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Sebastien Van Bellegem

Personal Details

First Name:Sebastien
Middle Name:
Last Name:Van Bellegem
Suffix:
RePEc Short-ID:pva120
http://www.vanbellegem.org

Affiliation

Center for Operations Research and Econometrics (CORE)
Louvain Institute of Data Analysis and Modelling in Economics and Statistics (LIDAM)
Université Catholique de Louvain

Louvain-la-Neuve, Belgium
http://www.uclouvain.be/en-core.html
RePEc:edi:coreebe (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Florens, Jean-Pierre & Schwarz, Maik & Van Bellegem, Sébastien, 2010. "Nonparametric Frontier Estimation from Noisy Data," IDEI Working Papers 625, Institut d'Économie Industrielle (IDEI), Toulouse.
  3. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2010. "Iterative Regularization in Nonparametric Instrumental Regression," TSE Working Papers 10-184, Toulouse School of Economics (TSE).
  4. Manzi, Jorge & San Martin, Ernesto & Van Bellegem, Sébastien, 2010. "School System Evaluation By Value-Added Analysis under Endogeneity," TSE Working Papers 10-185, Toulouse School of Economics (TSE).
  5. Bigot, Jérôme & Van Bellegem, Sébastien, 2009. "Log-Density Deconvolution by Wavelet Thresholding," TSE Working Papers 09-011, Toulouse School of Economics (TSE).
  6. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2009. "Convergence Rates for III-Posed Inverse Problems with an Unknown Operator," TSE Working Papers 09-030, Toulouse School of Economics (TSE).
  7. Daskovska, Alexandra & Simar, Léopold & Van Bellegem, Sébastien, 2009. "Forecasting the Malmquist Productivity Index," TSE Working Papers 09-048, Toulouse School of Economics (TSE).
  8. Schwarz, Maik & Van Bellegem, Sébastien, 2009. "Consistent Density Deconvolution under Partially Known Error Distribution," TSE Working Papers 09-097, Toulouse School of Economics (TSE).
  9. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," IDEI Working Papers 633, Institut d'Économie Industrielle (IDEI), Toulouse.
  10. JOHANNES, Jan & VAN BELLEGHEM, Sébastien & VANHEMS, Anne, 2007. "A unified approach to solve ill-posed inverse problems in econometrics," LIDAM Discussion Papers CORE 2007083, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  11. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2007. "Identification and estimation by penalization in nonparametric instrumental regression," LIDAM Discussion Papers CORE 2007085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  12. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2006. "Instrumental regression in partially linear models," LIDAM Discussion Papers CORE 2006025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

Articles

  1. Jean‐Pierre Florens & Jan Johannes & Sébastien Van Bellegem, 2012. "Instrumental regression in partially linear models," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 304-324, June.
  2. Florens, Jean-Pierre & Johannes, Jan & Van Bellegem, Sébastien, 2011. "Identification And Estimation By Penalization In Nonparametric Instrumental Regression," Econometric Theory, Cambridge University Press, vol. 27(3), pages 472-496, June.
  3. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2011. "Convergence Rates For Ill-Posed Inverse Problems With An Unknown Operator," Econometric Theory, Cambridge University Press, vol. 27(3), pages 522-545, June.
  4. 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.
  5. Jérémie Bigot & Sébastien Van Bellegem, 2009. "Log‐density Deconvolution by Wavelet Thresholding," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 749-763, December.
  6. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.
  7. Sébastien Van Bellegem & Rainer Dahlhaus, 2006. "Semiparametric estimation by model selection for locally stationary processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(5), pages 721-746, November.
  8. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.
  9. Denuit, Michel & Van Bellegem, Sébastien, 2001. "On the stop-loss and total variation distances between random sums," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 153-165, June.

