Creator: Rich, Robert W., 1958- and Tracy, Joseph S., 1956- Series: Joint committee on business and financial analysis Abstract:
This paper examines data on point and probabilistic forecasts of inflation from the Survey of Professional Forecasters. We use this data to evaluate current strategies for the empirical modeling of forecast behavior. In particular, the analysis principally focuses on the relationship between ex post forecast errors and ex ante measures of uncertainty in order to assess the reliability of using proxies based on predictive accuracy to describe changes in predictive confidence. After we adjust the data to account for certain features in the conduct and construct of the survey, we find a significant and robust correlation between observed heteroskedasticity in the consensus forecast errors and forecast uncertainty. We also document that significant compositional effects are present in the data that are economically important in the case of forecast uncertainty, and may be related to differences in respondents' access to information.
关键词: Forecasting, Inflation, Uncertainty, Disagreement, and Conditional heteroskedasticity 学科: C12 - Econometric and statistical methods : General - Hypothesis testing, C22 - Single equation models ; Single variables - Time-series models ; Dynamic quantile regressions, and E37 - Prices, business fluctuations, and cycles - Forecasting and simulation
Creator: Dahl, David S. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 001 描述:
A speech delivered to the Marketing Research Seminar for Gas Utilities, sponsored by the American Gas Association, October 2, 1969.
关键词: Regional surveys, Forecasting, and Data collection 学科: E66 - General Outlook and Conditions
Creator: Todd, Richard M. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) 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.
关键词: Forecast revisions, Innovation, Forecasting, and Data revisions 学科: E17 - General Aggregative Models: Forecasting and Simulation: Models and Applications
Creator: Anderson, Paul A. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 061 Abstract:
This paper puts forward a method for simulating an existing macroeconometric model while maintaining the additional assumption that individuals form their expectations rationally. This simulation technique is a first response to Lucas' criticism that standard econometric policy evaluation allows policy rules to change but doesn't allow expectations rules to change as economic theory predicts they will. The technique is applied to a version of the St. Louis Federal Reserve Model with interesting results. The rational expectations version of the St. Louis Model exhibits the same neutrality with respect to certain policy rules as small, analytic rational expectations models considered by Lucas, Sargent, and Wallace.
关键词: Rational expectations theory, Forecasting, and Simulation 学科: C53 - Forecasting Models; Simulation Methods
Creator: Doan, Thomas, Litterman, Robert B., and Sims, Christopher A. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 243 Abstract:
This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Although cross-variables responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates. We provide unconditional forecasts as of 1982:12 and 1963:3* We also describe how a model such as this can be used to make conditional projections and to analyse policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982:12. While no automatic causal interpretations arise from models like ours, they provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables, which may help in evaluating causal hypotheses, without containing any such hypotheses themselves.
关键词: Forecasting, Macroeconomics, and Bayesian methods 学科: E27 - Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications and C11 - Bayesian Analysis: General
Creator: Doan, Thomas, Litterman, Robert B., and Sims, Christopher A. Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 093 Abstract:
This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. We apply the procedure to 10 macroeconomic variables and show that it produces more accurate out-of-sample forecasts than univariate equations do. Although cross-variable responses are damped by the prior, our estimates capture considerable interaction among the variables.
We provide unconditional forecasts as of 1982:12 and 1983:3. We also describe how a model such as this can be used to make conditional projections and analyze policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982:12.
While no automatic casual interpretations arise from models like ours, such models provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables. That information may help evaluate casual hypotheses without containing any such hypotheses.
关键词: Conditional projections, Forecasting, Vector autoregressions, Macroeconomic modeling, and Rayesian analysis
Creator: Beauchemin, Kenneth Ronald Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 493 Abstract:
This paper describes recent modifications to the mixed-frequency model vector autoregression (MF-VAR) constructed by Schorfheide and Song (2012). The changes to the model are restricted solely to the set of variables included in the model; all other aspects of the model remain unchanged. Forecast evaluations are conducted to gauge the accuracy of the revised model to standard benchmarks and the original model.
关键词: Forecasting and Bayesian Vector Autoregression 学科: C32 - Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models, C53 - Forecasting Models; Simulation Methods, and C11 - Bayesian Analysis: General