Download Document

Borrowing: An overview about a
New Methodology for New
Economic Sciences
Houcemeddine Turki
B.Sc. Student, Faculty of Medicine of Sfax, University of Sfax, Sfax, Tunisia
Abstract
• Borrowing is the use of the methods and laws
of one science to solve a matter of another
science. Developed since the 19th Century, this
technique is nowadays highly recognized and
widely used in solving problems mainly for
Social Sciences. In this brief overview, the
principle and the development of this
technique as well as proofs from
Scientometrics and Science of its use and
efficiency would be provided.
Alexis Foundation
Notes
• This work has been done in order to obtain the
Certificate on Research Methodology as provided by
Alexis Foundation, Lucknow, India in 01 November
2014. Several parts of this work had been a subject of
participation to Fatih Koleji International
Environmental Project Olympiad 2012, Google Science
Fair 2012 and 2013, Intel ISEF National Qualifiers 2012
and several other important meetings in 2012.
• All existing computations in this work were updated in
01 March 2016. Even the computations of the Hirsch
indexes for leading Tunisian Scientists were updated in
31 January 2016.
Alexis Foundation
Acknowledgements
• I have to thank the Alexis Foundation for the
Certificate on Research Methodology that was
given to me for doing this research.
Alexis Foundation
Introduction
• Borrowing is the use of the methods and laws of one science to
solve a matter of another science (Steele & Stier, 2000). This
method is mainly used when the other science does not have
sufficient axioms and methods to solve its own advanced
fundamental problems. This is unfortunately the situation of Social
Sciences and mainly Economic Sciences. In fact, when they were
created in the 16th Century, Social Sciences were based only on
simple and abstract observation (Khaldun, 1978) and because of the
fact that observation returns only descriptive and imprecise
anthropologic deductions (Wikimedia Foundation, 2014; Thims,
2014), created Social Science Theories were inaccurate (Wikimedia
Foundation, 2014; Thims, 2014), imprecise (Wikimedia Foundation,
2014; Thims, 2014) and even ideologically explained (Shelby, 2003).
Alexis Foundation
Principle
• According to the General Systems Theory, any
axiom in a given science has its equivalent in
any other science as all of them are originally
created from Logic (Boulding, 1956).
• That is why an Economic Problem can be
assimilated to an equivalent problem in
another science. This is just what is meant by
Borrowing (Dove, 2001; Steele & Stier, 2000).
Alexis Foundation
Principle
Choice of the
analogue science
• It should be an Exact Science to get trusted results (Thims, 2014; Pentland, 2014; Drakopoulos, 2014;
Steele & Stier, 2000)
• Nowadays, lists of equivalence between the Economic axioms and the axioms of Exact Sciences like
Biology and Chemistry exist (Stanley, Amaral, Gabaix, Gopikrishnan, & Plerou, 2001; Lichtfouse,
Schwarzbauer, & Robert, 2012; Callejas, 2007; Chao, Chen, & Millstein, 2013; Becker, 1976; Mantegna
& Kertész, 2011; Richmond, Mimkes, & Hutzler, 2013; Mantegna & Stanley, 1999). It will be sufficient
Definition of the
to consider them.
Analogy
• It is just done by applying the analogy to the Economic Problem (Dove, 2001; Steele & Stier, 2000)
Conversion of the
problem
Alexis Foundation
Principle
Resolution of the
problem
Conversion of the
Results
Verification and
Interpretation of
the Results
• Resolution of the analogue problem using the axioms and methods of the
analogue science (Thims, 2014; Pentland, 2014; Richmond, Mimkes, & Hutzler,
2013; Dove, 2001).
• Conversion of the results of the analogue problem using the analogy to define
the result of the Economic Problem (Thims, 2014; Pentland, 2014; Richmond,
Mimkes, & Hutzler, 2013; Dove, 2001).
