SOME ASPECTS OF SPECIFIKATION OF LINEAR PROBABILITY MODEL
Keywords:
Linear probability modelAbstract
In many situations dependent variable in a regression equation is not continual, but discrete choice. Modeling in such situations includes cases when dependent variable takes only two values as well as cases when the choice has to be made between few possibilities. All the models can be basically classified as linear and nonlinear. The linear probability model allows simple estimation of the parameters and interpretation of the results. Besides the model with dichotomous dependent variable, in the article is presented the model with replicated data and the model with polytomous dependent variables.
References
Aldrich, John H., Nelson D.Forrest, Linear probability, Logit and Probit models, SAGE Publications, Newbury Park, 1984.
Gujarati, Damodar, Essentials of Econometrics, AMcGraw-Hill , New York, 1992.
Ramanat an, Ramu, Introductory Econometrics, The Dryden Press, Harcourt Brace & Company, Orlando, 1997.
Кмента, Јан , Почела економетрије, Мате, Загреб, 1997.
Милојић, Драгана, Дискретни регресиони модели, SYMOPIS 1997, Економски институт, Београд, 1997.
Judge,George G., Griffiths,William E., Hill Carter R., Lee Tsoung-Chao, The Theory and practise of econometrics, John Wiley & Sons, New York, 1980.
