[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/iaf/journl/y2020i4p112-119.html
   My bibliography  Save this article

Vocational Teacher Productivity in Palembang: Education Production Function

Author

Listed:
  • Evi Oktavia

    (Sriwijaya University, Palembang, Indonesia)

Abstract
In education sector the direct estimates of worker productivity are available for the majority of the workforce. In recent years, educational economists examine productivity returns to work experience among teachers using predicted contributions to increase student test scores as a proxy for productivity. Teacher productivity in the labor economy is measured using the education production function model. An education production function is an application of the economic concept of a production function to the field of education. It relates various inputs affecting a student's learning (schools, families, peers, neighborhoods, etc.) to measured outputs including subsequent labor market success, college attendance, graduation rates, and, most frequently, standardized test scores. This study was aimed to determine the effect of wages, level of education and training toward honorary teachers’ productivity in Palembang. The data used in this study were primary data in the form of questionnaires which were asked directly to the respondents with a total number of 310 respondents from 28 private vocational schools in Palembang. Survey was used as the data collection method with proportional random sampling withdrawal. Data analysis method used in this study was multiple regression with OLS method. The results of this study indicated that wages, education and training affect the productivity of private vocational school teachers in Palembang. The coefficient of determination for the variable of wages, education and training was 65%. It showed that wages, education, and training had 65% effects on productivity and the remaining 35% was influenced by other variables. As the research results show, the productivity was very important in measuring the success of an employee. It can be seen by paying attention to the level of wages, education and training participated by teachers in a school institution, especially in Palembang.

Suggested Citation

  • Evi Oktavia, 2020. "Vocational Teacher Productivity in Palembang: Education Production Function," Oblik i finansi, Institute of Accounting and Finance, issue 4, pages 112-119, December.
  • Handle: RePEc:iaf:journl:y:2020:i:4:p:112-119
    as

    Download full text from publisher

    File URL: http://www.afj.org.ua/pdf/798-produktivnist-profesiynoi-diyalnosti-uchitelya-v-palembangu-virobnicha-funkciya-osviti.pdf
    Download Restriction: no

    File URL: http://www.afj.org.ua/en/article/798/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Almond, Douglas & Currie, Janet, 2011. "Human Capital Development before Age Five," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 15, pages 1315-1486, Elsevier.
    2. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
    3. Joppe de Ree & Karthik Muralidharan & Menno Pradhan & Halsey Rogers, 2018. "Double for Nothing? Experimental Evidence on an Unconditional Teacher Salary Increase in Indonesia," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(2), pages 993-1039.
    4. Eric A. Hanushek & Steven G. Rivkin, 2012. "The Distribution of Teacher Quality and Implications for Policy," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 131-157, July.
    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. Elisabetta De Cao, 2015. "The Height Production Function from Birth to Age Two," Journal of Human Capital, University of Chicago Press, vol. 9(3), pages 329-363.
    2. Fitzsimons, Emla & Malde, Bansi & Mesnard, Alice & Vera-Hernández, Marcos, 2016. "Nutrition, information and household behavior: Experimental evidence from Malawi," Journal of Development Economics, Elsevier, vol. 122(C), pages 113-126.
    3. Flèche, Sarah & Lekfuangfu, Warn N. & Clark, Andrew E., 2021. "The long-lasting effects of family and childhood on adult wellbeing: Evidence from British cohort data," Journal of Economic Behavior & Organization, Elsevier, vol. 181(C), pages 290-311.
    4. Augsburg, Britta & Rodríguez-Lesmes, Paul Andrés, 2018. "Sanitation and child health in India," World Development, Elsevier, vol. 107(C), pages 22-39.
    5. Juan F. Castro, 2015. "Linear decompositions of cognitive achievement gaps a cautionary note and an illustration using peruvian data," Working Papers 15-08, Centro de Investigación, Universidad del Pacífico.
    6. Warn N. Lekfuangfu & Nattavudh Powdthavee & Nele Warrinnier & Francesca Cornaglia, 2018. "Locus of Control and its Intergenerational Implications for Early Childhood Skill Formation," Economic Journal, Royal Economic Society, vol. 128(608), pages 298-329, February.
    7. M. Caridad Araujo & Pedro Carneiro & Yyannú Cruz-Aguayo & Norbert Schady, 2016. "Teacher Quality and Learning Outcomes in Kindergarten," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1415-1453.
    8. Gabriella Conti, 2013. "The Developmental Origins of Health Inequality," Research on Economic Inequality, in: Health and Inequality, volume 21, pages 285-309, Emerald Group Publishing Limited.
    9. Kabir Dasgupta, 2019. "Youth response to state cyberbullying laws," New Zealand Economic Papers, Taylor & Francis Journals, vol. 53(2), pages 184-202, May.
    10. Daniela Del Boca & Christopher Flinn & Matthew Wiswall, 2014. "Household Choices and Child Development," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(1), pages 137-185.
    11. Azam, Mehtabul & Kingdon, Geeta Gandhi, 2015. "Assessing teacher quality in India," Journal of Development Economics, Elsevier, vol. 117(C), pages 74-83.
    12. Oketch, Moses & Rolleston, Caine & Rossiter, Jack, 2021. "Diagnosing the learning crisis: What can value-added analysis contribute?," International Journal of Educational Development, Elsevier, vol. 87(C).
    13. Elizabeth M. Caucutt & Lance Lochner, 2020. "Early and Late Human Capital Investments, Borrowing Constraints, and the Family," Journal of Political Economy, University of Chicago Press, vol. 128(3), pages 1065-1147.
    14. Elisabetta De Cao, 2010. "The Height Production Function from Birth to Early Adulthood," CEIS Research Paper 165, Tor Vergata University, CEIS, revised 28 May 2010.
    15. repec:lic:licosd:35314 is not listed on IDEAS
    16. Motegi, Hiroyuki & Oikawa, Masato, 2019. "The effect of instructional quality on student achievement: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 52(C).
    17. Isaac Mbiti & Mauricio Romero & Youdi Schipper, 2023. "Designing Effective Teacher Performance Pay Programs: Experimental Evidence from Tanzania," The Economic Journal, Royal Economic Society, vol. 133(653), pages 1968-2000.
    18. Elisabetta De Cao, 2014. "The height production function from birth to maturity," CSAE Working Paper Series 2014-31, Centre for the Study of African Economies, University of Oxford.
    19. Ingo Outes-Leon & Catherine Porter & Alan Sánchez, 2011. "Early Nutrition and Cognition in Peru," Working Papers 402632300, Lancaster University Management School, Economics Department.
    20. Greaves, Ellen & Sibieta, Luke, 2019. "Constrained optimisation? Teacher salaries, school resources and student achievement," Economics of Education Review, Elsevier, vol. 73(C).
    21. Lisa Grazzini, 2016. "The Importance of the Quality of Education: Some Determinants and its Effects on Earning Returns and Economic Growth," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2016(2), pages 43-82.

    More about this item

    Keywords

    productivity; wages; education; training; education production function;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:iaf:journl:y:2020:i:4:p:112-119. 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: Serhiy Ostapchuk (email available below). General contact details of provider: https://edirc.repec.org/data/iafkvua.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.