IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/105283.html
   My bibliography  Save this paper

A systematic review of statistical methods for estimating an education production function

Author

Listed:
  • Ogundari, Kolawole

Abstract

The quality of administrative or longitudinal data used in education research has always been an issue of concern since they are collected mainly for recording and reporting, rather than research. The advancement in computational techniques in statistics could help researchers navigates many of these concerns by identifying the statistical model that best fits this type of data for research. The paper provides a comprehensive review of the statistical methods important for estimating education production function to recognize this. The article also provides an extensive overview of empirical studies that used the techniques identified. We believe a systematic review of this nature provides an excellent resource for researchers and academicians in identifying critical statistical methods relevant to educational studies.

Suggested Citation

  • Ogundari, Kolawole, 2021. "A systematic review of statistical methods for estimating an education production function," MPRA Paper 105283, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:105283
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/105283/1/MPRA_paper_105283.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stratton, Leslie S. & O'Toole, Dennis M. & Wetzel, James N., 2008. "A multinomial logit model of college stopout and dropout behavior," Economics of Education Review, Elsevier, vol. 27(3), pages 319-331, June.
    2. Martin R. West & Ludger Woessmann, 2010. "'Every Catholic Child in a Catholic School': Historical Resistance to State Schooling, Contemporary Private Competition and Student Achievement across Countries," Economic Journal, Royal Economic Society, vol. 120(546), pages 229-255, August.
    3. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    4. Mary A. Burke & Tim R. Sass, 2013. "Classroom Peer Effects and Student Achievement," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 51-82.
    5. Lechner, Michael, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," IZA Discussion Papers 12040, Institute of Labor Economics (IZA).
    6. Richard E. Just & David Zilberman & Eithan Hochman, 1983. "Estimation of Multicrop Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(4), pages 770-780.
    7. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    8. Croninger, Robert G. & Rice, Jennifer King & Rathbun, Amy & Nishio, Masako, 2007. "Teacher qualifications and early learning: Effects of certification, degree, and experience on first-grade student achievement," Economics of Education Review, Elsevier, vol. 26(3), pages 312-324, June.
    9. Zahra Siddique, 2014. "Randomized control trials in an imperfect world," IZA World of Labor, Institute of Labor Economics (IZA), pages 110-110, December.
    10. Julia Kuzmina & Martin Carnoy, 2016. "The effectiveness of vocational versus general secondary education," International Journal of Manpower, Emerald Group Publishing Limited, vol. 37(1), pages 2-24, April.
    11. Denny, Kevin & Oppedisano, Veruska, 2013. "The surprising effect of larger class sizes: Evidence using two identification strategies," Labour Economics, Elsevier, vol. 23(C), pages 57-65.
    12. Stefan Wager & Susan Athey, 2018. "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
    13. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    14. Gyimah-Brempong, Kwabena & Gyapong, Anthony O., 1991. "Characteristics of education production functions: An application of canonical regression analysis," Economics of Education Review, Elsevier, vol. 10(1), pages 7-17, March.
    15. Hugo Storm & Kathy Baylis & Thomas Heckelei, 2020. "Machine learning in agricultural and applied economics," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 849-892.
    16. William N. Evans & Robert M. Schwab, 1995. "Finishing High School and Starting College: Do Catholic Schools Make a Difference?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(4), pages 941-974.
    17. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
    18. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2019. "A Theory of Statistical Inference for Matching Methods in Causal Research," Political Analysis, Cambridge University Press, vol. 27(1), pages 46-68, January.
    19. Chakraborty, Tanika & Jayaraman, Rajshri, 2019. "School feeding and learning achievement: Evidence from India's midday meal program," Journal of Development Economics, Elsevier, vol. 139(C), pages 249-265.
    20. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863, Elsevier.
    21. Siqing Shan & Cangyan Li & Jihong Shi & Li Wang & Huali Cai, 2014. "Impact of Effective Communication, Achievement Sharing and Positive Classroom Environments on Learning Performance," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 471-482, May.
