EconPapers    
Economics at your fingertips  
 

PERTURBED POLYNOMIAL PATH METHOD FOR ACCURATELY COMPUTING AND EMPIRICALLY EVALUATING TOTAL FACTOR PRODUCTIVITY

Baoline Chen and Peter A. Zadrozny

No 268, Computing in Economics and Finance 2004 from Society for Computational Economics

Abstract: 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.

Keywords: Purterbation methods; Computing productivity index numbers (search for similar items in EconPapers)
JEL-codes: C32 C43 C63 (search for similar items in EconPapers)
Date: 2004-08-11
References: Add references at CitEc
Citations: Track citations by RSS feed

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf4:268

Access Statistics for this paper

More papers in Computing in Economics and Finance 2004 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2019-12-03
Handle: RePEc:sce:scecf4:268