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Centre for Monitoring Indian Economy, Mumbai, https://consumerpyramidsdx.cmie.com/.

The chapter uses data from surveys conducted in 2020. 35. See Stigler Center (2019) for a review of such evidence on market power and competition in digital platforms. 36. See Jayachandran (2020), McKenzie and Woodruff (2014), and Woodruff (2018) for reviews of the evidence base on microenterprise and small business development programs.

Although not targeted on the informal sector, the beneficiaries of the programs are generally small and informal. 37. In comparison with grants, microcredit has been found to have limited impact on enterprise performance, with relatively few recipients benefiting from the loans (Jayachandran 2020). 38. Differences in measured ability can predict the future growth of small businesses, although the predictive power is low (Fafchamps and Woodruff 2017; McKenzie and Sansone 2017).

Some evidence suggests that the potential to benefit from credit or similar interventions varies. In Hyderabad, for instance, entrepreneurs who were in business before microfinance was widely available experienced large and lasting gains in business performance from randomized access to microfinance, while those without a prior business did not experience any significant gains, an outcome that may derive from inherent variations in the potential to benefit from microcredit (Banerjee, Karlan, and Zinman 2015). 39. Interventions that address entrepreneurial orientation, motivation, and aspiration are also beingtested.Theysitsomewhereinthemiddleofthesetypes.Forinstance,personalinitiative training increased profits by 30 percent among microentrepreneurs in Togo (Campos et al. 2017). 40. Banerjee et al. (2015) report similar results from randomized evaluations of six graduation programs implemented in different countries. 41. See e-Shram (dashboard), Ministry of Labour and Employment, New Delhi, https://eshram .gov.in.

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