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Trygve Haavelmo’S Experimental Methodology And Scenario Analysis In A Cointegrated Vector Autoregression

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  • Hoover, Kevin
  • Juselius, Katarina

Abstract

The paper provides a careful, analytical account of Trygve Haavelmo’s use of the analogy between controlled experiments common in the natural sciences and econometric techniques. The experimental analogy forms the linchpin of the methodology for passive observation that he develops in his famous monograph, The Probability Approach in Econometrics (1944). Contrary to some recent interpretations of Haavelmo’s method, the experimental analogy does not commit Haavelmo to a strong apriorism in which econometrics can only test and reject theoretical hypotheses, rather it supports the acquisition of knowledge through a two-way exchange between theory and empirical evidence. Once the details of the analogy are systematically understood, the experimental analogy can be used to shed light on theory-consistent cointegrated vector autoregression (CVAR) scenario analyses. A CVAR scenario analysis can be interpreted as a clear example of Haavelmo’s ‘experimental’ approach; and, in turn, it can be shown to extend and develop Haavelmo’s methodology and to address issues that Haavelmo regarded as unresolved.

Suggested Citation

  • Hoover, Kevin & Juselius, Katarina, 2015. "Trygve Haavelmo’S Experimental Methodology And Scenario Analysis In A Cointegrated Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 31(2), pages 249-274, April.
  • Handle: RePEc:cup:etheor:v:31:y:2015:i:02:p:249-274_00
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    Cited by:

    1. Sergej Gričar & Štefan Bojnec, 2021. "Technical Analysis of Tourism Price Process in the Eurozone," JRFM, MDPI, vol. 14(11), pages 1-25, October.
    2. Katarina Juselius, 2017. "Using a Theory-Consistent CVAR Scenario to Test an Exchange Rate Model Based on Imperfect Knowledge," Econometrics, MDPI, vol. 5(3), pages 1-20, July.
    3. Katarina Juselius, 2017. "A CVAR scenario for a standard monetary model using theory-consistent expectations," Discussion Papers 17-08, University of Copenhagen. Department of Economics.
    4. Kevin D. Hoover, 2020. "The Discovery of Long-Run Causal Order: A Preliminary Investigation," Econometrics, MDPI, vol. 8(3), pages 1-25, August.
    5. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
    6. Katarina Juselius, 2017. "Recent Developments in Cointegration," Econometrics, MDPI, vol. 6(1), pages 1-5, December.
    7. Paul Plummer & Daisaku Yamamoto, 2019. "Economic resilience of Japanese nuclear host communities: A quasi-experimental modeling approach," Environment and Planning A, , vol. 51(7), pages 1586-1608, October.

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