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. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bonsoo Koo & Oliver Linton, 2013. "Let's get LADE: robust estimation of semiparametric multiplicative volatility models," CeMMAP working papers CWP11/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    4. Bonsoo Koo & Oliver Linton, 2013. "Let's get LADE: robust estimation of semiparametric multiplicative volatility models," CeMMAP working papers 11/13, Institute for Fiscal Studies.

  2. Florens, Jean-Pierre & Schwarz, Maik & Van Bellegem, Sébastien, 2010. "Nonparametric Frontier Estimation from Noisy Data," IDEI Working Papers 625, Institut d'Économie Industrielle (IDEI), Toulouse.

    Cited by:

    1. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Dai, Xiaofeng, 2016. "Non-parametric efficiency estimation using Richardson–Lucy blind deconvolution," European Journal of Operational Research, Elsevier, vol. 248(2), pages 731-739.
    3. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Leonardo Andrade Rocha & Ahmad Saeed Khan & Patrícia Verônica Pinheiro Sales Lima & Maria Ester Dal Poz & Fernando Porfirio Soares De Oliveira, 2016. "Corrupção, Burocracia E Outras Falhas Institucionais: O “Câncer” Da Inovação E Do Desenvolvimento," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 090, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  3. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2010. "Iterative Regularization in Nonparametric Instrumental Regression," TSE Working Papers 10-184, Toulouse School of Economics (TSE).

    Cited by:

    1. 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.
    2. Bréchet, Thierry & Jouvet, Pierre-André & Rotillon, Gilles, 2013. "Tradable pollution permits in dynamic general equilibrium: Can optimality and acceptability be reconciled?," Ecological Economics, Elsevier, vol. 91(C), pages 89-97.
    3. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2013. "Iterative regularisation in nonparametric instrumental regression," LIDAM Reprints CORE 2442, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    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. BIRKE, Mélanie & VAN BELLEGEM, Sébastien & VAN KEILEGOM, Ingrid, 2016. "Semi-Parametric Estimation in a Single- Index Model with Endogenous Variables," LIDAM Discussion Papers CORE 2016022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Liao, Yuan & Jiang, Wenxin, 2011. "Posterior consistency of nonparametric conditional moment restricted models," MPRA Paper 38700, University Library of Munich, Germany.
    7. 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.
    8. Jean-Pierre Florens & Elia Lapenta, 2022. "Partly Linear Instrumental Variables Regressions without Smoothing on the Instruments," Papers 2212.11012, arXiv.org, revised Oct 2023.
    9. Vanhems, Anne & Van Keilegom, Ingrid, 2019. "Estimation Of A Semiparametric Transformation Model In The Presence Of Endogeneity," Econometric Theory, Cambridge University Press, vol. 35(1), pages 73-110, February.
    10. 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.
    11. Malikov, Emir & Zhao, Shunan & Kumbhakar, Subal C., 2020. "Estimation of Firm-Level Productivity in the Presence of Exports: Evidence from China's Manufacturing," MPRA Paper 98077, University Library of Munich, Germany.

  4. Manzi, Jorge & San Martin, Ernesto & Van Bellegem, Sébastien, 2010. "School System Evaluation By Value-Added Analysis under Endogeneity," TSE Working Papers 10-185, Toulouse School of Economics (TSE).

    Cited by:

    1. Alejandro Carrasco & Ernesto San Mart’n, 2012. "Voucher system and school effectiveness: Reassessing school performance difference and parental choice decision-making," Estudios de Economia, University of Chile, Department of Economics, vol. 39(2 Year 20), pages 123-141, December.
    2. Vanhems, Anne & Van Keilegom, Ingrid, 2019. "Estimation Of A Semiparametric Transformation Model In The Presence Of Endogeneity," Econometric Theory, Cambridge University Press, vol. 35(1), pages 73-110, February.
    3. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.

  5. Bigot, Jérôme & Van Bellegem, Sébastien, 2009. "Log-Density Deconvolution by Wavelet Thresholding," TSE Working Papers 09-011, Toulouse School of Economics (TSE).

