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Shinichi Sakata

Personal Details

First Name:Shinichi
Middle Name:
Last Name:Sakata
Suffix:
RePEc Short-ID:psa970
http://ssakata.sdf.org

Affiliation

(in no particular order)

Department of Economics
University of Southern California

Los Angeles, California (United States)
https://dornsife.usc.edu/econ/
RePEc:edi:deuscus (more details at EDIRC)

Vancouver School of Economics
University of British Columbia

Vancouver, Canada
http://www.economics.ubc.ca/
RePEc:edi:deubcca (more details at EDIRC)

Department of Economics
University of Michigan-Flint

Flint, Michigan (United States)
http://www.umflint.edu/economics/
RePEc:edi:demifus (more details at EDIRC)

Department of Economics
University of California-San Diego (UCSD)

La Jolla, California (United States)
http://economics.ucsd.edu/
RePEc:edi:deucsus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Marmer, Vadim & Sakata, Shinichi, 2011. "Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction," Microeconomics.ca working papers vadim_marmer-2011-26, Vancouver School of Economics, revised 28 Sep 2011.
  2. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Sakata, S., 1998. "Instrumental Variable Estimation Based on Mean Absolute Deviation," Papers 98-08, Michigan - Center for Research on Economic & Social Theory.

Articles

  1. Joseph V. Terza & Donald S. Kenkel & Tsui‐Fang Lin & Shinichi Sakata, 2008. "Care‐giver advice as a preventive measure for drinking during pregnancy: zeros, categorical outcome responses, and endogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 41-54, January.
  2. Pao-Li Chang & Shinichi Sakata, 2007. "Estimation of impulse response functions using long autoregression," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 453-469, July.
  3. Sakata, Shinichi, 2007. "Instrumental variable estimation based on conditional median restriction," Journal of Econometrics, Elsevier, vol. 141(2), pages 350-382, December.
  4. Arie Preminger & Shinichi Sakata, 2007. "A model selection method for S-estimation," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 294-319, July.
  5. Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 5-72, July.
  6. Shinichi Sakata & Halbert White, 1998. "High Breakdown Point Conditional Dispersion Estimation with Application to S&P 500 Daily Returns Volatility," Econometrica, Econometric Society, vol. 66(3), pages 529-568, May.
  7. Morimune, Kimio & Sakata, Shinichi, 1993. "Modified three-stage least squares estimator which is third-order efficient," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 257-276.
  8. Kobayashi, Masahito & Sakata, Shinichi, 1990. "Mallows' Cp criterion and unbiasedness of model selection," Journal of Econometrics, Elsevier, vol. 45(3), pages 385-395.

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. Marmer, Vadim & Sakata, Shinichi, 2011. "Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction," Microeconomics.ca working papers vadim_marmer-2011-26, Vancouver School of Economics, revised 28 Sep 2011.

    Cited by:

    1. Victor Chernozhukov & Christian Hansen, 2013. "Quantile models with endogeneity," CeMMAP working papers CWP25/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  2. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.

  3. Sakata, S., 1998. "Instrumental Variable Estimation Based on Mean Absolute Deviation," Papers 98-08, Michigan - Center for Research on Economic & Social Theory.

    Cited by:

    1. Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers CWP01/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Marmer, Vadim & Sakata, Shinichi, 2011. "Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction," Microeconomics.ca working papers vadim_marmer-2011-26, Vancouver School of Economics, revised 28 Sep 2011.
    3. Elise Coudin & Jean-Marie Dufour, 2010. "Finite and Large Sample Distribution-Free Inference in Median Regressions with Instrumental Variables," Working Papers 2010-56, Center for Research in Economics and Statistics.
    4. Komarova Tatiana & Severini Thomas A. & Tamer Elie T., 2012. "Quantile Uncorrelation and Instrumental Regressions," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 2-14, August.
    5. Tae-Hwan Kim & Christophe Muller, 2012. "A test for endogeneity in conditional quantile models," Working papers 2012rwp-49, Yonsei University, Yonsei Economics Research Institute.

Articles

  1. Joseph V. Terza & Donald S. Kenkel & Tsui‐Fang Lin & Shinichi Sakata, 2008. "Care‐giver advice as a preventive measure for drinking during pregnancy: zeros, categorical outcome responses, and endogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 41-54, January.

