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J. Pearl (1995)
Causal diagrams for empirical researchBiometrika, 82
A. Dawid (1979)
Conditional Independence in Statistical TheoryJournal of the royal statistical society series b-methodological, 41
I. Shpitser, J. Pearl (2006b)
Proceedings of the Twenty?Second Conference on Uncertainty in Artificial Intelligence
A. Chesher (2003)
Identification in Nonseparable ModelsEconometrica, 71
J. Pearl (2000)
Causality: Models, Reasoning, and Inference
L. Hurwicz (1950)
Statistical Inference in Dynamic Economic Models, Cowles Commission Monograph 10
J. Tian (2009)
Proceedings of the International Joint Conference on Artificial Intelligence
J. Pearl (1995)
Causal diagrams for empirical research? (with discussion), 82
S. Wright (1921)
Correlation and causation, 20
P.R. Rosenbaum, D. Rubin (1983)
The central role of the propensity score in observational studies for causal effects, 70
K. Hirano, G. Imbens (2005)
The Propensity Score with Continuous Treatments
(2002)
Generalized instrumental variables,' in Uncertainty in Artificial Intelligence
S. Greenland (2003)
Quantifying biases in causal models: classical confounding versus collider?stratification biasEconometrica, 14
H. White (2006)
Time-series estimation of the effects of natural experimentsJournal of Econometrics, 135
(2010)
equilibrium, and learning,
Z. Griliches (1977)
Estimating the returns to schooling: some econometric problemsReview of Economics and Statistics, 45
P. Wright
The tariff on animal and vegetable oils
C. Brito, J. Pearl (2002a)
Proceedings of the Eighteenth National Conference on Artificial IntelligenceEconometrica
J. Heckman, Richard Robb (1985)
Alternative methods for evaluating the impact of interventions: An overviewJournal of Econometrics, 30
Alberto Abadie (2003)
Semiparametric instrumental variable estimation of treatment response modelsJournal of Econometrics, 113
J. Angrist, G. Imbens, D. Rubin (1993)
Identification of Causal Effects Using Instrumental Variables
B. Barnow (1980)
Issues in the Analysis of Selectivity Bias. Discussion Papers. Revised.
(1990)
The History of Econometric Ideas (Cambridge
T. Haavelmo (1944)
The probability approach in econometricsInternational Journal of Biostatistics, iii‐vi
J. Hausman, W. Taylor (1983)
Identification in Linear Simultaneous Equations Models with Covariance Restrictions: An Instrumental Variables InterpretationEconometrica, 51
R. Mcdonald (2002)
What can we learn from the path equations?: Identifiability, constraints, equivalencePsychometrika, 67
A. Roy (1951)
Some thoughts on the distribution of earnings, 3
(2006)
Parametric and nonparametric estimation of covariate
J. D. Hamilton (1994)
Time Series AnalysisEconometrica
(2004)
Nonparametric estimation of average treatment effects under exogeneity: a review,
(1956)
The Direction of Time (Berkeley: University of California
Jin Tian (2009)
Parameter Identification in a Class of Linear Structural Equation Models
H. White (2001)
Asymptotic Theory for Econometricians
R.A. Fisher (1935)
The Design of ExperimentsEconometrica
J. Heckman (2005)
The scientific model of causalityJournal of Educational Psychology, 35
J. Heckman, Hidehiko Ichimura, Petra Todd (1998)
Matching As An Econometric Evaluation EstimatorThe Review of Economic Studies, 65
Carlos Brito, J. Pearl (2002)
A graphical criterion for the identification of causal effects in linear models
F. Hayashi (2000)
EconometricsPsychometrika
Kristin Butcher, A. Case (1994)
The Effect of Sibling Sex Composition on Women's Education and EarningsQuarterly Journal of Economics, 109
M. Hernán, J. Robins (2001)
Instruments for causal inference: an epidemiologist?s dreamJournal of Agricultural Research, 17
B. Barnow, G. Cain, A. Goldberger (1980)
Evaluation StudiesQuarterly Journal of Economics, 5
(2003)
OXI(i) nor CP:PXI(i) holds, since neither Z nor U z causes X, justifying the label 'irrelevant exogenous variables.' When = k (as assumed here), condition References Abadie
J. Angrist, G. Imbens, D. Rubin (1996)
Identification of causal effects using instrumental variables? (with discussion)Journal of the American Statistical Association, 91
Karim Chalak, H. White (2012)
Causality, Conditional Independence, and Graphical Separation in Settable SystemsNeural Computation, 24