    Cited by:

    1. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bak, Kwan-Young & Jhong, Jae-Hwan & Lee, JungJun & Shin, Jae-Kyung & Koo, Ja-Yong, 2021. "Penalized logspline density estimation using total variation penalty," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    3. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2011. "Convergence rates for ill-posed inverse problems with an unknown operator," LIDAM Reprints CORE 2330, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  6. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2009. "Convergence Rates for III-Posed Inverse Problems with an Unknown Operator," TSE Working Papers 09-030, Toulouse School of Economics (TSE).

    Cited by:

    1. Fève, Frédérique & Florens, Jean-Pierre, 2014. "Non parametric analysis of panel data models with endogenous variables," Journal of Econometrics, Elsevier, vol. 181(2), pages 151-164.
    2. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
    4. Jad Beyhum & Elia Lapenta & Pascal Lavergne, 2023. "One-step nonparametric instrumental regression using smoothing splines," Papers 2307.14867, arXiv.org, revised Sep 2023.
    5. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    6. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2013. "Iterative regularisation in nonparametric instrumental regression," LIDAM Reprints CORE 2442, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. 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.
    8. Birke, M. & Van Bellegem, S. & Van Keilegom, I., 2014. "Semi-parametric estimation in a single-index model with endogenous variables," LIDAM Discussion Papers ISBA 2014043, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Beyhum, Jad & Lapenta, Elia & Lavergne, Pascal, 2023. "One-step nonparametric instrumental regression using smoothing splines," TSE Working Papers 23-1467, Toulouse School of Economics (TSE).
    10. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. BIRKE, Mélanie & VAN BELLEGEM, Sébastien & VAN KEILEGOM, Ingrid, 2016. "Semi-Parametric Estimation in a Single- Index Model with Endogenous Variables," LIDAM Discussion Papers CORE 2016022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Feve, Frederique & Florens, Jean-Pierre & Van Keilegom, Ingrid, 2012. "Estimation of conditional ranks and tests of exogeneity in nonparametric nonseparable models," LIDAM Discussion Papers ISBA 2012036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Bigot, Jérôme & Van Bellegem, Sébastien, 2009. "Log-Density Deconvolution by Wavelet Thresholding," TSE Working Papers 09-011, Toulouse School of Economics (TSE).
    14. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
    15. Van Bellegem, Sébastien & Florens, Jean-Pierre, 2014. "Instrumental variable estimation in functional linear models," LIDAM Discussion Papers CORE 2014056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  7. Daskovska, Alexandra & Simar, Léopold & Van Bellegem, Sébastien, 2009. "Forecasting the Malmquist Productivity Index," TSE Working Papers 09-048, Toulouse School of Economics (TSE).

    Cited by:

