Perception to Adaptation of Climate Change in Nepal: An Empirical Analysis Using Multivariate Probit Model

Sci ◽  
2019 ◽  
Vol 1 (3) ◽  
pp. 57
Author(s):  
GC ◽  
Yeo
Keyword(s):  
Climate Change ◽  
Probit Model ◽  
Vulnerability Index ◽  
Climatic Variables ◽  
Multivariate Probit ◽  
Multivariate Probit Model ◽  
Credit Access ◽  
Ecological Zones ◽  
Explanatory Variables ◽  
Adaptation Options

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

scholarly journals Perception to Adaptation of Climate Change in Nepal: An Empirical Analysis Using Multivariate Probit Model

Sci ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 12 ◽  
Author(s):  
Arun GC ◽  
Jun-Ho Yeo
Keyword(s):  
Climate Change ◽  
Probit Model ◽  
Vulnerability Index ◽  
Climatic Variables ◽  
Multivariate Probit ◽  
Multivariate Probit Model ◽  
Credit Access ◽  
Ecological Zones ◽  
Explanatory Variables ◽  
Adaptation Options

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

scholarly journals Perception to Adaptation of Climate Change in Nepal: An Empirical Analysis Using Multivariate Probit Model

Sci ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 87
Author(s):  
Arun GC ◽  
Jun-Ho Yeo
Keyword(s):  
Climate Change ◽  
Probit Model ◽  
Vulnerability Index ◽  
Climatic Variables ◽  
Multivariate Probit ◽  
Multivariate Probit Model ◽  
Ecological Zones ◽  
Explanatory Variables ◽  
The Impact ◽  
Adaptation Options

This study assessed farmers’ perception of climate change, and estimated the determinants of, and evaluated the relationship among, adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, were found to be more influential compared to other factors. All four adaptation options were found to be complimentary to each other. Importantly, the intensity of the impact of dependent variables in different models, and for the available adaptation options, were found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

Determinants of Relevant Constraints Inhibiting Farmers’ Adoption of Climate Change Adaptation Strategies in South Africa

2020 ◽  
pp. 002190962093483
Author(s):  
KT Thinda ◽  
AA Ogundeji ◽  
JA Belle ◽  
TO Ojo
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Agricultural Sector ◽  
Smallholder Farmers ◽  
Probit Model ◽  
Adaptation Strategies ◽  
Multivariate Probit ◽  
Agricultural Credit ◽  
Multivariate Probit Model ◽  
Climate Change Adaptation Strategies

The adverse effects of climate change on agricultural productivity are on the increase. This study employed both descriptive statistics and the multivariate probit model to estimate factors constraining the adoption of climate change adaptation strategies among smallholder farmers in the study area. The empirical results of the multivariate probit model showed that a lack of knowledge of climate change constraints was influenced by smallholder farmers’ age, gender, off-farm activity, susceptibility and membership in farmer-based organizations. Thus, to improve the adaptive capacity of farmers, government and development partners should work together to improve the conditions under which farmers can gain access to climate change information and suitable agricultural credit as well as policy incentives aimed at lowering the stringent conditions of borrowing in the agricultural sector.

scholarly journals Determinants of Pesticide Application in Nepalese Vegetable Farming: An Empirical Analysis using Multivariate Probit Model

2017 ◽  
Author(s):  
Arun GC ◽  
Kiran Ghimire
Keyword(s):  
Empirical Analysis ◽  
Winter Season ◽  
Household Survey ◽  
Probit Model ◽  
Multivariate Probit ◽  
Multivariate Probit Model ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Head Of Household ◽  
Vegetable Farming

Currently, the pesticides are the global core concern because it is a boon to farmers against increasing disease-pest and simultaneously, pesticide residue is the major anxiety regarding human health. For that reason, identification and determination of factors affecting the application of pesticides are essential. To identify and evaluate determinants of pesticides application in Nepal, a household survey of 300 households was carried-out and an empirical analysis was done using multivariate probit model. Moreover, powder and liquid forms of pesticides were considered for summer and winter season in vegetable farming, which was assigned as outcome variables. Likewise, socio-economic, demographic, farm-level and perception data were considered as explanatory variables. Use of chemical fertilizers, age and gender of head of household, household size and access to weather information were found the most influencing factors. Moreover, forms of pesticides and growing seasons were found complementary to each other. Therefore, devising the policy options accordingly should balance needs of farmers and health of consumers.

scholarly journals Factors Influencing Farmer’s Choice of Crop Production Response Strategies to Climate Change and Variability in Narok East Sub-county, Kenya

2018 ◽  
Vol 8 ◽  
pp. 69-77
Author(s):  
Kelvin J. Kinuthia ◽  
Shadrack K. Inoti ◽  
Lenah Nakhone
Keyword(s):  
Climate Change ◽  
Household Head ◽  
Probit Model ◽  
Multivariate Probit ◽  
Annual Rainfall ◽  
Multivariate Probit Model ◽  
Response Strategies ◽  
Climate Change And Variability ◽  
The World ◽  
Impacts Of Climate Change

Climate change is considered one of the most serious threats to sustainable development in the world. As a sector, agriculture is very dependent on climatic conditions, which makes it extremely vulnerable to the impacts of climate change and variability. The semi-arid areas of the world are especially more vulnerable to the impacts of climate change and variability. The purpose of this study was to determine how farmers adapt to changing climate in Narok East, and determine the factors that influence their choice of response strategies. Data was collected from 223 household heads using a semi-structured questionnaire. Data was analysed using descriptive statistics to determine how farmers adapt to climate change and variability while Principal Component Analysis and a multivariate probit model were used to assess the factors that influence the choice of response strategies. The results showed that early planting, increased use of manure, use of terraces, increased use of inorganic fertilisers, and planting short season crops were the most widely used strategies while the least used were planting agroforestry trees, crop diversification and irrigation. Results of the multivariate probit model showed that the age of the household head, total household size, level of education of the household head, noticing changes in mean annual rainfall and onset of rains, receiving weather information, and the land tenure system were all significant factors that influence the choice of the response strategy. This study, therefore, recommends boosting more education and climate change awareness for the farmers of Narok East Sub-county.

