scholarly journals Retornos heterogéneos a la Educación en el Mercado laboral Peruano, 2015

2016 ◽  
Vol 18 (3) ◽  
Author(s):  
Roberto Arpi-Mayta ◽  
Luis Arpi-Quilca
Keyword(s):  
Rural Areas ◽  
Work Experience ◽  
Urban Areas ◽  
Returns To Education ◽  
Household Survey ◽  
Labor Income ◽  
Employment Policy ◽  
National Household Survey ◽  
Las Mujeres ◽  
Politica Educativa

<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>

scholarly journals Human capital and job opportunities according to educational level in Perú

2021 ◽  
Vol 25 (110) ◽  
pp. 48-57
Author(s):  
Freddy Carrasco Choque ◽  
Rudy Francheska Castillo Araujo
Keyword(s):  
Human Capital ◽  
Rural Areas ◽  
Work Experience ◽  
Returns To Education ◽  
Household Survey ◽  
Healthcare Spending ◽  
Middle Income ◽  
Heckman Model ◽  
Schooling Experience ◽  
Mincer Equation

Education promotes progress and economic and social growth, improves the quality of life of the population. The first objective of the study was to identify people's income according to the years of schooling, the second was to estimate the income gap according to gender, residence and working conditions, the third was to identify the return of education, work experience towards the income of the Peruvian inhabitants. Parametric tests and the two-stage Heckman model were used to obtain the results. The data come from the National Household Survey. Income differs according to schooling. There are gaps in earned income. For one more year of education, the monetary return amounts to 12,46%, if it is a woman, it is 13,23%, if it is a man, it is 11,51%, if it resides in an urban area it amounts to 10,62%, if it is a resident in rural areas it amounts to 9,83%. Keywords: Labor income, returns to education, Mincer equation, Heckman methodology. References [1]J. Mincer, “Schooling, Experience, and Earnings,” Natl. Bur. Econ. Res., 1974, [Online]. Available: https://www.nber.org/books-and-chapters/schooling-experience-and-earnings. [2]T. W. Schultz, “Investment in Human capital,” Am. Econ. Rev., vol. Vil. (1)2, 1961. [3]J. Freire and M. Teijeiro, “Las ecuaciones de Mincer y las tasas de rendimiento de la educación en Galicia,” Investig. Econ. la Educ. 5 - Univ. A Coruña, 2010. [4]K. Ogundari and A. Abdulai, “Determinants of Household’s Education and Healthcare Spending in Nigeria: Evidence from Survey Data,” African Dev. Rev., vol. Vol. 26, N, pp. 1–14, 2014. [5]C. Montenegro and H. Patrinos, “Comparable estimates of returns to schooling around the world,” Policy Res. Work. Pap. Ser. 7020, World Bank., 2014. [6]G. Fink and E. Peet, “Returns to Education in Low and Middle-Income Countries: Evidence from the Living Standards and Measurement Surveys,” Progr. Glob. Demogr. Aging Harvard Univ., vol. PGDA Worki, 2014, [Online]. Available: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1288/2015/06/PGDA_WP_120_Fink.pdf. [7]L. Godínez, E. Figueroa, and F. Pérez, “Rentabilidad privada de la educación en el Estado de México,” Papeles Poblac. - Univ. Auton. Mex., vol. Vol. 22 N°, 2016. [8]M. Diaz, “Brecha Salarial por Género en Colombia.,” Econ. y Finanz. Int. - Univ. la Sabana - Colomb., 2014. [9]M. Urroz and M. Salgado, “La relación entre educación e ingresos: estimación de las diferencias salariales por nivel educativo alcanzado,” Fund. Zamora Terán, 2014. [10]E. Tarupi, “El capital humano y los retornos a la educación en Ecuador,” Gest. - Rev. Int. Adm., 2015, [Online]. Available: https://revistas.uasb.edu.ec/index.php/eg/article/view/571. [11]R. Arpi and L. Arpi, “Retornos Heterogeneos a La Educación En el Mercado Laboral Peruano, 2015,” Rev. Investig. Altoandina, vol. Vol. 18, 2016. [12]R. Paz and J. C. Quilla, “Retornos a la Educación de los Jefes de Hogar en la Región de Puno, 2011 – 2015,” Rev. Investig. Altoandina, vol. V. 18, 2016. [13]INEI, “Instituto Nacional de Estadistica e Informatica - Evolucion de la Pobreza Monetaria 2008 - 2019,” 2020. [Online]. Available: https://www.inei.gob.pe/media/cifras_de_pobreza/informe_pobreza2019.pdf. [14]A. Smith, An Inquiry into the Nature and Causes of the Wealth of Nations. Londres: Londres - Reino Unido, 1776. [15]G. Becker, “A Theory of the Allocation of Time,” Econ. J., vol. Vol. 75 N°, p. pp.493-517, 1964. [16]R. Hernández, C. Fernández, and M. del P. Baptista, Metodologia de la Investigación, vol. 6ta Ed. 2014. [17]W. Mendoza, Cómo Investigan los Economistas, 1ra Ed. Lima - Perú, 2014. [18]D. Alfaro and E. Guerrero, “Brechas de genero en el ingreso: Una mirada mas alla de la media en el sector agropecuario,” Consorc. Investig. Econ. y Soc. - CIES, 2013, [Online]. Available: http://cies.org.pe/sites/default/files/investigaciones/1_informe_final_pb19_-_alfaro_y_guerrero_final.pdf. [19]J. Wooldridge, Introduccion a la Econometria. Un enfoque moderno, 4ta Ed. Mexico, D.F., 2009. [20]D. Gujarati and D. Porter, Econometría. 2010.

