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David M. Kaplan

Not to be confused with: David Scott Kaplan

Personal Details

First Name:David
Middle Name:M.
Last Name:Kaplan
Suffix:
RePEc Short-ID:pka649
[This author has chosen not to make the email address public]
https://kaplandm.github.io/
Terminal Degree:2013 Department of Economics; University of California-San Diego (UCSD) (from RePEc Genealogy)

Affiliation

Economics Department
University of Missouri

Columbia, Missouri (United States)
http://economics.missouri.edu/
RePEc:edi:edumous (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software

Working papers

  1. David M. Kaplan & Xin Liu, 2025. "Confidence intervals for intentionally biased estimators," Papers 2502.00450, arXiv.org.
  2. David M. Kaplan & Wei Zhao, 2025. "Comparing latent inequality with ordinal data," Papers 2501.05338, arXiv.org.
  3. David M. Kaplan & Xin Liu, 2024. "Finite-Sample Inference on Auction Bid Distributions Using Transaction Prices," Working Papers 2403, Department of Economics, University of Missouri.
  4. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Papers 2408.13949, arXiv.org.
  5. David M. Kaplan & Qian Wu, 2024. "Ordinal Decomposition," Working Papers 2404, Department of Economics, University of Missouri.
  6. Wei Zhao & David M. Kaplan, 2023. "Conditions for Extrapolating Differences in Consumption to Differences in Welfare," Working Papers 2307, Department of Economics, University of Missouri.
  7. David M. Kaplan & Qian Wu, 2023. "Multiple Testing of Ordinal Stochastic Monotonicity," Working Papers 2313, Department of Economics, University of Missouri.
  8. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
  9. David M. Kaplan, 2021. "Distcomp: Comparing distributions," Papers 2110.02327, arXiv.org.
  10. David M. Kaplan & Xin Liu, 2021. "k-Class Instrumental Variables Quantile Regression," Working Papers 2104, Department of Economics, University of Missouri.
  11. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
  12. David M. Kaplan, 2020. "Assessing Policy Effects with Unconditional Quantile Regression," Working Papers 2011, Department of Economics, University of Missouri.
  13. David M. Kaplan, 2020. "Interpreting Unconditional Quantile Regression with Conditional Independence," Papers 2010.03606, arXiv.org, revised Oct 2021.
  14. David M. Kaplan & Lonnie Hofmann, 2019. "High-order coverage of smoothed Bayesian bootstrap intervals for population quantiles," Working Papers 1914, Department of Economics, University of Missouri, revised 19 Sep 2020.
  15. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
  16. Matt Goldman & David M. Kaplan, 2017. "Comparing distributions by multiple testing across quantiles or CDF values," Papers 1708.04658, arXiv.org.
  17. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
  18. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
  19. Matt Goldman & David M. Kaplan, 2016. "Fractional order statistic approximation for nonparametric conditional quantile inference," Papers 1609.09035, arXiv.org.
  20. David M. Kaplan & Longhao Zhuo, 2016. "Frequentist properties of Bayesian inequality tests," Papers 1607.00393, arXiv.org, revised Jul 2024.
  21. David M. Kaplan & Yixiao Sun, 2016. "Smoothed estimating equations for instrumental variables quantile regression," Papers 1609.09033, arXiv.org.
  22. David M. Kaplan & Matt Goldman, 2015. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1503, Department of Economics, University of Missouri.
  23. David M. Kaplan, 2015. "Bayesian and frequentist tests of sign equality and other nonlinear inequalities," Working Papers 1516, Department of Economics, University of Missouri.
  24. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
  25. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
  26. David M. Kaplan, 2013. "IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1316, Department of Economics, University of Missouri.
  27. David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 1319, Department of Economics, University of Missouri, revised Feb 2018.
  28. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
  29. Sun, Yixiao & Kaplan, David M., 2011. "A New Asymptotic Theory for Vector Autoregressive Long-run Variance Estimation and Autocorrelation Robust Testing," University of California at San Diego, Economics Working Paper Series qt8cx0t4gc, Department of Economics, UC San Diego.

Articles

  1. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
  2. David M. Kaplan & Xin Liu, 2024. "Confidence intervals for intentionally biased estimators," Econometric Reviews, Taylor & Francis Journals, vol. 43(2-4), pages 197-214, April.
  3. Wei Zhao & David M. Kaplan, 2024. "Conditions for extrapolating differences in consumption to differences in welfare," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 1090-1104, July.
  4. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
  5. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
  6. David M. Kaplan, 2022. "Smoothed instrumental variables quantile regression," Stata Journal, StataCorp LLC, vol. 22(2), pages 379-403, June.
  7. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
  8. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
  9. David M. Kaplan, 2019. "distcomp: Comparing distributions," Stata Journal, StataCorp LLC, vol. 19(4), pages 832-848, December.
  10. Goldman, Matt & Kaplan, David M., 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
  11. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
  12. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
  13. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
  14. Kaplan, David M., 2015. "Improved quantile inference via fixed-smoothing asymptotics and Edgeworth expansion," Journal of Econometrics, Elsevier, vol. 185(1), pages 20-32.

Software components

  1. David M. Kaplan, 2021. "DISTCOMP: Stata module to compare distributions," Statistical Software Components S459001, Boston College Department of Economics.
  2. David M. Kaplan, 2021. "SIVQR: Stata module to perform smoothed IV quantile regression," Statistical Software Components S459002, Boston College Department of Economics, revised 14 Mar 2023.

