% Encoding: windows-1252

@UNPUBLISHED{aast:unpub,
  author = {Aastveit, Knut Are and Torres G. Trovik},
  title = {Can Factor Models Improve Output Gap Estimates in Real Time?},
  note = {Norges Bank working paper},
  month = {October},
  year = {2008},
}

@Article{Abeln:JBCR2018,
  author   = {Barend Abeln and Jan P.A.M. Jacobs and Pim Ouwehand},
  title    = {CAMPLET: Seasonal Adjustment Without Revisions},
  journal  = {Journal of Business Cycle Research},
  year     = {2018},
  issn     = {2509-7962},
  abstract = {Seasonality in economic time series can ‘obscure’ movements of other components 
in a series that are operationally more important for economic and econometric analyses.
In practice, one often prefers to work with seasonally adjusted data to assess
the current state of the economy and its future course. This paper presents a seasonal
adjustment program called CAMPLET, an acronym of its tuning parameters,
which consists of a simple adaptive procedure to extract the seasonal and the nonseasonal
component from an observed series. Once this process is carried out there
will be no need to revise these components at a later stage when new observations
become available. The paper describes the main features of CAMPLET. We evaluate
the outcomes of CAMPLET and X-13ARIMA-SEATS in a controlled simulation
framework using a variety of data generating processes and illustrate CAMPLET
and X-13ARIMA-SEATS with three time series: U.S. non-farm payroll employment,
operational income of Ahold and real GDP in the Netherlands.},
  doi      = {10.1007/s41549-018-0031-3},
}

@UNPUBLISHED{adje:unpub,
  author = {Adjemain, St\'ehane and St\'ephane Gregoir and Florian Pelgrin},
  title = {Modelling Data Revisions and Weak Structural Analysis of Forecasts:
	A Bayesian VAR Perspective},
  note = {Working paper},
  month = {July},
  year = {2006},
}

@ARTICLE{aguirre:iref2018,
  author = {Idoia Aguirre and Jesus Vazquez},
  title = {Inflation Monitoring in Real Time: A Comparative Analysis of the
	Federal Reserve and the Bank of England},
  journal = {International Review of Economics \& Finance},
  year = {2018},
  volume = {58},
  pages = {200-209},
}

@UNPUBLISHED{ahmad:oecd,
  author = {Ahmad, Nadim and Sophie Bournot and Francette Koechlin},
  title = {Revisions to Quarterly GDP Estimates: A Comparative Analysis for
	Seven Large OECD Countries},
  year = {2007},
  note = {OECD Paper},
  database = {OECD's Main Economic Indicators Database},
  institution = {OECD},
  url = {http://www.oecd.org/dataoecd/20/26/34350524.pdf}
}

@INCOLLECTION{aiolfi:ohef,
  author = {Marco Aiolfi and Carlos Capistran and Allan Timmermann},
  title = {Forecast Combinations},
  booktitle = {Oxford Handbook of Economic Forecasting},
  publisher = {Oxford University Press},
  year = {2011},
  editor = {Michael P. Clements and David F. Hendry},
  address = {New York: Oxford},
  abstract = {We consider combinations of subjective survey forecasts and model-based
	forecasts from linear and non-linear univariate specifications as well as multivariate
	factor-augmented models. Empirical results suggest that a simple equal-weighted average of
	survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables
	and forecast horizons. Additional improvements can in some cases be gained by using a simple
	equal-weighted average of survey and model-based forecasts. We also provide an analysis of
	the importance of model instability for explaining gains from forecast combination. Analytical
	and simulation results uncover break scenarios where forecast combinations outperform the
	best individual forecasting model.},
    url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Carlos\%20Capistran\%20paper.pdf}
}

@ARTICLE{aksoy:qqass2010,
  author = {Kurmas Akdogan and Yunus Aksoy},
  title = {Exchange Rates and Fundamentals: Is there a Role for Nonlinearities in Real Time?},
  journal = {Quantitative and Qualitative Analysis in Social Sciences},
  year = {2010},
  volume = {4},
  pages = {49-81},
}

@UNPUBLISHED{almuzara:wp2022,
  author = {Almuzara, Marin and Dante Amengual and Gabriele Fiorentini and Enrique Sentana},
  title = {GDP Solera: The Ideal Vintage Mix},
  note = {Working paper, Federal Reserve Bank of New York},
  month = {August},
  year = {2022},
}

@UNPUBLISHED{altcicc:policy2011,
  author = {Altavilla, Carlo and Matteo Ciccarelli},
  title = {Monetary Policy Analysis in Real-Time: Vintage Combination from a Real-Time Dataset},
  month = {March},
  year = {2011},
  note = {Working paper},
  abstract = {This paper provides a general strategy for analyzing monetary policy
	in real time which accounts for data uncertainty without explicitly modelling the revision
	process. The strategy makes use of all the data available from a real-time data matrix and
	averages model estimates across all data releases. Using standard forecasting and policy models
	to analyze monetary authorities' reaction functions, we show that this simple method can
	improve forecasting performance and provide reliable estimates of the policy model coefficients
	associated with small central bank losses, in particular during periods of high macroeconomic
	uncertainty.},
}

@UNPUBLISHED{altavilla:infocombo,
  author = {Altavilla, Carlo and Matteo Ciccarelli},
  title = {Information Combination and Forecast (St)ability: Evidence from Vintages of Time-Series Data},
  note = {European Central Bank working paper 846},
  month = {December},
  year = {2007},
  url = {http://www.ecb.int/pub/pdf/scpwps/ecbwp846.pdf}
}

@ARTICLE{amato:jme,
  author = {Amato, Jeffery D. and Swanson, Norman R.},
  title = {The Real Time Predictive Content of Money for Output},
  journal = {Journal of Monetary Economics},
  year = {2001},
  volume = {48},
  pages = {3-24},
}

@ARTICLE{amir:JEDC2017,
  author = {Pooyan Amir-Ahmadi and Christian Matthes and Mu-Chun Wang},
  title = {Measurement Errors and Monetary Policy: Then and Now},
  journal = {Journal of Economic Dynamics and Control},
  year = {2017},
  volume = {79},
  pages = {66-78},
  month = {June},
}

@ARTICLE{amstad:obes2009,
  author = {Amstad, Marlene and Andreas M. Fischer},
  title = {Are Weekly Inflation Forecasts Informative?},
  journal = {Oxford Bulletin of Economics and Statistics},
  year = {2009},
  month = {April},
  volume = {71},
  pages = {237-252}
}

@UNPUBLISHED{amstad:passthrough,
  author = {Amstad, Marlene and Andreas M. Fischer},
  title = {Real Time Pass-Through Estimates from Import Prices to Consumer Prices
	in a Data Rich Environment},
  note = {Working paper, Swiss National Bank},
  month = {June},
  year = {2006},
}

@UNPUBLISHED{amstad:CEPR2004,
  author = {Amstad, Marlene and Andreas M. Fischer},
  title = {Sequential Information Flow and Real-Time Diagnosis of Swiss Inflation: Intra-Monthly DCF Estimates for a Low-Inflation Environment},
  note = {Centre for Economic Policy Research Discussion Paper No.4627},
  month = {September},
  year = {2004},
  number = {4627},
  url = {http://www.szgerzensee.ch/fileadmin/Dateien_Anwender/Dokumente/working_papers/wp-0406.pdf}
}

@ARTICLE{anderson:frbstlr2006,
  author = {Anderson, Richard G.},
  title = {Replicability, Real-Time Data, and the Science of Economic Research: FRED, ALFRED, and VDC},
  journal = {Federal Reserve Bank of St. Louis Review},
  year = {2006},
  volume = {88},
  pages = {81-93},
  month = {January/February},
  url = {http://research.stlouisfed.org/publications/review/06/01/Anderson.pdf}
}

@ARTICLE{anderson:frbstlr2006b,
  author = {Anderson, Richard G. and Kevin L. Kliesen},
  title = {The 1990s Acceleration in Labor Productivity: Causes and Measurement},
  journal = {Federal Reserve Bank of St. Louis Review},
  year = {2006},
  volume = {88},
  pages = {181-202},
  number = {3},
  month = {May/June},
  url = {http://research.stlouisfed.org/publications/review/06/05/Anderson.pdf}
}

@ARTICLE{anesti:jae2021,
  author = {Nikoleta Anesti and Ana Beatriz Galvão and Silvia Miranda-Agrippino},
  title = {Uncertain Kingdom: Nowcasting Gross Domestic Product and Its Revisions},
  journal = {Journal of Applied Econometrics},
  year = {2021},
  doi = {https://doi.org/10.1002/jae.2845},
}

@UNPUBLISHED{antonio:assessment2005,
  author = {David de Antonio Liedo and Kai Carstensen},
  title = {A Model for Real-Time Data Assessment and Forecasting},
  month = {September},
  year = {2005},
  note = {Working Paper},
  database = {RTDSM; Bundesbank (Germany) - described in Gerberding et al. (2004);
	undisclosed 'preliminary' European data set},
  url = {http://www.cirano.qc.ca/fin/Real-timeData/Carstensen.pdf}
}

@ARTICLE{aoki:jme2003,
  author = {Aoki, Kosuke},
  title = {On the Optimal Monetary Policy Response to Noisy Indicators},
  journal = {Journal of Monetary Economics},
  year = {2003},
  volume = {50},
  pages = {510-523},
  url = {personal.lse.ac.uk/aoki/publication/noisy\%20indicators.pdf}
}

@ARTICLE{arai:ijf2020,
  author = {Arai, Natsuki},
  title = {Investigating the inefficiency of the CBO's budgetary projections},
  journal = {International Journal of Forecasting},
  year = {2020},
  volume = {36},
  pages = {1290-1300}
}

@Article{aruoba:jmcb2008,
  author    = {Aruoba, S. Boragan},
  title     = {Data Revisions Are Not Well Behaved},
  journal   = {Journal of Money, Credit, and Banking},
  year      = {2008},
  volume    = {40},
  pages     = {319-340},
  month     = {March-April},
  comment   = {Looks at revisions to real output, nominal output, retail sales, GDP
	inflation, unemployment rate, employment growth, industrial production,
	capacity utilization, productivity growth. Finds all mean revisions
	(initial to final) positive, with most statistically significant.
	Standard deviation of revisions is about 0.39 x standard deviations
	of variables, so revisions are large relative to variable itself.
	For most variables, reject both news and noise. In sample, revisions
	are predictable. Many variables are also forecastable in real time,
	using a state space model.},
  database  = {RTDSM; small data set of their own using BLS data},
  url       = {http://www.econ.umd.edu/~aruoba/research/paper10/well_behaved.pdf},
}

@UNPUBLISHED{aruoba:uncertainty,
  author = {Aruoba, S. Boragan},
  title = {Data Uncertainty in General Equilibrium},
  note = {Manuscript, University of Maryland},
  month = {May},
  year = {2004},
  database = {RTDSM},
}

@ARTICLE{aruoba:aerpp2010,
  author = {S. Boragan Aruoba and Francis X. Diebold},
  title = {Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions},
  journal = {American Economic Review: Papers and Proceedings},
  year = {2010},
  volume = {100},
  pages = {20-24},
  number = {2},
  month = {May},
}

@ARTICLE{aruoba:jbes2009,
  author = {Aruoba, S. Boragan and Francis X. Diebold and Chiara Scotti},
  title = {Real-Time Measurement of Business Conditions},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {417-427},
  month = {October},
  url = {http://www.econ.umd.edu/~aruoba/research/paper13/paper13.html}
}

@ARTICLE{ashley:boe2005,
  author = {Ashley, James and Ronnie Driver and Simon Hayes and Christopher Jeffery},
  title = {Dealing with Data Uncertainty},
  journal = {Bank of England Quarterly Bulletin},
  year = {2005},
  pages = {23-29},
  month = {Spring},
  url = {http://www.bankofengland.co.uk/publications/quarterlybulletin/qb050101.pdf}
}

@ARTICLE{atkeson:frbmqr2001,
  author = {Atkeson, Andrew and Lee E. Ohanian},
  title = {Are Phillips Curves Useful for Forecasting Inflation?},
  journal = {Federal Reserve Bank of Minneapolis Quarterly Review},
  year = {2001},
  volume = {25},
  pages = {2-11},
  number = {1},
  month = {winter},
  database = {RTDSM},
  url = {http://www.minneapolisfed.org/research/QR/QR2511.pdf}
}

@UNPUBLISHED{barbarino:wp2020,
  author = {Barbarino, Alessandro and Travis J. Berge and Han Chen and Andrea Stella},
  title = {Which Output Gaps Are Stable in Real Time and Why?},
  note = {Working paper, Federal Reserve Board},
  month = {December},
  year = {2020},
}

@INCOLLECTION{banbura:hef2013,
  author = {Marta Banbura and Domenico Giannone and Michele Modugno and Lucrezia
	Reichlin},
  title = {Now-casting and the real-time data flow},
  booktitle = {Handbook of economic forecasting},
  publisher = {elsevier},
  year = {2013},
}

@ARTICLE{barklem:et2000,
  author = {Barklem, A.J.},
  title = {Revisions Analysis of Initial Estimates of Key Economic Indicators and GDP Components},
  journal = {Economic Trends},
  year = {2000},
  volume = {556},
  pages = {31-52},
}

@ARTICLE{barnett:je2016,
  author = {William A. Barnett and Marcelle Chauvet and Danilo Leiva-Leon},
  title = {Real-time nowcasting of nominal GDP with structural breaks},
  journal = {Journal of Econometrics},
  year = {2016},
  volume = {191},
  pages = {312-324},
}

@ARTICLE{barro:jme1980,
  author = {Barro, Robert J. and Zvi Hercowitz},
  title = {Money Stock Revisions and Unanticipated Money Growth},
  journal = {Journal of Monetary Economics},
  year = {1980},
  volume = {6},
  pages = {257-267},
  url = {http://www.nber.org/papers/w0329.pdf}
}

@UNPUBLISHED{basistha:wp2008,
  author = {Basistha, Arabinda},
  title = {A Comparison of Business Cycle Regime Nowcasting Performance between Real-Time and Revised Data},
  note = {Working paper, West Virginia University},
  month = {December},
  year = {2008},
}

@ARTICLE{baumeister:jbes2012,
  author = {Christiane Baumeister and Lutz Kilian},
  title = {Real-Time Forecasts of the Real Price of Oil},
  journal = {Journal of Business and Economic Statistics},
  month = {April},
  year = {2012},
  volume = {30},
  pages = {326-336},
  abstract = {We construct a monthly real-time data set consisting of vintages for
	1991.1-2010.12 that is suitable for generating forecasts of the real price of oil
	from a variety of models. We document that revisions of the data typically represent news, and
	we introduce backcasting and nowcasting techniques to fill gaps in the real-time data. We show
	that real-time forecasts of the real price of oil can be more accurate than the no-change forecast
	at horizons up to one year. In some cases real-time MSPE reductions may be as high as 25 percent
	one month ahead and 24 percent three months ahead. This result is in striking contrast to
	related results in the literature for asset prices. In particular, recursive vector autoregressive (VAR)
	forecasts based on global oil market variables tend to have lower MSPE at short horizons than forecasts
	based on oil futures prices, forecasts based on AR and ARMA models, and the no-change forecast.
	In addition, these VAR models have consistently higher directional accuracy. We demonstrate
	how with additional identifying assumptions such VAR models may be used not only to understand
	historical fluctuations in the real price of oil, but to construct conditional
	forecasts that reflect hypothetical scenarios about future demand and supply conditions in the market
	for crude oil. These tools are designed to allow forecasters to interpret their oil price forecast
	in light of economic models and to evaluate its sensitivity to alternative assumptions.},
}

@Unpublished{bea:seasonality2016,
  author    = {BEA},
  title     = {Residual Seasonality in GDP and GDI: Findings and Next Steps},
  month     = {June},
  year      = {2016},
  note = {Bureau of Economic Analysis working paper},
}

@ARTICLE{bentancor:te2010,
  author = {Andrea Bentancor and Pablo M. Pincheira},
  title = {Improving Inflation Forecasts from the Survey of Professional Forecasters in Chile},
  journal = {TE},
  month = {January-March},
  year = {2010},
  volume = {78},
  number = {305},
  pages = {129-154},
  abstract = {We evaluate inflation forecasts from the Survey of Professional Forecasters (SPF) of the Central Bank of Chile. Forecast errors for the period 2000-2008 show an excess of autocorrelation and a statistically significant bias at the end of the sample. We take advantage of the bias and autocorrelation structure of the forecast errors to build new and more accurate inflation forecasts. We evaluate these new forecasts in an out-of-sample exercise. The new forecasts display important reductions in bias and Mean Square Prediction Error. Moreover, these reductions are, in general, statistically significant.},
}

@ARTICLE{bernanke:jme2003,
  author = {Ben S. Bernanke and Jean Boivin},
  title = {Monetary Policy in a Data-Rich Environment},
  journal = {Journal of Monetary Economics},
  year = {2003},
  volume = {50},
  pages = {525-546},
  database = {composite data set from RTDSM and Ghysels (1998)},
}

@ARTICLE{bernhard:SNB2016,
  author = {Severin Bernhard},
  title = {A real-time GDP data set for Switzerland},
  journal = {SNB Economic Studies},
  year = {2016},
}

@ARTICLE{bernhardsen:najef2005,
  author = {Bernhardsen, Tom and Oyvind Eitrheim and Anne Sofie Jore and Oistein
	Roisland},
  title = {Real Time Data for Norway: Challenges for Monetary Policy},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {333-49},
  number = {3},
  month = {December},
  comment = {Electronic Copy available through Elsevier / Science Direct},
  database = {new real-time dataset for Norway},
 url = {www.bundesbank.de/download/volkswirtschaft/dkp/2004/200426dkp.pdf}
}

@UNPUBLISHED{bernoth:fiscal2008,
  author = {Bernoth, Kerstin and Andrew Hughes Hallett and John Lewis},
  title = {Did Fiscal Policy Makers Know What They Were Doing? Reassessing Fiscal Policy with Real-Time Data},
  note = {De Nederlandsche Bank working paper},
  month = {October},
  year = {2008},
}

@ARTICLE{boero:ijf2008,
  author = {Boero, Gianna and Jeremy Smith and Kenneth F. Wallis},
  title = {Evaluating a Three-Dimensional Panel of Point Forecasts: The Bank of England Survey of External Forecasters},
  journal = {International Journal of Forecasting},
  year = {2008},
  volume = {24},
  pages = {354-367},
}

@ARTICLE{boivin:jmcb2006,
  author = {Boivin, Jean},
  title = {Has U.S. Monetary Policy Changed? Evidence from Drifting Coefficients and Real-Time Data},
  journal = {Journal of Money, Credit, and Banking},
  year = {2006},
  volume = {38},
  pages = {1149-1173},
  month = {August},
}

@ARTICLE{bomfim:jme2001,
  author = {Bomfim, Antulio},
  title = {Measurement Error in General Equilibrium: The Aggregate Effects of Noisy Economic Indicators},
  journal = {Journal of Monetary Economics},
  year = {2001},
  volume = {48},
  pages = {585-603},
}

@Article{Boonman:OER2019,
  author   = {Tjeerd M. Boonman and Jan P.A.M. Jacobs and Gerard H. Kuper and Alberto Romero},
  title    = {Early Warning Systems for Currency Crises with Real-Time Data},
  journal  = {Open Economies Review},
  year     = {2019},
  abstract = {This paper investigates the performance of early warning systems for currency crises in real-time, using forecasts of indicators that are available at the moment predictions are to be made. We investigate two types of commonly used early warning systems for currency crises: the signal approach and the logit model. We apply each EWS to a panel of fifteen emerging economies, distinguishing an estimation period 1991Q1-2010Q4 and a prediction period 2011Q1–2017Q4. We find that using indicator forecasts in the predictions worsens the ability of early warning systems to signal crises compared to the most recently available information.},
  doi      = {10.1007/s11079-019-09530-0},
}

@Article{bordalo:aer2020,
  author   = {Pedro Bordalo and Nicola Gennaioli and Yuelran Ma and Anrei Shleifer},
  journal  = {American Economic Review},
  title    = {Overreaction in Macroeconomic Expectations},
  year     = {2020},
  month    = {September},
  volume   = {110},
  abstract = {We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts underreact relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)},
}

@ARTICLE{boschen:jme1982,
  author = {Boschen, John F. and Herschel I. Grossman},
  title = {Tests of Equilibrium Macroeconomics Using Contemporaneous Monetary Data},
  journal = {Journal of Monetary Economics},
  year = {1982},
  volume = {10},
  pages = {309-333},
  comment = {Electronic Copy available through Elsevier / Science Direct},
  url = {http://www.nber.org/papers/w0558.pdf}
}

@ARTICLE{bouwman:jmacro2011,
  author = {Bouwman, Kees E. and Jan P.A.M. Jacobs},
  title = {Forecasting with Real-Time Macroeconomic Data: The Ragged Edge Problem and Revisions},
  journal = {Journal of Macroeconomics},
  year = {2011},
  volume = {33},
  pages = {784-792},
  number = {4},
  note = {Working paper, University of Groningen},
  abstract = {Real-time macroeconomic data are typically incomplete for today and
	the immediate past ('ragged edge') and subject to revision. To enable more timely forecasts
	the recent missing data have to be imputed. The paper presents a state-space model that
	can deal with publication lags and data revisions. The framework is applied to the US leading
	index. We conclude that including even a simple model of data revisions improves the
	accuracy of the imputations and that the univariate imputation method in levels adopted
	by The Conference Board can be improved upon.},
}

@ARTICLE{brodsky:ijf1994,
  author = {Brodsky, Noel and Paul Newbold},
  title = {Late Forecasts and Early Revisions of United States GNP},
  journal = {International Journal of Forecasting},
  year = {1994},
  volume = {10},
  pages = {455-460},
}

@ARTICLE{bulligan:ee2010,
  author = {Guido Bulligan and Roberto Golinelli and Giuseppe Parigi},
  title = {Forecasting Monthly Industrial Production in Real-Time: From Single Equations to Factor-Based Models},
  journal = {Empirical Economics},
  year = {2010},
  volume = {39},
  pages = {303-336},
  number = {2},
  month = {October},
}

@ARTICLE{busetti:jf2006,
  author = {Busetti, Fabio},
  title = {Preliminary Data and Econometric Forecasting: An Application with the Bank of Italy Quarterly Model},
  journal = {Journal of Forecasting},
  volume = {25},
  year = {2006},
  pages = {1-23},
}

@ARTICLE{camacho:jae2010,
  author = {Camacho, Maximo and Gabriel Perez-Quiros},
  title = {Introducing the EURO-STING: Short Term INdicator of Euro Area Growth},
  journal = {Journal of Applied Econometrics},
  volume = {25},
  year = {2010},
  pages = {663-694},
}

@ARTICLE{capistran:jme2008,
  author = {Capistran, Carlos},
  title = {Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?},
  journal = {Journal of Monetary Economics},
  volume = {55},
  year = {2008},
  pages = {1415-1427},
  database = {RTDSM},
  url = {http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1041&context=ucsdecon}
}

@ARTICLE{capistran:jbes2009,
  author = {Capistran, Carlos and Allan Timmermann},
  title = {Forecast Combination with Entry and Exit of Experts},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {428-440},
  month = {October},
  database = {RTDSM},
  url = {rady.ucsd.edu/faculty/directory/timmermann/docs/Capistran_Timmermann_June29_2007.pdf}
}

@ARTICLE{capistran:jmcb2009,
  author = {Capistran, Carlos and Allan Timmermann},
  title = {Disagreement and Bias in Inflation Expectations},
  journal = {Journal of Money, Credit and Banking},
  volume = {41},
  month = {March-April},
  year = {2009},
  number = {2-3},
  pages = {365-396},
}

@Unpublished{carlton:wp2010,
  author    = {Amelie Benear Carlton},
  title     = {Oil Prices and Real-Time Output Growth},
  month     = {February},
  year      = {2010},
  note = {working paper},
  comment   = {Uses oil prices in real time to forecast real GDP with out-of-sample forecasting exercises},
}