scholarly journals Human Capital and Urbanization in the People’s Republic of China

2019 ◽  
pp. 475-513
Author(s):  
Chunbing Xing
Keyword(s):  
Human Capital ◽  
Rural Areas ◽  
Urban Areas ◽  
Returns To Education ◽  
People’S Republic Of China ◽  
Urban Migration ◽  
People's Republic Of China ◽  
Large Cities ◽  
Republic Of China ◽  
Capital Development

This chapter explores the relationship between human capital development and urbanization in the People’s Republic of China, highlighting the Hukou system and decentralized fiscal system. Educated workers disproportionately reside in urban areas and in large cities, and the returns to education are higher in urban areas relative to those in rural areas, and in large, educated cities relative to small, less educated cities. In addition, the external returns to education in urban areas are at least comparable to the magnitude of private returns. Rural areas are the major reservoir for urban population growth, and the more educated have a higher chance of moving to cities and obtaining urban Hukou. As for health, rural–urban migration is selective in that healthy rural residents choose to migrate. However, occupational choices and living conditions are detrimental to migrants’ health. While migration has a positive effect on migrant children, its effect on ‘left-behind’ children is unclear.

scholarly journals Health shocks and vulnerability to poverty in Congo

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Séverin Aimé Blanchard Ouadika
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Poverty Reduction ◽  
Household Survey ◽  
Generalized Least Squares ◽  
Well Being ◽  
Health Shocks ◽  
Health Shock ◽  
Vulnerability To Poverty ◽  
Future Consumption

AbstractThe analysis of the link between poverty and health status in developing countries is a major focus of development policy. However, few studies, particularly in the Congo, focus on a prospective analysis of poverty and consider the variability of future consumption after a health shock. The objective of this study is to estimate vulnerability to poverty and analyse the factors that lead to a loss of well-being after a health shock in Congo. The study uses data from the 2011 Congolese Household Survey (CHS). Estimation of vulnerability to poverty and modelling of the effect of the health shock on expected future consumption are performed using the three-step feasible generalized least squares (FGLS) method. This method is also used to identify the socio-demographic determinants of vulnerability. On average, 26.8% of households are vulnerable to poverty in Congo. Health shocks accentuate this vulnerability. Households living in rural areas are more vulnerable to poverty than those in urban areas. Furthermore, household size and the level of education and marital status of the head of household have an impact on vulnerability. In view of the results obtained, poverty reduction efforts should focus on strategies to develop social safety nets and/or health insurance programmes to stabilize consumption in the event of a health shock in the household.

