CC BY
188
DOI https://doi.org/10.18551/rjoas.2018-11.45
ESTIMATION OF HOUSEHOLD CONSUMPTION EXPENDITURE OF SMALL-SCALE
FISHERMEN IN INDONESIA
Rahim A., Hastuti D.R.D.
Faculty of Economics, University of Negeri Makassar, Indonesia
Bustanul N.
Faculty of Agriculture, University of Hasanuddin, Indonesia
*E-mail: abd.rahim@unm.ac.id ORCID: 0000-0002-1720-7150
ABSTRACT
One of the causes of changes in household consumption expenditure of small-scale fishermen in Indonesia is the change of catches production and catching business income resulting from seasonal changes every year. Changes in household consumption expenditures are certainly influenced by the determinants. Based on the time dimension, this paper uses cross-sectional data sourced from primary data with the respondents of outboard motor fishermen and non-powered motor. The econometric analysis of multiple linear regressions with the classical assumption test is used in this method. The determinants of expenditure for household consumption of outboard motor are positively influenced by the number of family members covered and the difference in the area of residence of the fisherman and negatively by the household income, whereas the wife's formal education has no significant effect. In contrast, household consumption expenditures of non-powered motor fishermen are positively influenced by household income and are negatively influenced by wife education and regional differences, while the number of family members borne has no significant effect.
KEY WORDS
Household expenditure, small-scale fisherman, outboard motor, non-powered motor, Indonesia.
International fisheries policy through the Committee on Fisheries (COFI) and Subcommittee is to support the sustainable development and safeguard of small fisheries in the context since small-scale fisheries produce two-thirds of all targeted catches for direct human consumption and provide 90% of employment in this sector (Food and Agriculture Organizations, 2016), while the objective of fisheries development in Indonesia is to improve the welfare of fishermen, fish farmers and other coastal communities (Keputusan Menteri Kelautan dan Perikanan No.18/Men/2002) through the development of economic activities, quality improvement and quantity of human resources, strengthening of socio-economic institutions, and utilize marine and fishery resources in an optimal and (Keputusan Menteri Kelautan dan Perikanan No.18/ Men/2004).
In particular traditional fishermen are small-scale fishermen (Al-Marshudi and Kotagama, 2006; Andrew and Evans, 2009; Lopes and Begossi, 2011; Gebremedhin et al., 2013) or artisanal fisheries (Mozumder, et.al., 2018) characterized as poor and marginalized (Asiedu, et al., 2013), but these small-scale fisheries support the livelihoods and wellbeing of more than 500 million people worldwide and as an important source of income in developing countries where millions of poor people live near the coast and nearly 97% of world's fishermen are located (Pomeroy and Andrew, 2011; Mauthe et al., 2013) of the 36 million fishermen in the world (Mohammed, et al., 2017) In Indonesia, the fishing population is dominated by small-scale fishermen (Susanto et.al., 2017), 95% of traditional fishermen (Sudarmo et al., 2015).
Small-scale fishermen consist of outboard motor and non-powered motor while modern fishermen are using motor boats (Gebremedhin et al., 2013) using catching technology in the form of outboard engines (Ele and Nkang, 2014) and simple fishing gear (Rahim and Hastuti, 2017; Rahim et al., 2018), whereas according to Law no. 45 of 2009 on fisheries in Indonesia that small-scale fishermen are small fishermen with the size of fishing vessels owned by the largest 5 gmsstonase (GT).
Most of the small-scale fishermen in Indonesia are found in coastal areas (Rahim and Hastuti, 2018; Rahim, 2018) and become one of the economic development sections of the coastal zone (Israel et al., 2004). Although part of economic development, however, the level of welfare is still below other sectors and generally occupy the lowest strata compared to other communities on land, even as marginalized groups (Asiedu, et al., 2013) because it belongs to the poorest groups in all countries with the attributes of "the poorest of poor" (Wiyono and Mustaruddin, 2015), ironically 32.14% of the 16.42 million people in coastal communities in Indonesia are alive below the poverty line with an income indicator of US $ 1 per day (Muflikhati et al., 2010) or with per capita income per month US $ 7-10 (Agunggunanto, 2011).
