In 2019, armed conflicts cause the displacement of one person every two seconds. Motivated by our fieldwork in refugee camps in north-western Greece, we study the effect of the two main humanitarian assistance types provided to refugees: in-kind and cash assistance. In-kind assistance occurs when the humanitarian organization (HO) purchases goods and provides them to refugees directly. Cash assistance enables refugees to purchase the goods they want. Their purchases benefit local businesses---retailers---in the host community to the detriment of the purchasing power of local residents. We analyze the tradeoffs between in-kind and cash assistance from the perspective of a HO, which aims to maximize social welfare of refugees and host communities---retailers and residents. The combined purchasing power of refugees and residents may lead to increased selling prices and thus decreased quantities purchased by refugees. We propose a price regulation, implementable by a partnership between the HO and the local government, to curb the retailer's market power. We show that regulating the good's price benefits refugees and residents while ensuring retailer's profitability. Moreover, the HO's in-kind assistance to refugees should be balanced across multiple goods to discourage the retailer from increasing goods' prices asymmetrically.

Most US nonprofits disclose three types of expenses: program spending to meet their beneficiaries’ needs; fundraising spending to increase their future budget; administration spending to make their future budget more impactful. Charity watchdogs expect nonprofits to prioritize program over fundraising and administration. We study if nonprofits should ever prioritize fundraising and administration instead. Using a two-period model, we capture the tradeoff between the immediate reward from program and future rewards from fundraising and administration. We show that the optimal budget allocation depends critically on the nonprofit's budget and return on program (the net value of program to beneficiaries). For moderate return on program, the budget’s effect is intricate. While low budgets favor the prioritization of program, higher budgets might favor the prioritization of fundraising and administration for the nonprofit to be forward-looking. We then calibrate our model in a case study of two nonprofits with divergent models: in-kind aid versus cash aid. To assess the soundness of a nonprofit's budget allocation, one should know its return on program – a challenging metric to estimate. We derive the imputed return on program instead (the return on program at which the nonprofit's actual allocation matches our model’s optimal allocation). The imputed return on program, which uses public data, reasonably distinguishes between the nonprofits’ implicit assumptions, confirming that the in-kind nonprofit operates under the assumption that its services have added value for beneficiaries. This points to the imputed return on program as a promising tool to capture meaningful differences among nonprofits' budget allocations.

This study examines empirically the fleet composition of a large international humanitarian organization (HO) that responds to natural disasters and armed conflicts. We focus on understanding how the HO configures its fleet and specifically decides on renting or subcontracting transportation to deliver services to its beneficiaries. Transportation expenses are one of the largest expenses for the organization. We use thirteen-year panel data on transportation and personnel (local and expatriate) expenses of twenty-four country offices of this organization to build a fixed-effect model. We combine our proprietary data with publicly available data on natural disasters and armed conflicts.