scholarly journals An Assessment of Factors Influencing Forest Harvesting in Smallholder Tobacco Production in Hurungwe District, Zimbabwe: An Application of Binary Logistic Regression Model

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Chipo Chivuraise ◽  
Tafireyi Chamboko ◽  
Godfrey Chagwiza
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Forest Harvesting ◽  
Natural Forest ◽  
Selling Price ◽  
Binary Logistic Regression Model ◽  
Factors Influencing ◽  
Tobacco Production

Deforestation is one of the major effects posed by the smallholder tobacco farming as the farmers heavily depend on firewood sourced from natural forest for curing tobacco. The research aims at assessing the factors that influence the harvesting of natural forest in the production of tobacco. Data is collected through the structured questionnaire from 60 randomly selected farmers. Binary logistic regression model is used to explain the significance of factors influencing natural forest harvesting. Results show that farmer experience, tobacco selling price, and agricultural training level negatively affect the harvesting of natural forests (to obtain firewood) for curing tobacco significantly (p<0.05). However, gender, size of the household, tobacco yield, and level of education are insignificant (p>0.05) in influencing natural forest harvesting. Though farmers are exploiting the environment and at the same time increasing foreign currency earning through tobacco production, there is therefore a need to put in place policies that encourage sustainable forest product utilization such as gum plantations, subsidizing price of coal, and introducing fees, as well as penalties or taxes to the offenders.

scholarly journals Study of Factors Affecting the Entrepreneurship Behavior of Returned Migrants Using Binary Logistic Regression Model

2019 ◽  
Vol 3 ◽  
pp. 57-68
Author(s):  
Madhav Kumar Bhusal ◽  
Hari Prasad Pandey
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Home Country ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Educational Status ◽  
Categorical Variables ◽  
Binary Logistic Regression Model ◽  
Factors Influencing

Background: Entrepreneurship or business ownership is a significant source of employment and economic growth. Many studies conducted by different researchers have shown that increase in entrepreneurial activities helps to reduce unemployment. Thousands of Nepalese youths exodus for foreign migration every year for employments due to lack of adequate working environment in Nepal. In this context, identification of significant factors influencing the entrepreneurship behavior of returned migrants could be useful for planner, decision makers, and other concerned authorities. Objective: To explore the entrepreneurship status of returned migrants and to ascertain the factors influencing the entrepreneurship behavior of returned migrants. Materials and Methods: This study was based on primary data of 393 returned migrants collected through convenience sampling in Sarawal Rural Municipality of Parasi district, Nepal. People who stayed abroad at least one year and returned during 2010 to 2017 were included in the study. On the basis of Industrial Enterprise Act, 2016a, Nepal, a person who has invested Nepalese rupees five lakh or more in business besides housing and land is considered as an entrepreneur. The response variable is entrepreneurship status and it is defined according to the aforementioned act. Both quantitative and categorical variables were used as predictor variables. Factors associated with entrepreneurship behavior were extracted using Chi-square test and binary logistic regression model. Results: Out of sample of 393 returned migrants, 137 (34.9%) were entrepreneur and rest 256 (65.1%) were non-entrepreneur. Results showed that for main occupation of household head odds ratio (OR) = 4.008 & confidence interval (CI) = 2.396 to 6.703. Similarly, for educational status of returned migrants OR = 2.650 & CI = 1.599 to 4.392. For the covariate skills learnt at abroad OR = 2.750 & CI = 1.654 to 4.573. Conclusion: The study revealed that majority of returned migrants were non-entrepreneur. The factors ‘main occupation of household head’, ‘educational status of returned migrant’, ‘remittance received at home per year’ and ‘skills learnt abroad’ are the major determinants behind the entrepreneurship behavior of returned migrants. It is suggested that higher education and adequate skills should be taken before departing from home country so that the migrants can earn more money which will help to start their own businesses once they get back to their home country.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PEROLEHAN KREDIT OLEH PENGUSAHA MIKRO

2018 ◽  
Vol 4 (3) ◽  
Author(s):  
Abdul Azis Safii ◽  
Tri Suwarno
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Large Scale ◽  
Logistic Regression Model ◽  
Banking Sector ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Access To Credit ◽  
The Poor ◽  
Micro Enterprises

