This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Dynamic Factor Demand Models and Productivity Analysis

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
M. Ishaq Nadiri () (Department of Economics, New York University and National Bureau of Economic Research)
Ingmar R. Prucha () (Department of Economics, University of Maryland)
Abstract

In this paper we discuss recent advances in modeling and estimating dynamic factor demand models, and review the use of such models in analyzing the production structure, the determinants of variable and quasi-fixed factors, and productivity growth. The paper also discusses the traditional approach to productivity analysis based on the Divisia index number methodology. Both approaches may be seen a complementary. The conventional index number approach will measure the rate of technical change correctly if certain assumptions about the underlying technology of the firm and output and input markets hold. Furthermore, the conventional index number approach is appealing in that it can be easily implemented. However, if the underlying assumptions do not hold, then the conventional index number approach will, in general, yield biased estimates of technical change. The econometric approach based on general dynamic factor demand models allows for a careful testing of various features of a postulated model. Furthermore it not only provides for estimates of technical change, but can also yield a rich set of critical information on the structure of production, the dynamics of investment in physical and R&D capital, the effects of spillovers, the depreciation rate of capital, the impact of taxes, expectations, etc. The paper also explores in terms of a Monte Carlo study how estimates of important characteristics of the production process can be affected by model misspecification. The results suggest adopting a simple specification for reasons of convenience may result in serious biases.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.bsos.umd.edu/econ/papers/prucha3.pdf
File Format: application/pdf
File Function: Full text
Download Restriction: no

Publisher Info
Paper provided by University of Maryland, Department of Economics in its series Electronic Working Papers with number 99-005.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: May 1999
Date of revision:
Handle: RePEc:umd:umdeco:99-005

Contact details of provider:
Postal: Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
Web page: http://www.econ.umd.edu/

Order Information:
Postal: Ms. Elizabeth Martinez, Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
Email:

For technical questions regarding this item, or to correct its listing, contact: (Peter Murrell).

Related research
Keywords:

Find related papers by JEL classification:
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
D2 - Microeconomics - - Production and Organizations
O3 - Economic Development, Technological Change, and Growth - - Technological Change
O4 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Petri Rouvinen, 2002. "The Existence Of R&D Spillovers: A Cost Function Estimation With Random Coefficients," Economics of Innovation and New Technology, Taylor and Francis Journals, vol. 11(6), pages 525-541, January. [Downloadable!] (restricted)
  2. Susanto Basu & John Fernald, 2000. "Why Is Productivity Procyclical? Why Do We Care?," NBER Working Papers 7940, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
Statistics
Access and download statistics

Did you know? All RePEc services are meant to be be free forever, as they are all run by volunteers.

This page was last updated on 2009-12-10.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.