You are viewing a javascript disabled version of the site. Please enable Javascript for this site to function properly.
Go to headerGo to navigationGo to searchGo to contentsGo to footer
In content section. Select this link to jump to navigation

Towards a political economy of statistics

Abstract

Presently, many countries are discussing the future of official statistical data production. As a contribution to this discussion, we shall examine in this article a number of methodological aspects of a ``political economy of statistics'', focussing on ``statistical operationalization'', which we see as a central challenge for data production in the field of economic and social activities. In a ``political economy of statistics'' it is assumed that the producers and users of statistical data behave self-interested and will try to shape the statistical infrastructure to meet their personal needs, which do not necessarily coincide with the socially optimal form of data provision. As a result, individual rationality and collective rationality may fall apart and create welfare losses for society. In this contribution we therefore ask how the process of statistical data production can be organized to benefit society in total and not only specific interest groups. To that end we shall combine insights from political economy with insights from statistical operationalization.

References

[1] 

Brigdman, The Logic of Modern Physics, New York, 1927.

[2] 

Dillman D.A., Why Innovation is Difficult in Government Surveys, Journal of Official Statistics 12 (1996), 113-124.

[3] 

Eltinge J.L., , Biemer P.P., and Holmberg A., A Potential Framework for Integration of Architecture and Methodology to Improve Statistical Production Systems, Journal of Official Statistics 29 (2013), 113-124.

[4] 

Fellegi I.P., Characteristics of an Effective Statistical System, International Statistical Review 64 (1996), 165-187.

[5] 

Giere R.N., Epistemological Roots of Scientific Knowledge. In Induction, Probability, and Confirmation, Minnesota Studies in the Philosophy of Science, Vol. VI. Ed. G. Maxwell and R.M. Anderson, Jr., Minneapolis: University of Minnesota Press, 1975, pp. 212-261.

[6] 

Heine K., and Mause K., Policy Advice as an Investment Problem, Kyklos 57 (2004), 403-428.

[7] 

Hempel C.G., A Logical Appraisal of Operationism, Scientific Monthly 79 (1954), 215-220.

[8] 

High-Level Group for the Modernisation of Statistical Production and Services (2014), Strategic Vision of the HLG. http://www1.unece.org/stat/platform/display/hlgbas/Strategic +vision+of+the+HLG.

[9] 

Hirshleifer J., The Private and Social Value of Information and the Reward to Incentive Activity, American Economic Review 61 (1971), 561-574.

[10] 

Hirshleifer J., and Riley J.G., The Analytics of Uncertainty, Cambridge, 1992.

[11] 

Kramer A.D.I., , Guillory J.E., and Hancock J.T., Experimental evidence of massive scale emotional contagion through social networks, Proceedings of the National Academy of Sciences 111 (2014), 8788-8790.

[12] 

Mueller D.C., Public Choice III, Cambridge, 2003.

[13] 

OECD (2013). New Data for Understanding the Human Condition, OECD Global Science Forum Report on Data and Research Infrastructure for the Social Sciences, Paris.

[14] 

Pearson E.S., Statistical Concepts in the Relation to Reality, Journal of the Royal Statistical Society, Series B 20 (1955), 204-207.

[15] 

Penneck, St. Discussion on Systems and Architectures for High-Quality Statistics Production, Journal of Official Statistics 29 (2013), 187-192.

[16] 

Reamer A., Putting America to Work: The Essential Role of Federal Labor Market, Working Paper, Brookings Institution, Metropolitan Policy Program, 2010.

[17] 

Spanos A., Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation, Rationality, Markets and Morals 2 (2011), 146-178.

[18] 

Stegmueller W., Logical Understanding and the Dynamics of Theories, Collected Papers on Epistemology, Philosophy of Science and History of Philosophy, Synthese Library, Dordrecht, 91, 1977, 150-176.

[19] 

Struijs P., , Camstra A., , Renssen R., and Braaksmaf B., Redesign of Statistics Production within an Architectural Framework: The Dutch Experience, Journal of Official Statistics 29 (2013), 125-145.

[20] 

Sundgren B., Making Statistical Data More Available, International Statistical Review 64 (1996), 23-38.

[21] 

United Nations (1994/2014). Fundamental Principles of Official Statistics, Resolution adopted by the General Assembly on 29 January 2014. New York.

[22] 

United Nations. Economic and Social Council. Economic Commission for Europe (2014). Generic Statistical Business Process Modell. Prepared by the High-Level Group for the Modernization of Statistical Production and Services for the Sixty-second plenary session of the Conference of European Statisticians in Paris, 9-11 April 2014.

[23] 

Vanberg V., Rules and Choices, London and New York, 1994.

[24] 

Veen, Gosse van der (2007). Changing Statistics Netherlands. Driving Forces for Changing Dutch Statistics. Paper presented at the Seminar on the Evolution of National Statistical Systems. Commemorative Event for the 60th Anniversary of the United Nations Statistical Commission. New York, 23 February 2007.