Abstract
This paper tries to answer a basic (and often-asked) question about econophysics: “Whereas it is quite understandable that physical techniques of observation (e.g., infra-red spectroscopy) can be useful in investigating DNA or proteins, it is much less obvious why and how ideas from physics can be helpful in investigating socio-economic phenomena”. The main obstacle to the understanding of social phenomena is the fact that they are multifaceted, which makes it difficult to observe one effect at a time. In this paper we argue that in its early phase of development physics was confronted with the same difficulty and that the basic methodology of experimental physics has been set up precisely as a way to disentangle multi-faceted phenomena. In order to make this point, we first explain how this can be done for a very simple phenomenon, namely, the free fall. In this case, even though there are only two effects, namely, gravitation and drag, their combination can give rise to quite complicated motions. In the second part we show how the same methodology can be used to resolve social phenomena into simple mechanisms. As an illustration we consider the phenomenon of suicide and explain how it is possible to focus on one factor at a time. As a case in point, we investigate the suicide rate of unmarried versus married persons; it turns out that the population of Chinese immigrants in the United States provides an ideal “laboratory” for observing this effect. In a general way, in this approach the crucial question is to find a situation in which the impact of the factor under study is amplified as much as possible. In its concluding part the paper briefly discusses how the usefulness of mathematical models can be improved.
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Roehner, B.M. Econophysics: Challenges and Promises —An Observation-based Approach. Evolut Inst Econ Rev 4, 251–266 (2008). https://doi.org/10.14441/eier.4.251
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DOI: https://doi.org/10.14441/eier.4.251
Keywords
- econophysics
- free fall
- suicide
- observation
- experiment
- noise reduction
- multi-factor phenomena
- modeling
- prediction
- models