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  • G Johnes

Abstract

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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Bibliographic Info

Paper provided by Lancaster University Management School, Economics Department in its series Working Papers with number 541985.

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Date of creation: 2003
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Handle: RePEc:lan:wpaper:541985

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  1. Blanchflower, D. & Oswald, A. & Garrett, M., 1988. "Insider Power In Wage Determination," Papers, London School of Economics - Centre for Labour Economics 319, London School of Economics - Centre for Labour Economics.
  2. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, Econometric Society, vol. 47(1), pages 153-61, January.
  3. Blundell, Richard, et al, 2000. "The Returns to Higher Education in Britain: Evidence from a British Cohort," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 110(461), pages F82-99, February.
  4. Akerlof, George A, 1998. "Men without Children," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 108(447), pages 287-309, March.
  5. 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.
  6. Spence, A Michael, 1973. "Job Market Signaling," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 87(3), pages 355-74, August.
  7. Grubb, W. Norton, 1993. "Further tests of screening on education and observed ability," Economics of Education Review, Elsevier, Elsevier, vol. 12(2), pages 125-136, June.
  8. Joseph G. Altonji, 1992. "The Effects of High School Curriculum on Education and Labor Market Outcomes," NBER Working Papers 4142, National Bureau of Economic Research, Inc.
  9. 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 433-55, July.
  10. Cohn, Elchanan & Kiker, B. F. & De Oliveira, M. Mendes, 1987. "Further evidence on the screening hypothesis," Economics Letters, Elsevier, Elsevier, vol. 25(3), pages 289-294.
  11. Geraint Johnes, 2000. "Up Around the Bend: Linear and nonlinear models of the UK economy compared," International Review of Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 14(4), pages 485-493.
  12. 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, American Statistical Association, vol. 13(2), pages 137-49, April.
  13. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, July.
  14. Geraint Johnes, 1998. "Human capital versus sorting: new data and a new test," Applied Economics Letters, Taylor & Francis Journals, Taylor & Francis Journals, vol. 5(2), pages 85-87.
  15. 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, Elsevier, vol. 13(4), pages 439-461, December.
  16. Andrew K.G. Hildreth and Andrew J. Oswald, . "Rent-Sharing and Wages: Evidence from Company and Establishment Panels," Economics Discussion Papers, University of Essex, Department of Economics 425, University of Essex, Department of Economics.
  17. Wolpin, Kenneth I, 1977. "Education and Screening," American Economic Review, American Economic Association, American Economic Association, vol. 67(5), pages 949-58, December.
  18. Curry, B. & Morgan, P., 1997. "Neural networks: a need for caution," Omega, Elsevier, Elsevier, vol. 25(1), pages 123-133, February.
  19. 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, London School of Economics and Political Science, vol. 67(265), pages 19-35, February.
  20. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 8(2), pages 202-29, April.
  21. Arrow, Kenneth J., 1973. "Higher education as a filter," Journal of Public Economics, Elsevier, Elsevier, vol. 2(3), pages 193-216, July.
  22. Harmon, Colm & Walker, Ian, 1995. "Estimates of the Economic Return to Schooling for the United Kingdom," American Economic Review, American Economic Association, American Economic Association, vol. 85(5), pages 1278-86, December.
  23. 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 1141-77, September.
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Cited by:
  1. Sally Atkins-Burnett, 2007. "Measuring Children's Progress from Preschool Through Third Grade," Mathematica Policy Research Reports, Mathematica Policy Research 5687, Mathematica Policy Research.

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