scholarly journals Economic Assessment and Community Management of Prosopis juliflora Invasion in Sweimeh Village, Jordan

2020 ◽  
Vol 12 (20) ◽  
pp. 8327
Author(s):  
Amani Al-Assaf ◽  
Maher J. Tadros ◽  
Salsabeel Al-Shishany ◽  
Stephanie Stewart ◽  
Mohammad Majdalawi ◽  
...  
Keyword(s):  
Negative Impact ◽  
Binary Logistic Regression ◽  
Economic Assessment ◽  
Prosopis Juliflora ◽  
Jordan Valley ◽  
Binary Logistic Regression Model ◽  
Policy Makers ◽  
Management Plans ◽  
Use Values ◽  
And Control

Invasions by invasive alien species (IAS) are recognized as one of the largest threats to earth’s ecosystem services and represent rapidly growing economic costs as they damage local ecosystems and force surrounding communities to divert resources towards IAS management and control. The study objectives were to assess the economic impacts of a Prosopis juliflora invasion in Jordan and gauge community preferences for management plans. The study was conducted in Sweimeh, Jordan Valley using a combination of focus groups and randomized interviews with 203 local households. Direct-use values for products derived from P. juliflora and direct costs owing to P. juliflora’s presence have been calculated. A binary logistic regression model was then developed to predict the households’ preferences between two policy responses: P. juliflora management or complete eradication. The results revealed the dualistic role of P. juliflora in household livelihoods: it was widely used for firewood, fodder, and charcoal offering benefits valued at JOD 2165 per household/year (JOD 1 = USD 0.71). At the same time, the invasion reduced household welfare by taking over arable lands and injuring humans and animals. Consequently, the income lost as a result of the invasion was estimated by JOD 1410.5 per household/year. As a result, two-thirds of respondents choose the option of P.juliflora invasion management. Only respondents’ monthly income and perception of P. juliflora’s impact on the prevention of soil erosion were significant predictors of respondents’ preferences for the management plans. In conclusion, more coordinated responses between policy makers, institutions, and local communities are required to mitigate the negative impact of P. juliflora invasion.

scholarly journals COLLATERAL REQUIREMENTS FOR SME LOANS: EMPIRICAL EVIDENCE FROM THE VISEGRAD COUNTRIES

2017 ◽  
Vol 18 (4) ◽  
pp. 650-675 ◽  
Author(s):  
Ashiqur RAHMAN ◽  
Jaroslav BELAS ◽  
Tomas KLIESTIK ◽  
Ladislav TYLL
Keyword(s):  
Slovak Republic ◽  
Small And Medium Enterprises ◽  
Binary Logistic Regression ◽  
Business Environment ◽  
Binary Logistic Regression Model ◽  
Data Set ◽  
Policy Makers ◽  
Medium Enterprises ◽  
Bank Concentration ◽  
Visegrád Countries

The purpose of this paper is to examine the determinants of collateral for small and medium enterprises (smes) in the context of Visegrad countries: Czech Republic, Slovak Republic, Hungary and Poland. The data set for this paper was obtained from the Business Environment and Enterprise Performance Survey (BEEPS), which was conducted by the World Bank and the European Bank for Reconstruction and Development (EBRD) from 2012–2014. A binary logistic regression model with different specifications was employed to examine the effect of independent variables on the incidence of collateral. The results show that risky borrowers need to pledge collateral and the reduction of asymmetric information can lower the incidence of collateral for smes. Moreover, we find that female borrowers are more likely to pledge collateral than male borrowers are. The results also suggest that loans with a longer maturity are more likely to be collateralized than short-term loans. We find evidence that bank-borrower proximity can alleviate the incidence of collateral whereas bank concentration may increase collateral requirements. Policy makers may consider these results to implement policies that can promote bank competition and can lower collateral requirements for female borrowers. The paper contributes to the ongoing debate on the determinants of collateral.

Democracy under Fire: Voter Confusion and Influences in Colorado's Anti-Affirmative Action Initiative

2013 ◽  
Vol 83 (3) ◽  
pp. 432-462 ◽  
Author(s):  
Amy Farley ◽  
Matthew Gaertner ◽  
Michele Moses
Keyword(s):  
Affirmative Action ◽  
Direct Democracy ◽  
Voting Behavior ◽  
Negative Impact ◽  
Binary Logistic Regression ◽  
Ballot Initiatives ◽  
Education Policies ◽  
Binary Logistic Regression Model ◽  
University Of Texas ◽  
Previous Scholarship

