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Anna Simoni

Personal Details

First Name:Anna
Middle Name:
Last Name:Simoni
Suffix:
RePEc Short-ID:psi733
[This author has chosen not to make the email address public]
https://sites.google.com/view/simonianna

Affiliation

Centre de Recherche en Économie et Statistique (CREST)

Palaiseau, France
http://crest.science/
RePEc:edi:crestfr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Jean-Pierre Florens & Anna Simoni, 2021. "Revisiting identification concepts in Bayesian analysis," Papers 2110.09954, arXiv.org.
  2. Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.
  3. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
  4. Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.
  5. Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  6. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Post-Print hal-03089882, HAL.
  7. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
  8. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
  9. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.
  10. Johannes, Jan & Simoni, Anna & Schenk, Rudolf, 2015. "Adaptive Bayesian estimation in indirect Gaussian sequence space models," LIDAM Discussion Papers ISBA 2015003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  11. Jean-Pierre Florens & Anna Simoni, 2015. "Gaussian processes and Bayesian moment estimation," Working Papers 2015-09, Center for Research in Economics and Statistics.
  12. Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2015. "Semiparametric Estimation of Random Coefficients in Structural Economic Models," Boston College Working Papers in Economics 895, Boston College Department of Economics, revised 01 Feb 2016.
  13. Johannes, Jan & Schenk, Rudolf & Simoni, Anna, 2014. "Adaptive Bayesian estimation in Gaussian," LIDAM Reprints ISBA 2014026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  14. Johannes, Jan & Schenk, Rudolf & Simoni, Anna, 2014. "Adaptive Bayesian estimation in Gaussian sequence space models," LIDAM Discussion Papers ISBA 2014006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  15. Anna Simoni & Jean-Pierre Florens, 2013. "Regularizing Priors for Linear Inverse Problems," THEMA Working Papers 2013-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  16. Jean-Pierre Florens & Anna Simoni, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Post-Print hal-00922877, HAL.
  17. Liao, Yuan & Simoni, Anna, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," MPRA Paper 43262, University Library of Munich, Germany.
  18. Christoph Breunig & Enno Mammen & Anna Simoni, "undated". "Nonparametric Estimation in case of Endogenous Selection," SFB 649 Discussion Papers SFB649DP2015-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

  1. Jean-Pierre Florens & Anna Simoni, 2021. "Revisiting Identification Concepts in Bayesian Analysis," Annals of Economics and Statistics, GENES, issue 144, pages 1-38.
  2. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.
  3. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
  4. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  5. Jan Johannes & Anna Simoni & Rudolf Schenk, 2020. "Adaptive Bayesian Estimation in Indirect Gaussian Sequence Space Models," Annals of Economics and Statistics, GENES, issue 137, pages 83-116.
  6. Liao, Yuan & Simoni, Anna, 2019. "Bayesian inference for partially identified smooth convex models," Journal of Econometrics, Elsevier, vol. 211(2), pages 338-360.
  7. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
  8. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1656-1668, October.
  9. Jean-Pierre FLORENS & Anna SIMONI, 2017. "Introduction to the Special Issue on Inverse Problems in Econometrics," Annals of Economics and Statistics, GENES, issue 128, pages 1-3.
  10. Hoderlein, Stefan & Nesheim, Lars & Simoni, Anna, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1265-1305, December.
  11. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
  12. Jean-Pierre Florens & Anna Simoni, 2012. "Regularized Posteriors in Linear Ill-Posed Inverse Problems," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(2), pages 214-235, June.
  13. Florens, Jean-Pierre & Simoni, Anna, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Journal of Econometrics, Elsevier, vol. 170(2), pages 458-475.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    2. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
    3. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.

  2. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.

    Cited by:

    1. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    2. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    3. Jean-Pierre Florens & Anna Simoni, 2021. "Revisiting identification concepts in Bayesian analysis," Papers 2110.09954, arXiv.org.
    4. Liu, Xiaobin & Li, Yong & Yu, Jun & Zeng, Tao, 2022. "Posterior-based Wald-type statistics for hypothesis testing," Journal of Econometrics, Elsevier, vol. 230(1), pages 83-113.
    5. Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
    6. Emanuele Bacchiocchi & Toru Kitagawa, 2022. "Locally- but not Globally-identified SVARs," Working Papers wp1171, Dipartimento Scienze Economiche, Universita' di Bologna.

  3. Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.

    Cited by:

    1. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    2. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    3. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    4. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2022. "Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP," Papers 2209.01910, arXiv.org.
    5. Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Reprints LFIN 2021010, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Monitoring daily unemployment at risk"," IREA Working Papers 202211, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.

