Creator: Todd, Richard M. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Dept.) Number: 355 Abstract:
Forecasts are routinely revised, and these revisions are often the subject of informal analysis and discussion. This paper argues 1) that forecast revisions are analyzed because they help forecasters and forecast users to evaluate forecasts and forecasting procedures, and 2) that these analyses can be sharpened by using the forecasting model to systematically express its forecast revision as the sum of components identified with specific data revisions and forecast errors. An algorithm for this purpose is explained and illustrated.
Keyword: Forecasting, Forecast revisions, Innovation, and Data revisions Subject (JEL): E17 - General aggregative models - Forecasting and simulation
Creator: Croushore, Dean Darrell, 1956- and Evans, Charles, 1958- Series: Joint committee on business and financial analysis Abstract:
Monetary policy research using time series methods has been criticized for using more information than the Federal Reserve had available in setting policy. To quantify the role of this criticism, we propose a method to estimate a VAR with real-time data while accounting for the latent nature of many economic variables, such as output. Our estimated monetary policy shocks are closely correlated with a typically estimated measure. The impulse response functions are broadly similar across the methods. Our evidence suggests that the use of revised data in VAR analyses of monetary policy shocks may not be a serious limitation.
Keyword: Monetary policy, Identification, VARs, Data revisions, Real-time data, and Shocks Subject (JEL): C82 - Data collection and data estimation methodology ; Computer programs - Methodology for collecting, estimating, and organizing macroeconomic data, C32 - Multiple or simultaneous equation models - Time-series models ; Dynamic quantile regressions, and E52 - Monetary policy, central banking, and the supply of money and credit - Monetary policy