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. David M. Kaplan & Wei Zhao, 2025. "Comparing latent inequality with ordinal data," Papers 2501.05338, arXiv.org.

    Cited by:

    1. Stephen P. Jenkins, 2020. "Comparing distributions of ordinal data," Stata Journal, StataCorp LLC, vol. 20(3), pages 505-531, September.
    2. Arthur Grimes & Stephen P. Jenkins & Florencia Tranquilli, 2023. "The Relationship Between Subjective Wellbeing and Subjective Wellbeing Inequality: An Important Role for Skewness," Journal of Happiness Studies, Springer, vol. 24(1), pages 309-330, January.
    3. Andrew Chesher & Adam Rosen & Zahra Siddique, 2019. "Estimating Endogenous Effects on Ordinal Outcomes," CeMMAP working papers CWP66/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Grimes, Arthur & Jenkins, Stephen P. & Tranquilli, Florencia, 2020. "The Relationship between Subjective Wellbeing and Subjective Wellbeing Inequality: Taking Ordinality and Skewness Seriously," IZA Discussion Papers 13692, Institute of Labor Economics (IZA).
    5. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    6. Shuo Liu & Nick Netzer, 2023. "Happy Times: Measuring Happiness Using Response Times," CESifo Working Paper Series 10360, CESifo.
    7. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.

  2. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Papers 2408.13949, arXiv.org.

    Cited by:

    1. Wei Zhao & David M. Kaplan, 2023. "Conditions for Extrapolating Differences in Consumption to Differences in Welfare," Working Papers 2307, Department of Economics, University of Missouri.

  3. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.

    Cited by:

    1. Sultanuzzaman, Md Reza & Yahya, Farzan & Lee, Chien-Chiang, 2024. "Exploring the complex interplay of green finance, business cycles, and energy development," Energy, Elsevier, vol. 306(C).
    2. Afi Florence Akakpo & Koffi Sodokin & Mawuli Kodjovi Couchoro, 2025. "Social capital, gender‐based resilience, and well‐being among urban and rural households in Togo," Journal of International Development, John Wiley & Sons, Ltd., vol. 37(1), pages 251-299, January.
    3. Andriy Tsapin & Oleksandr Faryna, 2024. "The Role of Financial Literacy in Anchoring Inflation Expectations: The Case of Ukraine," Working Papers 02/2024, National Bank of Ukraine.
    4. Dooyeon Cho & Seunghwa Rho, 2024. "Reassessing growth vulnerability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 225-234, January.
    5. Chien-Chiang Lee & Farzan Yahya & Md Reza Sultanuzzaman, 2024. "Monetary Policy Uncertainty And Agricultural Climate Risk: Does The Agricultural Kuznets Curve Exist?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(4), pages 631-654, December.
    6. Vardges Hovhannisyan & Vahé Heboyan & Magdana Kondaridze, 2024. "An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach," Empirical Economics, Springer, vol. 67(2), pages 465-493, August.
    7. Idrissa Ouedraogo & Issa Dianda & Pegdwende Patrik Roland Ouedraogo & Tiraogo Rodrigue Ouedraogo & Bassirou Konfe, 2025. "The Effects of Taxation on Income Inequality in Sub-Saharan Africa," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 67(1), pages 84-149, March.
    8. Sodokin, Koffi & Djafon, Joseph Kokouvi & Dandonougbo, Yevessé & Akakpo, Afi & Couchoro, Mawuli K. & Agbodji, Akoété Ega, 2023. "Technological change, completeness of financing microstructures, and impact on well-being and income inequality," Telecommunications Policy, Elsevier, vol. 47(6).
    9. Yahya, Farzan & Lee, Chien-Chiang, 2023. "Disentangling the asymmetric effect of financialization on the green output gap," Energy Economics, Elsevier, vol. 125(C).
    10. Bakouan, Pousseni & Sawadogo, Relwendé, 2024. "BioTrade and income inequality: Does frontier technology readiness matter?," Structural Change and Economic Dynamics, Elsevier, vol. 70(C), pages 650-665.
    11. Jinglin Feng & Linlin Fan & Edward C. Jaenicke, 2024. "The distributional impact of SNAP on dietary quality," Agricultural Economics, International Association of Agricultural Economists, vol. 55(1), pages 104-139, January.
    12. Alishba Hania & Chien-Chiang Lee & Farzan Yahya, 2025. "Climate anxiety, economic policy uncertainty, and green growth," Economic Change and Restructuring, Springer, vol. 58(1), pages 1-34, February.