    1. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Benjamin Hampf, 2016. "Efficiency and productivity measurement with persistent benchmarks," Economics Bulletin, AccessEcon, vol. 36(3), pages 1715-1721.
    3. Md. Harun Ur Rashid & Shah Asadullah Mohd. Zobair & Md. Asad Iqbal Chowdhury & Azharul Islam, 2020. "Corporate governance and banks’ productivity: evidence from the banking industry in Bangladesh," Business Research, Springer;German Academic Association for Business Research, vol. 13(2), pages 615-637, July.
    4. Growiec, Jakub, 2009. "On the Measurement of Technological Progress Across Countries," MPRA Paper 19321, University Library of Munich, Germany.
    5. Reza Fallahnejad & Mohammad Reza Mozaffari & Peter Fernandes Wanke & Yong Tan, 2024. "Nash Bargaining Game Enhanced Global Malmquist Productivity Index for Cross-Productivity Index," Games, MDPI, vol. 15(1), pages 1-21, January.
    6. Andreas Mayer & Valentin Zelenyuk, 2014. "An Aggregation Paradigm for Hicks-Moorsteen Productivity Indexes," CEPA Working Papers Series WP012014, School of Economics, University of Queensland, Australia.
    7. Yubin Zheng & Md. Harun Ur Rashid & Abu Bakkar Siddik & Wei Wei & Syed Zabid Hossain, 2022. "Corporate Social Responsibility Disclosure and Firm’s Productivity: Evidence from the Banking Industry in Bangladesh," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    8. Oleg Badunenko & Daniel J. Henderson & Valentin Zelenyuk, 2017. "The Productivity of Nations," Working Papers in Economics & Finance 2017-05, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    9. Antonio Peyrache, 2013. "Multilateral productivity comparisons and homotheticity," Journal of Productivity Analysis, Springer, vol. 40(1), pages 57-65, August.
    10. Valentin Zelenyuk & Andreas Mayer, 2013. "Aggregation of Malmquist productivity indexes allowing for reallocation of resources," CEPA Working Papers Series WP062013, School of Economics, University of Queensland, Australia.
    11. Andreas Mayer & Valentin Zelenyuk, 2018. "Aggregation of Individual Efficiency Measures and Productivity Indices," CEPA Working Papers Series WP012018, School of Economics, University of Queensland, Australia.
    12. Simar, Leopold & Wilson, Paul, 2015. "Statistical Approaches for Nonparametric Frontier Models: A Guided Tour," LIDAM Reprints ISBA 2015022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Shittu, Adebayo M. & Odine, Agatha I., 2014. "Agricultural Productivity Growth in Sub-Saharan Africa, 1990-2010: the role of Investment, Governance and Trade," Conference papers 332439, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    14. Martin Boďa & Mariana Považanová, 2020. "Productivity patterns in Europe: adaptation of the Malmquist index to measuring group performance and productivity change over time," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 949-989, November.
    15. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    16. Gloria O. Dzeha & Joshua Abor & Festus Turkson & Elikplimi Agbloyor, 2018. "Technical Efficiency and Technical Change in Africa: The Role of Money from the Diasporas," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(7), pages 177-177, July.

  8. Schwarz, Maik & Van Bellegem, Sébastien, 2009. "Consistent Density Deconvolution under Partially Known Error Distribution," TSE Working Papers 09-097, Toulouse School of Economics (TSE).

    Cited by:

    1. Jean-Pierre Florens & Léopold Simar & Ingrid van Keilegom, 2020. "Estimation of the Boundary of a Variable Observed with A Symmetric Error," Post-Print hal-02929524, HAL.
    2. Abdelaati Daouia & Jean-Pierre Florens & Léopold Simar, 2020. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," Post-Print hal-02573853, HAL.
    3. Aurélie Bertrand & Ingrid Van Keilegom & Catherine Legrand, 2019. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," Biometrics, The International Biometric Society, vol. 75(1), pages 297-307, March.
    4. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Kneip, Alois & Simar, Léopold & Van Keilegom, Ingrid, 2015. "Frontier estimation in the presence of measurement error with unknown variance," Journal of Econometrics, Elsevier, vol. 184(2), pages 379-393.
    6. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2021. "Density deconvolution with Laplace errors and unknown variance," Journal of Productivity Analysis, Springer, vol. 56(2), pages 103-113, December.
    7. Kneip, A. & Simar, L. & Van Keilegom I., 2010. "Boundary estimation in the presence of measurement error with unknown variance," LIDAM Discussion Papers ISBA 2010046, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Koen Jochmans & Marc Henry & Bernard Salanié, 2017. "Inference on Two-Component Mixtures under Tail Restrictions," SciencePo Working papers Main hal-03945858, HAL.
    9. Jeon, Jeong Min & Van Keilegom, Ingrid, 2023. "Density estimation for mixed Euclidean and non-Euclidean data in the presence of measurement error," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    10. D’Haultfœuille, Xavier & Février, Philippe, 2015. "Identification of mixture models using support variations," Journal of Econometrics, Elsevier, vol. 189(1), pages 70-82.
    11. Zhuan Pei & Yi Shen, 2016. "The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable," Working Papers 606, Princeton University, Department of Economics, Industrial Relations Section..
    12. Bertrand, Aurelie & Van Keilegom, Ingrid & Legrand, Catherine, 2017. "Flexible parametric approach to classical measurement error variance estimation without auxiliary data," LIDAM Discussion Papers ISBA 2017025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. 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.

