
the unmeasured fixed costs of exporting? If not, how
could such an unexploited potential for gain persist in a
competitive market? Why should firms not undertake
more profitable investment and ignore less profitable
ones? The researchers claim to have measured costs
completely. If this is accepted, one strong possibility to
explain persistence of the effect is inadequate
information. Information can be costly to acquire and the
value may be unknown until it is obtained. So the
optimum investment in information is hard to establish.
Language skills are often essential for acquiring
information about opportunities in other economies.
Human behaviour requires more explanation than
expressed by a gravity equation and so various attempts
have been made to model what underlies the trade
versions. A recent attempt (Andrews and van Wincoop
2003) adopts the following assumptions. Each region or
country engaging in bilateral trade produces a fixed
quantity of a distinctive good. Because these goods are
distinctive they are less than perfect substitutes for each
other. The income of a region is determined by the
exports of the good to all other regions (including itself).
12
On the other hand, firms in countries already very open to
trade may already be exposed to these competitive pressures
and benefits form learning, whether or not they export.
13
Ravenstein (1885) appears to have been the first to make an
economic application of the gravity model.
6
Consumers with identical constant elasticity of
substitution preferences, in each region, demand these
exports. How much they demand depends upon (to us)
unobservable prices, which include trade costs, such as
language barriers and transport costs. Trade costs or
barriers are symmetrical between country pairs.
much larger than the average for the whole world, in the
period 1990–97. Whereas a common language boosts
trade (using 1990–1997) by 57% for the whole world, for
the UK the advantage is 103%. Given that the gravity
model (with country random effects) controls for other
influences on the determinants of bilateral trade, this
language
impact
is
consistent
with
British
underinvestment in language, both relative to the world
as a whole and absolutely, reducing trade. Although there
is a warrant for Britain investing less in languages than
non-English-speaking countries, no distinctive trade
effect should be apparent, for lower British commitment
should be offset by the investment of other economies.
Trade between a pair of regions or countries depends on
their bilateral trade barrier relative to average trade
barriers with all partners. This last insight is an important
feature of the model and survives relaxation of many of
the assumptions. For present purposes, trade between
Britain and any one partner depends not only on language
barriers, distance, and so on, but on language barriers and
other costs between all other partners as well. By ‘taxing’
trade with some partners but not with others, language
underinvestment lowers trade with some, in part to the
benefit of others (trade diversion) and in part reducing
trade in total (trade destruction).
At the national level, different languages may be thought
of as a tax on trade. Inadequate language skills reduce the
chances of identifying profitable trading opportunities.
The ‘tax’ is lower the more widespread are language
skills in potential trading partners. The common language
effect captures some of the trade diversion of language
barriers. A greater trade diversion effect of the British
common language implies greater trade destruction as
well. The burden of the ‘tax’ imposed by language
barriers depends in this model on the extent to which
national goods are substitutes. The more substitutable are
the products of different trading nations the less the ‘tax
equivalent’ of a given foreign language effect.
The principal interest here is in the price mark up for
trade costs, a portion of which depends upon national
language differences, but that also is determined by
distance between trading partners, trade agreements and
so on.
The empirical gravity model is estimated from bilateral
trade time series collected for most countries in the world
in a data set generously made available on Andrew K
Rose’s web pages.14 Common languages are broadly
interpreted so that for example Britain is defined as
sharing a common language with India and with
Pakistan. Comparable with the other Rose data set (such
as Frankel and Rose 2002), 69.11% of British bilateral
trades are with different language economies.
On reasonable assumptions about the range of
substitutability, raising British standards of language
competence to the rest of the world average is equivalent
to between a 3 and a 7 percentage point tax reduction on
British trade. These numbers (7% and 3% of exports)
may be interpreted as the maximum sum worth spending
on raising British language skills if the investment was
effective, assuming other economies spend the optimum
on language investment. Optimum investment in
language skills depends upon how effective the
investment is in reducing language barriers to trade. It is
beyond the scope of the present paper to assess such
efficacy directly, but it is the next step for public policy.
