Administrative Data

Definition

Administrative data refers to information collected by government or organizations as part of their routine operations. This data is often used to manage programs and services, making it a valuable resource for measuring outcomes, evaluating policies, and assessing the impact of interventions. Its systematic collection can provide insights into various indicators and facilitate more efficient research designs, such as randomized control trials and regression discontinuity analyses.

5 Must Know Facts For Your Next Test

1. Administrative data is often derived from various sources like tax records, school enrollment files, healthcare databases, and employment records.
2. Using administrative data can enhance the efficiency of impact evaluations by providing large sample sizes without the need for extensive field data collection.
3. This type of data allows for the analysis of outcomes over time, enabling researchers to observe trends and effects that might not be apparent in cross-sectional studies.
4. One challenge with administrative data is ensuring its accuracy and completeness, which is essential for drawing valid conclusions from evaluations.
5. Administrative data can also be linked with other datasets, such as survey data or experimental data, to provide a richer context for understanding outcomes.

Review Questions

• How can administrative data improve the measurement of outcomes in impact evaluations?
  • Administrative data improves outcome measurement by providing large and often comprehensive datasets that capture relevant indicators over time. This information can help researchers assess program effectiveness more accurately than small-scale surveys alone. By leveraging existing records from various sources, evaluators can analyze trends and compare results across different demographics or geographical areas, leading to more reliable conclusions about the impact of interventions.
• Discuss how administrative data can be utilized in factorial designs and multi-arm trials for evaluating interventions.
  • In factorial designs and multi-arm trials, administrative data can provide baseline measurements and outcome tracking across different treatment groups. By incorporating this pre-existing data, researchers can save time and resources on collecting primary data while still ensuring that they have enough information to analyze the effects of different interventions. The integration of administrative data allows for a more robust evaluation by maintaining a higher level of statistical power due to larger sample sizes from diverse populations.
• Evaluate the potential limitations of using administrative data in regression discontinuity analysis compared to traditional survey methods.
  • While administrative data offers significant advantages in terms of sample size and efficiency for regression discontinuity analysis, there are limitations compared to traditional survey methods. One major concern is the potential lack of specific variables needed for causal inference which might be available through surveys but absent in administrative records. Additionally, issues related to data accuracy and completeness can affect the reliability of findings. Furthermore, administrative datasets may not capture context-specific factors or subjective experiences that surveys could provide, thus limiting a comprehensive understanding of the intervention's impact.

Related terms

Data Quality: Data quality refers to the overall utility of a dataset, including its accuracy, completeness, reliability, and relevance to the intended purpose.

Impact Evaluation: Impact evaluation is the assessment of the changes that can be attributed to a particular intervention or program, using various methodologies to determine effectiveness.

Longitudinal Data: Longitudinal data is collected over a period of time, allowing researchers to track changes and trends in outcomes for the same subjects.