The case in this research is the change of expenditure for the consumption of small-scale fishermen in West coastal area of Barru District South Sulawesi Province Indonesia caused by the change of catching production and catching income (Rahim and Hastuti, 2017). Research on household consumption expenditure of fishermen has been done in many countries, as reported by Israel et al., (2004) in the Philippines, Mukarrama et al., (2010) in Sri Lanka, Khan et al., (2012) in Bangladesh, Ofwona (2013) in Kenya, Olamedji et al., (2015) in Nigeria, as well as in Indonesia itself (Zamroni and Yamao, 2011; Zulkifli et al., 2015). However, the findings have not yet discussed the determinant or factors that affect the change in household consumption expenditure of small-scale fishermen.
In economics, household consumption expenditure is financial planning (Tapsin and Hepsa, 2014) considered the primary indicator of the welfare economy (Moratti and Natali, 2012) and the most important component of national income and aggregate demand (Khan, 2014). Furthermore each household seeks to maximize utility in consuming goods and services with income levels as constraints (Carrol, 2001), which refers to an independent household decision (Bonke, 2015). In general, changes in consumption are influenced by changes in income (Carrol, 2001; Ofwona, 2013), net income and time-discount rate, leisure, wealth or assets (Branson, 1989), while changes in household consumption expenditures are microeconomically affected by age, income, marital status, insurance and household size (Caglayan and Astar, 2012), while macroeconomically influenced by price level changes that have the effect of real income and real exchange rate (Bonsu and Muzindutsi, 2017).
The purpose of this paper is to estimate the consumption expenditure of small-scale fishermen households using econometric approach with a qualitative independent variable determinant model in the West coastal area of Barru District, South Sulawesi Province, Indonesia as the case study.
MATERIALS AND METHODS OF RESEARCH
We used an Explanatory method for estimate of small-scale catch fishermen household consumption expenditure in Indonesia. Cross-Section data from a household fishermen survey. Questionnaires were administered to 107 of 586 total respondents, including 69 of outboard motor and 38 of non-powered motor boats. Number of sample about 10-20% of total respondents (Gay and Diehl, 1992)
We used a multiple regression method with exponential functions model for analyzed estimate of small-scale catch fishermen household consumption expenditure using econometric approach of qualitative independent variable (dummy variable) with method of analysis with non linear regression equation: (Gujarati and Porter, 2009).
CRTNPM = p0 nRTNPM^AEdlstr^QAKT^KTR slKBszKSRSiKBLsSi^ (1)
CRTNPTM = ft nRTNPM^AEdlstr^QAKT^KTR^KB^KSR^KBLs® (2)
To facilitate the computation of equations (1) and (2) models, the equations are converted to multiple linear by double log or natural logarithms (Ln) as follows:
LnCRTNPM = Lnp0 + p2LnnRTNPM + p3LnEdIstr + P^LnQAKT + StKTR + dKB + d^KSR + SAKBls + (3)
LnCRTNPTM = Lnps + p6LnnRTNPM + P7LnEdIstr + paLnQAKT + S5KTR + S6KB + S7KSR + SaKBLs + (4)
Where, LnCRTNPM : household consumption expenditure fisherman outboard motor boats on food and non-food (IDR); LnCRTNPTM: household consumption expenditure fisherman non-powered motor on food and non-food (IDR); and fis : intercept; Pa and independent variable regression coefficients; d,..., d8: dummy variable coefficient; nRTNPM: household income of fishermen outboard motor (IDR); nRTNPTM: household income of fishermen non-powered motor (IDR); Edlstr: wife education (years); QAK: the number of dependent family members (people); Dummy small-scale fishermen regional differences; KTR: 1, for the District of Tanete Rilau; 0, for the other; KB: 1, for the District of Barru; 0, for the other; KSR: 1, for the District of Soppeng Riaja; 0, for the other; KBLs: 1, for the District of Balusu; 0, for the other; dan error term
RESULTS AND DISCUSION
Determinant or factors affecting household consumption expenditures of outboard motor and non-powered motor in the western coastal area of Barru District in addition to using multiple regression analysis models also used classical assumption assumptions of multicollinearity and heteroscedasticity (Table 1). The results of multicollinearity testing with Gujarati and Porter (2009) variance inflection factor (VIF) method do not show or indicate multicollinearity or double collinearity, VIF values less than 10 (Table 1). As for heteroscedasticity testing using park test (Gujarati and Porter, 2009), variable error as dependent variable with each independent variable and produce coefficient value (P) is not significant it can be concluded there is no heteroscedasticity (Table 1).