  4. Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.

    Cited by:

    1. Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
    2. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    3. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre (Seville site).
    4. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    5. Larson, William D. & Sinclair, Tara M., 2022. "Nowcasting unemployment insurance claims in the time of COVID-19," International Journal of Forecasting, Elsevier, vol. 38(2), pages 635-647.
    6. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    7. Marcelo C. Medeiros & Henrique F. Pires, 2021. "The Proper Use of Google Trends in Forecasting Models," Papers 2104.03065, arXiv.org, revised Apr 2021.
    8. Vera Z. Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2022. "Obtaining consistent time series from Google Trends," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 694-705, April.
    9. Valentin BURCA, 2020. "Earnings Quality Versus Accounting Regulation. Empirical Assesment On Accuracy Of Macroeconomic Estimates," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(1), pages 72-87, November.
    10. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    11. Tea Livaic & Ana Perisic, 2019. "What can Google Tell us about Bitcoin Trading Volume in Croatia? Evidence from the Online Marketplace Localbitcoins," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 17(4), pages 707-715.
    12. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.

  5. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Post-Print hal-03089882, HAL.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    3. Max Breitenlechner & Georgios Georgiadis & Ben Schumann, 2021. "What goes around comes around: How large are spillbacks from US monetary policy?," Working Papers 2021-05, Faculty of Economics and Statistics, University of Innsbruck.
    4. Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
    5. Bedoui, Adel & Lazar, Nicole A., 2020. "Bayesian empirical likelihood for ridge and lasso regressions," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    6. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
    7. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
    8. Arnab Kumar Maity & Sanjib Basu & Santu Ghosh, 2021. "Bayesian criterion‐based variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 835-857, August.
    9. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    10. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    11. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
    12. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.

  6. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.

    Cited by:

    1. Lee, Chien-Chiang & Wang, Chih-Wei & Ho, Shan-Ju, 2022. "The dimension of green economy: Culture viewpoint," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 122-138.
    2. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "Testing Overidentifying Restrictions with High-Dimensional Data and Heteroskedasticity," Papers 2205.00171, arXiv.org.

  7. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.

    Cited by:

    1. Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.

  8. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.

    Cited by:

    1. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers CWP43/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Christian Bontemps & Thierry Magnac, 2017. "Set identification, moment restrictions, and inference," Post-Print hal-01575813, HAL.

  9. Jean-Pierre Florens & Anna Simoni, 2015. "Gaussian processes and Bayesian moment estimation," Working Papers 2015-09, Center for Research in Economics and Statistics.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Li, Cheng & Jiang, Wenxin, 2016. "On oracle property and asymptotic validity of Bayesian generalized method of moments," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 132-147.
    3. Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
    4. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
    5. Dante Amengual & Enrique Sentana, 2016. "Comments on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(2), pages 248-252.
    6. Isaiah Andrews & Anna Mikusheva, 2022. "Optimal Decision Rules for Weak GMM," Econometrica, Econometric Society, vol. 90(2), pages 715-748, March.

  10. Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2015. "Semiparametric Estimation of Random Coefficients in Structural Economic Models," Boston College Working Papers in Economics 895, Boston College Department of Economics, revised 01 Feb 2016.

    Cited by:

    1. Escanciano, J C. & Hoderlein, S. & Lewbel, A. & Linton, O. & Srisuma, S., 2020. "Nonparametric Euler Equation Identi?cation and Estimation," Cambridge Working Papers in Economics 2064, Faculty of Economics, University of Cambridge.
    2. Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
    3. De Nadai, Michele & Lewbel, Arthur, 2016. "Nonparametric errors in variables models with measurement errors on both sides of the equation," Journal of Econometrics, Elsevier, vol. 191(1), pages 19-32.
    4. Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," TSE Working Papers 13-384, Toulouse School of Economics (TSE).
    5. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    6. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
    7. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2013. "On the Testability of Identification in Some Nonparametric Models With Endogeneity," Econometrica, Econometric Society, vol. 81(6), pages 2535-2559, November.
    8. Nail Kashaev & Bruno Salcedo, 2019. "Discerning Solution Concepts," University of Western Ontario, Departmental Research Report Series 20193, University of Western Ontario, Department of Economics.
    9. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Nonparametric estimation in case of endogenous selection," Post-Print hal-03089885, HAL.
    10. Nagasawa, Kenichi, 2020. "Identification and Estimation of Group-Level Partial Effects," The Warwick Economics Research Paper Series (TWERPS) 1243, University of Warwick, Department of Economics.
    11. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Irene Botosaru, 2017. "Identifying Distributions in a Panel Model with Heteroskedasticity: An Application to Earnings Volatility," Discussion Papers dp17-11, Department of Economics, Simon Fraser University.
    13. Gaurab Aryal, 2014. "Identifying Multidiemsnional Adverse Selection Models," Papers 1411.6250, arXiv.org, revised Nov 2015.

