In the Tocantins state, fish farming is one of the agricultural activities of highest potential, presenting a considerable growth in recent years and exceeding.

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In the Tocantins state, fish farming is one of the agricultural activities of highest potential, presenting a considerable growth in recent years and exceeding the value of capture fishery sector. Considering these facts, in 2008, the Ministry of Fisheries and Aquaculture, in partnership with the regional office of Ruraltins, initiated a project aimed to promote the development of family farming in Divinópolis region, located in western state of Tocantins. About 20 fish farmers began activity and the project consisted in the distribution of fingerlings and technical assistance. Nowadays, there are about 80 familiar fish farmers in the Divinópolis region. The objective of this paper is to investigate which socioeconomic factors have an influence on the fact of fish farmers in the region of the Divinópolis in Tocantins state reach a level of efficiency in production enough that the fish can be good for sale in the local market. VariableCoefficientStd. ErrorzP>|z|ΔProb experience members fem transfer2.963* religion income ponds dug3.568* by-products area9.458* Log likelihood = Pseudo R 2 = N = 30 AN ANALYSIS OF EFFECTS OF SOCIO-ECONOMIC VARIABLES ON FISH PRODUCTION OF SMALL FARMERS IN THE STATE OF TOCANTINS, BRAZIL Roberto Manolio Valladão Flores (1) ; Manoel Xavier Pedroza Filho (1) (1) Embrapa Fisheries and Aquaculture 104 Sul Av. LO 01 n° 34 conj. 04, Plano Diretor Sul, Palmas, Brazil INTRODUCTION METHODOLOGY To estimate the effects of different socioeconomic factors on the probability of the small farmer sell the fish can be used a qualitative choice model, was chosen the logit model. The data used for the proposed analysis in this article were collected through Project Divinópolis, research project from Embrapa Fisheries and Aquaculture that has been following the production of fish farmers in the western of Tocantins state. Were conducted, in early 2012, interviews with 30 fish farmers, visiting them in their homes and applying a questionnaire that, among other technical questions of production, had questions of which were taken the variables used in the econometric model presented. Table 1 presents descriptive statistics of the variables collected at the beginning of the project and used in the logit model. RESULTS Table 2. Results for logit model. Obs.: *significant at 10% The results show that the probability of the fish farmer sell fish is significantly and positively influenced by "transf", "pond" and "area" variables, i.e., farmers who receive some benefit from programs to transfer income from the government, who produces fish in pond dug or who have a large area of water are, on average, more likely to produce fish efficiently to sell their product. These results confirm the expected positive effect on the dependent variable of these three variables. All other variables weren't significantly different from zero at a level of 10% (Table 2). CONCLUSION In 2012, only 30% of the fish farmers could at some point sell the fish produced, and the others had only household consumption as the end of production of fish. In a total of nine exogenous factors evaluated, three had significant effect on the probability of sale of fish produced on the household farm. Farmers that receive some benefit from income transfer programs of the government, that produces fish in pond dug or that have large area of water have, on average, more likelihood to produce fish efficiently to get sell your output. Considering technical factors such as the area of water and production in ponds, government actions can have good efficiency if it was made technical trainings with farmers, both for the management of fish and to perform initial investment in production, for example, how to make ponds dug, equipment purchase, preparation of farm to maximize production etc. The results found in this study and in future by Divinópolis Project may be multiplied to other regions of Brazil and the world that have similar background and the same technical and socio-economic needs. VariableMeanStd. Dev.MinMaxExpected sign dependent (Z) N/A experience members Fem transfer religion /- income2, , , /- Ponds dug By-products area Table 1. Descriptive statistics of variables used in the logit model.