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paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Broschiert. Condizione: Gut. Auflage: 1. 473 Seiten Einband und Kanten minimal berieben, sonst gut erhalten. LIEFERZEITEN / DELIVERY TIMES: DEUTSCHLAND 5 - 14 Tage EUROPA/EUROPE: 7 - 30 Tage/Days USA/WELTWEIT/WORLDWIDE: 14 - 60 Tage/Days (!!!) +++ Sprache: Deutsch Gewicht in Gramm: 600.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 251 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condizione: New.

Condizione: New. pp. 224.

Condizione: New. pp. 244.

Condizione: New. pp. 260.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.…

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.…

Taschenbuch. Condizione: Neu. Causal Analysis in Population Studies | Concepts, Methods, Applications | Henriette Engelhardt (u. a.) | Taschenbuch | The Springer Series on Demographic Methods and Population Analysis | viii | Englisch | 2010 | Springer | EAN 9789048182329 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condizione: New.

Condizione: New.

Taschenbuch. Condizione: Neu. Human Capital and Economic Growth | The Impact of Health, Education and Demographic Change | Alberto Bucci (u. a.) | Taschenbuch | xxxii | Englisch | 2021 | Springer | EAN 9783030216016 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This edited collection explores the links between human capital (both in the form of health and in the form of education), demographic change, and economic growth. Using empirical as well as theoretical perspectives, the authors investigate several important issues in the context of human capital, namely population ageing, inequality, public policy, and long-term economic development. Ultimately, they demonstrate that the accumulation of human capital is of crucial importance to long-run economic growth.…

Condizione: New. pp. XXXII, 361 47 illus., 18 illus. in color. 1st ed. 2019 edition NO-PA16APR2015-KAP.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Paperback. Condizione: Brand New. 396 pages. 8.27x5.83x0.93 inches. In Stock.

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Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: New. Warum bleibt der Kinderwunsch vieler Paare unerfuellt, waehrend sich andere gegen Kinder entscheiden? Das Buch praesentiert die Ergebnisse einer Arbeitsgruppe der Berlin-Brandenburgischen Akademie der Wissenschaften und der Leopoldina zu den Gruenden niedriger .

Condizione: new. Questo è un articolo print on demand.

Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference. 252 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Agent-Based Computational Demography (ABCD) aims at starting a new stream of research among social scientists whose interests lie in understanding demographic behaviour. The book takes a micro-demographic (agent-based) perspective and illustrates the potentialities of computer simulation as an aid in theory building. The chapters of the book, written by leading experts either in demography or in agent-based modelling, address several key questions. Why do we need agent-based computational demography How can ABCD be applied to the study of migrations, family demography, and historical demography What are the peculiarities of agent-based models as applied to the demography of human populations ABCD is of interest to all scientists interested in studying demographic behaviour, as well as to computer scientists and modellers who are looking for a promising field of application. 210 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. Examples include population dynamics, evolution of social norms, communication structures, patterns in eco-systems and socio-biology, natural resource management, spread of diseases and development processes. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases. 226 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference. 260 pp. Englisch.…

Condizione: new. Questo è un articolo print on demand.