    22. Serena Canaan & Pierre Mouganie, 2018. "Returns to Education Quality for Low-Skilled Students: Evidence from a Discontinuity," Journal of Labor Economics, University of Chicago Press, vol. 36(2), pages 395-436.
    23. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    24. Shawna Grosskopf & Kathy Hayes & Lori L. Taylor, 2014. "Applied efficiency analysis in education," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 19-26.
    25. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
    26. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    27. Vandenberghe, V. & Robin, S., 2004. "Evaluating the effectiveness of private education across countries: a comparison of methods," Labour Economics, Elsevier, vol. 11(4), pages 487-506, August.
    28. Duchini, Emma, 2017. "Is college remedial education a worthy investment? New evidence from a sharp regression discontinuity design," Economics of Education Review, Elsevier, vol. 60(C), pages 36-53.
    29. José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
    30. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 497-532.
    31. Kang, Lili & Peng, Fei & Zhu, Yu, 2018. "Returns to higher education subjects and tiers in China - Evidence from the China Family Panel Studies," GLO Discussion Paper Series 238, Global Labor Organization (GLO).
    32. Ponzo, Michela, 2013. "Does bullying reduce educational achievement? An evaluation using matching estimators," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1057-1078.
    33. Zhuo Liu & Christopher A. Kanter & Kent D. Messer & Harry M. Kaiser, 2013. "Identifying significant characteristics of organic milk consumers: a CART analysis of an artefactual field experiment," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3110-3121, July.
    34. Deaton, Angus & Cartwright, Nancy, 2018. "Understanding and misunderstanding randomized controlled trials," Social Science & Medicine, Elsevier, vol. 210(C), pages 2-21.
    35. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
    36. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    37. Kolawole Ogundari & Adebayo B Aromolaran, 2014. "Impact of Education on Household Welfare in Nigeria," International Economic Journal, Taylor & Francis Journals, vol. 28(2), pages 345-364, June.
    38. Wooldridge, Jeffrey M., 2019. "Correlated random effects models with unbalanced panels," Journal of Econometrics, Elsevier, vol. 211(1), pages 137-150.
    39. Kaliba, Aloyce R. & Mushi, Richard J. & Gongwe, Anne G. & Mazvimavi, Kizito, 2020. "A typology of adopters and nonadopters of improved sorghum seeds in Tanzania: A deep learning neural network approach," World Development, Elsevier, vol. 127(C).
    40. repec:iza:izawol:journl:y:2014:p:110 is not listed on IDEAS
    41. Eric A. Hanushek, 1979. "Conceptual and Empirical Issues in the Estimation of Educational Production Functions," Journal of Human Resources, University of Wisconsin Press, vol. 14(3), pages 351-388.
    42. Doyle, William R., 2011. "Effect of increased academic momentum on transfer rates: An application of the generalized propensity score," Economics of Education Review, Elsevier, vol. 30(1), pages 191-200, February.
    43. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    44. Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-844, September.
    45. Michael Lokshin & Zurab Sajaia, 2004. "Maximum likelihood estimation of endogenous switching regression models," Stata Journal, StataCorp LP, vol. 4(3), pages 282-289, September.
    46. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    47. Clark, Jeffrey A, 1984. "Estimation of Economies of Scale in Banking Using a Generalized Functional Form," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(1), pages 53-68, February.
    48. Bernal, Pedro & Mittag, Nikolas & Qureshi, Javaeria A., 2016. "Estimating effects of school quality using multiple proxies," Labour Economics, Elsevier, vol. 39(C), pages 1-10.
    49. Jill Johnes & Maria Portela & Emmanuel Thanassoulis, 2017. "Efficiency in education," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 331-338, April.
    50. Ariel Linden, 2015. "Conducting interrupted time-series analysis for single- and multiple-group comparisons," Stata Journal, StataCorp LP, vol. 15(2), pages 480-500, June.
    51. Sascha O. Becker, 2016. "Using instrumental variables to establish causality," IZA World of Labor, Institute of Labor Economics (IZA), pages 250-250, April.
    52. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    53. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    54. Kolawole Ogundari & Olufemi D. Bolarinwa, 2018. "Impact of agricultural innovation adoption: a meta†analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), pages 217-236, April.
