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https://doi.org/10.56556/gssr.v3i4.1070 

                                                     

 

Global Scientific Research   74 

 

RESEARCH ARTICLE  

Production economics of jute farming in Sunsari district, Nepal 

Surakshya Sharma1*, Eishaina Chaudhary1, Pratik Gautam1, Kamal Regmi1, Huma Neupane2 

 

1Institute of Agriculture and Animal Science, Paklihawa, Rupandehi, Nepal 
2Tribhuvan University, Nepal 

 

Corresponding Author: Surakshya Sharma. Email: surakshyasharma111@gmail.com 

Received: 06 November, 2024, Accepted: 23 November, 2024, Published: 24 November, 2024 

 

Abstract 

Jute cultivation has shown decreasing trend in recent years globally despite the prospective demand. Being labor-

intensive, with labor making up over 70% of the entire cost and technological advancements still not evident in 

farmers' fields limits productivity of jute in Nepal. This study aims to analyze the economic viability of jute 

production, factors affecting it and constraints of jute production in Sunsari district, Nepal. Well-structured and 

pretested interview schedule was used to acquire required data from 120 jute cultivators of Bhokhraha Narsingh 

and Duhabi municipality using random and purposive sampling technique. Benefit-cost ratio analysis and multiple 

regression were conducted using Excel 2019 and SPSS Version 25. Jute production is found profitable as shown 

by positive gross margin and the average Benefit-Cost ratio of 1.52. Highest education of the family, machinery 

and subsidy were positively significant with Benefit-cost ratio. Number of economically active female members 

had shown negative influence on benefit-cost ratio of jute production. Distance to nearest extension service center 

showed highly significant negative relation with benefit-cost ratio implying increasing distance lowers BC ratio 

by a greater extent. High cost of production and labor problem were ranked as major problem in sustainable jute 

production. To increase the jute productivity and sustainability, this study recommends focusing on labor issues 

and enhancing technology interventions. The findings of this study offer policymakers a foundation to implement 

strategies that strengthen jute production, fostering both economic stability and environmental sustainability in 

Sunsari district, Nepal. 

Keywords: BC ratio; economic viability; regression 

 

Introduction 

Jute, often known as the golden fiber, is a natural fiber. It is one of the most affordable and durable natural fibers, 

and it is regarded as the fiber of the future (Uddin & Chowdhury, 2015). Jute is the cash crop for the poor and the 

marginal farmers and it continues to be an important commodity for employment and source of income for them 

(Kumari et al., 2018). Jute (Corchorus capsularis L. & Corchorus olitorius L.) is the world's second most produced 

natural bast fiber, with an anticipated average production of 2.39 million tons in 2020/21(Singh et al., 2019). The 

fibers are used to manufacture twine and rope, either alone or in combination with other types of fibers. Jute butts, 

which are the coarse ends of the stalks, are used to manufacture cheap cloth. In contrast, very fine jute threads can

be extracted and turned into imitation silk (Islam & Ali, 2018). Jute has a long history of use in the sacking, carpet, 

wrapping fabric (cotton bale), and building fabric production industries (Islam & Ali, 2018). Man-made synthetic 



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fibers are created in many nations due to insufficient production to fulfill demand and limited geographical 

distribution in India, Pakistan, Bangladesh, and other Asian countries (Maiti & Singh, 2019). Countries are 

currently focusing heavily on developing eco-friendly products such as jute bags in order to reduce climate impact 

and save the environment. Farmers are returning to jute production as the price of jute continues to rise. Jute's 

market is rapidly expanding (Islam, 2018). To meet industry demands, jute and associated fiber production must 

be expanded. Increased productivity and increased jute cultivation area are two major ways to do this (Kumari et 

al., 2018).  By lowering dependency on synthetic materials, improving soil health through rotation, and increasing 

biodiversity, increased jute production could be crucial to the advancement of sustainable agriculture techniques. 

