IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp816.html
   My bibliography  Save this paper

Key Parameters and Efficiency of Mexican Manufacturing: Are There Still Differences between the North and the South? An Application of Nested and Stochastic Frontier Panel Data Models

Author

Listed:
  • Frauke G. Braun
  • Astrid Cullmann

Abstract

This study explores the prevalence and nature of the regional divide for the Mexican manufacturing production across sub-national regions. We utilize a unique panel of municipality-level data from the manufacturing sector. An important contribution is the use of different panel methods to account for latent regional characteristics and the computation of performance indicators for each municipality which will enable detailed regional rankings. Firstly, we apply nested panel methods to estimate regional production functions and to analyze production characteristics and scale economies. Subsequently, we use stochastic frontier analysis methods to test for productivity and efficiency differences in manufacturing throughout the country. Our results suggest that the economic structure and productivity of southern Mexico is considerably different from the centrally located manufacturing belt and the north. Remarkably, rankings based on nested panel and stochastic frontier estimations confirm very similar regional patterns. Nevertheless, efficiency varies strongly within states, indicating that 'islands of excellence' prevail in otherwise highly inefficient and lagging states.

Suggested Citation

  • Frauke G. Braun & Astrid Cullmann, 2008. "Key Parameters and Efficiency of Mexican Manufacturing: Are There Still Differences between the North and the South? An Application of Nested and Stochastic Frontier Panel Data Models," Discussion Papers of DIW Berlin 816, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp816
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.88646.de/dp816.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hanson, Gordon H., 1998. "Regional adjustment to trade liberalization," Regional Science and Urban Economics, Elsevier, vol. 28(4), pages 419-444, July.
    2. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    3. Yu Hsing, 1996. "An empirical estimation of regional production functions for the U.S. manufacturing industry," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 30(4), pages 351-358.
    4. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    5. 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.
    6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    7. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    8. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    9. Héctor Salgado Banda & Lorenzo Bernal Verdugo, 2011. "Multifactor productivity and its determinants: an empirical analysis for Mexican manufacturing," Journal of Productivity Analysis, Springer, vol. 36(3), pages 293-308, December.
    10. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, November.
    11. H. Baltagi, Badi & Heun Song, Seuck & Cheol Jung, Byoung, 2001. "The unbalanced nested error component regression model," Journal of Econometrics, Elsevier, vol. 101(2), pages 357-381, April.
    12. Garcia-Mila, Teresa & McGuire, Therese J & Porter, Robert H, 1996. "The Effect of Public Capital in State-Level Production Functions Reconsidered," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 177-180, February.
    13. 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.
    14. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    15. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275.
    16. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    17. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    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.
    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. Jaime A. Prudencio‐Vázquez & Esteban Fernandez Marquez & Fernando Rubiera Morollón, 2022. "Productivity and agglomeration economies in the manufacturing of the metropolitan areas of Mexico, 1998–2018," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(5), pages 1188-1200, October.

    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. 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.
    2. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    3. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    4. Tim J. Coelli, 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 219-245, December.
    5. Keller, Michael, 2020. "Wasted windfalls: Inefficiencies in health care spending in oil rich countries," Resources Policy, Elsevier, vol. 66(C).
    6. 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.
    7. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    8. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
    9. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    10. Julio Peña & Julio Aguirre & René Cerca D'amico, 2004. "Pesca demersal en Chile: eficiencia técnica y escalas de operación," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 119-160, June.
    11. 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).
    12. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    13. 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.
    14. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    15. Gian Carlo Scarsi, 1999. "Local Electricity Distribution in Italy: Comparative Efficiency Analysis and Methodological Cross-Checking," Working Papers 1999.16, Fondazione Eni Enrico Mattei.
    16. Eduardo Fé & Richard Hofler, 2013. "Count data stochastic frontier models, with an application to the patents–R&D relationship," Journal of Productivity Analysis, Springer, vol. 39(3), pages 271-284, June.
    17. Hailu, Kidanemariam Berhe & Tanaka, Makoto, 2015. "A “true” random effects stochastic frontier analysis for technical efficiency and heterogeneity: Evidence from manufacturing firms in Ethiopia," Economic Modelling, Elsevier, vol. 50(C), pages 179-192.
    18. 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.
    19. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2021. "What do we know from the vast literature on efficiency and productivity in healthcare? A Systematic Review and Bibliometric Analysis," CEPA Working Papers Series WP092021, School of Economics, University of Queensland, Australia.
    20. Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1996. "On the Use of Panel Data in Bayesian Stochastic Frontier Models," Other publications TiSEM d27e7bcf-bb16-457a-934a-a, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

    Mexico; Manufacturing; Efficiency Analysis; Stochastic Frontier Analysis; Panel Data Models;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:diw:diwwpp:dp816. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.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.