Determinants of illegal migration from North Africa to Southern Europe

2016 ◽  
Vol 13 (3) ◽  
pp. 455-467 ◽  
Author(s):  
Amany Hassan Abdel-karim
Keyword(s):  
Logistic Regression ◽  
North Africa ◽  
Logistic Regression Model ◽  
Southern Europe ◽  
Illegal Migration ◽  
Financial Situation ◽  
Level Of Education ◽  
And Migration ◽  
High Level ◽  
Migration Network

This study focuses on determining the effects of demographic, socioeconomic and migration network factors on illegal migration from North Africa to Southern Europe using logistic regression model. The results indicated that migrants who thought it is easier to find a job in destination countries, had job before migration, had high level of financial situation before migration and had high level of education were more likely to migrate legally. However, migrants who had children before migration and migrated with others were more likely to migrate illegally. These findings can be useful for migration legislations in both sending and receiving countries.

scholarly journals Assessment of factors that affect the bankruptcy of an organization

2020 ◽  
Vol 19 (1) ◽  
pp. 57-71
Author(s):  
Irina Vinnikova
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Timely Manner ◽  
Financial Situation ◽  
Significant Factors

Analysis of factors that influence the company's bankruptcy is one of the main tasks for companies that want to assess their financial situation and prevent possible bankruptcy in a timely manner. This article analyzes the factors that affect the company's bankruptcy. A logistic regression model was constructed based on the indicators of both bankrupt and financially stable companies. During the development of the model, significant factors were identified for predicting the bankruptcy of the organization. The results will be useful both for future bankruptcy researchers and for those companies that want to assess their financial situation.

scholarly journals Determinan Keputusan Melakukan Migrasi Ulang-Alik

2018 ◽  
Vol 1 (3) ◽  
pp. 242-251
Author(s):  
Rifqi Nur Fahmy
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Analysis Method ◽  
Binary Logistic Regression Model ◽  
Level Of Education ◽  
Independent Variables ◽  
Variable Level

The aim of this research is to analyze the influence of dependent variable of family dependent, education level, age, marital status, and distance partially to workforce’s decision to migrate from Surakarta to Karanganyar Regency. This research used binary logistic regression analysis method. The sample in this research is 100 respondents. The result of binary logistic regression model analysis in this research shows that from five independent variables, there are two variables that have significant effect on workforce’s decision to do the commuter migration that is dependent variable of family and marital status. While the variable level of education, age, and distance have no effect on workforce’s decisions to do the commuter migration. Tujuan dari penelitian ini adalah untuk menganalisis pengaruh variabel dependen dependen keluarga, tingkat pendidikan, usia, status perkawinan, dan jarak secara parsial terhadap keputusan tenaga kerja untuk bermigrasi dari Surakarta ke Kabupaten Karanganyar. Penelitian ini menggunakan metode analisis regresi logistik biner. Sampel dalam penelitian ini adalah 100 responden. Hasil analisis model regresi logistik biner dalam penelitian ini menunjukkan bahwa dari lima variabel independen, ada dua variabel yang berpengaruh signifikan terhadap keputusan angkatan kerja untuk melakukan migrasi komuter yang merupakan variabel dependen keluarga dan status perkawinan. Sedangkan tingkat variabel pendidikan, usia, dan jarak tidak berpengaruh pada keputusan tenaga kerja untuk melakukan migrasi komuter.  

Revealing images as Facebook profile pictures: Influences of demographics and relationship status

2017 ◽  
Vol 45 (6) ◽  
pp. 987-997 ◽  
Author(s):  
Amir Hetsroni ◽  
Dror A. Guldin
Keyword(s):  
Logistic Regression ◽  
Romantic Relationship ◽  
Logistic Regression Model ◽  
Relationship Status ◽  
Multiple Logistic Regression ◽  
Self Presentation ◽  
Level Of Education ◽  
Younger Age ◽  
The Impact ◽  
Profile Pictures

In this study, we examined the impact of demographics and relationship status on posting a revealing picture of oneself as a profile picture on Facebook. We randomly sampled and coded 1,000 profiles of Israeli Facebook users ranging in age between 18 and 61 years. Over 40% of the profiles showed at least 1 picture of the user dressed in a skimpy outfit. Results of a multiple logistic regression model indicated that younger age, a lower level of education, and not being engaged in a committed romantic relationship were significant predictors of the posting of these pictures. Further, gender alone was not a significant predictor, but the interaction of gender and level of education was. Specifically, women with a high-schoollevel education posted revealing pictures of themselves more often than did men with a similar level of education. We analyzed our results in light of Goffman's theory of self-presentation.

