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152
Estimation of Nonparametric Simultaneous Equations
, 2005
"... This paper considers identification in parametric and nonparametric models, with additive or nonadditive unobservables, and with or without simultaneity among the endogenous variables. Several characterizations of observational equivalence are presented and conditions for identification are develope ..."
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Cited by 40 (7 self)
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This paper considers identification in parametric and nonparametric models, with additive or nonadditive unobservables, and with or without simultaneity among the endogenous variables. Several characterizations of observational equivalence are presented and conditions for identification are developed based on these. It is shown that the results can be extended to situations where the dependent variables are latent. We also demonstrate how the results may be used to derive constructive ways to calculate the unknown functions and distributions in simultaneous equations models, directly from the probability density of the observable variables. Estimators based on this do not suffer from the illposed inverse problem that other methods encounter.
An Extended Class of Instrumental Variables for the Estimation of Causal Effects
 UCSD DEPT. OF ECONOMICS DISCUSSION PAPER
, 1996
"... This paper builds on the structural equations, treatment effect, and machine learning literatures to provide a causal framework that permits the identification and estimation of causal effects from observational studies. We begin by providing a causal interpretation for standard exogenous regresso ..."
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Cited by 40 (16 self)
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This paper builds on the structural equations, treatment effect, and machine learning literatures to provide a causal framework that permits the identification and estimation of causal effects from observational studies. We begin by providing a causal interpretation for standard exogenous regressors and standard “valid” and “relevant” instrumental variables. We then build on this interpretation to characterize extended instrumental variables (EIV) methods, that is methods that make use of variables that need not be valid instruments in the standard sense, but that are nevertheless instrumental in the recovery of causal effects of interest. After examining special cases of single and double EIV methods, we provide necessary and sufficient conditions for the identification of causal effects by means of EIV and provide consistent and asymptotically normal estimators for the effects of interest.
Identification and Estimation of a Nonparametric Panel Data Model with Unobserved Heterogeneity
, 2009
"... This paper considers a nonparametric panel data model with nonadditive unobserved heterogeneity. As in the standard linear panel data model, two types of unobservables are present in the model: individualspecific effects and idiosyncratic disturbances. The individualspecific effects enter the stru ..."
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Cited by 32 (1 self)
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This paper considers a nonparametric panel data model with nonadditive unobserved heterogeneity. As in the standard linear panel data model, two types of unobservables are present in the model: individualspecific effects and idiosyncratic disturbances. The individualspecific effects enter the structural function nonseparably and are allowed to be correlated with the covariates in an arbitrary manner. The idiosyncratic disturbance term is additively separable from the structural function. Nonparametric identification of all the structural elements of the model is established. No parametric distributional or functional form assumptions are needed for identification. The identification result is constructive and only requires panel data with two time periods. Thus, the model permits nonparametric distributional and counterfactual analysis of heterogeneous marginal effects using short panels. The paper also develops a nonparametric estimation procedure and derives its rate of convergence. As a byproduct the rates of convergence for the problem of conditional deconvolution are obtained. The proposed estimator is easy to compute and does not require numeric optimization. A MonteCarlo study indicates that the estimator performs very well in finite sample properties.
The Browser War. Econometric Analysis of Markov Perfect Equilibrium in Markets with Network Effects
"... ABSTRACT: When demands for heterogeneous goods in a concentrated market shift over time due to network effects, forwardlooking firms consider the strategic impact of investment, pricing, and other conduct. A Markov perfect equilibrium model captures this strategic behavior, and permits the compari ..."
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Cited by 26 (4 self)
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ABSTRACT: When demands for heterogeneous goods in a concentrated market shift over time due to network effects, forwardlooking firms consider the strategic impact of investment, pricing, and other conduct. A Markov perfect equilibrium model captures this strategic behavior, and permits the comparison of "as is" market trajectories with "but for" trajectories under counterfactuals where some "bad acts" by firms are eliminated. We give conditions for econometric identification and estimation of a Markov perfect equilibrium model from observations on partial trajectories, and discuss estimation of the impacts of firm conduct on consumers and rival firms. Our analysis is applied to a stylized description of the browser war between Netscape and Microsoft.
