Abstract
Much of the research on the accuracy of symbolic regression (SR) has focused on artificially constructed search problems where there is zero noise in the data. Such problems admit of exact solutions but cannot tell us how accurate the search process is in a noisy real world domain. To explore this question symbolic regression is applied here to an area of research which has been well-travelled by regression modelers: the prediction of unemployment rates. A respected dataset was selected, the CEP-OECD Labor Market Institutions Database, to provide a testing environment for a variety of searches. Metrics of success for this paper went beyond the normal yardsticks of statistical significance to demand “plausibility”. Here it is assumed that a plausible model must be able to predict unemployment rates out of the sample period for six future years: this metric is referred to as the “out of sample R2”. We conclude that the two packages tested, Eureqa and ARC, can produce models that go beyond the power of traditional stepwise regression. ARC, in particular, is able to replicate the format of published economic research because ARC contains a high level Regression Query Language (RQL). This research produced a number of models that are consistent with published economic research, have in sample R2 values over 0.80, no negative unemployment rates, and out of sample R2 values above 0.45. It is argued that SR offers significant new advantages to social science researchers.
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Blanchard O, Wolfers J (1999) The role of shocks and institutions in the rise of European unemployment: the aggregate evidence (working paper no. 7282). National Bureau of Economic Research
de Tocqueville A, Reeve H, Commager HSJ (1952) Democracy in America. Oxford University Press, London
Hayek FA (1994) The road to serfdom. University of Chicago Press, Chicago
Kaldor N (1982) The scourge of monetarism. Oxford University Press, New York
King JE (2009) Nicholas Kaldor. Palgrave Macmillan, New York
Korns MF (2007) Large-scale, time-constrained symbolic regression. In: R. Riolo, T. Soule, & B. Worzel (Eds.), Genetic programming theory and practice IV. Springer, US pp. 299–314. http://www.springerlink.com/content/p77g8gv231v37538/abstract/
Korns MF (2010) Symbolic regression of conditional target expressions. In: R. Riolo, U.-M. O’Reilly, & T. McConaghy (Eds.), Genetic programming theory and practice VII. Springer, US pp. 211–228. http://www.springerlink.com/content/n1m456589un33317/abstract/
Korns MF (2011) Abstract expression grammar symbolic regression. In: R. Riolo, T. McConaghy, & E. Vladislavleva (Eds.), Genetic programming theory and practice VIII. Springer, New York 8:109–128. http://www.springerlink.com/content/m763q88030380332/abstract/
Layard R, Nickell SJ, Jackman R (1991) Unemployment: macroeconomic performance and the labour market. Oxford University Press, New York
Layard PRG, Nickell SJ, Eichhorst W, Zimmermann KF (2011) Combatting unemployment. Oxford; New York: Oxford University Press
Nickell SJ, Nunziata L, Ochel W, Quintini G. (2001) The Beveridge Curve, Unemployment and Wages in the OECD from the 1960s to the 1990s - Preliminary Version (CEP Discussion Paper). Centre for Economic Performance, LSE. http://econpapers.repec.org/paper/cepcepdps/dp0502.htm
Nickell W (2006) The CEP-OECD institutions data set (1960–2004) (CEP discussion paper no. dp0759). Centre for Economic Performance, London School of Economics
Nickell S, Nunziata NL, Ochel W, Quintini G (2003) The Beveridge curve, unemployment and wages in the OECD from the 1960s to the 1990s. Princeton University Press, Princeton
Scmidt M (2013) Eureqa (version 0.98 beta)[software]. Available from http://www.eureqa.com
Schmidt M, Lipson H (2009) Distilling free-form natural laws from experimental data. Science 324(5923):81–85
Targetti F (1992) Nicholas Kaldor: the economics and politics of capitalism as a dynamic system. Oxford University Press, New York
World Bank (2012) Databank. The World Bank, Washington, DC. Retrieved on 24/8/2012 from http://data.worldbank.org
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Truscott, P., Korns, M.F. (2014). Explaining Unemployment Rates with Symbolic Regression. In: Riolo, R., Moore, J., Kotanchek, M. (eds) Genetic Programming Theory and Practice XI. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0375-7_7
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DOI: https://doi.org/10.1007/978-1-4939-0375-7_7
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