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What constitutes a causal explanation, and must an explanation be causal? What warrants a causal inference, as opposed to a descriptive regularity? What techniques are available to detect when causal effects are present, and when can these techniques be used to identify the relative importance of these effects? What complications do the interactions of individuals create for these techniques? When can mixed methods of analysis be used to deepen causal accounts? Must causal claims include generative mechanisms, and how effective are empirical methods designed to discover them? The Handbook of Causal Analysis for Social Research tackles these questions with nineteen chapters from leading scholars in sociology, statistics, public health, computer science, and human development.
In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.
How often do working-class children obtain college degrees and then
pursue professional careers? Conversely, how frequently do the
children of doctors and lawyers fail to enter high status careers
upon completion of their schooling? As inequalities of wealth and
income have increased in industrialized nations over the past 30
years, have patterns of between-generation mobility changed?
In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.
How often do working-class children obtain college degrees and then pursue professional careers? Conversely, how frequently do the children of doctors and lawyers fail to enter high status careers upon completion of their schooling? As inequalities of wealth and income have increased in industrialized nations over the past 30 years, have patterns of between-generation mobility changed? In this volume, leading sociologists and economists present original findings and conceptual arguments in response to questions like these. After assessing the range of mobility patterns observed in recent decades, the volume considers the mechanisms that generate mobility, focusing on both the training and skills that are rewarded in the labor market as well as the role of educational institutions in certifying graduates for professional positions. The volume concludes with chapters that assess the contexts of social mobility, examining the impact of macroeconomic conditions and societal levels of inequality on social and economic mobility.
What constitutes a causal explanation, and must an explanation be causal? What warrants a causal inference, as opposed to a descriptive regularity? What techniques are available to detect when causal effects are present, and when can these techniques be used to identify the relative importance of these effects? What complications do the interactions of individuals create for these techniques? When can mixed methods of analysis be used to deepen causal accounts? Must causal claims include generative mechanisms, and how effective are empirical methods designed to discover them? The Handbook of Causal Analysis for Social Research tackles these questions with nineteen chapters from leading scholars in sociology, statistics, public health, computer science, and human development.
China's transformation over the past four decades has been unprecedented. The vision of its leaders for the next three decades is unprecedented too, as China seeks to fashion an advanced economy without significant political and social liberalization. Stephen Morgan provides a wide-ranging examination of China's remarkable economic history from the time of the great divergence to the present day. Alongside the familiar story of GDP growth, he considers a comprehensive range of issues, including business management, energy use, foreign direct investment, government, innovation and consumerism as well as social and demographic factors such as social networks, health, education and migration and their interlinked challenges for the Chinese state. The specifics of development are examined - capitalism from above and below and its regional variances - as well as notable consequences, including growing inequality and severe pollution. The book also assesses the challenges to China's continued growth, including its ageing and shrinking workforce (and rising dependency ratio), the constraints on innovation and raising productivity, as well as its ambitious international plans. The book provides an accessible and authoritative survey of China's recent economic history and the workings of its unique political economy suitable for courses in Asian business and economy, Chinese history and East Asian studies.
China's transformation over the past four decades has been unprecedented. The vision of its leaders for the next three decades is unprecedented too, as China seeks to fashion an advanced economy without significant political and social liberalization. Stephen Morgan provides a wide-ranging examination of China's remarkable economic history from the time of the great divergence to the present day. Alongside the familiar story of GDP growth, he considers a comprehensive range of issues, including business management, energy use, foreign direct investment, government, innovation and consumerism as well as social and demographic factors such as social networks, health, education and migration and their interlinked challenges for the Chinese state. The specifics of development are examined - capitalism from above and below and its regional variances - as well as notable consequences, including growing inequality and severe pollution. The book also assesses the challenges to China's continued growth, including its ageing and shrinking workforce (and rising dependency ratio), the constraints on innovation and raising productivity, as well as its ambitious international plans. The book provides an accessible and authoritative survey of China's recent economic history and the workings of its unique political economy suitable for courses in Asian business and economy, Chinese history and East Asian studies.
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