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Wage Inequality and Innovative Intelligence-Biased Technological Change

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  • Harashima, Taiji

Abstract

In this paper, “innovative intelligence–biased technological change” (IIBTC) is examined as an alternative to the traditional concept of skill-biased technological change (SBTC) as a source of increases in wage inequality. The innovative intelligence of ordinary or average workers is an important element in productivity and can be heterogeneous across workers. Because technologies are heterogeneous in that they have different characteristics and are used in different situations, some technologies are “innovative intelligence-biased” and are advantageous for workers with relatively high innovative intelligence. If IIBTC prevails over a certain period of time, these workers become additionally advantaged and thereby wage inequality will increase during the period.

Suggested Citation

  • Harashima, Taiji, 2017. "Wage Inequality and Innovative Intelligence-Biased Technological Change," MPRA Paper 82337, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:82337
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    References listed on IDEAS

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    1. Lawrence F. Katz & Kevin M. Murphy, 1992. "Changes in Relative Wages, 1963–1987: Supply and Demand Factors," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(1), pages 35-78.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    3. Wolfgang F. Stolper & Paul A. Samuelson, 1941. "Protection and Real Wages," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 9(1), pages 58-73.
    4. Pinelopi Koujianou Goldberg & Nina Pavcnik, 2007. "Distributional Effects of Globalization in Developing Countries," Journal of Economic Literature, American Economic Association, vol. 45(1), pages 39-82, March.
    5. David Card & John E. DiNardo, 2002. "Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
    6. Harashima, Taiji, 2017. "A Theory on the Economic Impacts of Immigration," MPRA Paper 78821, University Library of Munich, Germany.
    7. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1169-1213.
    8. Harashima, Taiji, 2009. "A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element," MPRA Paper 15508, University Library of Munich, Germany.
    9. Harashima, Taiji, 2012. "A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence," MPRA Paper 43151, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Wage inequality; Innovative intelligence; Technological change; Total factor productivity; Approximate effective production function;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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