Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2013 | nr 93 Expectations and Forecasting | 45--69
Tytuł artykułu

End-of-sample vs. Real Time Data: Perspectives for Analysisof Expectations,

Warianty tytułu
Języki publikacji
Data revision is usually defined as an adjustment published after initial value had been announced; it may reflect rectification of errors, availability of new information, introduction of new measurement or aggregation techniques etc. This paper addresses the impact of data revisions on measures of expectations and offers an introduction to empirical analysis of data vintage in testing properties of expectations. It also defines and classifies data revisions and presents a review of literature and databases available for the purposes of real time analysis.(original abstract)
Słowa kluczowe
  • Szkoła Główna Handlowa w Warszawie
  • Arnold, E. A. (2012). The Role of Revisions and Uncertainty in Professional Forecasts. Paper presented at the National Bank of Poland Workshop 'Are We Really Forward-Looking? Measuring and Testing Expectations - Central Bank Perspective', Warszawa.
  • Beetsma, R., Giuliodori, M., Wierts, P. (2009). Planning to cheat: EU fiscal policy in real time. "Economic Policy", 24, 753-804.
  • Bernoth, K., Hughes Hallett, A., Lewis, J. (2008). Did fiscal policy makers know what they were doing? Reassessing fiscal policy with real time data. CEPR Discussion Paper, 6758.
  • Borağan Aruoba, S. (2008). Data revisions are not well-behaved. "Journal of Money, Credit and Banking", 40, 319-340.
  • Central Statistical Office (2007). Gross Domestic Product. Regional Accounts in 2005. Katowice.
  • Christoffersen, P., Ghysels, E., Swanson, N. R. (2002). Let's get 'real' about using economic data. "Journal of Empirical Finance", 9, 343-360.
  • Cimadomo, J. (2008). Fiscal policy in real time, ECB Working Paper Series, 919.
  • Cimadomo, J. (2011). Real-time data and fiscal policy analysis: A survey of the literature, ECB Working Paper Series, 1408.
  • Clements, M. P., Galvão, A. B. (2010). Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions. Paper presented at the Federal Reserve Bank of Philadelphia Conference, 18-19.10.2010, Philadelphia.
  • Clements, M. P., Galvão, A. B. (2011). Improving real-time estimates of output gaps and inflation trends with multiple-vintage models. Department of Economics Working Paper, 678, Queen Mary University of London.
  • Conrad, W., Corrado, C. (1979). Application of the Kalman filter to revisions in monthly retail sales estimates. "Journal of Economic Dynamics and Contro"l, 1, 177-198.
  • Croushore, D. (2006a). An evaluation of inflation forecasts from surveys using real-time data. Federal Reserve Bank of Philadelphia Working Paper, 06-19.
  • Croushore, D. (2006b). Forecasting with real-time macroeconomic data. [w:] G. Elliott, C. W. J. Granger, A. Timmermann (eds.), Handbook of Economic Forecasting, vol. I, Amsterdam: Elsevier B.V., 961-982.
  • Croushore, D. (2011). Frontiers of real-time data analysis. "Journal of Economic Literature", 49:72-100
  • Croushore, D. (2012). Forecast bias in two dimensions. Federal Reserve Bank of Philadelphia Working Paper, 12-9.
  • Croushore, D., Evans, C. L. (2006). Data revisions and the identification of monetary policy shocks. "Journal of Monetary Economic"s, 53, 1135-1160.
  • Croushore, D., Stark, T. (2001). A real-time data set for macroeconomists. "Journal of Econometrics", 105, 111-130.
  • Croushore, D., Stark, T. (2002). Is macroeconomic research robust to alternative data sets? Federal Reserve Bank of Philadelphia Working Paper, 02-3.
  • Croushore, D., Stark, T. (2003). A real-time data set for macroeconomists: Does the data vintage matter? "The Review of Economics and Statistics", 85, 605-617.
  • Diebold, F. X., Rudebusch, G. D. (1991). Forecasting output with the composite leading index: A real-time analysis. "Journal of the American Statistical Association", 86, 603-610.
  • Döpke, J., Hartmann, D., Pierdzioch, C. (2006). Real-time macroeconomic data and ex ante predictability of stock returns. Deutsche Bundesbank Discussion Paper, 10/2006.
  • Faust, J., Rogers, J. H., Wright, J. H. (2003). Exchange rate forecasting: The errors we've really made. "Journal of International Economic Review", 60, 35-39.
  • Faust, J., Rogers, J. H., Wright, J. H. (2005). News and noise in G-7 GDP announcements. "Journal of Money, Credit and Banking", 37, 403-419.
  • Forni, L., Momigliano, S. (2005). Cyclical sensitivity of fiscal policies based on real-time data. "Applied Economics Quarterly", 50, 299-326.
  • Franses, P. H. (2013). Data revisions and periodic properties of macroeconomic data. "Economic Letters", 120, 139-141.
  • Gartaganis, A. J., Goldberger, A. S. (1955). A note on the statistical discrepancy in the national accounts. "Econometrica", 23, 166-173.
  • Giannone, D., Henry, J., Lalik, M., Modugno, M. (2010). An area-wide real-time database for the Euro area, ECB Working Paper, 1145.
