Stata Do-Files for Long-Term Care Analysis Across Europe and the U.S.

Matthias Kredler's research provides a methodology to correct care hours for nursing home selection bias. The accompanying Stata do-files, harvested by e-cienciaDatos, were last updated in October 2025. This work develops stylized facts on how informal and formal care is provided across several countries.

Use Cases

• Replicate the study's methodology for correcting care hour estimates based on nursing home selection.
• Conduct comparative analysis of informal versus formal care provision across different countries.
• Build upon the provided stylized facts to model long-term care demand and supply.
• Apply the developed correction methodology to other demographic or health survey datasets.

Strengths

• Methodology is explicitly designed to address a known selection bias in nursing home data.
• Analysis covers a cross-country scope, including several European nations and the United States.
• Associated with a specific research paper, providing academic context for the code.

Limitations

• The dataset description lacks column-level documentation, requiring manual inspection of the do-files.
• Row count and data scale are unknown, limiting suitability assessment for large-scale modeling.
• The actual data files referenced by the do-files are not described and must be sourced separately.

Provenance

Source

KREDLER, MATTHIAS via e-cienciaDatos Harvested Dataverse

Collection Method

Likely contains statistical code (Stata do-files) developed for the associated research paper.

Freshness

Last updated 2025-10-14 21:27:32.

Geography

Several European countries and the United States.