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    • Fig introduces in addition to credit

    2018-10-30

    Fig. 2 introduces, in addition to credit constraints, the second source of friction in the model: taxes on formal entrepreneurs and on labor income. Now the informal sector becomes profitable for some individuals, since they JSH-23 can avoid paying taxes. In particular, for a given level of wealth, the least talented individuals opt for wage working. Increases in talent then induce individuals to become informal entrepreneurs: since their scale is relatively low, they prefer to operate informally in spite of not having access to credit markets. Further increases in θ (for the same level of z) are then related to larger scale: access to credit markets becomes essential, thus inducing such individuals to operate in the formal sector. This reasoning applies to intermediate values of θ, such as θ=4 in Fig. 2. However, there is also a set of highly talented individuals that operate informally, specifically those with very low levels of wealth (upper left corner of Fig. 2). If these individuals were to operate in the formal sector, they would raise a very limited amount of resources and, therefore, produce with substantially low capital. That would be particularly costly since the formal sector features a capital intensive technology. These individuals therefore prefer the informal sector, in which technology is labor intensive (although inferior) and they do not have to pay taxes. Table 2 presents some descriptive statistics about our calibrated economy. About 65.6 percent of all individuals are wage workers, and 17.9 percent are entrepreneurs operating in the formal sector. The informal sector employs the majority of workers (51.7%), but produces only 41 percent of the output in this economy. This is because such sector is both more labor intensive and less productive than the formal sector. Wage workers are the least talented individuals of this economy, while formal entrepreneurs are slightly more talented than informal ones on average. Nonetheless, informal entrepreneurs are wealthier, especially those unconstrained: since these individuals do not need to borrow to operate at the optimal scale, they choose the informal sector in order to avoid paying taxes.
    Concluding remarks This paper analyzed the effects of taxation and credit market frictions on occupational choice, aggregate efficiency and income inequality, in an environment where a large fraction of output is produced in the informal sector. In particular, we extended the model of Evans and Jovanovic (1989) to consider two sectors: the formal sector, in which entrepreneurs have limited access to credit markets and must pay taxes; and the informal sector, in which entrepreneurs can evade the payment of taxes, but have to rely exclusively on their wealth to finance their capital. Individuals are heterogeneous in their wealth and entrepreneurial talent, and decide between three occupations: wage worker, entrepreneur in the formal and entrepreneur in the informal sector. In addition, the informal sector is both less productive and more labor intensive than the formal sector. Our work leaves some interesting questions for future research. For instance, we assumed that informal entrepreneurs cannot borrow any resources to finance their capital. One could argue that, in reality, they have some access to credit, although at a higher cost than formal businesses. Merlin and Teles (2014) suppose that informal entrepreneurs borrow funds through personal credit lines (at substantially higher rates than through business credit lines) to invest in their firms. Incorporating this feature in our setting would certainly reduce the impact of removing frictions (especially borrowing constraints and the taxes on formal enterprises), since it would lower the incentives to operate formally. On the other hand, this would force us to recalibrate the model, so that the share of the informal sector would approximate that in the data. In other words, we would have to reduce the relative efficiency parameter ψ, which would probably increase aggregate inefficiency in our baseline calibration.