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Ivan Fernandez-Val

Personal Details

First Name:Ivan
Middle Name:
Last Name:Fernandez-Val
Suffix:
RePEc Short-ID:pfe104
http://sites.bu.edu/ivanf/
Terminal Degree:2005 Economics Department; Massachusetts Institute of Technology (MIT) (from RePEc Genealogy)

Affiliation

Department of Economics
Boston University

Boston, Massachusetts (United States)
http://www.bu.edu/econ/
RePEc:edi:decbuus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software

Working papers

  1. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis & Peracchi, Franco, 2022. "Selection and the Distribution of Female Hourly Wages in the U.S," IZA Discussion Papers 15028, Institute of Labor Economics (IZA).
  2. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
  3. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP10/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Fernández-Val, Iván & Peracchi, Franco & van Vuuren, Aico & Vella, Francis, 2020. "Hours Worked and the U.S. Distribution of Real Annual Earnings 1976–2016," IZA Discussion Papers 13016, Institute of Labor Economics (IZA).
  5. Ivan Fernandez-Val & Franco Peracchi & Francis Vella & Aico van Vuuren, 2019. "Decomposing Changes in the Distribution of Real Hourly Wages in the U.S," CeMMAP working papers CWP61/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  6. Shuowen Chen & Victor Chernozhukov & Ivan Fernandez-Val, 2019. "Mastering Panel Metrics: Causal Impact of Democracy on Growth," CeMMAP working papers CWP33/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Fernandez-Val , Ivan & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules," Working Papers in Economics 716, University of Gothenburg, Department of Economics.
  8. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2018. "Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," NBER Working Papers 24678, National Bureau of Economic Research, Inc.
  9. Victor Chernozhukov & Iván Fernández-Val & Sukjin Han & Amanda Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," NBER Working Papers 24232, National Bureau of Economic Research, Inc.
  10. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Decomposing Real Wage Changes in the United States," IZA Discussion Papers 12044, Institute of Labor Economics (IZA).
  11. Victor Chernozhukov & Ivan Fernandez-Val & Martin Weidner, 2018. "Network and panel quantile effects via distribution regression," CeMMAP working papers CWP21/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  13. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis, 2018. "Nonseparable Sample Selection Models with Censored Selection Rules: An Application to Wage Decompositions," IZA Discussion Papers 11294, Institute of Labor Economics (IZA).
  14. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers CWP33/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP42/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  16. Michael Lipsitz & Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2017. "Quantreg.nonpar: an R package for performing nonparametric series quantile regression," CeMMAP working papers CWP29/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  17. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017. "Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Papers 1712.04802, arXiv.org, revised Oct 2023.
  18. Victor Chernozhukov & Iván Fernández-Val & Whitney Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models," Bristol Economics Discussion Papers 17/690, School of Economics, University of Bristol, UK.
  19. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  20. Victor Chernozhukov & Ivan Fernandez-Val & Tetsuya Kaji, 2017. "Extremal quantile regression: an overview," CeMMAP working papers CWP65/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  21. Mingli Chen & Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2017. "Counterfactual analysis in R: a vignette," CeMMAP working papers CWP64/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  22. Mario Cruz-Gonzalez & Ivan Fernandez-Val & Martin Weidner, 2016. "probitfe and logitfe: Bias corrections for probit and logit models with two-way fixed effects," Papers 1610.07714, arXiv.org, revised Feb 2017.
  23. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar W thrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Diskussionsschriften dp1607, Universitaet Bern, Departement Volkswirtschaft.
  24. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers CWP13/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  25. Victor Chernozhukov & Ivan Fernandez-Val & Ye Luo, 2015. "The sorted effects method: discovering heterogeneous effects beyond their averages," CeMMAP working papers CWP74/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  26. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
