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In the mid-1990s, the term digital divide was used to describe the unequal access to the internet for different population groups in the USA. The 1995 report Falling Through the Net found that the population in rural areas and low-income households in particular were disadvantaged by limited internet access in the emerging digital age. This disparity was further compounded by differences in ICT literacy consisting of proficiency with databases, the Internet, spreadsheets and operating systems which exacerbated labor market inequalities.
This study investigates whether ICT literacy can improve individual incomes and narrow the income gap, utilizing data from the LifE-study, a comprehensive longitudinal study conducted in Germany.
The LifE-Study, which followed participants annually from 1979 to 1983 and again in 2002, 2012 and 2024, offers a unique longitudinal perspective on the long-term economic impact of digital literacy. We specifically analyse how the different waves of 2002, and 2024 reflect changing patterns of ICT literacy acquisition and its evolving role in shaping economic outcomes over time. Our analysis focused on the cohort born in 1967 and 1968 who are now around 57 years old. This group encountered computers and the internet during their early adulthood, providing valuable insights into how mid-life digital skill acquisition influences income inequality over the life course.
Grounded in both digital divide theory and human capital theory, this study explores digital literacy as a key driver of economic mobility. We define digital literacy as encompassing both basic digital skills and more advanced competencies, offering a nuanced understanding of how different levels of ICT proficiency impact income across socioeconomic groups.
The purpose of this study is twofold: first, to examine the digital divide in terms of access and usage; second, to assess whether digital literacy contributes to social inequality in the life course, particularly in relation to income disparities in the labor market.
We employ regression analysis, including Recentered Influence Function (RIF) models, to assess how digital literacy influences income distributions. Preliminary findings reveal significant disparities in internet usage and a strong positive correlation between digital literacy and income growth, especially for lower earners, demonstrating its potential to reduce income inequality.