PIERS 2017

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https://ir.lib.pdn.ac.lk/handle/20.500.14444/2908

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Browsing PIERS 2017 by Subject "Fixed effect model"

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    The impact of cost of paddy production on farmers’ standard of living : a case study to Maritimpattu divisional secretariat in Mullaitivu district
    (University of Peradeniya, 2017-10-12) Neruja, N.; Vinayagathasan, T.
    Introduction Paddy production has become a main source of standard of living for farmers in Sri Lanka not only by providing them with basic food requirement but also generating income and increasing the number of jobs to rural communities. Demand for paddy production is steadily increasing day by day in all over the world due to rise in population. In this regard, demand for paddy in Sri Lanka increase at rate of 1.1 % per year. To meet this, the rice production should grow at the rate of 2.9 % per year (Department of Agriculture, 2014). However, the increases of cost of production, climate changes, inadequate market opportunities and etc. tend to leads for stagnated yield which has made paddy farming a non-viable enterprise during the last few decades. For example, cost of labor, farm power cost and tradable inputs constitutes 5 5 %, 23 % and 2 3 % respectively in total cost of paddy (Department of Agriculture, 2015). Even though Sri Lanka achieved self-sufficiency in paddy production, due to above reasons the farmers are unable to earn profit from their paddy business. Thus, several farmers leave from farming due to inadequate and/ or uncertainty of income. The majority of the rural people, i.e. more than 61 %, in Mullaitivu District depend on agriculture as their main source of income (Department of Agriculture in Mullaitivu, 2015). At the same time poverty level of this district was 28.8 % (Central Bank of Sri Lanka, 2015), Since Mullaitivu District was harshly affected by war for a long period, large amount of lands are not in use due to security reasons yet, high cost of production and lower prices of their product tend to leads to the extreme poverty and low living standard among the farmers. At the same time, society also has faced socio-economic problems. Such situation arises due to lack of research and less attention by government policy makers on this area. Although there are several researches which focus on the economic impact of cost of paddy production on the living standard of farmers (Rahman et al., 2005; Rabu et al., 2013) in the world, Mullaitivu district is not yet adequately explored. Objectives The primary objective of this study is to examine the impact of cost of paddy production on the living standard of farmers’ of Mullaitivu district. The specific objectives are: (i) To diagnose the main socio-economic factors affecting the cost of paddy cultivation, (ii) To identify and analyze the factors which influence on paddy production (iii) To examine the factors that affecting the income of farmers. Methodology This study mainly use primary and secondary data also employed where it necessary. The primary data was collected using percentage random sampling method by issuing the questionnaire for 60 families of study area in two round survey (2012 and 2015). The study area of Martimapattu DS division was selected based on purposive random sampling method. The secondary data were collected from the reports of relevant department. Following the Neo Classical growth theory, we used Fixed Effect Multiple Linear Regression Model (FEMLRM) to identify the determinants of cost of paddy production and farmers’ income, which are given by equation (1) and (2) respectively. Thirdly, we adopted Cobb-Douglas production function to examine the factors that affect the paddy production, which is given by: where, TC : average production cost, Q : average paddy production, TNC : total income of farmers,X = [KC, LC, SC, FC,WC, PDC, TRC] KC : capital cost, LC : labour cost, SC: seed cost, PDC : pesticides cost, WC: weed cost, FC: fertilizers cost, EDU: education level of the farmers, HHS: household size, Y: monthly average income from farm, FS: farm size, experience of the farmer, NY: monthly average income from non-farm, AG: age of farmers, TRC: transport cost, INPC: inputs cost, SAV: saving, D₁: land ownership, D₂: agriculture training D₃: irrigation system, D₄: quality of land and μ₁ : individual specific fixed effect, and : error terms (0, σ²). Finally, we utilized Logit model to investigate the living standard of farmers, which is takes the form as: where, LS is the standard of living of farmers which takes value 1, if the household i is the standard of living, is above average level, 0 otherwise; NY: