Spatial differentiation of the impact of transport accessibility on the multidimensional poverty of rural households in karst mountain areas

PurposeThis paper evaluates the impact of socio and demographic factors on the multidimensional poverty of smallholder arable crop farming households in Nigeria.Design/methodology/approachData were drawn from the second wave of the LSMS-Integrated Surveys on Agriculture General Household Survey Panel 2012/2013. The methods adopted in analysing the data were descriptive statistics, Alkire and Foster Method (AFM) and logit regression model.FindingsThe result shows that 84.34% of the households were headed by a male while 80.26% of the respondents were married with a mean household size of seven persons. The multidimensional poverty of arable crop farm households in Nigeria is 0.60, while the adjusted headcount ratio (MPI) is 0.27, with an average intensity of 0.45. We found that deprivation in the dimension of living standard accounted for 45.5% of the overall multidimensional poverty index (MPI). The result of the logistic regression indicates that household location, gender, household size and non-farm income are negatively correlated to poverty. The factors that increase poverty among households are the age of the household head and access to extension services.Originality/valueThe study presents an alternative means of assessing poverty among smallholder arable crop farming households in Nigeria. This study recommends that policymakers should focus more on improving the living standard of arable crop farming households to reduce poverty in rural areas. Similarly, concerted efforts should be made towards providing adequate health care and improved sanitation, supply of electricity and educational training that goes beyond primary education for farming household members.

Download Full-text

Towards a Universal Social Impact Metric for Engineered Products That Alleviate Poverty

Volume 2B: 43rd Design Automation Conference ◽

10.1115/detc2017-67584 ◽

2017 ◽

Author(s):

Phillip D. Stevenson ◽

Christopher A. Mattson ◽

Kenneth M. Bryden ◽

Nordica A. MacCarty

Keyword(s):

Quality Of Life ◽

Developing Countries ◽

Social Impact ◽

Multidimensional Poverty ◽

Social Impacts ◽

Five Dimensions ◽

Multidimensional Poverty Index ◽

The Social ◽

The Impact

More than ever before, engineers are creating products for developing countries. One of the purposes of these products is to improve the consumer’s quality of life. Currently, there is no established method of measuring the social impact of these types of products. As a result, engineers have used their own metrics to assess their product’s impact, if at all. Some of the common metrics used include products sold and revenue, which measure the financial success of a product without recognizing the social successes or failures it might have. In this paper we introduce a potential metric, the Product Impact Metric (PIM), which quantifies the impact a product has on impoverished individuals — especially those living in developing countries. It measures social impact broadly in five dimensions: health, education, standard of living, employment quality, and security. The PIM is inspired by the Multidimensional Poverty Index (MPI) created by the United Nations Development Programme. The MPI measures how the depth of poverty within a nation changes year after year, and the PIM measures how an individual’s quality of life changes after being affected by an engineered product. The Product Impact Metric can be used to predict social impacts (using personas that represent real individuals) or measure social impacts (using specific data from products introduced into the market).

Download Full-text

Does Religiosity Affect Multidimensional Poverty? Evidence from World Values Survey (2010-2014)

Journal of King Abdulaziz University-Islamic Economics ◽

10.4197/islec.32-2.1 ◽

2019 ◽

Vol 32 (2) ◽

pp. 3-24

Author(s):

Salman Syed Ali Salman Syed Ali

Keyword(s):

Economic Growth ◽

Multidimensional Poverty ◽

Macro Level ◽

World Values Survey ◽

Counting Approach ◽

The Poor ◽

The Impact

Based on macro-level observations that high religiosity is associated with lower economic growth, it is generally assumed that religiosity contributes to poverty. However, this conjecture may not be true because religion provides motivation to the poor, encourages cooperation in society, and influences preferences and habits in ways that could help reduce poverty. The present paper uses data from World Values Survey (WVS) covering 52 countries and 74,042 individuals, to construct a measure of multidimensional poverty based on deprivation counting approach and a measure of religiosity based on faith deprivation. It then addresses three questions: (a) Is religiosity similar among multidimensional-poor and non-poor? (b) Are there any differences in dimensions of deprivations among high religiosity and low religiosity people? (c) What is the impact of religiosity on multidimensional poverty? It finds that higher religiosity is associated with lower multidimensional poverty; faith-poor are more deprived in their protections of intellect and posterity than protections of life and wealth. A decrease in religiosity increases multidimensional poverty. An implication of the study is that a religious society would be less poor even if its economic growth is slow.