• Statistical and Economic Verification of the Results (Thims, 2014; Pentland, 2014;
Richmond, Mimkes, & Hutzler, 2013; Mantegna & Kertész, 2011)
• Economic Interpretation of the Efficient Results (Thims, 2014; Pentland, 2014;
Richmond, Mimkes, & Hutzler, 2013; Mantegna & Kertész, 2011)
Alexis Foundation
History
1377
•Ibn Khaldun defined the first principles of Economics in his Muqaddimah by using social
observations (Maunier, 1913; Khaldun, 1978). Although some of the theories of Ibn Khaldun
were proved nowadays as accurate like the relationship between tax and state income (Laffer,
2004), the theories of Ibn Khaldun were imprecise and only based on general descriptions as
they were only based on observations (Maunier, 1913).
15th, 16th and
17th Centuries
•Direct and Abstract Observations were used to determinate the Economic theories and
relationships (Peretz, 2004; Arborio, Fournier, de Singly, & Fournier, 2005). As these kinds of
observations were only based on what the observers sees and were not verified by any tool of
measurement and analysis, they were just intuitive and influenced by the thoughts and
convictions of the scientists (Peretz, 2004; Arborio, Fournier, de Singly, & Fournier, 2005).
•These observations were easily manipulated accorrding to the ideologies of the scientists of
that period (Dumont, 1979; Katouzian, Papineau, & Thomas, 1981). That is why Economic
theories were subjective and not considered as trusted as the theories of Exact Sciences
(Dumont, 1979; Katouzian, Papineau, & Thomas, 1981).
18th and 19th
Century
•Most scientists had recognized that Social Sciences are not as developed and trusted as Exact
Sciences. Scientists have thought about how to benefit from the accuracy and the precision of
Exact Sciences in order to promote underdeveloped sciences and mainly Economic ones
(Arborio, Fournier, de Singly, & Fournier, 2005; Fisher, 1941).
•Scienists have introduced two ways to benefit from Exact Sciences. In fact, they have proposed
to use Statistical Analysis to assess and measure Economic variables and patterns and they have
also thought of assimilating Economic Problems to problems from an exact science in order to
solve them. Both methods were efficient (Drakopoulos, 2014; Thims, 2014; Cournot, 1838).
Alexis Foundation
History
19011990
•Doing an analogy in order to prove an Economic fact requires a deep knowledge of Economics as
well as of the Exact Sciences (Treur, 2013). This can be hard for several researchers. However,
proving facts empirically using Statistics is simpler as Statistical Methods are unique and can be
easily peformed (Fisher, 1930; Fisher, 1941; Judge, Hill, Griffiths, Lutkepohl, & Lee, 1988) . That is
why several researches were conducted to promote the their use in Economics and let them more
efficient (Fisher, 1930; Fisher, 1941). The use of Statistics is Economics became a fundamental
field of Economics and was entitled Econometrics by the 1930s (Fisher, 1930; Fisher, 1941; Judge,
Hill, Griffiths, Lutkepohl, & Lee, 1988).
•Consequently, Econometrics became widely and excessively used to prove Economic patterns
(Judge, Hill, Griffiths, Lutkepohl, & Lee, 1988). However, The use of Borrowing became sharply
limited (Quddus & Rashid, 1994).
19902014
•Several Facts in Economics remained underdeveloped as they are not reducible to Mathematics
(Quddus & Rashid, 1994).. In fact, they cannot be assessed by numbers, scales or even as
qualitative factors because they are complex (Quddus & Rashid, 1994; Velupillai, 2005; Max-Neef,
2005).. For example, Paul Krugman has used Borrowing from Physics to prove facts in Economic
Geography that were not easily solvable by Statistics (Krugman, 2009).
•The usefulness of multidisciplinary borrowing is finally recognized .(Krugman, 2009; Max-Neef,
2005)
•There are some researches to ameliorate the use and the efficiency of multidisciplinary borrowing
in Economics (Apgar, Argumedo, & Allen, 2009). For example, works are currently done to solve
Economic matters more precisely by using Computer Simulation software like Matlab and Maple
to solve their analogue physical problems (Gander & Hrebicek, 2011; Gilbert & Troitzsch, 2005).
