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The Error Term In The History Of Time Series Econometrics

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  • Qin, Duo
  • Gilbert, Christopher L.
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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 the errors further 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. Because theoretical models were at that time mostly static, the structural modeling 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 vector autoregression modeling approach. The so-called London School of Economics dynamic specification approach decomposes the dynamics of the modeled variable into three parts: short-run shocks, disequilibrium shocks, and innovative residuals, with only the first two of these sustaining an economic interpretation.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 17 (2001)
Issue (Month): 02 (April)
Pages: 424-450

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Handle: RePEc:cup:etheor:v:17:y:2001:i:02:p:424-450_17

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Cited by:
  1. Duo Qin, 2006. "Uncover Latent PPP by Dynamic Factor Error Correction Model (DF-ECM) Approach: Evidence from Five OECD Countries," Working Papers 575, Queen Mary, University of London, School of Economics and Finance.
  2. Qin, Duo, 2001. "How much does excess debt contribute to currency crises? the case of Korea," Journal of Asian Economics, Elsevier, vol. 12(1), pages 87-104.
  3. Duo Qin, 2010. "Econometric Studies of Business Cycles in the History of Econometrics," Working Papers 669, Queen Mary, University of London, School of Economics and Finance.
  4. Jan Gottschalk, 2001. "An Introduction into the SVAR Methodology: Identification, Interpretation and Limitations of SVAR models," Kiel Working Papers 1072, Kiel Institute for the World Economy.
  5. Christopher L. Gilbert & Duo Qin, 2007. "Representation in Econometrics: A Historical Perspective," Working Papers 583, Queen Mary, University of London, School of Economics and Finance.
  6. Qin, Duo & Cagas, Marie Anne & Ducanes, Geoffrey & Magtibay-Ramos, Nedelyn & Quising, Pilipinas F., 2007. "Measuring Regional Market Integration in Developing Asia: a Dynamic Factor Error Correction Model (DF-ECM) Approach," Working Papers on Regional Economic Integration 8, Asian Development Bank.
  7. Duo Qin, 2006. "VAR Modelling Approach and Cowles Commission Heritage," Working Papers 557, Queen Mary, University of London, School of Economics and Finance.
  8. Christopher L. Gilbert & Duo Qin, 2005. "The First Fifty Years of Modern Econometrics," Working Papers 544, Queen Mary, University of London, School of Economics and Finance.
  9. Duo Qin & Yanqun Zhang, 2013. "A History of Polyvalent Structural Parameters: the Case of Instrument Variable Estimators," Working Papers 183, Department of Economics, SOAS, University of London, UK.
  10. Duo Qin & Marie Anne Cagas & Geoffrey Ducanes & Nedelyn Magtibay-Ramos & Pilipinas F. Quising, 2006. "Measuring Regional Market Integration by Dynamic Factor Error Correction Model (DF-ECM) Approach - The Case of Developing Asia," Working Papers 565, Queen Mary, University of London, School of Economics and Finance.

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