scholarly journals THE DETERMINANTS OF REVERSE MORTGAGE CHOICE OF INDIAN ELDERLY HOMEOWNERS FOR SUSTAINABLE LIVELIHOOD: A LOGIT ANALYSIS

2019 ◽  
Vol 7 (4) ◽  
pp. 309-317
Author(s):  
Sarita Gupta ◽  
Dr. Sanjay Kumar
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Later Life ◽  
Primary Data ◽  
Logit Analysis ◽  
Sustainable Livelihood ◽  
Housing Wealth ◽  
Home Equity ◽  
Reverse Mortgage ◽  
Insurance Cover

Purpose: In the regime of stretched old-age social security, federals and policymakers are presuming housing wealth as a means of sustainable livelihood for elderly homeowners.  The current study attempts to discover which demographic and financial factors are significant determinants of home equity liquidation through reverse mortgage of Indians in later life. Methodology: Binary logistic regression is applied to survey-based primary data of 410 elderly homeowners through SPSS software. Main Findings: Results of binary logistic regression model depicts that elderly considering an RM likely to be female, older, having poor health, childless or having girl child only, long life expectancy, resident of metro, employed, cash-constrained, not having any kind of insurance cover and those children are financially well are significantly more willing to opt for RM scheme. Implication: Study renders implications for Government and NHB, to provide refinancing facility to commercial banks so that home equity liquidation product like Reverse Mortgage can be able to fulfill income needs of greying India. Novelty/Originality: Length of research in European and western countries have been carried out to explore the attitude of older homeowner for housing wealth liquidation but Indian context, is largely untapped that how Indian older homeowner perceive their housing wealth and which factor influences them to delete it. In this way, current study attempts to bridge the research gap.

scholarly journals The Impact of International Remittances on Poverty Alleviation in Bangladesh

2019 ◽  
Vol 4 (1) ◽  
pp. 67-86 ◽  
Author(s):  
Bezon Kumar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Poverty Alleviation ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Model ◽  
Household Poverty ◽  
International Remittances ◽  
The Impact

This article mainly explores to what extent international remittances alleviate household poverty in Bangladesh. This study uses primary data collected from 216 households and employs multi-methods. Firstly, I measure the level of household poverty through Foster-Greer-Thorbecke index. The article secondly focuses on the impact of remittances on household poverty using a binary logistic regression model. I found that the level of poverty among remittance recipient households is notably lower than households that are not receiving remittances. Similarly, the probability of a household being poor is alleviated by 28.07 per cent if the household receives remittance. It can be suggested that nursing international remittances can be useful for poverty alleviation in Bangladesh. 

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI STATUS PENERIMAAN BERAS KELUARGA MISKIN MENGGUNAKAN REGRESI LOGISTIK BINER DI KECAMATAN LANGSA BARAT

2020 ◽  
Vol 14 (2) ◽  
pp. 181-192
Author(s):  
Amelia Amelia ◽  
Fitra Mulyani ◽  
Ulya Nabilla
Keyword(s):  
Logistic Regression ◽  
Economic Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
The Status ◽  
Rice Consumption ◽  
The Government

Poverty is an inability to meet basic needs measured by expenditure, including rice consumption. Based on data from the Central Statistics Agency (BPS), as much as 95% of Indonesia's population consumes rice as the main food, with an average rice consumption of 102 kg/person/ year (BPS, 2013). Furthermore, BPS stated that almost 1/4 of them or around 25.95 million people were included in the category of the poor population as of March 2018. So the government made a policy to tackle the problem through the program of giving poor family rice (Raskin), namely subsidized rice assistance to households poor. However, in the implementation of the Raskin program, there was a deviation of around 40% of Indonesia's population with a middle-upper social-economic status receiving Raskin and 12.5% ​​of the population with a socio-economic status upon receiving Raskin. Therefore this study aims to analyze the significant factors that affect the status of rice in poor families using binary logistic regression analysis. The location of the study was conducted in the District of West Langsa because the district was one of the districts receiving the most Raskin in the City of Langsa. The data used in this study are primary data and secondary data. The results of the analysis show that the factors that influence Raskin's acceptance status are the level of education, type of floor, type of fuel, expenditure for food, and frequency of purchasing new clothes. The binary logistic regression model obtained is

scholarly journals Analisis Faktor-Faktor yang Mempengaruhi Keputusan Migrasi Commuter di Kabupaten Demak

