IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v71y2018icp25-33.html
   My bibliography  Save this article

Efficient creativity in Mexican metropolitan areas

Author

Listed:
  • Benita, Francisco
  • Urzúa, Carlos M.

Abstract

Human creativity is the most important economic resource. Yet, very few studies in the economic literature have attempted to evaluate the efficiency of creative sectors around the world. In that regard, this paper examines the efficiency of the production of creative goods in Mexico. The empirical examination is made covering 36 metropolitan areas at four different periods of time, using the quinquennial economic censuses taken by the government in 1998, 2003, 2008 and 2013. The paper first estimates the static performance of the creative industries by means of data envelopment analysis models. Subsequently, the Malmquist productivity index is used to estimate their dynamic efficiency. Using both analyses, it is shown that, contrary to a commonly held view in the literature, most of the efficient creative industries in Mexico are to be found in metropolitan areas that are not relatively large. Furthermore, it is also found that more than three fourths of the creative sectors in the metropolitan areas are inefficient. The paper then makes use of Florida's 3Ts model to explore some possible factors that could account for those inefficiencies. Two features that are not widespread in Mexico, good public infrastructure and culturally diverse cities, are found to be explanatory factors of best practices in the production of creative goods.

Suggested Citation

  • Benita, Francisco & Urzúa, Carlos M., 2018. "Efficient creativity in Mexican metropolitan areas," Economic Modelling, Elsevier, vol. 71(C), pages 25-33.
  • Handle: RePEc:eee:ecmode:v:71:y:2018:i:c:p:25-33
    DOI: 10.1016/j.econmod.2017.11.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999317303127
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2017.11.018?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ron A. Boschma & Michael Fritsch, 2009. "Creative Class and Regional Growth: Empirical Evidence from Seven European Countries," Economic Geography, Taylor & Francis Journals, vol. 85(4), pages 391-423, October.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Jason Potts & Stuart Cunningham & John Hartley & Paul Ormerod, 2008. "Social network markets: a new definition of the creative industries," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 32(3), pages 167-185, September.
    4. Victor Podinovski & Emmanuel Thanassoulis, 2007. "Improving discrimination in data envelopment analysis: some practical suggestions," Journal of Productivity Analysis, Springer, vol. 28(1), pages 117-126, October.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Ungkyu Han & Mette Asmild & Martin Kunc, 2016. "Regional R&D Efficiency in Korea from Static and Dynamic Perspectives," Regional Studies, Taylor & Francis Journals, vol. 50(7), pages 1170-1184, July.
    7. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    8. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    9. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    10. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    11. Malin Song & Jun Tao & Shuhong Wang, 2015. "FDI, technology spillovers and green innovation in China: analysis based on Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 228(1), pages 47-64, May.
    12. Mei Xue & Patrick T. Harker, 2002. "Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models," Management Science, INFORMS, vol. 48(5), pages 705-710, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Francisco Benita, 2019. "A New Measure of Transport Disadvantage for the Developing World Using Free Smartphone Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 415-435, August.
    2. Hwayoon Seok & Yoonjae Nam, 2022. "A Social Network Analysis of International Creative Goods Flow," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    3. Wu, Yueh-Cheng & Lin, Sheng-Wei, 2022. "Efficiency evaluation of Asia's cultural tourism using a dynamic DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Alfonso Mendoza-Velázquez & Francisco Benita, 2019. "Efficiency, Productivity, and Congestion Performance: Analysis of the Automotive Cluster in Mexico," Journal of Industry, Competition and Trade, Springer, vol. 19(4), pages 661-678, December.

    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. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    2. Hisham Alidrisi & Mehmet Emin Aydin & Abdullah Omer Bafail & Reda Abdulal & Shoukath Ali Karuvatt, 2019. "Monitoring the Performance of Petrochemical Organizations in Saudi Arabia Using Data Envelopment Analysis," Mathematics, MDPI, vol. 7(6), pages 1-16, June.
    3. Congcong Yang & Alfred Taudes & Guozhi Dong, 2017. "Efficiency analysis of European Freight Villages: three peers for benchmarking," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 91-122, March.
    4. Li, Yongjun & Liu, Jin & Ang, Sheng & Yang, Feng, 2021. "Performance evaluation of two-stage network structures with fixed-sum outputs: An application to the 2018winter Olympic Games," Omega, Elsevier, vol. 102(C).
    5. Ruiz, José L. & Sirvent, Inmaculada, 2016. "Common benchmarking and ranking of units with DEA," Omega, Elsevier, vol. 65(C), pages 1-9.
    6. Holý, Vladimír, 2024. "Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education," Operations Research Perspectives, Elsevier, vol. 12(C).
    7. Kottas, Angelos T. & Madas, Michael A., 2018. "Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 1-17.
    8. Michael Kourtis & Panayiotis Curtis & Michael Hanias & Eleftherios Kourtis, 2021. "A Strategic Financial Management Evaluation of Private Hospitals’ Effectiveness and Efficiency for Sustainable Financing: A Research Study," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 1025-1054.
    9. Catarina Alexandra Neves Proença & Maria Elisabete Duarte Neves & Maria Castelo Baptista Gouveia & Mara Teresa Silva Madaleno, 2023. "Technological, healthcare and consumer funds efficiency: influence of COVID-19," Operational Research, Springer, vol. 23(2), pages 1-42, June.
    10. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    11. Gouveia, M.C. & Dias, L.C. & Antunes, C.H. & Boucinha, J. & Inácio, C.F., 2015. "Benchmarking of maintenance and outage repair in an electricity distribution company using the value-based DEA method," Omega, Elsevier, vol. 53(C), pages 104-114.
    12. Gouveia, M.C. & Henriques, C.O. & Costa, P., 2021. "Evaluating the efficiency of structural funds: An application in the competitiveness of SMEs across different EU beneficiary regions," Omega, Elsevier, vol. 101(C).
    13. Mariano, Enzo Barberio & Sobreiro, Vinicius Amorim & Rebelatto, Daisy Aparecida do Nascimento, 2015. "Human development and data envelopment analysis: A structured literature review," Omega, Elsevier, vol. 54(C), pages 33-49.
    14. An, Qingxian & Tao, Xiangyang & Xiong, Beibei, 2021. "Benchmarking with data envelopment analysis: An agency perspective," Omega, Elsevier, vol. 101(C).
    15. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.
    16. Ying Li & Yung-Ho Chiu & Tai-Yu Lin & Tzu-Han Chang, 2020. "Pre-Evaluating the Technical Efficiency Gains from Potential Mergers and Acquisitions in the IC Design Industry," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 525-559, April.
    17. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(C).
    18. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    19. Cheng, Gang & Zervopoulos, Panagiotis, 2012. "A proxy approach to dealing with the infeasibility problem in super-efficiency data envelopment analysis," MPRA Paper 42064, University Library of Munich, Germany.
    20. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.

    More about this item

    Keywords

    Creative industries; Metropolitan areas; DEA; 3Ts model; Malmquist productivity index; Mexico;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    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:eee:ecmode:v:71:y:2018:i:c:p:25-33. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.