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Language Learning and Communicative Benefits

  • Efthymios Athanasiou
  • Juan D. Moreno-Ternero
  • Shlomo Weber

Abstract

Most economic contributions in this handbook deal with the way languages and linguistic diversity affect economic outcomes. The reverse direction, that is, how economic issues can have an impact on linguistic diversity and the evolution and acquisition of languages, is explored to a lesser degree, with the exception of Chapter 3 on language evolution (as well as, and to some extent, Chapters 16to 19 on linguistic standardization in this volume). One can immediately point out that linguistic diversity and, more specifically, an equal distribution of linguistic skills in multi-lingual societies offers both individual and societal opportunities and challenges. Indeed, there are economic and cultural incentives to acquire languages in addition to one’s mother tongue. It may be beneficial for an individual to acquire languages spoken by important trade partners of his or her own country. If there existed a universal and dominant lingua franca spoken by everybody, the incentives of learning foreign languages in our increasingly globalized society would not be that strong. Even though de Swaan (2001) claims that ‘globalization proceeds in English’, many commercial and trade negotiations in China, India, Latin America and other parts of the world are conducted in other languages than English. China’s and India’s populations are much larger than that of all English speaking countries combined, and one can wonder why a Chinese businessman would learn English, as he has direct access to 1.5 billion potential domestic customers. The same applies to individuals in English-speaking countries. However, the improving English-language skills in China, and the ever-rising demand for studying Chinese in the US and Africa, imply that language acquisition is enhanced by trade, as Ginsburgh et al. (2014) show.

Keywords

Nash Equilibrium Foreign Language Linguistic Diversity Language Acquisition Network Externality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Efthymios Athanasiou, Juan D. Moreno-Ternero and Shlomo Weber 2016

Authors and Affiliations

  • Efthymios Athanasiou
  • Juan D. Moreno-Ternero
  • Shlomo Weber

There are no affiliations available

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