  4. David M. Kaplan, 2021. "Distcomp: Comparing distributions," Papers 2110.02327, arXiv.org.

    Cited by:

    1. Barbara Boelmann, 2024. "Women's Missing Mobility and the Gender Gap in Higher Education: Evidence from Germany's University Expansion," CRC TR 224 Discussion Paper Series crctr224_2024_518, University of Bonn and University of Mannheim, Germany.
    2. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
    3. Wellhausen, Rachel L, 2023. "Waste Not, Want Not: Tariffs as Environmental Protection," Institute on Global Conflict and Cooperation, Working Paper Series qt40m4179x, Institute on Global Conflict and Cooperation, University of California.
    4. Ayllón, Sara, 2021. "Online Teaching and Gender Bias," IZA Discussion Papers 14787, Institute of Labor Economics (IZA).
    5. Getahun, Tigabu D. & Fetene, Gebeyehu M. & Baumüller, Heike & Kubik, Zaneta, 2024. "Gender gaps in wages and nonmonetary benefits: Evidence from Ethiopia’s manufacturing sector," Discussion Papers 344126, University of Bonn, Center for Development Research (ZEF).
    6. Millemaci, Emanuele & Monteforte, Fabio & Temple, Jonathan R. W., 2023. "Have autocrats governed for the long term?," SocArXiv w8khb, Center for Open Science.
    7. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2017. "Talent, Career Choice and Competition: The Gender Wage Gap at the Top," Working Paper Series 1169, Research Institute of Industrial Economics, revised 06 Mar 2023.
    8. Getahun, Tigabu D. & Fetene, Gebeyehu M. & Baumüller, Heike & Kubik, Zaneta, 2024. "Exploring the relationship between job quality and firm productivity in the manufacturing sector: Panel data evidence from Ethiopia," Discussion Papers 344125, University of Bonn, Center for Development Research (ZEF).
    9. Fetene, Gebeyehu Manie & Balew, Solomon & Abro, Zewdu & Kassie, Menale & Tefera, Tadele, 2021. "Push-Pull Technology As a Climate-Smart Integrated Pest Management Strategy in Southern Ethiopia," 2021 Conference, August 17-31, 2021, Virtual 315246, International Association of Agricultural Economists.
    10. Zewdu Abro & Gebeyehu Manie Fetene & Menale Kassie & Tigist Mekonnen Melesse, 2023. "Socioeconomic burden of trypanosomiasis: Evidence from crop and livestock production in Ethiopia," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 785-799, September.
    11. Barbara Boelmann, 2024. "Women’s Missing Mobility and the Gender Gap in Higher Education: Evidence from Germany’s University Expansion," ECONtribute Discussion Papers Series 280, University of Bonn and University of Cologne, Germany.
    12. Stefano Boscolo, 2019. "Quantifying the Redistributive Effect of the Erosion of the Italian Personal Income Tax Base: A Microsimulation Exercise," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2019(2), pages 39-80.

  5. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.

    Cited by:

    1. Federico Favata & Sofia Zamparo, 2021. "Estimación del efecto de la segregación ocupacional por sexo en el ingreso laboral para Argentina (2016-2020)," Asociación Argentina de Economía Política: Working Papers 4467, Asociación Argentina de Economía Política.
    2. Vardges Hovhannisyan & Vahé Heboyan & Magdana Kondaridze, 2024. "An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach," Empirical Economics, Springer, vol. 67(2), pages 465-493, August.
    3. Feito-Ruiz, Isabel & Menéndez-Requejo, Susana, 2022. "Debt maturity in family firms: Heterogeneity across countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    4. Alfonso Rosolia, 2021. "Does information about current inflation affect expectations and decisions? Another look at Italian firms," Temi di discussione (Economic working papers) 1353, Bank of Italy, Economic Research and International Relations Area.

  6. David M. Kaplan, 2020. "Assessing Policy Effects with Unconditional Quantile Regression," Working Papers 2011, Department of Economics, University of Missouri.

    Cited by:

    1. Julian Martinez-Iriarte & Yixiao Sun, 2020. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: An Unconditional MTE Approach," Papers 2010.15864, arXiv.org, revised Aug 2024.
    2. Martínez-Iriarte, Julian & Sun, Yixiao, 2021. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: an Unconditional MTE Approach," University of California at San Diego, Economics Working Paper Series qt2bc57830, Department of Economics, UC San Diego.

  7. David M. Kaplan, 2020. "Interpreting Unconditional Quantile Regression with Conditional Independence," Papers 2010.03606, arXiv.org, revised Oct 2021.

    Cited by:

    1. Julian Martinez-Iriarte & Yixiao Sun, 2020. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: An Unconditional MTE Approach," Papers 2010.15864, arXiv.org, revised Aug 2024.
    2. Martínez-Iriarte, Julian & Sun, Yixiao, 2021. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: an Unconditional MTE Approach," University of California at San Diego, Economics Working Paper Series qt2bc57830, Department of Economics, UC San Diego.

  8. Matt Goldman & David M. Kaplan, 2017. "Comparing distributions by multiple testing across quantiles or CDF values," Papers 1708.04658, arXiv.org.

    Cited by:

    1. David M. Kaplan, 2019. "distcomp: Comparing distributions," Working Papers 1908, Department of Economics, University of Missouri.
    2. Caetano, Carolina & Caetano, Gregorio & Nielsen, Eric, 2024. "Are children spending too much time on enrichment activities?," Economics of Education Review, Elsevier, vol. 98(C).
    3. Gay, Victor, 2023. "Culture: An Empirical Investigation of Beliefs, Work, and Fertility – A Verification and Reproduction of Fernández and Fogli (2009)," I4R Discussion Paper Series 91, The Institute for Replication (I4R).
    4. Wei Zhao & David M. Kaplan, 2023. "Conditions for Extrapolating Differences in Consumption to Differences in Welfare," Working Papers 2307, Department of Economics, University of Missouri.
    5. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
    6. John Mullahy, 2020. "Discovering Treatment Effectiveness via Median Treatment Effects—Applications to COVID-19 Clinical Trials," NBER Working Papers 27895, National Bureau of Economic Research, Inc.
    7. Comin, Diego & Cirera, Xavi & Cruz, Marcio & Lee, Kyung Min, 2020. "Anatomy of Technology in the Firm," CEPR Discussion Papers 15427, C.E.P.R. Discussion Papers.
    8. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    9. Gedikli, Cigdem & Popli, Gurleen & Yilmaz, Okan, 2023. "The impact of intimate partner violence on women’s labour market outcomes," World Development, Elsevier, vol. 164(C).
    10. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    11. Benjamin Blemings & Brad Humphreys, 2024. "Public Financing of Professional Sports Facilities and Drug Asset Forfeiture," Public Finance Review, , vol. 52(4), pages 439-465, July.
    12. Dennis Wesselbaum, 2023. "Understanding the Drivers of the Gender Productivity Gap in the Economics Profession," The American Economist, Sage Publications, vol. 68(1), pages 61-73, March.
    13. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.
    14. Millemaci, Emanuele & Monteforte, Fabio & Temple, Jonathan R. W., 2023. "Have autocrats governed for the long term?," SocArXiv w8khb, Center for Open Science.
    15. Wang, Duoyu & Cleary, Rebecca, 2024. "The Effect of SNAP on Black Households' Nutritional Quality of Food Purchases," 2024 Annual Meeting, July 28-30, New Orleans, LA 343960, Agricultural and Applied Economics Association.
    16. Fasianos, Apostolos & Evgenidis, Anastasios, 2020. "Unconventional Monetary Policy and Wealth Inequalities in Great Britain," CEPR Discussion Papers 14656, C.E.P.R. Discussion Papers.
    17. Melo, Grace & Palma, Marco A. & Ribera, Luis A., 2024. "Are experts overoptimistic about the success of food market labeling information?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343870, Agricultural and Applied Economics Association.
    18. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2017. "Talent, Career Choice and Competition: The Gender Wage Gap at the Top," Working Paper Series 1169, Research Institute of Industrial Economics, revised 06 Mar 2023.
    19. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    20. Kochhar,Nishtha & Knippenberg,Erwin Willem Yvonnick Leon, 2023. "Droughts and Welfare in Afghanistan," Policy Research Working Paper Series 10272, The World Bank.
    21. Wossen, Tesfamicheal & Spielman, David J. & Alene, Arega D. & Abdoulaye, Tahirou, 2024. "Estimating seed demand in the presence of market frictions: Evidence from an auction experiment in Nigeria," Journal of Development Economics, Elsevier, vol. 167(C).
    22. Cirera,Xavier & Comin,Diego Adolfo & Vargas Da Cruz,Marcio Jose & Lee,Kyungmin, 2020. "Technology Within and Across Firms," Policy Research Working Paper Series 9476, The World Bank.
    23. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    24. Huang, Wei & Li, Teng & Pan, Yinghao & Ren, Jinyang, 2021. "Teacher Characteristics and Student Performance: Evidence from Random Teacher-Student Assignments in China," IZA Discussion Papers 14184, Institute of Labor Economics (IZA).
    25. Klenio Barbosa & Dakshina De Silva & Liyu Yang & Hisayuki Yoshimoto, 2020. "Bond Losses and Systemic Risk," Working Papers 288072615, Lancaster University Management School, Economics Department.
    26. Jaime Ramirez-Cuellar, 2023. "Testing for idiosyncratic Treatment Effect Heterogeneity," Papers 2304.01141, arXiv.org.
    27. Martin DeLuca & Roberto Pinheiro, 2023. "US Labor Market after COVID-19: An Interim Report," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(04), pages 1-7, February.
    28. John Mullahy, 2021. "Discovering treatment effectiveness via median treatment effects—Applications to COVID‐19 clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1050-1069, May.
    29. S. S. Swathysree & Manisha Chakrabarty & Debopriti Bhattacharya, 2023. "Getting Real in the Real Consumption Expenditure: A Case of Rural India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(4), pages 817-846, December.
    30. Gay, Victor, 2023. "Culture: An Empirical Investigation of Beliefs, Work, and Fertility. A Verification and Reproduction of Fernández and Fogli (American Economic Journal: Macroeconomics, 2009)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 2, pages 1-15.
    31. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.