Download Full-text

Research on the Impact of Relationship Networks on Farmers’ Formal Credit Constraints: The Case of China

International Journal of Engineering and Management Research ◽

10.31033/ijemr.11.4.13 ◽

2021 ◽

Vol 11 (4) ◽

Author(s):

Lun-song Chen ◽

Bi-Lin Sun

Keyword(s):

Credit Constraints ◽

Rural Households ◽

Credit Constraint ◽

Constraint Function ◽

Relationship Networks ◽

Social Interests ◽

Relationship Network ◽

The Impact ◽

The Relationship

Based on the survey data of Lishui City, Zhejiang Province, this paper uses the Heckman two-stage model to construct a credit constraint function without selection bias, and explores the relationship between the scale and quality of the relationship network and the credit constraints of rural households. Research shows that the scale of the relationship network is affected adversely by urbanization and networking, having a weaker impact on the formal credit constraints of rural households. The quality of the relationship networks can improve farmers’ awareness of formal credit, reduce transaction exposure, regulate farmers’ behavior and act as a “guarantee”, thereby effectively alleviating farmers’ formal credit constraints. At the same time, the relationship network of farmers is gradually becoming more structured, where farmers' social interests are becoming more purposeful. Additionally, formal financial institutions have set a threshold for farmers’ credit, which requires a certain amount of securities for money.

Download Full-text

Applying Horizontal Diffusion on Pressure Surface to Mesoscale Models on Terrain-Following Coordinates

Monthly Weather Review ◽

10.1175/mwr2925.1 ◽

2005 ◽

Vol 133 (5) ◽

pp. 1384-1402 ◽

Cited By ~ 3

Author(s):

Hann-Ming Henry Juang ◽

Ching-Teng Lee ◽

Yongxin Zhang ◽

Yucheng Song ◽

Ming-Chin Wu ◽

...

Keyword(s):

Vertical Mixing ◽

Flow Patterns ◽

Spectral Model ◽

Mountain Areas ◽

Pressure Surface ◽

Horizontal Diffusion ◽

Synoptic Conditions ◽

Temperature And Humidity ◽

Terrain Following ◽

The Impact

Abstract The National Centers for Environmental Prediction regional spectral model and mesoscale spectral model (NCEP RSM/MSM) use a spectral computation on perturbation. The perturbation is defined as a deviation between RSM/MSM forecast value and their outer model or analysis value on model sigma-coordinate surfaces. The horizontal diffusion used in the models applies perturbation diffusion in spectral space on model sigma-coordinate surfaces. However, because of the large difference between RSM/MSM and their outer model or analysis terrains, the perturbation on sigma surfaces could be large over steep mountain areas as horizontal resolution increases. This large perturbation could introduce systematical error due to artificial vertical mixing from horizontal diffusion on sigma surface for variables with strong vertical stratification, such as temperature and humidity. This nonnegligible error would eventually ruin the forecast and simulation results over mountain areas in high-resolution modeling. To avoid the erroneous vertical mixing on the systematic perturbation, a coordinate transformation is applied in deriving a horizontal diffusion on pressure surface from the variables provided on terrain-following sigma coordinates. Three cases are selected to illustrate the impact of the horizontal diffusion on pressure surfaces, which reduces or eliminates numerical errors of mesoscale modeling over mountain areas. These cases address concerns from all aspects, including unstable and stable synoptic conditions, moist and dry atmospheric settings, weather and climate integrations, hydrostatic and nonhydrostatic modeling, and island and continental orography. After implementing the horizontal diffusion on pressure surfaces for temperature and humidity, the results show better rainfall and flow pattern simulations when compared to observations. Horizontal diffusion corrects the warming, moistening, excessive rainfall, and convergent flow patterns around high mountains under unstable and moist synoptic conditions and corrects the cooling, drying, and divergent flow patterns under stable and dry synoptic settings.

Download Full-text