Household Head-Related Social Capital: The Trump Card for Facilitating Actual Uptake of Innovation in Rural Smallholder Systems

Although Salvadoran emigration to the United States is one of the most important migratory flows emanating from Latin America, there is insufficient information about the predictors of first unauthorized migration from El Salvador to the United States. In this study, we use data from the Latin American Migration Project–El Salvador (LAMP-ELS4) to perform an event history analysis to discern the factors that influenced the likelihood that a Salvadoran household head would take a first unauthorized trip to the United States between 1965 and 2007. We take into account a series of demographic, social capital, human capital, and physical capital characteristics of the Salvadoran household head; demographic and social context variables in the place of origin; as well as economic and border security factors at the place of destination. Our findings suggest that an increase in the Salvadoran civil violence index and a personal economic crisis increased the likelihood of first-time unauthorized migration. Salvadorans who were less likely to take a first unauthorized trip were business owners, those employed in skilled occupations, and persons with more years of experience in the labor force. Contextual variables in the United States, such as a high unemployment rate and an increase in the Border Patrol budget, deterred the decision to take a first unauthorized trip. Finally, social capital had no effect on the decision to migrate; this means that for unauthorized Salvadoran migrants, having contacts in the United States is not the main driver to start a migration journey to the United States. We suggest as policy recommendations that the United States should award Salvadorans more work-related visas or asylum protection. For those Salvadorans whose Temporary Protected Status (TPS) has ended, the United States should allow them to apply for permanent residency. The decision not to continue to extend TPS to Salvadorans will only increase the number of unauthorized immigrants in the United States. The United States needs to revise its current immigration policies, which make it a very difficult and/or extremely lengthy process for Salvadorans and other immigrants to regularize their current immigration status in the United States. Furthermore, because of our research findings, we recommend that the Salvadoran government — to discourage out-migration — invest in high-skilled job training and also offer training and credit opportunities to its population to encourage business ventures.

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The Effect of Income, Health, Education, and Social Capital on Happiness in Indonesia

Asian Social Science ◽

10.5539/ass.v12n7p75 ◽

2016 ◽

Vol 12 (7) ◽

pp. 75 ◽

Cited By ~ 1

Author(s):

Theresia Puji Rahayu ◽

Sonny Harry B. Harmadi

Keyword(s):

Social Capital ◽

Health Education ◽

Urban Areas ◽

Positive Impact ◽

Household Head ◽

Relative Income ◽

Marginal Effect ◽

National Bureau ◽

Low Education ◽

Family Harmony

The purpose of the study is to analyze the effect of income, health, education, and social capital on happiness in Indonesia. The data was taken from National Survey of Social Economic conducted by National Bureau of Statistics of Indonesia in 2012. Ordered probit model was used as estimation technique due to ordinal dependent variable and normal distribution of error assumption. The findings show happiness is affected by absolute income, physical perceived health status, mental health, medium and high level of education, trust in leader, participation on society’s activities, tolerance, and help for and from others. However relative income, gender, household head, junior high school, and trust to neighbors do not have significant effect on happiness. Easterlin paradox does not exist in Indonesia because income has positive impact on happiness. Satisfaction on works, financial, family harmony, and leisure time also have significant effect on happiness. Satisfaction on family harmony is the most important factor than others. From demographic variables, it was known that happiness is not different across gender, household head, and low education people. People who are married, live in urban areas, live outside Java and Bali islands, and have more children are found happier. Happiness-age relationship indicates U-shaped curve. Happiness tends to decrease over time until people reach 51 years old. For all three level of happiness, some predictors do not have significant marginal effect on happiness namely relative income, gender, low education level, and trust to neighbors. Meanwhile the variables of household head and number of infant are not robust.

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Determinan Kebahagiaan Di Indonesia

Jurnal Ekonomi dan Bisnis ◽

10.24914/jeb.v19i1.485 ◽

2016 ◽

Vol 18 (1) ◽

pp. 149 ◽

Cited By ~ 1

Author(s):

Theresia Puji Rahayu

Keyword(s):