  9. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    3. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    4. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(5), pages 123-128, August.
    5. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Feb 2025.
    6. Fusejima, Koki, 2024. "Identification of multi-valued treatment effects with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    7. Di Liu, 2024. "Instrumental-variables quantile regression," French Stata Users' Group Meetings 2024 07, Stata Users Group.
    8. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    9. Mingquan Wang & Xiaohua Ma & Xinrui Wang & Jun Wang & Xiuqing Zhou & Qibing Gao, 2025. "Smoothing Estimation of Parameters in Censored Quantile Linear Regression Model," Mathematics, MDPI, vol. 13(2), pages 1-28, January.
    10. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Di Liu, 2024. "Instrumental variables quantile regression," Chinese Stata Conference 2023 07, Stata Users Group.
    12. Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
    13. Man Fung Leung & Kin Wai Chan & Xiaofeng Shao, 2025. "Online Generalized Method of Moments for Time Series," Papers 2502.00751, arXiv.org.
    14. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    15. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    16. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    17. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    18. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    19. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    20. de Castro, Luciano I. & Galvao, Antonio F. & Nunes, Daniel da Siva, 2025. "Dynamic economics with quantile preferences," Theoretical Economics, Econometric Society, vol. 20(1), January.
    21. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  10. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    3. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    4. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(5), pages 123-128, August.
    5. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Feb 2025.
    6. Fusejima, Koki, 2024. "Identification of multi-valued treatment effects with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    7. Di Liu, 2024. "Instrumental-variables quantile regression," French Stata Users' Group Meetings 2024 07, Stata Users Group.
    8. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    9. Mingquan Wang & Xiaohua Ma & Xinrui Wang & Jun Wang & Xiuqing Zhou & Qibing Gao, 2025. "Smoothing Estimation of Parameters in Censored Quantile Linear Regression Model," Mathematics, MDPI, vol. 13(2), pages 1-28, January.
    10. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Di Liu, 2024. "Instrumental variables quantile regression," Chinese Stata Conference 2023 07, Stata Users Group.
    12. Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
    13. Man Fung Leung & Kin Wai Chan & Xiaofeng Shao, 2025. "Online Generalized Method of Moments for Time Series," Papers 2502.00751, arXiv.org.
    14. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    15. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    16. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    17. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    18. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    19. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    20. de Castro, Luciano I. & Galvao, Antonio F. & Nunes, Daniel da Siva, 2025. "Dynamic economics with quantile preferences," Theoretical Economics, Econometric Society, vol. 20(1), January.
    21. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  11. Matt Goldman & David M. Kaplan, 2016. "Fractional order statistic approximation for nonparametric conditional quantile inference," Papers 1609.09035, arXiv.org.

    Cited by:

    1. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    2. David M. Kaplan & Lonnie Hofmann, 2019. "High-order coverage of smoothed Bayesian bootstrap intervals for population quantiles," Working Papers 1914, Department of Economics, University of Missouri, revised 19 Sep 2020.
    3. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    4. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    5. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    6. Chaitra H. Nagaraja & Haikady N. Nagaraja, 2020. "Distribution‐free Approximate Methods for Constructing Confidence Intervals for Quantiles," International Statistical Review, International Statistical Institute, vol. 88(1), pages 75-100, April.
    7. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
    8. Alan Hutson, 2018. "Comment on “What Do Interpolated Nonparametric Confidence Intervals for Population Quantiles Guarantee?”, Frey and Zhang (2017)," The American Statistician, Taylor & Francis Journals, vol. 72(3), pages 302-302, July.

  12. David M. Kaplan & Longhao Zhuo, 2016. "Frequentist properties of Bayesian inequality tests," Papers 1607.00393, arXiv.org, revised Jul 2024.

    Cited by:

    1. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    2. David M. Kaplan & Wei Zhao, 2025. "Comparing latent inequality with ordinal data," Papers 2501.05338, arXiv.org.
    3. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    4. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.