  • Golinelli, R., Momigliano, S. (2006). Real-time determinants of fiscal policies in the Euro area. "Journal of Policy Modeling", 28, 943-964.
  • Gollinelli, R., Parigi, G. (2007). GDP Forecasting with Real-time Data. Presentation at the 27th Annual International Symposium on Forecasting, New York.
  • Griliches, Z. (1986). Economic data issues. In Z. Griliches, M. D. Intriligator (eds.), "Handbook of Econometrics", vol. 3, Amsterdam: North Holland, 1465-1514.
  • Harrison, R., Kapetanios, G., Yates, T. (2005). Forecasting with measurement errors in dynamic models. "International Journal of Forecasting", 21, 595-607.
  • Hartmann, D. (2007). Stock Market and Real-time Macroeconomic Data. Hamburg: Verlag Dr. Kovač.
  • Jacobs, J. P. A. M., Sturm, J.-E., van Norden, S. (2010). Modeling Multivariate Data Revisions. Presentation at the 30th CIRET Conference, New York.
  • Jacobs, J. P. A. M., van Norden, S. (2010). Modeling data revisions: Measurement error and the dynamics of 'true' values. "Journal of Econometrics" (doi:10.1026/j.jeconom.2010.04.010).
  • Klepper, S., Leamer, E. E. (1984). Consistent sets of estimates for regressions with errors in all variables. Econometrica, 52, 162-183.
  • Koenig, E. F., Dolmas, S., Piger, J. (2003). The use and abuse of real-time data in economic forecasting."The Review of Economic and Statistics", 85, 618-628.
  • Kozicki, S. (2004). How do data revisions affect the evalutaion and conduct of monetary policy? Federal Reserve Bank of Kansas City Economic Review, I.
  • Landefeld, J. S., Grimm, B. T. (2000). A note on the impact of hedonics and computers on real GDP. Survey of Current Business, December 2000, 17-22.
  • Mankiw, N. G., Runkle, D. E., Shapiro, M. D. (1984). Are preliminary announcements of the money stock rational forecasts? Journal of Monetary "Economics", 14, 15-27.
  • Mankiw, N. G., Shapiro, M. D. (1986). News or noise: An analysis of GNP revisions. Survey of Current Business, 66, 20-25.
  • Mariano, R. S., Tanizaki, H. (1995). Prediction of final data with use of preliminary and/or revised data. "Journal of Forecasting", 14, 351-380.
  • McKenzie, R. (2006). Undertaking revisions and real-time data analysis using the OECD main economic indicators original release data and revisions. OECD Statistics Working Paper, STD/DOC(2006)2 ( = en&cote=std/doc(2006)2).
  • McKenzie, R., Tosetto, E., Fixler, D. (2008). Assessing the efficiency of early release estimates of economic statistics. OECD Working Paper.
  • Morgenstern, O. (1963). On the Accuracy of Economic Observations. Princeton: Princeton University Press.
  • Mork, K. A. (1987). Ain't behavin': Forecast errors and measurement errors in early GNP estimates. "Journal of Business and Economic Statistics", 5, 165-175.
  • National Bank of Poland and Monetary Policy Council (2006). Raport o infacji [Inflation Report], Warszawa ( _pieniezna/dokumenty/raport_o_inflacji/ raport_kwiecien2006.pdf).
  • Orphanides, A. (2001). Monetary policy rules based on real-time data. "American Economic Review", 91, 964-985.
  • Orphanides, A., van Norden, S. (2002). The unreliability of output gap estimates in real time. "Review of Economic and Statistics", 84, 569-583.
  • Patterson, K. D. (2003). Exploiting information in vintages of time-series data. "International Journal of Forecasting", 19, 177-197.
  • Persons, W. M. (1919). Indices of business conditions. "Review of Economic Statistics", 1, 5-107.
  • Phillips, K. R., Nordlund, J. (2012). The efficiency of benchmark revisions to the current employment statistics (CES) data. "Economic Letters", 115, 431-434.
  • Pierce, D. A. (1981). Sources of error in economic time series. "Journal of Econometrics", 17, 305-321.
  • Stark, T., Croushore, D. (2002). Forecasting with a real-time data set for macroeconomists. "Journal of Macroeconomics", 24, 507-531.
  • Swanson, N. (1996). Forecasting using first-available versus fully revised economic timeseries data. Pennsylvania State Department of Economics Paper, 4-96-7.
  • Tomczyk, E. (2011). Oczekiwania w ekonomii. Idea, pomiar, analiza [Expectations in Economic. Definitions, Measurement, Analysis], Warszawa: Oficyna Wydawnicza SGH.
  • Vázquez, J., María-Dolores, M., Londoño, J. M. (2012). The effect of data revisions on the basic New Keynesian model. International Review of Economics and Finance, doi:10.1016/j.iref.2012.03.005.
  • Zarnowitz, V., Braun, P. (1992). Twenty-two years of of the NBER-ASA quarterly economic outlook surveys: aspects and comparisons of forecasting performance. NBER Working Paper, 3965.
  • Zellner, A. (1958). A statistical analysis of provisional estimates of gross national product and its components, of selected national income components, and of personal saving. "Journal of the American Statistical Association", 53, 54-65.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.