A new approach to limited-dependent variable count data or other model types is considered. Instead of adopting maximum likelihood estimation based on a full distributional assumption or smoothing techniques and semiparametric estimation, the novel idea is to use an approximation to the probability of, say, the zero event. The approximation is based on moments and uses old results for the probability generating function. The approximation is evaluated in a small Monte Carlo experiment. In empirical models of choice set size for Swedish unemployed and of nationalization frequencies for developing countries the results indicate good performance both computationally and resultwise. The results indicate that already quite low order expansions are well-behaved and useful for estimation.
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 Umeå University, Department of Economics in its series Umeå Economic Studies with number
451.
Length: 6 pages Date of creation: 15 Dec 1997 Date of revision: Publication status: Published in American Statistical Association: Proceedings of the Business and Economic Statistics Section, 1997, pages 189-194. Handle: RePEc:hhs:umnees:0451
Contact details of provider: Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden Phone: 090 - 786 61 42 Fax: 090 - 77 23 02 Email: Web page: http://www.econ.umu.se/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Kjell-Göran Holmberg).