  13. David M. Kaplan & Yixiao Sun, 2016. "Smoothed estimating equations for instrumental variables quantile regression," Papers 1609.09033, arXiv.org.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    3. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    4. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    5. Afi Florence Akakpo & Koffi Sodokin & Mawuli Kodjovi Couchoro, 2025. "Social capital, gender‐based resilience, and well‐being among urban and rural households in Togo," Journal of International Development, John Wiley & Sons, Ltd., vol. 37(1), pages 251-299, January.
    6. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    7. Fengrui Di & Lei Wang, 2022. "Multi-round smoothed composite quantile regression for distributed data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 869-893, October.
    8. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Feb 2025.
    10. David M. Kaplan & Xin Liu, 2023. "Confidence Intervals for Intentionally Biased Estimators," Working Papers 2308, Department of Economics, University of Missouri.
    11. Kaspar W thrich, 2014. "A Comparison of two Quantile Models with Endogeneity," Diskussionsschriften dp1408, Universitaet Bern, Departement Volkswirtschaft.
    12. Dooyeon Cho & Seunghwa Rho, 2024. "Reassessing growth vulnerability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 225-234, January.
    13. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
    14. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
    15. Federico Favata & Sofia Zamparo, 2021. "Estimación del efecto de la segregación ocupacional por sexo en el ingreso laboral para Argentina (2016-2020)," Asociación Argentina de Economía Política: Working Papers 4467, Asociación Argentina de Economía Política.
    16. Di Liu, 2024. "Instrumental-variables quantile regression," French Stata Users' Group Meetings 2024 07, Stata Users Group.
    17. Marcelo Fernandes & Emmanuel Guerre & Eduardo Horta, 2021. "Smoothing Quantile Regressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 338-357, January.
    18. David M. Kaplan & Xin Liu, 2024. "k-Class instrumental variables quantile regression," Empirical Economics, Springer, vol. 67(1), pages 111-141, July.
    19. Tae-Hwy Lee & Aman Ullah & He Wang, 2024. "The second-order bias and mean squared error of quantile regression estimators," Indian Economic Review, Springer, vol. 59(1), pages 11-68, October.
    20. Santiago Acerenza & Vitor Possebom & Pedro H. C. Sant'Anna, 2023. "Was Javert right to be suspicious? Marginal Treatment Effects with Duration Outcomes," Papers 2311.13969, arXiv.org, revised Apr 2025.
    21. Vardges Hovhannisyan & Vahé Heboyan & Magdana Kondaridze, 2024. "An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach," Empirical Economics, Springer, vol. 67(2), pages 465-493, August.
    22. Byunghoon Kang & Seojeong Lee & Juha Song, 2025. "Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification," Papers 2501.09540, arXiv.org.
    23. Idrissa Ouedraogo & Issa Dianda & Pegdwende Patrik Roland Ouedraogo & Tiraogo Rodrigue Ouedraogo & Bassirou Konfe, 2025. "The Effects of Taxation on Income Inequality in Sub-Saharan Africa," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 67(1), pages 84-149, March.
    24. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Di Liu, 2024. "Instrumental variables quantile regression," Chinese Stata Conference 2023 07, Stata Users Group.
    26. Jean-Jacques Forneron, 2023. "Noisy, Non-Smooth, Non-Convex Estimation of Moment Condition Models," Papers 2301.07196, arXiv.org, revised Feb 2023.
    27. Sodokin, Koffi & Djafon, Joseph Kokouvi & Dandonougbo, Yevessé & Akakpo, Afi & Couchoro, Mawuli K. & Agbodji, Akoété Ega, 2023. "Technological change, completeness of financing microstructures, and impact on well-being and income inequality," Telecommunications Policy, Elsevier, vol. 47(6).
    28. Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
    29. Bruins, Marianne & Duffy, James A. & Keane, Michael P. & Smith, Anthony A., 2018. "Generalized indirect inference for discrete choice models," Journal of Econometrics, Elsevier, vol. 205(1), pages 177-203.
    30. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    31. Antonio Francesco Gravina & Neil Foster-McGregor, 2024. "Unraveling wage inequality: tangible and intangible assets, globalization and labor market regulations," Empirical Economics, Springer, vol. 67(4), pages 1375-1420, October.
    32. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    33. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    34. Yinchu Zhu, 2018. "Learning non-smooth models: instrumental variable quantile regressions and related problems," Papers 1805.06855, arXiv.org, revised Sep 2019.
    35. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    36. Wenjie Wang & Yichong Zhang, 2024. "Gradient Wild Bootstrap for Instrumental Variable Quantile Regressions with Weak and Few Clusters," Papers 2408.10686, arXiv.org.
    37. Bakouan, Pousseni & Sawadogo, Relwendé, 2024. "BioTrade and income inequality: Does frontier technology readiness matter?," Structural Change and Economic Dynamics, Elsevier, vol. 70(C), pages 650-665.
    38. Lorenzo Tedesco & Jad Beyhum & Ingrid Van Keilegom, 2023. "Instrumental variable estimation of the proportional hazards model by presmoothing," Papers 2309.02183, arXiv.org.
    39. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
    40. Idrissa Ouedraogo & Issa Dianda & Pegdwende Patrik Ouedraogo & Rodrigue Tiraogo Ouedraogo & Bassirou Konfe, 2022. "The effects of taxation on income inequality in sub-Saharan Africa," WIDER Working Paper Series wp-2022-129, World Institute for Development Economic Research (UNU-WIDER).
    41. Dieudonné Mignamissi & Eric Xaverie Possi Tebeng & Arnold Dilane Momou Tchinda, 2024. "Does trade openness increase CO2 emissions in Africa? A revaluation using the composite index of Squalli and Wilson," Environment Systems and Decisions, Springer, vol. 44(3), pages 645-673, September.
    42. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    43. 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.
    44. de Castro, Luciano & Cundy, Lance D. & Galvao, Antonio F. & Westenberger, Rafael, 2023. "A dynamic quantile model for distinguishing intertemporal substitution from risk aversion," European Economic Review, Elsevier, vol. 159(C).
    45. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    46. Machado, José A.F. & Santos Silva, J.M.C., 2019. "Quantiles via moments," Journal of Econometrics, Elsevier, vol. 213(1), pages 145-173.
    47. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    48. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    49. Armstrong, Christopher S. & Blouin, Jennifer L. & Jagolinzer, Alan D. & Larcker, David F., 2015. "Corporate governance, incentives, and tax avoidance," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 1-17.
    50. Tae-Hwy Lee & Aman Ullah & He Wang, 2023. "The Second-order Bias and Mean Squared Error of Quantile Regression Estimators," Working Papers 202313, University of California at Riverside, Department of Economics.
    51. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    52. Borgen, Nicolai T. & Haupt, Andreas & Wiborg, Øyvind N., 2021. "Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands," SocArXiv 4vquh, Center for Open Science.
    53. Rios-Avila, Fernando & Siles, Leonardo & Canavire Bacarreza, Gustavo J., 2024. "Estimating Quantile Regressions with Multiple Fixed Effects through Method of Moments," IZA Discussion Papers 17262, Institute of Labor Economics (IZA).
    54. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
    55. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.

  14. David M. Kaplan & Matt Goldman, 2015. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1503, Department of Economics, University of Missouri.

