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Globalization and productivity: A robust nonparametric world frontier analysis

Author

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  • Mastromarco, Camilla
  • Simar, Leopold

Abstract

How to exit the economic recession and improve the economic condition in a globalized world is a central policy issue of importance. This paper examines whether countries that pursue outward orientation policies and that are increasingly economically integrated with the rest of the world have seen an increase in economic performance. Increasing globalization and interconnection among countries generates spatial and temporal dependence which will affect the production process of each country. We extend existing methodological tools – robust frontier in non parametric location-scale models - to estimate the world frontier of 44 countries over 1970–2007 and to obtain more reliable measure of productivity and efficiency to better investigate the driven forces behind the catching-up productivity process among countries. We explore the channels under which Foreign Direct Investment (FDI) and time affect the production process and its components: impact on the attainable production set (input-output space), and the impact on the distribution of efficiencies.
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Suggested Citation

  • Mastromarco, Camilla & Simar, Leopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," LIDAM Reprints ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2018008
    Note: In : Economic Modelling, vol. 69, p. 134–149 (2018)
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    Cited by:

    1. Richard Gearhart & Nyakundi Michieka, 2020. "A non-parametric investigation of supply side factors and healthcare efficiency in the U.S," Journal of Productivity Analysis, Springer, vol. 54(1), pages 59-74, August.
    2. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
    3. Paul W. Wilson & Shirong Zhao, 2025. "A non-parametric analysis of world productivity growth, 1990–2019," Annals of Operations Research, Springer, vol. 346(3), pages 2253-2285, March.
    4. Camilla Mastromarco & Léopold Simar & Valentin Zelenyuk, 2021. "Predicting recessions with a frontier measure of output gap: an application to Italian economy," Empirical Economics, Springer, vol. 60(6), pages 2701-2740, June.
    5. José Manuel Cordero & Carlos Díaz Caro & Francisco Pedraja Chaparro & Cristina Polo Fernández, 2020. "Tributos cedidos y eficiencia en la gestión tributaria de las Comunidades Autónomas," Hacienda Pública Española / Review of Public Economics, IEF, vol. 232(1), pages 75-112, March.
    6. Cordero, Jose Manuel & Polo, Cristina & Simancas, Rosa, 2022. "Assessing the efficiency of secondary schools: Evidence from OECD countries participating in PISA 2015," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    7. Michael L. Polemis, 2020. "A note on the estimation of competition-productivity nexus: a panel quantile approach," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 663-676, December.
    8. Nickolaos G. Tzeremes, 2019. "Technological change, technological catch-up and export orientation: evidence from Latin American Countries," Journal of Productivity Analysis, Springer, vol. 52(1), pages 85-100, December.
    9. Camilla Mastromarco & Léopold Simar & Valentin Zelenyuk, 2019. "Predicting Recessions: A New Measure of Output Gap as Predictor," CEPA Working Papers Series WP112019, School of Economics, University of Queensland, Australia.
    10. Daraio, Cinzia & Simar, Léopold & Wilson, Paul W., 2021. "Quality as a latent heterogeneity factor in the efficiency of universities," Economic Modelling, Elsevier, vol. 99(C).
    11. Makiela, Kamil & Ouattara, Bazoumana, 2018. "Foreign direct investment and economic growth: Exploring the transmission channels," Economic Modelling, Elsevier, vol. 72(C), pages 296-305.
    12. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.
    13. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    14. Fall, François Seck & Tchakoute Tchuigoua, Hubert & Vanhems, Anne & Simar, Léopold, 2024. "A panel analysis of microfinance efficiency measures: Evidence on the effects of unobserved managerial ability," LIDAM Discussion Papers ISBA 2024020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Michael L. Polemis & Thanasis Stengos & Nickolaos G. Tzeremes, 2020. "Modeling the effect of competition on US manufacturing sectors’ efficiency: an order-m frontier analysis," Journal of Productivity Analysis, Springer, vol. 54(1), pages 27-41, August.
    16. Zike Qi, 2024. "A Simulation of the Necessary Total Factor Productivity Growth and Its Feasible Dual Circulation Source Pathways to Achieve China’s 2035—Economic Goals: A Dynamic Computational General Equilibrium Stu," Sustainability, MDPI, vol. 16(18), pages 1-41, September.
    17. Marco A. DeBenedetto & Michele G. Giuranno & Camilla Mastromarco & Diego Ravenda & Pierluigi Toma, 2024. "Legality rating and corporate efficiency: evidence from a conditional nonparametric frontier analysis," Empirical Economics, Springer, vol. 66(5), pages 2137-2168, May.
    18. Gearhart, Richard & Michieka, Nyakundi, 2019. "Natural resource abundance and healthcare efficiency in Appalachia: A robust conditional approach," Energy Policy, Elsevier, vol. 129(C), pages 985-996.
    19. Sushanta Mallick & Aarti Rughoo & Nickolaos G. Tzeremes & Wei Xu, 2020. "Technological Change and Catching-Up in the Indian Banking Sector: A Time-Dependent Nonparametric Frontier Approach," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 217-237, June.
    20. Gearhart, Richard S. & Michieka, Nyakundi M., 2018. "A comparison of the robust conditional order-m estimation and two stage DEA in measuring healthcare efficiency among California counties," Economic Modelling, Elsevier, vol. 73(C), pages 395-406.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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