scholarly journals Hunger and the Issue of Agricultural Productivity in Congo

2020 ◽  
Vol 8 (2) ◽  
pp. 306
Author(s):  
Mayéko Léon
Keyword(s):  
Least Squares ◽  
Rural Areas ◽  
Negative Impact ◽  
Agricultural Productivity ◽  
Large Majority ◽  
Least Squares Regression ◽  
Crucial Issue ◽  
Agricultural Industry ◽  
Agricultural Households ◽  
Household Members

In the Congo agricultural techniques of agricultural households base agricultural productivity on the physical aptitudes of the members of these households. In rural areas, however, the hunger affects a large majority of households, especially households headed by households in an agricultural industry. Improving agricultural productivity in this situation is a crucial issue as household members no longer consume the required calories.Ordinary least squares regression has yielded results that indicate that an increase in the number of undernourished people has a negative impact on agricultural productivity.

Impact of Rapid Urbanization and Climate Change on Agricultural Productivity in Africa

2016 ◽  
pp. 416-426
Author(s):  
Mutisya Emmanuel ◽  
Lilian Muasa ◽  
Chiahsin Chen ◽  
Florence Mutisya ◽  
Ram Avtar
Keyword(s):  
Climate Change ◽  
Rapid Growth ◽  
Rural Areas ◽  
Urban Areas ◽  
Negative Impact ◽  
Agricultural Productivity ◽  
Well Being ◽  
Rapid Urbanization ◽  
Vulnerability To Climate Change ◽  
The Impact

Africa continues to experience serious signs of multiple crises in the context of sustainability. These crises include vulnerability to climate change, rapid urbanization, food insecurity, and many others. One crisis, that defines Africa today, is the unprecedented rapid urbanization which continues to pose a big challenge to the diminishing available resources, environmental quality and human well-being. Cities in Africa continue to experience a fast horizontal growth of settlements due to influx of people from rural areas who often settle in the economically lowest segments in urban areas. This horizontal rapid growth has eaten up land set for agriculture around cities and promoted the rapid growth of informal settlements exacerbating the impacts of climate change leading to a negative impact on agricultural production. Policies linking rapid urbanization and climate change with agricultural productivity are need. This paper explores and documents the impact of rapid urbanization on climate change policies and subsequent impact on agriculture in Africa.

Impact of corruption on bank soundness: the moderating impact of Shari’ah supervision

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mushtaq Hussain Khan ◽  
Ahmad Fraz ◽  
Arshad Hassan ◽  
Syed Zohaib Hassan Kazmi
Keyword(s):  
Least Squares ◽  
Negative Impact ◽  
Supervisory Board ◽  
Positive Contribution ◽  
Islamic Banks ◽  
Least Squares Regression ◽  
Content Type ◽  
Conventional Banks ◽  
The Relationship ◽  
Bank Soundness

Purpose This study aims to examine whether the soundness of Islamic banks is differently affected by corruption compared to conventional counterparts. Moreover, the Shari’ah supervisory board (SSB), as a cornerstone of Islamic banking and representing a multi-layer corporate governance model, is expected to moderate the influence of corruption on soundness for Islamic banks. Design/methodology/approach This study considers a unique sample of 1,528 observations on 71 Islamic banks and 120 conventional banks operating in 11 emerging and developing Muslim countries over the 2010–2017 period. This study uses generalized least squares regression model and the coefficients are estimated by using random-effects estimator. In addition, to overcome a potential endogeneity concern for corruption and bank stability relationship, this study uses Two-Stage Least Squares regression instrumental variable estimator. Findings The authors find consistent evidence that higher levels of corruption adversely impact the soundness for conventional banks, in favor of the sand the wheel hypothesis in the corruption–development nexus. However, as expected, this study finds a less negative impact of corruption on soundness of Islamic banks. Moreover, SSB moderates the relationship between corruption and soundness of Islamic banks. The findings are robust to a battery of alternative checks. Research limitations/implications Findings of the paper regarding the detrimental impact of corruption on bank soundness justify the urgency of the anti-corruption campaigns in these countries, particularly for conventional banks. Moreover, the findings provide support for the positive contribution of SSBs to overcome the adverse effect of corruption on soundness of Islamic banks and thereby underscoring the need for enforcement and regulatory mechanism for SSBs to be more effective. Originality/value To the best of the authors’ knowledge, this is the first study to examine the moderating impact of Shari’ah supervision on the relationship between corruption and soundness of Islamic banks.

scholarly journals E-agriculture Framework for Improving Agricultural Productivity among the Smallholder Farmers in Rural Kenya

2021 ◽  
Vol 78 (2) ◽  
pp. 17
Author(s):  
Daisy Mbucu IRERI ◽  
Mzee AWUOR ◽  
James OGALO
Keyword(s):  
Rural Areas ◽  
Smallholder Farmers ◽  
Agricultural Productivity ◽  
Work Force ◽  
Target Population ◽  
Small Scale ◽  
Specific Information ◽  
Smallholder Farming ◽  
Agricultural Industry ◽  
Ict Tools

The economy of Kenya depends mainly on agriculture where smallholder farming has a significant role as it employs 65 percent of the work force and contributes 32 percent of Kenya’s GDP. However, the agricultural industry in Kenya is currently facing difficulties in low productivity. The rural areas have the largest concentration of poverty and food insecurity. Majority of the farming activities in Kenya are on small scale and the problems of these farmers are multifaceted including sub-divisions and small farm sizes, leading to diseconomies of scale and low productivity. The goal of this research was to develop and validate an E-agriculture Framework for Improving Agricultural Productivity among the Smallholder Farmers. Descriptive research design was used. The study was carried out in South Eastern Kenya. The target population comprised 224 meteorological staff, 421 agricultural extension officers, 208 ICT personnel and 3,833 farmers. Data was collected using self-administered questionnaires, observation and interviews and analyzed using SPSS. The study found that challenges faced farmers were cost, illiteracy and ICT skills among others. Further, the study established that farmers required specific information such as soil management, pest management etc., for mainly improving their productivity. The researcher proposed an e-agriculture framework for improving agricultural productivity through promoting innovative use of ICT tools to bridge the distance between the farmers and the research communities. The proposed e-framework could be used by government policy makers and stakeholders on ICT on agricultural services in other developing countries to implement policies that speeded up the use of ICT on agricultural information.

