scholarly journals Spatial Variation and Factors Impacting Grassland Circulation Price in Inner Mongolia, China

2018 ◽  
Vol 10 (12) ◽  
pp. 4381 ◽  
Author(s):  
Jing Zhang ◽  
Colin Brown
Keyword(s):  
Quantile Regression ◽  
Spatial Autocorrelation ◽  
Inner Mongolia ◽  
Local Market ◽  
High Demand ◽  
Grazing Land ◽  
Regression Methods ◽  
Price Distribution ◽  
Quantile Regression Analysis ◽  
The Impact

As the circulation of grassland use rights in China increases, relatively little is known about the factors that influence circulation price. This paper examines the spatial distribution of grassland circulation prices and the impact of various attributes on grassland circulation prices in Inner Mongolia Autonomous Region (IMAR). Spatial autocorrelation tests and quantile regression methods are applied to data from an online land-circulation website covering the period from January to October 2017. The spatial analysis found that grassland circulation price does vary greatly throughout IMAR but that no significant spatial autocorrelation is evident. The quantile regression analysis revealed significant, though varied, quantile effects across the price distribution indicating that local market structures, strong demand for grazing land in desert steppe, high demand of poor herders for smaller plots, and high demand of richer herders for larger plots all play an important role in determining circulation prices. These nuanced findings should enable policy makers, grassland users, and other grassland actors to better understand how grassland price is determined with respect to a range of factors across the quantiles of price as well as the spatial pattern of price characteristics. This information and understanding are a crucial step in improving grassland circulation.

scholarly journals The Impact of Education on Household Income in Rural Vietnam

2020 ◽  
Vol 8 (1) ◽  
pp. 11 ◽  
Author(s):  
Hung Van Vu
Keyword(s):  
Quantile Regression ◽  
Household Income ◽  
Living Standard ◽  
Regression Analyses ◽  
Poor Households ◽  
Quantile Regression Analysis ◽  
Research Findings ◽  
Using Data ◽  
The Impact ◽  
Positive Effect

Using data from the 2018 Vietnam Household Living Standard Survey, our study investigates the impact of education on household income in rural Vietnam. Both mean and quantile regression analyses were employed to analyze the impact of education. We found that education has a positive effect on the household income after controlling for various factors in the models. However, quantile regression analysis reveals that the effect of schooling years increases with quantiles, suggesting that education bring higher returns for richer households. We also found that households with the heads having higher qualifications or vocational education tend to earn higher income levels. Combined together, these findings imply that while education was found to increase household income, it increases income inequality in rural Vietnam. Our research findings suggest that improving the access of poor households to better education is expected to increase their income and reduce inequality in rural Vietnam.

Herding behavior in Islamic GCC stock market: a daily analysis

2018 ◽  
Vol 11 (2) ◽  
pp. 182-193 ◽  
Author(s):  
Mustapha Chaffai ◽  
Imed Medhioub
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Financial Markets ◽  
Stock Returns ◽  
Stock Markets ◽  
Content Type ◽  
Quantile Regression Analysis ◽  
Herd Behaviour ◽  
The Impact ◽  
Quantile Regression Method

Purpose This paper aims to examine the presence of herd behaviour in the Islamic Gulf Cooperation Council (GCC) stock markets following the methodology given by Chiang and Zheng (2010). Generalized auto regressive conditional heteroskedasticity (GARCH)-type models and quantile regression analysis are used and applied to daily data ranging from 3 January 2010 to 28 July 2016. Results show evidence of herd behaviour in the GCC stock markets. When the data are divided into down and up market periods, herd information is found to be statistically significant and negative during upward market periods only. These results are similar to those reported in some emerging markets such as China, Japan and Hong Kong, where stock returns perform more similarly during down market periods and differently during rising markets. Design/methodology/approach The authors present a brief literature on herd behaviour. Second, the authors provide some specificity of the GCC Islamic stock market, followed by the presentation of the methodology and the data, results and their interpretation. Findings The authors take into account the difference existing in market conditions and find evidence of herding behaviour during rising markets only for GCC markets. This result was confirmed after using the quantile regression method, as evidence of herding was observed only in highly extreme periods. Stock returns perform more similarly when market is down in Islamic GCC stock market. Research limitations/implications The research limitation consists in the fact that this work can be extended to compare the GCC stock markets with other markets in Asia such as Malaysia and Indonesia. Practical implications The principal implication consists in the fact that herding behaviour is limited in the GCC markets and Islamic finance can have an important contribution to moderate the behaviour in the financial markets. Social implications The work focusses on the role of ethics in the financial markets and their ability to reduce the impact of behavioural biases. Originality/value The paper studies the behaviour of investors in the Islamic financial markets and gives an idea about the importance of the behaviour in this particular market regarding its characteristics.

scholarly journals Extreme return, extreme volatility and investor sentiment

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 3949-3961 ◽  
Author(s):  
Xu Gong ◽  
Fenghua Wen ◽  
Zhifang He ◽  
Jia Yang ◽  
Xiaoguang Yang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Quantile Regression ◽  
Regression Model ◽  
Least Squares ◽  
Linear Regression Model ◽  
Investor Sentiment ◽  
Generalized Least Squares ◽  
Regression Methods ◽  
Leading Role ◽  
The Impact

