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Estimating Monthly GDP In A General Kalman Filter Framework: Evidence From Switzerland




In this paper, we estimate deseasonalized monthly series for Swiss Gross Domestic Product at constant prices of 1990 for the period 1980-1998. They are consistent with the quarterly figures estimated by the Federal Office for Economic Development and Labour and are obtained by including information contained in related series. We present a general approach using the Kalman Filter technique nesting a great variety of interpolation setups. We evaluate competing models and provide a time series that can be used by other researchers.

Suggested Citation

  • Nicolas A. Cuche & Martin K. Hess, 1999. "Estimating Monthly GDP In A General Kalman Filter Framework: Evidence From Switzerland," Working Papers 99.02, Swiss National Bank, Study Center Gerzensee.
  • Handle: RePEc:szg:worpap:9902

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    References listed on IDEAS

    1. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    2. Milton Friedman, 1962. "The Interpolation of Time Series by Related Series," NBER Books, National Bureau of Economic Research, Inc, number frie62-1, January.
    3. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    4. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
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    Cited by:

    1. International Monetary Fund, 2002. "Macroeconomic Adjustment in a Highly Dollarized Economy; The Case of Cambodia," IMF Working Papers 02/92, International Monetary Fund.
    2. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
    3. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    4. Issler, João Victor & Notini, Hilton Hostalacio, 2016. "Estimating Brazilian Monthly GDP: a State-Space Approach," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 70(1), March.
    5. Hess, Martin K., 2004. "Dynamic and asymmetric impacts of macroeconomic fundamentals on an integrated stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(5), pages 455-471, December.
    6. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    7. Byeongchan Seong & Sung K. Ahn & Peter Zadrozny, 2007. "Cointegration Analysis with Mixed-Frequency Data," CESifo Working Paper Series 1939, CESifo Group Munich.
    8. Dellas, Harris & Hess, Martin K, 2002. "Financial Development and the Sensitivity of Stock Markets to External Influences," Review of International Economics, Wiley Blackwell, vol. 10(3), pages 525-538, August.
    9. Konstantins Benkovskis, 2008. "Short-Term Forecasts of Latvia's Real Gross Domestic Product Growth Using Monthly Indicators," Working Papers 2008/05, Latvijas Banka.
    10. Jonas Stulz, 2007. "Exchange rate pass-through in Switzerland: Evidence from vector autoregressions," Economic Studies 2007-04, Swiss National Bank.
    11. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    12. Alexander Perruchoud, 2009. "Estimating a Taylor Rule with Markov Switching Regimes for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 145(II), pages 187-220, June.
    13. Rocío Elizondo, 2012. "Monthly GDP estimates based on the IGAE," Working Papers 2012-11, Banco de México.
    14. repec:bbz:fcpbbr:v:3:y:2006:i:1:p:1-14 is not listed on IDEAS
    15. Works, Richard & Haan, Perry, 2017. "An Empirical Study of Japanese and South Korean Exchange Rates Using the Sticky-Price Monetary Theory," MPRA Paper 77235, University Library of Munich, Germany.
    16. repec:voj:journl:v:63:y:2016:i:1:p:45-60 is not listed on IDEAS
    17. Ureche-Rangau, Loredana & Burietz, Aurore, 2013. "One crisis, two crises…the subprime crisis and the European sovereign debt problems," Economic Modelling, Elsevier, vol. 35(C), pages 35-44.
    18. Yueqing Jia, 2011. "A New Look at China’s Output Fluctuations: Quarterly GDP Estimation with an Unobserved Components Approach," Working Papers 2011-006, The George Washington University, Department of Economics, Research Program on Forecasting.

    More about this item


    Interpolation; Kalman filter; National accounting.;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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