Abstract
This survey paper discusses the Cointegrated Vector AutoRegressive (CVAR) methodology and how it has evolved over the past 30 years. It describes major steps in the econometric development, discusses problems to be solved when confronting theory with the data, and, as a solution, proposes a so-called theory-consistent CVAR scenario. A number of early CVAR applications are motivated by the urge to find out why the empirical results did not support Milton Friedman’s concept of monetary inflation. The paper also proposes a method for combining partial CVAR analyses into a large-scale macroeconomic model. It argues that an empirically-based approach to macroeconomics preferably should be based on Keynesian disequilibrium economics, where imperfect knowledge expectations replace so called rational expectations and where the financial sector plays a key role for understanding the long persistent movements in the data. Finally, the paper argues that the CVAR is potentially a candidate for Haavelmo’s “design of experiment for passive observations” and provides several illustrations.
Highlights
I was happy to accept the invitation by the guest editors to write this survey paper based on my retirement lecture given at the Economics Department of the University of Copenhagen in 2014
The paper ends with some personal reflections on obstacles and bumps on the long journey and concludes with a discussion of what we should require from empirically relevant macroeconomics
The theory division of variables into endogenous, exogenous and fixed could not a priori be assumed to hold in the empirical model. Expectations, which play such a prominent role in economic models, were problematic for Cointegrated Vector AutoRegressive (CVAR) models formulated in terms of observed variables. Economists usually solve this problem by making assumptions on how economic agents would forecast future outcomes given the chosen theoretical model—the so-called model based rational expectations hypothesis (REH)
Summary
It was the working paper on cointegration and error correction (Granger 1983). His thorough insight in the methodology of economics helped me see that the problems were not necessarily related to the CVAR model All this and much more is discussed in the rest of the paper which is organized around four major themes. The first one is about the development of the econometric foundations of the CVAR and describes (i) major stepping stones that were needed in order to apply cointegration techniques to relevant economic problems, (ii) my first attempts to confront economic theories with data and my puzzlement when results did not support standard economic assumptions, and (iii) the development of a user-friendly software. The paper ends with some personal reflections on obstacles and bumps on the long journey and concludes with a discussion of what we should require from empirically relevant macroeconomics
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