Impact of social, geographic and economic variables on formal financial inclusion for households in Peru and Piura 2019

Reviewing economic theory, to maximize utility, the individual will have to decrease consumption, according to the income they receive and demand financial services to opt for savings, for which the objective was to determine the effect of economic and social variables and geographical areas that affect formal financial inclusion for the department of Piura in 2019. The best binary logistic model was chosen as a method through the lowest AIC and BIC, finding that the best model is the Probit, and the survey was also used as an instrument. national household (ENAHO), resulting in that the education and income variables have a greater direct relationship with the use of some type of financial services, the same happens with married marital status and age but to a lesser extent, in terms of location geographical area the rural area has an indirect relationship with the use of some type of financial services. Keywords: Financial inclusion, Economic Variables, categorical models, financial determinants. References [1]Instituto Nacional de Estadistica e Informatica, «Panorama de la Económia Peruana 1950-2018,» Lima, 2019. [2]A. Sanderson, L. Mutandwa y L. R. Pierre, «A Review of Determinants of Financial Inclusion,» International Journal of Economics and Financial, vol. 8, nº 3, pp. 1-8, 2018. [3]K. Dai Won, Y. Jung Suk y H. M. Kabir, «Financial inclusion and economic growth in OIC countries,» Research in International Business and Finance, vol. 43, pp. 1-14, 2018. [4]Superintendencia de Bancos e Instituciones Financieras Chile, «Informe de Inclusión Financiera en Chile 2019,» 2019. [5]C. Aparicio y M. Jaramillo, « Determinantes de la inclusión al sistema financiero: ¿cómo hacer para que el Perú alcance los mejores estándares a nivel internacional?,» Superintendencia de Banca, Seguros y Administradoras Privadas de Fondos de Pensiones., Lima , 2012. [6]N. Cámara Izquierdo y D. Tuesta, «Factors that matter for financial inclusion evidence from Peru,» Dialnet, vol. 10, pp. 10-31, 2015. [7]M. Jaramillo, C. Aparicio y B. Sevallos, «¿Qué factores explican las diferencias en el acceso al sistema financiero?: evidencia a nivel de hogares en el Per´u,» Superintendencia de Banca, Seguros y Administradoras Privadas de Fondos de Pensiones, Lima, 2013. [8]E. Anchapuri, principales determinantes del acceso al crédito financiero en economías rurales y urbanas del distrito de juli, año 2013, Puno , 2014. [9]Banco Mundial, Banco Mundial. [10]Ministerio de Economía y Finanzas , «Estrategia Nacional de Inclusión Financiera,» Lima , 2015. [11]Superintendencia de Banca, Seguros y AFP, «Reporte de Indicadores de Inclusión Financiera de los Sistemas Financieros, de Seguros y de Pensiones,» Lima, 2019. [12]Banco Central de Reserva del Perú Sucursal Piura , «Caracterización del departamento de Piura,» Piura, 2018. [13]J. Wooldridge, Introducción a la econometría un enfoque moderno, Mexico: Cengage Learning Editores, S.A., 2010, p. 575. [14]D. Gujarati y P. Dawn, Econometría, Mexico: McGRAW-HILL/INTERAMERICANA EDITORES.S.A, 2010, p. 563.