Nature and determinants of migration: Insights from NSSO data in three states of India

2021 ◽  
Vol 18 (3) ◽  
pp. 261-280
Author(s):  
Ruchi Singh ◽  
Uday Salunkhe ◽  
Vaishali Vivek Patil
Keyword(s):  
West Bengal ◽  
Rural Households ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Monthly Expenditure ◽  
Level Data ◽  
Determining Factors ◽  
Internal Migrants ◽  
Significant Factors

The exodus of men is the most opted strategy adopted by rural households to diversify income and reduce risks associated with agriculture. Migration plays a very important role in reducing the liquidity and credit constraints of rural households in India. Data shows there are roughly 30 per cent internal migrants in the country. Despite the existence of studies on patterns and determinants of migration in various out-migrating states such as Uttar Pradesh, Bihar, Kerala etc., literature on the same in States with high in-migration are scarce. This article makes an attempt to comprehensively look into patterns and determinants of in-migration in three states. We have used the unit level data on migration (NSSO 64th Round) and tabulated it with suitable statistical techniques. To have a better understanding of determinants of in-migration in the states of Maharashtra, Delhi and West Bengal, a binary logistic regression model have been employed. We found that the majority of male migrants in these states is from within the state and but from different districts. Another interesting finding is that determining factors for migration vary across states. Social group, education, age, monthly expenditure are significant factors in determining migration decisions.

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.

Deciphering Links Between Sexual Violence and Castes in India

2021 ◽  
pp. 2455328X2110325
Author(s):  
Yogendra Musahar
Keyword(s):  
Regression Model ◽  
Sexual Violence ◽  
Economic Status ◽  
Family Health ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Bivariate Analysis ◽  
Binary Logistic Regression Model ◽  
Explanatory Variables

The recent incident, the gang rape and murder of a 19-year-old woman in Hathras, a small village in Uttar Pradesh of India, once again sparks a debate on links between sexual violence and castes in India. This article aims to examine the links between sexual violence and castes in India. This study utilizes the national representative National Family Health Survey 4 (NFHS-4, 2015–16) data. A bivariate analysis was carried out to analyse the data. A binary logistic regression model was applied to predict the effect of explanatory variables, viz. type of place of residence, years of schooling complete, economic status in terms of wealth index and finally castes on predicted variable, i.e. sexual violence. The binary regression model indicates that there were links between sexual violence and castes. For secured and dignified life of women, caste-based sexual violence must be annihilated.

scholarly journals FENOMENA DAN DETERMINAN KESEMPATAN ANAK MASUK DUNIA KERJA

2013 ◽  
Vol 2 (1) ◽  
pp. 49
Author(s):  
Selli Nelonda
Keyword(s):  
Labor Market ◽  
Human Resources ◽  
Logistic Regression Model ◽  
Development Process ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Number Of Children ◽  
Geographic Factor ◽  
Food Expenditure ◽  
Significant Factors

In most countries including Indonesia, children are very valuable future human resources in development process; they are the future of a country. For these reasons all stakeholders have the equal obligation to promote opportunity for the children to get their basic needs for their better future. But, the reality is not always as good as it should be, for some reasons, there are many children still enter the labor market than being at school for their education. Using 2009 Susenas data with binary logistic regression model, this research find that parents education, parents marital status, parent jobs sector, economic sector activity, number of children in a household, share of food expenditure and geographic factor are the significant factors to determine the probability a child entering the labor market.

scholarly journals MIGRATION DECISIONS AMONG RURAL HOUSEHOLDS IN RWANDA: WHAT DOES THE PUSH-AND-PULL MODEL REVEAL?