M. Hernán, J. Robins (2006)
Instruments for Causal Inference: An Epidemiologist's Dream?Epidemiology, 17
(2001)
Asymptotic Theory for Econometricians (New York: Academic
Karim Chalak (2010)
Identification of Local Treatment Effects Using a Proxy for an Instrument
Manabu Kuroki, Zhihong Cai (2008)
On Identifying Total Effects in the Presence of Latent Variables and Selection biasArXiv, abs/1206.3239
J. I (1936)
The Design of ExperimentsNature, 137
J. Heckman, E. Vytlacil (2001)
Nonlinear Statistical Inference: Essays in Honor of Takeshi AmemiyaJournal of Econometrics
(2000)
Econometrics (Princeton, NJ
Vicnent Crawford (2006)
Look-ups as the Windows of the Strategic Soul: Studying Cognition via Information Search in Game ExperimentsLevine's Bibliography
S. Wright (1923)
The Theory of Path Coefficients a Reply to Niles's Criticism.Genetics, 8 3
J. Heckman (1997)
Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations.Journal of Human Resources, 32
M.S. Morgan (1990)
The History of Econometric Ideas
K. Butcher, A. Case (1994)
The effects of sibling sex composition on women's education and earningsEconometrica, 109
H. White, K. Chalak (2010)
Testing a conditional form of exogeneity, 109
G.W. Imbens, W.K. Newey (2009)
Identification and estimation of triangular simultaneous equations without additivity, 77
Carlos Brito, J. Pearl (2006)
Graphical Condition for Identification in recursive SEMArXiv, abs/1206.6821
H. White, K. Chalak (2009b)
Settable systems: an extension of Pearl's causal model with optimization, equilibrium, and learning, 10
M. Joffe, Dylan Small, T. Have, S. Brunelli, H. Feldman (2008)
Extended Instrumental Variables Estimation for Overall EffectsThe International Journal of Biostatistics, 4
I. Shpitser, J. Pearl (2006)
Identification of Conditional Interventional DistributionsArXiv, abs/1206.6876
J. Angrist (1990)
Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative RecordsThe American Economic Review, 80
I. Shpitser, J. Pearl (2006)
Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
Stefan Hoderlein (2004)
Nonparametric Demand Systems , Instrumental Variables and a Heterogeneous Population
J. Stock (2003)
Who Invented Instrumental Variable RegressionJournal of Economic Perspectives, 17
J. Heckman, H. Ichimura, P. Todd (1998)
Matching as an econometric evaluation estimatorEconomics Letters, 65
T. Haavelmo (1943)
The Statistical Implications of a System of Simultaneous EquationsEconometrica, 11
Jin Tian, J. Pearl (2002)
A general identification condition for causal effects
V. Crawford (2008)
Perspectives on the Future of Economics: Positive and Normative Foundations, Vol. 1 of Handbooks of Economic MethodologiesJournal of Human Resources
(2005)
Structural equations, treatment effects, and econometric policy evaluation
A.P. Dawid (1979)
Conditional independence in statistical theory? (wish discussion)Sociological Methodology, 41
Susanne Schennach, H. White, Karim Chalak (2012)
Local indirect least squares and average marginal effects in nonseparable structural systemsJournal of Econometrics, 166
I. Shpitser, J. Pearl (2008)
Complete Identification Methods for the Causal HierarchyJ. Mach. Learn. Res., 9
(1933)
Partial regressions as compared with individual trends,
J. Heckman, S. Urzua, E. Vytlacil (2006)
Understanding instrumental variables in models with essential heterogeneityJournal of Financial Econometrics, 88
C. Brito, J. Pearl (2002b)
Uncertainty in Artificial Intelligence. Proceedings of the Eighteenth ConferenceJournal of the Royal Statistical Society
Rosa Matzkin (2008)
Identification in Nonparametric Simultaneous Equations ModelsEconometrica, 76
Jeffrey Woodbridge (2002)
Econometric Analysis of Cross Section and Panel Data
P. Rosenbaum (2006)
Matched Sampling for Causal Effects: The Central Role of the Propensity Score in Observational Studies for Causal Effects
J. Heckman (1997)
Instrumental variables: a study of implicit behavioral assumptions used in making program evaluationsBiometrika, 32
(1994)
Time Series Analysis (Princeton, NJ
H. Reichenbach (1956)
The Direction of Time
Stefan Hoderlein, E. Mammen (2007)
Identification of marginal effects in nonseparable models without monotonicityEconometrica, 75
D. Rubin (1974)