Additionally, jute supports the creation of environmentally friendly products by offering biodegradable substitutes 

for plastics, which is in line with international sustainability objectives. Economically, by stabilizing farmer 

incomes and generating job opportunities, increased jute production strengthens rural communities. Despite such 

prospective demand, jute cultivation and area in the regions have shown changing trends in recent years. As a 

result, an attempt must be made to comprehend the current state of Jute farming, as well as the identification of 

limits from the perspective of growers. The dominance of marginal and small-scale farmers in jute farming is one 

of the limiting elements in the process of achieving cost competitiveness, resource use efficiency, and marketing 

efficacy (Kalita & Bhuyan, 2018). Technological progress is still not noticeable in the farmers' fields, and jute 

cultivation is labor intensive, accounting for almost 70% of the cost of human labor (S. Dutta & Mondal, 2021). 

The yield and quality of olitorius jute are now diminishing due to a lack of improved jute cultivars and other biotic 

stress factors. Insect pests are the most important biotic stressors in jute farming. Identifying the best jute varieties 

to grow on farms and utilizing quality tossa fibers in the jute sector industry would assist farmers in selecting the 

best jute varieties to grow (Karki et al., 2021).  

In relation to this, knowing the economics of jute production and identifying the key factors affecting and/or 

causing variations among producers in this study area is found very imperative in the course of planning for 

improvement. In this regard, there was no similar study conducted on similar issue in the specific targeted study 

area and hence this study is meant to fill this information gap. This study sets out to analyze economics of jute 

farming in Sunsari district, and to identify characteristics that explain variation in the economic viability of the 

farmers. An understanding of these relationships could provide policymakers with information to design programs 

that can contribute to measures needed to expand the jute production potential of Sunsari district. 

To analyze economics of jute farming in Sunsari district, the objectives are; To analyze the economic viability of 

jute farming, to identify factors affecting economic viability of jute farming and to identify problems associated 

with of jute farming in Sunsari district. 

Methodology 

Study Area 

Sunsari District is a district in Koshi Zone, Eastern Development Region, Nepal at latitude 26°38′29.76″ North, 

longitude 87°07′44.76″ East. Sunsari district is the second highest jute producing district of Nepal where jute is 

cultivated in 1392 hectares with productivity 1.48 mt/ha. Sunsari has a moderate climate. There is a lot of rainfall 

in the summer, and in the winter, it is quite dry. Bhokraha Narsingh Rural Municipality and Duhabi Municipality 

were selected for the study as population of jute cultivating farmers is relatively high. 

Sources of Data  

Both primary and secondary data will be used. Primary data will be collected through well prepared and pretested 

questionnaire to the sampled farmers. Secondary data will be collected from different journals, publications, 

reports and different internet sites.  



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Sample Size Determination 

From two selected municipalities, the representative respondents will be selected to enhance reliability and validity 

of the study. Accordingly, the sample size of the study is determined by using Kothari sampling design formula, 

(Kothari, 2004) 

 n =
N

1+N(e2)
 

Where, 

n = sample size  

N = total population  

e = acceptable error term (0.1)  

Simple random sampling was done to collect data from 120 jute farmers. 

 

Sampling and Data Collection 

The required quantitative data was collected through household survey using structured questionnaire which was 

pretested in 10 randomly selected jute growers of selected municipalities. We collected a list of jute cultivating 

farmers of Bhokhraha Narsingh and Duhabi municipality and selected 120 jute growers using simple random 

sampling technique. The data collection was carried out by visiting each household personally and interviewing 

them with the help of a pretested interview schedule. In each of jute producing respondent households, the 

household head or any adult who had lived with the household for at least one previous crop production seasons 

and conversant with the farming activities of the other household members were interviewed.  

Data Analysis  

Data collection was done by interview schedule, data was entered in SPSS version 25 and data was analyzed using 

SPSS version 25 and MS Excel 2019. Following analysis were done: 

Gross margin analysis 

Gross margin is the gross return over variable cost. Gross margin is calculated by deducting the total variable cost 

from the gross return (Bristy, 2020). 

Gross margin = Gross return – Variable cost 

Gross return 

Gross return is calculated by multiplying the total amount of product with respective per unit price and adding 

value of by-product. 

Gross return of jute production = Unit price of jute * Total production + value of by-product.  

Net return 

Net return or profit was calculated by deducting the total cultivation/production cost from the total return or gross 

return. 

Net return = Total return – Total cultivation cost 



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Benefit cost ratio  

Benefit Cost Ratio (BCR) is a relative measure, which is used to compare benefit per unit of cost. 