AGROFOR ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Edouard MUSABANGANJI ◽  
Charles RURANGA ◽  
Aristide MANIRIHO
Keyword(s):  
Internal Migration ◽  
Economic Status ◽  
Regional Growth ◽  
Rural Households ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Situational Analysis ◽  
Binary Logistic Regression Model ◽  
Pull Factors ◽  
Migration Decisions

A country economic status is strongly linked to the transition of its population from one area to another. This, because labor and other forms of migration, has a twofold advantage: (I) resourcing the targeted location by skilled labor force, and (II) improving migrant households’ livelihoods by lowering the vulnerability level. This research aimed at understanding the factors affecting migration decisions among rural households in Rwanda. Data on internal migration were collected in 5033 rural households in 2016/2017 as a part of the fifth nation-wide crosssectional survey on the Households Living Conditions, and analyzed using the binary logistic regression model. The major findings showed that internal migration was higher in Southern (31.9%) and Western (24.3%) provinces, where official reports pointed out a high level of poverty. The lower rate was observed in Kigali City (3.5%) which was actually considered as richest area and the most internal migration ‘pull factors’ (jobs and other livelihoods opportunities) offering zone. Results also revealed that, on one hand, being from a rural area, the age, having a large household size, having advanced education level, and being an female household head were the ‘push factors’ increasing by around 30% and more the probability of deciding to migrate to another region. On the other hand, owning a land and being reach decreased the likelihood of moving to other zones. This leads to affirm that employment opportunity and availability of diversified livelihoods sources in receiving regions constitute the main ‘pull factors’ of migration decisions at rural household level. In light of these findings, it is recommended to (I) ensure more balanced regional growth and opportunities for increased access to off-farm employment for a larger proportion of the rural population and (II) carry out a study on the effects of migration on the livelihoods of migrant-sending households in order to make a thorough and refined situational analysis.

scholarly journals Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Tianpei Tang ◽  
Hua Wang ◽  
Jie Ma ◽  
Xizhao Zhou
Keyword(s):  
Traffic Management ◽  
Red Light ◽  
Binary Logistic Regression ◽  
Signalized Intersections ◽  
Influential Factors ◽  
Binary Logistic Regression Model ◽  
Site Type ◽  
Demographic Attributes ◽  
Signal Time ◽  
Significant Factors

This paper focuses on investigating electric bikers’ (e-bikers) crossing behavior and violations based on survey data of 3,126 e-bikers collected at signalized intersections in Nantong, China. We first explore e-bikers’ characteristics of late crossing, incomplete crossing, and violating crossing behaviors by frequency analysis and duration distribution, and examine a few influential factors for e-bikers’ red-light running (RLR) behavior, including site type, crossing length and traffic signal countdown timers (TSCTs). E-bikers’ RLR behavior is further divided into three categories, namely GR near-violations, RR violations, and RG violations. Second, we use a binary logistic regression model to identify the relationship between e-bikers’ RLR behavior and potential influential factors, including demographic attributes, movement information, and infrastructure conditions. We not only make regression analysis for respective violation type, but also carry out an integrated regression of a census of all three types of violations. Some insightful findings are revealed: (i) the green signal time and site type are the most significant factors to GR near-violations, but with little impact on the other two violation types; (ii) the waiting time, waiting position, passing cars and crossing length exert considerable impact on RR violations; (iii) for RG violations, TSCTs, leading violators and gender are the most significant factors; (iv) it is also unveiled that site type, green signal time and TSCTs have negligible impact on the whole violations regardless of the violation types. Thus, it is more meaningful to investigate the impacts of these variables on e-bikers’ RLR behavior according to different violation types; otherwise, the potential relationship between some crucial factors and e-bikers’ RLR behavior might be ignored. These findings would help to improve intersection crossing safety for traffic management.

scholarly journals Effects of Different Socio-economic Characteristics of Rural Households on Their Saving Decision in Pabna District of Bangladesh: A Binary Logistic Regression Analysis

2020 ◽  
pp. 14-20
Author(s):  
Md. Al-Amin
Keyword(s):  
Logistic Regression ◽  
Random Sampling ◽  
Rural Households ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Household Saving ◽  
Private Savings

