scholarly journals Urban-Rural Consumption Inequality in China from 1988 to 2002: Evidence from Quantile Regression Decomposition

2008 ◽  
Author(s):  
Zhaopeng (Frank) Qu ◽  
Zhong Zhao
Keyword(s):  
Quantile Regression ◽  
Urban Rural ◽  
Quantile Regression Decomposition ◽  
Regression Decomposition

scholarly journals A quantile regression decomposition of urban–rural inequality in Vietnam

2007 ◽  
Vol 83 (2) ◽  
pp. 466-490 ◽  
Author(s):  
Binh T. Nguyen ◽  
James W. Albrecht ◽  
Susan B. Vroman ◽  
M. Daniel Westbrook
Keyword(s):  
Quantile Regression ◽  
Urban Rural ◽  
Quantile Regression Decomposition ◽  
Regression Decomposition

Charcoal production and household welfare in Uganda: a quantile regression approach

2013 ◽  
Vol 18 (5) ◽  
pp. 537-558 ◽  
Author(s):  
John Herbert Ainembabazi ◽  
Gerald Shively ◽  
Arild Angelsen
Keyword(s):  
Quantile Regression ◽  
Household Income ◽  
Parametric Method ◽  
Natural Forests ◽  
Charcoal Production ◽  
Regression Approach ◽  
Heterogeneous Effect ◽  
Productive Assets ◽  
Quantile Regression Decomposition ◽  
Regression Decomposition

AbstractPrevious research suggests that forest-dependent households tend to be poorer than other groups, and that extreme reliance on forest resources might constitute a poverty trap. We provide an example in which a non-timber forest product – charcoal – appears to be providing a pathway out of poverty for some rural households in Uganda. Data come from households living adjacent to natural forests, some of whom engage in charcoal production. We use a semi-parametric method to identify the determinants of participation in charcoal production and a quantile regression decomposition to measure the heterogeneous effect of participation on household income. We find that younger households and those with few productive assets are more likely to engage in charcoal production. We also show that, as a result of their participation, charcoal producers are better off than non-charcoal producers in terms of income, even though they are worse off in terms of productive assets.

The gender wage gap and the presence of foreign firms in Vietnam: evidence from unconditional quantile regression decomposition

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dao Dinh Nguyen ◽  
Xinran Zhang ◽  
Trang Huyen Nguyen
Keyword(s):  
Quantile Regression ◽  
Gender Discrimination ◽  
Gender Wage Gap ◽  
Wage Gap ◽  
Wage Distribution ◽  
Foreign Firms ◽  
Content Type ◽  
Foreign Companies ◽  
Unconditional Quantile Regression ◽  
Quantile Regression Decomposition

PurposeThe objective of this study is to estimate the gender wage gap in Vietnam and its rural and urban areas, especially with the presence of foreign firms.Design/methodology/approachThe authors use cross-sectional data from three rounds of the Vietnam Household Living Standards Survey (VHLSS 2008, 2012, and 2016) to investigate this issue. The unconditional quantile regression and Oaxaca–Blinder (OB) decomposition are used in this article.FindingsThe article finds the gender wage gap favouring men, especially in higher quantiles of the wage distribution. The gap in urban Vietnam was higher than in rural areas. The OB decomposition indicates that gender wage gap is mainly driven by gender discrimination. The differences in return to participation in foreign companies only contributed significantly and positively to such a gap in some models. It suggests that the gap in those models is affected by gender discrimination in employment opportunities in foreign companies. Regarding the endowment effect, some models provide the significantly negative impacts of foreign firms on gender wage inequality.Originality/valueThe study suggests that policies to reduce the gender wage gap should pay more attention to foreign firms, especially at higher wage classes.

scholarly journals Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method

2015 ◽  
Vol 8 (7) ◽  
pp. 116 ◽  
Author(s):  
Ramazan Fallah ◽  
Anoshirvan Kazemnejad ◽  
Farid Zayeri ◽  
Alireza Shoghli
Keyword(s):  
Health Status ◽  
Quantile Regression ◽  
Developed Countries ◽  
Regression Method ◽  
Cluster Sampling ◽  
Related Factors ◽  
Urban Rural ◽  
Rural Health Centers ◽  
The Mean ◽  
Quantile Regression Method

<p><strong>INTRODUCTION:</strong> Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province.<strong> </strong></p><p><strong>METHODS: </strong>This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software.<strong> </strong></p><p><strong>RESULTS: </strong>From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p&lt;0.05), weight and educational level of the mothers (p&lt;0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p&gt;0.05).</p><p><strong>CONCLUSION: </strong>This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.</p>

Sign in / Sign up

Export Citation Format

Share Document