Nonparametric Estimation of Triangular Simultaneous Equations Models
This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. The authors use series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. The authors derive consistency and asymptotic normality results for their estimator, including optimal convergence rates. An empirical example, on the relationship between the hourly wage rate and hours worked, illustrates the utility of the authors' approach.
(This abstract was borrowed from another version of this item.)
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.
|Date of creation:||May 1998|
|Date of revision:|
|Contact details of provider:|| Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA|
Phone: (617) 253-3361
Fax: (617) 253-1330
Web page: http://econ-www.mit.edu/
More information through EDIRC
|Order Information:|| Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA|
When requesting a correction, please mention this item's handle: RePEc:mit:worpap:98-6. 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: (Linda Woodbury)
If references are entirely missing, you can add them using this form.