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Deconvolution from panel data with unknown error distribution

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  • Neumann, Michael H.

Abstract

We devise a new method of estimating a distribution in a deconvolution model with panel data and an unknown distribution of the additive errors. We prove strong consistency under a minimal condition concerning the zero sets of the involved characteristic functions.

Suggested Citation

  • Neumann, Michael H., 2007. "Deconvolution from panel data with unknown error distribution," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1955-1968, November.
    • Handle: RePEc:eee:jmvana:v:98:y:2007:i:10:p:1955-1968
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    References listed on IDEAS

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    1. Joel L. Horowitz & Marianthi Markatou, 1996. "Semiparametric Estimation of Regression Models for Panel Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 63(1), pages 145-168.
    2. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
    3. Hall, Peter & Yao, Qiwei, 2003. "Inference in components of variance models with low replication," LSE Research Online Documents on Economics 17701, London School of Economics and Political Science, LSE Library.
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    Cited by:

    1. Christophe Chesneau & Fabienne Comte & Gwennaëlle Mabon & Fabien Navarro, 2014. "Estimation of Convolution In The Model with Noise," Working Papers 2014-39, Center for Research in Economics and Statistics.
    2. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    3. Florens, Jean-Pierre & Schwarz, Maik & Van Bellegem, Sébastien, 2010. "Nonparametric Frontier Estimation from Noisy Data," TSE Working Papers 10-179, Toulouse School of Economics (TSE).
    4. Carrasco, Marine & Florens, Jean-Pierre, 2011. "A Spectral Method For Deconvolving A Density," Econometric Theory, Cambridge University Press, vol. 27(3), pages 546-581, June.
    5. Fabienne Comte & Adeline Samson, 2012. "Nonparametric estimation of random-effects densities in linear mixed-effects model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 951-975, December.
    6. Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Gwennaëlle Mabon, 2014. "Adaptive Estimation of Random-Effects Densities In Linear Mixed-Effects Model," Working Papers 2014-41, Center for Research in Economics and Statistics.
    8. Schwarz, Maik & Van Bellegem, Sébastien, 2010. "Consistent density deconvolution under partially known error distribution," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 236-241, February.
    9. Julie McIntyre & Ronald P. Barry, 2012. "Bivariate deconvolution with SIMEX: an application to mapping Alaska earthquake density," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 297-308, April.
    10. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    11. Daisuke Kurisu & Taisuke Otsu, 2021. "On linearization of nonparametric deconvolution estimators for repeated measurements model," STICERD - Econometrics Paper Series 615, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. Martin Kroll, 2019. "Nonparametric intensity estimation from noisy observations of a Poisson process under unknown error distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(8), pages 961-990, November.
    13. Johanna Kappus & Gwennaelle Mabon, 2013. "Adaptive Density Estimation in Deconvolution Problems with Unknown Error Distribution," Working Papers 2013-31, Center for Research in Economics and Statistics.
    14. Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.

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