Identification Problems in the Social Sciences 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Identification Problems in the Social Sciences

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Charles F. Manski 作者
Harvard University Press
譯者
1999-3-15 出版日期
194 頁數
USD 33.50 價格
Paperback
叢書系列
9780674442849 圖書編碼

Identification Problems in the Social Sciences 在線電子書 圖書標籤: econometrics  經濟學  方法論  identification  Methodology  Manski  英文原版  經濟   


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Identification Problems in the Social Sciences 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Identification Problems in the Social Sciences 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Identification Problems in the Social Sciences 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Identification Problems in the Social Sciences 在線電子書 著者簡介


Identification Problems in the Social Sciences 在線電子書 著者簡介


Identification Problems in the Social Sciences 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Identification Problems in the Social Sciences 在線電子書 圖書描述

This text provides a language and a set of tools for finding bounds on the predictions that social and behavioural scientists can logically make from non-experimental and experimental data. Economist Charles Manski draws on examples from criminology, demography, epidemiology, social psychology and sociology as well as economics to illustrate this language and to demonstrate the broad usefulness of the tools. There are many traditional ways to present identification problems in econometrics, sociology and psychometrics. Some of these are primarily statistical in nature, using concepts such as flat likelihood functions and non-distinct parameter estimates. Manski's strategy is to divorce identification from purely statistical concepts and to present the logic of identification analysis in ways that are accessible to a wide audience in the social and behavioural sciences. In each case problems are motivated by real examples with real policy importance, the mathematics is kept to a minimum, and the deductions on identifiability are derived providing fresh insights. Manski begins with the conceptual problem of extrapolating predictions from one population to some new population or to the future. He then analyzes the fundamental selection problem that arises whenever a scientist tries to predict the effects of treatments on outcomes. He specifies assumptions and develops his non-parametric methods of bounding predictions. Manski shows how these tools should be used to investigate common problems such as predicting the effect of family structure on children's outcomes and the effect of policing on crime rates. Successive chapters deal with topics such as the use of experiments to evaluate social programmes, the use of case-control sampling by epidemiologists studying the association of risk factors and disease and the use of intentions data by demographers seeking to predict future fertility. The book closes by examining two central identification problems in the analysis of social interactions: the classical simultaneity problem of econometrics and the reflection problem faced in analyses of neighbourhood and contextual effects.

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