A principal component analysis of the determinants of spatial disparity between rural and urban localities of Ghana

2017 ◽  
Vol 44 (6) ◽  
pp. 715-731 ◽  
Author(s):  
Ivy Drafor
Keyword(s):  
Principal Component Analysis ◽  
Rural Areas ◽  
Urban Areas ◽  
Principal Component ◽  
Component Analysis ◽  
Spatial Inequality ◽  
Necessary Condition ◽  
Spatial Disparity ◽  
Content Type ◽  
Rural And Urban

Purpose The purpose of this paper is to analyse the spatial disparity between rural and urban areas in Ghana using the Ghana Living Standards Survey’s (GLSS) rounds 5 and 6 data to advance the assertion that an endowed rural sector is necessary to promote agricultural development in Ghana. This analysis helps us to know the factors that contribute to the depravity of the rural sectors to inform policy towards development targeting. Design/methodology/approach A multivariate principal component analysis (PCA) and hierarchical cluster analysis were applied to data from the GLSS-5 and GLSS-6 to determine the characteristics of the rural-urban divide in Ghana. Findings The findings reveal that the rural poor also spend 60.3 per cent of their income on food, while the urban dwellers spend 49 per cent, which is an indication of food production capacity. They have low access to information technology facilities, have larger household sizes and lower levels of education. Rural areas depend a lot on firewood for cooking and use solar/dry cell energies and kerosene for lighting which have implications for conserving the environment. Practical implications Developing the rural areas to strengthen agricultural growth and productivity is a necessary condition for eliminating spatial disparities and promoting overall economic development in Ghana. Addressing rural deprivation is important for conserving the environment due to its increased use of fuelwood for cooking. Absence of alternatives to the use of fuelwood weakens the efforts to reduce deforestation. Originality/value The application of PCA to show the factors that contribute to spatial inequality in Ghana using the GLSS-5 and GLSS-6 data is unique. The study provides insights into redefining the framework for national poverty reduction efforts.

Evaluation of access to electricity and the socioeconomic effects in rural and urban expanses of Nigeria

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Toluwalope Ogunro ◽  
Luqman Afolabi
Keyword(s):  
Socioeconomic Status ◽  
Rural Areas ◽  
Urban Areas ◽  
National Development ◽  
Content Type ◽  
Factors Affecting ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
The Government ◽  
Electricity Access

PurposeRecently, multidimensional aspects of poverty has been increasingly focused on which includes education, economy and health, while access to modern energy such as stable electricity is also one of the possible solution; thus, this article aims to divulge the relation between access to electricity and progression in socioeconomic status in urban and rural areas of Nigeria in an attempt to propose a sustainable framework for access to electricity.Design/methodology/approachDemographic and health survey data are collected using four categories of model of questionnaires. A standard questionnaire was designed to gather information on features of the household's dwelling element and attributes of visitors and usual residents between the 2018 period. Biomarker questionnaire was used to gather biomarker data on men, women and children. Logistic model estimation technique was employed to estimate the socioeconomic factors affecting access to electricity in Nigeria.FindingsThese studies discovered that there are diverse set of factors affecting access to electricity in Nigeria especially in the rural areas. However, respondent residing in rural areas are still largely deprived access to electricity; most importantly, households with no access to electricity are more likely to use self-generating sets as revealed. Additionally, empirical findings indicated that the higher the level of your education and wealth, the higher the likelihood of having access to electricity in Nigeria. These factors included political will to connect the rural areas to the national grid, development of other infrastructures in those deprived areas and others.Practical implicationsThe problem confronting access to electricity in Nigeria has three components. The first is the significance of those deprived access to electricity in the rural areas and the physical resources needed to connect them to the national grid. The second is the political willingness of the government to have equitable distribution of public goods evenly between rural and urban areas especially on electricity access which will go a long way in reducing poverty in Nigeria. The third is lack of robust national development plans and strategy to tackle the problems facing electricity access in Nigeria.Social implicationsAs the rate of socioeconomic status/development increases, access to electricity is anticipated to rise up in Nigeria.Originality/valueThe findings can be used by the policy makers to address problems facing access to electricity in Nigeria.

scholarly journals On Optimal Allocation of Treatment/Condition Variance in Principal Component Analysis