  27. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers CWP66/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  28. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  29. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP60/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  30. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2013. "Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income," IZA Discussion Papers 7651, Institute of Labor Economics (IZA).
  31. Victor Chernozhukov & Ivan Fernandez-Val, 2011. "Inference for extremal conditional quantile models, with an application to market and birthweight risks," CeMMAP working papers CWP40/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  32. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2011. "Conditional quantile processes based on series or many regressors," CeMMAP working papers CWP19/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  33. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Cowles Foundation Discussion Papers 1797, Cowles Foundation for Research in Economics, Yale University.
  34. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves without Crossing," SciencePo Working papers Main hal-01052958, HAL.
  35. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.
  36. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2009. "Inference on counterfactual distributions," CeMMAP working papers CWP09/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  37. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Average and Quantile Effects in Nonseparable Panel Models," Papers 0904.1990, arXiv.org, revised Mar 2013.
  38. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney K. Newey, 2008. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP25/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  39. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2008. "Improving point and interval estimates of monotone functions by rearrangement," CeMMAP working papers CWP17/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  40. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Improving Estimates Of Monotone Functions By Rearrangement," Boston University - Department of Economics - Working Papers Series WP2007-012, Boston University - Department of Economics.
  41. Ivan Fernandez-Val, 2007. "Fixed Effects Estimation of Structural Parameters and Marginal Effects in Panel Probit Models," Boston University - Department of Economics - Working Papers Series WP2007-009, Boston University - Department of Economics.
  42. Fernández-Val, Iván & Vella, Francis, 2007. "Bias Corrections for Two-Step Fixed Effects Panel Data Estimators," IZA Discussion Papers 2690, Institute of Labor Economics (IZA).
  43. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile And Probability Curves Without Crossing," Boston University - Department of Economics - Working Papers Series WP2007-011, Boston University - Department of Economics.
  44. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Rearranging Edgeworth-Cornish-Fisher expansions," CeMMAP working papers CWP19/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  45. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
  46. Ivan Fernandez-Val, 2005. "Bias Correction in Panel Data Models with Individual Specific Parameters," Boston University - Department of Economics - Working Papers Series WP2005-041, Boston University - Department of Economics.
  47. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc.
  48. I. Fernandez-Val & J. Angrist & V. Chernozhukov, 2004. "Quantile Regression under Misspecification," Econometric Society 2004 North American Winter Meetings 198, Econometric Society.
  49. Iván Fernández-Val & Joonhwan Lee, "undated". "Panel Data Models with Nonadditive Unobserved Heterogeneity: Estimation and Inference," Boston University - Department of Economics - Working Papers Series wp2010-001, Boston University - Department of Economics.
  50. Victor Chernozhukov & Ivan Fernandez-Val & Amanda E. Kowalski, "undated". "Censored Quantile Instrumental Variable Estimation via Control Functions," Boston University - Department of Economics - Working Papers Series wp2009-012, Boston University - Department of Economics.
  51. V. Chernozhukov & Ivan Fernandez-Val, "undated". "Quantile and Average Effects in Nonseparable Panel Models," Boston University - Department of Economics - Working Papers Series wp2009-011, Boston University - Department of Economics.

