| 期刊全稱 | Analysis of Microdata | | 影響因子2023 | Rainer Winkelmann,Stefan Boes | | 視頻video | http://file.papertrans.cn/157/156396/156396.mp4 | | 發(fā)行地址 | Can be used as a textbook for undergraduate, Master`s or first-year Ph.D. students in economics and related disciplines as well a supplementary text to an applied microeconomics field course (e. g. ar | | 圖書封面 |  | | 影響因子 | The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book is to familiarize readers with a wide range of commonly used models, and thereby to enable them to become critical consumers of current empirical research, and to conduct their own empirical analyses. The focus of the book is on regression-type models in the context of large cross-section samples. In microdata applications, dependent variables often are qualitative and discrete, while in other cases, the sample is not randomly drawn from the population of interest and the dependent variable is censored or truncated. Hence, models and methods are required that go beyond the standard linear regression model and ordinary least squares. Maximum li- lihood estimation of conditional probability models and marginal probability e?ects are introduced here as the unifying principle for modeling, estimating and interpreting microdata relationships. We consider the limitation to m- imum likelihood sensible, from a pedagogical point of view if the book is to be used in a sem | | Pindex | Book 20061st edition |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-11-3 04:46
發(fā)表于 2025-3-21 17:29:08
