Estimating Learning Curves from Aggregate Monthly Data
In this paper the problems of using aggregate monthly data to estimate learning curves are investigated. Here, aggregate monthly data on labor hours are assumed to contain some of both fixed and variable labor hours. They are also assumed to be influenced by fluctuating quantities of work in process. A distributed lag model is developed to deal with these two characteristics of aggregate monthly data. The model is generalized to permit production rate to influence labor productivity. This generalized model is then estimated and compared to a cumulative average learning curve in analyzing the impact of a production break. A set of production data which arose from a government contract claim is used for this purpose.
Volume (Year): 30 (1984)
Issue (Month): 8 (August)
|Contact details of provider:|| Postal: |
Web page: http://www.informs.org/Email:
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:30:y:1984:i:8:p:982-992. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc)
If references are entirely missing, you can add them using this form.