Articles

  1. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly, 2022. "Fast algorithms for the quantile regression process," Empirical Economics, Springer, vol. 62(1), pages 7-33, January.
  2. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
  3. Paolo Frumento & Matteo Bottai & Iván Fernández-Val, 2021. "Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 783-797, April.
  4. Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 40-77.
  5. Victor Chernozhukov & Iván Fernández‐Val & Whitney Newey & Sami Stouli & Francis Vella, 2020. "Semiparametric estimation of structural functions in nonseparable triangular models," Quantitative Economics, Econometric Society, vol. 11(2), pages 503-533, May.
  6. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
  7. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
  8. Shuowen Chen & Victor Chernozhukov & Iván Fernández-Val, 2019. "Mastering Panel Metrics: Causal Impact of Democracy on Growth," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 77-82, May.
  9. Victor Chernozhukov & Ivan Fernández-Val & Sukjin Han & Amanda Kowalski, 2019. "Censored quantile instrumental-variable estimation with Stata," Stata Journal, StataCorp LP, vol. 19(4), pages 768-781, December.
  10. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
  11. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
  12. Victor Chernozhukov & Iván Fernández‐Val & Ye Luo, 2018. "The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages," Econometrica, Econometric Society, vol. 86(6), pages 1911-1938, November.
  13. Mario Cruz-Gonzalez & Iván Fernández-Val & Martin Weidner, 2017. "Bias corrections for probit and logit models with two-way fixed effects," Stata Journal, StataCorp LP, vol. 17(3), pages 517-545, September.
  14. A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017. "Program Evaluation and Causal Inference With High‐Dimensional Data," Econometrica, Econometric Society, vol. 85, pages 233-298, January.
  15. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2017. "Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments," Economics & Human Biology, Elsevier, vol. 25(C), pages 85-98.
  16. Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
  17. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
  18. Chernozhukov, Victor & Fernández-Val, Iván & Hoderlein, Stefan & Holzmann, Hajo & Newey, Whitney, 2015. "Nonparametric identification in panels using quantiles," Journal of Econometrics, Elsevier, vol. 188(2), pages 378-392.
  19. Adam Ashcraft & Iván Fernández‐Val & Kevin Lang, 2013. "The Consequences of Teenage Childbearing: Consistent Estimates When Abortion Makes Miscarriage Non‐random," Economic Journal, Royal Economic Society, vol. 123, pages 875-905, September.
  20. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
  21. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
  22. Iván Fernández‐Val & Joonhwah Lee, 2013. "Panel data models with nonadditive unobserved heterogeneity: Estimation and inference," Quantitative Economics, Econometric Society, vol. 4(3), pages 453-481, November.
  23. Fernández-Val, Iván & Vella, Francis, 2011. "Bias corrections for two-step fixed effects panel data estimators," Journal of Econometrics, Elsevier, vol. 163(2), pages 144-162, August.
  24. Victor Chernozhukov & Iván Fernández-Val, 2011. "Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 559-589.
  25. Victor Chernozhukov & Iván Fernández-Val & Alfred Galichon, 2010. "Rearranging Edgeworth–Cornish–Fisher expansions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 419-435, February.
  26. V. Chernozhukov & I. Fernández-Val & A. Galichon, 2009. "Improving point and interval estimators of monotone functions by rearrangement," Biometrika, Biometrika Trust, vol. 96(3), pages 559-575.
  27. Fernández-Val, Iván, 2009. "Fixed effects estimation of structural parameters and marginal effects in panel probit models," Journal of Econometrics, Elsevier, vol. 150(1), pages 71-85, May.
  28. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
  29. Iván Fernández Val, 2003. "Household labor supply: evidence for Spain," Investigaciones Economicas, Fundación SEPI, vol. 27(2), pages 239-275, May.

Software components

  1. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2020. "QRPROCESS: Stata module for quantile regression: fast algorithm, pointwise and uniform inference," Statistical Software Components S458763, Boston College Department of Economics.
  2. Mario Cruz-Gonzalez & Ivan Fernandez-Val & Martin Weidner, 2016. "LOGITFE: Stata module to compute analytical and jackknife bias corrections for fixed effects estimators of panel logit models with individual and time effects," Statistical Software Components S458278, Boston College Department of Economics, revised 10 Mar 2017.
  3. Mario Cruz-Gonzalez & Ivan Fernandez-Val & Martin Weidner, 2016. "PROBITFE: Stata module to compute analytical and jackknife bias corrections for fixed effects estimators of panel probit models with individual and time effects," Statistical Software Components S458279, Boston College Department of Economics, revised 10 Mar 2017.
  4. Victor Chernozhukov & Ivan Fernandez-Val & Sukjin Han & Amanda Kowalski, 2012. "CQIV: Stata module to perform censored quantile instrumental variables regression," Statistical Software Components S457478, Boston College Department of Economics, revised 25 Sep 2019.

