GMMCOVEARN: A Stata Module for GMM Estimation of the Covariance Structure of Earnings
This note describes and illustrates a new Stata program, gmmcovearn, that estimates the covariance structure of earnings for a variety of models using the GMM estimator. The program estimates models that incorporate time factor loadings and cohort factor loadings on both the transitory and permanent component, allows the transitory component to follow either an AR(1) or an ARMA(1,1) process and allows for a random growth and/or random walk process on the permanent component. The program has been used in recent papers by Doris et al (2010a, 2010b).
|Date of creation:||2010|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.maynoothuniversity.ie/economics-finance-and-accounting
More information through EDIRC
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.:
- Aedin Doris & Donal O'Neill & Olive Sweetman, 2010. "Aggregate Earnings Inequality in Europe: Permanent Differences or Transitory Fluctuations?," Economics, Finance and Accounting Department Working Paper Series n211-10.pdf, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
When requesting a correction, please mention this item's handle: RePEc:may:mayecw:n212-10.pdf. 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: ()
If references are entirely missing, you can add them using this form.