Objectives: Our aim is to assess whether analogical econometrics or numerical econometrics yield the best results. Methods: Through analogical econometrics, we show that, at the equilibrium level, each productive factor and each good or service is far from having the same price in each generation and country. This cannot realize an efficient trade of externalities that decouples growth and volatility. Second, we use numerical econometrics tests. Stressing the theory of multidimensional trade is sufficiently similar to a biological mechanism, we could say of one or more things that also apply to the other. We would then have more powerful analytical tools than the very approximate analogical econometric methods, and economic policy would become normative. Results: Using numerical tests, through laboratory experiments, we find that the human organism’s multidimensional exchange mechanism, consisting of more or less integral compensation processes for negative and positive externalities, leads to volatility of human growth(ecosystems), the main determinant of life expectancy, analogous to the relationship between the processes of economic growth volatility and sustainable growth. Because the analogy is clearly established, the frontier of production possibilities of neurotransmitter secretion centers appears to be the sole determinant of life expectancy, as is the global technology frontier for sustainable growth. Finally, the assumption of multidimensional exchange becomes the optimal policy for managing ecosystems and biodiversity and is the only one to guarantee general equilibrium in all markets. Any imbalance in social ecosystems is transmitted to natural ecosystems, affecting any efficient exchange system at all levels due to functional or conflicting interdependencies.
References
[1]
Abramovitz, M. (1986). Catching Up, Forging Ahead and Falling Behind. Journal of Economic History, 46, 385-406. https://doi.org/10.1017/S0022050700046209
[2]
Afman, M., Chappin, E., Dijkema, G., & Jager, W. (2010). Agent-Based Model of Transitions in Consumer Lighting. In Proceedings of 3rd World Congress on Social Simulation.
[3]
Aldred, S., Rohalu, M., Edwards, K., & Burns, V. (2009). Altered DHEA and DHEAS Response to Exercise in Healthy Older Adults. Journal of Aging and Physical Activity,17, 77-88. https://doi.org/10.1123/japa.17.1.77
[4]
Bajona, C., & Kehoe, T. J. (2006). Demographics in Dynamic Heckscher-Ohlin Models: Overlapping Generations versus Infinitely Lived Consumers. Journal of Economics, 105, 501-526. https://doi.org/10.3386/w12566
[5]
Barro, R. J. (1983). Economic Growth in a Cross-Section of Countries. The Quarterly Journal of Economics, 106, 407-443.
[6]
Black, F. (1987). Business Cycles and Equilibrium. Blackwell.
[7]
Blackburn, K. (1999). Can Stabilization Policy Reduce Long-Run Growth? The Economic Journal, 109, 67-77. https://doi.org/10.1111/1468-0297.00391
[8]
Blackburn, K., & Galindev, R. (2003). Growth, Volatility and Learning. Economics Letters, 79, 417-421. https://doi.org/10.1016/S0165-1765(03)00025-9
[9]
Cass, D. (1965). Optimum Growth in an Aggregative Model of Capital Accumulation. The Review of Economic Studies, 32, 233-240. https://doi.org/10.2307/2295827
[10]
Chappin, E. J. L., Dijkema, G. P. J., van Dam, K. H., & Lukszo, Z. (2007). Modeling Strategic and Operational Decision-Making Using an Agent-Based Model of Electricity Producers. In The European Simulation and Modeling Conference (pp. 201-219). Springer.
[11]
Choi, J., Im, N., & Park, J. (2012). Agent Based Model for Estimating Hybrid Electric Vehicle Market: The Case of Korea. Energy, Climate and Environment Modeling and Simulation, 44, 26e33.
[12]
Copeland, J. L. et al. (2002). Sedentary Time in Older Adults: A Critical Review of Measurement, Associations with Health, and Interventions. British Journal of Sports Medicine, 51, 1539.
[13]
Desmarchelier, C., Martin, J.-C., Planells, R., Gastaldi, M., Nowicki, M., Goncalves, A., Valero, R., & Borel, P. (2013). A Combination of SNPs Is Associated with the Postprandial Chylomicron Triacylglycerol Response in Healthy Male Adults. In International Congress on Coronary Artery Disease.
[14]
Edgeweblime, K. L. (2019). Multidimensional Trade and Ramsey Effects: Sustainable Growth versus Volatility. Journal of Cleaner Production,231, 1474-1488. https://doi.org/10.1016/j.jclepro.2019.03.318
[15]
Eppstein, D., Cross, A. W., Magesan, E., & Gambetta, J. M. (2013). Investigating the Limits of Randomized Benchmarking Protocols. Physical Review A, 89, Article 062321. https://doi.org/10.1103/PhysRevA.89.062321
[16]
Greendale, G. A. et al. (1999). The Menopause. The Lancet, 353, 571-580. https://doi.org/10.1016/S0140-6736(98)05352-5
[17]
Grossman, G. M., & Helpman, E. (1991). Innovation and Growth in the Global Economy. MIT Press.