  9. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," IDEI Working Papers 633, Institut d'Économie Industrielle (IDEI), Toulouse.

    Cited by:

    1. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    2. Karine Bertin & Nicolas Klutchnikoff, 2014. "Adaptive Estimation of a Density Function using Beta Kernels," Working Papers 2014-08, Center for Research in Economics and Statistics.

  10. JOHANNES, Jan & VAN BELLEGHEM, Sébastien & VANHEMS, Anne, 2007. "A unified approach to solve ill-posed inverse problems in econometrics," LIDAM Discussion Papers CORE 2007083, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    2. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
    3. Bigot, Jérôme & Van Bellegem, Sébastien, 2009. "Log-Density Deconvolution by Wavelet Thresholding," TSE Working Papers 09-011, Toulouse School of Economics (TSE).

  11. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2007. "Identification and estimation by penalization in nonparametric instrumental regression," LIDAM Discussion Papers CORE 2007085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Fève, Frédérique & Florens, Jean-Pierre, 2014. "Non parametric analysis of panel data models with endogenous variables," Journal of Econometrics, Elsevier, vol. 181(2), pages 151-164.
    2. Benatia, David & Carrasco, Marine & Florens, Jean-Pierre, 2017. "Functional linear regression with functional response," Journal of Econometrics, Elsevier, vol. 201(2), pages 269-291.
    3. Xiaohong Chen & Markus Reiss, 2007. "On Rate Optimality for Ill-posed Inverse Problems in Econometrics," Cowles Foundation Discussion Papers 1626, Cowles Foundation for Research in Economics, Yale University.
    4. Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
    5. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    6. 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.
    7. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    8. Christoph Breunig, 2019. "Goodness-of-Fit Tests based on Series Estimators in Nonparametric Instrumental Regression," Papers 1909.10133, arXiv.org.
    9. Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 17/11, Institute for Fiscal Studies.
    10. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    11. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Mar 2021.
    12. Breunig, Christoph, 2015. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Journal of Econometrics, Elsevier, vol. 184(2), pages 328-346.
    13. Marteau Clement & Loubes Jean-Michel, 2012. "Adaptive estimation for an inverse regression model with unknown operator," Statistics & Risk Modeling, De Gruyter, vol. 29(3), pages 215-242, August.
    14. Juan Carlos Escanciano & Wei Li, 2018. "Optimal Linear Instrumental Variables Approximations," Papers 1805.03275, arXiv.org, revised Feb 2020.
    15. Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Post-Print hal-03089886, HAL.
    16. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    17. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
    18. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
    19. Xiaohong Chen & Demian Pouzo, 2008. "Estimation of nonparametric conditional moment models with possibly nonsmooth moments," CeMMAP working papers CWP12/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Jad Beyhum & Elia Lapenta & Pascal Lavergne, 2023. "One-step nonparametric instrumental regression using smoothing splines," Papers 2307.14867, arXiv.org, revised Sep 2023.
    21. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    22. Birke, M. & Van Bellegem, S. & Van Keilegom, I., 2014. "Semi-parametric estimation in a single-index model with endogenous variables," LIDAM Discussion Papers ISBA 2014043, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Breunig, Christoph, 2012. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Working Papers 12-13, University of Mannheim, Department of Economics.
    24. Feng Yao & Junsen Zhang, 2013. "Efficient Kernel-Based Semiparametric IV Estimation with an Application to Resolving a Puzzle on the Estimates of the Return to Schooling," Working Papers 13-01, Department of Economics, West Virginia University.
    25. 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.
    26. Beyhum, Jad & Lapenta, Elia & Lavergne, Pascal, 2023. "One-step nonparametric instrumental regression using smoothing splines," TSE Working Papers 23-1467, Toulouse School of Economics (TSE).
    27. Fabian Dunker, 2015. "Adaptive estimation for some nonparametric instrumental variable models," Papers 1511.03977, arXiv.org, revised Aug 2021.
    28. 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).
    29. BIRKE, Mélanie & VAN BELLEGEM, Sébastien & VAN KEILEGOM, Ingrid, 2016. "Semi-Parametric Estimation in a Single- Index Model with Endogenous Variables," LIDAM Discussion Papers CORE 2016022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    31. Feve, Frederique & Florens, Jean-Pierre & Van Keilegom, Ingrid, 2012. "Estimation of conditional ranks and tests of exogeneity in nonparametric nonseparable models," LIDAM Discussion Papers ISBA 2012036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    32. 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.
