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Measuring inequality using censored data: a multiple-imputation approach to estimation and inference

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Cited by:

  1. Dang, Hai-Anh H & Carletto, Calogero, 2022. "Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation," IZA Discussion Papers 14997, Institute of Labor Economics (IZA).
  2. Philip Armour & Richard V. Burkhauser & Jeff Larrimore, 2016. "Using The Pareto Distribution To Improve Estimates Of Topcoded Earnings," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 1263-1273, April.
  3. Hai‐Anh Dang & Dean Jolliffe & Calogero Carletto, 2019. "Data Gaps, Data Incomparability, And Data Imputation: A Review Of Poverty Measurement Methods For Data‐Scarce Environments," Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 757-797, July.
  4. Clementi,Fabio & Fabiani,Michele & Molini,Vasco & Schettino,Francesco, 2022. "Is Inequality Systematically Underestimated in Sub-Saharan Africa ? A Proposal toOvercome the Problem," Policy Research Working Paper Series 10058, The World Bank.
  5. Doerrenberg, Philipp & Duncan, Denvil & Fuest, Clemens & Peichl, Andreas, 2012. "Nice Guys Finish Last: Are People with Higher Tax Morale Taxed More Heavily?," IZA Discussion Papers 6275, Institute of Labor Economics (IZA).
  6. Markus P. A. Schneider, 2013. "Race & Gender Differences in the Experience of Earnings Inequality in the US from 1995 to 2010," Working Papers 1303, New School for Social Research, Department of Economics.
  7. Lucio Barabesi & Giancarlo Diana & Pier Perri, 2015. "Gini index estimation in randomized response surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 45-62, January.
  8. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
  9. Nora Lustig, 2018. "Measuring the Distribution of Household Income, Consumption and Wealth: State of Play and Measurement Challenges," Working Papers 1801, Tulane University, Department of Economics.
  10. Vladimir Hlasny & Lidia Ceriani & Paolo Verme, 2022. "Bottom Incomes and the Measurement of Poverty and Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(4), pages 970-1006, December.
  11. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and Inequality Measurement: A Comparative Analysis of Correction Methods Using the EU SILC Data," Econometrics, MDPI, vol. 6(2), pages 1-21, June.
  12. Christian Schluter & Mark Trede, 2024. "Spatial earnings inequality," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(3), pages 531-550, September.
  13. Jekaterina Navickė & Romas Lazutka, 2018. "Distributional Implications of the Economic Development in the Baltics: Reconciling Micro and Macro Perspectives," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(1), pages 187-206, July.
  14. Philipp Doerrenberg & Denvil Duncan & Clemens Fuest & Andreas Peichl, 2014. "Nice Guys Finish Last: Do Honest Taxpayers Face Higher Tax Rates?," Kyklos, Wiley Blackwell, vol. 67(1), pages 29-53, February.
  15. Dang, Hai-Anh & Carletto, Calogero & Gourlay, Sydney & Abanokova, Kseniya, 2024. "Addressing Soil Quality Data Gaps with Imputation: Evidence from Ethiopia and Uganda," GLO Discussion Paper Series 1445, Global Labor Organization (GLO).
  16. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2021. "Inequality measurement with grouped data: Parametric and non‐parametric methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 964-984, July.
  17. Saparya Suresh & Sudheesh K. Kattumannil, 2025. "Jackknife empirical likelihood ratio test for testing the equality of semivariance," Statistical Papers, Springer, vol. 66(1), pages 1-17, February.
  18. Hai-Anh H. Dang & Peter F. Lanjouw & Umar Serajuddin, 2017. "Updating poverty estimates in the absence of regular and comparable consumption data: methods and illustration with reference to a middle-income country," Oxford Economic Papers, Oxford University Press, vol. 69(4), pages 939-962.
  19. Porro Francesco, 2014. "How We Can Evaluate the Inequality in Flint," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 119-128, December.
