Education production functions

2018 ◽  
pp. 246-271 ◽  
Author(s):  
Jack Britton ◽  
Anna Vignoles
Keyword(s):  
Production Functions ◽  
Education Production

scholarly journals Collegiate Grading Practices and the Gender Pay Gap

2000 ◽  
Vol 8 ◽  
pp. 10
Author(s):  
Alicia C. Dowd
Keyword(s):  
Higher Education ◽  
Theoretical Analysis ◽  
College Women ◽  
Production Functions ◽  
Grading Practices ◽  
Gender Pay Gap ◽  
Pay Gap ◽  
Education Production ◽  
Research Findings ◽  
High Grading

Extending research findings by R. Sabot and J. Wakeman-Linn (1991), this article presents a theoretical analysis showing that relatively low grading quantitative fields and high grading verbal fields create a disincentive for college women to invest in quantitative study. Pressures on grading practices are modeled using higher education production functions.

Regression Analyses and Education Production Functions: Can They Be Trusted?

1975 ◽  
Vol 45 (3) ◽  
pp. 325-350 ◽  
Author(s):  
Daniel Luecke ◽  
Noel McGinn
Keyword(s):  
Computer Simulation ◽  
Regression Analysis ◽  
Production Functions ◽  
Statistical Techniques ◽  
Computer Simulation Model ◽  
Data Sets ◽  
Regression Analyses ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Education Production

Many studies have purported to demonstrate that schooling has little independent impact on achievement and that administrators can do little to boost students'test scores. Daniel F. Luecke and Noel F. McGinn question such results and use variations of a computer simulation model to generate data sets similar to those collected by educational researchers. They subject the data generated to several kinds of aggregation procedures and regression analysis, and compare the statistics thus yielded with their knowledge of the causal relationships programmed into the data. They conclude that many "no significant effect" findings may be artifacts of statistical techniques used to analyze cross-sectional survey data.

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