@Unpublished{caruso:wp2021,
  author    = {Alberto Caruso and Laura Coroneo},
  title     = {Does real-time macroeconomic information help to predict interest rates?},
  month     = {February},
  year      = {2021},
  note = {working paper},
}

@ARTICLE{casares:md2016,
  author = {Miguel Casares and Jesus Vazquez},
  title = {Data Revisions in the Estimation of DSGE Models},
  journal = {Macroeconomic Dynamics},
  year = {2016},
  month = {October},
  volume = {20},
  number = {7},
  pages = {1683-1716},
  doi = {10.1017/S1365100515000024},
  url = {ftp://ftp.econ.unavarra.es/pub/DocumentosTrab/DT1104.PDF}
}

@ARTICLE{cassou:ae2018,
  author = {Steven P. Cassou and Patrick Scott and Jesus Vazquez},
  title = {Optimal Monetary Policy Revisited: Does Considering US Real-Time Data Change Things?},
  journal = {Applied Economics},
  year = {2018},
  volume = {50},
  pages = {6203-6219},
  number = {57},
  doi = {10.1080/00036846.2018.1489511},
}

@ARTICLE{castle:boeqb2002,
  author = {Castle, Jennifer and Colin Ellis},
  title = {Building a Real-Time Database for GDP(E)},
  journal = {Bank of England Quarterly Bulletin},
  year = {2002},
  pages = {42-49},
  month = {Spring},
  database = {Bank of England's GDP Database},
  url = {http://www.bankofengland.co.uk/publications/quarterlybulletin/qb020104.pdf}
}

@ARTICLE{cayen:najef2005,
  author = {Cayen, Jean-Philippe and Simon van Norden},
  title = {The Reliability of Canadian Output Gap Estimates},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {373-393},
  month = {December},
  url = {www.bundesbank.de/download/volkswirtschaft/dkp/2004/200429dkp.pdf}
}

@UNPUBLISHED{cenesizoglu:wp2008,
  author = {Cenesizoglu, Tolga},
  title = {Risk and Return Reaction of the Stock Market to Public Announcements about Fundamentals: Theory and Evidence},
  note = {HEC Montreal working paper},
  month = {March},
  year = {2008},
}

@ARTICLE{champagne:jme2018,
  author   = {Julien Champagne and Rodrigo Sekkel},
  title    = {Changes in Monetary Regimes and the Identification of Monetary Policy Shocks: Narrative Evidence from Canada},
  journal = {Journal of Monetary Economics},
  volume = {99},
  year     = {2018},
  pages = {72-87},
  abstract = {We use narrative evidence along with a novel database of real-time data and forecasts from the Bank of Canada's staff economic projections from 1974 to 2015 to construct a
new measure of monetary policy shocks and estimate the effects of monetary policy in Canada. We show that it is crucial to take into account the break in the conduct of monetary policy caused by the announcement of inflation targeting in 1991 when estimating the effects of monetary policy. For instance, we find that a 100-basis-point increase in our new shock series leads to a 1.0 per cent decrease in real GDP and a 0.4 per cent fall in the price level, while not accounting for the break leads to a permanent decrease in real GDP and a price puzzle. Finally, we compare our results with updated narrative evidence for the U.S. and the U.K. and argue that taking into account changes in the conduct of monetary policy in these countries also yields significantly different effects of monetary policy.},
}

@ARTICLE{chang:wp2015,
  author = {Andrew C. Chang and Tyler J. Hanson},
  title = {The Accuracy of Forecasts Prepared for the Federal Open Market Committee},
  journal = {Finance and Economics Discussion Series 2015-062, Federal Reserve
	Board},
  year = {2015},
  month = {July},
  owner = {dcrousho},
  timestamp = {2016.05.04}
}

@ARTICLE{chang:ei2018,
  author = {Andrew C. Chang and Phillip Li},
  title = {Measurement Error in Macroeconomic Data and Economics Research: Data Revisions, Gross Domestic Product, and Gross Domestic Income},
  journal = {Economic Inquiry},
  year = {2018},
  volume = {56},
  pages = {1846-1869},
  number = {3},
  month = {July},
  doi = {https://doi.org/10.1111/ecin.12567},
}

@Unpublished{chang:raiders,
  author   = {Andrew C. Chang and Trace J. Levinson},
  title    = {Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting},
  year     = {2020},
  abstract = {We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's GDP forecast errors correlate with its GDP forecast revisions, particularly for forecasts made more than two weeks from the start of a FOMC meeting, implying GDP forecasts exhibit time-varying inefficiency between FOMC meetings. We find some weaker evidence for inefficient inflation forecasts.},
  note  = {Federal Reserve Board FEDS wp 2020-090},
}

@INCOLLECTION{chauvet:dating2006,
  author = {Chauvet, Marcelle and James D. Hamilton},
  title = {Dating Business Cycle Turning Points},
  booktitle = {Nonlinear Time Series Analysis of Business Cycles},
  publisher = {Elsevier},
  year = {2006},
  editor = {Costas Milas and Philip Rothman and Dick van Dijk},
  url = {http://www.econbrowser.com/archives/2006_04/chauvet_hamilton_may_05.pdf}
}

@ARTICLE{chauvet:jbes2008,
  author = {Chauvet, Marcelle and Jeremy Piger},
  title = {A Comparison of the Real-Time Performance of Business Cycle Dating
	Methods},
  journal = {Journal of Business and Economic Statistics},
  year = {2008},
  volume = {26},
  pages = {42-49},
  number = {1},
  month = {January},
  database = {RTDSM and ALFRED},
  url = {http://research.stlouisfed.org/wp/2005/2005-021.pdf}
}

@ARTICLE{chauvet:frbstl2003,
  author = {Chauvet, Marcelle and Jeremy Piger},
  title = {Identifying Business Cycle Turning Points in Real Time},
  journal = {Federal Reserve Bank of St. Louis Review},
  year = {2003},
  pages = {47-61},
  month = {March/April},
  database = {RTDSM},
  url = {http://research.stlouisfed.org/publications/review/03/03/ChauvetPiger.pdf}
}

@ARTICLE{chauvet:ijf2016,
  author = {Marcelle Chauvet and Zeynep Senyuz},
  title = {A dynamic factor model of the yield curve components as a predictor
	of the economy},
  journal = {International Journal of Forecasting},
  year = {2016},
  volume = {32},
  pages = {324-343},
}

@ARTICLE{chauvet:jedc2015,
  author = {Marcelle Chauvet and Zeynep Senyuz and Emre Yoldas},
  title = {What Does Financial Volatility Tell Us About Macroeconomic Fluctuations?},
  year = {2015},
  journal = {Journal of Economic Dynamics and Control},
  volume = {52},
  pages = {340-360},
}

@UNPUBLISHED{chauvet:RTmonetary,
  author = {Chauvet, Marcelle and Heather L. R. Tierney},
  title = {Real Time Changes in Monetary Transmission - A Nonparametric VAR Approach},
  note = {working paper},
  month = {April},
  year = {2007},
  database = {RTDSM},
  url = {www.philadelphiafed.org/research-and-data/events/2007/real-time-conference/papers/Paper-Chauvet.pdf}
}

@ARTICLE{christoffersen:jef2002,
  author = {Christoffersen, Peter and Eric Ghysels and Norm Swanson},
  title = {Let's Get 'Real' About Using Economic Data},
  journal = {Journal of Empirical Finance},
  year = {2002},
  volume = {9},
  pages = {343-360},
  number = {3},
  database = {RTDSM},
  url = {http://www.cirano.qc.ca/pdf/publication/2001s-44.pdf}
}

@ARTICLE{ciccarelli:ecbrb2012,
  author = {Matteo Ciccarelli},
  title = {Monetary Policy Analysis and Data Revisions -- Vintage Combination
	from a Real-Time Dataset},
  journal = {ECB Research Bulletin},
  year = {2012},
  volume = {15},
  pages = {7-11},
  number = {15},
  month = {Spring},
}

@ARTICLE{cimadomo:jes2016,
  author = {Jacopo Cimadomo},
  title = {Real-Time Data and Fiscal Policy Analysis: A Survey of the Literature},
  journal = {Journal of Economic Surveys},
  year = {2016},
  volume = {30},
  pages = {302-326},
  number = {2},
  month = {April},
  abstract = {This paper surveys the empirical research on fiscal policy analysis
	based on real-time data. This literature can be broadly divided in three groups of papers,
	which focus on: (1) the statistical properties of revisions in fiscal data; (2) the political
	and institutional determinants of fiscal data revisions and of one-year-ahead projection errors by
	governments; (3) the reaction of fiscal policies to the business cycle. It emerges that,
	first, fiscal data revisions are large and initial releases are biased estimates of final values.
	Second, the presence of strong fiscal rules and institutions leads to relatively more accurate
	releases of fiscal data and small deviations of fiscal outcomes from government plans. Third,
	the cyclical stance of fiscal policies is estimated to be more 'counter-cyclical' when real-time
	data are used instead of ex-post data. Finally, more work is needed for the development
	of real-time datasets for fiscal policy analysis. In particular, a comprehensive real-time
	dataset including fiscal variables for industrialized (and possibly developing) countries,
	published and maintained by central banks or other institutions, is still missing.},
}

@ARTICLE{cimadomo:sje2012,
  author = {Jacopo Cimadomo},
  title = {Fiscal Policy in Real Time},
  journal = {Scandinavian Journal of Economics},
  month = {June},
  year = {2012},
  volume = {114},
  number = {2},
  pages = {440-465},
  abstract = {In this paper, fiscal plans reported at the time of budgeting, together
	with other information available to fiscal policymakers in real-time, are used
	for the estimation of the ex-ante, i.e. intentional, cyclical stance of fiscal policy in OECD
	countries. Fiscal plans may be significantly different from ex-post outcomes because governments
	do not have complete control on their implementation, which depend on several
	exogenous factors. When fiscal policy rules are estimated using real-time data, results
	indicate that OECD countries often planned a counter-cyclical fiscal stance, especially
	during economic expansions. This contrast with conventional findings based on actual
	data, which tend to point towards a-cyclicality or pro-cyclicality. The mis-measurement
	of potential output and the output gap plays a central role in explaining the differences
	between estimates based on ex-ante and ex-post data.},
}

@UNPUBLISHED{cimadomo:reversal,
  author = {Jacopo Cimadomo and Sebastian Hauptmeier and Sergio Sola},
  title = {Identifying the Effects of Government Spending Shocks With and Without
	Expected Reversal: An Approach Based on U.S. Real-Time Data},
  note = {ECB working paper also},
  month = {July},
  year = {2011},
  abstract = {This paper investigates how expectations about future government spending
	affect the transmission of fiscal policy shocks. We study the effects of two
	different types of government spending shocks in the United States: (i) spending shocks
	that are accompanied by an expected reversal of public spending growth below
	trend; (ii) spending shocks that are accompanied by expectations of future spending growth
	above trend. We use the Ramey (2011)'s time series of military build-ups to measure
	exogenous spending shocks, and deviations of forecasts of public spending with respect
	to past trends, evaluated in real-time, to distinguish shocks into these two categories.
	Based on a structural VAR analysis, our results suggest that shocks associated
	with an expected spending reversal exert expansionary effects on the economy and accelerate
	the correction of the initial increase in public debt. Shocks associated with expected
	spending growth above trend, instead, are characterized by a contraction in aggregate
	demand and a more persistent increase in public debt. The main channel of transmission
	seems to run through agents' perception of the future macroeconomic environment.},
}

@UNPUBLISHED{clark:RTdensity,
  author = {Clark, Todd E},
  title = {Real-Time Density Forecasts from VARs with Stochastic Volatility},
  note = {Unpublished, Federal Reserve Bank of Kansas City},
  month = {October},
  year = {2009},
  url = {http://www.kansascityfed.org/PUBLICAT/RESWKPAP/PDF/rwp09-08.pdf}
}

@ARTICLE{clark:najef2005,
  author = {Clark, Todd E. and Sharon Kozicki},
  title = {Estimating Equilibrium Real Interest Rates in Real Time},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {395-413},
  month = {December},
  database = {RTDSM and Robert Arnold of the CBO},
  url = {www.bundesbank.de/download/volkswirtschaft/dkp/2004/200432dkp.pdf}
}

@INCOLLECTION{clark:hef2013,
  author = {Todd E. Clark and Michael W. McCracken},
  title = {Advances in Forecast Evaluation},
  booktitle = {Handbook of Economic Forecasting},
  publisher = {Elsevier},
  year = {2013},
  editor = {Graham Elliott and Allan Timmermann},
  volume = {2B},
}

@ARTICLE{clark:JAE2010,
  author = {Clark, Todd E. and Michael W. McCracken},
  title = {Averaging Forecasts from VARs with Uncertain Instabilities},
  journal = {Journal of Applied Econometrics},
  year = {2010},
  volume = {25},
  number = {1},
  month = {Jan - Feb},
  pages = {5-29},
}

@ARTICLE{clark:jbes2009,
  author = {Clark, Todd E. and Michael W. McCracken.},
  title = {Tests of Equal Predictive Ability with Real-Time Data},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {441-454},
  month = {October},
  database = {RTDSM},
  url = {http://www.kansascityfed.org/PUBLICAT/RESWKPAP/PDF/rwp07-06.pdf}
}

@ARTICLE{clausen:imf2010,
  author = {Jens R Clausen and Bianca Clausen},
  title = {Simulating Inflation Forecasting in Real-Time; How Useful Is a Simple Phillips Curve in Germany, the UK, and the US?},
  journal = {IMF Working Papers 10/52, International Monetary Fund},
  year = {2010},
}

@ARTICLE{clements:jbes2017b,
  author = {Michael P. Clements},
  title = {Assessing Macro Uncertainty in Real Time When Data Are Subject to Revision},
  journal = {Journal of Business and Economic Statistics},
  year = {2017},
  volume = {35},
  number = {3},
  pages = {420-433},
  month = {July},
}

@ARTICLE{clements:jmcb2015,
  author = {Michael P. Clements},
  title = {Are Professional Macroeconomic Forecasters Able To Do Better Than Forecasting Trends?},
  journal = {Journal of Money, Credit and Banking},
  volume = {47}, 
  number = {2/3},
  month = {March-April},
  year = {2015},
  pages = {349-381},
}

@UNPUBLISHED{clements:Forecasters_same,
  author = {Michael Clements},
  title = {Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency},
  month = {October},
  year = {2016},
  note = {working paper},
}

@ARTICLE{clements:jae2013,
  author = {Michael Clements and Ana Beatriz Galvao},
  title = {Real-time Forecasting of Inflation and Output Growth with Autoregressive Models in the Presence of Data Revisions},
  journal = {Journal of Applied Econometrics},
  month = {April/May},
  year = {2013},
  volume = {28},
  number = {3},
  pages = {458-477},
  abstract = {We examine how the accuracy of real-time forecasts from models that
	include autoregressive terms can be improved by estimating the models on lightly-revised
	data instead of using data from the latest-available vintage. The benefits
	to estimating autoregressive models on lightly-revised data are related to the nature
	of the data revision process and on the underlying process for the true values. Empirically,
	we find RMSFE improvements of 2-4\% when forecasting output growth and inflation
	with univariate models, and of 8\% with multivariate models. We show that multiple-vintage
	models, which attempt to explicitly model data revisions, require large estimation
	samples to deliver competitive forecasts.},
 url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Clements-Galvao\%20paper.pdf}
}

@ARTICLE{clements:jbes2014,
  author = {Michael P. Clements},
  title = {Forecast Uncertainty--Ex Ante and Ex Post: U.S. Inflation and Output Growth},
  journal = {Journal of Business and Economic Statistics},
  year = {2014},
  volume = {32},
  pages = {206-216},
  number = {2},
  month = {April},
}

@ARTICLE{clements:IJF2019,
  author = {Michael P. Clements},
  title = {Do Forecasters Target First or Later Releases of National Accounts Data?},
  journal = {International Journal of Forecasting},
  volume = {35},
  number = {4},
  month = {October - December},
  year = {2019},
  pages = {1240-1249},
}

@ARTICLE{clements:JAE2022,
  author = {Michael P. Clements},
  title = {Individual Forecaster Perceptions of the Persistence of Shocks to GDP},
  journal = {Journal of Applied Econometrics},
  volume = {37},
  number = {3},
  month = {April/May},
  year = {2022},
  pages = {640-656},
}

@UNPUBLISHED{clements:value,
  author = {Michael P. Clements},
  title = {Characterising How Surveys of U.S. Macrovariables Add Value},
  month = {May},
  year = {2012},
  note = {working paper},
  abstract = {We investigate two characteristics of consensus survey forecasts which
	are shown to contribute to their accuracy. Consensus forecasts incorporate the effects of
	perceived changes in the long-run outlook. They also feature departures from the path toward the long-run expectation. At the level of the individual forecasts, there is some evidence that the departures from the long-run path enhance accuracy, but to a lesser extent.},
}

@Unpublished{clements:consistency,
  author    = {Clements, Michael P.},
  title     = {Internal Consistency of Survey Respondents' Forecasts: Evidence Based on the Survey of Professional Forecasters},
  note      = {Working paper, University of Warwick},
  month     = {November},
  year      = {2007},
  comment   = {Combines SPF data on point forecasts, histograms, and probability
	of negative GDP growth to examine consistency of forecasts. Finds
	point and probability forecasts more optimistic than histograms.
	Asymmetric loss functions cannot explain the puzzle. Uses real-time
	data for forecast evaluation.},
  database  = {RTDSM},
  url       = {http://www2.warwick.ac.uk/fac/soc/economics/research/papers/twerp_772.pdf},
}

@ARTICLE{clements:jbes2017,
  author = {Michael P. Clements and Ana Beatriz Galvao},
  title = {Predicting early data revisions to US GDP and the effects of releases on equity markets},
  journal = {Journal of Business and Economic Statistics},
  year = {2017},
  volume = {35},
  pages = {389-406},
  number = {3},
}

@ARTICLE{clements:jbes2012,
  author = {Michael P. Clements and Ana Beatriz Galvao},
  title = {Improving Real-Time Estimates of Output and Inflation Gaps With Multiple-Vintage
	Models},
  journal = {Journal of Business and Economic Statistics},
  year = {2012},
  volume = {30},
  pages = {554-562},
  number = {4},
  month = {May},
}

@ARTICLE{clements:jae2009,
  author = {Clements, Michael P. and Ana Beatriz Galvao},
  title = {Forecasting U.S. Output Growth Using Leading Indicators: An Appraisal Using MIDAS Models},
  journal = {Journal of Applied Econometrics},
  year = {2009},
  volume = {24},
  pages = {1187-1206},
  month = {July},
}

@ARTICLE{clements:eer2010,
  author = {Clements, Michael P. and Ana Beatriz Galvao},
  title = {First Announcements and Real Economic Activity},
  journal = {European Economic Review},
  year = {2010},
  volume = {54},
  number = {6},
  month = {August},
  pages = {803-817},
}

@ARTICLE{clements:jbes2008,
  author = {Clements, Michael P. and Ana Beatriz Galvao},
  title = {Macroeconomic Forecasting with Mixed Frequency Data: Forecasting
	Output Growth in the United States},
  journal = {Journal of Business and Economic Statistics},
  year = {2008},
  volume = {26},
  pages = {546-554},
  month = {October},
  database = {RTDSM},
  url = {http://www.econ.qmul.ac.uk/papers/doc/wp616.pdf}
}

@ARTICLE{clements:jae2010,
  author = {Clements, Michael P. and David I. Harvey},
  title = {Forecast Encompassing Tests and Probability Forecasts},
  note = {Working paper, University of Warwick No. 774},
  journal = {Journal of Applied Econometrics},
  volume = {25},
  year = {2010},
  pages = {1028 – 1062},
  database = {RTDSM},
  url = {http://www2.warwick.ac.uk/fac/soc/economics/research/papers/twerp_774.pdf}
}

@Article{clements:jedc2021,
  author   = {Michael P. Clements and Ana Beatriz Galvao},
  journal  = {Journal of Economic Dynamics and Control},
  title    = {Measuring the Effects of Expectations Shocks},
  year     = {2021},
  month    = {March},
  number   = {5},
  volume   = {124},
  abstract = {We seek to improve the measurement of the dynamic causal effects of expectation shocks by addressing issues related to data uncertainty. The expectations shocks are estimated in a mixed-frequency VAR model which incorporates monthly and quarterly economic and financial indicators. The VAR is estimated on real-time data to prevent the shocks being confounded with the effects of data uncertainty. But dynamic responses are calculated using a quarterly VAR for revised data, estimated using older vintages as instruments to account for the fact that ‘true values’ of key macroeconomic variables may never be observed. We show that expectations shocks – revisions in GDP expectations unrelated to changes in current economic fundamentals and orthogonalized to other, potentially related shocks – explain 7–8\% of the two-year variation of output, investment, consumption and hours. This is similar to the proportion of business-cycle variation explained by monetary shocks, for example.},
}

@InCollection{clements:oxford2019,
  author    = {Michael P. Clements and Ana Beatriz Galvao},
  title     = {Data Revisions and Real-Time Forecasting},
  booktitle = {Oxford Research Encyclopedia of Economics and Finance},
  publisher = {Oxford University Press},
  year      = {2019},
}

@ARTICLE{cloyne:aejm2016,
  author = {James Cloyne and Patrick Hurtgen},
  title = {The Macroeconomic Effects of Monetary Policy: A New Measure for the United Kingdom},
  journal = {American Economic Journal: Macroeconomics},
  year = {2016},
  volume = {8},
  pages = {75-102},
  number = {4},
}

@ARTICLE{coenen:eer2005,
  author = {Coenen, Gunter and Andrew Levin and Volker Wieland},
  title = {Data Uncertainty and the Role of Money as an Information Variable for Monetary Policy},
  journal = {European Economic Review},
  year = {2005},
  volume = {4},
  pages = {975-1006},
  month = {May},
  database = {built own set from ECB's Monthly Bulletin},
  url = {http://www.federalreserve.gov/pubs/feds/2001/200154/200154pap.pdf}
}

@ARTICLE{coibion:aer2015,
  author    = {Olivier Coibion and Yuriy Gorodnichenko},
  title     = {Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts},
  journal = {American Economic Review},
  year = {2015},
  volume = {105},
  number = {8},
  month = {August},
  pages = {2644-2678},
  abstract  = {We propose a new approach to test the full-information rational-expectations hypothesis which can identify whether rejections of the null arise from irrationality or limited information. This approach quantifies the economic significance of departures from the null by quantifying the underlying
	degree of information rigidity. Applying this approach to U.S. and international data of professional forecasters and other agents yields pervasive evidence consistent with models of imperfect information. Furthermore, the proposed approach sheds new light on policies, such as inflation-targeting and those leading to the Great Moderation, affecting expectations. Finally, we document evidence of state-dependence in the expectations formation process.},
  comment   = {Uses real-time data and SPF to evaluate how expectations are formed.},
}

@InCollection{cole:econfore1969,
  author    = {Rosanne Cole},
  title     = {Data Errors and Forecasting Accuracy},
  booktitle = {Economic Forecasts and Expectations: Analyses of Forecasting Behavior and Performance},
  publisher = {National Bureau of Economic Research},
  year      = {1969},
  editor    = {Jacob Mincer},
  pages     = {47-82},
  comment   = {A tidy paper that shows the effects on forecast errors when forecasts are made using preliminary rather than final data. Errors are substantially higher when forecasts are based on preliminary data; the use of preliminary data leads to both bias and inefficiency. In an example with consumption data, the use of preliminary data led to a doubling of the forecast errors. Thus improving the accuracy of preliminary data would help reduce forecast errors.},
}

@Article{conrad:jedc1979,
  author    = {Conrad, William and Carol Corrado},
  title     = {Application of the Kalman Filter to Revisions in Monthly Retail Sales Estimates},
  journal   = {Journal of Economic Dynamics and Control},
  year      = {1979},
  volume    = {1},
  pages     = {177-98},
  comment   = {Use Kalman filter in-sample to produce better estimates than initial data; find that revisions are auto-correlated and hence predictable.},
}

