Results 1  10
of
15
2009), “RealTime Measurement of Business Conditions
 Journal of Business and Economic Statistics
"... We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the framework i ..."
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Cited by 54 (2 self)
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We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the framework in a prototype empirical example and a simulation study calibrated to the example.
News And Noise In G7 GDP Announcements
, 2000
"... : Revisions to GDP announcements are known to be quite large in all G7 countries: many revisions in quarterly GDP growth are over a full percentage point at an annualized rate. In this paper, we examine the predictability of these data revisions. Previous work suggests that U.S. GDP revisions are l ..."
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Cited by 18 (0 self)
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: Revisions to GDP announcements are known to be quite large in all G7 countries: many revisions in quarterly GDP growth are over a full percentage point at an annualized rate. In this paper, we examine the predictability of these data revisions. Previous work suggests that U.S. GDP revisions are largely unpredictable, as would be the case if the revisions reflect news not available at the time that the preliminary number is produced. We find that the degree of predictability varies throughout the G7. For the U.S., the revisions are very slightly predictable, but for Italy, Japan and the UK, about half the variability of subsequent revisions can be accounted for by information available at the time of the preliminary announcement. For these countries, it appears that revisions reflect, to a significant degree, the removal of noise from the preliminary numbers, rather than the arrival of news. Keywords: Vintage data, preliminary data, final data, revision, GDP. # Division of Interna...
Nonlinear and NonGaussian StateSpace Modeling with Monte Carlo Techniques: A Survey and Comparative Study
 In Rao, C., & Shanbhag, D. (Eds.), Handbook of Statistics
, 2000
"... Since Kitagawa (1987) and Kramer and Sorenson (1988) proposed the filter and smoother using numerical integration, nonlinear and/or nonGaussian state estimation problems have been developed. Numerical integration becomes extremely computerintensive in the higher dimensional cases of the state vect ..."
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Cited by 16 (4 self)
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Since Kitagawa (1987) and Kramer and Sorenson (1988) proposed the filter and smoother using numerical integration, nonlinear and/or nonGaussian state estimation problems have been developed. Numerical integration becomes extremely computerintensive in the higher dimensional cases of the state vector. Therefore, to improve the above problem, the sampling techniques such as Monte Carlo integration with importance sampling, resampling, rejection sampling, Markov chain Monte Carlo and so on are utilized, which can be easily applied to multidimensional cases. Thus, in the last decade, several kinds of nonlinear and nonGaussian filters and smoothers have been proposed using various computational techniques. The objective of this paper is to introduce the nonlinear and nonGaussian filters and smoothers which can be applied to any nonlinear and/or nonGaussian cases. Moreover, by Monte Carlo studies, each procedure is compared by the root mean square error criterion.
Prediction Of Final Data With Use Of Preliminary And/or Revised Data
 Journal of Forecasting
, 1995
"... : In the case of U.S. national accounts, the data are revised for the first few years and every decade, which implies that we do not really have the final data. In this paper, we aim to predict the final data, using the preliminary data and/or the revised data. The following predictors are introduce ..."
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Cited by 12 (4 self)
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: In the case of U.S. national accounts, the data are revised for the first few years and every decade, which implies that we do not really have the final data. In this paper, we aim to predict the final data, using the preliminary data and/or the revised data. The following predictors are introduced and derived from a context of the nonlinear filtering or smoothing problem, which are: (i) prediction of the final data of time t given the preliminary data up to time t
Federal Reserve Board
, 2001
"... Abstract: There are large literatures about the role of three dummy variables in explaining economic activity: Republican elections, oil shocks, and Romer dates, which mark monetary tightening. Many have argued that one or more of the three is not a cause of recessions. This paper parallels those li ..."
