IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v13y2025i2p20-d1647468.html
   My bibliography  Save this article

Government Subsidies and Industrial Productivity in South Africa: A Focus on the Channels

Author

Listed:
  • Brian Tavonga Mazorodze

    (Faculty of Economic and Management Sciences, Department of Accounting and Economics, Sol Plaatje University, Kimberley 8301, South Africa)

Abstract

This article estimates the impact of government subsidies on productivity growth in South Africa, joining the ongoing debate among economists regarding the effectiveness of subsidies as a driver of industrial productivity. While some argue that subsidies address market failures, facilitate R&D, and improve efficiency, others criticise the attendant dependence, which reduces the incentive for industries to operate efficiently. This article contributes by examining the specific channels—efficiency and technical changes—through which subsidies affect productivity in South Africa. The analysis is based on a panel dataset comprising 64 three-digit industries observed between 1993 and 2023. Estimation is performed through an endogeneity robust panel stochastic frontier model, which treats subsidies as both an inefficiency driver and a technology variable. An additional estimation approach is proposed integrating the true fixed effects with a control function in a bid to account for both unobserved heterogeneity and idiosyncratic endogeneity. The results show that subsidies are detrimental to productivity, particularly through stifling technological progress. This result supports the view that subsidies reduce the incentive for beneficiaries to innovate. This evidence calls for a reevaluation and a possible restructuring of subsidy programmes in South Africa in a bid to mitigate their adverse effects on industrial productivity.

Suggested Citation

  • Brian Tavonga Mazorodze, 2025. "Government Subsidies and Industrial Productivity in South Africa: A Focus on the Channels," Econometrics, MDPI, vol. 13(2), pages 1-26, May.
  • Handle: RePEc:gam:jecnmx:v:13:y:2025:i:2:p:20-:d:1647468
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/13/2/20/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2225-1146/13/2/20/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Mingyang & Jin, Man & Kumbhakar, Subal C., 2022. "Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 303(1), pages 388-400.
    2. Timothy Köhler & Haroon Bhorat & Robert Hill, 2023. "The effect of wage subsidies on job retention in a developing country: Evidence from South Africa," WIDER Working Paper Series wp-2023-114, World Institute for Development Economic Research (UNU-WIDER).
    3. Zhenji Jin & Yue Shang & Jian Xu, 2018. "The Impact of Government Subsidies on Private R&D and Firm Performance: Does Ownership Matter in China’s Manufacturing Industry?," Sustainability, MDPI, vol. 10(7), pages 1-20, June.
    4. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    5. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    6. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    7. Réka Juhász & Nathan Lane & Dani Rodrik, 2024. "The New Economics of Industrial Policy," Annual Review of Economics, Annual Reviews, vol. 16(1), pages 213-242, August.
    8. repec:bla:jecsur:v:13:y:1999:i:2:p:119-47 is not listed on IDEAS
    9. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    10. Krueger, Anne O & Tuncer, Baran, 1982. "An Empirical Test of the Infant Industry Argument," American Economic Review, American Economic Association, vol. 72(5), pages 1142-1152, December.
    11. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    12. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
    13. Gerd Schwartz & Benedict Clements, 1999. "Government Subsidies," Journal of Economic Surveys, Wiley Blackwell, vol. 13(2), pages 119-148, April.
    14. Salustiano, Silvia Ferreira Marques & Barbosa, Natália & Moreira, Tito Belchior Silva, 2020. "Do subsidies drive technical efficiency? The case of portuguese firms in the agribusiness sector," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 58(3), January.
    15. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    16. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    17. Lin, Boqiang & Okyere, Michael Adu, 2023. "Race and energy poverty: The moderating role of subsidies in South Africa," Energy Economics, Elsevier, vol. 117(C).
    18. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    19. repec:osf:socarx:gsyq4_v1 is not listed on IDEAS
    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. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    2. Emilie Caldeira & Alou Adessé Dama & Ali Compaoré & Mario Mansour & Grégoire Rota-Graziosi, 2020. "Tax effort in Sub-Saharan African countries : evidence from a new dataset," Working Papers hal-02543162, HAL.
    3. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    4. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    5. Émilie Caldeira & Ali Compaore & Alou Adessé Dama & Mario Mansour & Grégoire Rota-Graziosi, 2019. "Effort fiscal en Afrique subsaharienne : les résultats d’une nouvelle base de données," Revue d’économie du développement, De Boeck Université, vol. 27(4), pages 5-51.
    6. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    7. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    8. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2017. "Determinants of transient and persistent hospital efficiency: The case of Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 5-22, September.
    9. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    10. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    11. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LLC, vol. 13(4), pages 718-758, December.
    12. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    13. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    14. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    15. Wanglin Ma & Kathryn Bicknell & Alan Renwick, 2019. "Feed use intensification and technical efficiency of dairy farms in New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(1), pages 20-38, January.
    16. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    17. Idaira Cabrera‐Suárez & Jorge V. Pérez‐Rodríguez, 2021. "Bank branch performance and cost efficiency: A stochastic frontier panel data approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5850-5863, October.
    18. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    19. Per J. Agrell & Mehdi Farsi & Massimo Filippini & Martin Koller, 2013. "Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems," CER-ETH Economics working paper series 13/171, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    20. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.

    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:13:y:2025:i:2:p:20-:d:1647468. 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.