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Aggregation, Unit Roots and the Time Series Structure on Manufacturing Real Wages

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  • Rossana, Robert J
  • Seater, John J

Abstract

The effects of both temporal and cross-sectional aggregation on the estimated time-series characteristics of manufacturing real wage data are examined. The effects, especially of temporal aggregation, are found to be quite large and in accord with statistical theory. The well-known results of J. Altonji and O. Ashenfelter (1980), that real wages are a random walk, and of C. R. Nelson and C. I. Plosser (1982), that real wages are an IMA(1, 1) process, both seem to be entirely artifacts of temporal aggregation, with the true models following processes that are much more complex and that display substantial cyclical behavior. Copyright 1992 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Rossana, Robert J & Seater, John J, 1992. "Aggregation, Unit Roots and the Time Series Structure on Manufacturing Real Wages," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 159-179, February.
    • Handle: RePEc:ier:iecrev:v:33:y:1992:i:1:p:159-79
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    Cited by:

    1. Choi, Chi-Young & Mark, Nelson C. & Sul, Donggyu, 2006. "Unbiased Estimation of the Half-Life to PPP Convergence in Panel Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 921-938, June.
    2. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    3. Aadland, David, 2005. "Detrending time-aggregated data," Economics Letters, Elsevier, vol. 89(3), pages 287-293, December.
    4. Casson, Catherine & Fry, J. M. & Casson, Mark, 2011. "Evolution or revolution? a study of price and wage volatility in England, 1200-1900," MPRA Paper 31518, University Library of Munich, Germany.
    5. Hari Luitel & Mehmet Tosun, 2014. "A reexamination of state fiscal health and amnesty enactment," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 21(5), pages 874-893, October.
    6. Ivan Paya & Agustin Duarte & Ken Holden, 2007. "On the Relationship between Inflation Persistence and Temporal Aggregation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1521-1531, September.
    7. Kőrösi, Gábor & Lovrics, László & Mátyás, László, 1995. "Aggregation and the long run properties of economic time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 279-286.
    8. Fleissig, Adrian R. & Strauss, Jack, 1997. "Unit root tests on real wage panel data for the G7," Economics Letters, Elsevier, vol. 56(2), pages 149-155, October.
    9. Yamin Ahmad & Ivan Paya, 2014. "Temporal Aggregation of Random Walk Processes and Implications for Asset Prices," Working Papers 14-01, UW-Whitewater, Department of Economics.
    10. Markus Eberhardt & Francis Teal, 2010. "Aggregation versus Heterogeneity in Cross-Country Growth Empirics," CSAE Working Paper Series 2010-32, Centre for the Study of African Economies, University of Oxford.
    11. Casson, Catherine & Fry, J. M., 2011. "Revolutionary change and structural breaks: A time series analysis of wages and commodity prices in Britain 1264-1913," MPRA Paper 27866, University Library of Munich, Germany.
    12. repec:lan:wpaper:2606 is not listed on IDEAS
    13. repec:lan:wpaper:2464 is not listed on IDEAS
    14. Gulasekaran Rajaguru & Michael O’Neill & Tilak Abeysinghe, 2018. "Does Systematic Sampling Preserve Granger Causality with an Application to High Frequency Financial Data?," Econometrics, MDPI, vol. 6(2), pages 1-24, June.

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