Table 1 - Determinant of Household Consumption Expenditure of Small-scale Fishermen
Independent Variable E.S Outboard Motor Non powered Motor
P t-test VIF Park P t-test VIF Park
Household income + -0,276*** -4,692 1,445 0,017 ns -0,086*** -3,334 1,101 -8,827 ns
Education wife + 0,013 1,521 1,522 -0,014 ns 1,011*** 40,921 1,335 -0,939 ns
Members of the family + 1,475*** 32,007 1,201 0,065 ns 0,031 1,261 1,028 0,941 ns
Tanete Rilau Sub-District + -0,028 -0,871 1,253 0,000 ns -0,011 -0,528 1,150 0,000 ns
Barru Sub-District + 0,020 0,709 1,334 0,000 ns 0,069** 1,967 7,082 0,000 ns
Soppeng Riaja Sub-District + -0,104* -2,143 3,393 0,000 ns -2,284*** 6,83 2,649 0,000 ns
Balusu Sub-District + 0,233* 1,887 1,882 0,000 ns 0,013 0,507 1,208 0,000 ns
Intercept -1,980 0,986
F-test 176,18 325,145
Adjusted R2 0,947 0,986
n 69 38
*** = Significant error rate of 1% (0.01), or 99% confidence level; ** = Significant error rate of 5% (0.05), or 95% confidence level; * = Significant error rate of 10% (0.10), or 90% confidence level; ns = not significant; ES is an expectation sign; If the VIF value is le'ss than 10 then there is no multicollinearity, otherwise If VIF value is greater than 10 then multicollinearity occurs ns => not significant; if p value is not significant, then it is not available heteroscedasticity, otherwise if the value of p significant, then there is heteroscedasticity.
In the measurement of the model accuracy of the adjusted R2 shows the independent variables in the expenditure function model for household consumption of outboard motor and non-powered motor the presented can explain each of the percentage of free variable contribution to household income, wife education, number of members (94.7%) and 98.6% of the variation (ups and downs) of non-free variables while the other by 5.3% and 1.4% respectively are contributions from other factors which is not included in the model (Table 1). The result of F-test that the factors influencing the expenditure for household consumption of outboard motor and non-powered motor significantly influence the error rate of 1 percent (Table 1). It can be interpreted that all independent variables together (simultaneously)
significantly affect the expenditure for household consumption of fishermen. Furthermore, individual influence (partial) from each independent variable to expenditure for household consumption of fisherman used t-test and regression coefficient value in the discussion.
Variable income of small-scale fisherman households either motor boat fisherman or motor boat without negative influence to household consumption expenditure at error rate of 1% or 99% confidence level, meaning that every change of household income increase hence the expenditure of capture fisherman household in coastal area West Coast of Barru District will decrease. This is due to the decline in demand for food items, and to switch to secondary non-food needs in the form of education, clothing, health, and the need for fishing (fuel and fish bait). If it is related to the theory of the elasticity of demand for income, then the change in income increase leads to a decrease in inferior good demanded (Henderson and Quant, 1980).
These findings are consistent with Kartika (2012) in Mataram City, that the higher the family income, the proportion of expenditure on food consumption declines, followed by an increase in the proportion of non-food expenditure. The results of this study are different from other research areas, ie, income has a positive effect on household consumption expenditure in Madura Strait (Primyastanto et al., 2013) and Donggala (Zulkifli et al., 2015) and Khan et. al. (2012) that the management of Community Based Fisheries (CBFM) in Bangladesh has a positive and significant impact on fishermen income and household expenditure. Changes in household income of fishermen will affect household expenditures derived from productive fishery conditions, such as those occurring in West Africa (Weigel et al., 2018), fishing season in Tamil Nandu, India (Colwella and Axelrod, 2016), and climate change in the West Pacific Palau (Wabnitz et al., 2018).
