Soothsaying or Science?: Falsification, Uncertainty and Social Change in Macroeconomic Modelling

Social Studies of Science

Volumn 27, Issue 3, 1997, Pages 395-438

  Evans, Robert ^a  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

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EID: 84992885791     PISSN: 03063127     EISSN: None     Source Type: Journal    
DOI: 10.1177/030631297027003002     Document Type: Article

References (39)

1. See, for example, Sheila Jasanoff, The Fifth Branch: Science Advisers as Policy-Makers (Cambridge, MA: Harvard University Press, 1991).
2. See, for example, Brian Wynne, Rationality and Ritual: The Windscale Inquiry and Nuclear Decisions in Britain (Chalfont St Giles, Bucks.: British Society for the History of Science, 1982).
3. Reproductive and genetic technologies are probably the most obvious examples. For a more general introduction to the field, see Wiebe E. Bijker, Thomas P. Hughes and Trevor J. Pinch (eds), The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology (Cambridge, MA & London: MIT Press, 1987).
4. See Peter Scott, Evelleen Richards and Brian Martin, ‘The Myth of the Neutral Social Science Researcher in Contemporary Scientific Controversies’, Science, Technology, & Human Values, Vol. 15 (1990), 474–494
5. For further discussion of these issues, see Evelleen Richards and Malcolm Ashmore (eds), ‘The Politics of SSK: Neutrality, Commitment and Beyond’, Special Issue of Social Studies of Science, Vol. 26, No. 2 (May 1996), 219–468.
6. References to the Analytic Critique of Science can be found in: H.M. Collins and T.J. Pinch, Unwanted Children: Essays in the Sociology of Fringe Science (unpublished manuscript, University of Bath, 1994)
7. Collins, ‘The “Logic” of Morality and Neutrality in the Sociology of Scientific Knowledge’ (unpublished manuscript, University of Bath, 1993).
8. See, for example, David Bloor, Knowledge and Social Imagery (London: Routledge & Kegan Paul, 1976)
9. H.M. Collins, ‘Stages in the Empirical Programme of Relativism’, in Collins (ed.), ‘Knowledge and Controversy: Studies of Modern Natural Science’, Special Issue of Social Studies of Science, Vol. 11, No. 1 (February 1981), 3–10.
10. H.M. Collins, Artificial Experts: Artificial Intelligence and Social Knowledge (Cambridge, MA & London: MIT Press, 1990).
11. Malcolm Ashmore, Michael Mulkay and Trevor Pinch, Health and Efficiency: A Sociology of Health Economics (Milton Keynes, Bucks.: Open University Press, 1989).
12. There is a sense in which both first and second generation SSK were politically motivated, although there the targets were positivist conceptions of science in general, and their social roots and influence. The change for third and fourth generation type SSK is therefore really just one of focus. See Trevor Pinch, ‘Generations of SSK’, Social Studies of Science, Vol. 23, No. 2 (May 1993), 363–373.
13. See, for example, H.M. Collins, ‘The Seven Sexes: A Study in the Sociology of a Phenomenon, or the Replication of Experiments in Physics’, Sociology, Vol. 9 (1975), 205–224.
14. This section offers an overview of the development of macroeconomic models in the United Kingdom. The treatment is necessarily brief and is intended solely to provide background detail and context for the rest of the paper. This discussion draws heavily on Keating's (1985) book, especially Chapters 1 and 7, and I am greatly indebted to Andrew Britton for alerting me to this source: Giles Keating, The Production and Use of Economic Forecasts (London & New York: Methuen, 1985).
15. Lawrence R. Klein, R. James Ball, Arthur Hazlewood and Peter Vandome, An Econometric Model of the UK (Oxford: Basil Blackwell, 1961).
16. See ‘Macroeconomic Modellers Multiply’, ‘Social Sciences: News from the ESRC, ESRC Newsletter, Issue 27 (April 1995), 2.
17. Details of model specification, and references for further reading, can be found in the regular reviews published by the ESRC Macromodelling Bureau. The first of these is: Kenneth F. Wallis (ed.), Martyn J. Andrews, Paul G. Fisher and John D. Whitley, Models of the UK Economy: A Review by the ESRC Macro-modelling Bureau (Oxford: Oxford University Press, 1984).
18. These labels have been chosen to conform with the major contemporary schools of thought identified in Begg, Fischer and Dornbusch's introductory textbook: David Begg, Stanley Fischer and Rudiger Dornbusch, Economics: British Edition (Maidenhead, Berks.: McGraw-Hill, 1984).
19. This was of course the central point of Milton Friedman's influential essay on ‘The Methodology of Positive Economies’, in which he writes: ‘The only relevant test of the validity of a hypothesis is the comparison of its predictions with experience’. See M. Friedman, The Methodology of Positive Economies’, Friedman, Essays in Positive Economics (Chicago, IL: The University of Chicago Press, 1953), 3–43, at 8–9.
20. The problem with this position is, of course, that it commits the fallacy of affirming the consequent – that is, drawing the logically unjustified inference that because there is some correspondence between the solution of a numerical model and an observed event, the veracity of the model has been proved. For a recent statement of this criticism, as it applies to mathematical models in general, see Naomi Oreskes, Kristen Shrader-Frechette and Kenneth Belitz, ‘Verification, Validation and Confirmation of Numerical Models in the Earth Sciences’, Science, Vol. 263 (4 February 1994), 641–646.