    Cited by:

    1. AZUMAH, Shaibu Baanni & MAHAMA, Abass & DONKOH, Samuel A., 2020. "Modelling The Determinants Of Adoption Of Multiple Climate Change Coping And Adaptation Strategies. A Micro Analysis Of Smallholder Farmers In Northern Ghana," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 23(1), March.
    2. Helge Liebert & Beatrice Mäder, 2018. "Physician Density and Infant Mortality: A Semiparametric Analysis of the Returns to Health Care Provision," CESifo Working Paper Series 7209, CESifo.
    3. Massimiliano Bratti & Alfonso Miranda, 2011. "Endogenous treatment effects for count data models with endogenous participation or sample selection," Mexican Stata Users' Group Meetings 2011 05, Stata Users Group.
    4. Maria Chiara Di Guardo & Kathryn Rudie Harrigan & Elona Marku, 2019. "M&A and diversification strategies: what effect on quality of inventive activity?," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 23(3), pages 669-692, September.
    5. Liebert, Helge & Mäder, Beatrice, 2017. "The impact of regional health care coverage on infant mortality and disease incidence," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168103, Verein für Socialpolitik / German Economic Association.
    6. Liebert, Helge & Mäder, Beatrice, 2022. "Physicians and the Production of Health: Returns to Health Care during the Mortality Transition," IZA Discussion Papers 15220, Institute of Labor Economics (IZA).
    7. Massimiliano Bratti & Alfonso Miranda, 2010. "Endogenous Treatment Effects for Count Data Models with Sample Selection or Endogenous Participation," DoQSS Working Papers 10-05, Quantitative Social Science - UCL Social Research Institute, University College London, revised 10 Dec 2010.
    8. Lambon-Quayefio, Monica Puoma & Owoo, Nkechi S., 2021. "Investigating the long-term effects of child labor on household poverty and food insecurity in Ghana," Journal of Demographic Economics, Cambridge University Press, vol. 87(4), pages 561-587, December.
    9. Giulia BETTIN & Riccardo LUCCHETTI, 2010. "Interval Regression Models with;Endogenous Explanatory Variables," Working Papers 339, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    10. Liebert, H. & Mäder, B., 2016. "Marginal effects of physician coverage on infant and disease mortality," Health, Econometrics and Data Group (HEDG) Working Papers 16/17, HEDG, c/o Department of Economics, University of York.

  2. Pao-Li Chang & Shinichi Sakata, 2007. "Estimation of impulse response functions using long autoregression," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 453-469, July.

    Cited by:

    1. Bentour, El Mostafa, 2013. "Should Moroccan Officials Depend on the Workers’ Remittances to Finance the Current Account Deficit?," MPRA Paper 52290, University Library of Munich, Germany, revised 01 May 2013.
    2. Fève, Patrick & Guay, Alain, 2009. "Identification of Technology Shocks in Structural VARs," TSE Working Papers 09-028, Toulouse School of Economics (TSE).
    3. Rabah Arezki & Valerie A. Ramey & Liugang Sheng, 2017. "News Shocks in Open Economies: Evidence from Giant Oil Discoveries," The Quarterly Journal of Economics, Oxford University Press, vol. 132(1), pages 103-155.
    4. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    5. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    6. Valerie A. Ramey, 2016. "Macroeconomic Shocks and Their Propagation," NBER Working Papers 21978, National Bureau of Economic Research, Inc.
    7. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..
    8. Mary C. Daly & John G. Fernald & Òscar Jordà & Fernanda Nechio, 2013. "Shocks and Adjustments," Working Paper Series 2013-32, Federal Reserve Bank of San Francisco.
    9. Dalibor Stevanovic, 2015. "Factor augmented autoregressive distributed lag models with macroeconomic applications," CIRANO Working Papers 2015s-33, CIRANO.
    10. Wu, Jyh-Lin & Lee, Chingnun & Wang, Tzu-Wei, 2011. "A re-examination on dissecting the purchasing power parity puzzle," Journal of International Money and Finance, Elsevier, vol. 30(3), pages 572-586, April.

  3. Sakata, Shinichi, 2007. "Instrumental variable estimation based on conditional median restriction," Journal of Econometrics, Elsevier, vol. 141(2), pages 350-382, December.

