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  • G Johnes


Regression and neural network models of wage determination are constructed where the explanatory variables include detailed information about the impact of school curricula on future earnings. It is established that there are strong nonlinearities and interaction effects present in the relationship between curriculum and earnings. The results have important implications in the context of the human capital versus signalling and screening debate. They also throw light on contemporary policy issues concerning the desirability of breadth versus depth in the school curriculum

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  • G Johnes, 2003. "Curriculum," Working Papers 541985, Lancaster University Management School, Economics Department.
  • Handle: RePEc:lan:wpaper:541985

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    1. Hildreth, Andrew K G & Oswald, Andrew J, 1997. "Rent-Sharing and Wages: Evidence from Company and Establishment Panels," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 318-337, April.
    2. Levine, Phillip B & Zimmerman, David J, 1995. "The Benefit of Additional High-School Math and Science Classes for Young Men and Women," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 137-149, April.
    3. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, vol. 8(2), pages 202-229, April.
    4. Akerlof, George A, 1998. "Men without Children," Economic Journal, Royal Economic Society, vol. 108(447), pages 287-309, March.
    5. Harmon, Colm & Walker, Ian, 2000. "The Returns to the Quantity and Quality of Education: Evidence for Men in England and Wales," Economica, London School of Economics and Political Science, vol. 67(265), pages 19-35, February.
    6. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters,in: Schooling, Experience, and Earnings, pages 1-4 National Bureau of Economic Research, Inc.
    7. Blundell, Richard, et al, 2000. "The Returns to Higher Education in Britain: Evidence from a British Cohort," Economic Journal, Royal Economic Society, vol. 110(461), pages 82-99, February.
    8. Joseph G. Altonji, 1995. "The Effects of High School Curriculum on Education and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 30(3), pages 409-438.
    9. Geraint Johnes, 2000. "Up Around the Bend: Linear and nonlinear models of the UK economy compared," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(4), pages 485-493.
    10. Cohn, Elchanan & Kiker, B. F. & De Oliveira, M. Mendes, 1987. "Further evidence on the screening hypothesis," Economics Letters, Elsevier, vol. 25(3), pages 289-294.
    11. Harmon, Colm & Walker, Ian, 1995. "Estimates of the Economic Return to Schooling for the United Kingdom," American Economic Review, American Economic Association, vol. 85(5), pages 1278-1286, December.
    12. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    13. Geraint Johnes, 1998. "Human capital versus sorting: new data and a new test," Applied Economics Letters, Taylor & Francis Journals, vol. 5(10), pages 665-667.
    14. Grubb, W. Norton, 1993. "Further tests of screening on education and observed ability," Economics of Education Review, Elsevier, vol. 12(2), pages 125-136, June.
    15. Wolpin, Kenneth I, 1977. "Education and Screening," American Economic Review, American Economic Association, vol. 67(5), pages 949-958, December.
    16. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, January.
    17. Blanchflower, David G & Oswald, Andrew J & Garrett, Mario D, 1990. "Insider Power in Wage Determination," Economica, London School of Economics and Political Science, vol. 57(226), pages 143-170, May.
    18. Green, Francis & Machin, Stephen & Manning, Alan, 1996. "The Employer Size-Wage Effect: Can Dynamic Monopsony Provide an Explanation?," Oxford Economic Papers, Oxford University Press, vol. 48(3), pages 433-455, July.
    19. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-1177, September.
    20. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    21. Arrow, Kenneth J., 1973. "Higher education as a filter," Journal of Public Economics, Elsevier, vol. 2(3), pages 193-216, July.
    22. Curry, B. & Morgan, P., 1997. "Neural networks: a need for caution," Omega, Elsevier, vol. 25(1), pages 123-133, February.
    23. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, Oxford University Press, vol. 87(3), pages 355-374.
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    curriculum; earnings; neural networks;


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