@ARTICLE{corradi:jbes2009,
  author = {Corradi, Valentina and Andres Fernandez and Norman R. Swanson},
  title = {Information in the Revision Process of Real-Time Datasets},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {455-467},
  month = {October},
  url = {http://econweb.rutgers.edu/afernandez/IRPRT_english.pdf}
}

@ARTICLE{corrado:frbull1997,
  author = {Corrado, Carol and Charles Gilbert and Richard Raddock},
  title = {Industrial Production and Capacity Utilization: Historical Revision and Recent Developments},
  journal = {Federal Reserve Bulletin},
  year = {1997},
  pages = {67-92},
  month = {February},
  database = {built own data set},
 url = {http://www.federalreserve.gov/pubs/bulletin/1997/0297lead.pdf}
}

@ARTICLE{crone:jmcb2013,
  author = {Crone, Theodore M. and N. Neil K. Khettry and Loretta J. Mester and
	Jason A. Novak},
  title = {Core Measures of Inflation as Predictors of Total Inflation},
  journal = {Journal of Money, Credit and Banking},
  volume = {45},
  number = {2/3},
  comment = {Federal Reserve Bank of Philadelphia working paper 08-9},
  month = {March-April},
  year = {2013},
  pages = {505-519},
}

@INCOLLECTION{croushore:hef2006,
  author = {Dean Croushore},
  title = {Forecasting with Real-Time Macroeconomic Data},
  booktitle = {Handbook of Economic Forecasting},
  publisher = {Elsevier},
  year = {2006},
  editor = {Graham Elliott and Clive W.J. Granger and Allan Timmermann},
  address = {Amsterdam: North-Holland},
  url = {http://oncampus.richmond.edu/~dcrousho/docs/hef_croushore.pdf}
}

@ARTICLE{croushore:jel2011,
  author = {Croushore, Dean},
  title = {Frontiers of Real-Time Data Analysis},
  journal = {Journal of Economic Literature},
  year = {2011},
  volume = {49},
  pages = {72-100},
  number = {1},
  month = {March},
  note = {Federal Reserve Bank of Philadelphia working paper No. 08-4},
  abstract = {In the past ten years, researchers have explored the impact of data revisions in many different contexts. Researchers have examined the properties of data revisions, how structural modeling is affected by data revisions, how data revisions affect forecasting, the impact of data revisions on monetary policy analysis, and the use of real-time data in current analysis. This paper summarizes many of the questions for which real-time data analysis has provided answers. In addition, researchers and institutions have developed better real-time data sets around the world. Still, additional research is needed in key areas and research to date has uncovered even more fruitful areas worth exploring. ( JEL C52, C53, C80, E01)},
  database = {RTDSM},
  url = {facultystaff.richmond.edu/~dcrousho/docs/Real\%20Time\%20Frontiers_08Mar.pdf}
}

@ARTICLE{croushore:bejm2010,
  author = {Dean Croushore},
  title = {An Evaluation of Inflation Forecasts from Surveys using Real-Time Data},
  journal = {B.E. Journal of Macroeconomics},
  year = {2010},
  volume = {10},
  pages = {article 10},
  number = {1},
  abstract = {This paper carries out the task of evaluating inflation forecasts from the Livingston Survey and the Survey of Professional Forecasters, using the Real-Time Data Set for Macroeconomists as a source of real-time data. We examine the magnitude and patterns of revisions to the inflation rate based on the output price index. We then run tests on the forecasts from the surveys to see how good they are. We find that there are several episodes in which forecasters made persistent forecast errors, but the episodes are so short that by the time they can be identified, they have nearly disappeared. Thus, improving on the survey forecasts seems to be very difficult in real time, and the attempt to do so leads to increased forecast errors.},
  keywords = {inflation forecasting, surveys, evaluating forecasts},
}

@ARTICLE{croushore:ijcb2019,
  author = {Croushore, Dean},
  title = {Revisions to PCE Inflation Measures: Implications for Monetary Policy},
  journal = {International Journal of Central Banking}, 
  month = {October}, 
  year ={2019}, 
  volume = {15},
  number = {4},
  pages = {241-265},
  note = {Federal Reserve Bank of Philadelphia Working Paper 08-8},
  database = {RTDSM},
  url = {facultystaff.richmond.edu/~dcrousho/docs/Revisions to PCE Inflation_08July.pdf}
}

@ARTICLE{croushore:najef2005,
  author = {Croushore, Dean},
  title = {Do Consumer Confidence Indexes Help Forecast Consumer Spending in Real Time},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {435-450},
  month = {December},
  database = {RTDSM},
  url = {http://oncampus.richmond.edu/~dcrousho/docs/najef_05jan.pdf},
}

@ARTICLE{croushore:jae2016,
  author = {Dean Croushore and Katherine Marsten},
  title = {Reassessing the Relative Power of the Yield Spread in Forecasting Recessions},
  journal = {Journal of Applied Econometrics},
  volume = {31},
  number = {6},
  month = {Sept./Oct.},
  year = {2016},
  pages = {1183-1191},
  doi = {10.1002/jae.2485},
  comment = {Federal Reserve Bank of Philadelphia Working-Paper Series, 14-5, Feb 2014},
}

@ARTICLE{croushore:restat2018,
  author = {Dean Croushore and Simon van Norden},
  title = {Fiscal Forecasts at the FOMC: Evidence from the Greenbooks},
  journal = {Review of Economics and Statistics},
  month = {December},
  year = {2018},
  volume = {100},
  number = {5},
  pages = {933-945},
  comment = {Fiscal Policy: Ex Ante and Ex Post, Federal Reserve Bank of Philadelphia Working-Paper Series, 14-22, August 2014},
}

@ARTICLE{croushore:ijf2019,
  author = {Dean Croushore and Simon van Norden},
  title = {Fiscal Surprises at the FOMC},
  journal = {International Journal of Forecasting},
  month = {October-December},
  year = {2019},
  volume = {35},
  number = {4},
  pages = {1583-1595},
}

@ARTICLE{croushore:wpdsge2014,
  author = {Dean Croushore and Keith Sill},
  title = {Analyzing Data Revisions with a Dynamic Stochastic General Equilibrium Model},
  journal = {Federal Reserve Bank of Philadelphia Working-Paper Series 14-29},
  year = {2014},
  month = {September},
}

@ARTICLE{croushore:restat2003,
  author = {Croushore, Dean and Tom Stark},
  title = {A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?},
  journal = {Review of Economics and Statistics},
  year = {2003},
  volume = {85},
  pages = {605-617},
  month = {August},
  database = {RTDSM},
}

@ARTICLE{croushore:je2001,
  author = {Croushore, Dean and Tom Stark},
  title = {A Real-Time Data Set for Macroeconomists},
  journal = {Journal of Econometrics},
  year = {2001},
  volume = {105},
  pages = {111-130},
  month = {November},
  database = {RTDSM},
  url = {http://www.philadelphiafed.org/files/wps/1999/wp99-4.pdf}
}

@ARTICLE{croushore:frbpbr2000,
  author = {Croushore, Dean and Tom Stark},
  title = {A Funny Thing Happened on the Way to the Data Bank: A Real-Time Data Set for Macroeconomists},
  journal = {Federal Reserve Bank of Philadelphia Business Review},
  year = {2000},
  pages = {15-27},
  month = {September/October},
  database = {RTDSM},
  url = {http://www.philadelphiafed.org/files/br/brso00dc.pdf},
}

@ARTICLE{croushore:jme2006,
  author = {Dean Croushore and Charles L. Evans},
  title = {Data Revisions and the Identification of Monetary Policy Shocks},
  journal = {Journal of Monetary Economics},
  year = {2006},
  volume = {53},
  pages = {1135-1160},
  month = {September},
  database = {RTDSM},
  url = {oncampus.richmond.edu/~dcrousho/docs/Croushore\%20Evans\%20DRIMPS\%2005Apr.pdf}
}

@ARTICLE{cukierman:jedc2005,
  author = {Cukierman, Alex and Francesco Lippi},
  title = {Endogenous Monetary Policy with Unobserved Potential Output},
  journal = {Journal of Economic Dynamics and Control},
  year = {2005},
  volume = {29},
  pages = {1951-83},
  number = {11},
  month = {November},
}

@ARTICLE{cunningham:jbes2012,
  author = {Cunningham, Alastair and Jana Eklund and Christopher Jeffery and George Kapetanios and Vincent Labhard},
  title = {A State Space Approach to Extracting the Signal from Uncertain Data},
  journal = {Journal of Business and Economic Statistics},
  year = {2012},
  month = {April},
  volume = {30},
  number = {2},
  pages = {173-180},
  comment = {Bank of England working paper No. 336},
  database = {Bank of England's GDP database},
  url = {http://www.bankofengland.co.uk/publications/workingpapers/wp336.pdf}
}

@ARTICLE{davies:ijf2006,
  author = {Davies, Antony},
  title = {A Framework for Decomposing Shocks and Measuring Volatilities Derived from Multi-Dimensional Panel Data of Survey Forecasts},
  journal = {International Journal of Forecasting},
  year = {2006},
  volume = {22},
  pages = {373-393},
  month = {April/June},
  database = {RTDSM},
}

@ARTICLE{davig:frbkc2008,
  author = {Davig, Troy},
  title = {Detecting Recessions in the Great Moderation: A Real-Time Analysis},
  journal = {Federal Reserve Bank of Kansas City Economic Review},
  year = {2008},
  pages = {5-33},
  month = {Fourth Quarter},
}

@ARTICLE{decastro:jmcb2013,
  author = {Francisco De Castro and Javier J. Perez and Marta Rodriguez-Vives},
  title = {Fiscal Data Revisions in Europe},
  journal = {Journal of Money, Credit, and Banking},
  year = {2013},
  volume = {45},
  pages = {1187-1209},
  number = {6},
  month = {September},
}

@ARTICLE{dejong:jbes1987,
  author = {DeJong, Piet},
  title = {Rational Economic Data Revisions},
  journal = {Journal of Business and Economic Statistics},
  year = {1987},
  volume = {5},
  pages = {539-548},
  month = {October},
}

@ARTICLE{deleeuw:jbes1990,
  author = {de Leeuw, Frank},
  title = {The Reliability of U.S. Gross National Product},
  journal = {Journal of Business and Economic Statistics},
  year = {1990},
  volume = {8},
  pages = {191-203},
  month = {April},
}

@ARTICLE{demetrescu:jae2022,
  author = {Matei Demetrescu and Christoph Hanck and Robinson Kruse-Becher},
  title = {Robust inference under time-varying volatility: A real-time evaluation of professional forecasters},
  journal = {Journal of Applied Econometrics},
  year = {2022},
  volume = {37},
  number = {5},
  pages = {1010-1030},
}

@ARTICLE{denreijer:aeq2006,
  author = {den Reijer, Ard H. J. and O. Roodenburg},
  title = {On the Predictability of GDP Data Revisions in the Netherlands},
  journal = {Applied Economics Quarterly},
  year = {2006},
  volume = {52},
  pages = {337-356},
}

@ARTICLE{denton:restat1965,
  author = {Denton, Frank T. and John Kuiper},
  title = {The Effect of Measurement Errors on Parameter Estimates and Forecasts:
	A Case Study Based on the Canadian Preliminary National Accounts},
  journal = {Review of Economics and Statistics},
  year = {1965},
  volume = {47},
  pages = {198-206},
  month = {May},
}

@ARTICLE{dewald:aer1986,
  author = {Dewald, William G. and Jerry G. Thursby and Richard G. Anderson},
  title = {Replication in Empirical Economics: The Journal of Money, Credit
	and Banking Project},
  journal = {American Economic Review},
  year = {1986},
  volume = {76},
  pages = {587-603},
  month = {September},
  database = {Constructed own data set from the Survey of Current Business},
}

@INPROCEEDINGS{diebold:asa1988,
  author = {Diebold, Francis X. and Glenn D. Rudebusch},
  title = {Stochastic Properties of Revisions in the Index of Indicators},
  booktitle = {Proceedings of the American Statistical Association},
  year = {1988},
  editor = {Diebold, Francis X. and Glenn D. Rudebusch},
  series = {Business and Economic Statistics Section},
  pages = {712-717},
  address = {Washington, DC},
  organization = {American Statistical Association},
}

@INCOLLECTION{diebold:tpplei1991,
  author = {Diebold, Francis X. and Glenn D. Rudebusch},
  title = {Turning Point Prediction with the Composite Leading Index: An Ex
	Ante Analysis},
  booktitle = {Leading Economic Indicators: New Approaches and Forecasting Records},
  publisher = {Cambridge University Press},
  year = {1991},
  editor = {K. Lahiri and G.H. Moore},
  pages = {231-256},
}

@ARTICLE{diebold:jasa1991,
  author = {Diebold, Francis X. and Glenn D. Rudebusch},
  title = {Forecasting Output With the Composite Leading Index: A Real-Time
	Analysis},
  journal = {Journal of the American Statistical Association},
  year = {1991},
  volume = {86},
  pages = {603-10},
  month = {September},
}

@ARTICLE{dopke:jbcma2005,
  author = {Dopke, Jorg},
  title = {Real-Time Data and Business Cycle Analysis in Germany},
  journal = {Journal of Business Cycle Measurement and Analysis},
  year = {2005},
  volume = {2004},
  pages = {103-161},
  month = {March},
  database = {built own set from German Federal Statistical Office},
  url = {http://opus.zbw-kiel.de/volltexte/2004/2020/pdf/200411dkp.pdf}
}

@UNPUBLISHED{dovern:wp2008,
  author = {Dovern, Jonas and Ulrich Fritsche},
  title = {Estimating fundamental cross-section dispersion from fixed event forecasts},
  note = {Working paper, Hamburg University},
  month = {May},
  year = {2008},
}

@UNPUBLISHED{dovern:wp2008b,
  author = {Dovern, Jonas and Christina Ziegler},
  title = {Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators
	Under Real-Time Conditions},
  note = {Kiel Working Papers 1397, Kiel Institute for the World Economy},
  month = {January},
  year = {2008},
}

@UNPUBLISHED{dwyer:wp2000,
  author = {Dwyer, Mark and Keisuke Hirano},
  title = {Optimal Forecasting Under Data Revisions},
  note = {working paper},
  year = {2000},
}

@UNPUBLISHED{dynan:wp2001,
  author = {Dynan, Karen E. and Douglas Elmendorf},
  title = {Do Provisional Estimates of Output Miss Economic Turning Points?},
  note = {Federal Reserve Board, FEDS Working Paper No. 2001-52},
  month = {November},
  year = {2001},
  database = {RTDSM},
  url = {http://www.federalreserve.gov/pubs/feds/2001/200152/200152abs.html}
}

@ARTICLE{edge:jae2010,
  author = {Edge, Rochelle M. and Michael T. Kiley and Jean-Phillipe Laforte},
  title = {A Comparison of Forecast Performance Between Federal Reserve Staff Forecasts, Simple Reduced-Form Models, and a DSGE Model},
  journal = {Journal of Applied Econometrics},
  volume = {25}, 
  number = {4},
  month = {June/July},
  year = {2010},
  pages = {720-754},
  database = {built own set from BEA data},
}

@ARTICLE{edge:jme2007,
  author = {Edge, Rochelle M. and Thomas Laubach and John C. Williams},
  title = {Learning and Shifts in Long-Run Productivity Growth},
  journal = {Journal of Monetary Economics},
  year = {2007},
  volume = {54},
  pages = {2421-2438},
  month = {November},
  url = {http://www.frbsf.org/publications/economics/papers/2004/wp04-04bk.pdf}
}

@ARTICLE{egginton:el2002,
  author = {Egginton, Don M. and Andreas Pick and Shaun P. Vahey},
  title = {'Keep It Real!': A Real-time UK Macro Data Set},
  journal = {Economics Letters},
  year = {2002},
  volume = {77},
  pages = {15-20},
  database = {New UK Macro Data Set},
  url = {http://repec.org/res2002/Egginton.pdf}
}

@UNPUBLISHED{eitrheim:wp2006,
  author = {Eitrheim, Oyvind and Anne Sofie Jore},
  title = {Revisions of Labour Productivity and Their Effects on Wage Inflation Forecasts},
  note = {working paper},
  month = {October},
  year = {2006},
  database = {Norwegian real-time database},
  url = {http://www.cirano.qc.ca/fin/Real-timeData/2006/Eitrheim.pdf}
}

@ARTICLE{elliott:jm2002,
  author = {Elliott, Graham},
  title = {Comments on: 'Forecasting with a Real-Time Data Set for Macroeconomists.'},
  journal = {Journal of Macroeconomics},
  year = {2002},
  volume = {24},
  pages = {533-39},
  month = {December},
  url = {Electronic Copy available through Elsevier / Science Direct}
}

@ARTICLE{english:bejm2003,
  author = {English, William B. and William R. Nelson and Brian P. Sack},
  title = {Interpreting the Significance of the Lagged Interest Rate in Estimated Monetary Policy Rules},
  journal = {Contributions in Macroeconomics},
  month = {April},
  year = {2003},
  volume = {3}, 
  number = {1},
  doi = {doi:10.2202/1534-6005.1073},                        
  database = {RTDSM},
  url = {http://www.federalreserve.gov/pubs/feds/2002/200224/200224pap.pdf}
}

@ARTICLE{evans:frbcep1998,
  author = {Evans, Charles L},
  title = {Real-Time Taylor Rules and the Federal Funds Futures Market},
  journal = {Federal Reserve Bank of Chicago Economic Perspectives},
  year = {1998},
  pages = {44-55},
  month = {Third Quarter},
  database = {built own set from NIPA tables},
  url = {http://www.chicagofed.org/publications/economicperspectives/1998/ep3Q98_4.pdf}
}

@ARTICLE{evans:ijcb2005,
  author = {Evans, Martin D. D.},
  title = {Where Are We Now? Real-Time Estimates of the Macroeconomy},
  journal = {International Journal of Central Banking},
  year = {2005},
  volume = {1},
  pages = {127-175},
  month = {September},
}

@ARTICLE{fackler:jm2002,
  author = {Fackler, J.S.},
  title = {Comments on: 'Forecasting with a Real-Time Data Set for Macroeconomists.'},
  journal = {Journal of Macroeconomics},
  year = {2002},
  volume = {24},
  pages = {559-562},
  month = {December},
}

@UNPUBLISHED{farmer:nberwp2021,
  author = {Leland Farmer and Emi Nakamura and Jon Steinsson},
  title = {Learning About the Long Run},
  note = {NBER working paper 29495},
  month = {November},
  year = {2021},
}

@Article{faust:jmcb2005,
  author    = {Faust, Jon and John H. Rogers and Jonathan H. Wright},
  title     = {News and Noise in G-7 GDP Announcements.},
  journal   = {Journal of Money, Credit, and Banking},
  year      = {2005},
  volume    = {37},
  pages     = {403-419},
  month     = {June},
  comment   = {Runs news-noise tests on GDP growth for six countries and finds mostly noise revisions. Runs out of sample real-time forecasting exercise (regress revision from initial to 2 years later on initial, use to form better estimate of 2 years later data). Also, in sample, other variables known at the time of the GDP release are correlated with revisions, so initial data are not efficient (but no oos exercise).},
  database  = {OECD's Main Economic Indicators},
  url       = {http://www.eabcn.org/research/documents/wright.pdf},
}

@ARTICLE{faust:jie2003,
  author = {Faust, Jon and John H. Rogers and Jonathan H. Wright},
  title = {Exchange Rate Forecasting: the Errors We've Really Made},
  journal = {Journal of International Economics},
  year = {2003},
  volume = {60},
  pages = {35-59},
  database = {built own set from OECD MEI},
  url = {http://www.federalreserve.gov/pubs/ifdp/2001/714/default.htm}
}

@ARTICLE{faust:jbes2009,
  author = {Faust, Jon and Jonathan H. Wright},
  title = {Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {468-479},
  month = {October},
  database = {built own set from Fed's Greenbooks},
  url = {http://papers.nber.org/papers/w13397}
}

@ARTICLE{feng:jfore2009,
  author = {Feng, Hui},
  title = {Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?},
  journal = {Journal of Forecasting},
  year = {2009},
  volume = {28},
  pages = {183-193},
  number = {3},
  note = {Econometrics Working Papers 0515, Department of Economics, University of Victoria},
}

@ARTICLE{fernald:frbsfel2005,
  author = {Fernald, John and Stephanie Wang},
  title = {Shifting Data: A Challenge for Monetary Policymakers},
  journal = {Federal Reserve Bank of San Francisco Economic Letter},
  volume = {2005-35},
  month = {December},
  year = {2005},
  database = {NIPA tables},
  url = {http://www.frbsf.org/publications/economics/letter/2005/el2005-35.html}
}

@UNPUBLISHED{fernandez:oecd2011,
  author = {Adriana Z. Fernandez and Evan F. Koenig and Alex Nikolsko-Rzhevskyy},
  title = {A Real-Time Historical Database for the OECD},
  month = {November},
  year = {2011},
  note = {published online},
  abstract = {Ongoing economic globalization makes real-time international data increasingly relevant, though little work has been done on collecting and analyzing real-time data for economies other than the U.S. In this paper, we introduce and examine a new international real-time dataset assembled from original quarterly releases of 13 quarterly variables presented in the 	OECD Main Economic Indicators from 1962 to 1998 for 26 OECD countries. By merging this data with the current OECD real-time dataset, which starts in 1999, researchers get access to a standard, up-to-date resource. To illustrate the importance of using real-time data in macroeconomic analysis, we consider five economic applications analyzed from a real-time perspective.},
  keywords = {real-time data, OECD, forecasting inflation, growth, exchange rates, output gap},
}

@ARTICLE{fernandez:frbd2007,
  author = {Fernandez, Adriana Z. and Alex Nikolsko-Rzhevskyy},
  title = {Measuring the Taylor Rule's Performance},
  journal = {Federal Reserve Bank of Dallas Economic Letter},
  year = {2007},
  month = {June},
}

@ARTICLE{fernandez:frbdel2012,
  author = {Adriana Z. Fernandez and Evan F. Koenig and Alex Nikolsko-Rzhevskyy},
  title = {Real-Time Historical Dataset Enhances Accuracy of Economic Analyses},
  journal = {Dallas Fed Economic Letter},
  year = {2012},
  volume = {7},
  number = {6},
  month = {July},
}

@ARTICLE{filardo:frbker1999,
  author = {Filardo, Andrew J.},
  title = {How Reliable are Recession Prediction Models?},
  journal = {Federal Reserve Bank of Kansas City Economic Review},
  year = {1999},
  pages = {35-55},
  month = {Second Quarter},
  url = {http://www.kansascityfed.org/PUBLICAT/ECONREV/PDF/2q99fila.pdf}
}

@UNPUBLISHED{fixler:bea2004,
  author = {Fixler, Dennis},
  title = {Revisions to GDP Estimates in the U.S.},
  note = {U.S. Bureau of Economic Analysis Paper},
  month = {October},
  year = {2004},
  url = {http://www.bea.gov/papers/pdf/fixler_gdp_revise.pdf}
}

@ARTICLE{fixler:scb2003,
  author = {Fixler, Dennis J. and Bruce T. Grimm and Anne E. Lee.},
  title = {The Effects of Revisions to Seasonal Factors on Revisions to Seasonally
	Adjusted Estimates},
  journal = {Survey of Current Business},
  year = {2003},
  pages = {43-50},
  month = {December},
  url = {http://www.bea.gov/bea/ARTICLES/2003/12December/1203Effects.pdf}
}

@Unpublished{fixler:bea2006,
  author    = {Fixler, Dennis J. and Jeremy J. Nalewaik},
  title     = {News, Noise, and Estimates of the 'True' Unobserved State of the Economy},
  note      = {U.S. U.S. Bureau of Economic Analysis Working Paper},
  month     = {January},
  year      = {2006},
  comment   = {Finds that GDP and gross domestic income mainly have news revisions; so modeling them jointly to estimate the true state of the economy requires a particular type of model. True nominal output is a weighted sum of the two.},
  url       = {http://www.bea.gov/papers/pdf/fixler_nalewaikrev.pdf},
}