    Cited by:

    1. Horowitz, Joel L. & Lee, Sokbae, 2009. "Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative," Journal of Econometrics, Elsevier, vol. 152(2), pages 141-152, October.
    2. Tae-Hwan Kim & Christophe Muller, 2020. "Inconsistency transmission and variance reduction in two-stage quantile regression," Post-Print hal-02084505, HAL.
    3. Kemp, GCR & Parente, PMDC & Santos Silva, JMC, 2015. "Dynamic Vector Mode Regression," Economics Discussion Papers 13793, University of Essex, Department of Economics.
    4. Zhenlin Yang & Liangjun Su, 2007. "Instrumental Variable Quantile Estimation of Spatial Autoregressive Models," Working Papers 05-2007, Singapore Management University, School of Economics.
    5. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," Working Papers halshs-01508067, HAL.
    6. Tao Chen & Gautam Tripathi, 2013. "Testing conditional symmetry without smoothing," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 273-313, June.
    7. Victor Chernozhukov & Christian Hansen, 2013. "Quantile models with endogeneity," CeMMAP working papers CWP25/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Working Papers halshs-02272874, HAL.
    9. Marmer, Vadim & Sakata, Shinichi, 2011. "Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction," Microeconomics.ca working papers vadim_marmer-2011-26, Vancouver School of Economics, revised 28 Sep 2011.
    10. Tae-Hwan Kim & Christophe Muller, 2013. "A Test for Endogeneity in Conditional Quantiles," AMSE Working Papers 1342, Aix-Marseille School of Economics, France, revised Aug 2013.
    11. Jia-Young Michael Fu & Joel L. Horowitz & Matthias Parey, 2015. "Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions," CeMMAP working papers CWP68/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Gilles Dufrenot & Valerie Mignon & Charalambos Tsangarides, 2010. "The trade-growth nexus in the developing countries: a quantile regression approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(4), pages 731-761, December.
    13. Tae-Hwan Kim, & Christophe Muller, 2012. "Bias Transmission and Variance Reduction in Two-Stage Quantile Regression," AMSE Working Papers 1221, Aix-Marseille School of Economics, France.
    14. Komarova, Tatiana & Severini, Thomas A. & Tamer, Elie, 2012. "Quantile Uncorrelation and Instrumental Regressions," Scholarly Articles 25267902, Harvard University Department of Economics.
    15. Komarova Tatiana & Severini Thomas A. & Tamer Elie T., 2012. "Quantile Uncorrelation and Instrumental Regressions," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 2-14, August.
    16. Tatiana Komorova & Thomas Severini & Elie Tamer, 2010. "Quantile Uncorrelation and Instrumental Regression," STICERD - Econometrics Paper Series 552, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    17. Juan Carlos Escanciano & Chuan Goh, 2010. "Specification Analysis of Structural Quantile Regression Models," Working Papers tecipa-415, University of Toronto, Department of Economics.
    18. Komarova, Tatiana & Severini, Thomas & Tamer, Elie, 2010. "Quantile uncorrelation and instrumental regression," LSE Research Online Documents on Economics 41949, London School of Economics and Political Science, LSE Library.

  4. Arie Preminger & Shinichi Sakata, 2007. "A model selection method for S-estimation," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 294-319, July.
    See citations under working paper version above.
  5. Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 5-72, July.

    Cited by:

    1. John M. Abowd & Francis Kramarz & Sebastien Perez-Duarte & Ian M. Schmutte, 2017. "Sorting Between and Within Industries: A Testable Model of Assortative Matching," Working Papers 17-43, Center for Economic Studies, U.S. Census Bureau.
    2. Pankaj Sinha & Naina Grover, 2021. "Interrelationship Among Competition, Diversification and Liquidity Creation: Evidence from Indian Banks," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 15(2), pages 183-204, May.
    3. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    4. PREMINGER Arie & STORTI Giuseppe, 2017. "Least squares estimation for GARCH (1,1) model with heavy tailed errors," LIDAM Discussion Papers CORE 2017015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. PREMINGER, Arie & STORTI, Giuseppe, 2006. "A GARCH (1,1) estimator with (almost) no moment conditions on the error term," LIDAM Discussion Papers CORE 2006068, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Sakata, Shinichi, 2007. "Instrumental variable estimation based on conditional median restriction," Journal of Econometrics, Elsevier, vol. 141(2), pages 350-382, December.
    7. Ana M. Bianco & Paula M. Spano, 2019. "Robust inference for nonlinear regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 369-398, June.
    8. Pavel Cizek & Wolfgang Härdle, 2006. "Robust Econometrics," SFB 649 Discussion Papers SFB649DP2006-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    10. Corina SAMAN, 2015. "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-106, March.
    11. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Sibbertsen, Philipp, 1999. "S-estimation in the nonlinear regression model with long-memory error terms," Technical Reports 1999,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  6. Shinichi Sakata & Halbert White, 1998. "High Breakdown Point Conditional Dispersion Estimation with Application to S&P 500 Daily Returns Volatility," Econometrica, Econometric Society, vol. 66(3), pages 529-568, May.