Estimating causal effects of treatments in randomized and nonrandomized studies.Journal of Educational Psychology, 66
A. Goldberger (1972)
Structural equation methods in the social sciencesReview of Economics and Statistics, 40
P. Carneiro, J. Heckman, E. Vytlacil (2009)
Evaluating marginal policy changes and the average effect of treatment for individuals at the marginEpidemiology, 78
Alberto Abadie, G. Imbens (2004)
Large Sample Properties of Matching Estimators for Average Treatment EffectsEconometrica, 74
Journal of Economic Perspectives—Volume 15, Number 4—Fall 2001—Pages 69–85 Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments
I. Shpitser, J. Pearl (2006a)
Proceedings of the Twenty?First National Conference on Artificial Intelligence
S. Greenland (2003)
Quantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification BiasEpidemiology, 14
P. Carneiro, J. Heckman, E. Vytlacil (2009)
Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the MarginIZA Institute of Labor Economics Discussion Paper Series
J. Heckman, E. Vytlacil (2000)
Local Instrumental VariablesEconometrics eJournal
P. Spirtes, C. Glymour, R. Scheines (1993)
Causation, Prediction and Search
(2009)
Identification without exogeneity in structural systems with proportional confounding,
J. Heckman, R. Robb (1985)
Longitudinal Analysis of Labor Market DataJournal of Machine Learning Research
N. Gordon, E. Vegas (2005)
Incentives to Improve Teaching: Lessons from Latin AmericaEpidemiology
Joseph Altonji, Rosa Matzkin (2005)
Cross Section and Panel Data Estimators for Nonseparable Models with Endogenous RegressorsEconometrica, 73
Rosa Matzkin (2003)
Nonparametric Estimation of Nonadditive Random FunctionsEconometrica, 71
J. Angrist, A. Krueger (2001)
Instrumental variables and the search for identification: from supply and demand to natural experimentsJournal of Economic Perspectives, 15
A. Chesher (2003)
Identification in nonseparable modelsJournal of the American Statistical Association, 71
J. Heckman (1996)
Comment on ?Identification of causal effects using instrumental variables? by Angrist, J., G. Imbens, and D. RubinBiometrika, 91
Z. Griliches (1977)
Estimating the Returns to Schooling: Some Econometric Problems.Econometrica, 45
H. White, Xun Lu (2010)
Granger Causality and Dynamic Structural SystemsJournal of Financial Econometrics, 8
N. Gordon, Emiliana Vegas (2005)
Educational Finance Equalization, Spending, Teacher Quality and Student Outcomes: The Case of Brazil’s FUNDEF
R. Anderson, T. Haavelmo (1944)
The Probability Approach in EconometricsJournal of the American Statistical Association, 40
J. Heckman, E. Vytlacil (1999)
Local instrumental variables and latent variable models for identifying and bounding treatment effects.Proceedings of the National Academy of Sciences of the United States of America, 96 8
H. White, Karim Chalak (2008)
Identifying Structural Effects in Nonseparable Systems Using Covariates
J. Heckman, E. Vytlacil (1999)
Proceedings of the National Academy of SciencesJournal of Economic Perspectives, 96
A. Gelman, Xiaoli Meng (2005)
Applied Bayesian Modeling And Causal Inference From Incomplete-Data Perspectives
A. Goldberger (1972)
STRUCTURAL EQUATION METHODS IN THE SOCIAL SCIENCESEconometrica, 40
(1950)
Generalization of the concept of identification,
Abstract We examine how structural systems can yield observed variables instrumental in identifying and estimating causal effects. We provide an exhaustive characterization of potentially identifying conditional exogeneity relationships and demonstrate how structural relations determine exogeneity and exclusion restrictions that yield moment conditions supporting identification. This provides a comprehensive framework for constructing instruments and covariates. We introduce notions of conditioning and conditional extended instrumental variables (XIVs). These permit identification but need not be traditional instruments, as they may be endogenous. We distinguish between observed XIVs and proxies for unobserved XIVs. A main message is the importance of sufficiently specifying causal relations governing the unobservables.
Canadian Journal of Economics/Revue Canadienne D'économique – Wiley
Published: Feb 1, 2011
Keywords: ; ; ; ;
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