The generalized method of moments (GMM) estimation technique is discussed for count data models with endogenous regressors. Count data models can be specified with additive or multiplicative errors and it is shown that, in general, a set of instruments is not orthogonal to both error types. Simultaneous equations with a dependent count variable often do not have a reduced form which is a simple function of the instruments. However, a simultaneous model with a count and a binary variable can only be logically consistent when the system is triangular. Utilizing data from the British Health and Lifestyle Survey 1991-1992, the GMM estimator is used in the estimation of a model explaining the number of visits to doctors, with a self-reported binary health index as a possible endogenous regressor. If this regressor is truly endogenous, one expects the pseudo-likelihood estimate of its coefficient to be biased upwards. Indeed, for the additive model, the estimated coefficient of the binary health index decreases in value when the possible endogeneity of this regressor is taken into account. Further indication of endogeneity is given by the fact that the overidentifying restrictions are rejected in the multiplicative model, but not in the additive model. Finally, a model that includes predicted latent health instead of the binary health index is estimated in stages.
Download Info
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
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.
Publisher Info
Paper provided by Institute for Fiscal Studies in its series IFS Working Papers with number
W96/15.
Length: Date of creation: Aug 1996 Date of revision: Handle: RePEc:ifs:ifsewp:96/15
Contact details of provider: Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE Phone: (+44) 020 7291 4800 Fax: (+44) 020 7323 4780 Email: Web page: http://www.ifs.org.uk
Order Information: Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE Email:
For technical questions regarding this item, or to correct its listing, contact: (Emma Hyman).
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.) This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.