Christoph Breunig, Stephan Martin
arXiv 26 Sep 2020 · Econometrics
arXiv:2009.12665 · PDF · DOI · OpenAlex · Extracted main text
We study a semi-/nonparametric regression model with a general form of nonclassical measurement error in the outcome variable. We show equivalence of this model to a generalized regression model. Our main identifying assumptions are a special regressor type restriction and monotonicity in the nonlinear relationship between the observed and unobserved true outcome. Nonparametric identification is then obtained under a normalization of the unknown link function, which is a natural extension of the classical measurement error case. We propose a novel sieve rank estimator for the regression function and establish its rate of convergence. In Monte Carlo simulations, we find that our estimator corrects for biases induced by nonclassical measurement error and provides numerically stable results. We apply our method to analyze belief formation of stock market expectations with survey data from the German Socio-Economic Panel (SOEP) and find evidence for nonclassical measurement error in subjective belief data.
appendix boundary found by appendix_command · 57% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | C. Cavanagh and R. P. Sherman (1998) Rank estimators for monotonic index models | 0.843 | 4 | 4 | 75% |
| 2 | X. D'Haultfoeuille (2010) A new instrumental method for dealing with endogenous selection | 0.811 | 4 | 2 | 100% |
| 3 | C. Breunig, E. Mammen, and A. Simoni (2018) Nonparametric estimation in case of endogenous selection | 0.811 | 4 | 2 | 100% |
| 4 | X. Chen (2007) Large sample sieve estimation of semi-nonparametric models | 0.737 | 4 | 2 | 75% |
| 5 | J. Abrevaya and J. A. Hausman (1999) Semiparametric estimation with mismeasured dependent variables: an application to duration models for unemployment spells | 0.737 | 3 | 2 | 100% |
| 6 | S. M. Schennach (2013) Measurement error in nonlinear models - a review | 0.737 | 3 | 2 | 100% |
| 7 | A. K. Han (1987) Non-parametric analysis of a generalized regression model: the maximum rank correlation estimator | 0.737 | 3 | 2 | 100% |
| 8 | Y. Hu and S. M. Schennach (2008) Instrumental variable treatment of nonclassical measurement error models | 0.737 | 3 | 2 | 100% |
| 9 | R. L. Matzkin (2007) Nonparametric identification | 0.737 | 3 | 2 | 100% |
| 10 | X. Chen and D. Pouzo (2012) Estimation of nonparametric conditional moment models with possibly nonsmooth generalized residuals | 0.644 | 3 | 2 | 67% |
Showing the top 10 of 45 scored citations.