IDEAS home Printed from https://ideas.repec.org/f/pgr226.html
   My authors  Follow this author

Francesca Greselin

Personal Details

First Name:Francesca
Middle Name:
Last Name:Greselin
Suffix:
RePEc Short-ID:pgr226

Affiliation

Dipartimento di Metodi Quantitativi per le Scienze Economiche e Aziendali
Scuola di Economia e Statistica
Università degli Studi di Milano-Bicocca

Milano, Italy
http://www.dimequant.unimib.it/
RePEc:edi:dqmibit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.
  2. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
  3. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
  4. Greselin, Francesca & Pasquazzi, Leo, 2011. "Estimation of Zenga's new index of economic inequality in heavy tailed populations," MPRA Paper 31230, University Library of Munich, Germany.
  5. Greselin, Francesca & Pasquazzi, Leo & Zitikis, Ricardas, 2009. "Zenga’s new index of economic inequality, its estimation, and an analysis of incomes in Italy," MPRA Paper 17147, University Library of Munich, Germany.

Articles

  1. Andrea Cappozzo & Luis Angel García Escudero & Francesca Greselin & Agustín Mayo-Iscar, 2021. "Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling," Stats, MDPI, vol. 4(3), pages 1-14, July.
  2. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
  3. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  4. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
  5. Francesca Greselin & Alina Jȩdrzejczak, 2020. "Analyzing the Gender Gap in Poland and Italy, and by Regions," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 433-447, November.
  6. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 327-354, June.
  7. Francesca Greselin & Fabio Piacenza & Ričardas Zitikis, 2019. "Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement," Risks, MDPI, vol. 7(2), pages 1-20, May.
  8. Youri Davydov & Francesca Greselin, 2019. "Inferential results for a new measure of inequality," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 153-172.
  9. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(2), pages 203-233, June.
  10. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.
  11. García-Escudero, Luis Angel & Gordaliza, Alfonso & Greselin, Francesca & Ingrassia, Salvatore & Mayo-Iscar, Agustín, 2016. "The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 131-147.
  12. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.
  13. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2013. "Contrasting the Gini and Zenga indices of economic inequality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 282-297, February.
  14. Francesca Greselin & Antonio Punzo, 2013. "Closed Likelihood Ratio Testing Procedures to Assess Similarity of Covariance Matrices," The American Statistician, Taylor & Francis Journals, vol. 67(3), pages 117-128, August.
  15. Francesca Greselin & Salvatore Ingrassia & Antonio Punzo, 2011. "Assessing the pattern of covariance matrices via an augmentation multiple testing procedure," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 141-170, June.
  16. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2010. "Zenga's New Index of Economic Inequality, Its Estimation, and an Analysis of Incomes in Italy," Journal of Probability and Statistics, Hindawi, vol. 2010, pages 1-26, April.

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. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.

  2. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.

    Cited by:

    1. Sebastian Fuchs & Ruben Schlotter & Klaus D. Schmidt, 2017. "A Review and Some Complements on Quantile Risk Measures and Their Domain," Risks, MDPI, vol. 5(4), pages 1-16, November.

  3. Greselin, Francesca & Pasquazzi, Leo & Zitikis, Ricardas, 2009. "Zenga’s new index of economic inequality, its estimation, and an analysis of incomes in Italy," MPRA Paper 17147, University Library of Munich, Germany.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
    2. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.
    3. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    4. Michele Zenga, 2016. "On the decomposition by subpopulations of the point and synthetic Zenga (2007) inequality indexes," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 375-405, December.
    5. Matti Langel & Yves Tillé, 2012. "Inference by linearization for Zenga’s new inequality index: a comparison with the Gini index," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1093-1110, November.
    6. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    7. Pasquazzi Leo & Zenga Michele, 2018. "Components of Gini, Bonferroni, and Zenga Inequality Indexes for EU Income Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 149-180, March.
    8. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.

Articles

  1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.

    Cited by:

    1. Monti Maria Giovanna & Pellegrino Simone & Vernizzi Achille, 2024. "The Zenga Index Reveals More Than the Gini and the Bonferroni Indexes. An Analysis of Distributional Changes and Social Welfare Levels," Working papers 084, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.

  2. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.

    Cited by:

    1. Vytaras Brazauskas & Francesca Greselin & Ricardas Zitikis, 2023. "Measuring income inequality via percentile relativities," Papers 2308.03708, arXiv.org.
    2. Vytaras Brazauskas & Francesca Greselin & Ričardas Zitikis, 2024. "Measuring income inequality via percentile relativities," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4859-4896, October.

  3. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 327-354, June.

    Cited by:

    1. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).

  4. Francesca Greselin & Fabio Piacenza & Ričardas Zitikis, 2019. "Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement," Risks, MDPI, vol. 7(2), pages 1-20, May.

    Cited by:

    1. Teodora Maria SUCIU (AVRAM), 2020. "Possibilities Of Evaluation Of The Expenditure Of The Clothing Industry By The Monte Carlo Method," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 5(3), pages 29-37.
    2. Jiandong Ren & Kristina Sendova & Ričardas Zitikis, 2019. "Special Issue “Risk, Ruin and Survival: Decision Making in Insurance and Finance”," Risks, MDPI, vol. 7(3), pages 1-7, September.

