scholarly journals Labor market and crisis: an analysis of sectoral segmentation in Brazilian rural

2022 ◽  
Vol 60 (4) ◽  
Author(s):  
Gabriela Gomes Mantovani ◽  
Jefferson Andronio Ramundo Staduto ◽  
Carlos Alves do Nascimento
Keyword(s):  
Labor Market ◽  
Rural Areas ◽  
Bias Correction ◽  
Explanatory Power ◽  
Sample Selection ◽  
Household Survey ◽  
Sample Selection Bias ◽  
Agricultural Activities ◽  
The Difference ◽  
Counterfactual Decomposition

Abstract: The article aims to analyze which factors contributed to the inequality across income distribution of Brazilian workers in rural areas, occupied in agricultural and non-agricultural activities. Quantile regression with sample selection bias correction and counterfactual decomposition of income by quantiles were applied, using the microdata from the National Continuous Household Survey (PNAD-C) for the years 2012 and 2019. The results showed that there is income inequality favorable to workers occupied in non-agricultural activities concerning agricultural activities, which is intensive for those with lower incomes, as well as for those with high incomes. The presence of sectorial segmentation was also confirmed, of which the largest portion in 2012 corresponds to the labor market duality. However in 2019, in lower quantiles the segmentation obtained greater explanatory power for the difference in income between the groups, while in higher quantiles the theory of human capital prevailed.

Face Hallucination Based On Sample Selection Bias Correction

2012 ◽  
Vol 4 (5) ◽  
pp. 91-98
Author(s):  
Tao Lu ◽  
Ruimin Hu ◽  
Zhen Han ◽  
Junjun Jiang ◽  
Jun Chang
Keyword(s):  
Selection Bias ◽  
Bias Correction ◽  
Sample Selection ◽  
Sample Selection Bias ◽  
Face Hallucination

scholarly journals Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Risk Analysis ◽  
2020 ◽  
Author(s):  
Dennis Wagenaar ◽  
Tiaravanni Hermawan ◽  
Marc J. C. Homberg ◽  
Jeroen C. J. H. Aerts ◽  
Heidi Kreibich ◽  
...  
Keyword(s):  
Selection Bias ◽  
Bias Correction ◽  
Sample Selection ◽  
Data Driven ◽  
Sample Selection Bias ◽  
Damage Models

scholarly journals Pro-rural Policies, Income, and Inequality: Evaluating a Cash-for-Work Program in Rural China

2014 ◽  
Vol 13 (3) ◽  
pp. 87-114 ◽  
Author(s):  
Yu Chen ◽  
Sylvie Démurger
Keyword(s):  
Rural Areas ◽  
Household Income ◽  
Rural China ◽  
Household Survey ◽  
Crowding Out ◽  
Agricultural Activities ◽  
Mountainous Areas ◽  
Work Program ◽  
The Past ◽  
Household Survey Data

Despite the dramatic reduction of poverty in China over the past 35 years, poverty has not been fully eradicated in rural areas and, in the context of growing inequalities, it remains a national concern. This paper examines a local cash-for-work program launched in mountainous areas of the Beijing municipality in December 2004, with a view to understanding both the challenges and achievements of pro-poor programs in China. Using original household survey data, we first highlight the fairly good targeting performance of the program towards the local poor. Second, participation equations provide evidence of increasing local income without crowding out local agricultural activities. Finally, a decomposition of household income inequality by source highlights the strongly equalizing effect of the program on peasants' income.

scholarly journals Does the Labor Market Structure Explain Differences in Poverty in Rural Punjab?

2008 ◽  
Vol 13 (Special Edition) ◽  
pp. 139-162 ◽  
Author(s):  
Rashid Amjad ◽  
G. M. Arif ◽  
Usman Mustafa
Keyword(s):  
Labor Market ◽  
Market Structure ◽  
Rural Areas ◽  
Poverty Reduction ◽  
Agricultural Sector ◽  
Household Survey ◽  
Industrial Sector ◽  
Good Opportunity ◽  
Low Intensity ◽  
Poverty Levels