2018 ◽  
Vol 7 (4) ◽  
pp. 50
Author(s):  
André Beauducel ◽  
Norbert Hilger
Keyword(s):  
Principal Component Analysis ◽  
Treatment Condition ◽  
Optimal Allocation ◽  
Principal Component ◽  
Event Related Potentials ◽  
Component Analysis ◽  
Necessary Condition ◽  
Condition Effect ◽  
Loading Patterns ◽  
Related Potentials

The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-level is a necessary condition for an optimal allocation of between-condition variance, whereas a similar loading magnitude is not necessary.

scholarly journals Design of a Development Index for Spanish Municipalities

2020 ◽  
Vol 12 (21) ◽  
pp. 8910
Author(s):  
Ana Nieto Masot ◽  
Gema Cárdenas Alonso ◽  
Ángela Engelmo Moriche
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Principal Component ◽  
Point Of View ◽  
Development Index ◽  
Rural And Urban Areas ◽  
Economic Diversity ◽  
Rural And Urban ◽  
The Social ◽  
New Variables

Currently, the demographic vacuum and poor development suffered by most areas of Spain are some of the most worrying issues from a territorial point of view, which is why this study is necessary. In this paper, the objective is to create a Development Index with which to study the different realities of rural and urban spaces through demographic and socioeconomic variables of the Spanish municipalities. Principal Component Analysis is carried out, with whose results the index has been prepared. This is then explored with a Spatial Autocorrelation Analysis. The results show that most developed Spanish municipalities and most of the population are concentrated in coastal areas and in the main cities of the country. In opposition, there are interior rural areas with less developed municipalities at risk of disappearance due to their increasing ages and levels of depopulation. Thus, in this paper, new variables and methods are used in the study of the social and economic diversity of rural and urban areas, verifying the inequality that still exists between both.

Factorial analysis of stress factors among the sample of Lebanese police officers

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fadi Afif Fayyad ◽  
Filip Vladimir Kukić ◽  
Nemanja Ćopić ◽  
Nenad Koropanovski ◽  
Milivoj Dopsaj
Keyword(s):  
Principal Component Analysis ◽  
Police Officers ◽  
Psychological Health ◽  
Social Life ◽  
Principal Component ◽  
Component Analysis ◽  
Stress Factors ◽  
Research Approach ◽  
Content Type ◽  
Stress Management Training

PurposeThe purpose of the study is to determine the prevalence of stress and to identify the occupational stressors among Lebanese police officers.Design/methodology/approachOperational Police Stress Questionnaire (PSQ-op) was addressed to 100 randomly selected male Lebanese Police officers. Twenty items from the PSQ-op were run through the principal component analysis to determine the most significant factors of stress and loading within each of the factors.FindingsThe results indicated that 59% of officers reported moderate stress level and 41% reported strenuous stress. Principal component analysis identified six independent factors or stress among Lebanese police officers explaining in total 72.1% of the total variance: excessive workload (30.6%), social-life time management (12.8%), occupational fitness (9.1%), success-related stress (8.6%), physical and psychological health (5.8%), and working alone at night (5.2%).Research limitations/implicationsThis research approach encountered some limitations so further research must: use a larger sample size, include female gender and identify other sources of stressors mainly organizational or job context stressors.Originality/valueAddressing and understanding stress factors among Lebanese police officers helps improving awareness and developing individualized treatment strategies leading police officers to engage in stress-management training to learn coping strategies and use effective tools for preventing stress before it becomes chronic.

scholarly journals Global money laundering appeal index: application of principal component analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Milind Tiwari ◽  
Adrian Gepp ◽  
Kuldeep Kumar
Keyword(s):  
Principal Component Analysis ◽  
Money Laundering ◽  
Principal Component ◽  
Component Analysis ◽  
Economic Feasibility ◽  
Ranking System ◽  
Single Measure ◽  
Financial Flows ◽  
Content Type ◽  
To Come

