Measurement of on-farm diversification in Vietnam

2017 ◽  
Vol 46 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Diep Thanh Tung
Keyword(s):  
Regional Differences ◽  
Markov Chain Model ◽  
Mekong Delta ◽  
Farm Income ◽  
Chain Model ◽  
Total Income ◽  
Economic Shocks ◽  
Farm Diversification ◽  
Northern Regions ◽  
On Farm

This study aims to assess levels of on-farm diversification in Vietnam. The results reflect regional differences in terms of on-farm diversification and its determinants. Households in northern regions have adapted to the fragmented and small-sized parcels of land by diversifying their on-farm activities. In contrast, the Mekong Delta region in the south of Vietnam is characterized by larger agricultural parcels and a specialization in rice production. Land use fragmentation, as reflected by a large number of plots in a given area, is one of the most important reasons for the high levels of on-farm diversification, while the higher share of non-farm income in total income is the reason of lower levels of on-farm diversification. Households have reacted to natural and economic shocks by diversifying their on-farm activities. The non-stationary Markov chain model used here shows various diversification scenarios and trends. In most cases, the on-farm diversification is expected to reduce in coming years.

scholarly journals Farm Household Income and On- and Off-Farm Diversification

2005 ◽  
Vol 37 (1) ◽  
pp. 37-48 ◽  
Author(s):  
Kevin T. McNamara ◽  
Christoph Weiss
Keyword(s):  
Household Income ◽  
Census Data ◽  
Farm Income ◽  
Federal State ◽  
Farm Labor ◽  
Farm Household ◽  
Labor Allocation ◽  
Farm Diversification ◽  
Upper Austria ◽  
On Farm

The paper analyzes the relationship between off-farm labor allocation and on-farm enterprise diversification as farm household income stabilization strategies with census data from the federal state of Upper Austria, Austria. The results suggest that both on-farm diversification and off-farm labor allocation are related to farm and household characteristics. Larger farms tend to be more diversified. Younger farmers are more likely to work off-farm. Larger farm households tend to allocate more labor to off-farm income activities.

scholarly journals Farmland Rental Participation, Agricultural Productivity, and Household Income: Evidence from Rural China

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 899
Author(s):  
Wenjing Han ◽  
Zhengfeng Zhang ◽  
Xiaoling Zhang ◽  
Li He
Keyword(s):  
Rural Households ◽  
Agricultural Productivity ◽  
Household Survey ◽  
Farm Size ◽  
Farm Income ◽  
Rural Land ◽  
Total Income ◽  
Land System ◽  
Rural Land System ◽  
On Farm

The rural land rental market is playing an increasingly important role in the agricultural transformation period for developing countries, including China, where rural farmland rental is highly context-specific with the implementation of the collective-owned rural land system; thus, in turn, the access to farmland rental markets for rural households has profoundly influenced their livelihood strategies and income earnings. This paper investigates the income impact differences caused by rural households’ farmland rental participation activities and explores such impact mechanisms by further evaluating the income impacts caused by rental area and household agricultural productivity. Data from the Chinese national household survey were used for estimating the empirical models. Our results show that farmland renting has positively affected households’ on-farm and total income, but there is no significant effect upon off-farm income. According to income differences across quantiles, we find households with high on-farm income are more sensitive about enlarging their farm size by renting farmland, and households with middle and upper-middle off-income may benefit more from renting out their farmland. Furthermore, the joint effects of renting area and household agricultural productivity on lessee households’ farm income is significantly positive. For lessor households, our results indicate that renting out farmland did not improve their off-farm and total income as it may have a limited effect on farm household labor distribution. Our findings suggest that engaging in farmland rental activity can enhance farming productivity efficiency and poverty alleviation among rural households. Under the collective-owned rural land system, it is urgent and necessary to initiate and design incentive policies to encourage highly efficient large farms to expand the farm size and provide smallholders with equal opportunities to engage in farmland rental activities.

