Creator: Wallace, Neil Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 000 Description:
This paper was published with no issue number.
Keyword: Economic models, Forecasts, Policy studies , and Neutrality view Subject (JEL): E17 - General Aggregative Models: Forecasting and Simulation: Models and Applications, R15 - General Regional Economics: Econometric and Input-Output Models; Other Models, and E52 - Monetary Policy
Creator: Sargent, Thomas J. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 022 Abstract:
A statistical definition of the natural unemployment rate hypothesis is advanced and tested. A particular illustrative structural macroeconomic model satisfying the definition is set forth and estimated. The model has "classical" policy implications, implying a number of neutrality propositions asserting the invariance of the conditional means of real variables with respect to the feedback rule for the money supply. The aim is to test how emphatically the data reject a model incorporating rather severe "classical" hypotheses.
Keyword: Rational expectations theory, Montarist model, Natural unemployment rate, Post-1945, and Postwar United States Subject (JEL): E24 - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity and E17 - General Aggregative Models: Forecasting and Simulation: Models and Applications
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.
Keyword: Forecast revisions, Innovation, Forecasting, and Data revisions Subject (JEL): E17 - General Aggregative Models: Forecasting and Simulation: Models and Applications