More information

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Statistics

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Rankings

This author is among the top 5% authors according to these criteria:
  1. Average Rank Score
  2. Number of Works
  3. Number of Distinct Works, Weighted by Simple Impact Factor
  4. Number of Distinct Works, Weighted by Recursive Impact Factor
  5. Number of Distinct Works, Weighted by Number of Authors and Simple Impact Factors
  6. Number of Distinct Works, Weighted by Number of Authors and Recursive Impact Factors
  7. Number of Citations
  8. Number of Citations, Discounted by Citation Age
  9. Number of Citations, Weighted by Simple Impact Factor
  10. Number of Citations, Weighted by Simple Impact Factor, Discounted by Citation Age
  11. Number of Citations, Weighted by Recursive Impact Factor
  12. Number of Citations, Weighted by Recursive Impact Factor, Discounted by Citation Age
  13. Number of Citations, Weighted by Number of Authors
  14. Number of Citations, Weighted by Number of Authors, Discounted by Citation Age
  15. Number of Citations, Weighted by Number of Authors and Simple Impact Factors
  16. Number of Citations, Weighted by Number of Authors and Simple Impact Factors, Discounted by Citation Age
  17. Number of Citations, Weighted by Number of Authors and Recursive Impact Factors
  18. Number of Citations, Weighted by Number of Authors and Recursive Impact Factors, Discounted by Citation Age
  19. h-index
  20. Number of Registered Citing Authors
  21. Number of Registered Citing Authors, Weighted by Rank (Max. 1 per Author)
  22. Number of Journal Pages, Weighted by Simple Impact Factor
  23. Number of Journal Pages, Weighted by Recursive Impact Factor
  24. Number of Journal Pages, Weighted by Number of Authors and Simple Impact Factors
  25. Number of Journal Pages, Weighted by Number of Authors and Recursive Impact Factors
  26. Number of Abstract Views in RePEc Services over the past 12 months
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  28. Number of Abstract Views in RePEc Services over the past 12 months, Weighted by Number of Authors
  29. Number of Downloads through RePEc Services over the past 12 months, Weighted by Number of Authors
  30. Euclidian citation score
  31. Breadth of citations across fields
  32. Wu-Index
  33. Record of graduates

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 49 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 (31) 2004-06-10 2004-07-17 2006-10-28 2007-04-14 2007-08-14 2007-08-14 2007-08-14 2007-11-24 2007-11-24 2007-11-24 2008-08-21 2009-04-05 2009-06-10 2009-06-10 2009-08-22 2010-04-17 2010-12-11 2011-04-30 2011-05-07 2011-06-18 2012-01-25 2013-11-29 2013-12-29 2015-08-19 2016-10-02 2017-05-14 2017-11-26 2018-01-08 2018-02-26 2019-02-18 2022-03-21. Author is listed
  2. NEP-DCM: Discrete Choice Models (8) 2006-10-28 2007-08-14 2007-08-14 2018-01-15 2018-01-29 2018-07-23 2019-02-18 2021-03-01. Author is listed
  3. NEP-BIG: Big Data (3) 2018-01-08 2018-07-30 2018-08-20
  4. NEP-EXP: Experimental Economics (3) 2018-01-08 2018-07-30 2018-08-20
  5. NEP-LAB: Labour Economics (3) 2019-02-04 2020-04-13 2022-02-28
  6. NEP-CMP: Computational Economics (2) 2018-07-30 2018-08-20
  7. NEP-LMA: Labor Markets - Supply, Demand, and Wages (2) 2020-04-13 2022-05-16
  8. NEP-NET: Network Economics (2) 2020-01-13 2021-07-19
  9. NEP-BAN: Banking (1) 2022-03-21
  10. NEP-CTA: Contract Theory and Applications (1) 2017-10-22
  11. NEP-ETS: Econometric Time Series (1) 2015-08-13
  12. NEP-GRO: Economic Growth (1) 2020-01-13
  13. NEP-HEA: Health Economics (1) 2013-10-25
  14. NEP-MAC: Macroeconomics (1) 2006-03-18
  15. NEP-MFD: Microfinance (1) 2018-07-30
  16. NEP-ORE: Operations Research (1) 2015-08-13
  17. NEP-SOC: Social Norms and Social Capital (1) 2020-01-13
  18. NEP-UPT: Utility Models and Prospect Theory (1) 2018-01-15

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