  5. Youri Davydov & Francesca Greselin, 2019. "Inferential results for a new measure of inequality," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 153-172.

    Cited by:

    1. Mario Schlemmer, 2021. "Coupling the Gini and Angles to Evaluate Economic Dispersion," Papers 2110.13847, arXiv.org, revised Sep 2022.
    2. Vytaras Brazauskas & Francesca Greselin & Ricardas Zitikis, 2023. "Measuring income inequality via percentile relativities," Papers 2308.03708, arXiv.org.
    3. Vytaras Brazauskas & Francesca Greselin & Ričardas Zitikis, 2024. "Measuring income inequality via percentile relativities," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4859-4896, October.

  6. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(2), pages 203-233, June.

    Cited by:

    1. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 327-354, June.
    2. Cong, Lin & Yao, Weixin, 2021. "A Likelihood Ratio Test of a Homoscedastic Multivariate Normal Mixture Against a Heteroscedastic Multivariate Normal Mixture," Econometrics and Statistics, Elsevier, vol. 18(C), pages 79-88.
    3. Keefe Murphy & Thomas Brendan Murphy, 2020. "Gaussian parsimonious clustering models with covariates and a noise component," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 293-325, June.

  7. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.

    Cited by:

    1. Maha A Aldahlan & Farrukh Jamal & Christophe Chesneau & Ibrahim Elbatal & Mohammed Elgarhy, 2020. "Exponentiated power generalized Weibull power series family of distributions: Properties, estimation and applications," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-25, March.
    2. Nadezhda Gribkova & Ričardas Zitikis, 2019. "Weighted allocations, their concomitant-based estimators, and asymptotics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 811-835, August.
    3. Piotr Misztal & Paweł Dziekański, 2023. "Green Economy and Waste Management as Determinants of Modeling Green Capital of Districts in Poland in 2010–2020," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    4. Luigi Mastronardi & Aurora Cavallo, 2020. "The Spatial Dimension of Income Inequality: An Analysis at Municipal Level," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    5. Debora Daniela Escobar & Georg Ch. Pflug, 2020. "The distortion principle for insurance pricing: properties, identification and robustness," Annals of Operations Research, Springer, vol. 292(2), pages 771-794, September.
    6. Daniela Escobar & Georg Pflug, 2018. "The distortion principle for insurance pricing: properties, identification and robustness," Papers 1809.06592, arXiv.org.
    7. Hai-Yan Yu & Jing-Jing Chen & Jying-Nan Wang & Ya-Ling Chiu & Hang Qiu & Li-Ya Wang, 2019. "Identification of the Differential Effect of City-Level on the Gini Coefficient of Health Service Delivery in Online Health Community," IJERPH, MDPI, vol. 16(13), pages 1-18, June.
    8. Marco Capaldo & Antonio Di Crescenzo & Alessandra Meoli, 2024. "Cumulative information generating function and generalized Gini functions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 87(7), pages 775-803, October.
    9. Antonia Castaño-Martínez & Gema Pigueiras & Georgios Psarrakos & Miguel A. Sordo, 2020. "Increasing concave orderings of linear combinations of order statistics with applications to social welfare," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(6), pages 699-712, August.
    10. Satya R. Chakravarty & Palash Sarkar, 2021. "An inequality paradox: relative versus absolute indices?," METRON, Springer;Sapienza Università di Roma, vol. 79(2), pages 241-254, August.

  8. García-Escudero, Luis Angel & Gordaliza, Alfonso & Greselin, Francesca & Ingrassia, Salvatore & Mayo-Iscar, Agustín, 2016. "The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 131-147.

    Cited by:

    1. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 327-354, June.
    2. Kasa, Siva Rajesh & Rajan, Vaibhav, 2022. "Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation," Econometrics and Statistics, Elsevier, vol. 22(C), pages 67-97.
    3. Francesca Torti & Domenico Perrotta & Marco Riani & Andrea Cerioli, 2019. "Assessing trimming methodologies for clustering linear regression data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 227-257, March.
    4. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(2), pages 203-233, June.

  9. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.

    Cited by:

    1. Francesca Greselin & Alina Jȩdrzejczak, 2020. "Analyzing the Gender Gap in Poland and Italy, and by Regions," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 433-447, November.
    2. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
    3. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    4. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.
    5. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.