Does agro-processing adoption affect farm income and farm diversification? Empirical evidence from Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lin Lin ◽  
Hung-Hao Chang
Keyword(s):  
Large Scale ◽  
Farm Households ◽  
Farm Income ◽  
Processing Methods ◽  
Content Type ◽  
Farm Diversification ◽  
Effect Model ◽  
Agricultural Census ◽  
On Farm ◽  
The Impact

PurposeThe purpose of this paper is to identify the factors associated with the adoption of agro-processing methods and to estimate their impact on farm income and farm diversification.Design/methodology/approachUsing a large-scale sample of 12,122 special crop farm households drawn from the 2015 Agricultural Census Survey in Taiwan, the semiparametric multivalued treatment effect model was estimated.FindingsThe authors found that agro-processing farm households obtain higher farm incomes than non-agro-processing farm households. Among the agro-processing methods, self-processing generates higher farm income than outsourced-processing. Moreover, farm households that adopt either agro-processing method are more likely to diversify into agritourism and other agribusinesses than non-agro-processing farms.Research limitations/implicationsThe authors could only access data on farm income and not on agro-processing costs. Future studies may address the impact of agro-processing on farm profitability if relevant data are available.Originality/valueVery few studies have examined the relationship between agro-processing, farm income and farm diversification. To the best of the authors’ knowledge, this is one of the first papers to examine the impact of different agro-processing practices on farm income and farm diversification.

scholarly journals On- and Off-Farm Diversification and Travel Time to Markets: Linkages to Food Security in Rural Ethiopia

2021 ◽  
Author(s):  
Sven Bergau ◽  
Tim K. Loos ◽  
Orkhan Sariyev
Keyword(s):  
Travel Time ◽  
Dietary Diversity ◽  
Smallholder Farmers ◽  
Farm Income ◽  
Food And Nutrition Security ◽  
Farm Diversification ◽  
Nutrition Security ◽  
Food And Nutrition ◽  
Production Diversity ◽  
On Farm

AbstractFood insecurity persists in large parts of Ethiopia. Recent literature suggests that both on-farm and off-farm diversification, as well as access to agricultural markets, may help improve household dietary diversity scores (HDDS) as an indicator for food and nutrition security. While the HDDS is frequently used, a diversity score for the production side has rarely been applied at a comparable level of (dis-)aggregation. Employing socio-economic data collected covering 400 Ethiopian smallholder farmers, this study investigates how the travel time to markets, non-farm income, and on-farm production diversity associate with household food and nutrition security. Findings suggest that production diversity and higher non-farm income are linked to more diverse diets. With longer travel time to markets, food consumption is less varied. Production diversity and increased market participation do not appear to be mutually exclusive, and thus, should be considered equally when developing policy interventions.

Enhancing on-farm diversity: drivers and constraints. A review.

2021 ◽  
Author(s):  
Francesco Tacconi ◽  
Katharina Waha ◽  
Jonathan Ojeda ◽  
Peat Leith
Keyword(s):  
Farming Systems ◽  
Agroforestry Systems ◽  
Farm Size ◽  
Farm Income ◽  
Sustainable Rural Development ◽  
Farm Diversification ◽  
Market Risks ◽  
Farm Scale ◽  
The Times ◽  
On Farm