In this article, Amy N. Farley, Matthew N. Gaertner, and Michele S. Moses examine the use of ballot initiatives as a particularly attractive form of direct democracy for opponents of affirmative action in higher education. Building on previous scholarship, the authors question whether anti-affirmative ballot initiatives validly reflect voters’ attitudes toward affirmative action. The authors examine the case of Colorado's Amendment 46, an anti-affirmative action ballot initiative. They investigate the language of the initiative itself, as well as voters’ perceptions of and confusion around its intent, and the factors that influenced voting behavior. They employ item response theory to estimate voters’ attitudes toward affirmative action. The authors then describe the prevalence of voter confusion around the initiative's intent. Finally, employing a binary logistic regression model, they analyze survey data to determine which factors influenced voting behavior. They find that the initiative's language was successful at confusing voters who intended to support affirmative action. Following the U.S. Supreme Court's recent decision in Fisher v. University of Texas and in anticipation of its decision in Schuette v. Coalition to Defend Affirmative Action, the authors call for greater scrutiny with regard to the use of initiatives to craft education policies that have a disproportionately negative impact on members of disadvantaged populations.

scholarly journals Research on the Influence of Brand Certification on Farmers’ Professional Cooperatives Participating in E-commerce

2021 ◽  
Vol 235 ◽  
pp. 01044
Author(s):  
Guoqiang Liu ◽  
Bizhong Zhang ◽  
Xinhong Fu ◽  
Ruixin Zhang
Keyword(s):  
Negative Impact ◽  
Positive Impact ◽  
Binary Logistic Regression ◽  
Agricultural Products ◽  
Agricultural Product ◽  
Binary Logistic Regression Model ◽  
Positive Role ◽  
Local Conditions ◽  
Policy Suggestions ◽  
Product Sales

Based on the microscopic survey data of 100 vegetable cooperatives in Sichuan Province, this paper empirically analyzes the influence of brand certification on cooperatives participating in the ecommerce by binary logistic regression model. The results show that the proportion of Sichuan vegetable cooperatives participating in the e-commerce is generally lower, which needs further improvement. Brand certification has a positive role in promoting cooperatives to participate in the e-commerce, with a marginal contribution of 19.7%. In addition, government sales support has a positive impact on the cooperative ecommerce, which is an important guarantee for promoting cooperatives to participate in the e-commerce. While the difficulty of agricultural product sales has a negative impact on the cooperative e-commerce, and the more difficult the agricultural products are sold, the higher the probability that the cooperative will participate in the e-commerce. Thus, this article puts forward policy suggestions such as actively promoting cooperatives to participate in brand certification, promoting cooperatives to participate in the e-commerce according to local conditions and strengthening government sales support.

scholarly journals Parenting Styles and Alcohol Use in Brazilian Males

2020 ◽  
Vol 30 ◽  
Author(s):  
Elke do Pillar Pinheiro ◽  
Paula Inez Cunha Gomide
Keyword(s):  
Alcohol Use ◽  
Parenting Styles ◽  
Parenting Practices ◽  
Binary Logistic Regression ◽  
Adult Males ◽  
Control Groups ◽  
Binary Logistic Regression Model ◽  
Significant Difference ◽  
History Of ◽  
And Control

Abstract Parenting styles have been identified as some of the most important factors of risk for and protection against alcohol use among adolescents. This study aimed at comparing maternal and paternal parenting styles in groups of adult alcoholic and non-alcoholic men. Participants were 260 adult males, half of whom had been diagnosed with alcoholism whilst the others did not have a history of such disorder. The comparison between the alcoholic and control groups showed a statistically significant difference (p < 0.001) in relation to both paternal and maternal parenting practices. The binary logistic regression model containing paternal PSI, age, education and maternal PSI (χ2 = 5.224; p = 0.022; R2Nagelkerke = 0.801) showed that paternal PSI was the main predictor of alcoholism.

scholarly journals Adoption of Conservation Tillage on the Semi-Arid Loess Plateau of Northwest China

2018 ◽  
Vol 10 (8) ◽  
pp. 2621 ◽  
Author(s):  
Qingfeng Han ◽  
Kadambot Siddique ◽  
Fengmin Li
Keyword(s):  
Loess Plateau ◽  
Negative Impact ◽  
Conservation Tillage ◽  
Binary Logistic Regression ◽  
Farming Systems ◽  
Northwest China ◽  
Binary Logistic Regression Model ◽  
Positive Effects ◽  
The Government ◽  
Semi Arid

Conservation tillage is an important approach to prevent water loss and soil erosion and promote soil fertility that has been adopted widely throughout the world. However, despite promotion of the benefits of conservation tillage, obstacles are still encountered in some regions. A survey of 385 farmer households in the semi-arid Loess Plateau of China was conducted to assess the adoption of conservation tillage (ACT). This investigation was located in two counties that have run conservation tillage demonstrations with wheat for at least eight years. A binary logistic regression model was used to quantify the factors determining whether or not farmers adopt conservation tillage. Farmer’s education level, the influence of training, and field demonstrations by agricultural departments had significant positive effects on ACT. Although the adoption rate of conservation tillage in this paper was very high (89%), farmers were reluctant to continue practicing conservation tillage based on their experiences, which is contrary to the expectations of the government. The area available for planting winter wheat and the number of arable plots per household also had significant positive effects on ACT. However, the total cultivated area of land per household had a significant negative impact on ACT. Farmer awareness of conservation tillage technology, the distance from a farmer’s house to the nearest agricultural market, and the size of the active labor force in the family had significant negative impacts on ACT. These results will help in the development of more effective and targeted policies to improve the sustainability of farming systems on the semi-arid Loess Plateau.