non-farm income, SAV: saving. μᵢ is the individual specific fixed effect and is the white noise error term. We also used Weighted Least Squared (WLS) Method to compare the results of FEMLRM Results and Discussion Hausman test suggests that fixed effect model is appropriate to this study. The Table 1 below presents the estimated results of cost of paddy production. The above table reveals that as expected to the theory and some of the existing literature (Egbodian and Ahmadu, 2015; Ahmad and Razmy, 2005; Aheer et al., 2005), cost of capital, labour and total input cost (SC, FC, WC, PDC and TRC) have significant and positive impact on cost of paddy production. Further, method of irrigation negatively affects cost of paddy production at 10 % significant level. The estimated result of production function is given by Table 2. The results in Table 2 indicate that the cost of capital and cost of transportation, farm size and irrigation method have significant and positive impact on quantity of paddy production. This findings is similar to some of the existing empirical findings (e.g., Aung, 2012; Egbodin and Ahmadu, 2015; Gamawelagedara et al., 2011).
    The Fixed effect income estimates in Table 3 reveal that as expected farm income, non-farm income, saving and irrigation system affect the farmers total income positively at 5 % significant level, while cost of paddy production affect and negatively at 10 % level of significant. Moreover, irrigation system has positive and significant impact on total income of farmers.
    The WLS method also reveals the same results as FEMLRM (results are not presented here but available up on request). The Logit regression results in Table 4 imply that several variables are significantly correlated to the living standard of farmers. First, negative coefficient estimate of LNTC indicates that an increase in total cost of farmers decreases the probability of the farmers being above the average living standard level. Second, an increase in monthly average income of farm increases the probability of the farmers being above the average living standard level as coefficient of LNY variable is statistically significant and positive. This finding is similar to some of the existing empirical findings (Abur, 2014; Labbe, 2014; Makki et al., 2013). Third, a rise in non-farm income appears to increase the probability of the farmers being above the average living standard level. Finally, an increase in saving raises the probability of the farmers being above the average living standard level as coefficient of LNSAV variable is statistically significant and positive. The odd ratio also suggests the same conclusion as the value of odd ratio of LNTC is less than 1 and LNY, LNNY and LNSAV are greater than 1.
    Conclusion and Policy Implications The results of FEMLRM reveal that capital, labour and total input costs have significant and positive impact on cost of paddy production. Further, cost of capital, transportation cost and farm size are positively linked with quantity of paddy production. Moreover, total cost is negatively correlated with farmer’s total income while farm income, non-farm income and saving have positive impact on monthly average total income of farmers. Logit model suggest that raises in cost of paddy production decreases the probability of farmers being above the average level of living standard, whereas farm income, non-farm income and saving have a positive impact on it. Therefore, the government should take necessary actions to reduce the cost of paddy production in order to increase the living standard of farmers. References Aung, N. M. 2012. Production and Economic Efficiency of Farmers and Millers in Myanmar Rice Industry. IDE Discussion Paper No. 471. Myanmar: Institute of Developing Economics. Central Bank of Sri Lanka. 2015. Annual Report, Colombo: Central Bank of Sri Lanka. Department of Agriculture. 2015. Statistical Hand Book, Mullaitivu: Department of Agriculture. Egbodion, J. and Ahmadu, J. 2015. Production Cost Efficiency and Profitability of Abakaliki Rice in Ihialia Local Government Area of Anambra State, Nigeria’. Journal of Applied Sciences and Environmental Management.19(2), pp.327-33. Gamawelagedara, W. C. Wickramasinghe, Y.M. and Dissanagake, C.A.K., 2011. 'Impact of Rice Processing Villages on Household Income of Rural Farmers in Anuradhapura District'. The Journal of Agricultural Sciences. 6(2), pp.92-99. Rabu, M. R. and Shah, M.D.M. 2013. 'Food and Livelihood Security of the Malaysian Paddy Farmers. Economics and Technology Management Review. 8(3), pp.49-52. Rahman, S. M. Takeda, j. and Shiratake, Y. 2005. The Role of Marketing in Standard of Living : A Case Study of Rice Farmers in Bangladesh. Journal of Applied Sciences. 5(1)