Borrowing is more commonly adopted nowadays (Apgar, Argumedo, & Allen, 2009).
•Trials began to implement multidisciplinary methods and mainly borrowing in the higher
education of Social Sciences (Max-Neef, 2005; Treur, 2013).
Alexis Foundation
Efficiency
• When calculating it using Google Scholar, it was seen
that the rate of the papers about Economic Geography
out of the papers about Economics has increased from
2003 until 2014 by over 11.80 percents as shown in
Table 1.
• As Economic Geography cannot be efficiently solved
only by using common Statistical Methods (Krugman,
2009), this proves that the use of Borrowing has been
efficient to increase precise research outputs about
fields in Economics that were not easily solvable using
Statistics due to their complexity.
Alexis Foundation
Table 1: Google Scholar Search Results
for Economic Geography and
Economics from 2003 until 2014
Year
Google
Scholar
Search
Results
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Economic
Geography
71800
83600
86600
96200
107000
113000
121000
133000
122000
116000
93900
67100
Economics
922000
981000
1020000
1020000
1090000
1100000
1070000
1010000
844000
717000
589000
341000
7.8
8.5
8.5
9.4
9.8
10.3
11.3
13.2
14.5
16.2
15.9
19.7
Percentile Rate
Alexis Foundation
Efficiency
• When seeing the Ranking of Tunisian
Scientists of 2014 (Turki & Turki, 2014), it is
clear that it includes five researchers in
Economics. These five scientists have
unfortunately not worked about the
simulation of Economic Problems as analogue
problems of an Exact Science. There are rather
working about Applied Economics and
Econometrics.
Alexis Foundation
Table 2: Ranking of the Best Tunisian
Scientists in Economics according to
their Efficient Productivity
Rank
Surname
Forename
Institution
Country
Field
Hirsch
Index
1
El Karoui
Nicole
France
Mathematics
40,29
2
Touzi
Nizar
France
Management
39,33
3
Boubakri
Narjess
24,19
Nabli
Mustapha
Kamel
United
Arab
Emirates
United
States
Economics
4
Université de Paris
VI
Université Paris
Dauphine
American
University in
Sharjah
World Bank,
Washington, D.C
Economics
20,15
5
Jouini
Elyes
Université Paris
Dauphine
France
Mathematics
19,14
Alexis Foundation
Efficiency
• These scientists do not exist in IDEAS h-index rankings
(RePEC, 2014).
• The only scientist existing in the ranking and that was born
in MENA Region is Raouf Boucekkine (RePEC, 2014) even if
he works under the same conditions as the leading Tunisian
Scientists.
• When seeing the work of Boucekkine, it was clear that he
has using Borrowing to solve several Economic Problems in
his works unlike the main Tunisian Scientists (Boucekkine &
Ruiz-Tamarit, 2008).
• This means that scientists and consequently works using
Borrowing have better research effect than the scientists
that are limited to the use of Econometrics to solve
problems.
Alexis Foundation
Efficiency
• This fact is confirmed in several studies. In fact,
– A tendency to cite multidisciplinary journals in Wikipedia has been
witnessed showing that interdisciplinary works and mainly the ones
using Borrowing are more efficiently received by the general audience
as they solve problems that were not evocated before using basic
Statistical Methods and as they use simple words in explaining facts so
that such works can be intelligible to the Economic scientists as well as
to the scientists of the analogue Exact Science (Nielsen, 2007; Nielsen,
2008).
– More interest in citing and creating Interdisciplinary Researches has
been reported in several researches proving that the scientific
audience has absolutely been convinced of the quality of the results
given by interdisciplinary methods (Rinia, van Leeuwen, & van Raan,
2002; Rinia, Van Leeuwen, Bruins, Van Vuren, & Van Raan, 2002;
Porter & Rafols, 2009). Interdisciplinary Borrowing researches are the
most ones that are benefiting from such interests (Steele & Stier,
2000).