21. See, for example: Ken Holden, ‘Macro-economic Models’, in David Green-away (ed.), Current Issues in Macroeconomics (London: Macmillan Education), 163–181
22. Theo Barker, ‘Forecasting the Economic Recession in the UK: A Comparison Based on ex ante Forecasts’, Journal of Forecasting, Vol. 4 (1985), 133–151
23. Kenneth F. Wallis (ed.), MJ. Andrews, P.G. Fisher, J. Andrew Longbottom and J.D. Whitley, Models of the UK Economy: A Third Review by the ESRC Macro-modelling Bureau (Oxford: Oxford University Press, 1987)
24. Wallis and Whitley, ‘Sources of Error in Forecasts and Expectations: UK Economic Models, 1984–8’, Journal of Forecasting, Vol. 10 (1991), 231–253.
25. See, for example, H.M. Collins, ‘Concepts and Methods in Participatory Research’, in Colin Bell and Helen Roberts (eds), Social Researching: Politics, Problems, Practice (London: Routledge & Kegan Paul, 1984), 54–69.
26. It is arguable that when the object of study is an elite or expert definition of a given problem, then non-standardized interviews are the preferred method, and in no sense a ‘second best’ strategy. See: Lewis A. Dexter, Elite and Specialized Interviewing (Evanston, IL: Northwestern University Press, 1970)
27. George Moyser, ‘Non-Standardized Interviewing in Elite Research’, in Robert Burgess (ed.), Studies in Qualitative Methodology: Conducting Qualitative Research (Greenwich, CT & London: JAI Press, 1988), 109–136.
28. See H.M. Collins, ‘The Meaning of Lies’, in Nigel Gilbert and Peter Abell (eds), Accounts and Action: (papers from the 1st) Surrey Conference on Sociological Theory and Method (Aldershot, Hants.: Gower, 1983), 69–78.
29. Robert E. Lucas, ‘Econometric Policy Evaluation: A Critique’, Karl Brunner and Allan H. Meltzer (eds), The Phillips Curve and Labour Markets, Vol.1
30. of the Proceedings of the Carnegie-Rochester Conferences on Public Policy, published as a supplement to the Journal of Monetary Economics (Amsterdam: North-Holland, 1976), 19–46.
31. The multiplier is defined as ‘the change in equilibrium real GDP divided by the change in autonomous expenditure which caused GDP to change’. In other words, if a government increases its spending by ∗, with the result that GDP increases by 2∗, then the multiplier is 2. The multiplier is greater than one because the initial increase in government expenditure will create jobs which will enable further increases in expenditure by the newly employed workers. This additional increase in expenditure will, in turn, create more new jobs and further increases in expenditure. This cycle of increased expenditure and employment will continue for several iterations before the new equilibrium is reached. Consequently the final increase in GDP is always larger than the initial change in expenditure, and hence the multiplier is greater than one. Finally, note that the change in GDP need not be brought about by an increase in government spending; taxes could be reduced so that the increase comes from increased consumer spending. See Michael Parkin and David King, Economics (Wokingham, Berks.: Addison Wesley, 1992), Chapter 26.
32. See, for example, David S. Turner, ‘The Role of Judgement in Economic Forecasting’, Journal of Forecasting, Vol. 9 (1990), 315–345.
33. The fact that this is the same economist who earlier praised the virtues of the formal procedures, and dismissed judgement as soothsaying, should not trouble us too much. Research in discourse analysis should have led us to expect such variability in accounts. See G. Nigel Gilbert and Michael Mulkay, Opening Pandora's Box: A Sociological Analysis of Scientists' Discourse (Cambridge: Cambridge University Press, 1984).
34. It is interesting to note the idea of science used here. For a sociological analysis of the Michelson-Morley experiments, see H.M. Collins and TJ. Pinch, The Golem: What Everyone Needs to Know About Science (Cambridge: Cambridge University Press, 1993), Chapter 2.
35. The Collins Softback English Dictionary (Glasgow: HarperCollins, 3rd edn, 1992) defines ‘the City’ as ‘the various financial institutions located in the City of London’. The American equivalent would be ‘Wall Street’.
36. See Robert J. Evans, Economic Modelling: A Sociological Perspective (unpublished MSc dissertation, University of Bath, 1993), in which I argued that the distinction between exogenous projections and judgemental adjustments was not a clear one. In the course of this project I discovered that this concern is also shared by some economists.
37. For more on the importance of rhetoric in economics, see Donald N. McCloskey, The Rhetoric of Economics (Brighton, Sussex: Wheatsheaf Books; Madison, WI: University of Wisconsin Press, 1985).
38. The paper Currie is referring to is David Hendry, ‘The Role of Prediction in Evaluating Econometric Models’, Proceedings of the Royal Society of London, Series ‘A’, Mathematical and Physical Sciences, Vol.407 (1986), Part 1832, 25–34.
39. Interestingly, during the 1980s, the National Institute did head each forecast table in the National Institute Review with the disclaimer: ‘the forecast figures are not intended to be any more precise than the general statements in the text’: see, for example, National Institute Review, No. 123 (February 1988), 7, Table 1.