BC ratio= Total return/Total cost 

 

Factors affecting benefit cost ratio 

Factors affecting benefit cost ratio were identified using multiple regression (Kothari, 2004).  

Regression is the determination of a statistical relationship between two or more variables. In simple regression, 

we have only two variables, one variable (defined as independent) is the cause of the behavior of another one 

(defined as dependent variable). Regression can only interpret what exists physically i.e., there must be a physical 

way in which independent variable X can affect dependent variable Y. The basic relationship between X and Y is 

given by 

Y = a + bX 

 

This equation is known as the regression equation of Y on X (also represents the regression line of Y on X when 

drawn on a graph) which means that each unit change in X produces a change of b in Y, which is positive for direct 

and negative for inverse relationships. When there are two or more than two independent variables, the analysis 

concerning relationship is known as multiple correlation and the equation describing such relationship as the 

multiple regression equation. Multiple regression equation assumes the form ; 

 

Y =  a +  b₁X₁ +  b₂X₂ +  b₃X₃ + ⋯ … … … . + bₙXₙ  

 

The multiple regression equation for jute production is defined as; 

 

Y =  a +  b₁X₁ + b₂X₂ + b₃X₃ + b₄X₄ + b₅X₅ + b₆X₆ + b₇X₇ +  b₈X₈ 

Where, 

Y = B/C ratio 

a = y-intercept 

b = coefficient or slope for each variable 

X1 = Sex of Household 

X2 = Highest education in family 

X3 = Number of females economically active members 

X4 = Machinery 

X5 = Member of cooperatives 

X6 = Loan for jute 



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X7 = Subsidy 

X8 = Distance to nearest extension service 

 

Preference ranking 

Indexing was done in order to rank the problem by using the formula. 

I = Σ SiFi / N (Miah, 1993)  

Where, 

 I= Index Score  

Si = Scale value of ith level  

Fi = Frequency of ith level  

N =Total number of observations 

 

Result and discussion 

Descriptive Statistical Analysis of the Variables 

Table 11 shows the population characteristics of continuous variables with their mean and standard deviation. The 

study found the overall mean highest education of family to be 11.89 years with standard deviation 2.83. Higher 

education among farmers helps to maximize yield per unit area by improving crop management practices. Average 

of 1.38 number of females were found to be economically active in study area. Furthermore, the study found 

nearest extension service center was 3.53 km far from household in average.  

Table 1. Population characteristics (Continuous variables) 

Variables Mean Std. Deviation 

Highest education of family (years) 11.89 2.83 

Number of economically active females 1.38 0.60 

Distance to nearest extension service (km) 3.53 1.70 

Source: Field survey 2024 

Table 22 shows the population characteristics of categorical variables with their frequencies. Study shows majority 

of households (87.50%) have male household head while only 12.50% of female household head. 74.20% of 

farmers had some kind of machineries which indicated 25.80% of farmers are deprived of any kind of machineries. 

Very few farmers were member of cooperatives which might be due to low abundance of cooperatives or 

ineffective functions of cooperatives available there. Meanwhile 68.30% of farmers received subsidy on seed and 

fertilizer reducing cost of production. 31.70% of farmers were found to be out of reach from any kind of subsidy. 

Very few farmers were found to have drawn loan especially for jute production.    



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Table 2. Population Characteristics (Categorical variables) 

Variables Category Frequency 

Sex of HH 
Male 105 (87.50%) 

Female 15 (12.50%) 

Machinery 
Yes 89 (74.20%) 

No 31 (25.80%) 

Member of cooperatives 
Yes 19 (15.80%) 

No 101 (84.20%) 

Subsidy 
Yes 82 (68.30%) 

No 38 (31.70%) 

Loan for jute 
Yes 3 (2.50%) 

No 117 (97.5%) 

Source: Field survey 2024 

Cost Structure of Jute Production 

The average total cost of jute production per ha per season was found to be Nrs.  205891.23. Among all the costs 

contributing to total cost in jute production, labor cost accounts the highest cost (36%) followed by processing cost 

(25%), machinery cost (15%), variable cost (12%) and land rent (12%). This indicates jute production is labor 

intensive mostly used during weeding and harvesting. Machine introduced for harvesting of jute was rejected by 

farmers due to loss of jute sticks by breakage which is high value jute byproduct in study area. Introducing effective 

machineries to lower human labor requirement is recommended. Improvement in mechanization in jute farming 

will result in increased yield efficiency while minimizing labor requirement aligning with sustainable agriculture. 