Alexis Foundation
Conclusion
• Borrowing is a useful tool to prove Economic facts. This method should not
be underestimated nor misconsidered because it can serve to solve
Economic matters that are not reducible to Statistics. That is why several
leading Economic scientists have nowadays the conviction that a
researcher in Economics should be like an Engineer who combines
Statistical Methods and Interdisciplinary Borrowing in the quest of
Economic Truths (Roth, 2001; Mankiw, 2006).
• This method will have a more prestigious place in Economic sciences in
the next few years when it will be more precise by applying it using physics
and engineering simulation software like MATLAB and OpenSim.
Useful reading
• Axelrod, R. (1997). Advancing the art of simulation in the social sciences.
In Simulating social phenomena (pp. 21-40). Springer Berlin Heidelberg.
• Conte, R., Hegselmann, R., & Terna, P. (Eds.). (2013). Simulating social
phenomena (Vol. 456). Springer Science & Business Media.
Alexis Foundation
References
•
•
•
•
•
•
•
•
•
•
Apgar, J. M., Argumedo, A., & Allen, W. (2009). Building transdisciplinarity for managing complexity:
Lessons from indigenous practice. International Journal of Interdisciplinary Social Sciences , 4 (5),
255-270.
Arborio, A. M., Fournier, P., de Singly, F., & Fournier, P. (2005). L'observation directe. Paris: Armand
Colin.
Becker, G. S. (1976). Altruism, egoism, and genetic fitness: Economics and sociobiology. Journal of
economic Literature , 14 (3), 817-826.
Boucekkine, R., & Ruiz-Tamarit, J. R. (2008). Special functions for the study of economic dynamics:
The case of the Lucas-Uzawa model. Journal of Mathematical Economics , 44 (1), 33-54.
Boulding, K. E. (1956). General systems theory-the skeleton of science. Management science , 2 (3),
197-208.
Callejas, D. G. (2007). Biology and Economics: Metaphors that Economists usually take from Biology.
Ecos de Economía: A Latin American Journal of Applied Economics , 11 (24), 153-164.
Chao, H. K., Chen, S. T., & Millstein, R. L. (2013). Mechanism and causality in biology and economics.
Springer.
Cournot, A. A. (1838). Recherches sur les principes mathématiques de la théorie des richesses par
Augustin Cournot. L. Hachette.
Dove, M. R. (2001). Interdisciplinary borrowing in environmental anthropology and the critique on
modern science.
Drakopoulos, S. A. (2014). Mathematical Psychics and Hydraulics: The Methodological Influence of
Edgeworth and Fisher.
Alexis Foundation
References
•
•
•
•
•
•
•
•
•
•
Dumont, L. (1979). From Mandeville to Marx. The genesis and triumph of economic ideology.
Fisher, I. (1941). Mathematical method in the social sciences. Econometrica: Journal of the
Econometric Society , 185-197.
Fisher, I. (1930). The application of mathematics to the social sciences. Bulletin of the American
Mathematical Society , 36 (4), 225-243.
Gander, W., & Hrebicek, J. (2011). Solving problems in scientific computing using Maple and
Matlab®. Springer Science & Business Media.
Gilbert, N., & Troitzsch, K. (2005). Simulation for the social scientist. McGraw-Hill Education (UK).
Judge, G. G., Hill, R. C., Griffiths, W., Lutkepohl, H., & Lee, T. C. (1988). Introduction to the theory
and practice of econometrics.
Katouzian, H., Papineau, D., & Thomas, D. (1981). Ideology and method in economics.
Khaldun, I. (1978). The muqaddimah (N. J. Dawood ed.). Routledge.
Krugman, P. (2009). The increasing returns revolution in trade and geography. The American
Economic Review , 99 (3), 561-571.
Laffer, A. B. (2004). The Laffer curve: Past, present, and future.
Alexis Foundation
References
•
•
•
•
•
•
•
•
•
•
Lichtfouse, E., Schwarzbauer, J., & Robert, D. (2012). Social chemistry. Environmental Chemistry
Letters , 10 (1), 1-4.
