Costing Babel: the Contribution of Language Skills to Exporting and Productivity

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

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.

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 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.

Despite these theoretical possibilities, studies of the private return to individual acquisition of language skills in Britainshow 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.

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.

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).

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 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.

What about native English-speakers? English is a world language so there is no perceived need for the US, the UK, Irelandand 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 2002Table 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 scarcestudents 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.

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 arepresentative 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 indication of whether there is or is not adequate investment.

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.

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.

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 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).

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]

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.

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 cross-section of company sizes was selected that also reflected national rather than regional patterns.

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 supportyour 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?

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.

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 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.