IDEAS home Printed from https://ideas.repec.org/a/liu/liucej/v19y2022i1p103-141.html
   My bibliography  Save this article

Separating innovation short-run and long-run technical efficiencies: Evidence from the Economic Community of West African States (ECOWAS)

Author

Listed:
  • Dorgyles C.M. Kouakou

Abstract

A stream of literature has been developed on the measurement of the efficient production of innovation, that is, innovation technical efficiency. However, the efficiency measured is quite fuzzy as no distinction is made between innovation short-run and long-run efficiencies. Also, African economies have been heavily neglected, despite the need to explore ways to improve the poor levels of innovation they usually exhibit. In this paper, we measure innovation technical efficiency by separating short-run and long-run efficiencies. Overall technical efficiency, that is, efficiency both in the short and long run is also assessed. The empirical evidence makes use of data from countries from the Economic Community of West African States, one of the most important economic areas in Africa. To obtain efficiency scores, we carry out a stochastic frontier analysis. Results show that research and development, market sophistication and human capital significantly influence innovation output. No country is found to be efficient following one of the types of efficiency. The long-run and average short-run efficiencies over the study period are not similar, which shows the need to separate the types of efficiency. Domestic credit to private sector and governance are highlighted as determinants of innovation efficiency. Some policies are suggested based on these findings.

Suggested Citation

  • Dorgyles C.M. Kouakou, 2022. "Separating innovation short-run and long-run technical efficiencies: Evidence from the Economic Community of West African States (ECOWAS)," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 19(1), pages 103-141, June.
  • Handle: RePEc:liu:liucej:v:19:y:2022:i:1:p:103-141
    as