The extreme return and extreme volatility have great influences on the investor sentiment in stock market. However, few researchers have taken the phenomenon into consideration. In this paper, we first distinguish the extreme situations from non-extreme situations. Then we use the ordinary generalized least squares and quantile regression methods to estimate a linear regression model by applying the standardized AAII, the return and volatility of SP 500. The results indicate that, except for extremely negative return, other return sequences can cause great changes in investor sentiment, and non-extreme return plays a leading role in affecting the overall American investor sentiment. Extremely positive (negative) return can rapidly improve (further reduce) the level of investor sentiment when investors encounter extremely pessimistic situations. The impact gradually decreases with improvement of the sentiment until the situation turns optimistic. In addition, we find that extreme and non-extreme volatility cannot a_ect the overall investor sentiment.

The effect of grassland transfer on herders' livestock production and grazing intensity in Inner Mongolia and Gansu, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaolong Feng ◽  
Jianjun Tang ◽  
Huanguang Qiu
Keyword(s):  
Quantile Regression ◽  
Selection Bias ◽  
Inner Mongolia ◽  
Grazing Intensity ◽  
Livestock Production ◽  
Impact Mechanism ◽  
Content Type ◽  
Self Selection ◽  
Heterogeneous Effects ◽  
The Impact

Purpose The purpose of this study is to understand the impact mechanism of grassland transfer on herders' production behaviour in pastoral areas. The impact of grassland transfer on herders' livestock production and grazing intensity is quantified.Design/methodology/approach Using the survey data collected for 356 herder households from Inner Mongolia and Gansu, China, quantile regression is employed to assess the heterogeneous effects of grassland transfer on livestock production and grazing intensity. To correct the potential self-selection bias of grassland transfer, the propensity score matching technique is used.Findings Results show that labour, percentage of livestock income and livestock stock are the main factors affecting herders' choice to transfer grassland. The positive effect of grassland transfer on livestock numbers on behalf of those who rented additional grassland is statistically significant but declines with livestock numbers. The sustainability-enhancing effect of grassland transfer on grazing intensity is significant, and the effect becomes larger amongst herder households with higher grazing intensity. The analysis on the impact mechanism shows that grassland transfer significantly promotes the adoption of sustainable grazing modes, such as rotational and seasonal rest grazing, which in turn increases herders' livestock numbers and decreases grazing intensity.Originality/value Few studies have empirically analysed the influence of grassland transfer on livestock numbers and grazing intensity. This study fills this gap by employing a quantile regression to assess the heterogeneous effects of grassland transfer on livestock numbers and grazing intensity, while accounting for self-selection bias. In addition, the authors have examined the influencing mechanisms under which grassland transfer impacts on livestock numbers and grazing intensity.

scholarly journals How Do Workers Sustain COVID-induced Labour Market Shock: Evidence from the Indian State of Kerala

2021 ◽  
pp. 001946622110238
Author(s):  
Muhammed Refeque ◽  
P Azad ◽  
PK Sujathan
Keyword(s):  
Human Capital ◽  
Quantile Regression ◽  
Labour Market ◽  
Empirical Analysis ◽  
Jel Codes ◽  
Explanatory Variables ◽  
Regression Methods ◽  
Labour Market Participation ◽  
Indian State ◽  
The Impact

This article is an empirical analysis of the resilience of workers over the COVID-hit labour market in the Indian state of Kerala. Quantile regression methods are used to ascertain the impact of COVID-19 on the labour market. This method is more advantageous than the traditional OLS method as it does not presume a constant effect of explanatory variables on the distribution of dependent variable. Evidences convey that all the five categories of workers under study were disproportionately buffeted by the pandemic. However, the factors education and experience were found to have a stabilising effect on the rate of labour market participation. The article pitches for a more responsive and responsible role that the State can deliver to embolden and reinforce human capital so that the pandemic like COVID-19 can at best be averted. JEL Codes: E24, H12, I15, J64

scholarly journals Estimating Impact of Austerity policies in COVID-19 fatality rates: Examining the dynamics of economic policy and Case Fatality Rates (CFR) of COVID-19 in OECD countries

2020 ◽  
Author(s):  
Dawa Sherpa
Keyword(s):  
Quantile Regression ◽  
Case Fatality ◽  
Oecd Countries ◽  
Regression Method ◽  
Health Policies ◽  
Health Crisis ◽  
Parametric Regression ◽  
Public Health Crisis ◽  
Quantile Regression Analysis ◽  
The Impact

AbstractThe paper will attempt to estimate factors which determine the variability of case fatality rates of COVID-19 across OECD countries in the recent time. The objective of the paper is to estimate the impact of government health policies on fatality rates (Case fatality rates) of COVID-19 in_OECD countries while controlling for other demographic and economic characteristics. The analysis is done using non-parametric regression method, i.e. Quantile regression. The result from quantile regression analysis shows that a policy of Austerity (health expenditure cuts) significantly increases the mortality rates of COVID-19 in OECD countries. The policy implication of the study is the need for a robust public-funded health system with wider accessibility to deal with major public health crisis like COVID-19 pandemic.

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