    Cited by:

    1. E. Ruiz & M.A. Carnero & D. Pereira, 2004. "Effects of Level Outliers on the Identification and Estimation of GARCH Models," Econometric Society 2004 Australasian Meetings 21, Econometric Society.
    2. Cizek, P., 2007. "General Trimmed Estimation : Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1)," Discussion Paper 2007-65, Tilburg University, Center for Economic Research.
    3. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    4. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    5. Jun, Sung Jae & Pinkse, Joris & Wan, Yuanyuan, 2011. "-Consistent robust integration-based estimation," Journal of Multivariate Analysis, Elsevier, vol. 102(4), pages 828-846, April.
    6. Sunil Sapra, 2003. "High-breakdown point estimation of some regression models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(14), pages 875-878.
    7. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    8. Cizek, P., 2009. "Generalized Methods of Trimmed Moments," Other publications TiSEM 46607f30-95c0-430a-8ef9-2, Tilburg University, School of Economics and Management.
    9. Cizek, P., 2010. "Reweighted Least Trimmed Squares : An Alternative to One-Step Estimators," Other publications TiSEM 850c8dcb-835b-4d68-ab98-6, Tilburg University, School of Economics and Management.
    10. Loriano Mancini & Fabio Trojani, 2011. "Robust Value at Risk Prediction," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(2), pages 281-313, Spring.
    11. Čížek, Pavel, 2008. "General Trimmed Estimation: Robust Approach To Nonlinear And Limited Dependent Variable Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1500-1529, December.
    12. L. Ingber & R.P. Mondescu, 2001. "Optimization of trading physics models of markets," Lester Ingber Papers 01ot, Lester Ingber.
    13. Gagliardini, Patrick & Trojani, Fabio & Urga, Giovanni, 2005. "Robust GMM tests for structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 139-182.
    14. Loriano Mancini & Elvezio Ronchetti & Fabio Trojani, 2005. "Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models," University of St. Gallen Department of Economics working paper series 2005 2005-01, Department of Economics, University of St. Gallen.
    15. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    16. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Cizek, P. & Härdle, W.K., 2005. "Robust Estimation of Dimension Reduction Space," Discussion Paper 2005-31, Tilburg University, Center for Economic Research.
    18. Jurgen A. Doornik & Marius Ooms, 2005. "Outlier Detection in GARCH Models," Economics Papers 2005-W24, Economics Group, Nuffield College, University of Oxford.
    19. Cizek, P., 2007. "Efficient Robust Estimation of Time-Series Regression Models," Other publications TiSEM d76eb299-a6b2-4f5a-bb9f-a, Tilburg University, School of Economics and Management.
    20. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    21. Aktham Maghyereh, 2006. "Regional Integration of Stock Markets in MENA Countries," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 5(1), pages 59-94, April.
    22. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    23. Cizek, P., 2004. "Asymptotics of Least Trimmed Squares Regression," Other publications TiSEM dab5d551-aca6-40bf-b92e-c, Tilburg University, School of Economics and Management.
    24. Cizek, P., 2008. "Semiparametric Robust Estimation of Truncated and Censored Regression Models," Other publications TiSEM a6228ada-1ab5-47ee-9d23-4, Tilburg University, School of Economics and Management.
    25. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    26. Francq, Christian & Zakoïan, Jean-Michel, 2022. "Testing the existence of moments for GARCH processes," Journal of Econometrics, Elsevier, vol. 227(1), pages 47-64.
    27. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    28. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    29. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    30. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    31. Fabio Trojani & Markus Leippold & Paolo Vanini, 2005. "Learning and Asset Prices under Ambiguous Information," University of St. Gallen Department of Economics working paper series 2005 2005-03, Department of Economics, University of St. Gallen.
    32. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    33. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    34. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    35. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, October.
    36. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    37. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    38. M. Angeles Carnero Fernández & Ana Pérez Espartero, 2018. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Working Papers. Serie AD 2018-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    39. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    40. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    41. Vincenzo Atella & Francesco Brindisi & Partha Deb & Furio C. Rosati, 2004. "Determinants of access to physician services in Italy: a latent class seemingly unrelated probit approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(7), pages 657-668, July.
