IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v6y2018i2p24-d144594.html
   My bibliography  Save this article

A Hybrid MCMC Sampler for Unconditional Quantile Based on Influence Function

Author

Listed:
  • El Moctar Laghlal

    (Laboratoire d’Économie d’Orléans (LEO), Faculté de Droit, D’économie et de Gestion, University of Orleans, LEO (FRE CNRS 2014), Rue de Blois, F-45067 Orleans, France)

  • Abdoul Aziz Junior Ndoye

    (Laboratoire d’Économie d’Orléans (LEO), Faculté de Droit, D’économie et de Gestion, University of Orleans, LEO (FRE CNRS 2014), Rue de Blois, F-45067 Orleans, France)

Abstract

In this study, we provide a Bayesian estimation method for the unconditional quantile regression model based on the Re-centered Influence Function (RIF). The method makes use of the dichotomous structure of the RIF and estimates a non-linear probability model by a logistic regression using a Gibbs within a Metropolis-Hastings sampler. This approach performs better in the presence of heavy-tailed distributions. Applied to a nationally-representative household survey, the Senegal Poverty Monitoring Report (2005), the results show that the change in the rate of returns to education across quantiles is substantially lower at the primary level.

Suggested Citation

  • El Moctar Laghlal & Abdoul Aziz Junior Ndoye, 2018. "A Hybrid MCMC Sampler for Unconditional Quantile Based on Influence Function," Econometrics, MDPI, vol. 6(2), pages 1-11, May.
    • Handle: RePEc:gam:jecnmx:v:6:y:2018:i:2:p:24-:d:144594
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/6/2/24/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/6/2/24/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    2. George Psacharopoulos & Harry Anthony Patrinos, 2004. "Returns to investment in education: a further update," Education Economics, Taylor & Francis Journals, vol. 12(2), pages 111-134.
    3. Michel Lubrano & Abdoul Aziz Junior Ndoye, 2014. "Bayesian Unconditional Quantile Regression: An Analysis of Recent Expansions in Wage Structure and Earnings Inequality in the US 1992–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 129-153, May.
    4. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, March.
    5. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    6. Psacharopoulos, George, 1994. "Returns to investment in education: A global update," World Development, Elsevier, vol. 22(9), pages 1325-1343, September.
    7. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-1382, November.
    8. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    9. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    10. Yu, Keming & Moyeed, Rana A., 2001. "Bayesian quantile regression," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 437-447, October.
    11. Dorothée Boccanfuso & Bernard Decaluwé & Luc Savard, 2008. "Poverty, income distribution and CGE micro-simulation modeling: Does the functional form of distribution matter?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(2), pages 149-184, June.
    12. José A. F. Machado & José Mata, 2001. "Earning functions in Portugal 1982-1994: Evidence from quantile regressions," Empirical Economics, Springer, vol. 26(1), pages 115-134.
    13. Russell Davidson, 2012. "Statistical inference in the presence of heavy tails," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 31-53, February.
    14. Ravallion, Martin, 2001. "Growth, Inequality and Poverty: Looking Beyond Averages," World Development, Elsevier, vol. 29(11), pages 1803-1815, November.
    15. Dorothee Boccanfuso & Antonio Estache & Luc Savard, 2009. "A Macro-Micro Analysis of the Effects of Electricity Reform in Senegal on Poverty and Distribution," Journal of Development Studies, Taylor & Francis Journals, vol. 45(3), pages 351-368.
    16. Michel Lubrano & Abdoul Aziz Junior Ndoye, 2014. "Bayesian Unconditional Quantile Regression: An Analysis of Recent Expansions in Wage Structure and Earnings Inequality in the US 1992–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 129-153, May.
    17. Lubrano, Michel & Ndoye, Abdoul Aziz Junior, 2016. "Income inequality decomposition using a finite mixture of log-normal distributions: A Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 830-846.
    18. International Monetary Fund, 2007. "Senegal: Poverty Reduction Strategy Paper," IMF Staff Country Reports 2007/316, International Monetary Fund.
    19. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    20. Yunwen Yang & Huixia Judy Wang & Xuming He, 2016. "Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood," International Statistical Review, International Statistical Institute, vol. 84(3), pages 327-344, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Philip Trostel & Ian Walker, 2006. "Education and Work," Education Economics, Taylor & Francis Journals, vol. 14(4), pages 377-399.
    2. Michel Lubrano & Abdoul Aziz Junior Ndoye, 2014. "Bayesian Unconditional Quantile Regression: An Analysis of Recent Expansions in Wage Structure and Earnings Inequality in the US 1992–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(2), pages 129-153, May.
    3. Maria Manuel Campos & Hugo Reis, 2018. "Returns to schooling in the Portuguese economy: a reassessment," Public Sector Economics, Institute of Public Finance, vol. 42(2), pages 215-242.
    4. Tushar Agrawal, 2011. "Returns to education in India: Some recent evidence," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2011-017, Indira Gandhi Institute of Development Research, Mumbai, India.
    5. Hugo Reis & Maria Manuel Campos, 2017. "Revisiting the returns to schooling in the Portuguese economy," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    6. Anuneeta Mitra, 2016. "Education and earning linkages of regular and casual workers in India: a quantile regression approach," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 18(1), pages 147-174, October.
    7. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    8. Uwaifo Oyelere, Ruth, 2010. "Africa's education enigma? The Nigerian story," Journal of Development Economics, Elsevier, vol. 91(1), pages 128-139, January.
    9. Majda Benzidia & Michel Lubrano, 2016. "A Bayesian Look at American Academic Wages: The Case of Michigan State University," AMSE Working Papers 1628, Aix-Marseille School of Economics, France.
    10. Bloom, David E. & Canning, David & Kotschy, Rainer & Prettner, Klaus & Schünemann, Johannes, 2018. "Health and Economic Growth: Reconciling the Micro and Macro Evidence," IZA Discussion Papers 11940, Institute of Labor Economics (IZA).
    11. Muhammad Nauman Malik & Masood Sarwar Awan, 2016. "Analysing Econometric Bias and Non-linearity in Returns to Education of Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 55(4), pages 837-851.
    12. Nikolov, Plamen & Jimi, Nusrat & Chang, Jerray, 2020. "The Importance of Cognitive Domains and the Returns to Schooling in South Africa: Evidence from Two Labor Surveys," Labour Economics, Elsevier, vol. 65(C).
    13. Pham, Thai-Hung & Reilly, Barry, 2007. "The gender pay gap in Vietnam, 1993-2002: A quantile regression approach," Journal of Asian Economics, Elsevier, vol. 18(5), pages 775-808, October.
    14. Ben-Halima, B. & Chusseau, N. & Hellier, J., 2014. "Skill premia and intergenerational education mobility: The French case," Economics of Education Review, Elsevier, vol. 39(C), pages 50-64.
    15. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    16. Marcelo Soto, 2006. "The Causal Effect of Education on Aggregate Income," Working Papers 0605, International Economics Institute, University of Valencia.
    17. Kentaro Shimada & Zeba Khan & Suguru Mizunoya & Ayako Wakano, 2016. "An Update of the Returns to Education in Kenya: Accounting both endogeneity and sample selection biases," Discussion Papers in Economics and Business 16-18, Osaka University, Graduate School of Economics.
    18. Angel de la Fuente & Antonio Ciccone, 2003. "Human capital in a global and knowledge-based economy," UFAE and IAE Working Papers 562.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    19. Yubilianto, 2020. "Return to education and financial value of investment in higher education in Indonesia," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-28, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecnmx:v:6:y:2018:i:2:p:24-:d:144594. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

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