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Identification of Liechtenstein's Historic Economic Growth and Business Cycles by Econometric Extensions of Data Series

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  • Brunhart, Andreas

Abstract

Several economic data series of Liechtenstein are backwardly estimated in order to achieve consistent historic time series. The generated series consist for instance of the national income for the years 1954 to 1992 (by regressive inter- and retropolation with indicators) and 1993 to 1997 (by approximative computation after national accounting scheme). Also, the sectoral and total employment of some missing years in the 70s, 80s and 90s is complemented and the gross domestic product from 1972 until 1997 is provided by an approximative computation/estimation relying on the identity of the generation of income account as part of the national accounts. These methods and the presented series are being evaluated with respect to their accuracy, which turns out to be satisfying, and can be linked with the released results from the official national accounts, which were introduced for the year 1998 and have been published until 2009 so far. Along with the provision of these figures, Liechtenstein’s economic growth pattern is being identified, the business cycles are detected and first analytical insights are obtained.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 44628.

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Date of creation: 20 Nov 2012
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Handle: RePEc:pra:mprapa:44628

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Keywords: Economic Growth; Business Cycles; Liechtenstein; Regressive Interpolation and Retropolation; Multiple Imputation; National Accounts;

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  1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, Elsevier, vol. 54(1-3), pages 159-178.
  2. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(6), pages 601-18, Nov.-Dec..
  3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, Econometric Society, vol. 37(3), pages 424-38, July.
  4. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, Wiley Blackwell, vol. 17(31), pages 334-55, December.
  5. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 12(2-3), pages 231-254.
  6. Andreas, Brunhart, 2011. "Stock market’s reactions to revelation of tax evasion: an empirical assessment," MPRA Paper 42047, University Library of Munich, Germany, revised Sep 2012.
  7. Durbin, J, 1970. "Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables," Econometrica, Econometric Society, Econometric Society, vol. 38(3), pages 410-21, May.
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