scholarly journals Differences in the Early Impact of COVID-19 on Food Security and Livelihoods and in Rural and Urban Areas in the Asia Pacific Region

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 229-229
Author(s):  
Yunhee Kang ◽  
Anurima Baidya ◽  
Alec Aaron ◽  
Jun Wang ◽  
Christabel Chan ◽  
...  
Keyword(s):  
Food Security ◽  
Rural Areas ◽  
Urban Areas ◽  
Household Survey ◽  
Essential Medicines ◽  
Asia Pacific ◽  
Rural And Urban Areas ◽  
Food Stock ◽  
Rural And Urban ◽  
Food Expenditure

Abstract Objectives Lockdowns due to COVID-19 had health, economic, social, and political consequences globally. This study examined if the early impact of COVID-19 on livelihoods and food security differed between rural and urban areas in six Asia-Pacific countries. Methods Secondary data analysis was conducted in May 2029 using a total of 13,522 household survey data collected cross-sectionally among socially disadvantaged populations through a World Vision's rapid response assessment (n = 13,522) in Bangladesh, India, Indonesia, Philippines, Myanmar, and Vietnam. Changes in food expenditure, availability of various food items, and accessibility and affordability of essential items (staple food, fresh foods, medicine, and hygiene) were tested between rural and urban areas using multivariate logistic regressions, accounting for confounding variables. Results Job loss or reduced income was prevalent (rang: 54.1%–89.6%), higher in urban than rural areas in all six countries. A higher percentage of households reduced food expenditure in urban areas (53.0%–80.3%) than in rural areas (34.2%–66.4%) in India, Myanmar, and Vietnam (all P &lt; 0.001). The proportion of households having no food stock varied in six countries (13.4%-66.0%), with lower odds of available food stocks in urban areas than rural areas (OR range in Bangladesh, India, and Myanmar: 0.30–0.53, all P &lt; 0.05). Access to essential items was moderate to high depending on the type of item. Essential medicines were more accessible in urban than in rural areas with an OR range of 1.88–5.63 in India, Myanmar, and Vietnam. Household affordability was low particularly for rent (3.8%-16.6%) and loan repayment (3.3%-19.9%), with higher affordability for rent payments in urban than in rural areas with an OR range of 1.98–22.2 across four countries (P &lt; 0.05). Access and affordability for essential items were better in urban areas than in rural areas in Vietnam. Conclusions Disproportional differences were found in experiencing food security and livelihoods between rural and urban areas in six Asia Pacific countries. An understanding of the differential implications of lockdowns related to COVID-19 by residence can inform specifically recovery policies and guide mitigation efforts. Funding Sources N/A

The nexus between poverty and socio-economic characteristics of the household and household head: Evidence from Sierra Leone

2021 ◽  
Vol 9 (3) ◽  
pp. 53-65
Author(s):  
Abu Bakarr Turay ◽  
Keyword(s):  
Sierra Leone ◽  
Rural Areas ◽  
Urban Areas ◽  
Poverty Reduction ◽  
Formal Education ◽  
Tertiary Education ◽  
Household Head ◽  
Household Survey ◽  
Policy Action ◽  
Extreme Poverty

