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Samantha Leorato

Personal Details

First Name:Samantha
Middle Name:
Last Name:Leorato
Suffix:
RePEc Short-ID:ple1193

Affiliation

Dipartimento di Economia, Management e Metodi Quantitativi (DEMM)
Università degli Studi di Milano

Milano, Italy
http://www.demm.unimi.it/
RePEc:edi:damilit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
  2. Franco Peracchi & Samantha Leorato, 2015. "Shape Regressions," Working Papers gueconwpa~15-15-06, Georgetown University, Department of Economics.
  3. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
  4. Samantha Leorato & Maura Mezzetti, 2015. "Spatial Panel Data Model with error dependence: a Bayesian Separable Covariance Approach," CEIS Research Paper 338, Tor Vergata University, CEIS, revised 09 Apr 2015.
  5. Roger Koenker & Samantha Leorato & Franco Peracchi, 2013. "Distributional vs. Quantile Regression," CEIS Research Paper 300, Tor Vergata University, CEIS, revised 17 Dec 2013.
  6. Samantha Leorato & Franco Peracchi & Andrei V. Tanase, 2010. "Asymptotically Efficient Estimation of the Conditional Expected Shortfall," EIEF Working Papers Series 1013, Einaudi Institute for Economics and Finance (EIEF), revised Dec 2010.
  7. Samantha Leorato, 2008. "A refined Jensen’s inequality in Hilbert spaces and empirical approximations," CEIS Research Paper 134, Tor Vergata University, CEIS, revised 24 Nov 2008.

Articles

  1. Anna Gloria Billé & Samantha Leorato, 2020. "Partial ML estimation for spatial autoregressive nonlinear probit models with autoregressive disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 437-475, May.
  2. Leorato, Samantha & Peracchi, Franco & Tanase, Andrei V., 2012. "Asymptotically efficient estimation of the conditional expected shortfall," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 768-784.
  3. Leorato, S., 2009. "A refined Jensen's inequality in Hilbert spaces and empirical approximations," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 1044-1060, May.
  4. Leorato, S. & Orsingher, E., 2009. "Branching on a Sierpinski graph," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 145-154, January.
  5. Broniatowski, M. & Leorato, S., 2006. "An estimation method for the Neyman chi-square divergence with application to test of hypotheses," Journal of Multivariate Analysis, Elsevier, vol. 97(6), pages 1409-1436, July.

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. Franco Peracchi & Samantha Leorato, 2015. "Shape Regressions," Working Papers gueconwpa~15-15-06, Georgetown University, Department of Economics.

    Cited by:

    1. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.

  2. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.

    Cited by:

    1. Samantha Leorato & Franco Peracchi, 2015. "Shape Regressions," EIEF Working Papers Series 1506, Einaudi Institute for Economics and Finance (EIEF), revised Jul 2015.
    2. Anatolyev, Stanislav & Baruník, Jozef, 2019. "Forecasting dynamic return distributions based on ordered binary choice," International Journal of Forecasting, Elsevier, vol. 35(3), pages 823-835.
    3. Rothe, Christoph & Wied, Dominik, 2020. "Estimating derivatives of function-valued parameters in a class of moment condition models," Journal of Econometrics, Elsevier, vol. 217(1), pages 1-19.
    4. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    5. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.

  3. Roger Koenker & Samantha Leorato & Franco Peracchi, 2013. "Distributional vs. Quantile Regression," CEIS Research Paper 300, Tor Vergata University, CEIS, revised 17 Dec 2013.

    Cited by:

    1. Kolodziej, Ingo W.K. & García-Gómez, Pilar, 2019. "Saved by retirement: Beyond the mean effect on mental health," Social Science & Medicine, Elsevier, vol. 225(C), pages 85-97.
    2. Boyarchenko, Nina & Adrian, Tobias & Giannone, Domenico, 2020. "Multimodality in Macro-Financial Dynamics," CEPR Discussion Papers 15088, C.E.P.R. Discussion Papers.
    3. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    4. Richey, Jeremiah & Rosburg, Alicia, 2016. "Understanding intergenerational economic mobility by decomposing joint distributions," MPRA Paper 72665, University Library of Munich, Germany.
    5. Ricardo J. Bessa & Corinna Möhrlen & Vanessa Fundel & Malte Siefert & Jethro Browell & Sebastian Haglund El Gaidi & Bri-Mathias Hodge & Umit Cali & George Kariniotakis, 2017. "Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry," Energies, MDPI, vol. 10(9), pages 1-48, September.
    6. Samantha Leorato & Franco Peracchi, 2015. "Shape Regressions," EIEF Working Papers Series 1506, Einaudi Institute for Economics and Finance (EIEF), revised Jul 2015.
    7. García, A., 2016. "Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes," Documentos de Trabajo 14186, Universidad del Rosario.
    8. Philippe Van Kerm & Seunghee Yu & Chung Choe, 2016. "Decomposing quantile wage gaps: a conditional likelihood approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 507-527, August.
    9. Kolodziej, Ingo W.K. & García-Gómez, Pilar, 2017. "The causal effects of retirement on mental health: Looking beyond the mean effects," Ruhr Economic Papers 668, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    10. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1-14, December.
    11. Richey, Jeremiah & Rosburg, Alicia, 2015. "Decomposing economic mobility transition matrices," MPRA Paper 66485, University Library of Munich, Germany.
    12. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2022. "Bivariate Distribution Regression with Application to Insurance Data," Papers 2203.12228, arXiv.org, revised Sep 2023.
    13. Paul Redmond & Karina Doorley & Seamus McGuinness, 2021. "The impact of a minimum wage change on the distribution of wages and household income," Oxford Economic Papers, Oxford University Press, vol. 73(3), pages 1034-1056.
    14. Dominik Wied, 2022. "Semiparametric Distribution Regression with Instruments and Monotonicity," Papers 2212.03704, arXiv.org.
    15. Xu Chen & Surya T. Tokdar, 2021. "Joint quantile regression for spatial data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 826-852, September.
    16. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    17. Yuanhua Feng & Wolfgang Karl Härdle, 2021. "Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression," Working Papers CIE 142, Paderborn University, CIE Center for International Economics.
    18. Ricardo Masini, 2022. "Distributional Counterfactual Analysis in High-Dimensional Setup," Papers 2202.11671, arXiv.org, revised Sep 2023.
    19. Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017. "Estimation and Inference for Actual and Counterfactual Growth Incidence Curves," IZA Discussion Papers 10473, Institute of Labor Economics (IZA).
    20. Bargain, Olivier B. & Doorley, Karina & Van Kerm, Philippe, 2018. "Minimum Wages and the Gender Gap in Pay: New Evidence from the UK and Ireland," IZA Discussion Papers 11502, Institute of Labor Economics (IZA).
    21. Redmond, Paul & Doorley, Karina & McGuinness, Seamus, 2019. "The impact of a change in the National Minimum Wage on the distribution of hourly wages and household income in Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS86.
    22. Doorley, Karina & Privalko, Ivan & Russell, Helen & Tuda, Dora, 2021. "The Gender Pay Gap in Ireland from Austerity through Recovery," IZA Discussion Papers 14441, Institute of Labor Economics (IZA).

  4. Samantha Leorato & Franco Peracchi & Andrei V. Tanase, 2010. "Asymptotically Efficient Estimation of the Conditional Expected Shortfall," EIEF Working Papers Series 1013, Einaudi Institute for Economics and Finance (EIEF), revised Dec 2010.

    Cited by:

    1. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    2. Yan Fang & Jian Li & Yinglin Liu & Yunfan Zhao, 2023. "Semiparametric estimation of expected shortfall and its application in finance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 835-851, July.
    3. Zhongde Luo, 2020. "Nonparametric kernel estimation of CVaR under $$\alpha $$α-mixing sequences," Statistical Papers, Springer, vol. 61(2), pages 615-643, April.
    4. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2013. "Pair Copula Construction based Expected Shortfall estimation," Economics Bulletin, AccessEcon, vol. 33(2), pages 1067-1072.
    5. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    6. Rockafellar, R.T. & Royset, J.O. & Miranda, S.I., 2014. "Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 234(1), pages 140-154.

Articles

  1. Anna Gloria Billé & Samantha Leorato, 2020. "Partial ML estimation for spatial autoregressive nonlinear probit models with autoregressive disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 437-475, May.

    Cited by:

    1. Piras, Gianfranco & Sarrias, Mauricio, 2023. "One or two-step? Evaluating GMM efficiency for spatial binary probit models," Journal of choice modelling, Elsevier, vol. 48(C).
    2. Alessio Tomelleri & Anna Gloria Billé, 2023. "Do micro-enterprises ask for local support measures? Evidence after the COVID-19 pandemic," FBK-IRVAPP Working Papers 2023-04, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.

  2. Leorato, Samantha & Peracchi, Franco & Tanase, Andrei V., 2012. "Asymptotically efficient estimation of the conditional expected shortfall," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 768-784.
    See citations under working paper version above.
  3. Broniatowski, M. & Leorato, S., 2006. "An estimation method for the Neyman chi-square divergence with application to test of hypotheses," Journal of Multivariate Analysis, Elsevier, vol. 97(6), pages 1409-1436, July.

    Cited by:

    1. Toma, Aida & Broniatowski, Michel, 2011. "Dual divergence estimators and tests: Robustness results," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 20-36, January.
    2. Cerqueti, Roy & Maggi, Mario, 2021. "Data validity and statistical conformity with Benford’s Law," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    3. Broniatowski, Michel, 2014. "Minimum divergence estimators, maximum likelihood and exponential families," Statistics & Probability Letters, Elsevier, vol. 93(C), pages 27-33.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 7 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 (6) 2010-08-21 2013-12-29 2015-04-19 2015-07-18 2015-11-15 2018-01-01. Author is listed
  2. NEP-RMG: Risk Management (2) 2015-07-18 2015-07-25
  3. NEP-URE: Urban and Real Estate Economics (2) 2015-04-19 2018-01-01
  4. NEP-ETS: Econometric Time Series (1) 2018-01-01
  5. NEP-ORE: Operations Research (1) 2018-01-01

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