    Cited by:

    1. Mototsugu Fukushige & Yingxin Shi, 2022. "Quantile regression approach for measuring production inefficiency with empirical application to the primary production sector for the Xinjiang Production and Construction Corps in China," Asia-Pacific Journal of Regional Science, Springer, vol. 6(2), pages 777-805, June.
    2. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    3. David M. Kaplan & Lonnie Hofmann, 2019. "High-order coverage of smoothed Bayesian bootstrap intervals for population quantiles," Working Papers 1914, Department of Economics, University of Missouri, revised 19 Sep 2020.
    4. Cui-Juan Kong & Han-Ying Liang, 2024. "Quantile difference estimation with censoring indicators missing at random," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(2), pages 345-382, April.
    5. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    6. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
    7. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.

  15. David M. Kaplan, 2015. "Bayesian and frequentist tests of sign equality and other nonlinear inequalities," Working Papers 1516, Department of Economics, University of Missouri.

    Cited by:

    1. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    2. David M. Kaplan & Wei Zhao, 2025. "Comparing latent inequality with ordinal data," Papers 2501.05338, arXiv.org.
    3. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    4. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.

  16. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.

    Cited by:

    1. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    2. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    3. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.

  17. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.

    Cited by:

    1. David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
    2. 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.
    3. David M. Kaplan, 2013. "IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1316, Department of Economics, University of Missouri.
    4. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.

  18. David M. Kaplan, 2013. "IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1316, Department of Economics, University of Missouri.

    Cited by:

    1. 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.

  19. David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 1319, Department of Economics, University of Missouri, revised Feb 2018.

    Cited by:

    1. David M. Kaplan, 2019. "distcomp: Comparing distributions," Working Papers 1908, Department of Economics, University of Missouri.
    2. Caetano, Carolina & Caetano, Gregorio & Nielsen, Eric, 2024. "Are children spending too much time on enrichment activities?," Economics of Education Review, Elsevier, vol. 98(C).
    3. Gay, Victor, 2023. "Culture: An Empirical Investigation of Beliefs, Work, and Fertility – A Verification and Reproduction of Fernández and Fogli (2009)," I4R Discussion Paper Series 91, The Institute for Replication (I4R).
    4. Wei Zhao & David M. Kaplan, 2023. "Conditions for Extrapolating Differences in Consumption to Differences in Welfare," Working Papers 2307, Department of Economics, University of Missouri.
    5. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
    6. John Mullahy, 2020. "Discovering Treatment Effectiveness via Median Treatment Effects—Applications to COVID-19 Clinical Trials," NBER Working Papers 27895, National Bureau of Economic Research, Inc.
    7. Comin, Diego & Cirera, Xavi & Cruz, Marcio & Lee, Kyung Min, 2020. "Anatomy of Technology in the Firm," CEPR Discussion Papers 15427, C.E.P.R. Discussion Papers.
    8. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    9. Gedikli, Cigdem & Popli, Gurleen & Yilmaz, Okan, 2023. "The impact of intimate partner violence on women’s labour market outcomes," World Development, Elsevier, vol. 164(C).
    10. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    11. Benjamin Blemings & Brad Humphreys, 2024. "Public Financing of Professional Sports Facilities and Drug Asset Forfeiture," Public Finance Review, , vol. 52(4), pages 439-465, July.
    12. Dennis Wesselbaum, 2023. "Understanding the Drivers of the Gender Productivity Gap in the Economics Profession," The American Economist, Sage Publications, vol. 68(1), pages 61-73, March.
    13. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.
    14. Millemaci, Emanuele & Monteforte, Fabio & Temple, Jonathan R. W., 2023. "Have autocrats governed for the long term?," SocArXiv w8khb, Center for Open Science.
    15. Wang, Duoyu & Cleary, Rebecca, 2024. "The Effect of SNAP on Black Households' Nutritional Quality of Food Purchases," 2024 Annual Meeting, July 28-30, New Orleans, LA 343960, Agricultural and Applied Economics Association.
    16. Fasianos, Apostolos & Evgenidis, Anastasios, 2020. "Unconventional Monetary Policy and Wealth Inequalities in Great Britain," CEPR Discussion Papers 14656, C.E.P.R. Discussion Papers.
    17. Melo, Grace & Palma, Marco A. & Ribera, Luis A., 2024. "Are experts overoptimistic about the success of food market labeling information?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343870, Agricultural and Applied Economics Association.
    18. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2017. "Talent, Career Choice and Competition: The Gender Wage Gap at the Top," Working Paper Series 1169, Research Institute of Industrial Economics, revised 06 Mar 2023.
    19. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    20. Kochhar,Nishtha & Knippenberg,Erwin Willem Yvonnick Leon, 2023. "Droughts and Welfare in Afghanistan," Policy Research Working Paper Series 10272, The World Bank.
    21. Wossen, Tesfamicheal & Spielman, David J. & Alene, Arega D. & Abdoulaye, Tahirou, 2024. "Estimating seed demand in the presence of market frictions: Evidence from an auction experiment in Nigeria," Journal of Development Economics, Elsevier, vol. 167(C).
    22. Cirera,Xavier & Comin,Diego Adolfo & Vargas Da Cruz,Marcio Jose & Lee,Kyungmin, 2020. "Technology Within and Across Firms," Policy Research Working Paper Series 9476, The World Bank.
    23. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    24. Huang, Wei & Li, Teng & Pan, Yinghao & Ren, Jinyang, 2021. "Teacher Characteristics and Student Performance: Evidence from Random Teacher-Student Assignments in China," IZA Discussion Papers 14184, Institute of Labor Economics (IZA).
    25. Klenio Barbosa & Dakshina De Silva & Liyu Yang & Hisayuki Yoshimoto, 2020. "Bond Losses and Systemic Risk," Working Papers 288072615, Lancaster University Management School, Economics Department.
    26. Jaime Ramirez-Cuellar, 2023. "Testing for idiosyncratic Treatment Effect Heterogeneity," Papers 2304.01141, arXiv.org.
    27. Martin DeLuca & Roberto Pinheiro, 2023. "US Labor Market after COVID-19: An Interim Report," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(04), pages 1-7, February.
    28. John Mullahy, 2021. "Discovering treatment effectiveness via median treatment effects—Applications to COVID‐19 clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1050-1069, May.
    29. S. S. Swathysree & Manisha Chakrabarty & Debopriti Bhattacharya, 2023. "Getting Real in the Real Consumption Expenditure: A Case of Rural India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(4), pages 817-846, December.
    30. Gay, Victor, 2023. "Culture: An Empirical Investigation of Beliefs, Work, and Fertility. A Verification and Reproduction of Fernández and Fogli (American Economic Journal: Macroeconomics, 2009)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 2, pages 1-15.
    31. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.