2018 ◽  
Vol 5 (4) ◽  
pp. 345-353
Author(s):  
Ahmad Shidiq
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Migration Decision ◽  
Significant Positive Effect ◽  
Rural Regions ◽  
Negative Effect ◽  
Positive Effect

Fenomena migrasi sangat mewarnai di beberapa negara berkembang, termasuk di berbagai daerah di Indonesia. Di Indonesia terutama banyak tenaga kerja yang berasal dari daerah pedesaan mengalir ke daerah perkotaan, Salah satunya dari Kabupaten Demak. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi keputusan migrasi commuter di Kecamatan Karangtengah Kabupaten Demak antara lain adalah pendapatan pendidikan, pekerjaan daerah asal, jumlah tanggungan serta status perkawinan. Dalam penelitian ini menggunakan data primer melalui instrumen kuesioner terhadap sampel yaitu sebanyak 89 responden, dan menggunakan data sekunder yaitu data dari instansi-instansi terkait serta literatur buku. Penelitian ini dilakukan di Kecamatan Karangtengah Kabupaten Demak. Analisi yang digunakan dalam penelitian ini adalah binary logistic regression. Hasil penelitian menunjukkan bahwa pendapatan berpengaruh negatif dan signifikan terhadap keputusan migrasi commuter, pendidikan berpengaruh positif dan tidak signifikan terhadap keputusan migrasi commuter, pekerjaan di daerah asal berpengaruh positif dan tidak signifikan terhadap keputusan migrasi commuter, jumlah tanggungan daerah asal berpengaruh negatif dan tidak signifikan terhadap keputusan migrasi commuter, status perkawinan berpengaruh positif dan signifikan terhadap keputusan migrasi commuter. The phenomenon of migration is very coloring in some developing countries , including in the various regions in Indonesia . In Indonesia especially many workers coming from rural regions flowed into the urban area, One of Demak District. This study aims to determine the factors that influence the decision of commuter migration in Sub Karangtengah Demak district include the earnings of education, employment areas of origin, number of dependents and marital status. In this research, using primary data through a questionnaire on the sample of 89 respondents, and using secondary data is data from relevant agencies and literature books. This research was conducted at Sub Karangtengah, Demak District. The analysis used in this study is a binary logistic regression. The results showed that the income a significant negative effect on the migration decision commuter, education has positive and not significant to the migration decision commuter, work in the area of origin has positive and not significant to the migration decision commuter, number of dependents homelands negative and not significant to decision commuter migration, marital status and significant positive effect on the decision commuter migration.

scholarly journals Analysis of Factors that Influence Migration in Alian and Ayah Subdistrict, Kebumen Regency, Central Java

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Diah Tiara Rahmasari ◽  
Abdul Aziz Ahmad
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Influential Factor ◽  
Primary Data ◽  
Or Education ◽  
Central Java ◽  
The Family ◽  
Medium Level ◽  
Work Skill ◽  
The Government

This research aimed to analyses migrants’ income contribution to income of the family at hometown, the influences of income, age, numbers of family to be responsible to, education, and marriage status on decision about migration in Kebumen. The method used in the research was survey of primary data which is gained through interviews and questionnaires. The data in this research were 91 migrants in Alian and Ayah Districts. Data analysis techniques used were binary logistic regression. The results showed that the contribution of migrants’ income to family’s income after migrating to the two districts was in medium level. It showed that the needs to live in migration place were expensive. Consequently, the income obtained in migration place could not give enough contribution to the family in hometown. Based on the analysis, the variable of the numbers of people the migrants had positive and significant effect for migration. Income and marriage variables status had negative and significant effect. While age and education variables had no contribution to the migration. Income is the most influential factor in migration, so the government or related organizations should give attentions to the citizen’s prosperity by creating making the job activities. The government and the society should cooperate in developing the economic potential in each area. It is also by giving the society some loans and work-skill coaching or education to increase their income. Those are to encourage the society to be more creative and autonomous.Keywords: Binary Logistic Regression, Citizen’s Prosperity, Marriage Status.