Abstract: The number of micro-entrepreneurs and the dominant number of micro enterprises compared to medium and large-scale enterprises in Indonesia are not balanced by the provision of access to credit and venture capital for micro businesses. This resulted in a micro-sector sector identical to the poor being vulnerable to exploitation by moneylenders who exploit the difficulties of micro entrepreneurs accessing credit from the banking sector. This study examines the factors that determine the accessibility of credit by micro entrepreneur in Bojonegoro regency. A total sum of 270 micro entrepreneurs who have applied for banking loan were sampled from the study area. With an binary logistic regression model the research resulting that education, skill on entrepreneur, and monthly net profits generated by the microenterprise are significant in determining the accessibility of microcredit. Keywords: micro entrepreneur, microcredit, credit accessibility Abstrak: Perkembangan jumlah pengusaha mikro serta dominannya jumlah usaha mikro dibandingkan dengan usaha menengah dan usaha besar di Indonesia, tidak diimbingi dengan penyediaan akses kredit dan modal usaha bagi para pelaku usaha mikro. Hal tersebut mengakibatkan sektor usaha mikro yang identik dengan masyarakat miskin rentan dieksploitasi oleh rentenir yang memanfaatkan sulitnya para pengusaha mikro mengakses kredit dari sektor perbankan. Penelitian ini menggunakan data primer yang di ambil langsung dari pengusaha mikro dengan teknik kuesioner. Analisis data dengan metode binary logistic regression mendapatkan hasil variabel yang berpengaruh signifikan terhadap akses kredit para pengusaha mikro adalah variabel usia pengusaha, laba bersih usaha tiap bulan, dan jumlah karyawan yang di pekerjakan. Kata kunci : usaha mikro, microcredit, akses kredit

scholarly journals ESTIMATION OF THE BINARY LOGISTIC REGRESSION MODEL PARAMETER USING BOOTSTRAP RE-SAMPLING

2018 ◽  
Vol 48 (3) ◽  
pp. 199-204 ◽  
Author(s):  
R. LI ◽  
J. ZHOU ◽  
L. WANG
Keyword(s):  
Logistic Regression ◽  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Parametric Bootstrap ◽  
Binary Logistic Regression Model ◽  
Bayesian Bootstrap ◽  
Non Parametric

In this paper, the non-parametric bootstrap and non-parametric Bayesian bootstrap methods are applied for parameter estimation in the binary logistic regression model. A real data study and a simulation study are conducted to compare the Nonparametric bootstrap, Non-parametric Bayesian bootstrap and the maximum likelihood methods. Study results shows that three methods are all effective ways for parameter estimation in the binary logistic regression model. In small sample case, the non-parametric Bayesian bootstrap method performs relatively better than the non-parametric bootstrap and the maximum likelihood method for parameter estimation in the binary logistic regression model.

Die Flexion der Indefinita jemand und niemand

2021 ◽  
Vol 49 (2) ◽  
pp. 209-243
Author(s):  
Linnéa Weitkamp
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Influencing Factors ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Corpus Study ◽  
Frequent Use ◽  
Current Variation ◽  
Reference Corpus

Abstract This article investigates the inflection of the German indefinite pronouns jemand and niemand in the accusative and dative. The pronouns are used both with inflectional suffix (jemanden/jemandem, niemanden/niemandem) and without (jemand, niemand) and are thus an example of current variation in contemporary German. The grammars take an unusually liberal stance and describe both forms as correct, partially even with preference to the uninflected form. A corpus study which examines conceptually written data of the DeReKo (German reference corpus) and conceptually oral data of the DECOW16B (German web corpus), shows that over 90 % of occurrences are inflected. But almost 10 % of uninflected forms show that these formations are no arbitrary errors either. To find out what influences the presence or absence of the inflectional ending, a binary logistic regression model was calculated. The following factors proved to be significant influencing factors for inflection: the degree of formality (DeReKo vs. DECOW16B), the lexeme (jemand vs. niemand), the case (acc vs. dat), government by preposition vs. government by verb and the following nominalized adjective (jemand anderen). With regard to the different inflectional suffixes, the frequent use of -en in the dative stood out in particular. Although this form is classified as erroneous in all grammars, almost 30 % of the dative occurrences in informal DECOW16B data are formed in this way.

scholarly journals Determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia

2020 ◽  
Vol 12 (4) ◽  
pp. 463-476
Author(s):  
Hurgesa Hundera Hirpha ◽  
Sylvester Mpandeli ◽  
Amare Bantider
Keyword(s):  
Climate Change ◽  
Logistic Regression ◽  
Regression Model ◽  
Climate Change Adaptation ◽  
Logistic Regression Model ◽  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Adaptation Strategies ◽  
Binary Logistic Regression Model ◽  
Content Type

Purpose The Ethiopian economy is mainly based on the rain-fed agriculture practiced by smallholder farmers. The sector is highly vulnerable to climate change impacts. This study aims to examine the determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia. Design/methodology/approach A cross-sectional survey design was used to collect quantitative data using questionnaire with 351 randomly selected smallholder farmers. To collect qualitative data focus group discussions, key informant interviews and field observations were also used. Triangulated with thematic analysis, descriptive statistics and binary logistic regression model were used for the analysis. Findings The result indicated that the majority of the smallholder farmers use at least one climate change adaptation strategy in their local areas though the strategy is generally weak. In this regard, some of the dominant climate change adaptation activities identified in the study area are using improved crop varieties, planting trees, watershed management, adjusting planting date and terracing. The result from binary logistic regression model showed that age and sex of household head, as well as their education, family size, access to agricultural extension services and training on climate change significantly influence the practices of adaptation measures. Originality/value This study would help the practitioners to modify the existing weak adaptation activities by introducing advanced and technological-based adaptation strategies to the rural farming communities.

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