Publication: Allocating Subsidies for Private Investments to Maximize Jobs Impacts
Romero, Jose Manuel
This paper develops a general framework to allocate subsidies to private investments in the presence of jobs-linked externalities (JLEs). JLEs emerge when wages exceed the opportunity cost of labor (labor externalities), or when there are social gains from creating better jobs for some classes of worker, such as women or youth (social externalities). Like all externalities, JLEs create a gap between private and social rates of return. Investments can be socially profitable (once the corresponding JLEs are internalized) but the private returns may be too low for the firm to go ahead. JLEs help to explain why many developing countries see insufficient investment in projects that would reallocate labor towards better jobs. The concept of JLEs is well established in economic literature, but there is a need for better operational approaches to address them. Like other externalities, JLEs can be corrected using a variety of possible subsidies (such as: grants, subsidized infrastructure, credit, training, technical assistance and tax exemptions). But doing this efficiently and at scale this requires mechanisms to (a) estimate the value of the externality and (b) discover the amount of subsidy needed to trigger the private investment. This paper shows that the optimal way to allocate subsidies to offset JLEs is through a competitive bidding process which selects projects based on the estimated amount of JLEs per dollar of subsidy. The bidding process provides an incentive to investors to reveal the subsidy needed for a project to become privately viable. The authors show that the proposed approach maximizes the jobs impacts of a given amount of fiscal resources that has been allotted to support better jobs outcomes.
“Robalino, David; Romero, Jose Manuel; Walker, Ian. 2020. Allocating Subsidies for Private Investments to Maximize Jobs Impacts. Jobs Working Paper;No. 45. © World Bank, Washington, DC. http://hdl.handle.net/10986/33868 License: CC BY 3.0 IGO.”