Empirically, the average expenditure for traditional fisherman household consumption expenditure in 5 sample sub-districts in Barru District y both food and non-food within a month, outboard motor fishermen (IDR 2.84 million = USD 218) and non-powered motor fishermen (IDR 1, 63 million = USD 125). Food consumption is the largest of non-food consumption, ie motor boat fishermen (IDR 1.8 million = uSd 138) and non-motorized boat fishermen (IDR 1 million = USD 130) in the form of rice, side dishes, gas / kerosene, cooking oil, tea / coffee, and sugar. According Primyastanto et al., (2013); Zulkifli et al., (2015) the amount of expenditure for household consumption of fishermen in Indonesia comes from food and non-food. These findings are consistent with findings in Donggala District (Zulkifli, et al., 2015) and Oladimeji et al., (2015) in Nigeria that 77% of total monthly fisheries household expenditure and the remaining 23% for non-food are in the form of payments for energy, clothing, health and education.
Unlike the case with findings Musemwa et. al., (2013) most household consumption expenditure in South Africa is used to buy food rather than agricultural production because in that area it does not explore its agricultural potential. According to Erdogen et al., (2011) food consumption, especially seafood is an important ingredient to improve intelligence in education and much needed parents, such as fish as the most inexpensive and affordable source of animal protein (Ogundari and Ojo, 2009). Furthermore, this finding is different from the findings that occurred in Sri Lanka that the expenditure for household consumption of fishermen has no effect on food security (Mukarrama et.al, 2010). According to Budiwinarto (2006) the greater the level of household income, the proportion of expenditure (consumption) for food is smaller than non-food, this is said to be the level of prosperity (welfare) of the economy getting better, as happened in Bangladesh that fishermen's welfare is determined by changes in household income and expenditure (Khan et al., 2012).
The education of wife without a motor has a positive effect on the change of household consumption expenditure at a 1% error level or 99% confidence level, meaning that the high level of formal education of wife will decrease the expenditure for fisherman household consumption in West coastal area of Barru District. This indicates that the existence of formal education wife can help manage the family finances both expenditure for food consumption and non-food. The benefits of education are investment (Psacharopoulos & Patrinos, 2002) for the increase of income and consumption and their welfare (Agarwal et al, 2009;
Rabearisoa and Norsi, 2013) because the higher the level of education, the decision will be more rational and lead to improved welfare economy of his family.
Another case education of outboard motor fishermen's wife does not significantly affect the changes in spending for household consumption of outboard motor fishermen both food and non-food expenditure. This happened because the average of formal education level of traditional fisherman wife of Barru District is not 55 (51,40%) primary school, followed by junior high level 29 (27,10%), elementary 17 soul (15,89%), senior high school as many as 6 people (5.61%), and college does not exist. This research is in line with Ningsih et al., (2013) study that education level has no significant effect on food consumption pattern and fisherman household fishery in Tungkal Ilir Sub-district, Tanjung Jabung Barat District, and the level of education of women in fishery households in Vietnam is lower so that little chance to work in processing fish despite having access to credit (Hao, 2012).
The variable of the quantity of family members who bear the positive effect of the expenditure for household consumption, meaning the more the number of family members there is a tendency of spending for household consumption more and more. Another case expenditure for household consumption of non-powered motor is not affected by the number of family members borne. This study is different from the findings of Lantika (2009) that the number of family members has a negative effect on household consumption in Samaan Malang City. The quantity of family members who will use a small amount of income will result in low levels of consumption because the number of family dependents will encourage fishermen to work hard to meet the needs of family members (Rahim and Hastuti, 2017). This affects the productivity of work, intelligence and declining ability to invest so as to affect the level of welfare, such as Roumah (2015) findings on coastal fishing communities in Malaysia, that the size or number of family members will greatly determine the poverty of fishermen other than income, Education, and marital status.
Empirically, the quantity of family members in the household of motor boat fishermen of Barru District consisting of his wife and children and other family members between 1 - 5 people who live in a fisherman's household thus affect the changes in household consumption expenditure such as food needs (rice, side dishes, cooking oil, kerosene, gas, sugar, tea and coffee), non-food (education, clothing, health, and the necessities of fishing like fuels and fish baits).