    33. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness," Papers 2302.05404, arXiv.org.
    34. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers 48/13, Institute for Fiscal Studies.
    35. 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.
    36. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
    37. Jad Beyhum & Jean-Pierre Florens & Elia Lapenta & Ingrid Van Keilegom, 2022. "Testing for homogeneous treatment effects in linear and nonparametric instrumental variable models," Papers 2208.05344, arXiv.org, revised Apr 2023.
    38. Van Bellegem, Sébastien & Florens, Jean-Pierre, 2014. "Instrumental variable estimation in functional linear models," LIDAM Discussion Papers CORE 2014056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  12. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2006. "Instrumental regression in partially linear models," LIDAM Discussion Papers CORE 2006025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Senay Sokullu, 2012. "Nonparametric Estimation of Semiparametric Transformation Models," Bristol Economics Discussion Papers 12/625, School of Economics, University of Bristol, UK.
    2. Xiaohong Chen & Demian Pouzo, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP20/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    4. 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.
    5. Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 17/11, Institute for Fiscal Studies.
    6. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    7. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2007. "Identification and estimation by penalization in nonparametric instrumental regression," LIDAM Discussion Papers CORE 2007085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    9. Sokullu, Senay, 2023. "More Is Better, Or Not? An Empirical Analysis of Buyer Preferences for Variety on the E-Market," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 450-470.
    10. Huang, Liquan & Khalil, Umair & Yıldız, Neşe, 2019. "Identification and estimation of a triangular model with multiple endogenous variables and insufficiently many instrumental variables," Journal of Econometrics, Elsevier, vol. 208(2), pages 346-366.
    11. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    12. Jing Nie & Juliana Malagon & Julian Williams, 2022. "The impact of high speed quoting on execution risk dynamics: Evidence from interest rate futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1434-1465, August.
    13. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
    14. Zhang, Hong-Fan, 2021. "Iterative GMM for partially linear single-index models with partly endogenous regressors," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    15. S. Centorrino & J. S. Racine, 2016. "Semiparametric Varying Coefficient Models with Endogenous Covariates," Department of Economics Working Papers 2016-02, McMaster University.
    16. Xiaolin Sun, 2022. "Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach," Papers 2210.15829, arXiv.org, revised Dec 2022.
    17. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    18. Rodrigo Adao & Costas Arkolakis & Sharat Ganapati, 2020. "Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models," Cowles Foundation Discussion Papers 2265, Cowles Foundation for Research in Economics, Yale University.
    19. 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.
    20. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    21. Kapetanios, George & Marcellino, Massimiliano, 2010. "Factor-GMM estimation with large sets of possibly weak instruments," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2655-2675, November.
    22. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2011. "Convergence rates for ill-posed inverse problems with an unknown operator," LIDAM Reprints CORE 2330, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. Bertille Antoine & Xiaolin Sun, 2020. "Partially Linear Models with Endogeneity: a conditional moment based approach," Discussion Papers dp20-06, Department of Economics, Simon Fraser University.
    24. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    25. 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).
    26. BIRKE, Mélanie & VAN BELLEGEM, Sébastien & VAN KEILEGOM, Ingrid, 2016. "Semi-Parametric Estimation in a Single- Index Model with Endogenous Variables," LIDAM Discussion Papers CORE 2016022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    28. 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.
    29. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.
    30. Vanhems, Anne & Van Keilegom, Ingrid, 2019. "Estimation Of A Semiparametric Transformation Model In The Presence Of Endogeneity," Econometric Theory, Cambridge University Press, vol. 35(1), pages 73-110, February.
    31. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.
    32. Jad Beyhum & Jean-Pierre Florens & Elia Lapenta & Ingrid Van Keilegom, 2022. "Testing for homogeneous treatment effects in linear and nonparametric instrumental variable models," Papers 2208.05344, arXiv.org, revised Apr 2023.

