2Department of Development and Poverty Studies, Sher-e-Bangla Agricultural University, Dhaka -1207, Bangladesh
3Department of Agribusiness and Marketing, Sher-e-Bangla Agricultural University, Dhaka -1207, Bangladesh
Key words: Farmer, profitability, shrimp farming and Bangladesh.
The shrimp/ prawn industry consists of distinct subsectors such as shrimp gher, shrimp hatcheries or post larvae (PL) collection, feed processing mills and shrimp processing and exporting plants. All these sub-sectors are linked together and constitute a horizontal integration of activities that create independent employment opportunities for males and females. Bangladesh Shrimp and Fish Foundation estimate that there are over 600,000 people employed directly in shrimp aquaculture who support approximately 3.5 million dependents [2].
Despite the rapid growth of Bangladeshi shrimp cultivation, the global frozen fish and seafood market continues to be dominated by Thailand, Indonesia, China and Ecuador. Significant innovations in production and processing in these countries have increased the value added associated with their exports and the market share that they command. Unfortunately, the same is not true for Bangladesh. Innovations in both production and processing have yet to be secured. Furthermore, stricter import requirements and compliance regulations in importing countries have meant that Bangladesh must invest in improving the safety and quality of their fish and seafood exports to avoid products being detained and rejected at point of entry into foreign markets. IFPRI (2003) report notes that: “The only way Bangladesh can improve its export position in the shrimp market is to improve the safety and quality of its exports.” “Roughly 33 per cent of the shrimps grown in Bangladesh are exported” told by [3]. Though shrimp fetch a large amount of foreign exchange through exports, it is not an.
Commercial shrimp culture has been dramatically expanded over the last three decades in the coastal zone of Bangladesh [4]. In FY 2016-17, the total amount of production from shrimp farm including secondary crop fish and crab was 246406 MT in Bangladesh with a significant growth rate of 2.76% [5]. Shrimp is the second most important export items in Bangladesh. The major shrimp-producing districts are Bagerhat, Satkhira, Pirojpur, Khulan, Cox’s Bazar and Chittagong. Among them, Chittagong, Cox’s Bazar, Khulna, Bangerhat and Satkhira districts are the main centers of shrimp culture [6]. Although several species are available in the coastal regions, Penaeusmonodon (locally known as bagdachingri) is the preferred species for cultivation as very high price in international markets. In Bangladesh, P. monodon comprises 60 % of farmed shrimp production, followed by the giant freshwater prawn, Macrobra chiumrosenbergii (galdachingri), which accounts for25 % of production [7] and [8]. Thus,of the fishery commodities exporting shrimps like Black Tiger (Penaeus Monodon) and fresh water scampi (Macrobrachium Rosenbergii) bring the most of foreign currency in this sector. Traditional ‘Gher’ (shrimp farming ponds which are converted from rice field) aquaculture had been practiced in the coastal region of Bangladesh to grow shrimp and other fishes long before the introduction of current shrimp farming practices.
In the Second Five-Year Plan (1980-1985), the government of Bangladesh acknowledged shrimp farming as an industry and adopted measures essential for increased shrimp production [9]. After that the production grew exponentially and the area covered by production was 22,000 ha in 1980 that increased to almost double (276,000 ha) in 2013[10] and [11]. Total shrimp production takes place from three sources, namely inland capture, inland culture and marine fisheries. In 1990–1991, total shrimp production was 80,384 tons in which cultured shrimp contributed 24 %. But, in 2010–2011, the total shrimp production increased to 306,168 tons of which cultured shrimp contributed 47.71 %. That means the shrimp production share from the culture sources increased by 23.47 % as compared to 1990–1991 [12].The economic incentives encourage farmers to bring thousands of acres of lands under shrimp farms [13].
1. To describe the socio-economic profile of shrimp farmers;
2. To find out the factors influencing farmers’ profitability of the shrimp farming in the study area;
Name of the district |
Name of the upazila |
Sample size |
Bagerhat |
Bagerhat Sadar |
30 |
Rampal |
30 |
|
Khulna |
Paikgacha Upazila |
30 |
Dumuria Upazila |
30 |
|
Total |
120 |
In this equation, Y*ij is a multinomial variable with subscript I depicting the farmers who profited to shrimp farming and j depicting profitability. Xk represents the vector of exogenous explanatory variables that influence the farmers’ profitability shrimp farming and k in the subscript shows the specific explanatory variable. The symbol α denotes the model intercept, βk the vector of multinomial logistic regression coefficients and ↋Y*ij is the error term which is normally distributed and homoscedastic.
Prior to the study, a multinomial logistic regression modeling approach was proposed to base on literature where most of the previous studies of farmer’s profitability of shrimp farming employed multinomial logistic regression model, the farmers are restricted to select one from a given set of profitability. Furthermore, the set of explanatory variables influencing the respondents’ decision was also expected to be different for different farmer’s profitability of shrimp farming. Therefore, we used the multinomial logistic regression model to identify the factors that affect the farmer’s profitability of shrimp farming. Table 2 shows the description and expected signs of explanatory variables used in this study.
