Borradores de Economia
Number:
1283
Published:
Eleonora Dávalose, Classification JEL:
J61, J64, R12, R14
Keywords:
Matching Function, spatial spillovers, Spatial econometrics
The most recent
María Teresa Ramírez-Giraldo, Karina Acosta, Olga Lucia Acosta Navarro, Lucia Arango-Lozano, Fernando Arias-Rodríguez, Oscar Iván Ávila-Montealegre, Oscar Reinaldo Becerra Camargo, Leonardo Bonilla-Mejía, Grey Yuliet Ceballos-Garcia, Luz Adriana Flórez, Juan Miguel Gallego-Acevedo, Luis Armando Galvis-Aponte, Luis M. García-Pulgarín, Andrés Felipe García-Suaza, Anderson Grajales, Daniela Gualtero-Briceño, Didier Hermida-Giraldo, Ana María Iregui-Bohórquez, Juliana Jaramillo-Echeverri, Karen Laguna-Ballesteros, Francisco Javier Lasso-Valderrama, Daniel Márquez, Carlos Alberto Medina-Durango, Ligia Alba Melo-Becerra, María Fernanda Meneses-González, Juan José Ospina-Tejeiro, Andrea Sofía Otero-Cortés, Daniel Parra-Amado, Juana Piñeros-Ruiz, Christian Manuel Posso-Suárez, Natalia Ramírez-Bustamante, Mario Andrés Ramos-Veloza, Jorge Leonardo Rodríguez-Arenas, Alejandro Sarasti-Sierra, Bibiana Taboada-Arango, Ana María Tribín-Uribe, Juanita Villaveces
Carlos David Ardila-Dueñas, Joel Santiago Castellanos-Caballero, Carlos David Murcia-Bustos
Karina Acosta, Jesus Saldaña
Abstract
Most macroeconomic labor literature on estimating matching functions does not consider spatial spillover effects. However, job search and vacancy-filling processes often involve neighboring locations, as local workers can search for and fill vacancies in nearby labor markets. We estimate a spatial spillover model using annual data for a middle-income country in Latin America. Our findings show that unemployment has a positive spatial spillover effect because an increase in the labor supply raises the probability of filling a vacancy. In contrast, vacancies have a negative spillover effect because local and neighboring vacancies compete to be filled by workers in both markets.