Social Capital ◽

Family Life ◽

Household Head ◽

Marginal Effect ◽

Cross Section Data ◽

Perceived Health Status ◽

Section Data ◽

Indonesia Family Life Survey ◽

Independent Variable ◽

Happiness Level

The research objective is to analyse the determinants of happiness in Indonesia. Using cross-section data from Indonesia Family Life Survey (IFLS) wave 4, 2007, this study takes 17.650 observations which estimated using Oprobit model. The Oprobit model was chosen because of ordinaled response variable and the normal assumption in error distribution. The result shows that happiness in Indonesia positively affected by income, education level, perceived health status and social capital. But social capital that connected with religion and ethnic don’t have significant effect on happiness. All predictors are robust. Demographic characteristics inform that married people, non household head, live in urban area, outside of Jawa-Bali islands and Javanese were happier than others. There is no difference in happiness level between man and woman. Happiness-age relationship indicated U-shaped curve. Marginal effect shows different effect for every happiness level due to a unit change in independent variable. Abstrak Tujuan penelitian ini adalah untuk menganalisis faktor-faktor penentu kebahagiaan di Indonesia. Dengan menggunakan data antar ruang/silang tempat dari Indonesia Family Life Survey (IFLS) wave 4, 2007, studi ini mengambil 17,650 pengamatan yang diestimasi menggunakan model Oprobit. Model Oprobit dipilih karena adanya variabel respon ordinal dan asumsi normal dalam distribusi kesalahan. Hasil penelitian menunjukkan bahwa kebahagiaan di Indonesia secara positif dipengaruhi oleh pendapatan, tingkat pendidikan, status kesehatan yang dirasakan dan modal sosial. Namun demikian, modal sosial yang berkaitan dengan agama dan etnis tidak memiliki pengaruh yang signifikan terhadap kebahagiaan. Semua prediktor bersifat robust. Karakteristik demografi menginformasikan bahwa orang yang menikah, bukan kepala rumah tangga, tinggal di daerah perkotaan, berada di luar pulau Jawa-Bali dan dari suku Jawa lebih bahagia daripada yang lain. Riset ini juga menemukan bahwa tidak terdapat perbedaan dalam tingkat kebahagiaan antara pria dan wanita. Kemudian, hubungan antara kebahagiaan dan usia menunjukkan kurva yang berbentuk U. Terakhir, efek marjinal menunjukkan efek yang berbeda untuk setiap tingkat kebahagiaan karena perubahan unit variabel independen.

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Benefits from Social Capital and Entrepreneurship Enhancement

IJEBD (International Journal Of Entrepreneurship And Business Development) ◽

10.29138/ijebd.v2i2.712 ◽

2019 ◽

Vol 2 (2) ◽

pp. 255-270

Author(s):

Mbu Daniel Tambi ◽

Mofow Neville Zoatsa

Keyword(s):

Social Capital ◽

Household Head ◽

Probit Model ◽

Household Consumption ◽

Strongly Correlated ◽

Environment Friendly ◽

The Government ◽

Consumption Survey

This study employed Multiple Correspondence Analyses to construct a social capital index and verified its relationship with entrepreneurship enhancement through Probit model correcting for endogeneity using the Cameroon household consumption survey in Stata. The results indicate that benefits from social capital is strongly correlated with entrepreneurship enhancement, while result by gender of household head, shows that entrepreneurship promotion is stronger among the female as compare to the male counterparts. The same applies for the rural than urban businessmen. We suggest that support policies by donors should be granted to useful associations, and that the government should invest in social capital either directly or indirectly by creating an environment friendly to the emergence of local associations.

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Evaluating the components of social and economic resilience: After two large earthquake disasters Rudbar 1990 and Bam 2003

Jàmbá Journal of Disaster Risk Studies ◽

10.4102/jamba.v9i1.368 ◽

2017 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Amir Bastaminia ◽

Mohammad R. Rezaei ◽

Mohammad H. Saraei

Keyword(s):

Neural Network ◽

Social Capital ◽

Linear Regression ◽

Length Of Stay ◽

Household Income ◽

Household Head ◽

Large Earthquake ◽

Economic Resilience ◽

Management Plans ◽

Different Dimensions

Extensive damages of natural disasters have made resilience a focus of disaster management plans in order to limit damages. The aim of this study was a comparative evaluation of social and economic resilience in Bam and Rudbar. This applied research attempted to quantify and compare different dimensions of social and economic resilience in Bam and Rudbar with a descriptive-analytical method. Cochran’s formula determined the sample size as 330 households from both cities (a total of 660 households). The indicators of social and economic resilience were identified from the literature, and then data were collected through a field study using questionnaires. Data were analysed using multiple linear regression and feedforward multilayer perceptron artificial neural network. Results denoted that several resilientrelated socio-economic features were significantly different for Bam and Rudbar cities, such as the number of earthquakes experienced, length of stay in current neighbourhood and mean individual and household income. Mean social and economic resilience scores were significantly higher for Rudbar (216.3 ± 33.4 and 30.6 ± 7.3) compared to Bam (193 ± 26.5 and 29.4 ± 7.07) ( p < 0.05). In addition, linear regression indicated that an increase in education level of the household head, length of stay in current neighbourhood and household income could result in an increase in social and economic resilience of the households under study. Neural network analysis revealed that social capital and employment recovery are the most and least effective factors, respectively, in both cities. In the population under study, social component, namely, social capital, was the most important determinant of resilience.

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