Mapping the spatial pattern of the uncertain data in urban areas: The disadvantaged predict global nonresponse rate in the National Household Survey

2019 ◽  
Vol 64 (1) ◽  
pp. 79-104
Author(s):  
Scott Bell ◽  
Michaela Sidloski ◽  
Tayyab Ikram Shah
Author(s):  
Roberto Arpi-Mayta ◽  
Luis Arpi-Quilca

<p>El objetivo del estudio fue determinar los retornos a la educación en el mercado laboral peruano durante el año 2015; según grupo étnico, área de residencia, sexo y categoría ocupacional de las personas; en forma específica se determina el efecto de la inversión en educación y la experiencia laboral sobre el ingreso laboral por hora. Los datos provienen de la Encuesta Nacional de Hogares del Instituto Nacional de Estadística e Informática y se estima la ecuación de ingresos de (Mincer, 1974) ampliada, utilizando la propuesta de (Heckman J. , 1979) en dos etapas bajo el marco teórico de (Becker, 1975). Sujeto a las limitaciones de datos y métodos utilizados, se concluye que el ingreso laboral de los peruanos aumenta 10,43% por año adicional de educación, aunque esto es diferenciado; tal es el caso, que el ingreso laboral por hora de los residentes del área urbana se incrementa 13,6% por año adicional de educación en relación a los del área rural (5,89%); los trabajadores asalariados perciben mayor ingreso (14,16%) que los trabajadores independientes (6,07%); los indígenas (8,32%) menos que los no indígenas (10,58%); y los las mujeres (10,62%) menos que las hombres (11,84%). La política educativa y laboral recomendada sería que se apliquen medidas de discriminación (positiva) a favor de las personas que se encuentren en el área rural, a los que trabajan en forma independiente, a los indígenas y a las mujeres.</p><p align="center"> </p><p align="center"> </p><p align="center">ABSTRACT</p><p align="center"> </p><p>The aim of the study was to determine the returns to education in the Peruvian labor market during 2015; by ethnic group, area of residence, sex and occupational category of people; specifically we determined the effect of investment in education and work experience on hourly labor income. The data come from the National Household Survey of the National Institute of Statistics and Informatics and the earnings equation (Mincer, 1974) extended (1974) is estimated using the proposed (Heckman J. , 1979) in two stages under the theoretical framework of (Becker, 1975). Subject to the limitations of data and methods used, it is concluded that the Peruvian labor income increases 10,43% per additional year of education, although this is differentiated; such is the case, the hourly labor income of residents in urban areas increased 13,6% per additional year of education in relation to rural areas (5.89%); salaried workers receive higher income (14.16%) than the self-employed (6.07%); indigenous (8.32%) less than non-indigenous (10.58%); and women (10.62%) less than men (11.84%). The educational and employment policy recommended would be that discrimination measures (positive) been applied for people who are in rural areas, who work independently, indigenous and women.</p><p><br /> <strong>KEYWORDS:</strong> Returns to education, employment income, investment in education,</p><p> </p>


2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Marika Morris

Over a quarter of Inuit in Canada now live outside Inuit Nunangat (Inuit traditional lands). Many have migrated to large Canadian urban centres such as Edmonton, Winnipeg, Ottawa, and Montreal. This article pieces together data from the Census, National Household Survey, Aboriginal People’s Survey, and General Social Survey on Victimization to create a statistical profile of today’s Inuit in terms of income, employment, education, health, housing, crime and safety, and culture and language, and the context in which these data should be read. The article discusses the implications of the increasing urbanization of Inuit for policy and research, and concludes that support for innovative Inuit services in urban areas is necessary. 


2007 ◽  
Author(s):  
Charles R. Figley ◽  
Elizabeth Donnelly ◽  
Hadi Mukhtar Ali Ridha ◽  
Fahad Al Naser

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