How efficient are German life sciences? Econometric evidence from a latent class stochastic output distance model

Area of Science:

• Economics of Education
• Higher Education Research
• Operations Research

Background:

• Technical efficiency in higher education is crucial for resource allocation.
• Production technology heterogeneity across academic sub-disciplines can bias efficiency measurements.
• Previous studies often overlook sub-disciplinary technological differences.

Purpose of the Study:

• To investigate technical efficiency in German higher education using a latent class stochastic frontier model.
• To determine if sub-disciplines within life sciences (biology, agricultural sciences) exhibit distinct production technologies.
• To assess the impact of neglecting latent classes on efficiency perceptions.

Main Methods:

• Latent class stochastic frontier model applied to an output distance function.
• Bootstrapping techniques for model validation.
• Unique dataset combining German Federal Statistical Office data with bibliometric data from ISI Web of Science.

Main Results:

• Neglecting latent classes leads to biased efficiency perceptions.
• A model distinguishing research-focused and teaching-focused units shows improved fit.
• Research-focused units demonstrate higher median technical efficiency than teaching-focused units.
• No significant difference in mean technical efficiency between German agricultural sciences and biology was found when using the latent class model.

Conclusions:

• Accounting for technological heterogeneity via latent classes is essential for accurate higher education efficiency analysis.
• Sub-disciplinary differences, particularly the research vs. teaching focus, significantly impact efficiency.
• The latent class model provides a more nuanced understanding of efficiency in diverse academic fields.