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Trend, Cycles and Chance

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  • Claude Diebolt

    (University of Strasbourg, Strasbourg, France)

Abstract

This paper is about the book Trend, Zyklus und Zufall. Bestimmungsgründe und Verlaufsformen langfristiger Wachstumsschwankungen (2002) written by Rainer Metz. It rehabilitates Metz’s somewhat forgotten milestone in the quantitative history literature on economic cycles. For me, it represents an indispensable standard work for anyone who wants to work in this field.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Claude Diebolt, 2021. "Trend, Cycles and Chance," Working Papers 05-21, Association Française de Cliométrie (AFC).
    • Handle: RePEc:afc:wpaper:05-21
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    File URL: https://www.cliometrie.org/images/wp/AFC_WP_05_2021.pdf
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    References listed on IDEAS

    as
    1. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    2. Claude Diebolt, 2016. "Cliometrica after 10 years: definition and principles of cliometric research," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 10(1), pages 1-4, january.
    3. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    4. Choi, In & Phillips, Peter C. B., 1993. "Testing for a unit root by frequency domain regression," Journal of Econometrics, Elsevier, vol. 59(3), pages 263-286, October.
    5. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    6. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    7. Kahn, James A. & Ogaki, Masao, 1990. "A chi-square test for a unit root," Economics Letters, Elsevier, vol. 34(1), pages 37-42, September.
    8. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    9. Perron, Pierre, 1988. "Trends and random walks in macroeconomic time series : Further evidence from a new approach," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 297-332.
    10. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    11. Claude Diebolt & Michael Haupert (ed.), 2019. "Handbook of Cliometrics," Springer Books, Springer, edition 2, number 978-3-030-00181-0, June.
    12. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    13. Dickey, David A & Pantula, Sastry G, 1987. "Determining the Ordering of Differencing in Autoregressive Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 455-461, October.
    14. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    15. Durlauf, Steven N., 1993. "Time series properties of aggregate output fluctuations," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 39-56, March.
    16. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
    17. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    Cited by:

    1. Ralph Hippe & Damien Demailly & Claude Diebolt, 2022. "The Digital Transition for a Sustainable Mobility Regime? A Long-Run Perspective," Working Papers of BETA 2022-19, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • N01 - Economic History - - General - - - Development of the Discipline: Historiographical; Sources and Methods
    • N14 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Europe: 1913-

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