EDUCATION LEVEL AND ADOPTION OF PROCESS INNOVATION IN THE DAIRY SECTOR OF ZIMBABWE

2021 ◽  
Vol 5 (9) ◽  
Author(s):  
Alpha Marlvin Manjera ◽  
Alpha Marlvin Manjera
Keyword(s):  
Logistic Regression ◽  
Change Management ◽  
Logistic Regression Model ◽  
Process Innovation ◽  
Education Level ◽  
Research Issue ◽  
Dairy Farmers ◽  
Level Of Education ◽  
Process Innovations ◽  
New Process

This paper, seek to assess factors that are hindering diffusion of process innovation under the Zimbabwean dairy industry. The paper utilized 400 smallmedium scale dairy farmers in Zimbabwe who are registered under Zimbabwe Association of Dairy Farmers (ZADF). The rationale behind the research issue is that Zimbabwean dairy sector has failed to adopt process innovations such as e-marketing and e-extension. The paper adopted a binomial logistic regression model and majority of the dairy farmers in Zimbabwe have not acquired any form of education and based on such evidence, level of education has affected the level of adoption of process innovations such as e-marketing and e-extension. The research recommends the dairy sector to introduce nonformal courses and trainings on change management and innovations prior to introduction of new process innovations.

scholarly journals Association of MAOA-uVNTR gene polymorphism with hostility in an open population of males aged 45-64 in Russia / Siberia (international program: WHO «MONICA-psychosocial», «HAPIEE»)

2020 ◽  
pp. 39-44
Author(s):  
V. V. Gafarov ◽  
E. A. Gromova ◽  
D. O. Panov ◽  
I. V. Gagulin ◽  
V. N. Maksimov ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Gene Polymorphism ◽  
Representative Sample ◽  
Logistic Regression Model ◽  
Random Number ◽  
International Program ◽  
Maoa Gene ◽  
Open Population ◽  
Active Allele ◽  
High Level

Objective: to study the association of hostility with high and low-active variants of the MAOA gene in an open population of men 45-64 years old. Using the methods proposed by the WHO International Program “MONICA-psychosocial” and “HAPIEE”, a representative sample of men aged 45–64 years old (n = 781 men, average age was 56.48 ± 0.2 years) in 2003-2005. All respondents independently completed a questionnaire on hostility. From the surveyed sample, using the random number method, 156 men were selected who were genotyped for MAOA-uVNTR polymorphism. It was approved that the level of hostility in the population of men was 60.3%. It was revealed that among persons with low-active alleles of the MAOA-L gene (allele 2 and 3) a high level of hostility was more common — 50.9%. The results of building a logistic regression model showed that the presence of low-active alleles (2; 3) of the MAOA gene increases the likelihood of hostility OR = 2,103 (95% CI 1,137-3,889, p = 0.018). The results obtained allow us to conclude that the low-active allele of the MAOA-L gene is associated with hostility.

scholarly journals Faktor-faktor Determinan Kemandirian Wanita dalam Berwirausaha untuk Wilayah Banten

2019 ◽  
Vol 3 (2) ◽  
pp. 257-267
Author(s):  
Arif Surahman ◽  
Chandra Fitra Arifianto ◽  
Andriyani Hapsari
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Influencing Factors ◽  
Women Entrepreneurs ◽  
Binary Logistic Regression ◽  
George Washington ◽  
Women Entrepreneurship ◽  
Level Of Education ◽  
Access To Technology ◽  
High Level

