participants in seminars at the Federal Reserve Bank of Philadelphia and the University of Pennsylvania, as well as those at the Midwest Macroeconomics meetings, for their comments. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Philadelphia or of the Federal Reserve System. A REAL-TIME DATA SET FOR MACROECONOMISTS This paper presents the concept and uses of a real-time data set that can be used by economists for testing the robustness of published econometric results, for analyzing policy, and for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper illustrates why such data may matter, explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, examines key empirical papers in macroeconomics and investigates their robustness to different vintages, looks at how policy analysis may be affected by data revisions, and shows how forecasts can be affected by data revisions. A REAL-TIME DATA SET FOR MACROECONOMISTS I.

Reserve Board, and George Washington University, as well as those at the Midwest

We would like to thank Neil Ericsson for kindly providing the data on M1 used in this paper. We bene tted from discussions with Glenn Rudebusch. While the customary disclaimer applies, we would like to thank Fabio Canova and two anonymous referees for their comments which helped streamline the presentation and better focus on the issues. Financial support from the Italian MURST and CNR is kindly acknowledged by Gallo.

Hayward, Jim Sherma, and Bill Wong for their fine research assistance. We thank Athanasios

We examine the prevalence of data, specification, and parameter uncertainty in the formation of simple rules which mimic monetary policy-making decisions. Our approach is to build realtime datasets and simulate a real-time policy-setting environment in which we are able to assess the actual performance of rules, had they been followed in real time. This approach allows us not only to track the performance of alternative rules over time (hence facillitating a type of model selection among competing rules), but also allows us more generally to assess the importance of the data revision process in the formation of macroeconomic time series models. From the perspective of real time data, our results suggest that the use of data which are erroneous, in the sense that they were not available at the time decisions based on forecasts from the rules were used, can lead to the selection of quantitatively di®erent models. From the perspective of policy rules, we find that: our version of "calibration" is better than naive estimation, although both are dominated by an approach to rule formation based on adaptive least squares learning using; rules based on seasonally unadjusted data are more reliable than those based on seasonally adjusted data; and rules based soly on preliminary data do not minimize mean square forecast error (MSE) risk. In particular, early releases of data can be noisy, and for this reason it is useful to also use data which have been revised when making decisions using policy rules.

We show that using data which are properly available in real time when assessing the sensitivity of asset prices to economic news leads to di®erent empirical ¯ndings than when data availability and timing issues are ignored. We do this by focusing on a particular example, namely Chen, Roll and Ross (1986), and examine whether innovations to economic variables can be viewed as risks that are rewarded in asset markets. Our ¯ndings support the view that data uncertainty is su±ciently prevalent to warrant careful use of real-time data when forming real-time news measures, and in general when undertaking empirical ¯nancial investigations involving macroeconomic data.

Le CIRANO est un organisme sans but lucratif constitué en vertu de la Loi des compagnies du Québec. Le financement de son infrastructure et de ses activités de recherche provient des cotisations de ses organisations-membres, d=une subvention d=infrastructure du ministère de l=Industrie, du Commerce, de la Science et de la Technologie, de même que des subventions et mandats obtenus par ses équipes de recherche. La Série Scientifique est la réalisation d=une des missions que s=est données le CIRANO, soit de développer l=analyse scientifique des organisations et des comportements stratégiques. CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the Ministère de l=Industrie, du Commerce, de la Science et de la Technologie, and grants and research mandates obtained by its research teams. The Scientific Series fulfils one of the

Le CIRANO est un organisme sans but lucratif constitué en vertu de la Loi des compagnies du Québec. Le financement de son infrastructure et de ses activités de recherche provient des cotisations de ses organisationsmembres, d’une subvention d’infrastructure du ministère de la Recherche, de la Science et de la Technologie, de même que des subventions et mandats obtenus par ses équipes de recherche. CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the Ministère de la Recherche, de la Science et de la Technologie, and grants and research mandates obtained by its research teams.

Reserve Board, and George Washington University, as well as those at the Midwest