Dummy of differences in the areas where have a positive and negative impact on household consumption expenditure of fishermen in the western coastal area of Barru District at error rate of 1%, 5% and 10% as a comparison of the high or low expenditure consumption of traditional fishermen. Empirically, the consumption expenditure per subdistrict within a month, that is the motor boat fisherman of Barru District as the capital of Barru District (IDR 3.1 million = USD 238) is bigger than the fishermen of Tanete Rilau Subdistrict (IDR 1.6 million = USD 123) and more small from Balusu sub-district fishermen, IDR 3.6 million = USD 276. Unlike the case of the consumption of non-motorized boat fishermen in Kecamatan Barru (IDR 1.6 = USD 123) smaller than Soppeng Riaja fishermen (IDR 1.8 million = USD138) and Mallusetasi (IDR 1.9 million = USD 146). This result is different from the Saptanto et al., (2011) study by comparing the amount of food and non-food household expenditure of each coastal fisherman in each sub district in Indramayu without using dummy variable regression determinant model such as this research.
Coastal fishing communities are a group of people living in coastal areas forming and having a distinctive culture associated with its dependence on the utilization of coastal resources in conducting economic activities (Fahrunnisa, 2015). This refers to the opinion of Ostorm and Hess (2007), that coastal coastal communities have rights over common property resources that provide the benefits and efficiency of the sustainability of existing resources. The role of common property provides (1) important roles in livelihoods, (2) minimizes the possibility of disputes or conflicts, and (3) shapes the community into a compact and control of shared resources (Fahrunnisa, 2015).
CONCLUSION AND RECOMMENDATIONS
Expenditures for household consumption of outboard motor small-scale fishermen are positively influenced by the number of family members covered and the different areas of the fisherman's residence, and then negatively influenced by household income, whereas the wife's formal education has no significant effect. Another case, household consumption expenditure of non-powered motor fishermen is positively influenced by household income and is negatively influenced by wife education and regional differences, while the number of family members covered is not significant
The increase in household income of outboard motor fishermen decreased their consumption expenditure, as a result of greater food consumption of non-food consumption. This is done by continuing to improve the pattern of food through subsidized rice distribution program or poor rice (raskin), especially during famine season (west season). In terms of education, the low education of the wife of outboard motor fishermen and non-powered motor so that consumption expenditures tend to not change in terms of quality because the income only comes from the sale of fish. Therefore, it is necessary to optimize the role of fishermen wife through the strategy of developing productive economy through empowerment program of fisherman wife such as cultivation of fish catch, fish cracker, fish meal and so on.
REFERENCES
1. Agarwal S., Rahman S., & Errington E. (2009). Measuring the determinants of relative economic income of rural areas. Journal of Rural Studies, 25, 309-321
2. Agunggunanto, E.Y. (2011), Analisis Kemiskinan dan Pendapatan Keluarga Nelayan Kasus di Kecamatan Wedung Kabupaten Demak, Jawa Tengah, Indonesia, Jurnal Dinamika Ekonomi Pembangunan, 1(1), 25-38
3. Al-Marshudi A.S., & Kotagama H. (2006). Socio-Economic Structure and Performance of Traditional Fishermen in the Sultanate of Oman. Journal of Marine Resource Economics, 21, 221-230.
4. Andrew N, & Evans. (2009). Approaches and Frameworks for Management and Research in Small-scale Fisheries in the Developing World. The World Fish Center Working Paper 1941. The World Fish Center, Penang, Malaysia
5. Asiedu B., Nunoo, F.K.E., Ofori-Danson, P.K., Sarpong, D.B., & Sumaila, U.R. (2013). Poverty Measurements in Small-scale Fisheries of Ghana: A Step towards Poverty Eradication. Current Research Journal of Social Sciences. 5(3),75-90
6. Barnes-Mauthe M, Oleson KLL., & Zafindrasilivonona B. (2013). The total economic value of small-scale fisheries with acharacterization of post-landing trends: An application in Madagascar with Global Relevance, Journal of Fisheries Research 147: 175-185.
