IDEAS home Printed from https://ideas.repec.org/a/vrs/poicbe/v17y2023i1p2172-2183n26.html
   My bibliography  Save this article

Analysis of the Educational System - An Econometric and Managerial Perspective

Author

Listed:
  • Munteanu Irina-Denisa

    (1 Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

Studying education from an econometric perspective provides an understanding of how economic and social factors influence educational process. From this perspective, it is possible to understand how different groups of people are affected by the educational system and find solutions to create a more equitable environment. Regarding this research area, the specialized literature is very vast. However, few schools recognize the interdependence and contributions that school infrastructure (buildings and furniture) can make to the improvement of academic activities in the school. This paperwork thus aims to study the public educational field in Romania from a managerial, as well as a spatial econometric perspective, in order to provide possible solutions for the improvement of the quality of the educational act in schools. The research hypothesis of this work is that certain infrastructure factors, such as the number of teaching staff, classrooms, IT equipment, gymnasiums, school laboratories, school workshops, and sports fields, have an impact on the number of graduates in each county of Romania. Conducting a spatial econometric analysis, the results validate the research hypothesis. The number of graduates from a county is influenced by the number of teaching staff, the number of IT equipment, school laboratories or sports fields existing in the respective county. Thus, Romania should allocate more financial resources to education, especially to motivate teachers, but also to transform the teaching career into an attractive one for passionate and well-prepared young people.

Suggested Citation

  • Munteanu Irina-Denisa, 2023. "Analysis of the Educational System - An Econometric and Managerial Perspective," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 2172-2183, July.
    • Handle: RePEc:vrs:poicbe:v:17:y:2023:i:1:p:2172-2183:n:26
    DOI: 10.2478/picbe-2023-0190
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/picbe-2023-0190
    Download Restriction: no
    File URL: https://libkey.io/10.2478/picbe-2023-0190?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Georges Bresson & Badi H. Baltagi & Alain Pirotte, 2007. "Panel unit root tests and spatial dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 339-360.
    2. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    3. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    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. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    2. Baltagi, Badi H. & Yen, Yin-Fang, 2014. "Hospital treatment rates and spillover effects: Does ownership matter?," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 193-202.
    3. Samantha Leorato & Maura Mezzetti, 2015. "Spatial Panel Data Model with error dependence: a Bayesian Separable Covariance Approach," CEIS Research Paper 338, Tor Vergata University, CEIS, revised 09 Apr 2015.
    4. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2012. "Forecasting with spatial panel data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3381-3397.
    5. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022. "Bayesian estimation of multivariate panel probits with higher‐order network interdependence and an application to firms' global market participation in Guangdong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1356-1378, November.
    6. Gianfranco Piras, 2013. "Efficient GMM Estimation of a Cliff and Ord Panel Data Model with Random Effects," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 370-388, September.
    7. Burridge, Peter & Iacone, Fabrizio & Lazarová, Štěpána, 2015. "Spatial effects in a common trend model of US city-level CPI," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 87-98.
    8. Fingleton, Bernard, 2008. "Competing models of global dynamics: Evidence from panel models with spatially correlated error components," Economic Modelling, Elsevier, vol. 25(3), pages 542-558, May.
    9. Hiller, Norbert & Lerbs, Oliver W., 2016. "Aging and urban house prices," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 276-291.
    10. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    11. Manoel BITTENCOURT, 2009. "Macroeconomic Performance And Inequality: Brazil, 1983–94," The Developing Economies, Institute of Developing Economies, vol. 47(1), pages 30-52, March.
    12. Guilherme Resende & Alexandre Carvalho & Patrícia Sakowski & Túlio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    13. Bittencourt, Manoel, 2011. "Inflation and financial development: Evidence from Brazil," Economic Modelling, Elsevier, vol. 28(1), pages 91-99.
    14. Bernard Fingleton & Manfred Fischer, 2010. "Neoclassical theory versus new economic geography: competing explanations of cross-regional variation in economic development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(3), pages 467-491, June.
    15. Sarafidis, Vasilis, 2009. "GMM Estimation of Short Dynamic Panel Data Models With Error Cross-Sectional Dependence," MPRA Paper 25176, University Library of Munich, Germany.
    16. Hans Dewachter & Romain Houssa & Priscilla Toffano, 2012. "Spatial propagation of macroeconomic shocks in Europe," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 148(2), pages 377-402, June.
    17. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    18. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    19. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
    20. Taşpınar, Süleyman & Doğan, Osman & Bera, Anil K., 2017. "GMM gradient tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 65-88.

    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:vrs:poicbe:v:17:y:2023:i:1:p:2172-2183:n:26. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.