Abstrak Penelitian ini berupaya untuk mengukur kemandirian wirausahawan wanita dengan melihat kepada faktor-faktor yang mempengaruhinya, antara lain berupa: akses terhadap teknologi,  pengalaman pernah kerja, kepemilikan anak, jumlah modal awal, dan tingkat pendidikan yang tinggi. Sampel yang diambil sebanyak 193 wirausahawan wanita yang memiliki usaha di wilayah provinsi Banten, dimana peneliti memberikan quesioner yang dijawab oleh responden. Metode untuk analisis data yang digunakan ialah model regresi binary logistic. Hasil penelitian ini menunjukkan hasil yang sama dengan yang ditemukan oleh Chaganti (1986), Universitas George Washington dan Riza, Setianingsih dan Chandra (2016) yang menemukan bahwa pengalaman kerja pada tempat sebelumnya dapat meningkatkan peluang seorang wirausahawan wanita menjadi mandiri. Selain itu, akses teknologi sebagai bagian dari perekonomian digital juga ditemukan bisa mendorong peluang seorang wirausahawan wanita menjadi mandiri.  Abstract This research is trying to measure the independence of women entrepreneurship by looking at various influencing factors such as Access to technology, working experience, owning a child, the amount of first capital and high level of education. The sample that is being used for this research is 193 respondent who lives in Banten. Questionnaires are used as an instrument for this research. The method of data analysis that is being used in this research are Binary Logistic Regression. The results from this research have shown the same result from findings of Chaganti (1986), and Riza, Setianingsih and Chandra (2016) which concluded that working experience can increase the probability for an independent women entrepreneurs. Moreover, access to technology as a part of the digital economy also has been proven can motivate the odds of women entrepreneur to become independent.    

scholarly journals Modeling Infant Mortality Risk Factors using Logistic Regression Model and Spatial Analysis in Kenya

2021 ◽  
pp. 21-33
Author(s):  
Erick Cheruiyot Kirui ◽  
Elphas Luchemo ◽  
Ayubu Anapapa
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Infant Mortality ◽  
Regression Model ◽  
Spatial Variation ◽  
Mortality Risk ◽  
Logistic Regression Model ◽  
Important Indicator ◽  
Weather Patterns ◽  
High Level

Globally, infant mortality is used as an important indicator for healthcare status hence an important tool for evaluation and planning of public health strategies. Despite of numerous interventions by governments aimed at reducing infant mortality, high rates are still reported in Kenya. A lot of resources are channeled towards its control leading to low productivity hence impacting the household economic welfare and national GD. The specific objective was to establish risk factors and the spatial variation of infant mortality in Kenya by analyzing the 2014 Kenya Demographic Health Survey data. A fully Bayesian paradigm and logistic regression model were used to determine infant mortality risk factors and spatial variation in Kenya. Demographic, socioeconomic and environmental factors were found to have significant effect on infant mortality. Counties from the northern parts of Kenya, Rift Valley, Central, Eastern, Nyanza, Coastal and Western parts of Kenya showed a high level of infant deaths. Infant mortality is high in arid and semi-arid areas and coastal areas due to high prevalence of infectious diseases and inadequate water supply, health facilities and low education levels. Infant mortality varies significantly across regions in Kenya due to cultural activities, and weather patterns hence exists spatial autocorrelation among neighboring regions.

scholarly journals Perceptions of grasscutter (Thryonomys swinderianus) farmers on production technologies in the Agona West Municipality, Central Region - Ghana

2019 ◽  
Vol 54 (1) ◽  
pp. 47-55
Author(s):  
B. Y. Folitse ◽  
S. A. Manteaw
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Central Region ◽  
Value Chain ◽  
Logistic Regression Model ◽  
Participatory Approach ◽  
Level Of Education ◽  
Thryonomys Swinderianus ◽  
Production Technologies ◽  
The Impact