@ARTICLE{flodberg:FEP2017,
  author = {Caroline Flodberg and Par Osterholm},
  title = {A Statistical Analysis of Revisions of Swedish National Accounts
	Data},
  journal = {Finnish Economic Papers},
  year = {2017},
  volume = {28},
  pages = {10-33},
  number = {1},
  month = {Fall},
}

@ARTICLE{frankel:nber2017,
  author = {Jeffrey A. Frankel and Ayako Saiki},
  title = {Does It Matter If Statistical Agencies Frame the Month's CPI Report 	on a 1-Month or 12-Month Basis?},
  journal = {NBER working paper series 23754},
  year = {2017},
  month = {August},
}

@UNPUBLISHED{franses:wp2007,
  author = {Franses, Philip Hans and Dick van Dijk},
  title = {Evaluating Real-Time Forecasts in Real Time},
  note = {presentation for Federal Reserve Bank of Philadephia, April 19-20,
	2007},
  month = {April},
  year = {2007},
}

@ARTICLE{fukuda:jf2007,
  author = {Fukuda, Kosei},
  title = {Forecasting Real-Time Data Allowing for Data Revisions},
  journal = {Journal of Forecasting},
  year = {2007},
  volume = {26},
  pages = {429-444},
  month = {September},
}

@ARTICLE{fulton:etrics2021,
  author = {Fulton, Chad and Kirstin Hubrich},
  year = {2021},
  title = {Forecasting US Inflation in Real Time},
  journal = {MDPI Econometrics}, 
  volume = {9},
  doi = {10.3390/econometrics9040036},
}

@UNPUBLISHED{galbraith:wp2008,
  author = {Galbraith, John W. and Simon van Norden},
  title = {The Calibration of Probabilistic Economic Forecasts},
  note = {working paper},
  month = {November},
  year = {2008},
  database = {ALFRED and RTDSM},
  url = {www.philadelphiafed.org/research-and-data/events/2007/real-time-conference/papers/Paper-Galbraith.pdf}
}

@UNPUBLISHED{galbraith:boc2006,
  author = {Galbraith, John W. and Greg Tkacz},
  title = {Electronic Transactions as High-Frequency Indicators of Economic 	Activity},
  note = {Bank of Canada Working Paper 2007-58},
  month = {December},
  year = {2007},
  database = {ALFRED and Campbell and Murphy (2007) Canadian database},
  url = {http://www.bankofcanada.ca/en/res/wp/2007/wp07-58.pdf}
}

@ARTICLE{galimberti:ijf2016,
  author = {Jaqueson K. Galimberti and Marcelo L. Moura},
  title = {Improving the reliability of real-time output gap estimates using 	survey forecasts},
  journal = {International Journal of Forecasting},
  year = {2016},
  volume = {32},
  pages = {358-373},
}

@UNPUBLISHED{gallo:unpub2,
  author = {Gallo, Giampiero M. and Massimiliano Marcellino},
  title = {Ex Post and Ex Ante Analysis of Provisional Data},
  note = {Working paper, Universita Bocconi},
  month = {November},
  year = {1998},
  crossref = {Forecasting},
  database = {built own data set},
  owner = {Sherry},
  timestamp = {2010.06.08},
  url = {ftp://ftp.igier.uni-bocconi.it/wp/1998/141.pdf}
}

@UNPUBLISHED{gallo:wp1996,
  author = {Gallo, Giampiero M. and Massimiliano Marcellino},
  title = {In Plato's Cave: Sharpening the Shadows of Monetary Announcements},
  note = {Working paper, not available online},
  year = {1996},
}

@UNPUBLISHED{galvao:perception2020,
  author = {Ana Beatriz Galvao and James Mitchell},
  title = {Real-Time Perceptions of Historical GDP Data Uncertainty},
  note = {Working paper},
  year = {2020},
}

@ARTICLE{garratt:ijf2009,
  author = {Garratt, Anthony and Kevin Lee, Emi Mise and Kalvinder Shields},
  title = {Real Time Representation of the UK Output Gap in the Presence of	Model Uncertainty},
  journal = {International Journal of Forecasting},
  year = {2009},
  volume = {25},
  number = {1},
  pages = {81-102},
  month = {January-March},
  database = {Bank of England real-time data set},
  url = {http://www.ems.bbk.ac.uk/research/wp/PDF/BWPEF0618.pdf}
}

@ARTICLE{garratt:jbes2009,
  author = {Garratt, Anthony and Gary Koop and Emi Mise and Shaun P. Vahey},
  title = {Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty},
  journal = {Journal of Business and Economic Statistics},
  year = {2009},
  volume = {27},
  pages = {480-491},
  database = {built own set using Bank of England data},
  url = {http://www.ems.bbk.ac.uk/research/wp/PDF/BWPEF0714.pdf}
}

@ARTICLE{garratt:ej2008,
  author = {Garratt, Anthony and Gary Koop and Shaun P. Vahey},
  title = {Forecasting Substantial Data Revisions in the Presence of Model Uncertainty},
  journal = {Economic Journal},
  year = {2008},
  volume = {118},
  pages = {1128-1144},
  month = {July},
  database = {BOE real-time data set},
  url = {http://www.ems.bbk.ac.uk/research/wp/PDF/BWPEF0617.pdf}
}

@ARTICLE{garratt:restat2008,
  author = {Garratt, Anthony and Kevin Lee and Emi Mise and Kalvinder Shields},
  title = {Real Time Representations of the Output Gap},
  journal = {Review of Economics and Statistics},
  year = {2008},
  volume = {90},
  pages = {792-804},
  month = {November},
  database = {RTDSM},
  url = {http://www.ems.bbk.ac.uk/research/wp/PDF/BWPEF0619.pdf}
}

@UNPUBLISHED{garratt:wp2009,
  author = {Garratt, Anthony and James Mitchell and Shaun P. Vahey},
  title = {Measuring Output Gap Uncertainty},
  note = {Unpublished, Birkbeck College},
  month = {September},
  year = {2009},
}

@Article{garratt:ej2006,
  author    = {Garratt, Anthony and Shaun P. Vahey},
  title     = {UK Real-Time Macro Data Characteristics},
  journal   = {Economic Journal},
  year      = {2006},
  volume    = {116},
  pages     = {F119-F135},
  month     = {February},
  comment   = {Look at 16 indicators of UK data. Find predictability of revisions.
	Predict revisions in VAR context based on bias in past revisions
	in real time.},
  database  = {Bank of England's data set},
  url       = {http://www.ems.bbk.ac.uk/research/wp/PDF/BWPEF0502.pdf},
}

@ARTICLE{garratt:najef2011,
  author = {Garratt, Anthony and James Mitchell and Shaun P. Vahey and Elizabeth C.},
  title = {Real-time inflation forecast densities from ensemble Phillips curves},
  journal = {The North American Journal of Economics and Finance},
  year = {2011},
  volume = {22},
  pages = {77-87},
  number = {1},
  month = {January},
  abstract = {A popular macroeconomic forecasting strategy takes combinations across many models to hedge against model instabilities of unknown timing; see (among others) Stock and Watson (2004) and Clark and McCracken (2009). In this paper, we examine the effectiveness of recursive-weight and equal-weight combination strategies for density forecasting using a time-varying Phillips curve relationship between inflation and the output gap. The densities reflect the uncertainty across a large number of models using many statistical measures of the output gap, allowing for a single structural break of unknown timing. We use real-time data for the US, Australia, New Zealand and Norway. Our main finding is that the recursive-weight strategy performs well across the real-time data sets, consistently giving well-calibrated forecast densities. The equal-weight strategy generates poorly-calibrated forecast densities for the US and Australian samples. There is little difference between the two strategies for our New Zealand and Norwegian data. We also find that the ensemble modeling approach performs more consistently with real-time data than with revised data in all four countries.},
}

@ARTICLE{gartaganis:ea1955,
  author = {Gartaganis, Arthur J. and Arthur S. Goldberger},
  title = {A Note on the Statistical Discrepancy in the National Accounts},
  journal = {Econometrica},
  year = {1955},
  volume = {23},
  pages = {166-173},
  month = {April},
  database = {Survey of Current Business},
}

@UNPUBLISHED{gaus:wp2016,
  author = {Eric Gaus and Christopher G. Gibbs},
  title = {Expectations and the Empirical Fit of DSGE Models},
  month = {August},
  year = {2016},
  note = {unpublished working paper},
}

@ARTICLE{gerberding:najef2005,
  author = {Gerberding, Christina and Franz Seitz and Andreas Worms},
  title = {How the Bundesbank Really Conducted Monetary Policy: An Analysis
	Based on Real-Time Data},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {277-292},
  month = {December},
  database = {built own set from Bundesbank monthly reports},
  url = {www.bundesbank.de/download/volkswirtschaft/dkp/2004/200425dkp.pdf}
}

@ARTICLE{gerdesmeier:najef2005,
  author = {Gerdesmeier, Dieter and Barbara Roffia},
  title = {The Relevance of Real-Time Data in Estimating Reaction Functions for the Euro Area},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {293-307},
  month = {December},
  database = {built own set using ECB Monthly Bulletins},
}

@ARTICLE{ghosh:ae2001,
  author = {Ghosh, Sucharita and Donald Lien},
  title = {Forecasting with Preliminary Data: A Comparison of Two Methods},
  journal = {Applied Economics},
  year = {2001},
  volume = {33},
  pages = {721-26},
}

@ARTICLE{ghosh:jf1997,
  author = {Ghosh, Sucharita and Donald Lien},
  title = {Forecasting with Preliminary Data},
  journal = {Journal of Forecasting},
  year = {1997},
  volume = {16},
  pages = {463-473},
}

@ARTICLE{ghosh:obes1995,
  author = {Ghosh, Sucharita and Donald Lien},
  title = {Data Revision and Market Response: The Case of United States Trade Balance Announcements},
  journal = {Oxford Bulletin of Economics and Statistics},
  year = {1995},
  volume = {57},
  number = {2},
}

@ARTICLE{ghysels:sej2002,
  author = {Ghysels, Eric and Norman R. Swanson and Myles Callan},
  title = {Monetary Policy Rules with Model and Data Uncertainty},
  journal = {Southern Economic Journal},
  year = {2002},
  volume = {69},
  pages = {239-265},
  month = {October},
  url = {http://www.cirano.qc.ca/pdf/publication/98s-40.pdf}
}

@ARTICLE{giannone:restat2012,
  author = {Giannone, Domenico and Jerome Henry and Magdalena Lalik and Michele Modugno},
  title = {An Area Wide Real Time Data Base for the Euro Area},
  journal = {The Review of Economics and Statistics},
  volume = {94},
  number = {4},
  pages = {1000-1013},
  month = {November},
  year = {2012},
  database = {EABCN database},
}

@INCOLLECTION{giannone:nberma2004,
  author = {Giannone, Domenico and Lucrezia Reichlin and Luca Sala},
  title = {Monetary Policy in Real Time},
  booktitle = {NBER Macroeconomics Annual 2004},
  publisher = {MIT Press},
  year = {2005},
  editor = {Mark Gertler and Kenneth Rogoff},
  pages = {161-224},
  address = {Boston},
 database = {RTDSM and Fed Greenbooks},
  url = {ftp://ftp.igier.uni-bocconi.it/wp/2005/284.pdf}
}

@ARTICLE{giannone:jme2008,
  author = {Giannone, Domenico and Lucrezia Reichlin and David Small},
  title = {Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases},
  journal = {Journal of Monetary Economics},
  year = {2008},
  volume = {55},
  pages = {665-676},
  month = {May},
  database = {built own set from several sources},
  url = {http://www.federalreserve.gov/pubs/feds/2005/200542/200542pap.pdf}
}

@UNPUBLISHED{gilbert:announce2010,
  author = {Thomas Gilbert and Chiara Scotti and Georg Strasser and Clara Vega},
  title = {Why Do Certain Macroeconomic News Announcements Have a Big Impact on Asset Prices?},
  note = {Thomas Gilbert (University of Washington), Chiara Scotti (BOG), Georg Strasser (Boston College), Clara Vega (BOG)},
  month = {July},
  year = {2010},
  abstract = {Previous literature documents a heterogenous asset price response to macroeconomic announcements. Some announcements have a strong impact on asset prices 	and others do not. The most common explanation is that timing matters - announcements released earlier in the cycle affect asset prices more. We define in a novel way the relevance or information content of a macroeconomic announcement as its ability to forecast FOMC decisions, to nowcast GDP growth and inflation; and investigate to what extent the information content, timeliness, and revision noise of macroeconomic announcements help explain the differential impact of news on asset prices. We find that a significant fraction of the variation in price impact can be explained by differences in information content. The timeliness of a news release is even slightly more important for its price impact. Revision noise of an announcement, in contrast, is less important, it has only about half of the impact of the other two properties.},
  keywords = {Central bank policy, public information, macroeconomic forecasting, learning, price discovery, coordination role of public information},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Strasser\%20paper.pdf}
}

@article{gilbert:jfe2011,
title = {Information aggregation around macroeconomic announcements: Revisions matter},
journal = {Journal of Financial Economics},
volume = {101},
number = {1},
pages = {114-131},
year = {2011},
issn = {0304-405X},
doi = {https://doi.org/10.1016/j.jfineco.2011.02.013},
url = {https://www.sciencedirect.com/science/article/pii/S0304405X11000468},
author = {Thomas Gilbert},
keywords = {Macroeconomic announcements, Revisions, Information precision, Price discovery},
abstract = {I show that an empirical relation exists between stock returns on macroeconomic news announcement days and the future revisions of the released data but that this link differs across the business cycle. Using three major macroeconomic series that undergo significant revisions (nonfarm payroll, gross domestic product, and industrial production), I present evidence that daily returns on the Standard & Poor's 500 index and revisions are positively related in expansions and negatively related in recessions. The results suggest that revisions do matter, i.e., that investors care about the final revised value of a macroeconomic series, that they infer accurate information from the release of the preliminary inaccurate report, and that the more precise information is aggregated into prices on the day of the initial announcement. The results are consistent with the predictions of rational expectations trading models around public announcements combined with well-established empirical results on the asymmetric interpretation of information across the business cycle.} 
}

@ARTICLE{giordani:eer2003,
  author = {Giordani, Paolo and Paul Soderlind},
  title = {Inflation Forecast Uncertainty},
  journal = {European Economic Review},
  year = {2003},
  volume = {47},
  pages = {1037-1059},
  month = {December},
  database = {RTDSM},
}

@ARTICLE{giusto:ijf2017,
  author = {Andrea Giusto and Jeremy Piger},
  title = {Identifying business cycle turning points in real time with vector quantization},
  journal = {International Journal of Forecasting},
  year = {2017},
  volume = {33},
  pages = {174-184},
  number = {1},
}

@ARTICLE{givens:jmcb2017,
  author = {Gregory E. Givens},
  title = {Do Data Revisions Matter for DSGE Estimation?},
  journal = {Journal of Money, Credit and Banking},
  volume = {49},
  number = {6},
  month = {September},
  year = {2017},
  pages = {1385-1407}, 
}

@UNPUBLISHED{glass:wp2015,
  author      = {Katharina Glass and Ulrich Fritsche},
  note        = {University of Hamburg DEP (Socioeconomic) Discussion Papers},
  title       = {Real-time Macroeconomic Data and Uncertainty},
  year        = {2015},
  month       = {June},
  number      = {6/2014},
  institution = {Universitaet Hamburg},
}

@ARTICLE{gleiser:riw1974,
  author = {Gleiser, H. and P. Schavey},
  title = {An Analysis of Revisions of National Accounts Data for 40 Countries},
  journal = {Review of Income and Wealth},
  year = {1974},
  volume = {20},
  pages = {317-32},
  number = {3},
  month = {September},
}

@UNPUBLISHED{gluck:quality,
  author = {Gluck, Heinz and Stefan P. Schleicher},
  title = {Forecast Quality and Simple Instrument Rules: A Real-Time Data Approach},
  note = {Manuscript},
  month = {May},
  year = {2004},
}

@ARTICLE{golinelli:jpm2006,
  author = {Golinelli, Roberto and Sandro Momigliano},
  title = {Real-time Determinants of the Fiscal Policies in the Euro Area},
  journal = {Journal of Policy Modeling},
  year = {2006},
  volume = {28},
  pages = {943-964},
  database = {built own data set from OECD data},
  url = {http://www.bancaditalia.it/pubblicazioni/econo/temidi/td06/td609_06/td609/en_tema_609.pdf}
}

@UNPUBLISHED{golinelli:ItalyGDP2005,
  author = {Golinelli, Roberto and Giuseppe Parigi},
  title = {Short-run Italian GDP Forecasting and Real-Time Data},
  note = {Working paper},
  month = {July},
  year = {2005},
  database = {built own set from ISTAT data},
}

@ARTICLE{gotz:ijf2016,
  author = {Thomas B. Gotz and Alain Hecq and Jean-Pierre Urbain},
  title = {Combining forecasts from successive data vintages: An application
	to U.S. growth},
  journal = {International Journal of Forecasting},
  year = {2016},
  volume = {32},
  pages = {61-74},
  abstract = {This paper combines the issues of dealing with variables sampled at
	mixed frequencies and the usage of real-time versus latest-available data. In particular,
	the repeated observations forecasting (ROF) analysis of Stark and Croushore (2002) is extended
	to a multivariate setting in which the regressors may be sampled at higher frequencies
	than the regressand. This does not only enlarge the set of models one is able to consider,
	but gives rise to additional high-frequency vintages from which to extract data and on which to
	build fore- or nowcasts. By means of an empirical analysis in which we aim at fore-
	and nowcasting quarterly US GDP growth employing monthly and daily regressors, we compare the
	forecasting performances of a univariate model with several mixed-frequency models
	among which the MIDAS model which is designed specifically to cope with variables sampled
	at different frequencies. The additional dimension provided by different vintages
	allows us to compute several forecasts for a given calendar date and use them to construct
	forecast densities for each model. Testing for the equality of several predictive densities
	using scoring rules leads to the alternative of combining them. Given the evolvement of the
	implied weights across time, we propose time-varying ROF-based weights presenting an alternative
	to traditional weighting schemes.},
  keywords = {Real-Time Data, MIDAS, Repeated Observations Forecasting, Forecast
	Densities, Forecast Combinations},
}

@ARTICLE{grant:ei2013,
  author = {Darren Grant},
  title = {What Makes a Good Economy? Evidence from Public Opinion Surveys},
  journal = {Economic Inquiry},
  year = {2013},
}

@UNPUBLISHED{gregory:payrolls2008,
  author = {Gregory, Allan W. and Julia Hui Zhu},
  title = {Forecast Accuracy Improvement: Evidence from U.S. Nonfarm Payroll Employment},
  note = {Queen's University working paper},
  month = {October},
  year = {2008},
}

@ARTICLE{grimm:scb1998,
  author = {Grimm, Bruce T. and Robert P. Parker},
  title = {Reliability of the Quarterly and Annual Estimates of GDP and Gross
	Domestic Income},
  journal = {Survey of Current Business},
  year = {1998},
  pages = {12-25},
  month = {December},
  url = {http://www.bea.gov/scb/pdf/NATIONAL/NIPA/1998/1298od.pdf}
}

@ARTICLE{Grimm:scb2006,
  author = {Bruce T. Grimm and Teresa L. Weadock},
  title = {Gross Domestic Product: Revisions and Source Data},
  journal = {Survey of Current Business},
  year = {2006},
  volume = {86},
  pages = {11-15},
  month = {February},
  abstract = {The goal of this article is to explain the relationship between the first three quarterly GDP estimates and the source data that each of these estimates incorporates. This article also illustrates that the differences between the quarterly GDP estimates and the first annual 	revision estimate, which incorporates higher quality source data, are relatively small. Thus, the earliest quarterly estimates of GDP present a general picture of the economy---growth, trends, and component activity---that changes relatively little through subsequent revisions.},
}

@ARTICLE{groshen:jep2017,
  author = {Erica L. Groshen and Brian C. Moyer and Ana M. Aizcorbe and Ralph Bradley and David M. Friedman},
  title = {How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches},
  journal = {Journal of Economic Perspectives},
  year = {2017},
  volume = {31},
  pages = {187-210},
  number = {2},
  month = {Spring},
}

@ARTICLE{guerrero:ijf1993,
  author = {Guerrero, Victor M.},
  title = {Combining Historical and Preliminary Information to Obtain Timely Time Series Data},
  journal = {International Journal of Forecasting},
  year = {1993},
  pages = {477-485},
}

@ARTICLE{gumbau:frbb2013,
  author = {Fabia Gumbau-Brisa and Giovanni P. Olivei},
  title = {An Evaluation of the Federal Reserve Estimates of the Natural Rate of Unemployment in Real Time},
  journal = {Federal Reserve Bank of Boston Working Paper No. 13-24},
  year = {2013},
}

@Unpublished{guo:stock,
  author   = {Hui Guo and Yu-Jou Pai},
  title    = {Stock Market and Real Economy: Unwritten History Matters},
  abstract = {Economic concepts, methods, and variable classifications of personal consumption expenditures (PCE) are regularly revised to accurately reflect evolving economy; however, history is rewritten when these updates are adopted retrospectively to measure past economy. Consequently, latest-vintage PCE is significantly less informative about future stock market returns than real-time-vintage PCE. Moreover, in revised data only the fourth quarter consumption growth predicts market returns. The seasonality, which reflects revisions of seasonal adjustment factors, disappears when using real-time data. These findings are consistent with the countercyclical equity premium hypothesis and lend support to using real-time data in empirical studies.},
  note = {manuscript}
}

@ARTICLE{guo:ei2009,
  author = {Guo, Hui},
  title = {Data Revisions and Out-of-Sample Return Predictability},
  journal = {Economic Inquiry},
  year = {2009},
  volume = {47},
  pages = {81-97},
  month = {January},
  note = {Previous version was: 'On the Real-Time Forecasting Ability of the Consumption-Wealth Ratio.' Working paper 2003-007B, Federal Reserve
	Bank of St. Louis},
  database = {built own data set from SCB (cites Croushore and Stark)},
   url = {http://research.stlouisfed.org/wp/2003/2003-007.pdf}
}

@ARTICLE{haltom:frbaer2005,
  author = {Haltom, Nicholas L. and Vanessa D. Mitchell and Ellis W. Tallman},
  title = {Payroll Employment Data: Measuring the Effects of Annual Benchmark Revisions},
  journal = {Federal Reserve Bank of Atlanta Economic Review},
  year = {2005},
  pages = {1-23},
  month = {Second Quarter},
  database = {RTDSM},
  url = {http://www.frbatlanta.org/filelegacydocs/erq205_haltom.pdf}
}

@ARTICLE{hamilton:ijf2011,
  author = {James D. Hamilton},
  title = {Calling Recessions in Real Time},
  journal = {International Journal of Forecasting},
  year = {2011},
  volume = {27},
  pages = {1006-1026},
  number = {4},
  month = {October-December},
}

@UNPUBLISHED{hanson:FedFore2006,
  author = {Hanson, Michael S. and Jayson Whitehorn},
  title = {Reconsidering the Optimality of Federal Reserve Forecasts},
  note = {Working paper, Wesleyan University},
  month = {August},
  year = {2006},
  database = {RTDSM},
  url = {la-macro.vassar.edu/HansonWhitehorn.pdf}
}

@ARTICLE{harrison:ijf2005,
  author = {Harrison, Richard and George Kapetanios and Tony Yates},
  title = {Forecasting with Measurement Errors in Dynamic Models},
  journal = {International Journal of Forecasting},
  year = {2005},
  volume = {21},
  pages = {595-607},
  number = {3},
  month = {July},
  url = {http://repec.org/res2003/Yates.pdf}
}

