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Endogenous Skill Biased Technical Change: Testing For Demand Pull Effect

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  • Francesco Bogliacino.
  • Matteo Lucchesex

Abstract

In this article we use the unification of Germany in 1990 to test the hypothesis that an increase in the supply of a production factor generates skill biased technical change. We test for this mechanism in the context of the model presented by Acemoglu and Autor (2011) that allows endogenous assignment of skills to tasks in the economy. We use cohorts of workers from comparable countries as a control group. After discussing the possible confounding factors, we conclude that this effect is absent. The differential pattern among the countries seems to be determined by labor market flexibilization and tax reform.

Suggested Citation

  • Francesco Bogliacino. & Matteo Lucchesex, 2015. "Endogenous Skill Biased Technical Change: Testing For Demand Pull Effect," Documentos de Trabajo, Escuela de Economía 12618, Universidad Nacional de Colombia, FCE, CID.
    • Handle: RePEc:col:000178:012618
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    11. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
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    Cited by:

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    2. Gabriele Ballarino & Francesco Bogliacino & Michela Braga & Massimiliano Bratti & Daniele Checchi & Antonio Filippin & Virginia Maestri & Elena Meschi & Francesco Scervini, 2012. "GINI Intermediate Report WP 3: Drivers of Growing Inequality," GINI Discussion Papers wp3, AIAS, Amsterdam Institute for Advanced Labour Studies.
    3. Marouani, Mohamed A. & Nilsson, Björn, 2016. "The labor market effects of skill-biased technological change in Malaysia," Economic Modelling, Elsevier, vol. 57(C), pages 55-75.
    4. Aldo Josafat Torres García & Gloria Lizeth Ochoa Adame, 2018. "Desigualdad salarial asociada al uso de las TIC en México: un análisis por ocupaciones," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(74), pages 353-390, July.
    5. Francesco Bogliacino & Dario Guarascio & Valeria Cirillo, 2015. "Where Does the Surplus Go? Disentangling the Capital-Labor Distributive Conflict," Documentos de Trabajo, Escuela de Economía 13535, Universidad Nacional de Colombia, FCE, CID.
    6. Francesco Bogliacino & Dario Guarascio & Valeria Cirillo, 2018. "The dynamics of profits and wages: technology, offshoring and demand," Industry and Innovation, Taylor & Francis Journals, vol. 25(8), pages 778-808, September.
    7. Laura Barbieri & Mariacristina Piva & Marco Vivarelli, 2016. "The Employment Impact of Different Forms of Innovation: Evidence from Italian Community Innovation Survey," DISCE - Quaderni del Dipartimento di Scienze Economiche e Sociali dises1620, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. Aldo Josafat Torres García & Gloria Lizeth Ochoa Adame, 2018. "Desigualdad salarial asociada al uso de TIC en México: un análisis por ocupaciones," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(74), pages 353-390, July.
    9. Oscar Afonso & Tiago Sequeira & Derick Almeida, 2023. "Technological knowledge and wages: from skill premium to wage polarization," Journal of Economics, Springer, vol. 140(2), pages 93-119, October.
    10. Strohmaier, R. & Rainer, A., 2016. "Studying general purpose technologies in a multi-sector framework: The case of ICT in Denmark," Structural Change and Economic Dynamics, Elsevier, vol. 36(C), pages 34-49.
    11. Laura Barbieri & Mariacristina Piva & Marco Vivarelli, 2019. "R&D, embodied technological change, and employment: evidence from Italian microdata," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(1), pages 203-218.
    12. Leibrecht, Markus & Scharler, Johann & Zhoufu, Yan, 2023. "Automation and unemployment: Does collective bargaining moderate their association?," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 264-276.
    13. Jelena Reljic & Rinaldo Evangelista & Mario Pianta, 2019. "Digital technologies, employment and skills," LEM Papers Series 2019/36, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    15. Van Roy, Vincent & Vértesy, Dániel & Vivarelli, Marco, 2018. "Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms," Research Policy, Elsevier, vol. 47(9), pages 1762-1776.
    16. Guarascio, Dario & Gualtieri, Valentina & Quaranta, Roberto, 2018. "Does routinization affect occupation dynamics? Evidence from the ‘Italian O*Net’ data," MPRA Paper 89585, University Library of Munich, Germany.
    17. Marta Fana & CIRILLO Valeria & GUARASCIO Dario & TUBIANA Matteo, 2020. "A Comparative national tasks database," JRC Working Papers on Labour, Education and Technology 2020-13, Joint Research Centre.

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    More about this item

    Keywords

    Skill Biased Technological Change; Polarization; Natural Experiment.;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe

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