Did mandatory busing programs in the 1970s increase the school achievement of disadvantaged minority youth? Does obtaining a college degree increase an individual's labor market earnings? Did the use of the butterfly ballot in some Florida counties in the 2000 presidential election cost Al Gore votes? If so, was the number of miscast votes sufficiently large to have altered the election outcome? At their core, these types of questions are simple cause-and-effect questions. Simple cause-and-effect questions are the motivation for much empirical work in the social sciences. This book presents a model and set of methods for causal effect estimation that social scientists can use to address causal questions such as these. The essential features of the counterfactual model of causality for observational data analysis are presented with examples from sociology, political science, and economics.
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The authors have done an excellent job in introducing RCM. Feel like that it's explanation of the RCM methodology is clearer than those in Mostly Harmless. But its explanations of econometrics are quite superficial. For in depth technical discussions, see Mostly Harmless. NOTE: The authors have revised, expanded, and published a 2nd edition.
评分一个严重被低估的书
评分The authors have done an excellent job in introducing RCM. Feel like that it's explanation of the RCM methodology is clearer than those in Mostly Harmless. But its explanations of econometrics are quite superficial. For in depth technical discussions, see Mostly Harmless. NOTE: The authors have revised, expanded, and published a 2nd edition.
评分看这么多文字的社会学的书还不太习惯，暂时就看了前两章。
评分看这么多文字的社会学的书还不太习惯，暂时就看了前两章。
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