@UNPUBLISHED{harrison:tvme2001,
  author = {R. Harrison and G. Kapetanios and T. Yates},
  title = {Estimating Econometric Equations under Time Varying Measurement Error},
  note = {Manuscript},
  year = {2001},
}

@UNPUBLISHED{harrison:pifore2001,
  author = {Harrison, Richard and George Kapetanios and Tony Yates},
  title = {Some Issues and Questions on Inflation Forecasting and Data Uncertainty},
  note = {Manuscript},
  year = {2001},
}

@ARTICLE{harvey:err1983,
  author = {Harvey, A.C. and C.R. McKenzie and D.P.C. Blake and M.J. Desai},
  title = {Irregular Data Revisions},
  journal = {U.S. Department of Commerce, Economic Research Report ER-5},
  year = {1983},
  pages = {329-347},
  part = {Applied Time Series Analysis of Economic Data},
  note = {in Arnold Zellner, ed. Washington, D.C},
}

@ARTICLE{hayashi:el2021,
  author = {Fumio Hayashi and Yuta Tachi},
  title = {The Nowcast Revision Analysis Extended},
  journal = {Economics Letters},
  year = {2021},
  volume = {209},
}

@UNPUBLISHED{hecq:varvecm2009,
  author = {Alain Hecq and Jan P.A.M. Jacobs},
  title = {On the VAR-VECM Representation of Real Time Data},
  month = {September},
  year = {2009},
  note = {working paper}
}

@UNPUBLISHED{hecq:revisions2008,
  author = {Hecq, Alain and Gian Luigi Mazzi},
  title = {Advanced Revision Analysis for Economic Time Series and Their Role for Improving Forecast Accuracy},
  note = {Working paper, Maastricht University},
  month = {June},
  year = {2008},
}

@Article{hecq:jmacro2019,
  author   = {Alain Hecq and Jan P.A.M. Jacobs and Michalis P. Stamatogiannis},
  title    = {Testing for news and noise in non-stationary time series subject to multiple historical revisions},
  journal  = {Journal of Macroeconomics},
  year     = {2019},
  volume   = {60},
  pages    = {396-407},
  abstract = {This paper focuses on testing non-stationary real-time data for forecastability, i.e., whether data revisions reduce noise or are news, by putting data releases in vector-error correction forms. To deal with historical revisions which affect the whole vintage of time series due to redefinitions, methodological innovations etc., we employ the recently developed impulse indicator saturation approach, which involves potentially adding an indicator dummy for each observation to the model. We illustrate our procedures with the U.S. real GNP/GDP series of the Federal Reserve Bank of Philadelphia and find that revisions to this series neither reduce noise nor can be considered as news.},
  doi      = {10.1016/j.jmacro.2019.03.003},
}

@ARTICLE{heij:ijf2011,
  author = {Christiaan Heij and Dick van Dijk and Patrick J.F. Groenen},
  title = {Real-time macroeconomic forecasting with leading indicators: An empirical	comparison},
  journal = {International Journal of Forecasting},
  year = {2011},
  volume = {27},
  pages = {466-481},
  number = {2},
  month = {April-June},
}

@ARTICLE{helliesen:ee2021,
  author = {Magnus Kvale Helliesen and Havard Hungnes and Terje Skjerpen},
  title = {Revisions in the Norwegian National Accounts: Accuracy, Unbiasedness, and Efficiency in the Preliminary Figures},
  journal = {Empirical Economics},
  year = {2021},
}

@UNPUBLISHED{herbst:comovement2010,
  author = {Edward Herbst and Frank Schorfheide},
  title = {Evaluating VAR and DSGE Model Predictions of Comovements},
  note = {University of Pennsylvania},
  month = {October},
  year = {2010},
  keywords = {Bayesian Methods, DSGE Models, Forecast Evaluation, Macroeconomic  Forecasting},
  owner = {dcrousho},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/fe_v2.pdf}
}

@ARTICLE{herrmann:najef2005,
  author = {Herrmann, Heinz and Athanasios Orphanides and Pierre L. Siklos},
  title = {Real-Time Data and Monetary Policy},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {271-276},
  month = {December},
}

@ARTICLE{himmelberg:frbny2004,
  author = {Himmelberg, Charles P. and James M. Mahoney and April Bang and Brian 	Chernoff},
  title = {Recent Revisions to Corporate Profits: What We Know and When We Know It},
  journal = {Federal Reserve Bank of New York Current Issues in Economics and Finance},
  year = {2004},
  volume = {10},
  month = {March},
  database = {RTDSM},
  url = {http://www.newyorkfed.org/research/current_issues/ci10-3.pdf}
}

@ARTICLE{hogrefe:asta2008,
  author = {Hogrefe, Jens},
  title = {Forecasting data revisions of GDP: a mixed frequency approach},
  journal = {Advances in Statistical Analysis},
  year = {2008},
  volume = {92},
  pages = {271-296},
  number = {3},
  month = {August},
}

@ARTICLE{holden:ae1982,
  author = {Holden, K. and D.A. Peel},
  title = {Data Revisions and Time Series Models of GDP and Its Components},
  journal = {Applied Economics},
  year = {1982},
  volume = {14},
  pages = {101-110},
}

@ARTICLE{holden:stat1982,
  author = {Holden, K. and D.A. Peel},
  title = {The Relationships Between Preliminary and Revised Estimates of GDP
	and Consumers' Expenditure in the UK},
  journal = {The Statistician},
  year = {1982},
  volume = {31},
  pages = {259-266},
  month = {June},
}

@ARTICLE{howrey:jesm1996,
  author = {Howrey, E. Philip},
  title = {Forecasting GNP With Noisy Data: A Case Study},
  journal = {Journal of Economic and Social Measurement},
  year = {1996},
  volume = {22},
  pages = {181-200},
}

@ARTICLE{howrey:restat1984,
  author = {Howrey, E. Philip},
  title = {Data Revision, Reconstruction, and Prediction: An Application to Inventory Investment},
  journal = {Review of Economics and Statistics},
  year = {1984},
  volume = {66},
  pages = {386-393},
  month = {August},
}

@Article{howrey:restat1978,
  author    = {Howrey, E. Philip},
  title     = {The Use of Preliminary Data in Econometric Forecasting},
  journal   = {Review of Economics and Statistics},
  year      = {1978},
  volume    = {60},
  pages     = {193-200},
  month     = {May},
  comment   = {Uses Kalman filter in forecasting to account for potential data revisions within a forecasting model},
  url       = {http://www.bancaditalia.it/pubblicazioni/econo/temidi/td01/td437_01/td437/tema_437_01.pdf},
}

@UNPUBLISHED{hugheshallett:deficits2007,
  author = {Hughes Hallett, Andrew and Rasmus Kattai and John Lewis},
  title = {Early Warning or Just Wise After the Event? The Problem of Using Cyclically Adjusted Budget Deficits for Fiscal Surveillance},
  note = {Working paper, Bank of Estonia},
  year = {2007},
  database = {built own set using OECD's Economic Outlook},
}

@UNPUBLISHED{hulsewig:eurogdp2008,
  author = {Hulsewig, Oliver and Johannes Mayr and Timo Wollmershauser},
  title = {Forecasting Euro Area Real GDP: Optimal Pooling of Information},
  note = {Ifo Institute for Economic Research working paper},
  month = {March},
  year = {2008},
  database = {OECD Main Economic Indicators Revisions Data Base},
  url = {http://www.cesifo.de/DocCIDL/cesifo1_wp2371.pdf}
}

@ARTICLE{ince:jimf2014,
  author = {Ince, Onur},
  title = {Forecasting Exchange Rates Out-of-Sample with Panel Methods and Real-Time Data},
  journal = {Journal of International Money and Finance},
  year = {2014},
  volume = {43},
  month = {May},
  pages = {1-18}
}

@UNPUBLISHED{ince:oosxrate2017,
  author = {Onur Ince and Tanya Molodtsova}, 
  title = {Out-of-Sample Exchange Rate Predictability with Real-Time Data},
  note = {working paper},
  month = {January},
  year = {2017},
}

@ARTICLE{ince:em2013,
  author = {Onur Ince and David H. Papell},
  title = {The (Un)Reliability of Real-Time Output Gap Estimates with Revised
	Data},
  journal = {Economic Modelling},
  volume = {33},
  pages = {713-721},
  month = {July},
  year = {2013},
  abstract = {This paper investigates the differences between real-time and ex-post 	output gap estimates using a newly-constructed international real-time data set over the period from 1973:Q1 to 2007:Q2. We extend the findings in Orphanides and van Norden (2002) for the United States that the use of ex-post information in calculating potential output, not the data revisions themselves, is the major cause of the difference between real-time and ex-post output gap estimates to nine additional OECD countries. The results are robust to the use of linear, quadratic, Hodrick-Prescott, and Baxter-King detrending methods. By using quasi real-time methods, reliable realtime output gap estimates can be constructed with revised data.},
}

@ARTICLE{inoue:jbes2005,
  author = {Inoue, Atsushi and Barbara Rossi},
  title = {Recursive Predictability Tests for Real-Time Data},
  journal = {Journal of Business and Economic Statistics},
  year = {2005},
  volume = {23},
  pages = {336-345},
  month = {July},
  database = {RTDSM},
}

@UNPUBLISHED{jaaskela:uncertainty2005,
  author = {Jaaskela, Jarkko and Tony Yates},
  title = {Monetary Policy and Data Uncertainty},
  note = {Manuscript, Bank of England},
  month = {October},
  year = {2005},
}

@UNPUBLISHED{jacobs:swiss2006,
  author = {Jacobs, Jan and Jan-Egbert Sturm},
  title = {A Real-Time Analysis of the Swiss Trade Account},
  note = {Working paper, University of Groningen},
  year = {2006},
  database = {new Swiss data set},
  url = {http://repec.org/mmf2006/up.10144.1159525837.pdf}
}

@ARTICLE{jacobs:jm2016,
  author = {Jan P.A.M. Jacobs and Simon van Norden},
  title = {Why are initial estimates of productivity growth so unreliable?},
  journal = {Journal of Macroeconomics},
  year = {2016},
  volume = {47},
  pages = {200-213},
}

@ARTICLE{jacobs:je2011,
  author = {Jacobs, Jan P.A.M. and Simon van Norden},
  title = {Modeling Data Revisions: Measurement Error and Dynamics of 'True' Values},
  journal = {Journal of Econometrics},
  volume = {161},
  number = {2},
  pages = {101-109},
  month = {April},
  year = {2011},
  abstract = {Policy makers must base their decisions on preliminary and partially revised data of varying reliability. Realistic modeling of data revisions is required to guide decision makers in their assessment of current and future conditions. This paper provides a new framework with which to model data revisions. Recent empirical work suggests that measurement errors typically have much more complex dynamics than existing models of data revisions allow. This paper describes a state-space model that allows for richer dynamics in these measurement errors, including the noise, news and spillover effects documented in this literature. We also show how to relax the common assumption that \true" values are observed after a few revisions. The result is a unified and flexible framework that allows for more realistic data revision properties, and allows the use of standard methods for optimal real-time estimation of trends and cycles. We illustrate the application of this framework with real-time data on U.S. real output growth.},
  database = {RTDSM},
  url = {http://neumann.hec.ca/pages/simon.van-norden/wps/CCSO\%20WP\%202006-07.pdf}
}

@ARTICLE{jacobs:ifos2004,
  author = {Jacobs, Jan and Jan-Egbert Sturm},
  title = {Do Ifo Indicators Help Explain Revisions in German Industrial Production?},
  journal = {Ifo Survey Data in Business Cycle and Monetary Policy Analysis},
  year = {2004},
  note = {Jan-Egbert Sturm and Timo Wollmershauser, eds. (Heidelberg: Physica-Verlag)},
  database = {Built own data set from Ifo Indicators},
  url = {http://www.cesifo-group.de/DocCIDL/cesifo1_wp1205.pdf}
}

@ARTICLE{jo:jbes2019,
  author = {Soojin Jo and Rodrigo Sekkel},
  title = {Macroeconomic Uncertainty Through the Lens of Professional Forecasters},
  journal = {Journal of Business and Economic Statistics},
  volume = {37},
  number = {3},
  year = {2019}, 
  pages = {436-446},
  abstract = {We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of various economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time measure of uncertainty surrounding subjective forecasts in a simple framework. We jointly model and estimate macroeconomic (common) and indicator-specific uncertainties of four indicators, using a factor stochastic volatility model. Our macroeconomic uncertainty estimates have three major spikes has three major spikes aligned with the 1973–1975, 1980, and 2007–2009 recessions, while other recessions were characterized by increases in indicator-specific uncertainties. We also show that the selection of data vintages affects the estimates and relative size of jumps in estimated uncertainty series. Finally, our macroeconomic uncertainty has a persistent negative impact on real economic activity, rather than producing “wait-and-see” dynamics.}
}

@ARTICLE{joutz:ae98,
  author = {Joutz, Frederick L. and Stekler, H. O.},
  title = {Data Revisions and Forecasting},
  journal = {Applied Economics},
  year = {1998},
  volume = {30},
  pages = {1011-1016},
  number = {8},
  month = {August},
}

@ARTICLE{kamada:najef2005,
  author = {Kamada, Koichiro},
  title = {Real-Time Estimation of the Output Gap in Japan and its Usefulness for Inflation Forecasting and Policymaking},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {309-32},
  number = {3},
  month = {December},
  database = {built own set with Bank of Japan data},
  url = {www.e.u-tokyo.ac.jp/cirje/research/workshops/macro/macropaper04/kamada.pdf}
}

@UNPUBLISHED{kapetanios:UKrevisions2004,
  author = {Kapetanios, George and Tony Yates},
  title = {Estimates of Measurement Error in United Kingdom GDP and its Expenditure Components},
  note = {Bank of England manuscript},
  year = {2004},
}

@UNPUBLISHED{kapetanios:refining2004,
  author = {Kapetanios, G. and T. Yates},
  title = {Using a Real-Time Dataset for Refining Preliminary Data and Forecasting},
  note = {Manuscript},
  month = {July},
  year = {2004},
}

@ARTICLE{kapetanios:jae2010,
  author = {George Kapetanios and Tony Yates},
  title = {Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Backcasting and Forecasting in Dynamic Models},
  journal = {Journal of Applied Econometrics},
  volume = {25},
  number = {5},
  pages = {869-893},
  month = {August},
  year = {2010},
  database = {Castle and Ellis (2002)},
  url = {http://www.econ.qmul.ac.uk/papers/doc/wp520.pdf}
}

@ARTICLE{kavajecz:frbstlr1994,
  author = {Kavajecz, Kenneth},
  title = {The Evolution of the Federal Reserve's Monetary Aggregates: A Timeline},
  journal = {Federal Reserve Bank of St. Louis Review},
  year = {1994},
  pages = {32-66},
  month = {March/April},
  url = {http://research.stlouisfed.org/publications/review/94/03/9403kk.pdf}
}

@ARTICLE{kavajecz:restat1995,
  author = {Kavajecz, Kenneth and Sean Collins},
  title = {Rationality of Preliminary Money Stock Estimates},
  journal = {Review of Economics and Statistics},
  year = {1995},
  volume = {77},
  pages = {32-41},
  month = {February},
  database = {built own from Fed Money Stock data},
}

@ARTICLE{kawagoe:qnaj2007,
  author = {Kawagoe, Masaaki},
  title = {How Is Economic Growth Rate Revised Afterwards? Real-time Data Analysis of Real GDP Growth Rate},
  journal = {Quarterly Journal of National Accounts of Japan},
  year = {2007},
  volume = {134},
  note = {Economic and Social Research Institute, Cabinet Office, Japanese Government (in Japanese)},
}

@ARTICLE{keane:aer1990,
  author = {Keane, Michael P. and David E. Runkle},
  title = {Testing the Rationality of Price Forecasts: New Evidence From Panel Data},
  journal = {American Economic Review},
  year = {1990},
  volume = {80},
  pages = {714-735},
  month = {September},
}

@UNPUBLISHED{kemme:rba2008,
  author = {Kemme, David M. and Gennady Lyakir},
  title = {Understanding Reserve Bank of Australia Monetary Policy Using Real-Time Data and Forward-Looking Taylor Rules},
  note = {Working paper},
  month = {November},
  year = {2008},
}

@UNPUBLISHED{kennedy:ip1990,
  author = {Kennedy, James E.},
  title = {An Analysis of Revisions to the Industrial Production Index},
  note = {working paper, Board of Governors of the Federal Reserve System, Economic Activity Section, 109},
  year = {1990},
}

@ARTICLE{kenny:et1985,
  author = {Kenny, P.B.},
  title = {Revisions to Quarterly Estimates of Gross Domestic Product},
  journal = {Economic Trends},
  year = {1985},
  pages = {97-112},
  month = {July},
}

@ARTICLE{kenny:et1987,
  author = {Kenny, P.B.},
  title = {Revisions to Quarterly Estimates of GDP},
  journal = {Economic Trends},
  year = {1987},
  pages = {82-90},
  month = {August},
}

@ARTICLE{kishor:jmcb2014,
  author = {Kundan Kishor and Evan Koenig},
  title = {Credit Indicators as Predictors of Economic Activity: A Real-Time VAR Analysis},
  journal = {Journal of Money, Credit, and Banking},
  year = {2014},
  volume = {46},
  pages = {545-564},
  number = {2-3},
  month = {March-April},
  note = {Kundan Kishor (University of Wisconsin-Milwaukee), Evan Koenig (FRB Dallas)},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Koenig\%20paper.pdf}
}

@UNPUBLISHED{kishor:IndiaWPI2009,
  author = {Kishor, N. Kundan},
  title = {Revisions to WPI Inflation in India: News or Noise?},
  note = {Working paper, University of Wisconsin-Milwaukee},
  month = {May},
  year = {2009},
}

@Article{kishor:jbes2012,
  author    = {Kishor, N. Kundan and Evan F. Koenig},
  journal   = {Journal of Business and Economic Statistics},
  title     = {VAR Estimation and Forecasting When Data Are Subject to Revision},
  year      = {2012},
  month     = {February},
  note      = {Federal Reserve Bank of Dallas Economic Research Working Paper No. 0501},
  pages     = {181-190},
  volume    = {30},
  database  = {RTDSM},
  url       = {http://dallasfed.org/research/papers/2005/wp0501.pdf},
}

@Article{kishor:ijcb2021,
  author   = {N. Kundan Kishor and Evan F. Koenig},
  journal  = {International Journal of Central Banking},
  title    = {Finding a Role for Slack in Real-Time Inflation Forecasting},
  year     = {2021},
  abstract = {Real-time forecasting of PCE inflation is most successful when headline inflation is stripped of high-frequency noise and core inflation’s trend and cycle are separately forecasted. It proves helpful, additionally, to allow cyclical inflation to respond to labor-market slack, to allow for a late-1990s break in the behavior of trend inflation, and to explicitly model revisions to headline inflation. We do all of this within the context of an unobserved common-components model of inflation and slack. The model’s real-time inflation forecasts are significantly more accurate than those generated by benchmark models. That outperformance and the finding that cyclical inflation responds to slack are robust to an alternative measure of slack, an alternative model of trend inflation, and an alternative treatment of data revisions.},
}

@UNPUBLISHED{knetsch:GermanRevisions2008,
  author = {Knetsch, Thomas A. and Hans-Eggert Reimers},
  title = {How to Treat Benchmark Revisions? The Case of German Production and Orders Statistics},
  note = {Deutsche Bundesbank working paper},
  month = {February},
  year = {2008},
  database = {built own data set},
}

@ARTICLE{koenig:frbdel2006,
  author = {Koenig, Evan},
  title = {Through a Glass Darkly: How Data Revisions Complicate Monetary Policy},
  journal = {Federal Reserve Bank of Dallas Economic Letter},
  year = {2006},
  month = {December},
}

@INBOOK{koenig:oecd2005,
  chapter = {The Use and Abuse of Real-Time and Anecdotal Information in Monetary Policy Making},
  pages = {241-253},
  title = {Statistics, Knowledge, and Policy: Key Indicators to Inform Decision-Making},
  publisher = {OECD},
  year = {2005},
  author = {Koenig, Evan},
  address = {Paris},
}

@ARTICLE{koenig:el2003,
  author = {Koenig, Evan},
  title = {Is the Markup a Useful Real-Time Predictor of Inflation?},
  journal = {Economics Letters},
  year = {2003},
  volume = {80},
  pages = {261-267},
  database = {built own data set},
}

@ARTICLE{koenig:restat2003,
  author = {Koenig, Evan and Sheila Dolmas and Jeremy Piger},
  title = {The Use and Abuse of 'Real-Time' Data in Economic Forecasting},
  journal = {Review of Economics and Statistics},
  year = {2003},
  volume = {85},
  pages = {618-628},
  url = {research.stlouisfed.org/wp/2001/2001-015.pdf}
}

@ARTICLE{kolasa:jmcb2012,
  author = {Marcin Kolasa and Michal Rubaszek and Pawel Skrzypczynski},
  title = {Putting the New Keynesian DSGE Model to the Real-Time Forecasting Test},
  journal = {Journal of Money, Credit, and Banking},
  year = {2012},
}

@Article{kozicki:frbker2004,
  author    = {Kozicki, Sharon},
  title     = {How Do Data Revisions Affect The Evaluation and Conduct of Monetary Policy?},
  journal   = {Federal Reserve Bank of Kansas City Economic Review},
  year      = {2004},
  month     = {First Quarter},
  comment   = {Examines revisions of data (observables), as well as revisions of economic concepts (ex: potential output) to see how they affect policy. Revisions to CBO potential output and the natural rate of unemployment affect estimates of the equilibrium real interest rate. Test how much data uncertainty affects policy prescriptions of different rules & supports nominal income targeting over Taylor rule and other rules.},
  database  = {RTDSM},
  url       = {http://www.kansascityfed.org/publicat/econrev/PDF/1Q04kozi.pdf},
}

@ARTICLE{kozicki:jm2002,
  author = {Kozicki, Sharon},
  title = {Comments on: `Forecasting with a Real-Time Data Set for Macroeconomists.'},
  journal = {Journal of Macroeconomics},
  year = {2002},
  volume = {24},
  pages = {541-558},
  month = {December},
  database = {RTDSM},
}

@UNPUBLISHED{kozicki:gap2005,
  author = {Kozicki, Sharon and P.A. Tinsley},
  title = {Minding the Gap: Central Bank Estimates of the Unemployment Natural Rate},
  note = {Federal Reserve Bank of Kansas City Research Working Paper 05-03},
  month = {September},
  year = {2005},
  database = {built own using Fed Greenbook forecasts},
  url = {http://www.kansascityfed.org/PUBLICAT/RESWKPAP/PDF/RWP05-03.pdf}
}

@ARTICLE{krane:frbcep2003,
  author = {Krane, Spencer},
  title = {An Evaluation of Real GDP Forecasts: 1996-2001},
  journal = {Federal Reserve Bank of Chicago Economic Perspectives},
  year = {2003},
  pages = {2-21},
  month = {First Quarter},
  database = {built own from NIPA data},
  url = {http://www.chicagofed.org/publications/economicperspectives/2003/1qeppart1.pdf}
}

@ARTICLE{krikelas:frbaer1994,
  author = {Krikelas, Andrew C.},
  title = {Revisions to Payroll Employment Data: Are They Predictable?},
  journal = {Federal Reserve Bank of Atlanta Economic Review},
  year = {1994},
  pages = {17-29},
  month = {November/December},
}

@ARTICLE{kugler:najef2005,
  author = {Kugler, Peter and Thomas J. Jordan and Carlos Lenz and Marcel R. Savioz},
  title = {GDP Data Revisions and Forward-Looking Monetary Policy in Switzerland},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {351-372},
  month = {December},
  database = {built own data set with Swiss GDP data},
}

@ARTICLE{kurrman:restat2021,
  author = {Andre Kurmann and Eric Sims},
  title = {Revisions in Utilization-Adjusted TFP and Robust Identification of News Shocks},
  journal = {Review of Economics and Statistics},
  year = {2021},
  volume = {103},
  number = {2},
  pages = {216–235},
  doi = {10.1162/rest_a_00896},
}