7. Budiwinarto, K. (2006). Penerapan Model Almost Ideal Demand System (AIDS) pada Pola Konsumsi Pangan Rumah Tangga Nelayan di Kecamatan Tambak Kabupaten Banyumas, Fakultas Ekonomi Universitas Surakarta
8. Bonke, J. 2015. Pooling of Income and Sharing Of Consumption Within Households. Review of Economics of The Household. 13(1):73-93
9. Bonsu, C.O., And Muzindutsi, P. 2017. Macroeconomic Determinants of Household Consumption Expenditure in Ghana: A Multivariate Cointegration Approach. International Journal of Economics and Financial. 7(4):737-745.
10. Branson, W.H. (1989). Macroeconomic Theory and Policy, 3th edition. Harper and Row Publisher, New York.
11. Ele, I.E, & Nkang MO. (2014). Analysis of Production Determinants and Technical Efficiency In Crayfish Production In The Lower Cross River Basin. Nigeria, Journal of Research In Humanities and Social Science. 2(11): 30-36
12. Caglayan, E., & Astar, M. (2012). A Microeconometric Analysis of Household Consumption Expenditure Determinants For Both Rural and Urban Areas In Turkey. American International Journal of Contemporary Research. 2(2):27-34
13. Carroll, C.D. (2001). A Theory of the Consumption Function, With and Without Liquidity Constraints. Journal of Economic Perspective. 23-45
14. Colwella, J.M.N., Axelrod, M. (2016). Socio-Economic Impacts of a Closed Fishing Season on Resource-Dependent Stakeholders in Tamil Nadu, India: Differences in Income and Expenditure Effects by Occupational Group. Marine Policy. 77: 182-190
15. Erdogan, B.E., Mol, S. Co§ansu, S. (2011). Factors Influencing the Consumption of Seafood in Istanbul, Turkey. Turkish Journal of Fisheries and Aquatic Sciences 11: 631639.
16. Fahrunnisa, Azhar, H., Muswar H.S, Miharja H.A., & Fahmi A. (2015). Dilema Agraria Pesisir (Studi Kasus Masyarakat Pesisir Dusun Ujung Genteng Kabupaten Sukabumi). Jurnal Sosiologi Pedesaan. 3 (3): 107-113.
17. Food and Agriculture Organization. (2016). Sustainable Small-Scale Fisheries. Fisheries and Aquaculture Department.
18. Gay, L.R., & Diehl, P.L. (1992). Research Methods for Business and Management. Publishing Company, New York
19. Gebremedhin S, Budusa M, Mingist M, & Vijverberg J. (2013). Determining Factors For Fishers' Income: The Case Of Lake Tana, Ethiopia. International Journal of Current Research. 5 (5):1182-1186.
20. Gujarati, D.N. and Porter, D.C. (2009), Basic Econometrics, 5th edition.McGraw-Hill, American
21. Hao, N.D. (2012). Gender Issues in the Fishery Communities of the Central Coastal Provinces of Vietnam. Asian Fisheries Science
22. Henderson, J.M., Quant, R.E. (1980). Microeconomic Theory (A Mathematical Approach) Third Edition, McGraw-Hill, New York
23. Israel DC, Adan, E.Y, Lopez, N.F., & Castro, J.C. (2004). Perceptions of Fishermen Households On The Long-Term Impact of Coastal Resources Management In Panguil Bay Philippine. Journal of Development. 31 (1):107-134
24. Kartika, I.B.E. (2012). Analisis Pola Konsumsi Masyarakat Berdasarkan Tingkat Pendapatan dan Jumlah Anggota Rumah Tangga di Kota Mataram, Jurnal Ekonomi,: 2(3) 25-31
25. Keputusan Menteri Kelautan dan Perikanan Nomor 18/Men/2002, Tentang Rencana Strategis Pembangunan Kelautan Perikanan Tahun 2002-2004, Jakarta
26. Keputusan Menteri Kelautan dan Perikanan Nomor 18/Men/2004, Tentang Program Pemberdayaan Ekonomi Masyarakat Pesisir, Jakarta
27. Khan, A., Alam, F., & Islam, K.J. (2012). The Impact of Co-Management on Household Income and Expenditure: An Empirical Analysis of Common Property Fishery Resource Management In Bangladesh. Ocean & Coastal Management. 65: 67-78.