[18]
Heaney, J. L. J., Carroll, D., & Phillips, A. C. (2013). Physical Activity, Life Events Stress, Cortisol, and DHEA in Older Adults. Journal of Aging and Physical Activity, 22, 465-473.
[19]
Herlenius, E., & Lagercrantz, H. (2011). Neurotransmitters and Neuromodulators during Early Human Development. Early Human Development, 87, 231-238.
[20]
Hsieh, C. T., & Klenow, P. J. (2009). Misallocation and Manufacturing TFP in China and India. The Quarterly Journal of Economics, 124, 1403-1448. https://doi.org/10.1162/qjec.2009.124.4.1403
[21]
King, R. G., Plosser, C. I., & Rebelo, S. T. (1988). Production, Growth and Business Cycles. II. New Directions. Journal of Monetary Economics, 21, 309-341. https://doi.org/10.1016/0304-3932(88)90034-7
[22]
Klenow, P. J. (2012). Reset Price Inflation and the Impact of Monetary Policy Shocks. American Economic Review, 102, 2798-2825. https://doi.org/10.1257/aer.102.6.2798
[23]
Koopmans, T. C. (1965). On the Concept of Optimal Economic Growth. In The Economic Approach to development Planning (pp. 225-287), Rand McNally.
[24]
Lamberts, S. W. et al. (1997). The Endocrinology of Aging. Science, 278, 419-424. https://doi.org/10.1126/science.278.5337.419
[25]
Lempert, R. (2002). Agent-Based Modeling as Organizational and Public Policy Simulators. PNAS, 99, 7195-7196. https://doi.org/10.1073/pnas.072079399
[26]
Lengnick, M. (2012). Agent-Based Macroeconomics: A Baseline Model. Journal of Economic Behavior & Organization, 86, 102-120. https://doi.org/10.1016/j.jebo.2012.12.021
[27]
Levine, R., & Renelt, D. (1992). A Sensitivity Analysis of Cross-Country Growth Regressions. The American Economic Review, 82, 942-963.
[28]
Pataky, T. C. et al. (2021). Landmark-Free, Parametric Hypothesis Tests Regarding Two-Dimensional Contour Shapes Using Coherent Point Drift Registration and Statistical Parametric Mapping. PeerJ Computer Science, e542. https://doi.org/10.7717/peerj-cs.542
[29]
Ramsey, F. P. (1928). A Mathematical Theory of Saving. The Economic Journal, 38, 543-559. https://doi.org/10.2307/2224098
[30]
Rawls, J. (1974). Some Reasons for the Maximin Criterion. In R. Manley (Ed.), Justice and Economic Distribution (pp. 31-44). Harvard University Press.
[31]
Solow, R. (1956). A Contribution to the Theory of Economic Growth. The Quarterly Journal of Economics, 70, 65-94. https://doi.org/10.2307/1884513
[32]
Sullivan et al. (1994). Key Concepts in Communication and Cultural Studies. Routledge.
[33]
Sutton, S. W., & Lazarus, R. S. (1976). Patterns of Adjustment. McGraw-Hill.
[34]
Tesfatsion, L. (2003). Agent-Based Computational Economics: Modeling Economies as Complex Adaptive Systems. Information Sciences, 149, 262-268. https://doi.org/10.1016/S0020-0255(02)00280-3
[35]
Tomczak, P., & Stachowiak, K. (2015). Location Patterns and Location Factors in Cultural and Creative Industries. Quaestiones Geographicae, 34. https://doi.org/10.1515/quageo-2015-0011
[36]
van der Veen, C., & van Oers, B. (2017). Advances in Research on Classroom Dialogue: Learning Outcomes and Assessments. Learning and Instruction, 48, 1-4. https://doi.org/10.1016/j.learninstruc.2017.04.002
[37]
Viguié, C. et al. (2012). Les perturbateurs endocriniens: Enjeux pour le consommateur et défis scientifiques. Innovations Agronomiques, 24, 91-103.
[38]
von Neumann, J. (1935). On Complete Topological Spaces. Transactions of the American Mathematical Society, 37, 1-20. https://doi.org/10.1090/S0002-9947-1935-1501776-7