@ARTICLE{kurz:el2018,
  author = {Malte S. Kurz},
  title = {A note on low-dimensional Kalman smoothers for systems with lagged states in the measurement equation},
  journal = {Economics Letters},
  year = {2018},
  volume = {168},
  pages = {42–45},
  doi = {10.1016/j.econlet.2018.03.037},
}

@ARTICLE{lahiri:jae2006,
  author = {Lahiri, Kajal and Fushang Liu},
  title = {Modeling Multi-Period Inflation Uncertainty Using a Panel of Density Forecasts},
  journal = {Journal of Applied Econometrics},
  year = {2006},
  volume = {21},
  pages = {1199-1220},
  month = {December},
  database = {RTDSM and SPF},
  url = {www.albany.edu/economics/Research/2006/Lahiri_LiuPaper_JAE_final.pdf}
}

@ARTICLE{lahiri:jae2016,
  author = {Kajal Lahiri and George Monokroussos and Yongchen Zhao},
  title = {Forecasting Consumption: The Role of Consumer Confidence in Real Time with Many Predictors},
  journal = {Journal of Applied Econometrics},
  volume = {31}, 
  number = {7},
  month = {November/December}, 
  pages = {1254-1275},
}

@UNPUBLISHED{lansing:TrendShift2002,
  author = {Lansing, Kevin},
  title = {Learning About a Shift in Trend Output},
  note = {Federal Reserve Bank of San Francisco working paper 2002},
  year = {2002},
  url = {http://www.sf.frb.org/econrsrch/workingp/2000/wp00-16bk.pdf}
}

@ARTICLE{lansing:frbsfer2002,
  author = {Lansing, Kevin J.},
  title = {Real-Time Estimation of Trend Output and the Illusion of Interest Rate Smoothing},
  journal = {Federal Reserve Bank of San Francisco Economic Review},
  year = {2002},
  pages = {17-34},
  database = {RTDSM},
  url = {http://www.frbsf.org/publications/economics/review/2002/article2.pdf}
}

@ARTICLE{lee:jmcb2015,
  author = {Kevin Lee and James Morley and Kalvinder Shields},
  title = {The Meta Taylor Rule},
  journal = {Journal of Money, Credit, and Banking},
  year = {2015},
  volume = {47},
  pages = {73-98},
  number = {1},
  month = {February},
}

@UNPUBLISHED{lee:newinfo2010,
  author = {Kevin Lee and Nilss Olekalns and Kalvinder Shields},
  title = {Nowcasting, Business Cycle Dating and the Interpretation of New Information When Real-Time Data Are Available},
  note = {University of Leicester},
  month = {Oct},
  year = {2010},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Lee\%20paper.pdf}
}

@UNPUBLISHED{lee:smoothing2020,
  author = {Saiah Lee},
  title = {Monetary Policy under Data Uncertainty: Interest-Rate Smoothing from a Cross-Country Perspective},
  note = {Ulsan National Institute of Science and Technology},
  month = {Dec},
  year = {2020},
}

@UNPUBLISHED{loukoianova:FiscalRule2002,
  author = {Loukoianova, Elena and Shaun P. Vahey and Elizabeth C. Wakerly},
  title = {A Real Time Tax Smoothing Based Fiscal Policy Rule},
  note = {Working paper, University of Cambridge},
  month = {September},
  year = {2002},
  url = {http://www.econ.cam.ac.uk/dae/repec/cam/pdf/wp0235.pdf}
}

@ARTICLE{lubik:jme2016,
  author = {Thomas A. Lubik and Christian Matthes},
  title = {Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation},
  journal = {Journal of Monetary Economics},
  year = {2016},
  volume = {82},
  pages = {85-106},
  month = {September},
}

@UNPUBLISHED{lupi:italy2003,
  author = {Lupi, Claudio and Peracchi, Franco},
  title = {The limits of statistical information: How important are GDP revisions in Italy?},
  note = {Economics \& Statistics Discussion Papers esdp03005, University of Molise, Dept. SEGeS},
  year = {2003},
}

@ARTICLE{mandler:najef2012,
  author = {Mandler, Martin},
  title = {Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data},
  journal = {The North American Journal of Economics and Finance},
  year = {2012},
  volume = {23},
  pages = {228-245},
  number = {2},
}

@Article{mankiw:jme1984,
  author    = {Mankiw, N. Gregory and David E. Runkle and Matthew D. Shapiro},
  title     = {Are Preliminary Announcements of the Money Stock Rational Forecasts?},
  journal   = {Journal of Monetary Economics},
  year      = {1984},
  volume    = {14},
  pages     = {15-27},
  month     = {July},
  comment   = {Tests whether money data are noisy estimates or efficient forecasts
	of final data; finds that they are noisy estimates.},
}

@Article{mankiw:scb1986,
  author    = {Mankiw, N. Gregory and Matthew D. Shapiro},
  title     = {News or Noise: An Analysis of GNP Revisions},
  journal   = {Survey of Current Business},
  year      = {1986},
  pages     = {20-5},
  month     = {May},
  comment   = {Introduces news vs. noise terminology; finds that nominal and real
	output are news, not noise.},
  database  = {built own from NIPA},
  url       = {http://fraser.stlouisfed.org/publications/SCB/page/10438/1961/download/10438.pdf},
}

@ARTICLE{manski:nber2014,
  author = {Charles F. Manski},
  title = {Communicating Uncertainty in Official Economic Statistics},
  journal = {NBER working paper series},
  year = {2014},
  month = {May},
}

@ARTICLE{maravall:ea1986,
  author = {Maravall, Augustin and David A. Pierce},
  title = {The Transmission of Data Noise into Policy Noise in U.S. Monetary Control},
  journal = {Econometrica},
  year = {1986},
  volume = {54},
  pages = {961-79},
  month = {July},
}

@UNPUBLISHED{marcellino:benchmark2006,
  author = {Marcellino, Massimiliano},
  title = {A Simple Benchmark for Forecasts of Growth and Inflation},
  note = {C.E.P.R. Discussion Papers: 6012},
  month = {June},
  year = {2006},
}

@ARTICLE{marcellino:em2011,
  author = {Massimiliano Marcellino and Alberto Musso},
  title = {The Reliability of Real Time Estimates of the Euro Area Output Gap},
  journal = {Economic Modelling},
  year = {2011},
  volume = {28},
  pages = {1842-1856},
}

@Article{mariano:jf1995,
  author    = {Mariano, Roberto S. and Hisashi Tanizaki},
  title     = {Prediction of Final Data with Use of Preliminary and/or Revised Data},
  journal   = {Journal of Forecasting},
  year      = {1995},
  volume    = {14},
  pages     = {351-380},
  comment   = {Shows that the optimal method of predicting final data is to use both the revised data and the preliminary data; however a close second is to just use the preliminary data. Thus knowledge of final data is not necessarily crucial to forecasting later final data.},
  database  = {built own data set from Economic Report of the President},
  url       = {www.lib.kobe-u.ac.jp/repository/90000576.pdf},
}

@ARTICLE{masolo:jmcb2019,
  author = {Riccardo M. Masolo and Alessia Paccagnini},
  title = {Identifying Noise Shocks: A VAR with Data Revisions},
  journal = {Journal of Money, Credit and Banking}, 
  volume = {51},
  number = {8}, 
  pages = {2145-2172}, 
  month = {December},
  year = {2019},
}

@ARTICLE{mavroeidis:jel2014,
  author = {Sophocles Mavroeidis and Mikkel Plagborg-Moller and James H. Stock},
  title = {Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve},
  journal = {Journal of Economic Literature},
  year = {2014},
  volume = {52},
  pages = {124-188},
  number = {1},
}

@Unpublished{mcadam:2020,
  author   = {Peter McAdam and Anders Warne},
  title    = {Density Forecast Combinations: The Real-Time Dimension},
  abstract = {Euro area real-time density forecasts from three DSGE and three BVAR models are
compared with six model combination methods. The terms information and observation lag are
introduced to distinguish time shifts between data vintages and actuals used to compute model
weights and compare the forecast, respectively. Bounds for the density forecasts are presented,
allowing for benchmarking the methods. Empirically, combinations with limited weight variation
often improve upon the individual models for the output and the joint forecasts with inflation,
reflecting over-confident BVAR forecasts before the Great Recession. For inflation, a model performs
best with a DSGE for the short and a BVAR for the long horizons.},
}

@Unpublished{mcadam:wp2021,
  author   = {Peter McAdam and Anders Warne},
  title    = {Monetary policy model combination in real time},
  note = {Working paper},
  month = {November},
  year = {2021},
}

@UNPUBLISHED{mckenzie:OECDrevisions2007,
  author = {McKenzie, Richard},
  title = {Relative Size and Predictability of Revisions to GDP, Industrial Production and Retail Trade---A Comparative Analysis Across OECD Member Countries},
  note = {Working paper, OECD},
  month = {July},
  year = {2007},
}

@ARTICLE{mcnees:ijf1989,
  author = {McNees, Stephen K.},
  title = {Forecasts and Actuals: The Trade-Off Between Timeliness and Accuracy},
  journal = {International Journal of Forecasting},
  year = {1989},
  volume = {5},
  pages = {409-416},
}

@ARTICLE{mcnees:neer1989,
  author = {McNees, Stephen K.},
  title = {Estimating GNP: The Trade-Off Between Timeliness and Accuracy},
  journal = {New England Economic Review},
  year = {1986},
  pages = {3-10},
  month = {January/February},
}

@UNPUBLISHED{mehra:frbrwp2002,
  author = {Mehra, Yash},
  title = {The Taylor Principle, Interest Rate Smoothing, and Fed Policy in the 1970s and 1980s},
  note = {Federal Reserve Bank of Richmond working paper},
  year = {2002},
  database = {RTDSM and Greenbook forecasts},
  url = {http://www.richmondfed.org/publications/economic_research/working_papers/pdfs/wp02-3.pdf}
}

@Article{mehra:frbreq2010,
  author    = {Mehra, Yash and Bansi Sawhney},
  title     = {Inflation Measure, Taylor Rules, and the Greenspan-Bernanke Years},
  journal   = {Federal Reserve Bank of Richmond Economic Quarterly},
  year      = {2010},
  volume    = {96},
  number    = {2},
  pages     = {123-151},
  month     = {Second Quarter},
  comment   = {Suggests that Taylor rule performs better using core inflation rather than headline inflation.},
}

@Article{mertens:qe2020,
  author    = {Elmar Mertens and James M. Nason},
  title     = {Inflation and Professional Forecast Dynamics: An Evaluation of Stickiness, Persistence, and Volatility},
  journal   = {Quantitative Economics},
  year      = {2020},
  volume    = {11},
  pages     = {1485-1520},
}

@UNPUBLISHED{mesonnier:eurogap2006,
  author = {Mesonnier, Jean-Stephane},
  title = {The predictive content of the real interest rate gap for macroeconomic variables in the euro area},
  note = {Working paper, Bank of France},
  month = {September},
  year = {2006},
}

@ARTICLE{milani:jedc2017,
  author = {Fabio Milani},
  title = {Sentiment and the U.S. Business Cycle},
  journal = {Journal of Economic Dynamics and Control},
  year = {2017},
  pages = {289-311},
  volume = {82}
}

@UNPUBLISHED{mitchell:niesr2005,
  author = {Mitchell, James},
  title = {Should We Be Surprised by the Unreliability of Real-Time Output Gap Estimates? Density Estimates for the Euro Area},
  note = {National Institute of Economic and Social Research, Discussion Paper 225},
  month = {January},
  year = {2005},
  database = {built own set using ECB's Area Wide Model},
  url = {http://www.niesr.ac.uk/pubs/DPS/DP225.pdf}
}

@UNPUBLISHED{molodtsova:xrate2007,
  author = {Molodtsova, Tanya},
  title = {Real-Time Exchange Rate Predictability with Taylor Rule Fundamentals},
  note = {Working paper, University of Houston},
  month = {November},
  year = {2007},
}

@ARTICLE{molodtsova:jmcb2011,
  author = {Molodtsova, Tanya and Alex Nikolsko-Rzhevskyy and David H. Papell},
  title = {Taylor Rules and the Euro},
  journal = {Journal of Money, Credit, and Banking},
  year = {2011},
  volume = {43},
  pages = {535-552},
  number = {2-3},
  month = {March-April},
  database = {RTDSM and OECD},
  url = {www.uh.edu/~dpapell/Taylor\%20Euro.pdf}
}

@ARTICLE{molodtsova:jme2008,
  author = {Molodtsova, Tanya and Alex Nikolsko-Rzhevskyy and David H. Papell},
  title = {Taylor Rules with Real-Time Data: A Tale of Two Countries and One Exchange Rate},
  journal = {Journal of Monetary Economics},
  year = {2008},
  volume = {55},
  pages = {S63-S79},
  number = {Supplement1},
  month = {October},
  database = {RTDSM; St. Louis Fed for non-revised data},
}

@UNPUBLISHED{monti:judgment2008,
  author = {Monti, Francesca},
  title = {Forecasting with Judgment and Models},
  note = {Working paper, ECARES},
  month = {October},
  year = {2008},
}

@BOOK{morgenstern:book1963,
  title = {On the Accuracy of Economic Observations},
  publisher = {Princeton University Press},
  year = {1963},
  author = {Morgenstern, Oskar},
  address = {Princeton},
}

@ARTICLE{mork:cje1990,
  author = {Mork, Knut A.},
  title = {Forecastable Money-Growth Revisions: A Closer Look at the Data},
  journal = {Canadian Journal of Economics},
  year = {1990},
  volume = {23},
  pages = {593-616},
  month = {August},
  database = {borrowed M1 data from Mankiw (1984)},
}

@Article{mork:jbes1987,
  author    = {Mork, Knut A.},
  title     = {Ain't Behavin': Forecast Errors and Measurement Errors in Early GNP Estimates},
  journal   = {Journal of Business and Economic Statistics},
  year      = {1987},
  volume    = {5},
  pages     = {165-75},
  month     = {April},
  comment   = {Shows that neither news nor noise are necessary; a better test is one for well-behavedness, which is a regression of the revision on data known when the initial release occurred. Finds that revisions to real GNP growth are correlated with data known when initial release was made.},
  database  = {built own data set},
}

@UNPUBLISHED{morris:wp2016,
  author = {Stephen D. Morris and Dillon Sandhu},
  title = {Controlling Output Gap Revisions Around Turning Points},
  month = {May},
  year = {2016},
  owner = {dcrousho},
  timestamp = {2017.06.05}
}

@ARTICLE{mullineaux:aer1980,
  author = {Mullineaux, Donald J},
  title = {Inflation Expectations and Money Growth in the United States},
  journal = {American Economic Review},
  year = {1980},
  volume = {70},
  pages = {149-161},
  month = {March},
}

@ARTICLE{nakamura:frbpbr2008,
  author = {Nakamura, Leonard},
  title = {The Mismeasured Personal Saving Rate Is Still Useful: Using Real-Time Data to Improve Forecasting},
  journal = {Federal Reserve Bank of Philadelphia Business Review},
  year = {2008},
  pages = {9-20},
  month = {Q4},
}

@UNPUBLISHED{nakamura:psrpih2007,
  author = {Nakamura, Leonard I. and Tom Stark},
  title = {Mismeasured Personal Saving and the Permanent Income Hypothesis},
  note = {Federal Reserve Bank of Philadelphia working paper 07-8},
  month = {February},
  year = {2007},
  database = {RTDSM},
  url = {http://www.philadelphiafed.org/files/wps/2007/wp07-8.pdf}
}

@UNPUBLISHED{nakamura:psrrev2005,
  author = {Nakamura, Leonard I. and Tom Stark},
  title = {Benchmark Revisions and the U.S. Personal Saving Rate},
  note = {Federal Reserve Bank of Philadelphia working paper 05-6},
  month = {April},
  year = {2005},
  database = {RTDSM},
  url = {http://www.phil.frb.org/files/wps/2005/wp05-6.pdf}
}

@Article{nalewaik:jmcb2012,
  author    = {Nalewaik, Jeremy J.},
  title     = {Estimating Probabilities of Recession in Real Time Using GDP and GDI},
  journal   = {Journal of Money, Credit, and Banking},
  year      = {2012},
  volume    = {44},
  number    = {1},
  pages     = {235-253},
  month     = {February},
  note      = {Federal Reserve Board of Governors, FEDS working paper 2007-07},
  comment   = {Uses gross domestic income to see if it helps show recessions in real time earlier than GDP; it does, especially because of shifts in corporate profits.},
  database  = {built own set using Survey of Current Business},
  url       = {http://www.federalreserve.gov/pubs/feds/2007/200707/200707pap.pdf},
}

@ARTICLE{nalewaik:ijf2011,
  author = {Jeremy J. Nalewaik},
  title = {Incorporating Vintage Differences and Forecasts into Markov Switching Models},
  journal = {International Journal of Forecasting},
  year = {2011},
  volume = {27},
  pages = {281-307},
  number = {2},
  month = {April-June},
}

@ARTICLE{nallareddy:ar2017,
  author = {Suresh Nallareddy and Maria Ogneva},
  title = {Predicting Restatements in Macroeconomic Indicators using Accounting Information},
  journal = {Accounting Review},
  year = {2017},
  volume = {92},
  pages = {151-182},
  number = {2},
  month = {March},
}

@ARTICLE{nelson:jeb2003,
  author = {Nelson, Edward and Kalin Nikolov},
  title = {UK Inflation in the 1970s and 1980s: The Role of Output Gap Mismeasurement},
  journal = {Journal of Economics and Business},
  year = {2003},
  volume = {55},
  pages = {353-370},
  month = {July/August},
  database = {built own set using Economic Trends},
  url = {http://www.bankofengland.co.uk/publications/workingpapers/wp148.pdf}
}

@ARTICLE{neumark:jbes1991,
  author = {Neumark, David and William L. Wascher},
  title = {Can We Improve Upon Preliminary Estimates of Payroll Employment Growth?},
  journal = {Journal of Business and Economic Statistics},
  year = {1991},
  volume = {9},
  pages = {197-205},
  month = {April},
}

@UNPUBLISHED{nikolskorzhevskyy:forward2007,
  author = {Nikolsko-Rzhevskyy, Alex},
  title = {Monetary Policy Evaluation in Real Time: Forward-Looking Rules without Forward-Looking Data},
  note = {Working paper, University of Houston},
  month = {November},
  year = {2007},
  database = {RTDSM and Greenbook forecasts},
  url = {http://mpra.ub.uni-muenchen.de/11352/}
}

@ARTICLE{oh:eej2005,
  author = {Oh, Seonghwan and Michael Waldman},
  title = {The Index of Leading Indicators as a Source of Expectational Shocks},
  journal = {Eastern Economic Journal},
  year = {2005},
  volume = {31},
  pages = {75-95},
  month = {Winter}
}

@ARTICLE{oh:qje1990,
  author = {Oh, Seonghwan and Michael Waldman},
  title = {The Macroeconomic Effects of False Announcements},
  journal = {Quarterly Journal of Economics},
  year = {1990},
  volume = {105},
  pages = {1017-1034},
  database = {built own data set}
}

@ARTICLE{oller:ijf2007,
  author = {Oller, Lars-Erik and Alex Teterukovsky},
  title = {Quantifying the Quality of Macroeconomic Variables},
  journal = {International Journal of Forecasting},
  year = {2007},
  volume = {23},
  pages = {205-217}
}

@ARTICLE{orphanides:jmcb2004,
  author = {Orphanides, Athanasios},
  title = {Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches},
  journal = {Journal of Money, Credit, and Banking},
  year = {2004},
  volume = {36},
  pages = {151-75},
  number = {2},
  month = {April},
  database = {built own data set},
  url = {www.federalreserve.gov/pubs/feds/2001/200162/200162pap.pdf}
}

@ARTICLE{orphanides:jme2003,
  author = {Orphanides, Athanasios},
  title = {Monetary Policy Evaluation with Noisy Information},
  journal = {Journal of Monetary Economics},
  year = {2003a},
  volume = {50},
  pages = {605-631},
  month = {April},
  database = {built own data set},
  url = {www.federalreserve.gov/Pubs/feds/1998/199850/199850pap.pdf}
}

@ARTICLE{orphanides:jme2003b,
  author = {Orphanides, Athanasios},
  title = {The Quest for Prosperity without Inflation},
  journal = {Journal of Monetary Economics},
  year = {2003b},
  volume = {50},
  pages = {633-663},
  month = {April},
  database = {built own data set},
  url = {www.stanford.edu/~johntayl/Papers/Orphanides.pdf}
}

@ARTICLE{orphanides:jme2003c,
  author = {Orphanides, Athanasios},
  title = {Historical Monetary Policy Analysis and the Taylor Rule},
  journal = {Journal of Monetary Economics},
  year = {2003c},
  volume = {50},
  pages = {983-1022},
  month = {July},
  database = {built own data set},
  url = {www.federalreserve.gov/Pubs/feds/2003/200336/200336pap.pdf}
}

@ARTICLE{orphanides:aerpp2002,
  author = {Orphanides, Athanasios},
  title = {Monetary-Policy Rules and the Great Inflation},
  journal = {American Economic Review Papers \& Proceedings},
  year = {2002},
  volume = {92},
  pages = {115-120},
  month = {May},
  url = {Electronic Copy available through JSTOR}
}

@ARTICLE{orphanides:aer2001,
  author = {Orphanides, Athanasios},
  title = {Monetary Policy Rules Based on Real-Time Data},
  journal = {American Economic Review},
  year = {2001},
  volume = {91},
  pages = {964-985},
  month = {September},
  database = {built own data set and used Greenbook forecasts},
  url = {www.federalreserve.gov/pubs/feds/1998/199803/199803pap.pdf}
}

@ARTICLE{orphanides:jmcb2005,
  author = {Orphanides, Athanasios and Simon van Norden},
  title = {The Reliability of Inflation Forecasts Based on Output Gaps in Real Time},
  journal = {Journal of Money, Credit, and Banking},
  year = {2005},
  volume = {37},
  pages = {583-601},
  database = {RTDSM},
  url = {www.federalreserve.gov/Pubs/feds/2004/200468/200468pap.pdf}
}

@ARTICLE{orphanides:restat2002,
  author = {Orphanides, Athanasios and Simon van Norden},
  title = {The Unreliability of Output Gap Estimates in Real Time},
  journal = {Review of Economics and Statistics},
  year = {2002},
  volume = {84},
  pages = {569-583},
  month = {November},
  database = {RTDSM},
  url = {neumann.hec.ca/pages/simon.van-norden/wps/CIRANO2001s-57.pdf}
}

@UNPUBLISHED{orphanides:jeb2000,
  author = {Orphanides, Athanasios and Richard D. Porter and David Reifschneider and Robert Tetlow and Federico Finan},
  title = {Errors in the Measurement of the Output Gap and the Design of Monetary Policy},
  journal = {Journal of Economics and Business},
  year = {2000}, 
  volume = {52},
  number = {1-2}, 
  pages = {117-141}, 
  note = {Federal Reserve Board, FEDS Working Paper No. 1999-45},
  database = {built own data set},
  url = {http://www.federalreserve.gov/pubs/feds/1999/199945/199945pap.pdf}
}

@ARTICLE{orphanides:jedc2005,
  author = {Orphanides, Athanasios and John C. Williams},
  title = {The Decline of Activist Stabilization Policy: Natural Rate Misperceptions, Learning, and Expectations},
  journal = {Journal of Economic Dynamics and Control},
  year = {2005},
  volume = {29},
  pages = {1927-50},
  month = {November},
  database = {RTDSM},
  url = {www.frbsf.org/publications/economics/papers/2003/wp03-24bk.pdf}
}