28. Khan, H. (2014). An Empirical Investigation of Consumption Function under Relative Income Hypothesis: Evidence from Farm Households in Northern Pakistan. International Journal of Economic Sciences. 3(2):43-52
29. Lopes, P.F.M, & Begossi, A. (2011). Decision-Making Processes By Small-Scale Fishermen On The Southeast Coast of Brazil. Journal Fisheries Management And Ecology. 2(3):1-11
30. Long, L.H., & Yabe., M. (2011). Factors Affecting to Household Income of The Kinh and The Ethnic Minority in Rural Vietnam: A Case Study in The Buffer Zone of Bach Ma National Park. Asian-African Journal of Economics and Econometrics. 1 (11):135-145.
31. Muflikhati, I., Hartoyo, Sumarwan, U., Fahrudin, A., Puspitawati, H. (2010). Kondisi Sosial Ekonomi dan Tingkat Kesejahteraan Keluarga: Kasus Di Wilayah Pesisir Jawa Barat. Jurnal Ilmu Kel. & Kons. 3(1): 1-10
32. Mukarrama, M.M.F., Udugama, J.M.M., Jayasinghemudaligae, U.K., Ikram, S.M.M., .& Dissanayake., S.N. (2010). Assessing the Household Food Security of Marine Fisheries Sector in Sri Lanka: Case of Muslim Fishing Community in the Beruwala Divisional Secretariat Division. Journal Aquatic Science. 61-73.
33. Musemwa, L., Zhou, L., Ndhleve, S., & Aghdasi, F. (2013). Factors Affecting Household Access To Enough Food In the Eastern Cape Province of South Africa. Journal of Development and Agricultural Economics, 5(3), 84-91. DOI: 10.5897/JDAE12.039
34. Mohammed, K.K., Dash, G., Kumari, S., 1, Sreenath, K.R1, Makwana, N.P., Dash, S.S., Ambrose T.V., Shyam, Shyam, S., Kripa, Zacharia,V., Zacharia, P. U. (2017). Vulnerability of Coastal Fisher Households to Climate Change: A Case Study from Gujarat, India. Turkish Journal of Fisheries and Aquatic Sciences 17, 193-203. DOI: 10.4194/1303-2712-v17_1_21
35. Moratti, M. & Natali, L. (2012). Measuring Household Welfare: Short versus long consumption modules. Working Paper 2012-04. UNICEF Office of Research, Florence
36. Mozumder, M.M.H., Shamsuzzaman, M., Un-Nabi, R., & Al-Rashid, A.H. (2018). SocioEconomic Characteristics and Fishing Operation Activities of the Artisanal Fishers in the Sundarbans Mangrove Forest, Bangladesh. Turkish Journal of Fisheries and Aquatic Sciences. 18, 789-799. DOI: 10.4194/1303-2712-v18_6_05
37. Ofwona, A.C. (2013). Determinant of the Consumption Function for Kenya Using Keynes' Absolute Income Hypothesis for the Period 1992-2011. Journal of Emerging Trends in Economics and Management Sciences (JETEMS), 4(1),103-105
38. Ogundari, K., & Ojo, S.S. (2009). An Examination of Income Generation Potential of Aquaculture Farms in Alleviating Household Poverty: Estimation and Policy Implications from Nigeria. Turkish Journal of Fisheries and Aquatic Sciences, 9, 39-45
39. Oladimeji, Y.U., Abdulsalam, Z., Damisa, M.A., & Omokore, D.F. (2015). Analysis of Food Consumption Pattern among Rural Fishery Households: A Panacea to Poverty Alleviation in North Central Nigeria. Asian Journal of Agricultural Extension, Economics & Sociology. 6(2), 102-110
40. Ostorm, E., & Hess, C. (2007). Private and Common Property Rights. Workshop in Political Theory and Policy Analysis, Indiana University. W07-25.