  20. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.

    Cited by:

    1. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    2. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "A robust confidence interval of historical Value-at-Risk for small sample," Documents de travail du Centre d'Economie de la Sorbonne 16034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    4. Chaitra H. Nagaraja & Haikady N. Nagaraja, 2020. "Distribution‐free Approximate Methods for Constructing Confidence Intervals for Quantiles," International Statistical Review, International Statistical Institute, vol. 88(1), pages 75-100, April.
    5. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.
    6. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    7. Dominique Guegan & Bertrand Hassani & Kehan Li, 2017. "Measuring risks in the extreme tail: The extreme VaR and its confidence interval," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317391, HAL.
    8. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2016. "Capturing the intrinsic uncertainty of the VaR: Spectrum representation of a saddlepoint approximation for an estimator of the VaR," Documents de travail du Centre d'Economie de la Sorbonne 16034r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.

  21. Sun, Yixiao & Kaplan, David M., 2011. "A New Asymptotic Theory for Vector Autoregressive Long-run Variance Estimation and Autocorrelation Robust Testing," University of California at San Diego, Economics Working Paper Series qt8cx0t4gc, Department of Economics, UC San Diego.

    Cited by:

    1. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
    2. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    3. David M. Kaplan, 2013. "Improved Quantile Inference Via Fixed-Smoothing Asymptotics And Edgeworth Expansion," Working Papers 1313, Department of Economics, University of Missouri.
    4. Yang, Jingjing & Vogelsang, Timothy J., 2018. "Finite sample performance of a long run variance estimator based on exactly (almost) unbiased autocovariance estimators," Economics Letters, Elsevier, vol. 165(C), pages 21-27.

Articles

  1. David M. Kaplan, 2024. "Inference on Consensus Ranking of Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 839-850, July.
    See citations under working paper version above.
  2. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
    See citations under working paper version above.
  3. David M. Kaplan, 2022. "Smoothed instrumental variables quantile regression," Stata Journal, StataCorp LLC, vol. 22(2), pages 379-403, June.
    See citations under working paper version above.
  4. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    See citations under working paper version above.
  5. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    See citations under working paper version above.
  6. David M. Kaplan, 2019. "distcomp: Comparing distributions," Stata Journal, StataCorp LLC, vol. 19(4), pages 832-848, December.
    See citations under working paper version above.
  7. Goldman, Matt & Kaplan, David M., 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
    See citations under working paper version above.
  8. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    See citations under working paper version above.
  9. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    See citations under working paper version above.
  10. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
    See citations under working paper version above.
  11. Kaplan, David M., 2015. "Improved quantile inference via fixed-smoothing asymptotics and Edgeworth expansion," Journal of Econometrics, Elsevier, vol. 185(1), pages 20-32.
    See citations under working paper version above.Sorry, no citations of articles recorded.

Software components

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 34 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 (26) 2014-06-28 2014-06-28 2014-06-28 2014-06-28 2014-06-28 2014-09-05 2015-02-22 2015-02-28 2015-11-21 2017-07-23 2018-03-05 2018-03-26 2018-03-26 2018-12-17 2019-10-14 2019-10-21 2019-11-18 2020-10-19 2020-12-14 2020-12-14 2021-06-14 2023-07-10 2024-01-08 2024-06-10 2024-06-17 2025-03-03. Author is listed
  2. NEP-UPT: Utility Models and Prospect Theory (7) 2017-07-23 2018-03-05 2018-03-26 2020-12-14 2022-08-29 2023-07-10 2024-10-07. Author is listed
  3. NEP-ORE: Operations Research (5) 2019-10-21 2020-12-14 2020-12-14 2020-12-14 2020-12-14. Author is listed
  4. NEP-HEA: Health Economics (2) 2018-12-17 2019-10-14
  5. NEP-MFD: Microfinance (2) 2023-07-10 2023-07-10
  6. NEP-COM: Industrial Competition (1) 2024-06-10
  7. NEP-ISF: Islamic Finance (1) 2021-08-30
  8. NEP-PBE: Public Economics (1) 2014-06-28
  9. NEP-RMG: Risk Management (1) 2020-10-19
  10. NEP-SEA: South East Asia (1) 2014-06-28

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