Mankiw, N. G. (2006). The macroeconomist as scientist and engineer. National Bureau of Economic
Research.
Mantegna, R. N., & Kertész, J. (2011). Focus on statistical physics modeling in economics and
finance. New Journal of Physics , 13 (2), 025011.
Mantegna, R. N., & Stanley, H. E. (1999). Introduction to econophysics: correlations and complexity
in finance. Cambridge university press.
Maunier, R. (1913). Les idées économiques d'un philosophe arabe au XIV e siècle Ibn Khaldoun.
Revue d'histoire économique et sociale , 409-419.
Max-Neef, M. A. (2005). Foundations of transdisciplinarity. Ecological economics , 53 (1), 5-16.
Nielsen, F. Å. (2008). Clustering of scientific citations in Wikipedia. arXiv preprint arXiv:0805.1154 .
Nielsen, F. Å. (2007). Scientific citations in Wikipedia. arXiv preprint arXiv:0705.2106 .
Pentland, A. (2014). Social physics: how good ideas spread-the lessons from a new science. Penguin.
Peretz, H. (2004). Les méthodes en sociologie: l'observation. Paris: La découverte.
Alexis Foundation
References
•
•
•
•
•
•
•
•
•
•
Porter, A., & Rafols, I. (2009). Is science becoming more interdisciplinary? Measuring and mapping
six research fields over time. Scientometrics , 81 (3), 719-745.
Quddus, M., & Rashid, S. (1994). The overuse of mathematics in economics: Nobel resistance.
Eastern Economic Journal , 20 (3), 251-265.
RePEC. (2014, November 1). H-index Ranking. Retrieved 11 1, 2014, from IDEAS:
https://ideas.repec.org/top/top.person.hindex.html
Richmond, P., Mimkes, J., & Hutzler, S. (2013). Econophysics and physical economics. OUP Oxford.
Rinia, E. J., Van Leeuwen, T. N., Bruins, E. E., Van Vuren, H. G., & Van Raan, A. F. (2002). Measuring
knowledge transfer between fields of science. Scientometrics , 54 (3), 347-362.
Rinia, E., van Leeuwen, T., & van Raan, A. (2002). Impact measures of interdisciplinary research in
physics. Scientometrics , 53 (2), 241-248.
Roth, A. (2001). The Economist as Engineer. Econometrica .
Shelby, T. (2003). Ideology, racism, and critical social theory. The Philosophical Forum. 34(2), pp.
153-188. Blackwell Publishing Ltd.
Stanley, H. E., Amaral, L. A., Gabaix, X., Gopikrishnan, P., & Plerou, V. (2001). Similarities and
differences between physics and economics. Physica A: Statistical Mechanics and its Applications ,
299 (1), 1-15.
Steele, T. W., & Stier, J. C. (2000). The impact of interdisciplinary research in the environmental
sciences: a forestry case study. Journal of the American Society for Information Science , 51 (5), 476484.
Alexis Foundation
References
• Thims, L. (2014). Hmolpedia: AZ Encyclopedia of Human
Thermodynamics, Human Chemistry, and Human Physics.
• Treur, J. (2013). Designing a Problem-oriented, Multi-disciplinary
Curriculum: Integrating Human Sciences and Exact Sciences.
Procedia-Social and Behavioral Sciences , 93, 258-265.
• Turki, H., & Turki, M. (2014). Ranking of Tunisian Scientists
According to Their Efficient Productivity. An Overview of Scientific
Research Output in Tunisia. Munich, Germany: GRIN Verlag.
• Velupillai, K. V. (2005). The unreasonable ineffectiveness of
mathematics in economics. Cambridge Journal of Economics , 29
(6), 849-872.
• Wikimedia Foundation. (2014). Wikipedia, the Free Encyclopedia.
Retrieved from https://en.wikipedia.org
Alexis Foundation
Alexis Foundation