On The Nonparametric Identification Of Nonlinear Simultaneous Equations Models: Comment On Brown
 Econometrica
, 2006
"... This note revisits the identification theorems of B. Brown (1983) and Roehrig (1988). We describe an error in the proofs of the main identification theorems in these papers, and provide an important counterexample to the theorems on the identification of the reduced form. Specifically, contrary to t ..."
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Cited by 25 (0 self)
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This note revisits the identification theorems of B. Brown (1983) and Roehrig (1988). We describe an error in the proofs of the main identification theorems in these papers, and provide an important counterexample to the theorems on the identification of the reduced form. Specifically, contrary to the theorems, the reduced form of a nonseparable simultaneous equations model is not identified even under the assumptions of those papers. We conclude the note with a conjecture that it may be possible to use classical exclusion restrictions to recover some of the key implications of the theorems. ∗We have had very helpful conversations with Pat Bayer, Don Brown, Yossi Feinberg, Guido Imbens, Yuliy Sannikov, Andy Skrzypacz, and Chris Timmons. Any remaining In this note, we reconsider the nonparametric identification of nonlinear simultaneous equations models, as in B. Brown (1983) and Roehrig (1988). We
Nonparametric estimation of nonadditive hedonic models
, 2002
"... We present methods to estimate marginal utility and marginal product functions that are nonadditive in the unobservable random terms, using observations from a single hedonic equilibrium market. We show that nonadditive marginal utility and nonadditive marginal product functions are capable of gener ..."
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Cited by 24 (7 self)
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We present methods to estimate marginal utility and marginal product functions that are nonadditive in the unobservable random terms, using observations from a single hedonic equilibrium market. We show that nonadditive marginal utility and nonadditive marginal product functions are capable of generating equilibria that exhibit bunching, as well as other types of equilibria. We provide conditions under which these types of utility and production functions are nonparametrically identified, and we propose nonparametric estimators for them. The estimators are shown to be consistent and asymptotically normal.
Nonparametric Demand Systems, Instrumental Variables and a Heterogeneous Population,”Mannheim
, 2005
"... This paper is concerned with empirically modelling the demand behavior of a population with heterogeneous preferences under a weak conditional independence assumption. More specifically, we characterize the testable implications of negative semidefiniteness and symmetry of the Slutsky matrix across ..."
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Cited by 18 (12 self)
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This paper is concerned with empirically modelling the demand behavior of a population with heterogeneous preferences under a weak conditional independence assumption. More specifically, we characterize the testable implications of negative semidefiniteness and symmetry of the Slutsky matrix across a heterogeneous population without assuming anything on the functional form of individual preferences. In the same spirit, implications of a linear budget set are being considered. Since the conditional independence assumption is the only substantial restriction in this model, we analyze possible alternatives and solutions if this assumption is violated. In particular, we consider in detail the concept of instruments in this framework. Besides being able to integrate econometric concepts, the same framework admits also economic extensions. As an example we consider welfare analysis. Finally, we provide asymptotic distribution theory for the new test statistics that emerge out of this framework, and apply these to Canadian data. 1
Nonparametric Estimation of Distributional Policy Effects
, 2008
"... PRELIMINARY VERSION. COMMENTS ARE WELCOME. This paper proposes a fully nonparametric procedure to evaluate the effect of a counterfactual change in the distribution of some covariates on the unconditional distribution of an outcome variable of interest. In contrast to other methods, we do not restri ..."
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Cited by 17 (2 self)
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PRELIMINARY VERSION. COMMENTS ARE WELCOME. This paper proposes a fully nonparametric procedure to evaluate the effect of a counterfactual change in the distribution of some covariates on the unconditional distribution of an outcome variable of interest. In contrast to other methods, we do not restrict attention to the effect on the mean. In particular, our method can be used to conduct inference on the change of the distribution function as a whole, its moments and quantiles, inequality measures such as the Lorenz curve or Gini coefficient, and to test for stochastic dominance. The practical applicability of our procedure is illustrated via a simulation study and an empirical application.
Nonparametric identification and estimation of nonadditive hedonic models
 Econometrica
, 2010
"... in Economic Theory and Econometrics " for their useful comments. We thank Myrna Wooders and Daniel McFadden for many stimulating conversations, and Donald J. Brown for specific comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the Nation ..."
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Cited by 15 (0 self)
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in Economic Theory and Econometrics " for their useful comments. We thank Myrna Wooders and Daniel McFadden for many stimulating conversations, and Donald J. Brown for specific comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.