Haavelmo's Probability Approach and the Cointegrated VAR
AbstractSome key econometric concepts and problems addressed by Trygve Haavelmo and Ragnar Frisch are discussed within the general framework of a cointegrated VAR. The focus is on problems typical of time series data such as multicollinearity, spurious correlation and regression results, time dependent residuals, normalization, reduced rank, model selection, missing variables, simultaneity, autonomy and identification. Specifically the paper discusses (1) the conditions under which the VAR model represents a full probability formulation of a sample of time-series observations, (2) the plausibility of the multivariate normality assumption underlying the VAR, (3) cointegration as a solution to the problem of spurious correlation and multicollinearity when data contain deterministic and stochastic trends, (4) the existence of a universe, (5) the association between Frisch's confluence analysis and cointegrated VAR analysis, (6) simultaneity and identification when data are nonstationary, (7) conditions under which identified cointegration relations can be considered structural or autonomous, and finally (8) a formulation of a design of experiment for passive observations based on theory consistent CVAR scenarios illustrated with a monetary model for inflation.
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Bibliographic InfoPaper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 12-01.
Length: 8 pages
Date of creation: 01 Mar 2012
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Haavelmo; CVAR; autonomy; identification; passive observations;
Find related papers by JEL classification:
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- B31 - Schools of Economic Thought and Methodology - - History of Economic Thought: Individuals - - - Individuals
- B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-03-28 (All new papers)
- NEP-ECM-2012-03-28 (Econometrics)
- NEP-ETS-2012-03-28 (Econometric Time Series)
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