@ARTICLE{orphanides:bpea2002,
  author = {Orphanides, Athanasios and John C. Williams},
  title = {Robust Monetary Policy Rules with Unknown Natural Rates},
  journal = {Brookings Papers on Economic Activity},
  year = {2002},
  pages = {63-118},
  database = {RTDSM},
  url = {www.frbsf.org/publications/economics/papers/2003/wp03-01bk.pdf}
}

@UNPUBLISHED{palis:frbog2004,
  author = {Palis, Rebeca de la Rocque and Roberto Luis Olinto Ramos and Patrice Robitaille},
  title = {News or Noise? An Analysis of Brazilian GDP Announcements},
  note = {Federal Reserve Board of Governors, International Finance Discussion Papers},
  year = {2004},
  number = {776},
  month = {April},
}

@UNPUBLISHED{paloviita:dsge2007,
  author = {Paloviita, Maritta},
  title = {Comparison of Estimated Dynamics in a Small DSGE Model Under Rational Expectations and Under Real-Time Expectations},
  note = {Working paper, Bank of Finland},
  year = {2007},
  database = {built own set using OECD data},
}

@Unpublished{paloviita:fiscal2011,
  author    = {Maritta Paloviita and Helvi Kinnunen},
  title     = {Real Time Analysis of Euro Area Fiscal Policies: Adjustment to the Crisis},
  year      = {2011},
  abstract  = {Using real time data from the OECD and fiscal policy reaction functions, this study explores euro area fiscal policies since the late 1990s. Both discretionary plans for the budget year and policy changes during budget implementation stages are investigated. The main focus is on the fiscal adjustment to the 	recent financial and economic crisis. The results suggest that during the monetary union (EMU) euro area planned fiscal policies have been long-term oriented and 	countercyclical. In the implementation stages new policy decisions have been made as a response to unexpected economics developments. We provide evidence that the crisis had a clear impact on discretionary policies. Due to the increased uncertainty, the crisis emphasized the impact of cyclical developments on fiscal planning. In the implementation stages, huge forecast errors made in budget planning were observed. As a consequence, new decisions were made in order to alleviate negative impacts of the crisis on the euro area economies.},
  comment   = {How fiscal policy in Europe changed during the crisis},
  note = {working paper, Bank of Finland}
}

@ARTICLE{paloviita:najef2005,
  author = {Paloviita, Maritta and David G. Mayes},
  title = {The Use of Real Time Information in Phillips Curve Relationships for the Euro Area},
  journal = {North American Journal of Economics and Finance},
  year = {2005},
  volume = {16},
  pages = {415-34},
  number = {3},
  month = {December},
}

@ARTICLE{patterson:ijf2003,
  author = {Patterson, K.D.},
  title = {Exploiting Information in Vintages of Time-Series Data},
  journal = {International Journal of Forecasting},
  year = {2003},
  volume = {19},
  pages = {177-197},
  database = {built own set from NIPA data},
}

@ARTICLE{patterson:el2000,
  author = {Patterson, K.D.},
  title = {Which Vintage of Data to Use When There Are Multiple Vintages of Data? Cointegration, Weak Exogeneity, and Common Factors},
  journal = {Economics Letters},
  year = {2000},
  volume = {69},
  pages = {115-121},
  database = {built own data set},
}

@ARTICLE{patterson:ej1995,
  author = {Patterson, K.D.},
  title = {An Integrated Model of Data Measurement and Data Generation Processes with an Application to Consumers' Expenditure},
  journal = {Economic Journal},
  year = {1995},
  volume = {105},
  pages = {54-76},
  month = {January},
  database = {CSO data set},
}

@ARTICLE{patterson:ijf1995,
  author = {Patterson, K.D.},
  title = {Forecasting the Final Vintage of Real Personal Disposable Income: A State Space Approach},
  journal = {International Journal of Forecasting},
  year = {1995},
  volume = {11},
  pages = {395-405},
}

@ARTICLE{patterson:obes1992,
  author = {Patterson, K.D.},
  title = {Revisions to the Components of the Trade Balance for the United Kingdom},
  journal = {Oxford Bulletin of Economics and Statistics},
  year = {1992},
  volume = {54},
  pages = {103-120},
}

@ARTICLE{patterson:JAS2011,
  author = {Kerry Patterson and Hossein Hassani and Saeed Heravi and Anatoly Zhigljavsky},
  title = {Multivariate singular spectrum analysis for forecasting revisions to real-time data},
  journal = {Journal of Applied Statistics},
  year = {2011},
  volume = {38},
  pages = {2183-2211},
  number = {10},
  url = {https://ideas.repec.org/a/taf/japsta/v38y2011i10p2183-2211.html}
}

@UNPUBLISHED{patterson:IP2009,
  author = {Patterson, Kerry and Hossein Hassani and Saeed Heravi and Anatoly Zhigljavsky.},
  title = {Forecasting the Final Vintage of the Index of Industrial Production},
  note = {Working Paper, University of Reading},
  year = {2009},
}

@Article{patterson:ej1991,
  author    = {Patterson, K.D. and S.M. Heravi},
  title     = {Data Revisions and the Expenditure Components of GDP},
  journal   = {Economic Journal},
  year      = {1991},
  volume    = {101},
  pages     = {887-901},
  month     = {July},
  comment   = {Looks at components of UK GDP and tests for cointegration between vintages (finds it) and runs Mork-type orthogonality tests (rejects orthogonality). All in sample; no o.o.s. testing.},
  database  = {CSO data set},
}

@ARTICLE{patterson:el1991,
  author = {Patterson, K.D. and S.M. Heravi},
  title = {Are Different Vintages of Data on the Components of GDP Co-Integrated?},
  journal = {Economics Letters},
  year = {1991},
  volume = {35},
  pages = {409-413},
}

@ARTICLE{patterson:statn1991,
  author = {Patterson, K.D. and S.M. Heravi},
  title = {Direct Estimation of Entropy and Revisions to the National Income Accounts},
  journal = {Statistician},
  year = {1991},
  volume = {40},
  pages = {35-50},
  number = {1},
}

@ARTICLE{patterson:jf2002,
  author = {Patterson, K. D.},
  title = {The Data Measurement Process for UK GNP: Stochastic Trends, Long Memory, and Unit Roots},
  journal = {Journal of Forecasting},
  year = {2002},
  volume = {21},
  pages = {245-264},
  url = {http://www3.interscience.wiley.com/cgi-bin/fulltext/93519994/PDFSTART}
}

@ARTICLE{patterson:jrss2002,
  author = {Patterson, K. D.},
  title = {Modelling the Data Measurement Process for the Index of Production},
  journal = {Journal of the Royal Statistical Society},
  year = {2002},
  volume = {165},
  pages = {279-296},
  number = {Series A},
  url = {http://www.blackwell-synergy.com/doi/pdf/10.1111/1467-985X.00622}
}

@Article{patterson:jf1995,
  author    = {Patterson, K. D.},
  title     = {A State Space Approach to Forecasting the Final Vintage of Revised Data with an Application to the Index of Industrial Production},
  journal   = {Journal of Forecasting},
  year      = {1995},
  volume    = {14},
  pages     = {337-350},
  comment   = {Uses Kalman filter to forecast final vintage of data, using UK industrial production data. Note: vintages are initial, 1st revision, 2nd revision, etc., but it may not be the same type of revision for all variables. Defines revision as early minus final value, so a negative mean revision means data are revised up over time. Finds such negative mean revisions for IP data. Runs regressions of later vintage on constant and earlier vintage. Finds bias and inefficiency in revisions. Then shows how to use Kalman filter to forecast final values.},
}

@Article{patterson:el1994,
  author    = {Patterson, K. D.},
  title     = {A State Space Model for Reducing the Uncertainty Associated with Preliminary Vintages of Data with an Application to Aggregate Consumption},
  journal   = {Economics Letters},
  year      = {1994},
  volume    = {46},
  pages     = {215-222},
  comment   = {Related to Patterson JFore 1995, but applied to consumption spending instead of industrial production.},
}

@ARTICLE{patterson:jos2004,
  author = {Patterson, K. D. and S.M. Heravi},
  title = {Revisions to Official Data on U.S. GNP: A Multivariate Assessment of Different Vintages},
  journal = {Journal of Official Statistics},
  year = {2004},
  volume = {20},
  pages = {573-602},
}

@ARTICLE{patterson:ae1991,
  author = {Patterson, K. D. and S.M. Heravi},
  title = {The Information Content and Gain of Revisions to the Components of
	GDP},
  journal = {Applied Economics},
  year = {1991},
  volume = {23},
  pages = {903-912},
}

@ARTICLE{patterson:jos2004b,
  author = {Patterson, K. D. and S.M. Heravi},
  title = {Rebasing, Common Cycles, and Some Practical Implications of Modelling Data Revisions},
  journal = {Journal of Official Statistics},
  year = {2004},
  volume = {20},
  pages = {631-644},
  database = {RTDSM},
}

@ARTICLE{patterson:msess1992,
  author = {Patterson, K.D. and S.M. Heravi},
  title = {Efficient Forecasts or Measurement Errors? Some Evidence for Revisions to the United Kingdom Growth Rates},
  journal = {Manchester School of Economic and Social Studies},
  year = {1992},
  volume = {60},
  pages = {249-263},
}

@ARTICLE{pesaran:et2004,
  author = {Pesaran, Hashem and Allan Timmermann},
  title = {Real Time Econometrics},
  journal = {Econometric Theory},
  year = {2004},
  pages = {212-231},
}

@ARTICLE{pierce:jetrics1981,
  author = {Pierce, David A.},
  title = {Sources of Error in Economic Time Series},
  journal = {Journal of Econometrics},
  year = {1981},
  volume = {17},
  pages = {305-21},
}

@ARTICLE{pierce:jfin1981,
  author = {Pierce, David A. and D. W. Parke and W. P. Cleveland and A. Maravall},
  title = {Uncertainty in the Monetary Aggregates: Sources, Measurement and Policy Effects},
  journal = {The Journal of Finance},
  year = {1981},
  volume = {36},
  pages = {507-515},
  number = {2},
  month = {May},
}

@ARTICLE{pincheira:ma2010,
  author = {Pablo Pincheira},
  title = {A real time evaluation of the Central Bank of Chile GDP Growth Forecasts},
  journal = {Money Affairs},
  year = {2010},
  volume = {23},
  pages = {37-73},
  number = {1},
  month = {January-June},
}

@ARTICLE{pruitt:jmcb2012,
  author = {Seth Pruitt},
  title = {Uncertainty Over Models and Data: The Rise and Fall of American Inflation},
  journal = {Journal of Money, Credit, and Banking},
  year = {2012},
  volume = {44},
  pages = {341-365},
  number = {2-3},
  month = {March-April},
  abstract = {An economic agent who is uncertain of her economic model learns, and this learning is sensitive to the presence of data measurement error. I investigate this idea in an existing framework that describes the Federal Reserve's role in U.S. inflation. This framework successfully fits the observed inflation to optimal policy, but fails to motivate the optimal policy by the perceived Philips curve trade-off between inflation and unemployment. I modify the framework to account for 	data uncertainty calibrated to the actual size of data revisions. The modified framework ameliorates the existing problems by adding sluggishness to the Federal Reserve's learning: the key point is that the data uncertainty is amplified by the nonlinearity induced by learning. Consequently there is an explanation for the rise and fall in inflation: the concurrent rise and fall in the perceived Philips curve trade-off.},
  keywords = {Data uncertainty, data revisions, real time data, optimal control, parameter uncertainty, learning, extended Kalman filter, Markov-chain Monte Carlo},
}

@UNPUBLISHED{pruitt:macro2007,
  author = {Pruitt, Seth},
  title = {When Data Revisions Matter to Macroeconomics},
  note = {UCSan Diego working paper},
  month = {November},
  year = {2007},
  database = {ALFRED},
  url = {http://www.econ.ucsd.edu/\%7Esjpruitt/research/wdrmm/paper.pdf}
}

@ARTICLE{rizki:et1993,
  author = {Rizki, U.M.},
  title = {Testing for Bias in Initial Estimates of the Components of GDP},
  journal = {Economic Trends},
  year = {1993},
  pages = {98-118},
  month = {February},
}

@ARTICLE{rizki:et1993b,
  author = {Rizki, U.M.},
  title = {Testing for Bias in Initial Estimates of Key Economic Indicators},
  journal = {Economic Trends},
  year = {1993},
  volume = {475},
  pages = {157-167},
}

@UNPUBLISHED{robertson:prior1999,
  author = {Robertson, John C. and Ellis W. Tallman},
  title = {Prior Parameter Uncertainty: Some Implications for Forecasting and Policy Analysis with VAR Models},
  note = {Federal Reserve Bank of Atlanta working paper 99-13},
  month = {October},
  year = {1999},
 url = {http://www.frbatlanta.org/filelegacydocs/wp9913.pdf}
}

@Article{robertson:frbaer1998,
  author    = {Robertson, John C. and Ellis W. Tallman},
  title     = {Data Vintages and Measuring Forecast Model Performance},
  journal   = {Federal Reserve Bank of Atlanta Economic Review},
  year      = {1998},
  volume    = {b},
  pages     = {4-20},
  month     = {Fourth Quarter},
  comment   = {Discussion of the importance of real-time data. Application to using the leading indexes to forecast real GDP and industrial production. Contradicts Diebold-Rudebusch; finds the leading indicators have value. Focus is on the real-time aspects.},
  database  = {built own set from NIPA data},
  url       = {http://www.frbatlanta.org/filelegacydocs/robertsontallman.pdf},
}

@UNPUBLISHED{robertson:VAR1998,
  author = {Robertson, John C. and Ellis W. Tallman},
  title = {Real-Time Forecasting with a VAR Model},
  note = {Manuscript, Federal Reserve Bank of Atlanta, November 1998a},
  month = {November},
  year = {1998},
}

@ARTICLE{rodriguezmora:eer2007,
  author = {Rodriguez Mora, Jose V. and Paul Schulstald},
  title = {The Effect of GNP Announcements on Fluctuations of GNP Growth},
  journal = {European Economic Review},
  volume = {51},
  number = {8},
  pages = {1922-1940},
  doi = {10.1016/j.euroecorev.2007.08.003},
  year = {2007},
  month = {November},
  database = {compiled own set (RTDSM mentioned in footnote)},
  comment   = {Regression of actual on lagged actual or first announcement shows announcement matters, not actual. Does not account for news vs. noise.},
}

@ARTICLE{rossi:ijf2010,
  author = {Barbara Rossi and Tatevik Sekhposyan},
  title = {Have Economic Models' Forecasting Performance for US Output Growth and Inflation Changed Over Time, and When?},
  journal = {International Journal of Forecasting},
  year = {2010},
  volume = {26},
  pages = {808-835},
  number = {4},
  month = {October-December},
}

@ARTICLE{rudebusch:ijcb2006,
  author = {Rudebusch, Glenn D.},
  title = {Monetary Policy Inertia: Fact or Fiction?},
  journal = {International Journal of Central Banking},
  year = {2006},
  volume = {2},
  pages = {85-135},
  month = {December},
}

@ARTICLE{rudebusch:ej2002,
  author = {Rudebusch, Glenn D.},
  title = {Assessing Nominal Income Rules for Monetary Policy with Model and Data Uncertainty},
  journal = {Economic Journal},
  year = {2002},
  volume = {112},
  pages = {402-432},
  month = {April},
  url = {http://fmwww.bc.edu/RePEc/es2000/0065.pdf}
}

@ARTICLE{rudebusch:restat2001,
  author = {Rudebusch, Glenn D.},
  title = {Is the Fed Too Timid? Monetary Policy in an Uncertain World},
  journal = {Review of Economics and Statistics},
  year = {2001},
  volume = {83},
  pages = {203-217},
  month = {May},
  database = {data supplied by Orphanides},
  url = {www.frbsf.org/econrsrch/workingp/wp99-05.pdf}
}

@ARTICLE{rudebusch:ier1998,
  author = {Rudebusch, Glenn D},
  title = {Do Measures of Monetary Policy in a VAR Make Sense?},
  journal = {International Economic Review},
  year = {1998},
  volume = {39},
  pages = {907-31},
  number = {a},
}

@ARTICLE{rudebusch:jbes2009,
  author = {Rudebusch, Glenn D. and John C. Williams},
  title = {Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve},
  journal = {Journal of Business \& Economic Statistics},
  volume = {27},
  number = {4},
  pages = {492-503},
  year  = {2009},
  doi = {10.1198/jbes.2009.07213},
  database = {built own data set},
  url = {www.frbsf.org/publications/economics/papers/2007/wp07-16bk.pdf}
}

@ARTICLE{runkle:frbmqr1998,
  author = {Runkle, David E.},
  title = {Revisionist History: How Data Revisions Distort Economic Policy Research},
  journal = {Federal Reserve Bank of Minneapolis Quarterly Review},
  year = {1998},
  pages = {3-12},
  month = {Fall},
  database = {built own data set from NIPA tables},
  url = {http://www.minneapolisfed.org/research/QR/QR2241.pdf}
}

@ARTICLE{sargent:jpe1989,
  author = {Sargent, Thomas},
  title = {Two Models of Measurements and the Investment Accelerator},
  journal = {Journal of Political Economy},
  year = {1989},
  volume = {97},
  pages = {251-287},
  database = {built own data set},
}

@ARTICLE{sarte:jmcb2014,
  author = {Pierre-Daniel Sarte},
  title = {When Is Sticky Information More Information?},
  journal = {Journal of Money, Credit and Banking},
  volume = {46}, 
  number = {7}, 
  pages = {1345-1379}, 
  month = {October},
  year = {2014},
  abstract = {This paper uses sectoral data to study survey-based diffusion indices designed to capture changes in the business cycle in real time. The empirical framework recognizes that when answering survey questions regarding their firm's output, respondents potentially rely on infrequently updated information. The analysis then suggests that their answers reflect considerable information lags, on the order of 16 months on average. Moreover, information stickiness implies that noisy output fluctuations will be attenuated in survey answers and, consequently, helps explain why diffusion indices successfully track business cycles. Conversely, the analysis also shows that in an environment populated by fully informed identical firms, as in the standard RBC framework for example, diffusion indices instead become degenerate. Finally, the data suggest that information regarding changes in aggregate output tends to be sectorally concentrated. The paper, therefore, is able to offer basic guidelines for the design of surveys used to construct diffusion indices.},
  keywords = {Information Stickiness, Diffusion Indices, Approximate Factor Model},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Sarte%20paper.pdf}
}

@UNPUBLISHED{Sarte:sectoral2010,
  author = {Sarte, Pierre-Daniel. manuscript},
  title = {Informational Rigidities: Evidence from Sectoral Data and Diffusion Indexes},
  note = {Federal Reserve Bank of Richmond working paper},
  month = {June},
  year = {2010},
}

@ARTICLE{sauer:ger2007,
  author = {Sauer, Stephan and Jan-Egbert Sturm},
  title = {Using Taylor Rules to Understand European Central Bank Monetary Policy},
  journal = {German Economic Review},
  year = {2007},
  volume = {8},
  pages = {375-398},
  database = {built own from ECB Monthly Bulletins},
}

@ARTICLE{schuh:neer2001,
  author = {Schuh, Scott},
  title = {An Evaluation of Recent Macroeconomic Forecast Errors},
  journal = {New England Economic Review, Federal Reserve Bank of Boston},
  year = {2001},
  pages = {35-56},
}

@ARTICLE{schumacher:ijf2008,
  author = {Schumacher, Christian and Jorg Breitung},
  title = {Real-Time Forecasting of German GDP Based on a Large Factor Model with Monthly and Quarterly Data},
  journal = {International Journal of Forecasting},
  year = {2008},
  volume = {24},
  pages = {386-398},
  number = {3},
  month = {October},
  note = {Deutsche Bundesbank Discussion Paper No. 33/2006},
  abstract = {This paper discusses a factor model for short-term forecasting of GDP growth using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm, combined with a principal components estimator. We discuss some in-sample properties of the estimator in a real-time environment and propose alternative methods for forecasting quarterly GDP with monthly factors. In the empirical application, we use a novel real-time dataset for the German economy. Employing a recursive forecast experiment, we evaluate the forecast accuracy of the factor model with respect to German GDP. Furthermore, we investigate the role of revisions in forecast accuracy and assess the contribution of timely monthly observations to the forecast performance. Finally, we compare the performance of the mixed-frequency model with that of a factor model, based on time-aggregated quarterly data.},
  database = {built own data set from Bundesbank Monthly Bulletin},
  keywords = {Forecasting; GDP; EM algorithm; Principal components; Factor models},
  url = {http://www.bundesbank.de/download/volkswirtschaft/dkp/2006/200633dkp.pdf}
}

@ARTICLE{shapiro:je2021,
  author = {Adam Hale Shapiro and Moritz Sudhof and Daniel J. Wilson},
  title = {Measuring News Sentiment},
  journal = {Journal of Econometrics},
  year = {2021},
  note = {Federal Reserve Bank of San Francisco Working Paper 2017-01; je year 2020 online, probably 2021},
}

@UNPUBLISHED{siklos:gradually2007,
  author = {Siklos, Pierre and Diana Weymark},
  title = {Why Did the Fed Act Gradually? Estimating Changes in Inflation Pressure in Real Time},
  note = {Wilfrid Laurier University working paper},
  month = {December},
  year = {2007},
  database = {RTDSM},
}

@INCOLLECTION{siklos:fegs2006,
  author = {Siklos, Pierre L.},
  title = {What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation? Some U.S. Evidence},
  booktitle = {Forecasting in the Presence of Structural Breaks and Model Uncertainty Frontiers of Economics and Globalization Series,},
  publisher = {Elsevier/Emerald},
  year = {2006},
  editor = {M. Wohar and D. Rapach},
  volume = {3},
  series = {Frontiers of Economics and Globalization Series},
  pages = {271-299},
  address = {Amsterdam},
  month = {October},
  note = {Working paper, Wilfrid Laurier University and Viessman Research Centre},
  database = {RTDSM},
  url = {www.cirano.qc.ca/fin/Real-timeData/2006/Siklos.pdf}
}

@ARTICLE{siklos:cje2010,
  author = {Siklos, Pierre L.},
  title = {Revisiting the Coyne Affair: A Singular Event that Changed the Course of Canadian Monetary History},
  journal = {Canadian Journal of Economics},
  volume = {43}, 
  number = {3},
  month = {August},
  year = {2010}, 
  pages = {994-1015},
  database = {Cayen and vanNorden (2005) and Banking and Monetary Statistics},
  url = {http://www.wlu.ca/viessmann/Pierres_stuff/Coyne.pdf}
}

@ARTICLE{siklos:afe1996,
  author = {Siklos, Pierre L.},
  title = {An Empirical Exploration of Revisions in US National Income Accounts},
  journal = {Applied Financial Economics},
  year = {1996},
  volume = {6},
  pages = {59-70},
}

@UNPUBLISHED{siklos:ECB2005,
  author = {Siklos, Pierre L. and Martin L. Bohl},
  title = {The Role of Asset Prices in Euro Area Monetary Policy: Specification and Estimation of Policy Rules and Implications for the ECB},
  note = {Manuscript},
  month = {July},
  year = {2005},
}

@UNPUBLISHED{siklos:Taylor2004,
  author = {P.L. Siklos and T. Werner and M. T. Bohl},
  title = {Asset Prices in Taylor Rules: Specification, Estimation, and Policy Implications for the ECB},
  note = {Discussion Paper Series 1: Studies of the Economic Research Centre, 22/2004, Deutsche Bundesbank},
  year = {2004},
}

@Article{sinclair:ijf2019,
  author   = {Tara M. Sinclair},
  journal  = {International Journal of Forecasting},
  title    = {Characteristics and implications of Chinese macroeconomic data revisions},
  year     = {2019},
  month    = jul,
  number   = {3},
  pages    = {1108-1117},
  volume   = {35},
  abstract = {The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.},
}

