On Friday, 2 December 2022, Kunal Sen presents to an audience of researchers at the University of Sussex including visitors from the Institute for Development Studies. The presentation draws from the forthcoming book The job ladder: Transforming informal work and livelihoods in developing countries due for release February 2023.
Examining formality and informality with a jobs ladder approach
Most jobs in low-income countries are in self-employment or unpaid family work in agriculture or services. Labour markets in developing countries are characterized by high levels of informal work. But with development comes a transformation in the jobs people do; a rise in the non-agricultural and waged shares of employment, urbanization, and increased formality.
Early literature modeling labour markets in developing countries characterized dualism in terms of formal and informal employment. Formal employment was seen as offering relatively attractive wages and working conditions, while informal employment offered relatively unattractive pay and conditions. More recent empirical work suggests labour markets in developing countries are more multi-layered, and jobs and labour earnings are heterogenous. Workers can either be in wage employment or self-employment, which can exist within both formal and informal employment. Informal employment has its own duality, waged- and self-employed informal workers can face capital or skill requirements which differentiate upper-tier from lower-tier informal employment.
Do some workers move up the tiers over time into better jobs? Who are they? Faced with labour market heterogeneity, what should policymakers focus on to nurture better jobs for more people with growth and structural transformation?
Drawing on research and analysis from The job ladder, this presentation introduces the concept of a job ladder for developing countries based on the employment type, formality, and entry requirements to jobs. Further, the presentation will explore evidence of worker transitions between the tiers of the ladder using panel labour force survey data.