    55. Alex J. Bowers & Ryan Sprott, 2012. "Examining the Multiple Trajectories Associated with Dropping Out of High School: A Growth Mixture Model Analysis," The Journal of Educational Research, Taylor & Francis Journals, vol. 105(3), pages 176-195, April.
    56. Papke, Leslie E., 2005. "The effects of spending on test pass rates: evidence from Michigan," Journal of Public Economics, Elsevier, vol. 89(5-6), pages 821-839, June.
    57. Riju Joshi & Jeffrey M. Wooldridge, 2019. "Correlated Random Effects Models with Endogenous Explanatory Variables and Unbalanced Panels," Annals of Economics and Statistics, GENES, issue 134, pages 243-268.
    58. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
    59. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    60. Anh Ngoc Nguyen & Jim Taylor, 2003. "Post-high school choices: New evidence from a multinomial logit model," Journal of Population Economics, Springer;European Society for Population Economics, vol. 16(2), pages 287-306, May.
    61. Alan Krueger, 1997. "Experimental Estimates of Education Production Functions," Working Papers 758, Princeton University, Department of Economics, Industrial Relations Section..
    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. José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
    2. Domenico Depalo, 2020. "Explaining the causal effect of adherence to medication on cholesterol through the marginal patient," Health Economics, John Wiley & Sons, Ltd., vol. 29(S1), pages 110-126, October.
    3. Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
    4. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
    5. Tamini, Lota D., 2011. "A nonparametric analysis of the impact of agri-environmental advisory activities on best management practice adoption: A case study of Québec," Ecological Economics, Elsevier, vol. 70(7), pages 1363-1374, May.
    6. Meghir, Costas & Rivkin, Steven, 2011. "Econometric Methods for Research in Education," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 1, pages 1-87, Elsevier.
    7. François Rycx & Yves Saks & Ilan Tojerow, 2015. "Does Education Raise Productivity and Wages Equally? The Moderating Roles of Age, Gender and Industry," Working Paper Research 281, National Bank of Belgium.
    8. Carpa, Nur & Martínez-Zarzoso, Inmaculada, 2022. "The impact of global value chain participation on income inequality," International Economics, Elsevier, vol. 169(C), pages 269-290.
    9. Luigi Biagini & Simone Severini, 2021. "The role of Common Agricultural Policy (CAP) in enhancing and stabilising farm income: an analysis of income transfer efficiency and the Income Stabilisation Tool," Papers 2104.14188, arXiv.org.
    10. Diaz-Serrano, Luis & Pérez, Jessica, 2013. "Do More Educated Leaders Raise Citizens' Education?," IZA Discussion Papers 7661, Institute of Labor Economics (IZA).
    11. Daniel Dietz & Thomas Zwick, 2016. "The retention effect of training – portability, visibility, and credibility," Economics of Education Working Paper Series 0113, University of Zurich, Department of Business Administration (IBW).
    12. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    13. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
    14. Corrado Andini, 2013. "How well does a dynamic Mincer equation fit NLSY data? Evidence based on a simple wage-bargaining model," Empirical Economics, Springer, vol. 44(3), pages 1519-1543, June.
    15. Cordero, Jose M. & Polo, Cristina & Santín, Daniel & Simancas, Rosa, 2018. "Efficiency measurement and cross-country differences among schools: A robust conditional nonparametric analysis," Economic Modelling, Elsevier, vol. 74(C), pages 45-60.
    16. Annie Tubadji & Vassilis Angelis & Peter Nijkamp, 2016. "Endogenous intangible resources and their place in the institutional hierarchy," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 36(1), pages 1-28, February.
    17. Committee, Nobel Prize, 2021. "Answering causal questions using observational data," Nobel Prize in Economics documents 2021-2, Nobel Prize Committee.
    18. Bourguignon, Francois, 2005. "The Effect of Economic Growth on Social Structures," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 27, pages 1701-1747, Elsevier.
    19. Lauber, Verena & Thomas, Lampert, 2014. "The Effect of Early Universal Daycare on Child Weight Problems," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100399, Verein für Socialpolitik / German Economic Association.
    20. Quader, Syed Manzur, 2017. "Differential effect of liquidity constraints on firm growth," Review of Financial Economics, Elsevier, vol. 32(C), pages 20-29.

    More about this item

    Keywords

    Education; Production Function; Statistical Methods; Causal Analysis; Regression;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:pra:mprapa:105283. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.