Articles

  1. Jean‐Pierre Florens & Jan Johannes & Sébastien Van Bellegem, 2012. "Instrumental regression in partially linear models," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 304-324, June.
    See citations under working paper version above.
  2. Florens, Jean-Pierre & Johannes, Jan & Van Bellegem, Sébastien, 2011. "Identification And Estimation By Penalization In Nonparametric Instrumental Regression," Econometric Theory, Cambridge University Press, vol. 27(3), pages 472-496, June.
    See citations under working paper version above.
  3. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2011. "Convergence Rates For Ill-Posed Inverse Problems With An Unknown Operator," Econometric Theory, Cambridge University Press, vol. 27(3), pages 522-545, June.
    See citations under working paper version above.
  4. 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.
    See citations under working paper version above.
  5. Jérémie Bigot & Sébastien Van Bellegem, 2009. "Log‐density Deconvolution by Wavelet Thresholding," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 749-763, December.
    See citations under working paper version above.
  6. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.

    Cited by:

    1. Čížek, Pavel & Koo, Chao Hui, 2021. "Jump-preserving varying-coefficient models for nonlinear time series," Econometrics and Statistics, Elsevier, vol. 19(C), pages 58-96.
    2. Anna Bykhovskaya & Peter C. B. Phillips, 2018. "Boundary Limit Theory for Functional Local to Unity Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(4), pages 523-562, July.
    3. Marie Hušková & Matúš Maciak, 2017. "Discontinuities in robust nonparametric regression with α-mixing dependence," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 447-475, April.
    4. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    5. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    6. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    7. Porter, Jack & Yu, Ping, 2015. "Regression discontinuity designs with unknown discontinuity points: Testing and estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 132-147.
    8. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.

  7. Sébastien Van Bellegem & Rainer Dahlhaus, 2006. "Semiparametric estimation by model selection for locally stationary processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(5), pages 721-746, November.

    Cited by:

    1. Dahlhaus, Rainer, 2009. "Local inference for locally stationary time series based on the empirical spectral measure," Journal of Econometrics, Elsevier, vol. 151(2), pages 101-112, August.
    2. Beran, Jan, 2007. "On parameter estimation for locally stationary long-memory processes," CoFE Discussion Papers 07/13, University of Konstanz, Center of Finance and Econometrics (CoFE).
    3. Abdelkamel Alj & Christophe Ley & Guy Melard, 2015. "Asymptotic Properties of QML Estimators for VARMA Models with Time-Dependent Coefficients: Part I," Working Papers ECARES ECARES 2015-21, ULB -- Universite Libre de Bruxelles.
    4. Abdelkamel Alj & Rajae Azrak & Christophe Ley & Guy Mélard, 2017. "Asymptotic Properties of QML Estimators for VARMA Models with Time-dependent Coefficients," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 617-635, September.
    5. Eckley, Idris A. & Nason, Guy P., 2011. "LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i03).
    6. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    7. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Marios Sergides & Efstathios Paparoditis, 2009. "Frequency Domain Tests of Semiparametric Hypotheses for Locally Stationary Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 800-821, December.
    9. Cardinali Alessandro & Nason Guy P, 2011. "Costationarity of Locally Stationary Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 2(2), pages 1-35, January.