Dutta (2012) also found labor cost constitute highest cost (55%) followed by variable cost. Within various variable 

costs, cost of fertilizer (urea, DAP and MOP) i.e. 48% was found highest followed by irrigation (31%), pesticide 

(12%), and seed (9%). This result is in line with result found by (Dutta, 2012) who also reported cost of fertilizer 

highest followed by irrigation. Figure 2 shows cost of pesticide is relatively lower which indicates farmers in study 

area use relatively lower quantity of pesticide. This highly contributes to sustainable agriculture. 

 

 

 

 

 

 

 

 

Figure 1: Pie-chart showing share of various cost in total cost 

Land rent

12%

Total 

variable …

Machinery 

cost…Labour cost

36%

Processing cost…



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Figure 2: Pie-chart showing share of various inputs in total variable cost 

Source: Field survey 2024 

Gross Margin, Gross Return and BC Ratio 

The study found gross return per ha land to be NPR 313423.36 which includes return from both main product and 

by-product with gross margin NPR 107532.13. Gross margin was found to be low due to high cost of production 

but low price of jute. Study found out BC ratio of jute production in study area to be 1.52. This implies with every 

1-rupee investment 1.52 will be returned. Therefore, jute production is found profitable as shown by positive gross 

margin and the BC ratio greater than one. This result is similar with result found by (Islam, 2018) who also found 

BC ratio to be 1.52.  

Table 3. Economic viability of jute production 

Variable Value 

Total cost  205891.23 

Gross margin  107532.13 

Gross return 313423.36 

BC ratio 1.52 

Source: Field survey 2024 

Factors Affecting Economic Viability 

Table 44 shows highest education of family in years was found positively significant with BC ratio at 5% level of 

significance with coefficient 0.03 which implies 1 years increase in highest education of family increases BC ratio 

by 3%. Number of females economically active members in family was found to be highly significant with negative 

Seed

9%

Urea

5%

DAP

28%

MOP

15%

Irrigation

31%

Pesticide

12%



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coefficient at 1% level of significance. This explains with increase in one female economically active member, BC 

ratio decreases by 6%. This is due to less efficiency of female as compared to male during various works on jute 

production increasing cost of production. Presence of machinery had shown positive significant relation with BC 

ratio at 5% level of significance. Similarly, subsidy had also shown positive significant relation with BC ratio at 

5% level of significance with coefficient 0.20 which describes one unit increase in subsidy will increase BC ratio 

by 20%. Providing subsidy to the farmers is seen to be highly effective in increasing profitability in jute production. 

Distance to nearest extension service center was found to be affecting BC ratio negatively at 1% level of 

significance. Increase in distance by 1 km decreases BC ratio by 31%. This is due to decrease in reach of farmers 

with extension service center in relation to subsidy and training with increase in distance.  

Table 44 shows that the R2 value for jute is 0.32 which means that 32% variation in the gross return of jute was 

explained by the independent variables included in the model respectively. The values of adjusted R2 was found 

0.27. This means that after considering the degrees of freedom (df), independent variables in the model still 

explained 27% of the variation in the gross return of jute. The F value for jute was found 6.58 which was highly 

significant at 1% level indicating the good fit of the model. 

 

Table 4. Factors affecting economic viability of jute production 

Variable Beta coefficient 

Sex of HH -0.18 (0.12) 

Highest education of family (years) 0.03 (0.01)** 

Female economically active members -0.06 (0.04)* 

Machinery 0.23 (0.09)** 

Member of cooperatives -0.01 (0.11) 

Loan for jute -0.24 (0.25) 

Subsidy 0.20 (0.08)** 

Distance to nearest extension service -0.31 (0.06)*** 

Constant 1.70 (0.21)*** 

F value 6.58*** 

R value 0.56 

R square 0.32 

Note: ***, ** and * signifies 1%, 5% and 10% level of significance respectively 

         Value in parenthesis indicates standard error 

Source: Field survey 2024 

Problem in Jute Production 

The study found out high cost of production as primary problem with index 0.93 followed by labor problem (0.92), 

technology constraint (0.86), lack of irrigation facility (0.58), lack of retting pond (0.53) and unavailability of 

quality seed (0.53). So, the study suggests decreasing the cost of production which may be achieved by increasing 

subsidy and solving labor problem by technology intervention may result higher return in jute production. Rashid 

(2022) also found high cost of production as primary problem followed by unavailability and high cost of labor. 