@Article{sinclair:ijf2013,
  author   = {Tara M. Sinclair and H.O. Stekler},
  journal  = {International Journal of Forecasting},
  title    = {Examining the quality of early GDP component estimates},
  year     = {2013},
  month    = oct,
  number   = {4},
  pages    = {736-750},
  volume   = {29},
  abstract = {In this paper we examine the quality of the initial estimates of headline GDP and 10 major components of both real and nominal U.S. GDP. We ask a number of questions about various characteristics of the differences between the initial estimates, available one month after the end of the quarter, and the estimates available three months after the end of the quarter. Do the first estimates have the same directional signs as the later numbers? Are the original numbers unbiased estimates of the later figures? Are any observed biases related to the state of the economy? Finally, we determine whether there is a significant difference between the vector of the 30-day estimates of the 10 major components and the vector of the 90-day estimates of the same components. We conclude that, under most circumstances, despite the existence of some bias, an analyst could use the early data to obtain a realistic picture of what had happened in the economy in the previous quarter.},
}

@UNPUBLISHED{sirchenko:Poland2010,
  author = {Andrei Sirchenko},
  title = {Policymakers' Votes and Predictability of Monetary Policy},
  month = {December},
  year = {2010},
  note = {working paper},
  abstract = {The National Bank of Poland does not publish the Monetary Policy Council's voting records before the subsequent policy meeting. Using real-time data, this paper shows that a prompter release 	of the voting records could improve the predictability of policy decisions. The voting patterns reveal strong and robust predictive content even after controlling for policy bias and responses to 	inflation, real activity, exchange rates and financial market information. They contain information 	not embedded in the spreads and moves in the market interest rates, nor in the explicit forecasts of the next policy decision made by market analysts in Reuters surveys. Moreover, the direction of policymakers' dissent explains the direction of analysts' forecast bias. These findings are based on the voting patterns only, without the knowledge of policymakers' names.},
  url = {http://escholarship.org/uc/item/8qj3z3qg}
}

@UNPUBLISHED{sirchenko:discreteness2008,
  author = {Sirchenko, Andrei},
  title = {Modeling Monetary Policy in Real Time: Does Discreteness Matter?},
  note = {European University Institute, working paper 08/07E},
  month = {July},
  year = {2008},
  abstract = {This paper applies an empirical framework, combining the use of ordered probit approach, novel real-time data set and decision-making meetings of monetary authority as a unit of observation, to estimate highly systematic reaction patterns between policy rate decisions of the National Bank of Poland and incoming economic data for the period 1999 - 2007. The paper measures the empirical significance of rate discreteness and demonstrates that both the discrete-choice approach and real-time `policy-meeting' data do matter in the econometric identification of Polish monetary policy. The study detects structural breaks in policy, which switched its focus from current to expected inflation and from exchange rate to real activity. The response to inflationary expectation is shown to be highly asymmetrical depending on whether the expectation is above or below the inflation target. The policy rate appears to be driven by key economic indicators without evidence for intentional interest-rate smoothing by central bank. The estimated rules explain correctly 95 percent of observed policy actions and surpass the market anticipation, made one day prior to a policy meeting, both in and out of sample.},
  url = {http://eerc.ru:8088/details/EERCWorkingPaper.aspx?id=595}
}

@ARTICLE{sleeman:rbnzb2006,
  author = {Sleeman, Cath},
  title = {Analysis of Revisions to Quarterly GDP - a Real-Time Database},
  journal = {Reserve Bank of New Zealand Bulletin},
  year = {2006},
  volume = {69},
  pages = {31-44},
  month = {March},
}

@ARTICLE{smets:ee2002,
  author = {Smets, Frank},
  title = {Output Gap Uncertainty: Does It Matter for the Taylor Rule?},
  journal = {Empirical Economics},
  year = {2002},
  volume = {27},
  pages = {113-129},
}

@UNPUBLISHED{smets:ecb2013,
  author = {Frank Smets and Anders Warne and Rafael Wouters},
  title = {Professional Forecasters and the Real-Time Forecasting Performance of an Estimated New Keynesian Model for the Euro Area},
  month = {August},
  year = {2013},
  note = {ECB working paper 1571},
  abstract = {This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets, and Wouters (2012) estimated on euro area data. It investigates to what extent forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated over the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model and a random walk.},
  keywords = {Bayesian methods, DSGE model, real-time database, Survey of Professional Forecasters, 	macroeconomic forecasting, estimated New Keynesian model, euro area.},
}

@ARTICLE{staiger:jep1997,
  author = {Staiger, Douglas and James H. Stock and Mark W. Watson},
  title = {The NAIRU, Unemployment, and Monetary Policy},
  journal = {Journal of Economic Perspectives},
  year = {1997},
  volume = {11},
  pages = {33-49},
  month = {Winter},
  database = {built own data set},
}

@ARTICLE{stark:rr2011,
  author = {Tom Stark},
  title = {Real GDP in Annual Revisions to the U.S. National Accounts: 1966-2011},
  journal = {Federal Reserve Bank of Philadelphia Research Rap},
  year = {2011},
  month = {August},
  abstract = {On July 29, 2011, the U.S. Bureau of Economic Analysis (BEA) released a flexible annual revision to the U.S. national income and product accounts. Real GDP growth was subject to large downward revisions. I use the Philadelphia Fed's real-time data set to compare the size of the recent revision with that of past annual revisions since 1966. I find: Large downward revisions are not uncommon in the annual revisions of recent years. In this regard, the 2011 annual revision does not stand out; Revisions are correlated with the state of the economy, as measured by real GDP growth itself and indicators of recession.},
  url = {http://www.philadelphiafed.org/research-and-data/publications/research-rap/2011/real-gdp-in-annual-revisions-1966-2011.pdf}
}

@ARTICLE{stark:rr2011b,
  author = {Tom Stark},
  title = {Revisions to Nonfarm Payroll Employment: 1964-2011},
  journal = {Federal Reserve Bank of Philadelphia Research Rap},
  year = {2011},
  month = {December},
  abstract = {Over recent months, the Bureau of Labor Statistics (BLS) has revised upward its initial estimates of the monthly change in nonfarm payroll employment. Similar positive revisions occurred to the initial estimates for September 2010 through February 2011. Moreover, upward revisions to initial estimates also occurred in the immediate months following the most recent NBER business-cycle trough of June 2009. This pattern of positive revisions suggests that the BLS might be having trouble pinning down initial estimates of job gains in the early stages of an expansion. It also cautions us against placing too much weight on very early, sometimes unreliable estimates of macroeconomic data.},
}

@ARTICLE{stark:rr2014,
  author = {Tom Stark},
  title = {The Real-Time Performance of GDPplus (and Alternative Model-Based Measures of GDP): 2005-2014},
  journal = {Federal Reserve Bank of Philadelphia Research Rap},
  year = {2014},
  month = {October},
}

@ARTICLE{stark:rr2015,
  author = {Tom Stark},
  title = {First Quarters in the National Income and Product Accounts},
  journal = {Research Rap Special Report},
  year = {2015},
  pages = {1-25},
  month = {May},
}

@ARTICLE{stark:jm2002,
  author = {Stark, Tom and Dean Croushore},
  title = {Forecasting with a Real-Time Data Set for Macroeconomists},
  journal = {Journal of Macroeconomics},
  year = {2002},
  volume = {24},
  pages = {507-31 and reply to comments, pp. 563-567},
  month = {December},
  database = {RTDSM},
  url = {http://www.phil.frb.org/files/wps/2001/wp01-10.pdf}
}

@ARTICLE{stekler:restat1961,
  author = {Stekler, H.O.},
  title = {Diffusion Index and First Difference Forecasting},
  journal = {Review of Economics and Statistics},
  year = {1961},
  volume = {43},
  pages = {201-208},
  month = {May},
  database = {built own data set},
}

@ARTICLE{stekler:jasa1967,
  author = {H.O. Stekler},
  title = {Data Revisions and Economic Forecasting},
  journal = {Journal of the American Statistical Association},
  year = {1967},
  volume = {62},
  pages = {470-483},
  number = {318},
  month = {June},
  url = {http://www.jstor.org/stable/pdfplus/2283975.pdf?acceptTC=true}
}

@INPROCEEDINGS{stekler:pbessasa1968,
  author = {H.O. Stekler},
  title = {Econometric Forecast Errors: Data Revisions and Judgmental Elements},
  booktitle = {Proceeding of the Business and Economic Statistics Section of the American Statistical Association},
  year = {1968},
}

@ARTICLE{stekler:ae1987,
  author = {H.O. Stekler},
  title = {The Effect of Data Revisions and Additional Observations on Time Series Estimates},
  journal = {Applied Economics},
  year = {1987},
  volume = {19},
  pages = {347-353},
  number = {3},
  month = {March},
}

@ARTICLE{stekler:jasa2009,
  author = {Stekler, H.O. and Susan W. Burch},
  title = {Selected Economic Data, Accuracy vs. Reporting Speed},
  journal = {Journal of the American Statistical Association},
  year = {2009},
  volume = {63},
  pages = {436-444},
  number = {322},
  month = {June},
  database = {built their own set}
}

@ARTICLE{stekler:el1979,
  author = {L. E. Stekler and H. O. Stekler},
  title = {Data revisions in the U.S. international transactions statistics},
  journal = {Economics Letters},
  year = {1979},
  volume = {4},
  pages = {45-49},
  number = {1},
}

@ARTICLE{stock:jbes2002,
  author = {Stock, James H. and Mark W. Watson},
  title = {Macroeconomic Forecasting Using Diffusion Indexes},
  journal = {Journal of Business and Economic Statistics},
  year = {2002},
  volume = {20},
  pages = {147-162},
}

@ARTICLE{stock:jme1999,
  author = {Stock, James H. and Mark W. Watson},
  title = {Forecasting Inflation},
  journal = {Journal of Monetary Economics},
  year = {1999},
  volume = {44},
  pages = {293-335},
  number = {2},
}

@Article{strohsal:ijf2020,
  author   = {Till Strohsal and Elias Wolf},
  journal  = {International Journal of Forecasting},
  title    = {Data Revisions to German National Accounts: Are Initial Releases Good Nowcasts?},
  year     = {2020},
  pages    = {1252-1259},
  volume   = {36},
  abstract = {Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small, and unpredictable. This article shows that revisions to German national accounts are biased, large, and predictable. Moreover, with use of filtering techniques designed to process data subject to revisions, the realtime forecasting performance of initial releases can be increased by up to 23\%. For total real GDP growth, however, the initial release is an optimal forecast. Yet, given the results for disaggregated variables, the averaging out of biases and inefficiencies at the aggregate GDP level appears to be good luck rather than good forecasting.},
}

@ARTICLE{sucharita:obes1997,
  author = {Ghosh Sucharita},
  title = {United States Trade Balance Announcements: The Nature of its Data Revisions},
  journal = {Oxford Bulletin of Economics and Statistics},
  year = {1997},
  volume = {59},
  number = {3},
}

@Unpublished{sulewski:oil2021,
  author   = {Christoph Sulewski and Alexander Putz and Pierre L. Siklos},
  title    = {Forecasting oil prices in a data-rich environment},
  note = {working paper},
  month    = mar,
  year     = {2021},
  abstract = {Forecasting the price of oil is of great interest to central banks and other economic agents. This study attempts to address this challenging endeavor by integrating recent advances in the use of machine learning methods with available large macroeconomic data-sets. The predictive abilities of classical as well as more recent machine learning methods compared to a set of benchmarks is examined. We show that the models under scrutiny are able to outperform the no-change benchmark in a data-rich environment, but cannot beat the AR(1).},
}

@ARTICLE{swanson:md2004,
  author = {Swanson, Eric},
  title = {Signal Extraction and Non-Certainty-Equivalence in Optimal Monetary Policy Rules},
  journal = {Macroeconomic Dynamics},
  year = {2004},
  volume = {8},
  pages = {27-50},
}

@ARTICLE{swanson:snde1996,
  author = {Swanson, Norman R.},
  title = {Forecasting Using First Available Versus Fully Revised Economic Time Series Data},
  journal = {Studies in Nonlinear Dynamics and Econometrics},
  year = {1996},
  volume = {1},
  pages = {47-64},
  month = {April},
}

@ARTICLE{swanson:jbes2006,
  author = {Swanson, Norman R. and Dick van Dijk},
  title = {Are Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry},
  journal = {Journal of Business \& Economic Statistics},
  year = {2006},
  volume = {24},
  pages = {24-42},
  month = {January},
  database = {compiles own set from SCB data; cites ALFRED},
  url = {econweb.rutgers.edu/nswanson/papers/realt20.pdf}
}

@INCOLLECTION{swanson:coint1999,
  author = {Swanson, Norman R. and Eric Ghysels and Myles Callan},
  title = {A Multivariate Time Series Analysis of the Data Revision Process for Industrial Production and the Composite Leading Indicator},
  booktitle = {Cointegration, Causality, and Forecasting: Festschrift in Honor of C.W.J. Granger},
  publisher = {Oxford University Press},
  year = {1999},
  editor = {Robert F. Engle and Halbert White},
}

@ARTICLE{swanson:restat1997,
  author = {Swanson, Norman R. and Halbert White},
  title = {A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks},
  journal = {Review of Economics and Statistics},
  year = {1997},
  pages = {540-550},
  month = {November},
  database = {compiled own set from SCB},
  url = {http://129.3.20.41/eps/mac/papers/9503/9503004.pdf}
}

@UNPUBLISHED{tallman:payroll2004,
  author = {Tallman, Ellis W. and Peter A. Zadrozny},
  title = {Information in Data Revision Processes: Payroll Employment and Real-Time Measurement of Employment Conditions},
  note = {manuscript},
  month = {October},
  year = {2004},
}

@UNPUBLISHED{tchaidze:taylor2001,
  author = {Tchaidze, Robert},
  title = {Estimating Taylor Rules in a Real-Time Setting},
  note = {Working paper, Johns Hopkins University},
  month = {August},
  year = {2001},
  database = {RTDSM},
  url = {http://www.econ.jhu.edu/pdf/papers/wp457.pdf}
}

@ARTICLE{tetlow:jmcb2007,
  author = {Tetlow, Robert J. and Brian Ironside},
  title = {Real-time Model Uncertainty in the United States: the Fed, 1996-2003},
  journal = {Journal of Money, Credit, and Banking},
  year = {2007},
  volume = {39},
  pages = {1533-1561},
  month = {October},
  database = {built own data set from NIPA tables},
}

@UNPUBLISHED{tosetta:oecd2008,
  author = {Tosetta, Elena},
  title = {Revisions of Quarterly Output Gap Estimates for 15 OECD Member Countries},
  note = {OECD Working Paper},
  month = {September},
  year = {2008},
}

@UNPUBLISHED{trimbur:gap2010,
  author = {Thomas M. Trimbur},
  title = {The Cyclical Dynamics of Output and a Method for Improving Output Gap Estimates in Real Time},
  note = {working paper},
  month = {April},
  year = {2010},
  abstract = {The output gap summarizes the current state of the economy by indicating position relative to trend activity; it represents a key concept for policymaking. This paper addresses the problem set out in Orphanides and van Norden (Review of Economics and Statistics, 2002), which shows the pervasive 	inaccuracy of output gap estimates in real-time. To achieve a solution, this paper introduces the analysis of higher order cycles in real-time and links the cyclical properties of output with capacity utilization, an indicator that contains complementary information about the relationship of production to potential. The higher order cycles lead to a better fit and to a closer match between real-time 	and final estimates. The bivariate higher order models lead to further advances in model performance and in real-time accuracy and revisions properties.},
  keywords = {Business cycles, Kalman filter, Potential output, state space, stochastic cycles, unobserved components},
}

@UNPUBLISHED{trimbur:gap2010b,
  author = {Trimbur, Thomas M.},
  title = {Improving Real-Time Estimates of the Output Gap and a Method for Improving Output Gap Estimates in Real Time},
  note = {Working paper, Federal Reserve Board},
  month = {April},
  year = {2010},
  database = {RTDSM},
}

@ARTICLE{triplett:scb1992,
  author = {Jack E. Triplett},
  title = {Economic Theory and BEA's Alternative Quantity and Price Indexes},
  journal = {Survey of Current Business},
  year = {1992},
  volume = {72},
  pages = {49-52},
  number = {4},
  month = {April},
}

@ARTICLE{trivellato:jbes1986,
  author = {Trivellato, Ugo and Enrice Rettore},
  title = {Preliminary Data Errors and Their Impact on the Forecast Error of Simultaneous-Equations Models},
  journal = {Journal of Business and Economic Statistics},
  year = {1986},
  volume = {4},
  pages = {445-53},
  month = {October},
}

@UNPUBLISHED{vandijk:forecasts2007,
  author = {Van Dijk, Dick and Philip Hans Franses and Francesco Ravazzolo},
  title = {Evaluating Real-Time Forecasts in Real Time},
  note = {Econometric Institute Report EI2007-33},
  month = {August},
  year = {2007},
  database = {RTDSM},
  url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1012571}
}

@UNPUBLISHED{vannorden:new2005,
  author = {van Norden, Simon},
  title = {Are We There Yet? Looking for Evidence of a New Economy},
  note = {Manuscript, HEC Montreal},
  month = {October},
  year = {2005},
  database = {Robert Rasche at the St. Louis Fed},
  url = {neumann.hec.ca/pages/simon.vannorden/wps/cirano\%20workshop\%20draft.pdf}
}

@ARTICLE{vazquez:iref2012,
  author = {Jesús Vázquez and Ramón María-Dolores and Juan M. Londoño},
  title = {The Effect of Data Revisions on the Basic New Keynesian Model},
  journal = {International Review of Economics \& Finance},
  year = {2012},
  volume = {24},
  pages = {235-249},
  month = {October},
}

@UNPUBLISHED{vonkalckreuth:fiscal2007,
  author = {von Kalckreuth, Ulf and Guntram B. Wolff},
  title = {Testing for Contemporary Fiscal Policy Discretion with Real Time Data},
  note = {Deutsche Bundesbank working paper No. 24/2007},
  year = {2007},
  database = {RTDSM},
}

@Article{walsh:frbsfer1985,
  author    = {Walsh, Carl E.},
  title     = {Revisions in the `Flash' Estimates of GNP Growth: Measurement Error or Forecast Error?},
  journal   = {Federal Reserve Bank of San Francisco Economic Review},
  year      = {1985},
  pages     = {5-13},
  month     = {Fall},
  comment   = {Shows that real GNP flash estimates represent `news' not `noise.'},
  database  = {own tables built from BEA data},
  url       = {http://www.frbsf.org/publications/economics/review/1985/85-4_5-13.pdf},
}

@Article{watson:frbreq2007,
  author    = {Watson, Mark W.},
  title     = {How Accurate Are Real-Time Estimates of Output Trends and Gaps?},
  journal   = {Federal Reserve Bank of Richmond Economic Quarterly},
  year      = {2007},
  volume    = {93},
  pages     = {143-161},
  month     = {Spring},
  comment   = {Looks at problems of estimating trends at beginning and end of sample. Examines methods but not using real-time data.},
  url       = {http://www.richmondfed.org/publications/research/economic_quarterly/2007/spring/watson.cfm#1},
}

@ARTICLE{wei:jae2013,
  author = {Min Wei and Jonathan Wright},
  title = {Reverse Regressions and Long-Horizon Forecasting},
  note = {Min Wei and Jonathan H. Wright},
  journal = {Journal of Applied Econometrics},
  volume = {28}, 
  number = {3}, 
  page = {353-371},
  month = {April-May},
  year = {2013},
  abstract = {Long-horizon predictive regressions in finance pose formidable econometric problems when estimated using available sample sizes. Hodrick (1992) proposed a remedy that is based on running a reverse regression of short-horizon returns on the long-run mean of the predictor. Unfortunately, this only allows the null of no predictability to be tested, and assumes stationary regressors. In this paper, we revisit long-horizon forecasting from reverse regressions, and argue that reverse regression methods avoid serious size distortions in long-horizon 	predictive regressions, even when there is some predictability and/or near unit roots. Meanwhile, the reverse regression methodology has the practical advantage of being easily applicable when there are many predictors. We apply these methods to forecasting excess bond returns using the term structure of forward rates, and find that there is indeed some return forecastability. But confidence intervals for the coefficients of the predictive regressions are about twice as wide as are obtained with the conventional approach to inference},
  keywords = {Predictive Regressions; Long Horizons, Confidence Intervals; Small Sample Problems; Persistence},
  url = {http://www.philadelphiafed.org/research-and-data/events/2010/data-revision/papers/Wei-\%20Wright\%20paper.pdf}
}

@UNPUBLISHED{wright:democratic2009,
  author = {Wright, Jonathan H.},
  title = {Evaluating Real-Time Forecasts with an Informative Democratic Prior},
  note = {Working paper, Johns Hopkins University},
  month = {October},
  year = {2009},
}

@ARTICLE{wroe:et1993,
  author = {Wroe, David},
  title = {Handling Revisions in the National Accounts},
  journal = {Economic Trends},
  year = {1993},
  volume = {480},
  pages = {121-123},
  month = {October},
}

@UNPUBLISHED{yetman:potential2005,
  author = {Yetman, James},
  title = {Discretionary Policy, Potential Output Uncertainty, and Optimal Learning},
  note = {Manuscript, University of Hong Kong},
  month = {September},
  year = {2005},
  url = {www.rbnz.govt.nz/research/discusspapers/dp05_07.pdf}
}

@ARTICLE{xu:jmcb2023,
  author = {Jiawen Xu and John Rogers},
  title = {How Well Does Uncertainty Forecast Economic Activity?},
  journal = {Journal of Money, Credit and Banking},
  year = {2023},
  pages = {NA},
  month = {NA},
  doi = {10.1111/jmcb.13123},
}

@ARTICLE{young:be1994,
  author = {Young, Allen H.},
  title = {The Statistics Corner: Reliability and Accuracy of Quarterly GDP},
  journal = {Business Economics},
  year = {1994},
  pages = {63-67},
  month = {October},
}

@ARTICLE{young:scb1993,
  author = {Young, Allen H.},
  title = {Reliability and Accuracy of the Quarterly Estimates of GDP},
  journal = {Survey of Current Business},
  year = {1993},
  pages = {29-43},
  month = {October},
  database = {built own data set using Survey of Current Business},
  url = {http://www.bea.gov/scb/pdf/NATIONAL/NIPA/1993/1093od.pdf}
}

@ARTICLE{young:scb1992,
  author = {Allan H. Young},
  title = {Alternative Measures of Change in Real Output and Prices},
  journal = {Su},
  year = {1992},
  volume = {72},
  pages = {32-48},
  number = {4},
  month = {April},
}

@ARTICLE{young:scb1989,
  author = {Allan H. Young},
  title = {Alternative Measures of Real GNP},
  journal = {Survey of Current Business},
  year = {1989},
  volume = {69},
  pages = {27-34},
  number = {4},
  month = {April},
}

@UNPUBLISHED{zaman:stars2021,
  author = {Saeed Zaman},
  title = {A Unified Framework to Estimate Macroeconomic Stars},
  note = {Federal Reserve Bank of Cleveland Working Paper},
  year = {2021},
}

@ARTICLE{zarnowitz:jb1982,
  author = {Zarnowitz, Victor},
  title = {On Functions, Quality, and Timeliness of Economic Information},
  journal = {Journal of Business},
  year = {1982},
  volume = {55},
  pages = {87-119},
  month = {January},
  url = {http://www.nber.org/papers/w0608.pdf}
}

@Article{zellner:jasa1958,
  author    = {Zellner, Arnold},
  title     = {A Statistical Analysis of Provisional Estimates of Gross National Product and Its Components, of Selected National Income Components, and of Personal Saving},
  journal   = {Journal of the American Statistical Association},
  year      = {1958},
  volume    = {53},
  pages     = {54-65},
  month     = {March},
  comment   = {The first paper (that I know of) to analyze data revisions. Oops, until I found Gartaganis-Goldberger (1955).},
 }

@UNPUBLISHED{zheng:monthly2006,
  author = {Zheng, Isabel Yi and James Rossiter},
  title = {Using Monthly Indicators to Predict Quarterly GDP},
  note = {Working Papers 06-26, Bank of Canada},
  year = {2006},
}