Farmers’ vulnerability to climate change-induced water poverty in spatially different agro-ecological areas of northwest Ethiopia

2015 ◽  
Vol 7 (1) ◽  
pp. 142-158 ◽  
Author(s):  
Menberu Teshome
Keyword(s):  
Climate Change ◽  
Meteorological Data ◽  
Rural Households ◽  
Standardized Precipitation Index ◽  
Vulnerability Index ◽  
Northwest Ethiopia ◽  
Poor People ◽  
Weighting Method ◽  
Ecological Zones ◽  
Functional Relationships

This study assessed the vulnerability levels of farmers to water poverty in spatially different agro-ecological areas of northwest Ethiopia, where severe climate change risks exist. Data were collected from 525 randomly selected rural households in dega (highland), woyna-dega (midland) and kola (lowland) agro-ecological zones using questionnaires. This study also used secondary meteorological data. Rural households' exposure and vulnerability levels were analyzed using simple regression, standardized precipitation index, drought intensity and climate vulnerability index (CVI). The study also used the United Nations Development Program's (UNDP's) equation to measure vulnerability differential across agro-ecologies. The indicators were normalized as indices by considering functional relationships of indicators with vulnerability. Composite vulnerability indices were calculated using the equal weighting method. The result indicates that households in kola agro-ecology were found to be more exposed and vulnerable (0.62 score) to climate change-induced water poverty than those households in woyna-dega (0.49) and dega (0.30 score). The assessment of vulnerability at the appropriate spatial scale is a key step in designing context-specific adaptation responses that are effective in addressing the needs of the poor people who reside in different agro-ecological settings.

scholarly journals Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model

2020 ◽  
Author(s):  
Junwen Bai ◽  
Shufeng Kong ◽  
Carla Gomes
Keyword(s):  
Probit Model ◽  
Representation Learning ◽  
Multivariate Probit ◽  
Multivariate Probit Model ◽  
Computational Sustainability ◽  
Variational Autoencoder ◽  
Label Correlations ◽  
Real World Datasets ◽  
Embedding Spaces

Multi-label classification is the challenging task of predicting the presence and absence of multiple targets, involving representation learning and label correlation modeling. We propose a novel framework for multi-label classification, Multivariate Probit Variational AutoEncoder (MPVAE), that effectively learns latent embedding spaces as well as label correlations. MPVAE learns and aligns two probabilistic embedding spaces for labels and features respectively. The decoder of MPVAE takes in the samples from the embedding spaces and models the joint distribution of output targets under a Multivariate Probit model by learning a shared covariance matrix. We show that MPVAE outperforms the existing state-of-the-art methods on important computational sustainability applications as well as on other application domains, using public real-world datasets. MPVAE is further shown to remain robust under noisy settings. Lastly, we demonstrate the interpretability of the learned covariance by a case study on a bird observation dataset.

scholarly journals Determinants of Market Outlet Choices by Smallholder Chickpea Farmers in Estie District Amhara Region, Ethiopia

2021 ◽  
Author(s):  
Chernet Worku Erkie ◽  
Marlign Adugna ◽  
Essa Chanie
Keyword(s):  
Smallholder Farmers ◽  
Joint Probability ◽  
Probit Model ◽  
Sampling Procedure ◽  
Multivariate Probit ◽  
Primary Data ◽  
Farm Income ◽  
Cash Income ◽  
Multivariate Probit Model ◽  
Market Channel

Abstract In Ethiopia, chickpea is an important plus crop, particularly in Estie district. It is a source of food and provides cash income for majority of smallholder farmers. To commercialize chickpea producers, selecting an appropriate market channel is mandatory. However, selecting an appropriate market channel is not an easy task because there are different factors that affect market outlet choices in the district. Hence, this study aimed to identify factors that affecting chickpea market outlet choices. Both primary & secondary sources of data were used. A two-stage random sampling procedure was used and a total of 122 smallholder farmers were randomly and proportionally selected to collect primary data. Multivariate probit model was employed to identify factors affecting chickpea market outlet choices. The result shows that five major chickpea marketing channels were identified and among them wholesalers and retailers purchased about (61.84%) and (18.2%) respectively. The estimation result of multivariate probit model showed that the likelihood of sampled households to select collectors, consumers, retailers and wholesalers were 25.3%, 35.4%, 30.5% and 36%, respectively. The joint probability of success and failure to select all market outlets was 0.01537% and 13.4% respectively. It also indicated that sex of household, education status, family size, off-farm income, access to credit; lagged price and distance to market significantly affected the market channel choice decision of producers. Based on the findings, Government and concerned stakeholders need to focus more on enhancing accessibility of infrastructures facilities, strengthening credit access and improving yield through extension service to accelerate selecting appropriate market channel.

Sign in / Sign up

Export Citation Format

Share Document