  8. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.

    Cited by:

    1. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    2. Cristina Amado & Timo Teräsvirta, 2012. "Modelling Changes in the Unconditional Variance of Long Stock Return Series," CREATES Research Papers 2012-07, Department of Economics and Business Economics, Aarhus University.
    3. Daskovska, Alexandra & Simar, Léopold & Van Bellegem, Sébastien, 2009. "Forecasting the Malmquist Productivity Index," IDEI Working Papers 634, Institut d'Économie Industrielle (IDEI), Toulouse.
    4. Silvennoinen Annastiina & Teräsvirta Timo, 2016. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 347-364, September.
    5. Abdelkamel Alj & Christophe Ley & Guy Melard, 2015. "Asymptotic Properties of QML Estimators for VARMA Models with Time-Dependent Coefficients: Part I," Working Papers ECARES ECARES 2015-21, ULB -- Universite Libre de Bruxelles.
    6. Abdelkamel Alj & Rajae Azrak & Christophe Ley & Guy Mélard, 2017. "Asymptotic Properties of QML Estimators for VARMA Models with Time-dependent Coefficients," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 617-635, September.
    7. Escribano, Alvaro & Sucarrat, Genaro, 2018. "Equation-by-equation estimation of multivariate periodic electricity price volatility," Energy Economics, Elsevier, vol. 74(C), pages 287-298.
    8. Cristina Amado & Timo Teräsvirta, 2011. "Conditional Correlation Models of Autoregressive Conditional Heteroskedasticity with Nonstationary GARCH Equations," CREATES Research Papers 2011-24, Department of Economics and Business Economics, Aarhus University.
    9. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    10. Sucarrat, Genaro, 2018. "The Log-GARCH Model via ARMA Representations," MPRA Paper 100386, University Library of Munich, Germany.
    11. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    12. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    13. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    14. Yuanhua Feng & Lixin Sun, 2013. "A semi-APARCH approach for comparing long-term and short-term risk in Chinese financial market and in mature financial markets," Working Papers CIE 69, Paderborn University, CIE Center for International Economics.
    15. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Holger Dette & Weichi Wu, 2020. "Prediction in locally stationary time series," Papers 2001.00419, arXiv.org, revised Jan 2020.
    17. Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 01 Aug 2007.
    18. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    19. Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," CREATES Research Papers 2017-28, Department of Economics and Business Economics, Aarhus University.
    20. Song, Wenjuan & Sun, Lixin, 2014. "The Measurement of the Long-Term and Short-Term Risks of Chinese Listed Banks," MPRA Paper 70007, University Library of Munich, Germany, revised Jul 2014.
    21. Ray Yeutien Chou & Chun-Chou Wu & Yi-Nung yang, 2012. "The euro's impacts on the smooth transition dynamics of stock market volatilities," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 169-179, May.

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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 15 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 (12) 2010-05-22 2010-05-22 2010-05-22 2010-05-22 2010-07-31 2010-09-18 2010-09-18 2010-09-18 2010-10-02 2010-10-02 2011-02-12 2011-05-14. Author is listed
  2. NEP-EFF: Efficiency and Productivity (4) 2010-05-22 2010-09-18 2010-10-02 2011-02-12
  3. NEP-LAB: Labour Economics (3) 2010-09-18 2010-10-02 2011-02-12
  4. NEP-ORE: Operations Research (3) 2010-09-18 2010-10-02 2010-10-02
  5. NEP-EDU: Education (2) 2010-10-02 2011-02-12
  6. NEP-URE: Urban and Real Estate Economics (2) 2010-09-18 2011-02-12
  7. NEP-ETS: Econometric Time Series (1) 2011-05-14
  8. NEP-FOR: Forecasting (1) 2010-05-22
  9. NEP-MIC: Microeconomics (1) 2010-09-18

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