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Cited by 1 (0 self)
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Abstract: There are large literatures about the role of three dummy variables in explaining economic activity: Republican elections, oil shocks, and Romer dates, which mark monetary tightening. Many have argued that one or more of the three is not a cause of recessions. This paper parallels those literatures in examining equity returns and the three dummies. Given that equity returns vary with the business cycle, it seems likely that the dummies will predict asset returns, and they do. The losses that predictably follow the dummy events, however, do not come when the dummy events happen, but later when the business cycle peak actually occurs. Based on this, we argue that the markets, at least, are also suspicious of the evidence that the dummies signal recession.
Acknowledgements
, 2006
"... This paper was written during visits of the first author to HEC Montréal, CIRANO and CIREQ, and of the second author to the research school SOM of the University of Groningen. The hospitality and support of these institutions is gratefully acknowledged. The second author would also like to thank th ..."
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This paper was written during visits of the first author to HEC Montréal, CIRANO and CIREQ, and of the second author to the research school SOM of the University of Groningen. The hospitality and support of these institutions is gratefully acknowledged. The second author would also like to thank the INE program of the Canadian SSHRC for financial support. The authors would like to thank
Estimating U.S. Output Growth with Vintage Data in a StateSpace Framework
"... This study uses a statespace model to estimate the “true ” unobserved measure of total output in the U.S. economy. The analysis uses the entire history (i.e., all vintages) of selected realtime data series to compute revisions and corresponding statistics for those series. The revision statistics, ..."
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This study uses a statespace model to estimate the “true ” unobserved measure of total output in the U.S. economy. The analysis uses the entire history (i.e., all vintages) of selected realtime data series to compute revisions and corresponding statistics for those series. The revision statistics, along with the most recent data vintage, are used in a statespace model to extract filtered estimates of the “true ” series. Under certain assumptions, Monte Carlo simulations suggest this framework can improve published estimates by as much as 30 percent, lasting an average of 11 periods. Realtime experiments using a measure of real gross domestic product show improvement closer to 10 percent, lasting for 1 to 2 quarters. (JEL C10, C53, E01) Federal Reserve Bank of St. Louis Review, July/August 2009, 91(4), pp. 34969. Statistical agencies face a tradeoff between accuracy and timely reporting of macroeconomic data. As a result, agencies release their best estimates of the “true ” unobserved series in the proceeding month, quarter, or year with some measurement
DEPARTMENT OF ECONOMICSRealtime Forecasting of Inflation and Output Growth in the Presence of Data Revisions
, 2010
"... We show how to improve the accuracy of realtime forecasts from models that include autoregressive terms by estimating the models on ‘lightlyrevised’data instead of using data from the latestavailable vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the estimati ..."
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We show how to improve the accuracy of realtime forecasts from models that include autoregressive terms by estimating the models on ‘lightlyrevised’data instead of using data from the latestavailable vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the estimation of the model in such a way that the vintages used in estimation are of a similar maturity to the data in the forecast loss function. The size of the expected reductions in mean squared error depend on the characteristics of the data revision process. Empirically, we find RMSFE gains of 24 % when forecasting output growth and inflation with AR models, and gains of the order of 8 % with ADL models.
Forecasting with Autoregressive Models in the Presence of Data Revisions
, 2008
"... We investigate the e¤ects of data revisions on forecasting using autoregressive models, when the data set consists of endofsample data, and when the data set is constructed in such a way that it comprises the …rstrelease value at each point in time. We derive analytical expressions for the e¤ects ..."
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We investigate the e¤ects of data revisions on forecasting using autoregressive models, when the data set consists of endofsample data, and when the data set is constructed in such a way that it comprises the …rstrelease value at each point in time. We derive analytical expressions for the e¤ects of noise, news and nonzero mean revisions on the estimates of the AR models’ parameters, and how these depend on the way the data set is constructed. Our calculations indicate that di¤erences in the construction of realtime data sets have only small e¤ects on estimating and evaluating forecasts from AR models when we consider the statistical process of data revisions on output growth and in‡ation in the US. An empirical exercise con…rms the implications of our analytical results. 1
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