A Monte Carlo Study Of Growth Regressions

Topics:
Growth
Tags:
Networking,
Stanford Knowledgebase,
Telecommunications,
VOIP
Source:
Stanford Knowledgebase

FREE Registration is required

Overview: This paper evaluates the bias properties of common estimators used in growth regressions derived from the Solow model. This paper suggests that using an OLS estimator applied in a single cross-section of variables averaged over time performs best in terms of the extent of bias on each of the estimated coefficients. The fixed-effects estimator and the Arellano-Bond estimator greatly overstate the speed of convergence under a wide variety of assumptions concerning the type and extent of measurement error, while between understates it somewhat. Finally, fixed effects and Arellano-Bond bias towards zero the slope estimates on the human and physical capital accumulation variables.

(Is this item miscategorized? Does it need more tags? Let us know.)

Format: PDF | Size: 579KB | Date: Dec 2003 | Pages: 53

People who downloaded this item also downloaded

White Paper A Global Knowledge Template: Project Management Workbook
White Paper Correlation and Simple Linear Regression
White Paper Integration of Advanced Gas Turbine and Combined Cycle Technologies for High Efficiency With Operational Flexibility

Top results from Growth

Case Study Ingersoll Rand Increases Business Agility With Microsoft Online Services
White Paper Citizants: Bringing IT In-House
White Paper Whitepaper:Intelligent Data Management with Dell Product Group
White Paper Whitepaper: Fast, Reliable Data protection from Dell and CommVault
Training Discover Windows 7 for only $99!

» View all Growth listings

advertisement
advertisement
  • Click Here
  • Click Here
  • Click Here
advertisement

Returning users: Log In Here!

Already registered on BNET, TechRepublic, or ZDNet? Simply log in.

Free Membership: Sign Up Now!

Sign up for a free membership today and get instant and unlimited access to one of the largest databases of white papers, webcasts, and casestudies anywhere. Your FREE membership allows you to:

  • Download an unlimited amount of content, including classic and current white papers, case studies, webcasts and more
  • Track content on your chosen topics of interest
  • Receive targeted email alerts when your favorite content is added
  • Save content for future reading
  • Receive our member newsletter

When you register to access this directory, you become a member of BNET. In addition, you allow us to share your information with companies that produce products or services featured in the library--so that such companies may contact you with information and offers regarding their products and services. This enables us to keep the library a free service. As a directory registrant, you will receive a complimentary subscription to the BNET member newsletter, The BNET Report. You can unsubscribe from this newsletter at any time. By clicking the Sign up button, you indicate that you agree to our Terms and Conditions and have read and understand our Privacy Policy (updated).