    Download full text from publisher

    File URL: https://ejce.liuc.it/articles/ejce010.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    2. Jacques Mairesse & Pierre Mohnen, 2002. "Accounting for Innovation and Measuring Innovativeness: An Illustrative Framework and an Application," American Economic Review, American Economic Association, vol. 92(2), pages 226-230, May.
    3. 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.
    4. Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Size, efficiency, market power, and economies of scale in the African banking sector," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-22, December.
    5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    6. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.
    7. Balsmeier, Benjamin, 2017. "Unions, collective relations laws and R&D investment in emerging and developing countries," Research Policy, Elsevier, vol. 46(1), pages 292-304.
    8. Efthymios G. Tsionas & Subal C. Kumbhakar, 2014. "FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM‐EFFECTS model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 110-132, January.
    9. Ufuk Akcigit & William R. Kerr, 2018. "Growth through Heterogeneous Innovations," Journal of Political Economy, University of Chicago Press, vol. 126(4), pages 1374-1443.
    10. Amable, Bruno & Ledezma, Ivan & Robin, Stéphane, 2016. "Product market regulation, innovation, and productivity," Research Policy, Elsevier, vol. 45(10), pages 2087-2104.
    11. Junhong Bai, 2013. "On Regional Innovation Efficiency: Evidence from Panel Data of China's Different Provinces," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 773-788, May.
    12. Simplice Asongu & Rexon Nting & Joseph Nnanna, 2020. "Market power and cost efficiency in the African banking industry," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(6), pages 1247-1264, May.
    13. Kontolaimou, Alexandra & Giotopoulos, Ioannis & Tsakanikas, Aggelos, 2016. "A typology of European countries based on innovation efficiency and technology gaps: The role of early-stage entrepreneurship," Economic Modelling, Elsevier, vol. 52(PB), pages 477-484.
    14. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
    15. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    16. Chen, Yongmin & Puttitanun, Thitima, 2005. "Intellectual property rights and innovation in developing countries," Journal of Development Economics, Elsevier, vol. 78(2), pages 474-493, December.
    17. Gerrit Rooks & Adam Szirmai & Arthur Sserwanga, 2012. "Network Structure and Innovative Performance of African Entrepreneurs: The Case of Uganda-super- †," Journal of African Economies, Centre for the Study of African Economies, vol. 21(4), pages 609-636, August.
    18. Paul Robson & Helen Haugh & Bernard Obeng, 2009. "Entrepreneurship and innovation in Ghana: enterprising Africa," Small Business Economics, Springer, vol. 32(3), pages 331-350, March.
    19. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    20. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    21. Lee, Jiyoung & Kim, Chulyeon & Choi, Gyunghyun, 2019. "Exploring data envelopment analysis for measuring collaborated innovation efficiency of small and medium-sized enterprises in Korea," European Journal of Operational Research, Elsevier, vol. 278(2), pages 533-545.
    22. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Panel data stochastic frontier model with determinants of persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 271(2), pages 746-755.
    23. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514, September.
    24. Gebreeyesus, Mulu & Mohnen, Pierre, 2013. "Innovation Performance and Embeddedness in Networks: Evidence from the Ethiopian Footwear Cluster," World Development, Elsevier, vol. 41(C), pages 302-316.
    25. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    26. Simar, L., 1991. "Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with boot strapping," LIDAM Discussion Papers CORE 1991026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Endogeneity in panel data stochastic frontier model with determinants of persistent and transient inefficiency," Economics Letters, Elsevier, vol. 162(C), pages 5-9.
    28. Maskus, Keith E. & Milani, Sahar & Neumann, Rebecca, 2019. "The impact of patent protection and financial development on industrial R&D," Research Policy, Elsevier, vol. 48(1), pages 355-370.
    29. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    30. Subal C. Kumbhakar & Gudbrand Lien, 2017. "Yardstick Regulation of Electricity Distribution Disentangling Short-run and Long-run Inefficiencies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    31. Guan, JianCheng & Zuo, KaiRui & Chen, KaiHua & Yam, Richard C.M., 2016. "Does country-level R&D efficiency benefit from the collaboration network structure?," Research Policy, Elsevier, vol. 45(4), pages 770-784.
    32. Fu, Xiaolan & Yang, Qing Gong, 2009. "Exploring the cross-country gap in patenting: A Stochastic Frontier Approach," Research Policy, Elsevier, vol. 38(7), pages 1203-1213, September.
    33. Elias G. Carayannis & Evangelos Grigoroudis, 2016. "Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation," Annals of Operations Research, Springer, vol. 247(2), pages 635-655, December.
    34. Fu, Xiaolan, 2012. "How does openness affect the importance of incentives for innovation?," Research Policy, Elsevier, vol. 41(3), pages 512-523.
    35. 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.
    36. Nelson, Richard R., 2008. "What enables rapid economic progress: What are the needed institutions," Research Policy, Elsevier, vol. 37(1), pages 1-11, February.
    37. Bruno Amable & Ivan Ledezma & Stéphane Robin, 2016. "Product market regulation, innovation, and productivity," Post-Print hal-03691909, HAL.
    38. Kumbhakar, Subal C. & Wang, Hung-Jen, 2005. "Estimation of growth convergence using a stochastic production frontier approach," Economics Letters, Elsevier, vol. 88(3), pages 300-305, September.
    39. 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.
    40. Kumbhakar, Subal C & Hjalmarsson, Lennart, 1995. "Labour-Use Efficiency in Swedish Social Insurance Offices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 33-47, Jan.-Marc.
    41. Furman, Jeffrey L. & Porter, Michael E. & Stern, Scott, 2002. "The determinants of national innovative capacity," Research Policy, Elsevier, vol. 31(6), pages 899-933, August.
    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. Dorgyles C.M. Kouakou, 2022. "Separating innovation short-run and long-run technical efficiencies: Evidence from the Economic Community of West African States (ECOWAS)," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 19(1), pages 103-141, June.
    2. Pontus Mattsson & Jonas Mansson & William H. Greene, 2018. "TFP Change and its Components for Swedish Manufacturing Firms During the 2008-2009 Financial Crisis," Working Papers 18-27, New York University, Leonard N. Stern School of Business, Department of Economics.
    3. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    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. Bernstein, David H., 2020. "An updated assessment of technical efficiency and returns to scale for U.S. electric power plants," Energy Policy, Elsevier, vol. 147(C).
    6. 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.
    7. Manuel Salas‐Velasco, 2020. "Assessing the performance of Spanish secondary education institutions: Distinguishing between transient and persistent inefficiency, separated from heterogeneity," Manchester School, University of Manchester, vol. 88(4), pages 531-555, July.
    8. Pontus Mattsson & Jonas Månsson & William H. Greene, 2020. "TFP change and its components for Swedish manufacturing firms during the 2008–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(1), pages 79-93, February.
    9. Subal C. Kumbhakar & Gudbrand Lien, 2017. "Yardstick Regulation of Electricity Distribution Disentangling Short-run and Long-run Inefficiencies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    10. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    11. Magambo, Isaiah & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Environmental and Technical Efficiency in Large Gold Mines in Developing Countries," MPRA Paper 108068, University Library of Munich, Germany.
    12. 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.
    13. Subal C. Kumbhakar & Norman V. Loayza & Vivian Norambuena, 2020. "International Benchmarking for Country Economic Diagnostics," Working Papers wp498, University of Chile, Department of Economics.
    14. 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).
    15. Kumbhakar,Subal C. & Loayza,Norman V. & Norambuena,Vivian, 2020. "International Benchmarking for Country Economic Diagnostics : A Stochastic Frontier Approach," Policy Research Working Paper Series 9304, The World Bank.
    16. 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.
    17. Skevas, Ioannis & Skevas, Theodoros, 2021. "A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1131-1142.
    18. Makieła, Kamil, 2016. "Bayesian inference in generalized true random-effects model and Gibbs sampling," MPRA Paper 69389, University Library of Munich, Germany.
    19. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    20. Heshmati, Almas & C. Kumbhakar, Subal & Kim, Jungsuk, 2016. "Persistent and Transient Efficiency of International Airlines," Working Paper Series in Economics and Institutions of Innovation 444, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.

    More about this item

    Keywords

    Innovation technical efficiency; Short-run efficiency; Long-run efficiency; Determinant factors; West Africa;
    All these keywords.

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa

    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:liu:liucej:v:19:y:2022:i:1:p:103-141. 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: Laura Ballestra (email available below). General contact details of provider: https://edirc.repec.org/data/liuccit.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.