Informal employment continues to dominate labor markets in developing economies, with digital platforms rapidly expanding the organization of low- to mid-skill service work. This coexistence raises an economic puzzle: what explains workers’ sorting into digital platform (gigs) versus traditional offline informal work, beyond differences in technology access and observed earnings? Little is known about how economic preferences, especially risk tolerance, and soft skills are distributed across digital platform and traditional offline informal workers, and whether these soft skills help explain why some informal workers engage in digital platform while others remain in traditional offline informal employment. We address this gap by using a lab-in-the-field experiment with informal service workers in urban India (dominantly male) by building on a post-sorting framework in which workers are already engaged in either digital platform (D) or traditional offline (T) work modes. We elicit incentivized measures of risk tolerance and selected soft skills, and collect harmonized information on perceived working conditions. Our results show substantial heterogeneity by age and work mode, such that younger T workers display higher risk tolerance than D workers, whereas older D workers are more likely to be risk-neutral or risk-averse. D workers also exhibit higher self-control and openness, but lower grit and conscientiousness, relative to T workers. These patterns are consistent with sorting in secondary labor markets based on heterogeneous trade-offs over income risk, flexibility, and community-based security, rather than simple adoption of new work technology. Our findings are best interpreted as applying to male urban informal service workers. Policies that seek to improve welfare in dual labor markets should combine platform expansion with risk-sharing and skill-building interventions and minimum standards for worker protection.
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Timilsina et al. (2026) studied this question.
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