Explanatory variable |
Mean |
SD |
Description |
Age |
41.82 |
11.42 |
Continuous |
Level of education |
7.67 |
4.62 |
Continuous |
Family size |
4.34 |
1.38 |
Continuous |
Credit received |
110.86 |
30.85 |
Continuous |
Income from shrimp farming |
258.37 |
117.92 |
Continuous |
Experience in shrimp cultivation |
13.61 |
7.41 |
Continuous |
Adopter |
1.38 |
0.48 |
Dummy, takes the value of 1 if adopter and 0 otherwise |
Training on shrimp cultivation |
2.75 |
1.83 |
Continuous |
Land under shrimp cultivation |
0.8060 |
0.60 |
Continuous |
Organizational participation |
3.61 |
3.24 |
Continuous |
Dependent variable |
Mean |
SD |
Description |
Profitability of shrimp farming |
0.56 |
0.499 |
Dummy, takes the value of 1 if yes and 0 otherwise |
We assessed determinants overall farmer’s profitability of shrimp farming. We modeled farmer’s profitability of shrimp farming using a profitability index. Using multinomial logistic regression models, the farmer’s profitability of shrimp farming index was regressed on a set of explanatory variables to access determinants of profitability of shrimp farming. Therefore, many factors are likely to influences farmer’s profitability of shrimp farming.
Then, we modeled individual farmer’s profitability of shrimp farming in order to get better assess the influences associated with profitability. Our dependent variables in this aspect were farmer’s profitability. Its strategy was a dummy variable equal to 1 if a farmer grain profitability from shrimp farming and 0 if otherwise.
In the second step, to test the overall significance of models, we used a global null hypothesis approach. For this analysis, we established a null hypothesis by assuming and setting all the regression coefficients of multinomial logistic regression models equal to zero versus the alternative that at least one of the regression coefficients (βk) is not zero.
H0: βk =0,
H1: at least one βk ≠0.
This approach is the same as the F test for model testing in OLS regression. This test checks whether the model with predictors, fits significantly better than the model with just an intercept.
The test statistic is calculated by taking the difference of the residual deviance for the model with predictors or explanatory variables from the null deviance of intercept-only model. The test statistic is distributed χ2 with a degree of freedom that is equal to the differences between the number of variables in the model with predictors and intercept-only model.
From the Table 3, it can be examined that χ2 values for all profitability models are positive. The associated p values are less than 0.001 which it can be concluded that our models with predictors fit significantly better than the intercept-only model. Hence, on the basis of test statistics, we can reject the null hypothesis (H0) and accept the other alternative hypothesis (H1) that at least one of the regression coefficients (βk) is zero.
Further, we calculated the Nagelkerke R2 measure to determine the correctness of fit of our profitability models. The values of Nagelkerke R2 for all models are 0.294 which indicates a better fit of our models in explaining farmer’s profitability of shrimp farming.
Models |
χ2 |
Degree of freedom |
p value |
-2log likelihood |
Cox & Snell R2 |
Nagelkerke R2 |
McFadden |
Profitability of shrimp farming |
29.767 |
11 |
0.000 |
134.951 |
0.220 |
0.294 |
0.181 |
With respect to socio-economic features of the farmers, the shrimp farmers were classified into three age categories such as young, middle and old aged. Out of the total farmers 20 percent belonged to the young, 48.3 percent belonged to the middle and 31.7 percent fell into the old aged. Out of 120 farmers, 10 percent farmers had illiterate, 26.7 percent farmers had completed primary education, 40.8 percent farmers had completed secondary level of education, and 22.5 percent farmers had completed their above secondary level of education. Data showed that the highest proportion (67.5%) of the farmers fell into the medium family of 4-6 members, while (26.7%) of them fell into the small family size of 2-3 members and (5.8%) fell into the large family size of above 6 members. About 2.5% farmers were taken loan from Banks, 20% farmers were taken credit from NGOs and no farmers were taken loan from their relatives as reported by the farmers and 77.5% farmers were used their own funding. About 50% of the shrimp farmers had earned Tk. 100,000 to 200,000 per year, 15.8 percent of the farmers had earned Tk. less than 100,000 per year and 34.2 percent farmers had earned Tk. above 200,000 per year. Data revealed that the majority (60.2%) of the farmers had medium experience as compared to (15.8%) and (20.8%) having high and low experience respectively. Data revealed that the majority (67.5%) of the farmers had adopter and (32.5%) had non-adopter respectively. Data indicated that the majority (53.3%) of the farmers had low training on shrimp farming that comprised by 36.7% and 4.2% farmers have low training and medium training on shrimp farming. Only (5.8%) of the respondents had high training on shrimp farming. Data revealed that 73.3%, 25.9% and 0.8% of the farmers had small land, medium land and high land respectively. The data indicated that the majority (50.8%) of the farmers had no organizational participation and 49.2 percent farmers had organizational participation.
