Application of the Kernel Density Function for the Analysis of Regional Growth and Convergence in the Service Sector through Productivity

Ronny Correa-Quezada, Lucía Cueva-Rodríguez, José Álvarez-García and María de la Cruz del Río-Rama
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Lucía Cueva-Rodríguez: Researcher and Consultant in Economics and Business, Loja 11-01-608, Ecuador
José Álvarez-García: Financial Economy and Accounting Department, Faculty of Business, Finance and Tourism, University of Extremadura, 10071 Cáceres, Spain
María de la Cruz del Río-Rama: Business Management and Marketing Department, Faculty of Business Sciences and Tourism, University of Vigo, 32004 Ourense, Spain

Mathematics, 2020, vol. 8, issue 8, 1-20

Abstract: The aim of this research work is to analyze growth and convergence processes in the service sector and its large groups, market, and non-market services, at the regional level in Ecuador by taking the labor productivity variable as a reference. The methodology used is an analysis of distributive dynamics of the data, applying the non-parametric method of Kernel density functions from a mathematical economics approach. The results obtained show that the service sector has non-alarming levels of inequality, its trend over time is increasing. When disaggregating the data, it was observed that non-market services show a rapid growth in inequality. In contrast, market services show greater stability during the period analyzed. Regarding intra-distribution dynamics for the service sector and its subsectors, in the long term, poor regions improve, while rich regions deteriorate. However, deterioration of advanced regions is less intense in non-market services.

Keywords: economic growth; regional growth; regional convergence; service sector; productivity; kernel density function (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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