Journal ArticleDOI
Estimation of Nonlinear Models with Measurement Error
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In this article, the root n consistent estimator for nonlinear models with measurement errors in the explanatory variables, when one repeated observation of each mismeasured regressor is available, is presented.Abstract:
This paper presents a solution to an important econometric problem, namely the root n consistent estimation of nonlinear models with measurement errors in the explanatory variables, when one repeated observation of each mismeasured regressor is available. While a root n consistent estimator has been derived for polynomial specifications (see Hausman, Ichimura, Newey, and Powell (1991)), such an estimator for general nonlinear specifications has so far not been available. Using the additional information provided by the repeated observation, the suggested estimator separates the measurement error from the “true” value of the regressors thanks to a useful property of the Fourier transform: The Fourier transform converts the integral equations that relate the distribution of the unobserved “true” variables to the observed variables measured with error into algebraic equations. The solution to these equations yields enough information to identify arbitrary moments of the “true,” unobserved variables. The value of these moments can then be used to construct any estimator that can be written in terms of moments, including traditional linear and nonlinear least squares estimators, or general extremum estimators. The proposed estimator is shown to admit a representation in terms of an influence function, thus establishing its root n consistency and asymptotic normality. Monte Carlo evidence and an application to Engel curve estimation illustrate the usefulness of this new approach.read more
Citations
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Journal ArticleDOI
Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation
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Book ChapterDOI
Endogeneity in Empirical Corporate Finance1
Michael Roberts,Toni M. Whited +1 more
TL;DR: In this paper, applied researchers in corporate finance can address endogeneity concerns, including omitted variables, simultaneity, and measurement error, and discuss a number of econometric techniques aimed at addressing endogeneity problems, including instrumental variables, difference-in-differences estimators, regression discontinuity design, matching methods, panel data methods, and higher order moments estimators.
Journal ArticleDOI
Estimating the technology of cognitive and noncognitive skill formation
TL;DR: In this paper, the elasticity of substitution between investments in one period and stocks of skills in another period is estimated to assess the benefits of early investment in children compared to later remediation.
Posted Content
Estimating the Technology of Cognitive and Noncognitive Skill Formation
TL;DR: In this paper, the elasticity of substitution between investments in one period and stocks of skills in another period is estimated to assess the benefits of early investment in children compared to later remediation.
Book ChapterDOI
Chapter 71 Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New Environments ⁎
TL;DR: The marginal treatment effect (MTE) as mentioned in this paper is a choice-theoretic parameter that can be interpreted as a willingness to pay parameter for persons at a margin of indifference between participating in an activity or not.
References
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Journal ArticleDOI
Specification Tests in Econometrics
TL;DR: In this article, the null hypothesis of no misspecification was used to show that an asymptotically efficient estimator must have zero covariance with its difference from a consistent but asymptonically inefficient estimator, and specification tests for a number of model specifications in econometrics.
Book
Weak Convergence and Empirical Processes: With Applications to Statistics
TL;DR: In this article, the authors define the Ball Sigma-Field and Measurability of Suprema and show that it is possible to achieve convergence almost surely and in probability.
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Weak Convergence and Empirical Processes
TL;DR: This chapter discusses Convergence: Weak, Almost Uniform, and in Probability, which focuses on the part of Convergence of the Donsker Property which is concerned with Uniformity and Metrization.
ReportDOI
Estimates of the Economic Return to Schooling from a New Sample of Twins
Alan B. Krueger,Alan B. Krueger,Alan B. Krueger,Orley Ashenfelter,Orley Ashenfelter,Orley Ashenfelter +5 more
TL;DR: The authors used a survey of identical twins to study the economic returns to schooling and found that an additional year of schooling increases wages by 12-16 percent, a higher estimate of the economic retums to schooling than has been previously found.
Journal ArticleDOI
On the Optimal Rates of Convergence for Nonparametric Deconvolution Problems
TL;DR: In this paper, it was shown that the difficulty of deconvolution depends on the smoothness of error distributions: the smoother, the harder it is to estimate the density of a random variable.
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