Purpose The paper aims at developing a global ranking system determining a country's appeal as a destination for money laundering. Design/methodology/approach This paper uses principal component analysis (PCA), with a mix of standardised and unstandardised components relating to attractiveness, economic freedom and money laundering risk to come up with an index of money laundering appeal. Findings Four components relating to economic feasibility, financial liberty, government spending and tax regime are critical in influencing a country's money laundering appeal. Research limitations/implications This paper attempts to use a standardised and replicable methodology to condense into a single measure the complex and multifaceted phenomenon of a country's appeal as a destination for money laundering, thus avoiding the difficulty associated with precisely calculating illicit financial flows. Practical implications The ranking system could be used to determine the destinations attractive for laundering money. Such information can be used to come up with more effective preventative strategies to combat phenomena responsible for the stagnation of economic growth through tax evasion, corruption and creation of non-competitive markets. Originality/value It is the first attempt to use a statistical technique to understand the underlying components of a country's money laundering appeal.

scholarly journals Principal Component Analysis of the LEADER Approach (2007–2013) in South Western Europe (Extremadura and Alentejo)

2019 ◽  
Vol 11 (15) ◽  
pp. 4034 ◽  
Author(s):  
Nieto Masot ◽  
Alonso ◽  
Moreno
Keyword(s):  
Principal Component Analysis ◽  
Rural Development ◽  
Rural Areas ◽  
Western Europe ◽  
Principal Component ◽  
Component Analysis ◽  
Demographic Variables ◽  
Development Aid ◽  
Border Regions ◽  
Political Differences

Since the end of the last century, the Rural Development Policy and the associated Rural Development Aid have been implemented (according to the LEADER Approach) in European rural areas as a model of endogenous, integrated, and innovative development. Its objective is to reduce the differences of development in these areas. The objective of this paper is to analyze statistically (using Principal Component Analysis) the investments and projects carried out during the period of 2007–2013 in the regions of Extremadura and Alentejo. These two border regions have many territorial similarities but also historical, cultural, and political differences. These variations may contribute to a different implementation of the LEADER Approach. As determined by the results from the statistical analysis of economic aids and demographic variables, it is evident that there are differences in the management of the Rural Development Aid in both territories but resemblances in the results.

Sociodemographic characteristics and dietary patterns in cardiometabolic risk subjects

2019 ◽  
Vol 121 (11) ◽  
pp. 2780-2790 ◽  
Author(s):  
Brenda Kelly Souza Silveira ◽  
Juliana Farias de Novaes ◽  
Sarah Aparecida Vieira ◽  
Daniela Mayumi Usuda Prado Rocha ◽  
Arieta Carla Gualandi Leal ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Dietary Patterns ◽  
Cardiovascular Health ◽  
Cardiometabolic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Unhealthy Lifestyle ◽  
Cross Sectional ◽  
Content Type ◽  
Traditional Pattern

Purpose The purpose of this paper is to examine the associations of dietary patterns with sociodemographic and lifestyle characteristics in a cardiometabolic risk population. Design/methodology/approach In this cross-sectional study data from 295 (n=123 men/172 women, 42±16 years) participants in a Cardiovascular Health Care Program were included. After a 24-hour recall interview the dietary patterns were determined using principal component analysis. Sociodemographic, clinical and lifestyle data were collected by medical records. Findings Subjects with diabetes and hypertension had a higher adherence in the “traditional” pattern (rice, beans, tubers, oils and meats). Poisson regression models showed that male subjects with low schooling and smokers had greater adherence to the “traditional” pattern. Also, students, women, and those with higher schooling and sleeping =7 h/night showed higher adherence to healthy patterns (whole grains, nuts, fruits and dairy). Women, young adults and those with higher schooling and fewer sleep hours had greater adherence to healthy dietary patterns. Those with low schooling and unhealthy lifestyle showed more adherence to the “traditional” pattern. Social implications The results indicate the importance to personalized nutritional therapy and education against cardiometabolic risk, considering the dietary patterns specific to each population. Originality/value Socioeconomic and lifestyle characteristics can influence dietary patterns and this is one of the few studies that investigated this relationship performing principal component analysis.