<p>Enhancing and maintaining on-farm diversity represent a potential strategy to improve farming systems sustainability, by reducing the pressure on the natural environment, alleviating farmers' risks and vulnerabilities, and increasing farms resilience. However, farms are complex systems and on-farm diversification, intended as the production of multiple crop, trees and/or livestock species, is not a panacea and it is driven or constrained by different factors and dynamics that vary across environmental, socio-economic and political contexts.</p><p>We argue that identifying indicators that reflect these drivers, constraints and contexts at farm scale is crucial to create favourable conditions for the farmers to increase on-farm diversity where doing so is likely to be beneficial. Therefore, the aim of this paper is to identify and clarify some of the patterns behind the process that lead farmers to adopt farm diversification strategies in order to understand where investments and interventions to support diversification are likely to be appropriate and effective, and how they should be targeted.</p><p>In this review, we analysed 97 articles, selected from the screening of 2,312 articles retrieved from Web of Science and Scopus, and published in English in peer-reviewed journals since 2010. Our selection criteria required that the articles focused on the analysis of drivers and constraints of agricultural diversification, intended as crops and/or livestock systems, agrobiodiversity and agroforestry systems, at farm and household scale.</p><p>From the selected studies, we identified and extracted a total of 239 different variables that were statistically assessed as potential drivers and constraints of farm diversity at farm scale. For each of the variables we counted the times they resulted as positive, negative and statistically significant, or not statistically significant. To present and discuss the results, we followed the Sustainable Rural Livelihood Framework, classifying the extracted variables as external (agroecological context, the political and institutional context, and exposure to environmental and market risks and shocks) and internal factors (human, economic/financial, socio-cultural and physical capitals), or other livelihood options (i.e. off-farm income).</p><p>Our findings show that the decision to maintain or increase on-farm diversification is a common strategy to cope with environmental and market risks, but that it is often alternative and negatively correlated to the adoption of off-farm livelihood. Overall, the drivers and constraints of diversification were highly context-dependent and contingent. For some relevant variables, such as farm size, household head's age, rainfall level and education, we also found some evidence of the presence of non-linear (e.g. inverted-U) relationships.</p><p>These results enforce the hypothesis of the complexity of land uses decision and the importance of understanding farms’ and farmers’ characteristics, and their local and wider context when it comes to design policies and research projects for sustainable rural development.</p>

An Efficient Markov Chain Model for the Simulation of Heterogeneous Soil Structure

2004 ◽  
Vol 68 (2) ◽  
pp. 346 ◽  
Author(s):  
Keijan Wu ◽  
Naoise Nunan ◽  
John W. Crawford ◽  
Iain M. Young ◽  
Karl Ritz
Keyword(s):  
Markov Chain ◽  
Soil Structure ◽  
Markov Chain Model ◽  
Chain Model ◽  
Heterogeneous Soil

Data Mining Technique Applied To DNA Sequencing

2015 ◽  
Vol 2 (7) ◽  
pp. 18
Author(s):  
R. Jamuna
Keyword(s):  
Data Mining ◽  
Dna Methylation ◽  
Markov Chain ◽  
Human Genome ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Effective Means ◽  
Cpg Islands ◽  
Chain Model ◽  
The Given

CpG islands (CGIs) play a vital role in genome analysis as genomic markers.  Identification of the CpG pair has contributed not only to the prediction of promoters but also to the understanding of the epigenetic causes of cancer. In the human genome [1] wherever the dinucleotides CG occurs the C nucleotide (cytosine) undergoes chemical modifications. There is a relatively high probability of this modification that mutates C into a T. For biologically important reasons the mutation modification process is suppressed in short stretches of the genome, such as ‘start’ regions. In these regions [2] predominant CpG dinucleotides are found than elsewhere. Such regions are called CpG islands. DNA methylation is an effective means by which gene expression is silenced. In normal cells, DNA methylation functions to prevent the expression of imprinted and inactive X chromosome genes. In cancerous cells, DNA methylation inactivates tumor-suppressor genes, as well as DNA repair genes, can disrupt cell-cycle regulation. The most current methods for identifying CGIs suffered from various limitations and involved a lot of human interventions. This paper gives an easy searching technique with data mining of Markov Chain in genes. Markov chain model has been applied to study the probability of occurrence of C-G pair in the given   gene sequence. Maximum Likelihood estimators for the transition probabilities for each model and analgously for the  model has been developed and log odds ratio that is calculated estimates the presence or absence of CpG is lands in the given gene which brings in many  facts for the cancer detection in human genome.

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