Causal Analysis in Population Studies (eBook)

Concepts, Methods, Applications

Henriette Engelhardt, Hans-Peter Kohler, Alexia Fürnkranz-Prskawetz (Herausgeber)

eBook Download: PDF

2009 | 2009
VIII, 252 Seiten
Springer Netherland (Verlag)
978-1-4020-9967-0 (ISBN)

Infos

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.

Inhalt

Contents 6
Contributors 8
Causal Analysis in Population Studies 10
1.1 Introduction 10
1.2 Structure of the Volume 13
References 16
Issues in the Estimation of Causal Effects in Population Research, with an Application to the Effects of Teenage Childbearing 17
2.1 Introduction 17
2.2 The Basic Causal Model 18
2.3 Instrumental Variables 21
2.4 Types of Instrumental Variables 26
2.5 Additional Issues 31
2.6 Summary and Conclusions 35
References 36
Sequential Potential Outcome Models to Analyze the Effects of Fertility on Labor Market Outcomes 38
3.1 Introduction 38
3.2 The Dynamic Causal Model - Notation, Effects, and Identification 41
3.3 Estimation 46
3.4 Specifying Causal Parameters of Interest 52
3.5 Data 54
3.6 Estimation Results 57
3.7 Conclusions 59
References 62
Structural Modelling, Exogeneity, and Causality 65
4.1 Causal Analysis in the Social Sciences 65
4.2 Structural Modelling 70
4.3 Conditional Models, Exogeneity and Causality 73
4.4 Confounding, Complex Systems and Completely Recursive Systems 77
4.5 Partial Observability and Latent Variables 82
4.6 Discussion and Conclusion 85
References 87
Causation as a Generative Process. The Elaboration of an Idea for the Social Sciences and an Application to an Analysis of an Interdependent Dynamic Social System 89
5.1 Introduction 89
5.2 Models of Causal Inference 90
5.3 Parallel and Interdependent Processes 94
5.4 An Application Example 103
5.5 Substantial Explanations 106
5.6 Summary and Concluding Remarks 111
References 112
Instrumental Variable Estimation for Duration Data 116
6.1 Introduction 116
6.2 Endogenous Covariates in Duration Models 119
6.3 Instrumental Variable Linear Rank Estimation 125
6.4 Application to the Illinois Re-employment Bonus Experiment 131
6.5 Conclusion 138
References 140
Appendix 1: Identification of the GAFT Model 141
Appendix 2: Counting Process Interpretation 143
Appendix 3 Asymptotic Properties of the IVLR 146
Appendix 4 Additional Tables for the IVLR of Reemployment Bonus Experiment 150
Female Labour Participation with Concurrent Demographic Processes: An Estimation for Italy 154
7.1 Introduction 154
7.2 Background 154
7.3 Model Specification: Theoretical and Methodological Issues 156
7.4 The Data 163
7.5 Results 164
7.6 Discussion 166
References 169
New Estimates on the Effect of Parental Separation on Child Health 171
8.1 Introduction 171
8.2 Background 173
8.3 Statistical Framework and Estimation Strategy 175
8.4 Data, Sample, and Descriptive Evidence 182
8.5 Estimation Results 187
8.6 Conclusion 196
References 198
Appendix 202
Assessing the Causal Effect of Childbearing on Household Income in Albania 204
9.1 Introduction 204
9.2 The Albanian Background 206
9.3 The Albania Living Standards Measurement Study 207
9.4 A Measure of Well-Being 208
9.5 Descriptive Statistics 212
9.6 Identifying the Causal Effect of a New Birth 214
9.7 Results 220
9.8 Conclusions 232
References 233
Causation and Its Discontents 235
References 241
Index 245

Produkt-Details

• Erscheint lt. Verlag: 5.5.2009
• Reihe/Serie: The Springer Series on Demographic Methods and Population Analysis
• Reihe/Serie: The Springer Series on Demographic Methods and Population Analysis
• Zusatzinfo: VIII, 252 p.
• Verlagsort: Dordrecht
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Sozialwissenschaften ► Politik / Verwaltung
• Themenwelt: Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung
• Themenwelt: Sozialwissenschaften ► Soziologie ► Spezielle Soziologien
• Themenwelt: Technik
• Schlagworte: Causal Analysis • Causal effects • Counterfactual Approach • Demographic Processes • Demography • Econometrics • Non-experimental Data • Population Research • Population Studies • Social Sciences
• ISBN-10: 1-4020-9967-3 / 1402099673
• ISBN-13: 978-1-4020-9967-0 / 9781402099670