  11. Anna Simoni & Jean-Pierre Florens, 2013. "Regularizing Priors for Linear Inverse Problems," THEMA Working Papers 2013-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

    Cited by:

    1. Johannes, Jan & Simoni, Anna & Schenk, Rudolf, 2015. "Adaptive Bayesian estimation in indirect Gaussian sequence space models," LIDAM Discussion Papers ISBA 2015003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    3. Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," TSE Working Papers 13-384, Toulouse School of Economics (TSE).
    4. Jean-Pierre Florens & Anna Simoni, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Post-Print hal-00922877, HAL.
    5. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
    6. Liao, Yuan & Jiang, Wenxin, 2011. "Posterior consistency of nonparametric conditional moment restricted models," MPRA Paper 38700, University Library of Munich, Germany.
    7. Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
    8. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.

  12. Jean-Pierre Florens & Anna Simoni, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Post-Print hal-00922877, HAL.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Centorrino Samuele & Feve Frederique & Florens Jean-Pierre, 2017. "Additive Nonparametric Instrumental Regressions: A Guide to Implementation," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-25, January.
    3. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    4. Asin, Nicolas & Johannes, Jan, 2016. "Adaptive non-parametric instrumental regression in the presence of dependence," LIDAM Discussion Papers ISBA 2016015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," TSE Working Papers 13-384, Toulouse School of Economics (TSE).
    6. Xiaohong Chen & Timothy Christensen, 2013. "Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression," Papers 1311.0412, arXiv.org.
    7. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
    8. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    9. Hedibert F. Lopes & Nicholas G. Polson, 2014. "Bayesian Instrumental Variables: Priors and Likelihoods," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 100-121, June.
    10. Liao, Yuan & Jiang, Wenxin, 2011. "Posterior consistency of nonparametric conditional moment restricted models," MPRA Paper 38700, University Library of Munich, Germany.
    11. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2014. "Bayesian Nonparametric Instrumental Variables Regression Based on Penalized Splines and Dirichlet Process Mixtures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 468-482, July.
    12. Samuele Centorrino & Jean-Pierre Florens, 2014. "Nonparametric Instrumental Variable Estimation of Binary Response Models," Department of Economics Working Papers 14-07, Stony Brook University, Department of Economics.
    13. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    14. Horowitz, Joel L., 2014. "Adaptive nonparametric instrumental variables estimation: Empirical choice of the regularization parameter," Journal of Econometrics, Elsevier, vol. 180(2), pages 158-173.
    15. Centorrino, Samuele & Florens, Jean-Pierre, 2021. "Nonparametric Instrumental Variable Estimation of Binary Response Models with Continuous Endogenous Regressors," Econometrics and Statistics, Elsevier, vol. 17(C), pages 35-63.
    16. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    17. Joel L. Horowitz, 2013. "Adaptive nonparametric instrumental variables estimation: empirical choice of the regularization parameter," CeMMAP working papers CWP30/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    19. Ziyu Wang & Yuhao Zhou & Jun Zhu, 2022. "Fast Instrument Learning with Faster Rates," Papers 2205.10772, arXiv.org, revised Oct 2022.
    20. Xiaohong Chen & Timothy M. Christensen, 2015. "Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation," CeMMAP working papers CWP32/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  13. Liao, Yuan & Simoni, Anna, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," MPRA Paper 43262, University Library of Munich, Germany.

    Cited by:

