IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Perturbed Polynomial Path Method For Accurately Computing And Empirically Evaluating Total Factor Productivity

  • Baoline Chen
  • Peter A. Zadrozny

The paper describes and illustrates a method for generalizing the standard computation of period-to-period percentage change of total factor productivity (TFP) to computation of TFP based on a best k-times-differentiable model. A "model" is a k-times-differentiable functional form of a production function, f(×), a parameterization of f(×) over a data sample, and values of constant structural parameters which determine f(×) in the sample. Given f(×) and sample input price and quantity vectors, we use the perturbed polynomial path method to compute the optimal input vector. Thus, a given model and input data imply input residuals (difference between optimal and observed inputs), and hence, –2x a normal-distribution log-likelihood function, L, or information criterion extension to account for parameter uncertainty. A model and its implied TFP are statistically reliable when L is finite and are "best" when L is minimized. The standard Solow-residual TFP is based on 1st-order Cobb-Douglas-type approximation of any differentiable production function and share parameters set to input-cost shares, implying observed inputs are always optimal, degrees of freedom are exhausted, so the model and implied TFP have no statistical reliability. In the paper, we illustrate these ideas using U.S. manufacturing industry data from 1949-2001. We develop models based on CES and tiered-CES production functions and compare their implied TFP with benchmark Solow residuals.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 268.

as
in new window

Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:sce:scecf4:268
Contact details of provider: Web page: http://comp-econ.org/
Email:


More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:sce:scecf4:268. 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: (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.