Determinants of Under-Five Mortality in Khartoum State

2019 ◽  
Vol 15 (1) ◽  
pp. 1-19
Author(s):  
Hisham Elgilany
Keyword(s):  
Logistic Regression ◽  
Random Sample ◽  
Binary Logistic Regression ◽  
Regression Technique ◽  
Primary Data ◽  
Medical Checkup ◽  
Under Five ◽  
Duration Of Pregnancy

This paper  aims to study the determinants of under-five mortality in Khartoum state the capital state of Sudan. Primary data on variables  of relevance to under-five mortality was collected from a random sample of  households in Khartoum state in 2018, and analyzed by using binary logistic regression technique where dying or not dying before reaching age 5 constituted the dependent variable. The resulting model revealed that the strongest predictors of under-five mortality are  age of mother , age at the first childbearing, numbers of medical checkup, duration of pregnancy less than 32 weeks, average of breastfeeding, and mother  suffers from diabetes. Under-five mortality in Khartoum state can thus be  reduced quite considerably  by positively addressing these determinants via orchestrated policy .

scholarly journals ANALISIS PENENTUAN RAFAKSI DAN PENGARUHNYA TERHADAP PILIHAN SALURAN PEMASARAN PETANI UBI KAYU DI KABUPATEN LAMPUNG TENGAH

2017 ◽  
Vol 6 (2) ◽  
pp. 129-144
Author(s):  
Kusmaria Kusmaria ◽  
Ratna Winandi Asmarantaka ◽  
Harianto Harianto
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Visual Observation ◽  
Marketing Channels ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Harvest Time ◽  
Major Producer

Cassava becomes an important commodity in Indonesia because Indonesia is one of the major producer of cassava in the world. Besides exporting cassava, in fact Indonesia also imported cassava in large quantities. Altough the price of cassava was increasing in Lampung but the production and harvested area were decreasing, moreover factory and trader also set rafaksi on cassavas sold by farmers. Rafaksi is a penalties quantity to assess the quality of cassava farmers. Cassava marketing channels play role in determining the price and rafaksi that received by farmers. The aims of this research are (1) to analyze mechanism of determining rafaksi (2) to analyze price received by farmers’ after obtained rafaksi (3) analyze influence rafaksi to choice of marketing channels cassava farmers in Central Lampung Regency. Primary data were collected rendomly from 74 respondents. Data were analyzed by describe, correlation and binary logistic regression. The results showed that in the perception of farmers, determination of cassava rafaksi determined by several criteria such as the age of harvest, varieties, aci levels and the amount of dirt but not obtained a measure to ensure that criteria and only use the visual observation. The results of correlation analysis showed that there was no statistically significant connection between harvest time and the varieties of cassava with rafaksi of cassava which received by farmers. The result of binary logistic regression analysis showed that rafaksi loan significantly affected the choice of marketing channels.

Positive deviance in child malnutrition of urban poor of Mumbai, India: A longitudinal analysis

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L Yaddanapudi ◽  
R Dalal ◽  
S B Agnihotri
Keyword(s):  
Logistic Regression ◽  
Nutritional Status ◽  
Urban Poor ◽  
Binary Logistic Regression ◽  
Wealth Quintile ◽  
Positive Deviance ◽  
Primary Data ◽  
P Value ◽  
Binary Logistic Regression Model ◽  
Nutritional Status Of Children

Abstract Background Maharashtra has the largest share of urban population in India (13.5%) and is home to the largest slums. Malnutrition rates in these settlements are very high due to insufficient feeding, poverty, poor water quality and sanitation. The Foundation for Mother and Child Health (FMCH) has been working on reducing malnutrition in the urban slums of Mumbai for about 14 years now. Longitudinal data (2014-2019) collected by them was used in this analysis. Objectives To analyze the nutritional status of children before and after the intervention of FMCH and identify underlying factors associated with positive deviance in them. Methods NFHS-4 urban data of the lowest wealth quintile was used to analyze nutritional status of urban poor in India. Primary data of 4634 children (age 0-5) from the slums of Mumbai was analyzed for nutritional status during baseline and end line using ENA software. Descriptive statistical methods and binary logistic regression model were applied on selected 1583 cases using SPSS. Results Malnutrition rates in these children were lesser than national averages until 2 years of age. From baseline to end line, 48% reduction was observed in wasting within the first 6 months of age. Binary logistic regression reveals that age at registration (Odds ratio, OR = 0.94, p-value=0.04) and area of residence (p-value=0.00) are two most significant factors contributing to positive deviance in the child's nutritional status. Another univariate logistic regression on categorized breastfeeding score reveals that a higher score results in higher odds (OR = 1.561, p-value=0.01) of positive deviance in nutritional status of the child. Conclusions Since the strategy in each area is different, the most successful strategy is thus identified. The importance of early identification and intervention for effective tackling of malnutrition is highlighted through this analysis. Also, the role of effective breastfeeding techniques has emerged to be extremely significant. Key messages Impacting over 4000 children, the right nutrition in the first 1000 days and regular monitoring resulted in almost 50% reduction in wasting. Effective breastfeeding techniques were found to be extremely significant in the improvement of child's nutritional status.

