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Measuring equity in education resource allocation: An exploratory analysis

Tue, April 16, 5:00 to 6:30pm, Hyatt Regency, Floor: Pacific Concourse (Level -1), Pacific G

Proposal

This paper starts from the working assumption that education systems are not inherently equitable, and in some cases, existing resource allocation mechanisms exacerbate starting levels of inequality across socioeconomic and cultural lines. Many governments around the world have sought to use their education finance systems and standalone budgeting regulations to correct for known disparities. More equitable systems shift more resources towards units – schools, districts – with greater need, or units starting at a greater disadvantage, while less equitable systems show an imbalance of resources benefitting units that already carry a greater amount of socioeconomic and resource privilege, thereby exacerbating inequity and setting students on vastly different paths. This paper uses data from four systems across the income spectrum, to examine the equity of resource allocation.

Analytical framework. The analysis consists of the following:
1. Need determination. The first step in assessing equity of a given system is understanding the distribution of need. The notion of “need” is arguably context-dependent: what signals need in one system may not mean the same in another. However, evidence shows that there are a set of factors that inevitably predict higher or lower learning outcomes across systems – such as various proxies of socioeconomic status, language, urbanicity, disability status, etc. Where local determinations of need are available (e.g. % students below a certain level of income or wealth index), the study will use them to construct the Needs distribution and identify “high” and “low” needs units. Otherwise, need will be determined based on known demographic predictors of outcomes within a given system (which will be documented for each context).
2. Resource allocation. Using the definition of “low” and “high” needs, the next step will consist of a descriptive analysis of the level of resources allocated at each level. We anticipate that similarly to needs, resources may be measured differently and with more or less precision across systems. However, key categories that can be expected in every system include: a) teachers: teacher experience, teacher qualifications and certifications, salary, and available metrics of performance; and 2) instructional environment: learning materials, school and classroom infrastructure, learning facilities.
3. Household education burden. A major element of equity discussion in low- and middle-income countries, the relative burden of education-related expenditure for households in the bottom quintile of a wealth distribution will be examined as a separate element, which may or may not be tied to the system data (depending on the country/system).
The paper will illustrate the differences in the magnitudes of (in-)equity in resource allocation across systems through the following indicators:
 The magnitude of gap between high-needs and low-needs schools on recognized, validated learning assessments, for each system with available data.
 Proportion of resources allocated to high-needs schools. This will include % of qualified teachers in high needs schools; % high needs classrooms and schools equipped with instructional materials (Will need to make decisions on what is reported for each).
 Proportion of educational resource burden on lowest income/ wealth families.

Data. The study will pull data from several education systems across a range of levels of economic development, including one high-income, two middle income, and one lower-income country. This paper will seek to draw cross-national parallels for analysis, and offer a way of applying a common lens to contextually determined estimations of needs and resources.
Application/ Contribution: The paper will serve as a starting point for cross-national analysis of equity in resource allocation, and provides both an empirical and a conceptual contribution to the education finance literature. It is hoped that this study will support ongoing work of the Global Partnership for Education, the UNESCO Institute for Statistics, and the World Bank.

Authors

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