In this data set, the average level of British trade is higher
with common language countries by one third. But then
common language countries’ GDPs per head are also
higher (by almost 20%), which should in itself generate
more trade, according to the gravity model. On the other
hand the effect will be attenuated by the greater GDPs
and relative closeness of different language trade
partners; the gravity model implies that the tradeboosting effects of a common language are partly offset
by the greater average distance of these countries from
the UK. The strongest associations of common language
are to be found with colonies (current and former) and
currency unions. Colonies are defined over several recent
centuries, so the US is identified as having colonial ties
with Britain (but Italy is not). 77.5% of bilateral trades
with sometime colonies in the data set were with those
with whom Britain shared a common language.
The boost to well being from the reduction of even a one
percent tax on British exports, that amount to one quarter
of GDP, can be substantial, for it is equivalent to a
similar rise in productivity. One percent of 25% of GDP
is 0.25%, more than £3 billion, from the 2005 GDP
figure. It would be worth spending almost up to this sum
on improving language skills, if the outlay brought
British proficiency closer to world levels equivalent, by
reducing language trade cost by one percent.
On top of the direct effects of reducing the ‘tax effects’
of language on exports are the productivity impacts of
accessing a wider market. As indicated in section 4, these
gains seem to be substantial; perhaps as much as a one
third increase in output, controlling for all inputs.
Turning to the gravity model estimates, controlling for
country effects as proxies for multilateral trade costs, the
principal result is that the UK common language effect is
14
http://faculty.haas.berkeley.edu/arose/RecRes.htm
7
Language is a barrier to trade, which can be represented
as equivalent to a tax. There is evidence that Britain’s
language investment is so low that it imposes a heavier
tax on British trade than the average for the rest of the
world. Britain’s greater estimated ‘common language
effect’ is consistent with British underinvestment in
languages. The mirror image of the common language
advantage is the handicap imposed upon international
trade by language differences. Even a one percent
reduction in the language tax — much less than the
difference between Britain’s ‘tax’ and the world average
— would be equivalent to a more than £3 billion increase
in productivity. The likely range of the language ‘tax’
(assuming the rest of the world invests the ideal amount)
is three to seven percent, so the minimum possible gains
from optimal investment in languages for Britain in 2005
was £9 billion.
6. Conclusion
Lack of a common language is a barrier to trade.
Overcoming the barrier is costly but there are widespread
benefits from doing so that may warrant public
intervention. Information shortcomings, network effects,
problems arising from the indivisibility of substantial
investments in language skills, complementarities
between firm-specific skills and languages, and
uncertainty, all suggest that underinvestment in
overcoming the language barrier to exporting may be
particularly marked for smaller firms. The payoff from
effective intervention in language investment could be
large.
These payoffs normally cannot be measured by market
returns to individuals’ investment in language skills. In
the absence of barriers, higher than ‘normal’ returns will
encourage more investment that will, in due course,
eliminate excess payoffs.
There are extra boosts from encouraging greater exports;
greater productivity stemming from larger markets in
which overheads can be spread, and expansion of more
productive firms at the expense of less. These spillover
effects add to both gross and net returns. Gains from
exporting persist most likely, in part because of
information failures and, in part because of the costs of
beginning exporting. Language investment contributes to
overcoming these hurdles.
The observation that English is a world language does
not imply that native English-speaking economies need
not invest in language skills; indeed there is evidence that
it promotes complacency and under-investment. If being
based in an English-speaking country alone conferred an
uncompensated advantage, the SME analysis would show
a positive UK effect on SME exports. After controlling
for investment in language skills, where the UK might
justifiably put in less than the continental European
average, there is no such positive effect.
The net gain from a ‘language tax’ reduction depends on
the effectiveness of the language investment that brings it
about. However, assessing the effectiveness of alternative
investment strategies is beyond the scope of the present
study.
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