Friday, December 12, 2014

"The Error Term in the History of Time Series Econometrics"

While we're on the subject of the history of econometrics ......... blog-reader Mark Leeds kindly drew my attention to this interesting paper published by Duo Qin and Christopher Gilbert in Econometric Theory in 2001.

I don't recall reading this paper before - my loss.

Mark supplied me with a pre-publication version of the paper, which you can download here if you don't have access to Econometric Theory.

Here's the abstract:
"We argue that many methodological confusions in time-series econometrics may be seen as arising out of ambivalence or confusion about the error terms. Relationships between macroeconomic time series are inexact and, inevitably, the early econometricians found that any estimated relationship would only fit with errors. Slutsky interpreted these errors as shocks that constitute the motive force behind business cycles. Frisch tried to dissect further the errors into two parts: stimuli, which are analogous to shocks, and nuisance aberrations. However, he failed to provide a statistical framework to make this distinction operational. Haavelmo, and subsequent researchers at the Cowles Commission, saw errors in equations as providing the statistical foundations for econometric models, and required that they conform to a priori distributional assumptions specified in structural models of the general equilibrium type, later known as simultaneous-equations models (SEM). Since theoretical models were at that time mostly static, the structural modelling strategy relegated the dynamics in time-series data frequently to nuisance, atheoretical complications. Revival of the shock interpretation in theoretical models came about through the rational expectations movement and development of the VAR (Vector AutoRegression) modelling approach. The so-called LSE (London School of Economics) dynamic specification approach decomposes the dynamics of modelled variable into three parts: short-run shocks, disequilibrium shocks and innovative residuals, with only the first two of these sustaining an economic interpretation."

© 2014, David E. Giles

No comments:

Post a Comment