Household poverty is widespread in Sierra Leone, affecting about 6 out of every 10 persons, which calls for urgent policy action. This study used the 2018 Sierra Leone Integrated Household Survey (2018 SLIHS) and a logistic model to analyze the influence of socio-economic characteristics of the household and household head on poverty. The analysis has shown that living in rural areas, having no formal education, or being unemployed, significantly increases the probability of a household being in extreme poverty. Other factors contributing to household extreme poverty status were: have a large household size with many children below 10 years, being separated from a spouse (widowed or divorced), being disabled, and working in the agriculture sector. On the other hand, the characteristics that decrease the probability of a household being poor include being a female household head, having at least secondary school education (notably tertiary education), residing in urban areas or cities, working in the services sector, and being single or married. Therefore, enhancing service delivery through a viable decentralization process, and supporting easily accessible quality education programmes, especially tertiary education, are critical for meaningful poverty reduction across all sections of the population. Keywords: Poverty, household, socio-economic characteristics, logistics model.

Burden of Anemia and its Socioeconomic Determinants among Adolescent Girls in India

2009 ◽  
Vol 30 (3) ◽  
pp. 217-226 ◽  
Author(s):  
Premananda Bharati ◽  
Suparna Shome ◽  
Suman Chakrabarty ◽  
Susmita Bharati ◽  
Manoranjan Pal
Keyword(s):  
Adolescent Girls ◽  
Rural Areas ◽  
Urban Areas ◽  
Economic Status ◽  
Household Survey ◽  
Sociodemographic Factors ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Health Project ◽  
Project Data

Background Anemia is still one of India's major public health problems, especially among adolescent girls. Objective To investigate the severity and distribution of anemia among Indian adolescent girls aged 10 to 19 years and its association with socioeconomic and sociodemographic factors. Methods The study used data from the District Level Household Survey, round II, 2002–04, conducted under the Reproductive and Child Health Project. Data were collected on hemoglobin along with socioeconomic and sociodemographic factors of the households. The survey covered rural and urban areas of 35 states or union territories. Data from 177,670 adolescent girls were analyzed. Results The highest prevalence of anemia (99.9%) was observed in Jharkhand in eastern India. The prevalence in the northeastern states was relatively low. The highest prevalence rates were observed among older girls (15 to 19 years), illiterate girls living in rural areas, girls in illiterate households, girls from households with a low standard of living, non-Christian girls, girls from Scheduled Tribes, girls living in west India, and married girls. The highest percentages of girls with normal hemoglobin were reported among Christian Scheduled Tribes (39.4%) and among girls in northeastern India (40.1%). Analysis by binary ordered logistic regression showed that anemia status did not depend on urban or rural residence or on age. Conclusions Enhancement of the economic status of families, especially poor families, is a prerequisite to the amelioration of anemia among adolescent girls. The level of education of the girls is also a major factor.

scholarly journals Returns to Education in Rural and Urban China: An Empirical Study

2018 ◽  
Vol 3 (4) ◽  
pp. 18
Author(s):  
Feng Wang ◽  
Hao Wu
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Returns To Education ◽  
Educational Inequality ◽  
National Level ◽  
Urban China ◽  
Data Set ◽  
Rural And Urban ◽  
Significant Difference ◽  
Rate Of Returns

This paper focuses on the returns to education in China, and it aims to determine the returns rate difference between those in the rural and urban areas. Mincer’s model has been used as the base for the returns rate calculation. OLS has been chosen as the estimator for the regression analysis. The data set selected for analyzing was CHIP 2013, which is one of the latest national level education and income surveys conducted in China. The empirical analysis results showed that the rate of returns to education for the general samples was 13.9%. This, therefore, was higher than the rate (around 10%) in 2000-2010 in China. Meanwhile, the significant difference between rural (3.7%) and urban (25.6%) areas has been detected. The gender equality testing showed that in rural areas, the rate of returns to education for females (9.1%) was much higher than males (2.5%). The results provided an overview of the current situation regarding the educational investment in China. It also pointed out the income and educational inequality between rural-urban and male-female.

scholarly journals Análisis de variables motivacionales y de estilos de vida saludables en practicantes de ejercicio físico en centros deportivos en función del género (Analysis of motivational variables and healthy lifestyles in sports center practitioners by gender)