  20. F. Clementi & A. L. Dabalen & V. Molini & F. Schettino, 2020. "We forgot the middle class! Inequality underestimation in a changing Sub-Saharan Africa," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 45-70, March.
  21. Fix, Blair, 2018. "Capitalist Income and Hierarchical Power," SocArXiv u8epv, Center for Open Science.
  22. Benjapon Prommawin & Nattanun Svavasu & Spol Tanpraphan & Voravee Saengavut & Theepakorn Jithitikulchai & Witsanu Attavanich & Bruce A. McCarl, 2024. "Impacts of climate change and agricultural diversification on agricultural production value of Thai farm households," Climatic Change, Springer, vol. 177(7), pages 1-26, July.
  23. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
  24. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
  25. Dang, Hai-Anh & Kilic, Talip & Hlasny, Vladimir & Abanokova, Kseniya & Carletto, Calogero, 2024. "Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment," GLO Discussion Paper Series 1392, Global Labor Organization (GLO).
  26. Li Tan, 2021. "Imputing Top‐Coded Income Data in Longitudinal Surveys," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 66-87, February.
  27. Emmenegger Jana & Münnich Ralf, 2023. "Localising the Upper Tail: How Top Income Corrections Affect Measures of Regional Inequality," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(3-4), pages 285-317, June.
  28. Vladimir Hlasny, 2019. "Redistributive Impacts of Fiscal Policies in Mexico: Corrections for Top Income Measurement Problems," LIS Working papers 765, LIS Cross-National Data Center in Luxembourg.
  29. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
  30. Fix, Blair, 2018. "Capitalist income and hierarchical power: A gradient hypothesis," Working Papers on Capital as Power 2018/06, Capital As Power - Toward a New Cosmology of Capitalism.
  31. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
  32. Kattumannil, Sudheesh K. & Dewan, Isha & N., Sreelaksmi, 2021. "Non-parametric estimation of Gini index with right censored observations," Statistics & Probability Letters, Elsevier, vol. 175(C).
  33. Conrad Scheibe, 2016. "Fiscal Consolidations and Their Effects on Income Inequality," UCL SSEES Economics and Business working paper series 2016-4, UCL School of Slavonic and East European Studies (SSEES).
  34. Jonathan D. Fisher & David S. Johnson & Timothy M. Smeeding, 2013. "Measuring the Trends in Inequality of Individuals and Families: Income and Consumption," American Economic Review, American Economic Association, vol. 103(3), pages 184-188, May.
  35. von Fintel, Dieter & Orthofer, Anna, 2020. "Wealth inequality and financial inclusion: Evidence from South African tax and survey records," Economic Modelling, Elsevier, vol. 91(C), pages 568-578.
  36. Speidel, Matthias & Drechsler, Jörg & Jolani, Shahab, 2018. "R package hmi: a convenient tool for hierarchical multiple imputation and beyond," IAB-Discussion Paper 201816, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  37. Dang,Hai-Anh H. & Lanjouw,Peter F. & Serajuddin,Umar & Dang,Hai-Anh H. & Lanjouw,Peter F. & Serajuddin,Umar, 2014. "Updating poverty estimates at frequent intervals in the absence of consumption data : methods and illustration with reference to a middle-income country," Policy Research Working Paper Series 7043, The World Bank.
  38. Bartels, Charlotte & Waldenström, Daniel, 2021. "Inequality and top incomes," GLO Discussion Paper Series 959, Global Labor Organization (GLO).
  39. Dang,Hai-Anh H. & Kilic,Talip & Carletto,Calogero & Abanokova,Kseniya, 2021. "Poverty Imputation in Contexts without Consumption Data : A Revisit with Further Refinements," Policy Research Working Paper Series 9838, The World Bank.
  40. Advani, Arun & Summers, Andy & Tarrant, Hannah, 2020. "Measuring UK top incomes," CAGE Online Working Paper Series 490, Competitive Advantage in the Global Economy (CAGE).
  41. 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.
  42. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.
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