The study sought to assess the dynamics of grasscutter (Thryonomys swinderianus) Produc­tion Technologies being used in the Agona West Municipality in the Central Region of Ghana. Farmers were selected from 20 communities with the help of staff from the Department of Ag­riculture and were interviewed using structured questionnaires. The results revealed that though the grasscutter farmers were varied in their views, the dissemination of grasscutter technologies through video in the study area was deemed to be effective. The results of the Logistic regression model (R-Square values of 0.119 and 0.158) showed that the impact of the dissemination pro­gramme on the livelihoods of farmers who had adopted the grasscutter production technologies was best predicted by age, household size and level of education of farmers. The overall mean, 3.99 showed that the livelihoods of the farmers had highly been improved. The paper makes a strong case for a more participatory approach anchored on inclusive problem identification and formulation of research solution that will further ensure that problems that are targeted by re­search emanate from farmers. This is expected to ensure a more effective extension of research technologies to farmers and other actors along the grasscutter value chain in the area. Keywords: Grasscutter; Production Technologies; Agona West Municipality; Central Region; Ghana

Study on financial risk prediction of enterprises based on logistic regression

2021 ◽  
pp. 1-7
Author(s):  
Qiaoyun Qi
Keyword(s):  
Logistic Regression ◽  
Financial Risk ◽  
Logistic Regression Model ◽  
Great Influence ◽  
Financial Indicators ◽  
Accuracy Rate ◽  
Financial Situation ◽  
Good Market ◽  
A Company

Financial risk has a great influence on the development of enterprises, and the prediction of financial risk can help enterprises to treat risks early. In order to realize the prediction of enterprise financial risk, find the risk as early as possible and make a response as soon as possible, according to the principle of predictability and reliability, this study selected 15 financial indicators from aspects of debt repayment level, profit level, operation level, growth level, and cash level, then predicted the risk by the logistic regression model, and analyzed the risk of 36 pairs of enterprises. The results showed that the model designed in this study had an accuracy rate of 91.67%, and the risk of a company was successfully predicted based on the financial situation of the company from 2018 to 2020, which verified the reliability of the method. Thus the model can effectively predict the financial risk of enterprises, and it can be further promoted and applied to ensure the long-term development of enterprises and establish a good market environment.

scholarly journals Biological Determinants of Hostility

2021 ◽  
Author(s):  
Valery V. Gafarov ◽  
Elena A. Gromova ◽  
Vladimir N. Maksimov ◽  
Igor V. Gagulin ◽  
Almira V. Gafarova
Keyword(s):  
Logistic Regression ◽  
Gene Polymorphisms ◽  
Logistic Regression Model ◽  
Male Population ◽  
Drd4 Gene ◽  
Genotype 4 ◽  
Maoa Gene ◽  
Biological Determinants ◽  
High Level ◽  
Different Levels

Our aim was to study the association of hostility with the DRD4, DAT, MAOA genes in an open male population of 25–64 years old. A representative sample of men aged 25–64 years (n = 657 men, average age 44.3 ± 0.4 years) was examined in 1994–1995 and 45–64 years old (n = 781 men, average age - 56.48 ± 0.2 years) in 2003–2005 using the methods proposed by the WHO international program “MONICA-psychosocial” and “HAPIEE”. All respondents completed the hostility questionnaire on their own. Genotyping of the DRD4, DAT and MAOA gene polymorphisms was carried out. It was established that the level of hostility in the male population was 76.9% in the group of 25–64 years old and 60.3% in the group of 45–64 years old. Genotypes 4/6, 4/7 of the DRD4 gene are reliably associated with a high level of hostility; the genotype 4/4 of the DRD4 gene is associated with an average and lower level of hostility. There was no association of individual genotypes and VNTR alleles of DAT gene polymorphism with different levels of hostility. It was found that among individuals with low-active alleles of the MAOA-L gene (alleles 2 and 3), a high level of hostility was more common - 50.9%. The results of constructing a logistic regression model showed that the presence of low-active alleles (2; 3) of the MAOA gene increases the likelihood of hostility OR = 2.103 (95% CI 1.137–3.889, p = 0.018). Based on the received data we can assume that the long alleles of the DRD4 gene and the low-level allele of the MAOA-L gene are associated with hostility.

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