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Structural change and wage inequality in the manufacturing sector: long run evidence from East Asia

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  • Bruno Martorano
  • Marco Sanfilippo

Abstract

This paper analyses the long run determinants of wage inequality in the manufacturing sector for a group of East Asian countries that have experienced rapid structural transformations over the last decades. In line with the Skill Biased Technological Change hypothesis, our results show that within manufacturing structural change –fostering the participation of higher skilled workers – is a strong determinant of the wage premium. However, the paper highlights also the peculiarity of the East Asian model, which shows how well-designed education policies, a prudent macroeconomic management and selective policies towards foreign capital can contribute to buffer the pressure of structural change on wage inequality, even in an open economy context.

Suggested Citation

  • Bruno Martorano & Marco Sanfilippo, 2014. "Structural change and wage inequality in the manufacturing sector: long run evidence from East Asia," Working Papers - Economics wp2014_09.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    • Handle: RePEc:frz:wpaper:wp2014_09.rdf
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    Cited by:

    1. Haraguchi, Nobuya & Martorano, Bruno & Sanfilippo, Marco, 2019. "What factors drive successful industrialization? Evidence and implications for developing countries," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 266-276.
    2. Gnangnon, Sèna Kimm, 2020. "Aid for Trade flows and Wage Inequality in the manufacturing sector of recipient-countries," EconStor Preprints 213936, ZBW - Leibniz Information Centre for Economics.
    3. Thanos Fragkandreas, 2022. "Three Decades of Research on Innovation and Inequality: Causal Scenarios, Explanatory Factors, and Suggestions," Working Papers 60, Birkbeck Centre for Innovation Management Research, revised Feb 2022.
    4. R, Rekha & M, Suresh Babu, 2022. "Premature deindustrialisation and growth slowdowns in middle-income countries," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 377-389.
    5. Xiao Dai & Liang Yan & Liu Jianping & JianWu, 2022. "A research on the threshold effect of human capital structure upgrading and industrial structure upgrading—based on the perspective of path dependence," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2645-2674, August.
    6. Ricardo Luiz Machado & Thiago Vizine da Cruz, 2022. "An Empirical Approach Analyzing the Socioeconomic Sustainability of the International Sugarcane Trade," Sustainability, MDPI, vol. 14(4), pages 1-16, February.
    7. Bruno Martorano & Donghyun Park & Marco Sanfilippo, 2017. "Catching-up, structural transformation, and inequality: industry-level evidence from Asia," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(4), pages 555-570.
    8. Weiping Li & Saite Lu, 2024. "Assessing Structural Transformation and the Potential Impacts of Belt and Road Initiative Projects in Africa," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(3), pages 548-570, June.

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    More about this item

    Keywords

    Structural change; Wage Inequality; East Asia;
    All these keywords.

    JEL classification:

    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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