    1. Raffaella Giacomini & Toru Kitagawa, 2014. "Inference about Non-Identi?ed SVARs," CeMMAP working papers CWP45/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Raffaella Giacomini & Toru Kitagawa & Alessio Volpicella, 2020. "Uncertain Identification," CeMMAP working papers CWP33/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  14. Christoph Breunig & Enno Mammen & Anna Simoni, "undated". "Nonparametric Estimation in case of Endogenous Selection," SFB 649 Discussion Papers SFB649DP2015-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    2. Breunig, Christoph, 2017. "Testing Missing At Random Using Instrumental Variables," Rationality and Competition Discussion Paper Series 59, CRC TRR 190 Rationality and Competition.
    3. Yang Zhao & Meng Liu, 2021. "Unified approach for regression models with nonmonotone missing at random data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(1), pages 87-101, March.
    4. Christoph Breunig, 2015. "Testing Missing at Random using Instrumental Variables," SFB 649 Discussion Papers SFB649DP2015-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Breunig, Christoph & Haan, Peter, 2021. "Nonparametric regression with selectively missing covariates," Journal of Econometrics, Elsevier, vol. 223(1), pages 28-52.
    6. Breunig, Christoph & Kummer, Michael & Ohnemus, Jörg & Viete, Steffen, 2016. "IT outsourcing and firm productivity: Eliminating bias from selective missingness in the dependent variable," ZEW Discussion Papers 16-092, ZEW - Leibniz Centre for European Economic Research.
    7. Christoph Breunig & Peter Haan, 2018. "Nonparametric Regression with Selectively Missing Covariates," Papers 1810.00411, arXiv.org, revised Oct 2020.
    8. Lukáš Lafférs & Bernhard Schmidpeter, 2021. "Early child development and parents' labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 190-208, March.
    9. Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
    10. Christoph Breunig, 2017. "Testing Missing at Random using Instrumental Variables," SFB 649 Discussion Papers SFB649DP2017-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

  1. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.
    See citations under working paper version above.
  2. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    See citations under working paper version above.
  3. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
    See citations under working paper version above.
  4. Liao, Yuan & Simoni, Anna, 2019. "Bayesian inference for partially identified smooth convex models," Journal of Econometrics, Elsevier, vol. 211(2), pages 338-360.
    See citations under working paper version above.
  5. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    See citations under working paper version above.
  6. Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1656-1668, October.
    See citations under working paper version above.
  7. Hoderlein, Stefan & Nesheim, Lars & Simoni, Anna, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1265-1305, December.
    See citations under working paper version above.
  8. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
    See citations under working paper version above.
  9. Jean-Pierre Florens & Anna Simoni, 2012. "Regularized Posteriors in Linear Ill-Posed Inverse Problems," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(2), pages 214-235, June.

    Cited by:

    1. Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," TSE Working Papers 13-384, Toulouse School of Economics (TSE).
    2. Jean-Pierre Florens & Anna Simoni, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Post-Print hal-00922877, HAL.
    3. Serge Darolles & Jean-Pierre Florens & Eric Renault, 2000. "Nonparametric Instrumental Regression," Working Papers 2000-17, Center for Research in Economics and Statistics.
    4. Jean-Pierre Florens & Anna Simoni, 2021. "Revisiting identification concepts in Bayesian analysis," Papers 2110.09954, arXiv.org.
    5. Jean-Pierre Florens & Anna Simoni, 2021. "Gaussian Processes and Bayesian Moment Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 482-492, March.
    6. Salomond, Jean-Bernard, 2014. "Propriétés fréquentistes des méthodes Bayésiennes semi-paramétriques et non paramétriques," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14331 edited by Rousseau, Judith & Rivoirard, Vincent, October.

  10. Florens, Jean-Pierre & Simoni, Anna, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Journal of Econometrics, Elsevier, vol. 170(2), pages 458-475. See citations under working paper version above.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 21 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (14) 2010-07-31 2010-08-21 2010-10-02 2010-10-02 2012-04-23 2013-01-07 2015-12-01 2016-07-16 2018-01-01 2018-07-09 2019-03-25 2019-12-23 2020-06-08 2021-10-25. Author is listed
  2. NEP-ORE: Operations Research (7) 2010-08-21 2015-12-01 2018-01-01 2019-12-23 2020-06-08 2021-11-22 2022-03-21. Author is listed
  3. NEP-BIG: Big Data (5) 2019-03-25 2019-04-01 2019-04-22 2020-06-08 2020-07-27. Author is listed
  4. NEP-DCM: Discrete Choice Models (3) 2016-02-12 2021-10-25 2022-02-14
  5. NEP-CWA: Central & Western Asia (2) 2021-11-22 2022-03-21
  6. NEP-ETS: Econometric Time Series (2) 2019-03-25 2021-10-25
  7. NEP-BAN: Banking (1) 2022-03-21
  8. NEP-EEC: European Economics (1) 2019-04-22
  9. NEP-FOR: Forecasting (1) 2019-03-25
  10. NEP-GER: German Papers (1) 2016-07-16
  11. NEP-HIS: Business, Economic & Financial History (1) 2022-02-14
  12. NEP-KNM: Knowledge Management & Knowledge Economy (1) 2018-07-09

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