The Economic Returns of Language Proficiency: A Review Based on the Perspective of Language Asset Pricing

Abstract

With the rapid development of globalization, the digital economy, and artificial intelligence, language proficiency has become a crucial factor influencing individual income, employment quality, and occupational mobility. Existing research largely explains the economic returns of language proficiency from the perspectives of human capital, labor market signals, and social capital. However, this perspective is relatively static and fails to fully explain the differentiated returns of language proficiency across different countries, industries, and individuals. It also struggles to explain the devaluation, reassessment, and structural differentiation of language proficiency under the impact of artificial intelligence. Therefore, this paper introduces the analytical approaches of asset pricing, portfolio construction, and risk-return from financial economics, understanding language proficiency as a “language asset” with investment costs, expected returns, risk exposure, and allocation value. Research shows that the economic returns of language assets are not solely due to wage premiums, but are formed through mechanisms such as information arbitrage, operating income, skill leverage, market access, and online and real options. Different language assets exhibit different risk-return characteristics: English proficiency resembles a highly liquid blue-chip language asset; bilingual proficiency reflects portfolio allocation and risk diversification value; and multilingual proficiency exhibits characteristics of growth assets and real options. The returns of language assets are also influenced by the national environment, industry structure, job demand, and the individual’s skill set. Artificial intelligence is further altering the pricing logic of language assets: the scarcity of basic language conversion skills is decreasing, while higher-order values such as contextual judgment, cross-cultural understanding, and human-machine collaboration are increasing. This article argues that the economic returns of language skills should be understood from a static “skill premium” to a dynamic “asset pricing” perspective.