There is considerable heterogeneity in the results. The data suggest contractors’ learning impacts fall into three categories, based on a k-means clustering algorithm. In the first group, YMCA, Rising Academies, Street Child, and Bridge International Academies generated an increase in learning of 0.27σ across all subjects. In the second group, BRAC and More than Me generated an increase in learning of 0.15σ. In the third group, consisting of Omega and Stella Maris,50 estimated learning gains are on the order of 0.01σ, and indistinguishable from zero in both cases. Below we explore whether “top-performing” contractors were more likely to behave in ways that might impose negative externalities on the broader education system, and hence whether better performance came at a cost to the education system as a whole.51
5.4
Non-learning outcomes and contracting flaws
Economists typically approach outsourcing in a principal-agent framework: A government (the principal) seeks to write a complete contract defining the responsibilities of the private contractor (the agent). This evaluation is part of that effort. In real-world settings, contracts are inevitably incomplete. It is impossible to pre-specify every single action and outcome that a private contractor must concern themselves with when managing a school. Economists have offered a number of responses to contractual incompleteness. One approach focuses on fostering competition among contractors via the procurement process and parental choice (Hart, Shleifer, & Vishny, 1997). Another, more recent approach puts greater focus on the identity of the contractors, on the premise that some agents are more “mission motivated” than others (Besley & Ghatak, 2005; Akerlof & Kranton, 2005). If contractors have intrinsic motivation and goals that align with the principal’s objectives then they are unlikely to engage in pernicious behavior. This may be the case for non-profit contractors whose core mission is education. In the particular case of Liberia, this may also be true for for-profit contractors who are eager to show their effectiveness and attract investors and philanthropic donors. But, if contractors define their objectives more narrowly than the government, they may neglect to pursue certain government goals. We examine three indicators illustrating how contractors and government goals may diverge under PSL: contractors’ willingness to manage any school (as opposed to the best schools); contractors’ willingness to work with existing teachers and improve their pedagogical practices and behavior (as opposed to having the worst performing teachers transferred to other public schools, imposing a negative externality on the broader school system); and contractors’ commitment to improving access to quality education (rather than learning gains for a subset of pupils). In short, we’re concerned with contractors rejecting “bad” schools, “bad” teachers, and excess pupils. We already studied school selection in Section 5.2. To measure teacher selection, we study the number of teachers dismissed and the number of new teachers recruited (Table 12 - Panel B). As noted above, PSL led to the assignment of 2.6 additional teachers per school and 1.1 additional teachers exiting per school. However, large-scale dismissal of teachers was unique to one contractor (Bridge International 50 Non-compliance likely explains the lack of effect for these two contractors. Stella Maris never took control of its assigned schools, and Omega had not taken control of all its schools by the end of the school year. Our teacher interviews reflect these contractors’ absence: in 3 out of four Stella Maris schools, all of the teachers reported that no one from Stella had been at the school in the previous week, and in 6 out of 19 Omega schools all of the teachers reported that no one from Omega had been at the school in the previous week. 51 We had committed in pre-analysis to compare for-profit to non-profit contractors. This comparison yields no clear patterns.
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