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Computer knowledge and earnings: evidence for Australia

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  • Jeff Borland
  • Joseph Hirschberg
  • Jenny Lye

Abstract

This paper uses data on wage and salary workers in Australia in 1993 to examine the relation between computer knowledge and earnings. A unique feature of the data set that is used is detailed information on the types and levels of computer skills possessed by individual workers. The main objectives of the study are to contribute to understanding the magnitude and sources of the relation between computer knowledge and earnings. Similar to existing research it is found that there is a large and significant return to computer knowledge, but that the magnitude of the return is substantially reduced in regressions that include detailed occupation controls. Using the detailed information on workers' computer skills the main finding is that earnings are significantly positively related to the number of types of skills and average level of skills possessed by a worker.

Suggested Citation

  • Jeff Borland & Joseph Hirschberg & Jenny Lye, 2004. "Computer knowledge and earnings: evidence for Australia," Applied Economics, Taylor & Francis Journals, vol. 36(17), pages 1979-1993.
    • Handle: RePEc:taf:applec:v:36:y:2004:i:17:p:1979-1993
    DOI: 10.1080/00036840410001710654
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    Cited by:

    1. Bruce Chapman & James Jordan & Ken Olivier & John Quiggin, 2000. "The Unemployment Trap Meets the Age-Earning Profile," CEPR Discussion Papers 415, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    2. Jeff Borland, 1999. "Earnings Inequality in Australia: Changes, Causes and Consequences," The Economic Record, The Economic Society of Australia, vol. 75(2), pages 177-202, June.
    3. Federico Biagi & Danilo Cavapozzi & Raffaele Miniaci, 2013. "Employment transitions and computer use of older workers," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 687-696, February.
    4. Joaquin Marandino & Phanindra V. Wunnava, 2017. "The Effect of Access to Information and Communication Technology on Household Labor Income: Evidence from One Laptop Per Child in Uruguay," Economies, MDPI, vol. 5(3), pages 1-10, September.
    5. Jenny N. Lye & Joseph G. Hirschberg, 2002. "Tests of Inference for Dummy Variables in Regressions with Logarithmic Transformed Dependent Variables," Department of Economics - Working Papers Series 852, The University of Melbourne.
    6. Vinod Mishra & Russell Smyth, 2014. "Technological Change and Wages in China: Evidence from Matched Employer–Employee Data," Review of Development Economics, Wiley Blackwell, vol. 18(1), pages 123-138, February.
    7. Bruce Chapman & Cezary Kapuscinski, 2000. "Avoiding Recessions and Australian Long-Term Unemployment," CEPR Discussion Papers 418, Centre for Economic Policy Research, Research School of Economics, Australian National University.

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    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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