 



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Table 5. Problems in jute production 

Problem in production Index Rank 

Unavailability of quality seed 0.53 VI 

Labor problem 0.92 II 

Lack of irrigation Facility 0.58 IV 

High cost of production 0.93 I 

Technology constraint 0.86 III 

Lack of retting pond 0.53 V 

Disease problem 0.36 VIII 

Pest problem 0.42 VII 

Source: Field survey 2024 

Problem in Jute Marketing 

The study found out low price of jute as major problem with index 0.94 followed by unstable price of jute (0.91), 

inadequate marketing infrastructures (0.71), fluctuating demand (0.68) and dominance of Indian market (0.61). 

Providing fair price to the farmers will improve return in jute production. Nowadays, many farmers were found to 

be shifting towards sugarcane and maize cultivation due to low profitability resulting from low price of jute as 

compared to cost of jute production. Rashid (2022) also found 55% farmers had problem of low price of jute as 

compared to production cost.       

Table 6. Problems in jute marketing 

Problem in marketing Index Rank 

Dominance of Indian market 0.61 V 

Low price of jute 0.94 I 

Unstable price of jute 0.91 II 

Fluctuating demand 0.68 IV 

Transportation 0.26 VIII 

Lack of market information 0.54 VI 

Inadequate marketing infrastructures 0.71 III 

Loss during marketing 0.32 VII 

Source: Field survey 2024 

Conclusion 

This study presents significant results in jute production in Sunsari district, Nepal. The study found jute production 

profitable as shown by Benefit-cost ratio of 1.52 and positive gross margin. Highest education of the family, 

machinery and subsidy were found to be positively significant with Benefit-cost ratio. While, distance to nearest 

extension service center showed highly significant negative relation with benefit-cost ratio implying increasing 

distance lowers B/C ratio by a greater extent. High cost of production was found major problem in jute production 

and low price of jute as marketing problem. This study recommends providing subsidy and enhancing technology 

interventions is necessary to increase profitability in jute production. Also providing fair price of jute to the farmers 



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is necessary to stop jute growers from shifting towards other farming practices as shifting towards maize and 

sugarcane cultivation is seen more prevalent in Sunsari district. Increased income will enable farmers to afford 

nutritious food and help address hunger in long run. Strengthening jute farming can enhance Nepal’s export 

revenue which eventually contributes to national economic growth. Jute being biodegradable and renewable, 

promoting jute usage aligns with responsible consumption practices. Jute farming also reduces environmental 

impact and improve soil health. So, we can conclude that enhancing jute sector in Nepal can reduce poverty, 

promote economic growth and improve environment. This describes jute farming as significant part of sustainable 

agriculture and sustainable development.  

Declaration  

 

Acknowledgment: We acknowledge Institute of Agriculture and Animal Science, Paklihawa Campus, 

Nepal for providing required materials and facilities for conducting this experiment. We also 

acknowledge Mr. Surendra Chaudhary for his unforgettable help during data collection. We heartfully 

acknowledge all the farmers who helped us with our research. 

 

Funding: Not applicable (N/A) 

Conflict of interest: The authors declare that they have no known competing financial interests or 

personal relationships that could have appeared to influence the work reported in this paper. 

 

Ethics approval/declaration: N/A 

 

Consent to participate: N/A 

 

Consent for publication: N/A 

 

Data availability: Data will be made available on request.  

 

Authors contribution: Data collection, S Sharma, E Chaudhary; Data analysis, S Sharma; manuscript, 

S Sharma; Review and editing, S Sharma, K Regmi, P Gautam; Guidance and manuscript final review, 

K Regmi, H Neupane. 

 
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