The main focus of this study is Rural Punjab and it contributes to regional poverty research in two ways; first, using a more recent household survey data, carried out in August 2007 by the Pakistan Institute of Development Economics (PIDE), it provides fresh poverty estimates for the rural areas of the Punjab. Second, the poverty differential across the agroclimatic zones of Punjab have been explained by urbanization, overseas migration and the labor market structure operating in these zones. This study shows four major factors that explain inequalities in poverty levels. First, the rural areas of two zones, barani and rice/wheat, are well integrated with urban settings. This integration has allowed their rural populations to work in the industrial sector of Central Punjab and the services sector in North Punjab primarily Rawalpindi and Islamabad. Second, the belt from Lahore to Attock in the Punjab has benefited the most from overseas migration. The flow of remittances has helped in reducing poverty levels. Third, the cotton/wheat and low intensity zone still largely depend for employment on the agricultural sector while this dependency is very low in the barani zone, which has good opportunity to seek job opportunities for its labor force in the armed services and government departments. Finally, demographic and social factors including education are less favorable in the cotton/wheat and low intensity zones which negatively impacts on a breakthrough in poverty reduction.

scholarly journals Rural Transformation and Labor Market Outcomes among Rural Youths in Nigeria

2021 ◽  
Vol 13 (24) ◽  
pp. 13794
Author(s):  
Adedoyin Mistura Rufai ◽  
Adebayo Isaiah Ogunniyi ◽  
Kabir Kayode Salman ◽  
Mutiat Bukola Salawu ◽  
Abiodun Olusola Omotayo
Keyword(s):  
Labor Market ◽  
Rural Areas ◽  
Unobserved Heterogeneity ◽  
Labor Market Outcomes ◽  
Household Survey ◽  
Special Focus ◽  
Urban Migration ◽  
Market Outcomes ◽  
Rural Transformation ◽  
Positive Effects

In Nigeria, unemployment in rural areas translates to economic problems, such as high levels of rural–urban migration. Interventions aimed at promoting rural transformation and development are designed to generate employment by promoting the growth of sectors such as manufacturing and services in rural areas. In this study, the General Household Survey (GHS) panel data for the post-planting and post-harvest periods of the 2011/2012 and 2015/2016 cropping seasons for Nigeria was used to investigate developments in rural areas in Nigeria between 2011 and 2015, and identified how these developments influenced labor market outcomes among rural youths. Fixed effect models were employed to control for unobserved heterogeneity that may exist because of the different years in the data used. Key levers of sustainable social and economic development, such as access to finance, health services, markets, and infrastructure such as electricity, were considered. The empirical results from the study revealed that being educated as well as having access to infrastructure and information had positive effects on the number of youths that took up wage/salary employment in the rural areas. The study concluded that the diversification of youths into other sectors would have higher growth effects on the development of rural areas, as they can invest more in agriculture, while also reducing the level of dependence on the sector. The study recommends an increase in budgetary allocations for education and rural development projects, with a special focus on electricity and financial institutions, while increasing access to information on available job opportunities.

scholarly journals Sample Selection Bias Correction Theory

2008 ◽  
pp. 38-53 ◽  
Author(s):  
Corinna Cortes ◽  
Mehryar Mohri ◽  
Michael Riley ◽  
Afshin Rostamizadeh
Keyword(s):  
Selection Bias ◽  
Bias Correction ◽  
Sample Selection ◽  
Sample Selection Bias

scholarly journals Demographic and labor market transformations in rural areas of Chile

2017 ◽  
Vol 66 (2) ◽  
Author(s):  
Carlos Rodrigues Garcés ◽  
María Julia Fawaz Yissi ◽  
Johana Andrea Muñoz Soto
Keyword(s):  
Labor Market ◽  
Rural Areas ◽  
Rural Population ◽  
Agricultural Activities ◽  
Demographic Trends ◽  
Rural Labor ◽  
Ongoing Process ◽  
Salaried Workers ◽  
Market Restructuring

Based on the information provided by the Encuesta de Caracterización Socioeconómica Nacional (CASEN) (National Socioeconomic Characterization Survey) of 1990 and 2013, the reconfigurations of the Chilean countryside are analyzed in terms of their demographic trends and labor market restructuring. An ongoing process of depopulation and aging of the rural population is found. Agricultural activities of the rural labor market become less relevant both in terms of jobs and income, showing a strong process of deagrarianisation, salaried workers and feminization of the labor market.

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