Household saving ensures a smooth future by softening the potential insecurities arise from uncertainty at the cost of present consumption. Moreover, the volume of national investment determines the actual health of an economy which is intensively associated with national savings. This study aimed at determining the effects of different socio-economic characteristics of rural households on their saving decision in Pabna district of Bangladesh. This research used a set of cross-sectional data from 250 households from three upazilas in Pabna district namely Pabna Sadar, Iswardi and Sujanagar on the relevant variables for the empirical analysis. A multistage random sampling technique involving simple, purposive and stratified random sampling was used to draw the sample. The study employed a binary logistic regression model to assess the influences of different socio-economic and demographic characteristics of rural household on their saving decision. The findings of the current study asserted that gender, family size and dependency ratio of household have significant and negative effects on their decision to start saving or not to start saving. Contrarily, the effects of the variables age, education level, marital status, income, secondary earner and liabilities on the decision of households to participate in saving were positive and significant. Moreover, the results revealed that social status has a strong but insignificant effect, but the variables access to bank and credit facilities have almost no significant effect on the household saving decisions. Since, private savings is essential for both the micro and macro level of an economy, therefore the study tried to suggest some recommendations with a view to increase private savings.

scholarly journals Family characteristics associated with rural households’ willingness to renew the family doctor contract services: a cross-sectional study in Shandong, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenjuan Li ◽  
Jie Li ◽  
Peipei Fu ◽  
Yan Chen ◽  
Yemin Yuan ◽  
...  
Keyword(s):  
Labor Force ◽  
Descriptive Analysis ◽  
Rural Households ◽  
Family Doctor ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Family Characteristics ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
The Family

Abstract Background In China, some previous studies have investigated the signing rate and willingness of residents to sign the family doctor contract services (FDCS). Few studies have explored residents’ willingness to renew the FDCS. This study is designed to understand the family characteristics difference towards rural households’ willingness of maintaining the FDCS. Methods A total of 823 rural households were included in the analysis. A descriptive analysis was conducted to describe the sample characteristics. The binary logistic regression model was used to explore the family characteristics that influence the renewal willingness for FDCS among rural households in Shandong province, China. Results Our study found that about 95.5% rural households had willingness to maintain the FDCS in Shandong, China. Those households with catastrophic health expenditures (CHE) (OR = 0.328, 95%CI = 0.153–0.703), with highest level of education at graduate or above (OR = 0.303, 95%CI = 0.123–0.747) were less willing to maintain the FDCS. Those whose households have more than half of the labor force (OR = 0.403, 95%CI = 0.173–0.941) and those households living in economically higher condition were less willing to maintain the FDCS. Conclusions This study demonstrates a significant association between family characteristics (CHE, highest education in households, proportion of the household labor force) and willingness to maintain FDCS among rural households in Shandong, China. Targeted policies should be made for rural residents of identified at-risk families.

scholarly journals A Culture-Centered Approach to Experiences of the Coronavirus Pandemic Lockdown Among Internal Migrants in India

2021 ◽  
pp. 000276422110003
Author(s):  
Devalina Mookerjee ◽  
Sujoy Chakravarty ◽  
Shubhabrata Roy ◽  
Anirudh Tagat ◽  
Shagata Mukherjee
Keyword(s):  
Migrant Workers ◽  
West Bengal ◽  
Uttar Pradesh ◽  
Indian States ◽  
Home Food ◽  
Additional Burden ◽  
Internal Migrants ◽  
Culture Centered ◽  
Difficult Times ◽  
The City

India’s coronavirus lockdown forced low-wage migrant workers to return from the city to the home towns and villages from which they came. Pre-pandemic living and working conditions were already stressful and difficult for these migrants. The lockdown became an additional burden, since it shut down sources of income with no assurance about when, or if, work and earning to support families could be resumed. This article draws on the lens of the Culture-Centered Approach (CCA) to understand how workers engaged with and navigated these difficult times. A total of 54 migrant workers locked-down at home across the Indian states of Bihar, Uttar Pradesh, and West Bengal were interviewed for this qualitative study. Financial worries were found to be endemic, with rising debt a major source of stress, and educational qualifications becoming an obstacle to earning. Returning migrants were suspected of bringing the virus from the city, and so stigmatized in their home towns and villages. However, the pandemic lockdown also showed some unexpected healthful consequences. It provided these marginalized, and always busy workers the time and space to stop working for a while, to stay home, eat home food, and take walks in the comparatively green and clean spaces of their home environments. In this, the pandemic lockdown may be seen to have enabled a measure of agency and health in the lives of these workers, an oasis albeit temporary, and ultimately subject to the demands of the globalized cities of India.

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.

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