    42. Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 5-72, July.
    43. Grané, Aurea & Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.
    44. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
    45. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    46. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    47. Ronchetti, Elvezio, 2020. "Accurate and robust inference," Econometrics and Statistics, Elsevier, vol. 14(C), pages 74-88.
    48. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    49. Ortelli, Claudio & Trojani, Fabio, 2005. "Robust efficient method of moments," Journal of Econometrics, Elsevier, vol. 128(1), pages 69-97, September.
    50. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    51. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    52. Marc G. Genton & André Lucas, 2003. "Comprehensive definitions of breakdown points for independent and dependent observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 81-94, February.
    53. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    54. Cízek, Pavel, 2011. "Semiparametrically weighted robust estimation of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 774-788, January.
    55. Murinde V. & Poshakwala S., 2001. "Volatility in the Emerging Stock Markets in Central and Eastern Europe: Evidence on Croatia, Czech Republic, Hungary, Poland, Russia and Slovakia," European Research Studies Journal, European Research Studies Journal, vol. 0(3-4), pages 73-102, July - De.
    56. Franses, Ph.H.B.F. & van Dijk, D.J.C., 1999. "Outlier detection in the GARCH (1,1) model," Econometric Institute Research Papers EI 9926-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    57. Hill, Jonathan B., 2015. "Robust Generalized Empirical Likelihood for heavy tailed autoregressions with conditionally heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 131-152.
    58. Pavel Cizek & Wolfgang Härdle, 2006. "Robust Econometrics," SFB 649 Discussion Papers SFB649DP2006-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    59. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    60. Korkie, Bob & Sivakumar, Ranjini & Turtle, Harry, 2002. "The dual contributions of information instruments in return models: magnitude and direction predictability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 511-523, December.
    61. Jianqing Fan & Yuan Ke & Yuan Liao, 2016. "Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia," Papers 1603.07041, arXiv.org, revised Sep 2018.
    62. Partha Deb & Ann M. Holmes, 2000. "Estimates of use and costs of behavioural health care: a comparison of standard and finite mixture models," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 475-489, September.
    63. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Post-Print hal-03794543, HAL.
    64. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    65. Camponovo, Lorenzo & Scaillet, Olivier & Trojani, Fabio, 2012. "Robust subsampling," Journal of Econometrics, Elsevier, vol. 167(1), pages 197-210.
    66. You, Jiazhong, 1999. "A Monte Carlo comparison of several high breakdown and efficient estimators," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 205-219, April.
    67. Chan, W.S. & Wong, C.S. & Chung, A.H.L., 2009. "Modelling Australian interest rate swap spreads by mixture autoregressive conditional heteroscedastic processes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2779-2786.
    68. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, October.
    69. Aguilar, Mike & Hill, Jonathan B., 2015. "Robust score and portmanteau tests of volatility spillover," Journal of Econometrics, Elsevier, vol. 184(1), pages 37-61.
    70. Corina SAMAN, 2015. "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-106, March.
    71. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    72. L. Ingber & R.P. Mondescu, 2003. "Automated internet trading based on optimized physics models of markets," Lester Ingber Papers 03ai, Lester Ingber.
    73. White, Halbert & Kim, Tae-Hwan, 2002. "Estimation, Inference, and Specification Testing for Possibly Misspecified Quantile Regression," University of California at San Diego, Economics Working Paper Series qt1s38s0dn, Department of Economics, UC San Diego.
    74. Carnero, M. Angeles & Peña, Daniel & Ruiz, Esther, 2012. "Estimating GARCH volatility in the presence of outliers," Economics Letters, Elsevier, vol. 114(1), pages 86-90.
    75. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    76. Pavlidis Efthymios G. & Paya Ivan & Peel David A., 2013. "Nonlinear causality tests and multivariate conditional heteroskedasticity: a simulation study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 297-312, May.
    77. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.

  7. Morimune, Kimio & Sakata, Shinichi, 1993. "Modified three-stage least squares estimator which is third-order efficient," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 257-276.

    Cited by:

    1. M. Dolores de Prada & Luis M. Borge, 1997. "Some methods for comparing first-order asymptotically equivalent estimators," Investigaciones Economicas, Fundación SEPI, vol. 21(3), pages 473-500, September.

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