41. Pameroy, R.S., & Andrew, N.L. (2011). Small-Scale Fisheries Management: Frameworks and Approaches for the Developing World. CPI Antony Rome, Chippenham
42. Psacharopoulos, G, & Patrinos, H.A. (2002). Returns to investment in education. A further update. Policy Research Working Paper No 2881. Washington, D.C. World Bank, Education Sector Unit, Latin America and the Caribbean Region, 36 pp
43. Rabearisoa, A.L., & Zorzi, E. (2013). An Economic Return To Education In Small-Scale Fisheries In North-East Madagascar. Western Indian Ocean J. Mar. Sci. 12 (2):185-188
44. Rahim, A., and Hastuti, D.R.D. (2017). Demand Estimation of Fresh Sea Fish with Panel Data Model. Proceeding. The 1st International Conference On Education, Science, Art and Technology (The 1st ICESAT) Universitas Negeri Makassar. 1(1): 279-287.
45. Rahim A, (2018). The Empowerment Strategy of The Traditional Fisherman's Wives In The Coastal Area of Barru Regency, South Sulawesi. Journal of Socioeconomics and Development. 1(1): 1-6
46. Rahim, A., and Hastuti, D.R.D. (2018). Applied Multiple Regression Method with Exponential Functions: an Estimation of Traditional Catch Fishermen Household Income. Journal of Physics: Conference Series. 1028(1), 1-8.
47. Rahim, A., Hastuti, D.R.D., Ningsih, S.R., Mardia, Nuryanti, D.M., Patta, A.A., Yatim, H., and Hayat, N.Z. 2018. The Influence of Marketing Volume and Marketing Channel on Fresh Tiger Shrimp Marketing Margin. Indonesian Journal of Fundamental Sciences. 4(1):16-23
48. Rhoumah, A.M.O. (2016). Determinants of Factors That Affect Poverty among Coastal Fishermen Community in Malaysia. Journal of Economics and Finance. 7(3):9-13. http://doi/10.9790/5933-0703020912
49. Primyastanto, M., Efani A., Soemarno, & Muhammad, S. (2013). Faktor Yang Berpengaruh Terhadap Pendapatan dan Pengeluaran Nelayan Payang Jurung Di Selat Madura. Wacana. 16 (1):15-23
50. Saptanto S., Lindawati, & Zulham A. (2011). Analisis Pola Migrasi Dan Konsumsi Rumah Tangga Di Daerah Asal Migrasi Terkait Kemiskinan Dan Kerentanan Pangan (Studi Kasus Indramayu). Jurnal Organisasi dan Manajemen. 7 (1): 21-37
51. Sudarmo, A.P., Baskoro,M.S., Wiryawan,B., Wiyono, E. S., & Monintja., D.R. (2015). Social Economics Characteristics of Coastal Small-Scale Fisheries In Tegal City, Indonesia. International Journal of Scientific & Technology Research. 4(1):85-88
52. Susanto, A., Irnawati R., Mustahal, & Syabana, M.A. (2017). Fishing Efficiency of LED Lamps for Fixed Lift Net Fisheries in Banten Bay Indonesia. Turkish Journal of Fisheries and Aquatic Sciences 17: 283-291. DOI: 10.4194/1303-2712-v17_2_07
53. Tapsin, G., & Hepsag. A. (2014). An Analysis Of Household Consumption Expenditures In Ea-18. European Scientific Journal. 10 (16):1-12
54. Wabnitz, C.C.C., Montemayor, A.M.C., Hanich, Q. & Ota, Y. (2018). Ecotourism, Climate Change and Reef Fish Consumption in Palau: Benefits, Trade-Offs And Adaptation Strategies. Marine Policy. 88:323-332 https://doi.org/10.1016/j.marpol.2017.07.022
55. Weigel, J.Y., Morand, P., Charpin, A., & Sadio, O. (2018). Impact Assessment of a Marine and Coastal Protected Area on Fishing Households Through a Counterfactual Approach. A Senegalese Case Study (West Africa). Ocean & Coastal Management. 55:113-125 https://doi.org/10.1016/j.ocecoaman.2018.02.009Get rights and content
56. Zamroni, A., & M. Yamao. (2011) Sustainable Household Economics: A Case of Altering Income of Small-Scale Fishermen In Indonesia. International Conference On Financial Management and Economics. 11 (11): 343-347
57. Zulkifli, Jokolelono E, & Muhtar, L.M. (2015).Analisis Konsumsi Rumah Tangga Nelayan Di Kelurahan Boneoge Kecamatan Banawa Kabupaten Donggala Jurnal Katalogis. 3 (12): 34-44
