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Citations for "Quantile and Probability Curves Without Crossing"

by Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon

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  1. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 9(3), pages 8, July.
  2. 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.
  3. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, Elsevier.
  4. Frandsen, Brigham R. & Frölich, Markus & Melly, Blaise, 2012. "Quantile treatment effects in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 168(2), pages 382-395.
  5. Marcella Lucchetta & Gianni De Nicolo, 2012. "Systemic Real and Financial Risks; Measurement, Forecasting, and Stress Testing," IMF Working Papers 12/58, International Monetary Fund.
  6. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
  7. Mendolia, Silvia & Paloyo, Alfredo R. & Walker, Ian, 2016. "Heterogeneous Effects of High School Peers on Educational Outcomes," IZA Discussion Papers 9795, Institute for the Study of Labor (IZA).
  8. Picchio, M. & Mussida, C., 2010. "Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction," Discussion Paper 2010-16, Tilburg University, Center for Economic Research.
  9. Žikeš, Filip & Baruník, Jozef, 2014. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," FinMaP-Working Papers 20, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  10. Franco Peracchi & Samantha Leorato, 2015. "Shape Regressions," Working Papers gueconwpa~15-15-06, Georgetown University, Department of Economics.
  11. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2013. "Inference on counterfactual distributions," CeMMAP working papers CWP17/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
  13. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
  14. Zhongjun Qu & Jungmo Yoon, 2015. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Boston University - Department of Economics - Working Papers Series wp2015-009, Boston University - Department of Economics.
  15. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  16. Habert white & Tae-Hwan Kim & Simone Manganelli, 2012. "VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles," Working papers 2012rwp-45, Yonsei University, Yonsei Economics Research Institute.
  17. Santiago Pereda Fernández, 2016. "A new method for the correction of test scores manipulation," Temi di discussione (Economic working papers) 1047, Bank of Italy, Economic Research and International Relations Area.
  18. Holger Dette & Matthias Guhlich & Natalie Neumeyer, 2015. "Testing for additivity in nonparametric quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(3), pages 437-477, June.
  19. Sabine Schnabel & Paul Eilers, 2013. "Simultaneous estimation of quantile curves using quantile sheets," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 77-87, January.
  20. Nicole Fortin & Thomas Lemieux & Sergio Firpo, 2010. "Decomposition Methods in Economics," NBER Working Papers 16045, National Bureau of Economic Research, Inc.
  21. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
  22. Kaspar Wüthrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
  23. Ritter, Joseph A. & West, Kristine L., 2014. "Field of Study and Earnings Inequality among the Highly Educated: 1993-2010," Miscellaneous Publications 195683, University of Minnesota, Department of Applied Economics.
  24. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  25. Christian Manuel Posso, 2010. "Desigualdad salarial en Colombia 1984-2005: cambios en la composición del mercado laboral y retornos a la educación post-secundaria," REVISTA DESARROLLO Y SOCIEDAD, UNIVERSIDAD DE LOS ANDES-CEDE, December.
  26. Ghossoub, Mario, 2011. "Monotone equimeasurable rearrangements with non-additive probabilities," MPRA Paper 37629, University Library of Munich, Germany, revised 23 Mar 2012.
  27. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile regression with censoring and endogeneity," CeMMAP working papers CWP20/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  28. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
  29. Roger Koenker & Samantha Leorato & Franco Peracchi, 2013. "Distributional vs. Quantile Regression," CEIS Research Paper 300, Tor Vergata University, CEIS, revised 17 Dec 2013.
  30. Nicodemo, Catia & Raya, Josep M., 2012. "Change in the Distribution of House Prices across Spanish Cities," IZA Discussion Papers 6503, Institute for the Study of Labor (IZA).
  31. Richard H. Spady & Sami Stouli, 2016. "Dual Regression," Bristol Economics Discussion Papers 16/669, Department of Economics, University of Bristol, UK.
  32. Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 423-457, September.
  33. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  34. Haben, Stephen & Giasemidis, Georgios, 2016. "A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1017-1022.
  35. Ruhose, Jens & Parey, Matthias & Waldinger, Fabian & Netz, Nicolai, 2015. "The Selection of High-Skilled Migrants," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113148, Verein für Socialpolitik / German Economic Association.
  36. Lamarche, Carlos, 2011. "Measuring the incentives to learn in Colombia using new quantile regression approaches," Journal of Development Economics, Elsevier, vol. 96(2), pages 278-288, November.
  37. Blaise Melly und Kaspar Wüthrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
  38. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "On the asymptotic theory for least squares series: pointwise and uniform results," CeMMAP working papers CWP73/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  39. Qi Li & Juan Lin & Jeffrey S. Racine, 2013. "Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 57-65, January.
  40. Stephen G. Donald & Yu-Chin Hsu, 2012. "Estimation and Inference for Distribution Functions and Quantile Functions in Treatment Effect Models," IEAS Working Paper : academic research 12-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  41. Julio Galvez & Javier Mencía, 2014. "Distributional Linkages Between European Sovereign Bond And Bank Asset Returns," Working Papers wp2014_1407, CEMFI.
  42. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
  43. Nicolas Albacete & Pirmin Fessler & Martin Schürz, 2012. "Risk Buffer Profiles of Foreign Currency Mortgage Holders," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 23, pages 58-71.
  44. Weili Ding & Steven F. Lehrer, 2014. "Understanding the Role of Time-Varying Unobserved Ability Heterogeneity in Education Production," NBER Working Papers 19937, National Bureau of Economic Research, Inc.
  45. Richard Spady & Sami Stouli, 2016. "Dual regression," CeMMAP working papers CWP04/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  46. Ilaria Lucrezia Amerise, 2013. "Weighted Non-Crossing Quantile Regressions," Working Papers 201308, Università della Calabria, Dipartimento di Economia, Statistica e Finanza (Ex Dipartimento di Economia e Statistica).
  47. de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2015. "Fuzzy Differences-in-Differences," The Warwick Economics Research Paper Series (TWERPS) 1065, University of Warwick, Department of Economics.
  48. Carolina Castagnetti, 2015. "The Analysis of the Gender Wage Gap in the Italian Public Sector: a Quantile Approach for Panel Data," DEM Working Papers Series 109, University of Pavia, Department of Economics and Management.
  49. 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.
  50. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
  51. P. Givord & X. Dhaultfoeuille, 2013. "La régression quantile en pratique," Document de travail "Methodologie Statistique" - DMS Working Paper m2013-01, Institut National de la Statistique et des Etudes Economiques.
  52. Souhaib Ben Taieb & Raphael Huser & Rob J. Hyndman & Marc G. Genton, 2015. "Probabilistic time series forecasting with boosted additive models: an application to smart meter data," Monash Econometrics and Business Statistics Working Papers 12/15, Monash University, Department of Econometrics and Business Statistics.
  53. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
  54. Lian, Heng, 2012. "A note on the consistency of Schwarz’s criterion in linear quantile regression with the SCAD penalty," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1224-1228.
  55. repec:gam:jecnmx:v:4:y:2015:i:1:p:2:d:61252 is not listed on IDEAS
  56. Gail Pacheco & Bill Cochrane, 2015. "Decomposing the temporary-permanent wage gap in New Zealand," Working Papers 2015-07, Auckland University of Technology, Department of Economics.
  57. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, Open Access Journal, vol. 4(1), pages 2, December.
  58. Holger Dette & Regine Scheder, 2011. "Estimation of additive quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 245-265, April.
  59. Charlier, Isabelle & Paindaveine, Davy & Saracco, Jérôme, 2015. "Conditional quantile estimation based on optimal quantization: From theory to practice," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 20-39.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.