scholarly journals Microcredit Accessibility in Rural Households: Evidence from Indonesia

2019 ◽  
Vol 65 (1) ◽  
pp. 67
Author(s):  
Danang Budi Santoso ◽  
Christopher Gan
Keyword(s):  
Logistic Regression ◽  
Interest Rates ◽  
Marital Status ◽  
Household Income ◽  
Rural Households ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Economic Welfare ◽  
Education Attainment ◽  
Factors Affecting

Extant literature suggests that microcredit may improve borrowers’ social and economic welfare. This study aimed to investigate the microcredit accessibility of rural households in Indonesia. Binary Logistic regression was used to distinguish the characteristics of microcredit borrowers and non-borrowers, and the factors affecting the approval of microcredit application. Primary data was collected through a survey on 488 rural households in Bantul, Yogyakarta. The empirical results suggested that age, marital status and education attainment significantly affect the characteristics of clients and non-clients of microcredit. The results also revealed that age of borrowers, household income, interest rates, and loan duration are key determinants affecting microcredit accessibility. The implications of the findings were provided.

scholarly journals The Impact of Literacy to Shariah Financial Service Preferences

ETIKONOMI ◽  
2016 ◽  
Vol 15 (1) ◽  
pp. 43-62 ◽  
Author(s):  
Anna Sardiana
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Financial Literacy ◽  
Financial Services ◽  
Binary Logistic Regression ◽  
Financial Service ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Descriptive Research ◽  
The Impact

The purpose of this study was to determine whether the Islamic financial literacy and the indicator as the knowledge, ability or skills and the confidence have a significant effect together and partially to the preferences of using the Islamic financial services. This type of research is descriptive research, while the method of analysis used in this study is the method of binary logistic regression analysis. The data used is primary data by the method of distributing questionnaires to users and non-users of Islamic financial services in Jakarta spread to the period April to May 2014. The results of this study indicate that Islamic financial literacy significant influence preference use Islamic financial services. In further testing, the knowledge indicator is partially significant toward the preferences of the use of Islamic financial services, as for indicators of ability and confidence does not affect the preferences of the use of Islamic financial servicesDOI: 10.15408/etk.v15i1.3115

scholarly journals Shifting from rice production to shrimp culture in coastal zones of Khulna: Determination of the determinants

2016 ◽  
Vol 13 (2) ◽  
pp. 257-264 ◽  
Author(s):  
M Anisuzzaman ◽  
MA Islam ◽  
KMM Rahman ◽  
MSR Shetu
Keyword(s):  
Logistic Regression ◽  
Saline Water ◽  
Binary Logistic Regression ◽  
Rice Cultivation ◽  
Primary Data ◽  
Bivariate Analysis ◽  
Coastal Zones ◽  
Shrimp Culture ◽  
Access To Credit ◽  
Land Holdings

This study aimed to investigate the determinants of shifting to shrimp culture from rice cultivation in coastal zones of Khulna district by using primary data collected from the four upazillas of Khulna, namely, Batiaghata, Dacope, Dumuria, and Paikgacha. Along with bivariate analysis, single-level binary logistic regression was carried out to identify the determinants of shifting. Through the bivariate analysis it had found that among all variables considered, some variables, precisely, amount of land holdings, access to credit, contact with GOs/NGOs, intrusion of saline water, perception of profitability of shrimp, and water logging had significant relation with shifting to shrimp culture. Similarly, the binary logistic regression had identified five significant determinants of shifting from rice cultivation to shrimp culture: occupation, land holding, access to credit, intrusion of saline water, and water logging.J. Bangladesh Agril. Univ. 13(2): 257-264, December 2015

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