Assessing socio-economic development in Bodoland Territorial Area District of Assam in India

2020 ◽  
Vol 47 (12) ◽  
pp. 1541-1559
Author(s):  
Nicodim Basumatary ◽  
Bhagirathi Panda
Keyword(s):  
Economic Development ◽  
Rural Areas ◽  
Urban Areas ◽  
Temporal Dynamics ◽  
Social Characteristics ◽  
Eastern Region ◽  
Content Type ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Socio Economic Development

PurposeThe study attempts to assess the socio-economic development in Bodoland Territorial Area District (BTAD) of Assam in North Eastern Region of India. This region is one of the most underdeveloped areas in India. The study also examines whether demographic and social characteristics in the form of social groups, number of family members, number of employed members in the family, education of the head of household, sources of income and location determine the variation in the level of socio-economic development. The authors surveyed 400 households during February to May 2018 in both rural and urban areas of BTAD to achieve the objective of the study.Design/methodology/approachThe authors use the concept of Amartya Sen's capability approach (CA) for assessment of development and constructed an index of Multidimensional Development.FindingsThere is variation in the distribution of developmental parameters across the study area. It is found that urban locations have better achievement in the multidimensional index score, while the spread of development is not even in the rural locations. An interesting revelation of this study is that while urban areas depict better performance in income, asset, education and empowerment, they have a relatively lower score in health dimension as compared to rural areas. The study shows that level of development depends on demographic as well as social characteristics of the households.Research limitations/implicationsThis study does not analyse temporal dynamics of development that is necessary to examine how development evolves because of data constraints.Originality/valueThe study provides an understanding of the socio-economic development in BTAD area in a multidimensional framework. This study is the first of its kind to assess the nature and extent of development realised in BTAD through the capability framework. The study supports more recent findings.

scholarly journals Characterising 3D spherical packings by principal component analysis

2019 ◽  
Vol 37 (3) ◽  
pp. 1023-1041 ◽  
Author(s):  
Tingting Zhao ◽  
Y.T. Feng ◽  
Yuanqiang Tan
Keyword(s):  
Principal Component Analysis ◽  
Gaussian Quadrature ◽  
Three Dimensional ◽  
Principal Component ◽  
Component Analysis ◽  
Particle Packing ◽  
Cross Sectional ◽  
Content Type ◽  
Computer Methods ◽  
Novel Approach

Purpose The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional. Design/methodology/approach Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images). Findings Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach. Originality/value Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

The long-run effects of energy use, urbanization and financial development on carbon dioxide emissions

2020 ◽  
Vol 14 (6) ◽  
pp. 1405-1424
Author(s):  
Paul Adjei Kwakwa
Keyword(s):  
Carbon Dioxide ◽  
Principal Component Analysis ◽  
Financial Development ◽  
Carbon Emission ◽  
Energy Use ◽  
Principal Component ◽  
Component Analysis ◽  
Content Type ◽  
Long Run ◽  
Emission Effect

Purpose This study aims to fill the gap in existing studies that have analyzed the drivers of carbon dioxide (CO2) emissions. The author investigate the long-run effects of energy types, urbanization, financial development and, the interaction between urbanization and financial development on CO2 emissions. Design/methodology/approach Stochastic impacts by regression on population, affluence and technology model served as the framework for empirical modeling. Using annual time-series data for Tunisia, autoregressive distributed lag bounds test was used to examine the cointegration of the variables. Also, the fully modified ordinary least squares was used to estimate the emission effect of the explanatory variables. Further investigations were done using the principal component analysis and variance decomposition analysis. Findings Income, urbanization, trade and financial development exert upward pressure on CO2 emissions. However, the interaction between urbanization and financial development reduces the emission of CO2. Furthermore, primary energy use, energy intensity, electricity consumption and fossil fuel consumption have positive effects on carbon emission, while combustible renewables and waste, and electricity production from natural gas have negative effects on carbon emission. Practical implications The policy implication/recommendation indicates that the financial sector’s authorities can combat carbon emission by properly regulating the development and activities of the financial sector in urban areas in Tunisia. The promotion of the development and usage of cleaner energy is recommended to help reduce carbon emission. Policymakers need to promote environmentally friendly economic growth and development agenda. Originality/value The contribution of this study to the environmental degradation literature is that it offers evidence from Tunisia, which has not received much empirical attention. It also examines the effect of various forms of energy usage on carbon emission. To the best of the author’s knowledge, this is the first study to examine the interaction effect between urbanization and financial development on carbon emission. Also, if not the first, this study is among the earliest to use the principal component analysis as a part of the prediction of the carbon emission effect of energy variables.

Sign in / Sign up

Export Citation Format

Share Document