Working Paper: NBER ID: w21592
Authors: David N. Figlio; Krzysztof Karbownik; Kjell G. Salvanes
Abstract: Thanks to extraordinary and exponential improvements in data storage and computing capacities, it is now possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago. As the world has developed this remarkable capacity to store and analyze data, so have the world’s governments developed large-scale, comprehensive data files on tax programs, workforce information, benefit programs, health, and education. While these data are collected for purely administrative purposes, they represent remarkable new opportunities for expanding our knowledge. This chapter describes some of the benefits and challenges associated with the use of administrative data in education research. We also offer specific case studies of data that have been developed in both the Nordic countries and the United States, and offer an (incomplete) inventory of data sets used by social scientists to study education questions on every inhabited continent on earth.
Keywords: Administrative Data; Education Research; Causal Inference
JEL Codes: I20
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| administrative data (C81) | identification of causal relationships (C22) |
| mandatory school reform in Norway (I28) | causal effect of parental education on children's educational outcomes (I24) |
| parental education (I24) | children's long-term outcomes (J13) |
| administrative data (C81) | heterogeneous effects of educational policies (I24) |
| early childhood education policies (I28) | various subgroups of children (C92) |
| administrative data (C81) | precision of estimates in educational research (C90) |
| large sample sizes (C55) | detection of modest yet meaningful relationships (C52) |
| administrative data (C81) | study of rare events (C46) |
| economic shocks (F69) | educational outcomes (I26) |