Impact of Rapid Urbanization and Climate Change on Agricultural Productivity in Africa

2017 ◽  
pp. 1121-1132
Author(s):  
Mutisya Emmanuel ◽  
Lilian Muasa ◽  
Chiahsin Chen ◽  
Florence Mutisya ◽  
Ram Avtar
Keyword(s):  
Climate Change ◽  
Rapid Growth ◽  
Rural Areas ◽  
Urban Areas ◽  
Negative Impact ◽  
Agricultural Productivity ◽  
Well Being ◽  
Rapid Urbanization ◽  
Vulnerability To Climate Change ◽  
The Impact

Africa continues to experience serious signs of multiple crises in the context of sustainability. These crises include vulnerability to climate change, rapid urbanization, food insecurity, and many others. One crisis, that defines Africa today, is the unprecedented rapid urbanization which continues to pose a big challenge to the diminishing available resources, environmental quality and human well-being. Cities in Africa continue to experience a fast horizontal growth of settlements due to influx of people from rural areas who often settle in the economically lowest segments in urban areas. This horizontal rapid growth has eaten up land set for agriculture around cities and promoted the rapid growth of informal settlements exacerbating the impacts of climate change leading to a negative impact on agricultural production. Policies linking rapid urbanization and climate change with agricultural productivity are need. This paper explores and documents the impact of rapid urbanization on climate change policies and subsequent impact on agriculture in Africa.

scholarly journals Ramifications of Households’ Nonfarm Income on Agricultural Productivity: Evidence From a Rural Area of Pakistan

SAGE Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 215824402090209
Author(s):  
Md.Salamun Rashidin ◽  
Sara Javed ◽  
Bin Liu ◽  
Wang Jian
Keyword(s):  
Urban Areas ◽  
Agricultural Sector ◽  
Negative Impact ◽  
Agricultural Productivity ◽  
Modern Science ◽  
Ordinary Least Squares ◽  
Farm Income ◽  
Least Squares Regression ◽  
Probit Regression ◽  
Nonfarm Income

Currently in Pakistan, the agricultural sector contributes up to 18.9% of the gross domestic product. As a result of modern science and technology development, the source of income for rural households is changing, and nonfarm income has become the main source. This study investigates the effects of nonfarm income on agricultural productivity in rural Pakistan. The current research data has been collected from the Pakistan Social and Living Standards Measurement Survey (PSLM) 2017–2018, a sample of rural and urban areas designed by Pakistan’s Federal Bureau of Statistics. In this study, Heckman’s two-step procedure is used to tackle the problems of endogeneity and selection bias. The first phase, probit regression, indicates that the accessibility of banks, motorable roads, forest, telecommunication substructure, montane grasslands, and shrublands zone affects nonfarm income. On the other hand, the second stage, ordinary least squares regression, found a negative impact of nonfarm income on per capita farm income. Furthermore, results reveal that nonfarm household income has a significant positive effect on agricultural productivity.

Access to Saloons, Wet Voter Turnout, and Statewide Prohibition Referenda, 1907–1919

2008 ◽  
Vol 32 (3) ◽  
pp. 373-404 ◽  
Author(s):  
Michael Lewis
Keyword(s):  
United States ◽  
Least Squares ◽  
Voter Turnout ◽  
Rural Areas ◽  
The United States ◽  
Ordinary Least Squares ◽  
Urban Life ◽  
Least Squares Regression ◽  
Demographic Groups ◽  
Evangelical Protestants

When explaining the success of the Prohibition movement in the United States between 1900 and 1920, scholars argue that prohibitionists were able both to tap into the distrust of many rural, native-born, evangelical Protestants toward modern urban life and to bring together disparate groups of reformers around one goal: the elimination of the saloon. Furthermore, localized campaigns resulting in the elimination of saloons from many rural areas kept this base of voters energized, ultimately leading to impressive dry turnouts in statewide Prohibition referenda. This study extends and amplifies these findings through an analysis of three sets of factors on voting outcomes: the percentage of various demographic groups (urban, immigrant, and ritualistic religious populations) residing in a county; the distance of each county to saloons; the presence or absence of producers of alcohol in a county. Results of ordinary least-squares regression demonstrate that access to saloons and the percentage of immigrant and ritualistic church members in a county are the variables that most influence the results of Prohibition referenda. Furthermore, unlike what previous research has demonstrated, these variables have their greatest influence by affecting wet turnout rates.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Speech Emotion Recognition Based on Sparse Representation

2013 ◽  
Vol 38 (4) ◽  
pp. 465-470 ◽  
Author(s):  
Jingjie Yan ◽  
Xiaolan Wang ◽  
Weiyi Gu ◽  
LiLi Ma
Keyword(s):  
Dimensionality Reduction ◽  
Emotion Recognition ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Speech Emotion Recognition ◽  
Least Squares Regression ◽  
Computer Science Pedagogy ◽  
Reduction Methods ◽  
Analysis Computer

Abstract Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.

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