Credit constraints and Rural Migration: Evidence from Six Villages in Uttar Pradesh

2018 ◽  
Vol 15 (3) ◽  
pp. 389-398
Author(s):  
Ruchi Singh
Keyword(s):  
Credit Constraints ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Male Migration ◽  
Rural Economies ◽  
And Migration ◽  
The Relationship ◽  
The Empirical Analysis

Rural economies in developing countries are often characterized by credit constraints. Although few attempts have been made to understand the trends and patterns of male out-migration from Uttar Pradesh (UP), there is dearth of literature on the linkage between credit accessibility and male migration in rural Uttar Pradesh. The present study tries to fill this gap. The objective of this study is to assess the role of credit accessibility in determining rural male migration. A primary survey of 370 households was conducted in six villages of Jaunpur district in Uttar Pradesh. Simple statistical tools and a binary logistic regression model were used for analyzing the data. The result of the empirical analysis shows that various sources of credit and accessibility to them play a very important role in male migration in rural Uttar Pradesh. The study also found that the relationship between credit constraints and migration varies across various social groups in UP.

The Frustration Regulation Journal: A Reflective Framework for Educators

Relay Journal ◽  
2019 ◽  
Author(s):  
Sam Morris
Keyword(s):  
Emotion Regulation ◽  
Process Model ◽  
Negative Impact ◽  
Language Education ◽  
Short Article ◽  
Language Classroom ◽  
As Stress ◽  
And Control ◽  
Important System ◽  
Behavioural Strategies

Teachers and advisors involved in the emotional business of language education feel frustrated from time to time, and if such emotions are not managed healthily, they may lead to negative outcomes such as stress and burnout. One important system for taking control of frustration is emotion regulation, the cognitive and behavioural strategies through which individuals manage their emotions. In this short article, I define frustration and discuss its negative impact on the language classroom. I then introduce a structured reflective journaling tool, built upon Gross’s Process model of emotion regulation (Gross, 2014, 2015) which may help teachers and advisors develop greater awareness and control over experiences of frustration.

Prevalence of facemask use among general public when visiting wet market during Covid-19 pandemic: An observational study. (Preprint)

2020 ◽  
Author(s):  
Gobi Hariyanayagam ◽  
Sera Selvanthan Sundram Gunasekaran ◽  
Shargunan Selvanthan Gunasekaran ◽  
Nur Syafina Insyirah Zaimi ◽  
Nor Amirah Abdul Halim
Keyword(s):  
High Risk ◽  
General Population ◽  
Binary Logistic Regression ◽  
Final Analysis ◽  
High Risk Population ◽  
Binary Logistic Regression Model ◽  
Chi Square ◽  
Hygiene Measures ◽  
Wet Market ◽  
Medical Grade

BACKGROUND In late December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was epidemiologically linked to seafood and wet animal market in Wuhan, Hubei, China. This event has instigated negative stigma among the general population to view the wet market as a high-risk location for potential transmission of coronavirus. OBJECTIVE This study investigated the prevalence of facemask use among general population visiting the wet market as well as factors contributing to unacceptable facemask practice. Setting The visitors to a district wet market selling range of live or freshly slaughtered animals during COVID-19 pandemic outbreak was observed for facemask practice. METHODS All Individuals visiting the market were observed for the type, category and practice of wearing facemas. Subjects were categorized into two groups of acceptable and unacceptable facemask practice. The Pearson chi-square was used to test for differences in investigated variables in the univariate setting and Binary Logistic regression model was used in the multivariate setting. Main outcome measure Prevalence, acceptance practice and odds ratio of unacceptance of facemask use. RESULTS Among 1697 individuals included in the final analysis, 1687 (99.7%) was observed wearing facemask with 1338 (78.8%) using medical-grade facemask. Among them, 1615 (95.7%) individuals facemask practice was acceptable while the reaming 72 (4.3%) individuals were observed with unacceptable facemask practice. Individuals using medical-grade facemask and high-risk age group are 6.4 times (OR=6.40; 95% CI, 2.00-20.43; p=.002) and 2.06 times practice (OR=2.06; 95% CI, 1.08-3.94; p=.028) more likely to have unacceptable facemask practice respectively. CONCLUSIONS High saturation of facemask among the general population is an adequate indicator of public hygiene measures strategy which can help to mitigate the COVID-19 epidemic impact. Alarmingly, the unacceptable facemask practice among high-risk population raises the need for a targeted approach by healthcare authorities to ensure satisfactory facemask use.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

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