Retos ◽  
2017 ◽  
pp. 166-171
Author(s):  
Marta Leytón Román ◽  
Judiht García Matador ◽  
Juan Pedro Fuentes García ◽  
Rhut Jiménez Castuera
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Healthy Lifestyle ◽  
Eating Habits ◽  
Psychological Needs ◽  
Need Satisfaction ◽  
Physical Activities ◽  
Psychological Need ◽  
Las Mujeres ◽  
Psychological Need Satisfaction

Los objetivos de estudio fueron analizar las diferencias en función del género y del ámbito de pertenencia (rural-urbano) respecto a las variables analizadas en el presente trabajo, todo ello desde la Teoría de la Autodeterminación. La muestra estuvo formada por 202 sujetos de edades comprendidas entre 18 y los 64 años (M=35.81 y DT=13.56), de los cuales 120 eran de género femenino y 82 de género masculino. Dicha muestra procedió tanto de zonas rurales (94 sujetos) como urbanas (108 sujetos) de Extremadura, constituida por practicantes en centros deportivos. Se aplicaron cinco cuestionarios, Regulación de la Conducta del Ejercicio Físico (BREQ-3), Escala de Satisfacción de las Necesidades Psicológicas Básicas en el ejercicio (PNSE), Motivos de Actividad Física, Intencionalidad para ser Físicamente Activo y Estilo de Vida Saludable. Respecto a la diferenciación de género, los hombres obtuvieron valores más elevados en cuanto a la necesidad psicológica básica de autonomía e intención de ser físicamente activo, mientras que las mujeres lo lograron en la necesidad psicológica básica de relaciones sociales y hábitos alimenticios. En el ámbito rural, la muestra obtuvo valores más elevados en cuanto a la forma de motivación más autodeterminada, la desmotivación, motivos de prácticas y variables de estilos de vida saludable referentes al consumo de tabaco y hábitos alimenticios que el ámbito urbano. Como conclusión, se determinó que un aumento de las formas de motivación más autodeterminadas a través de la satisfacción de las necesidades psicológicas básicas favorecerá los motivos de práctica referidos al disfrute y la competencia, consiguiendo así una adherencia a la práctica deportiva y estilos de vida más saludables.Abstract. The aim of the following report is to analyze gender and area (urban vs. rural) differences regarding the variables analyzed in this study using the Self Determination Theory as a framework. The sample was composed by two hundred and two (202) individuals aged between 18 and 64 (M= 35.81 and DT= 13.56), 120 women and 82 men. This sample is composed by participants from rural (94 persons) and urban areas (108 persons) from Extremadura (South West of Spain). A criterion for inclusion was to be engaged in physical activities in gyms. We used five questionnaires: the Behavioral Regulation in Exercise Questionnaire (BREQ-3), the Psychological Need Satisfaction in Exercise Scale (PNSE), the Motives for Physical Activities Measure, the Motives for Physical Activities, and the Measurement of Intention to be Physically Active and Healthy Lifestyle Scale. Regarding gender comparison, men got higher scores in autonomy and intention of doing physical activities, which are variables of Psychological Need Satisfaction. On the other hand, women got high scores in social interaction and eating habits from the Psychological Need Satisfaction. Individuals from rural areas show higher scores than those from urban areas in self-directed motivation, demotivation, Motives for Physical Activities, and healthy lifestyle variables referred to smoking and eating habits. As a conclusion, an increase of self-directed motivation through Psychological Needs Satisfaction may enhance Motives for Physical Activities. This may lead to increased adherence to physical activity and healthier lifestyles.

scholarly journals A Statistical Portrait of Inuit with a Focus on Increasing Urbanization: Implications for Policy and Further Research

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Marika Morris
Keyword(s):  
Urban Areas ◽  
General Social Survey ◽  
Household Survey ◽  
Social Survey ◽  
National Household Survey ◽  
Employment Education ◽  
Culture And Language

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. 

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