  10. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2013. "Contrasting the Gini and Zenga indices of economic inequality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 282-297, February.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
    2. Alex Cobham & Lukas Schlögl & Andy Sumner, 2016. "Inequality and the Tails: the Palma Proposition and Ratio," Global Policy, London School of Economics and Political Science, vol. 7(1), pages 25-36, February.
    3. Alex Cobham & Andrew Sumner, 2013. "Is it all about the tails? The Palma measure of income inequality," Working Papers 308, ECINEQ, Society for the Study of Economic Inequality.
    4. Luigi Grossi & Mauro Mussini, 2017. "Inequality in Energy Intensity in the EU-28: Evidence from a New Decomposition Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    5. Alex Cobham, Andy Sumner, 2013. "Is It All About the Tails? The Palma Measure of Income Inequality-Working Paper 343," Working Papers 343, Center for Global Development.
    6. Alex Cobham & Luke Schlogl & Andy Sumner, 2015. "Inequality and the tails: The Palma proposition and ratio revised," Working Papers 366, ECINEQ, Society for the Study of Economic Inequality.
    7. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
    8. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    9. Alina Jędrzejczak & Dorota Pekasiewicz, 2020. "Changes in Income Distribution for Different Family Types in Poland," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(2), pages 135-146, May.
    10. Michele Zenga, 2016. "On the decomposition by subpopulations of the point and synthetic Zenga (2007) inequality indexes," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 375-405, December.
    11. Kamila Trzcińska & Elżbieta Zalewska, 2024. "A Comparative Analysis of Household Incomes of People with Different Levels of Education in Poland and the USA," LIS Working papers 877, LIS Cross-National Data Center in Luxembourg.
    12. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    13. Pasquazzi Leo & Zenga Michele, 2018. "Components of Gini, Bonferroni, and Zenga Inequality Indexes for EU Income Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 149-180, March.
    14. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.
    15. Satya R. Chakravarty & Palash Sarkar, 2021. "An inequality paradox: relative versus absolute indices?," METRON, Springer;Sapienza Università di Roma, vol. 79(2), pages 241-254, August.
    16. Monti Maria Giovanna & Pellegrino Simone & Vernizzi Achille, 2024. "The Zenga Index Reveals More Than the Gini and the Bonferroni Indexes. An Analysis of Distributional Changes and Social Welfare Levels," Working papers 084, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    17. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.
    18. Małgorzata Ćwiek & Kamila Trzcińska, 2023. "Assessment of goodness of fit of income distribution in France and Germany based on the Zenga distribution," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4013-4027, October.

  11. Francesca Greselin & Antonio Punzo, 2013. "Closed Likelihood Ratio Testing Procedures to Assess Similarity of Covariance Matrices," The American Statistician, Taylor & Francis Journals, vol. 67(3), pages 117-128, August.

    Cited by:

    1. Luca Bagnato & Antonio Punzo, 2021. "Unconstrained representation of orthogonal matrices with application to common principal components," Computational Statistics, Springer, vol. 36(2), pages 1177-1195, June.
    2. Maruotti, Antonello & Punzo, Antonio, 2017. "Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 475-496.
    3. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    4. Salvatore D. Tomarchio & Luca Bagnato & Antonio Punzo, 2022. "Model-based clustering via new parsimonious mixtures of heavy-tailed distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 315-347, June.
    5. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.
    6. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 85-113, April.
    7. Angelo Mazza & Antonio Punzo, 2020. "Mixtures of multivariate contaminated normal regression models," Statistical Papers, Springer, vol. 61(2), pages 787-822, April.
    8. Dariush Najarzadeh & Mojtaba Khazaei & Mojtaba Ganjali, 2015. "Testing for equality of ordered eigenvectors of two multivariate normal populations," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 57-72, April.
    9. Tortora, Cristina & Franczak, Brian C. & Bagnato, Luca & Punzo, Antonio, 2024. "A Laplace-based model with flexible tail behavior," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).

  12. Francesca Greselin & Salvatore Ingrassia & Antonio Punzo, 2011. "Assessing the pattern of covariance matrices via an augmentation multiple testing procedure," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 141-170, June.

    Cited by:

    1. Luca Bagnato & Antonio Punzo, 2021. "Unconstrained representation of orthogonal matrices with application to common principal components," Computational Statistics, Springer, vol. 36(2), pages 1177-1195, June.
    2. Maruotti, Antonello & Punzo, Antonio, 2017. "Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 475-496.
    3. Salvatore D. Tomarchio & Luca Bagnato & Antonio Punzo, 2022. "Model-based clustering via new parsimonious mixtures of heavy-tailed distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 315-347, June.
    4. Ryan P. Browne & Luca Bagnato & Antonio Punzo, 2024. "Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(3), pages 597-625, September.
    5. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.
    6. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(2), pages 203-233, June.
    7. Dariush Najarzadeh & Mojtaba Khazaei & Mojtaba Ganjali, 2015. "Testing for equality of ordered eigenvectors of two multivariate normal populations," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 57-72, April.
    8. Tortora, Cristina & Franczak, Brian C. & Bagnato, Luca & Punzo, Antonio, 2024. "A Laplace-based model with flexible tail behavior," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).

  13. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2010. "Zenga's New Index of Economic Inequality, Its Estimation, and an Analysis of Incomes in Italy," Journal of Probability and Statistics, Hindawi, vol. 2010, pages 1-26, April.
    See citations under working paper version above.

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 3 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 (1) 2011-06-11
  2. NEP-EUR: Microeconomic European Issues (1) 2018-01-08
  3. NEP-GTH: Game Theory (1) 2015-08-19
  4. NEP-PBE: Public Economics (1) 2018-01-08
  5. NEP-PUB: Public Finance (1) 2018-01-08

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Francesca Greselin should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.