A distribution rule for allocation problems with priority agents using the least square method

Authors

DOI:

https://doi.org/10.46661/rev.metodoscuant.econ.empresa.7575

Keywords:

Allocation problems, Least-squares method, Priority agents

Abstract

We use the least-squares method for inconsistent systems to find a new allocation rule for rationing and surplus problems. In particular, we study allocation problems considering different priorities to satisfy the agents’ demands, which influence how the distribution is carried out. The new distribution rule is proposed by choosing different inner products defined in linear algebra and providing explicit formulas for assigning resources to the agents. Moreover, we illustrate how it can recover different allocation rules by adequately defining the priorities. As an application of the rationing problem with priority agents, we consider real data for allocating police officers in the states of Mexico. In this example, the agents represent the states of Mexico, and their priorities were established based on the criminal incidence. Also, we compute and compare the resource distribution given by classic allocation rules and the percentage of loss obtained with each one.

Downloads

Download data is not yet available.

References

Casella, G. and Berger, R. L. (2021). Statistical inference. Cengage Learning.

Cruze, N. B., Goel, P. K., and Bakshi, B. R. (2014). Revisiting least squares techniques for the purposes of allocation in life cycle inventory. The International Journal of Life Cycle Assessment 19(10), 1733-1744.

https://doi.org/10.1007/s11367-014-0771-9

Eldar, Y. C. (2002). Least-squares inner product shaping. Linear algebra and its applications 348(1-3),153-174.

https://doi.org/10.1016/S0024-3795(01)00575-4

Guerrero, F. M., Hinojosa, M. Á., and Sánchez, F. (2006). Teoría de juegos aplicada a problemas de bancarrota. Contribuciones a la Economía, (2006).

Herrero, C. (2003). Equal awards vs. equal losses: duality in bankruptcy. In Advances in economic design, Springer, Berlin, Heidelberg, pages 413-426.

https://doi.org/10.1007/978-3-662-05611-0_22

Hoffman, K., Kunze, R., and Finsterbusch, H. E. (1973). Álgebra lineal. Prentice-Hall Hispanoamericana.

INEGI (2021). Población total por entidad federativa y grupo quinquenal de edad según sexo, serie de años censales de 1990 a 2020. https://www.inegi.org.mx/app/tabulados/interactivos/?pxq=Poblacion_Poblacion_01_e60cd8cf-927f-4b94-823e-972457a12d4b idrt=123 opc=t. Accessed: 2023-08-01.

INEGI (2022a). Identifican déficit de más de 100,000 policas en el país. https://www.eleconomista.com.mx/politica/Identifican-deficit-de-mas-de-100000-policias-en-el-pais-20210504-0014.html. Accessed: 2023-08-01.

INEGI (2022b). Incidencia delictiva. https://www.inegi.org.mx/temas/incidencia. Accessed: 2023-08-01.

Lorenzo, L. (2010). The constrained equal loss rule in problems with constraints and claims. Optimization 59(5), 643-660.

https://doi.org/10.1080/02331930802180301

Margalit, D., Rabinoff, J., and Rolen, L. (2017). Interactive linear algebra. Georgia Institute of Technology.

Moulin, H. (2000). Priority rules and other asymmetric rationing methods. Econometrica 68(3), 643-684.

https://doi.org/10.1111/1468-0262.00126

Ólvera-López, W., Sánchez-Sánchez, F., and Tellez-Tellez, I. (2014). Bankruptcy problem allocations and the core of convex games. Economics Research International 2014, 517951.

https://doi.org/10.1155/2014/517951

O'Neill, B. (1982). A problem of rights arbitration from the talmud. Mathematical social sciences 2(4), 345-371.

https://doi.org/10.1016/0165-4896(82)90029-4

Strutz, T. (2011). Data fitting and uncertainty: A practical introduction to weighted least squares and beyond. Springer.

https://doi.org/10.1007/978-3-8348-9813-5

Thomson, W. (2003). Axiomatic and game-theoretic analysis of bankruptcy and taxation problems: a survey. Mathematical social sciences 45(3), 249-297.

https://doi.org/10.1016/S0165-4896(02)00070-7

Secretaría de Seguridad y Protection Ciudadana Diario Oficial (2021). Modelo nacional de policía y justicia cívica. https://www.gob.mx/cms/uploads/attachment/file/542605/DOC_1._MODELO_NACIONAL_DE_POLIC_A_Y_JC.pdf, Last accessed on 2017-11-30.

Published

2024-04-30

How to Cite

Macías Ponce, J. C., Giles Flores, A. E., Delgadillo Alemán, S. E., Kú Carrillo, R. A., & Rodríguez Esparza, L. J. (2024). A distribution rule for allocation problems with priority agents using the least square method. Journal of Quantitative Methods for Economics and Business Administration, 37, 1–20. https://doi.org/10.46661/rev.metodoscuant.econ.empresa.7575

Issue

Section

Articles