Characteristics |
Percent (%) |
Age |
|
Young (18-30 years) |
20.00 |
Middle (31-45 years) |
48.3 |
Old (Above 45 years) |
31.7 |
Education |
|
Illiterate/can sign only( 0 ) |
10 |
Primary level( 1-5 ) |
26.7 |
Secondary level( 6-10 ) |
40.8 |
Above secondary level( >10 ) |
22.5 |
Family size |
|
Small (2-3) |
26.7 |
Medium (4-6) |
67.5 |
Large (above 6) |
5.8 |
Credit received |
|
Banks |
2.5 |
NGOs |
20 |
Relatives |
0 |
Own funding |
77.5 |
Income |
|
Less than 100,000 |
34.2 |
100,000 to 200,000 |
15.8 |
Above 200,000 |
50 |
Experience in shrimp farming |
|
Low experience (3-7) |
20 |
Medium experience (8-21) |
60.2 |
High experience (above 21) |
15.8 |
Adopter |
|
Adopter (1) |
67.5 |
Non-adopter (2) |
32.5 |
Training on shrimp farming |
|
No training (0) |
36.7 |
Low training (1-5) |
53.3 |
Medium training (6-10) |
4.2 |
High training (above 10) |
5.8 |
Land under shrimp farming |
|
Small (0.13-1 ha) |
73.3 |
Medium (1.01-3 ha) |
25.9 |
Large land (above 3 ha) |
0.8 |
Organizational participation |
|
No participation (0) |
50.8 |
Participation (1) |
49.2 |
Explanatory variables |
Profitability of shrimp farming |
||||
B |
Std. Error |
Wald |
Sig. |
Exp(B) |
|
Age |
0.025 |
0.023 |
1.131 |
0.088* |
0.976 |
Level of education |
0.136 |
0.052 |
6.893 |
0.009*** |
0.873 |
Family size |
0.348 |
0.174 |
4.001 |
0.045** |
0.706 |
Credit received |
0.007 |
0.008 |
0.613 |
0.434 |
0.993 |
Income from shrimp farming |
0.001 |
0.002 |
0.190 |
0.663 |
0.999 |
Experience in shrimp farming |
0.063 |
0.035 |
3.313 |
0.029** |
1.065 |
Adopter |
0.320 |
0.455 |
0.494 |
0.482 |
0.726 |
Training on shrimp farming |
0.028 |
0.050 |
0.309 |
0.578 |
1.028 |
Land under shrimp farming |
-0.128 |
0.362 |
0.125 |
0.723 |
0.880 |
Organizational participation |
-0.285 |
0.093 |
9.500 |
0.002*** |
0.752 |
- Barmon BK, Kondo T and Osanami F. Impact of Rice-Prawn Gher Farming on Agricultural and Household Income in Bangladesh: A Case Study of Khulna District. Journal of Bangladesh Studies (JBS). 2004; 6(1&2): 51-61.
- Islam MS and Mahmud Y. Mixed Culture Technique of Golda and Mono-sex Tilapia in the Coastal Region. Bangladesh Fisheries Research Institute (BFRI). Shrimp Research Centre, Bagherhat-9300. 2011.
- Haque E. Sanitary and Phyto-Sanitary Barriers to Trade and its Impact on the Environment: The Case of Shrimp Farming in Bangladesh. Trade Knowledge Network Paper. The International Institute for Sustainable Development, Manitoba, Canada. 2004;
- Islam MR and Tabeta S. Impacts of Shrimp Farming on Local Environments and Livelihoods in Bangladesh. International Journal of Environmental Science. 2016; 1: 48-51.
- DoF. Yearbook of Fisheries Statistics of Bangladesh 2016-17. Fisheries Resources Survey System (FRSS), Department of Fisheries. Bangladesh: Director General, DoF. 2017; 34: 129.
- Belton, B. Review of aquaculture and fish consumption in Bangladesh: studies and reviews 2011-53. The World Fish Center.
- Rosenberry B. World shrimp farming, Annual report. Shrimp news international, San Diego. 1995;
- Ahmed N. Environmental impacts of fresh water prawn farming in Bangladesh. Shellfish News. May 2003; (15): 25–28.
- Haque SM. Annual report of Bangladesh Frozen Foods Exporters Associations (BFFEA). BFFEA Special Bulletin, Dhaka. 1994;
- Fisheries Resources Survey System (FRSS) Fisheries statistical yearbook of Bangladesh. Department of Fisheries, Bangladesh. 2012; 28.
- Kabir SH. Sea food export from Bangladesh and current status of traceability. 2013;
- Islam SMD and Bhuiyan MAH. Impact scenarios of shrimp farming in coastal region of Bangladesh: An approach of an ecological model for sustainable management. Aquaculture International. Aug 2016; 24(4): 1163–1190, doi: 10.1007/s10499-016-9978-z.
- Rahman MC, Salam MA, Rahman NMF, Rahman MM and Hossain MM. Present Status and Potentiality of Shrimp in Bangladesh. Australian Journal of Basic and Applied Sciences, 2013; 7(7): 281–286.
- Rakib TM, Kabir MH, Islam MR, and Islam MS. Profitability of Vegetable Cultivation by the Integrated Pest Management (IPM) Farmers. American Journal of Agricultural Research. 2019; 4: 60.