Titlebook: Semiparametric Methods in Econometrics; Joel L. Horowitz Book 1998 Springer Science+Business Media New York 1998 Estimator.Finite.Random v

爵士乐

不断的变动

淡紫色花

Nefarious

Single-Index Models,e the mean annual earnings of workers in a certain population as a function of observable characteristics such as level of education and experience in the workforce. As another example, one may want to estimate the probability that an individual is employed conditional on observable characteristics

乳白光

Binary Response Models,y variables, β is a . vector of constant parameters, Y. is an unobserved, latent dependent variable, and . is an unobserved random variable. The inferential problem is to use observations of . to estimate β and, to the extent possible, the probability that .1 conditional on .

散布

Deconvolution Problems,variable that is independent of .. Such estimation problems are called . because the distribution of the observed random variable, W, is the convolution of the distributions of . and .. Estimating the distribution of . requires deconvoluting the distribution of the observed random variable ..

埋伏

Transformation Models,bserved random vector, β is a vector of constant parameters that is conformable with .,and . is an unobserved random variable that is independent of . is assumed to be strictly increasing to insure that (5.1) uniquely determines . as a function of . and .. In applied econometrics, models of the form

Airtight

投票

HEED

0930-0325 els. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.978-0-387-98477-3978-1-4612-0621-7Series ISSN 0930-0325 Series E-ISSN 2197-7186