Income and income diversification of farm households in chau thanh a district a case study of tan phu thanh village

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM- NETHERLANDS PROJECT FOR M.A IN DEVELOPMENT ECONOMICS INCOME AND INCOME DIVERSIFICATION OF FARM HOUSEHOLDS IN CHAU THANH A DISTRICT: A CASE STUDY OF TAN PHU THANH VILLAGE Thesis submitted in partial fulfillment of the requirement for the degree of Master of Arts in Development Economics By LE TAN NGHIEM Supervisor: MSc NGUYEN HUU DUNG Ho Chi Minh City, December 2003 CERTIFICATION "I certify that the substance of this thesis has not already been submitted for any degree and it is not being currently submitted for any other degree I certify that, to the best of my knowledge, and help received in preparing this thesis, and all sources used, have been acknowledged in this thesis" Le Tan Nghiem ACKNOWLEDGEMENT I would like to express my special thanks to my supervisor, MSc Nguyen Huu Dung for his patient attention, guidance, and precious advices in my completion of the thesis My sincere regards to Dr Mai Van Nam and Dr Le Khuong Ninh, the lecturers of School of Economics and Business Administration, Can Tho University for their enthusiastic support in my study I would like to thank Ms Tran Thi Ngoc Huan, the researcher of Cuu Long Delta Rice Research Institute for her permission of using the data I wish to express my appreciation to all my teachers in the Vietnam-Netherlands Project for Master Program in Development Economics for their knowledge and support My thanks also go to the project staffs and all of my friends for their helpful advices Finally, I especially thank my family I would have never made this thesis without their loving and support 11 ABSTRACT Diversification is a basic strategy that farm households in the Mekong River Delta rely on This study highlights this issue by using the sample of 217 farm households in Tan Phu Thanh Village, Chau Thanh A District, Can Tho Province The theory of farm household model and the literature on livelihood diversification are reviewed to set out factors affected on income diversification of farm households A log-linear model and a logit model are then employed to seek the determinants of farm households' income and income diversification in this area The study finds that diversification significantly increased the farm households' total income Participating in non-farm activities brings higher income to farm households Among significant influencing factors, labour ratio has a strongest positive effect on farm households' income Finally, although land size is one of the most important inputs of farm production, its positive effect on the total income of farm households is smallest Identifying the determinants of farm households' income diversification, the study employed the logit model of farm households' participation in non-farm activities Theresults show that labour ratio is the most decisive factor inducing farm households to work in non-farm activities It has the strongest positive effect on households' income diversification Farm households' decision to engage in non-farm activities is negatively affected by landowning Low agricultural income per capita pushes farm households to stabilize their income by joining in non-farm work Finally, farm households recently faced difficulties in agricultural production are more likely to take up non-farm activities 111 TABLE OF CONTENTS CERTIFICATION i ACKNOWLEDGEMENT ii ABSTRACT iii TABLE OF CONTENTS iv LIST OF TABLES vii LIST OF FIGURES ix CHAPTER INTRODUCTION I 1.1 Statement ofthe problem 1.2 Objectives ofthe study 1.3 Research questions 1.4 Research methodology 1.5 Scope ofthe study 1.6 Organization ofthe study CHAPTER LITERATURE REVIEW 2.1 Relevant concepts 2.1.1 Farm household 2.1.2 Sources of farm households' income 2.1.3 Income diversification 10 2.2 Theoretical backgrounds of farm households 11 2.2.1 Theory of farm household behaviours 11 2.2.2 Income diversification (Ellis, 2000) 16 2.3 Reviews of relevant studies 23 IV 2.3.1 A Case study of rural Southern Mali (Abdulai and CroleRees, 2001) 23 2.3.2 A Case study ofNorthem Ethiopia (Woldehanna and Oskam, 2001) 24 2.3.3 A Case study ofEthiopia (Block and Webb, 2001) 25 CHAPTER ANALYTICAL FRAMEWORK AND MODEL SPECIFICATION 29 3.1 Sources ofthe data 29 3.2 Sources of income, income diversification and income inequality 30 2.1 Classification of farm households' income 30 2.2 Measurement of income diversification 31 3.2.3 Measurement of income inequality 32 3.3 Determinants of farm households' income 33 3.4 Determinants of farm households' participation in non-farm activities 4.1 Supplementary tests of the model 40 4.2 Marginal effects 41 CHAPTER GENERAL INFORMATION ON CHAU THANH A DISTRICT AND TAN PHU THANH VILLAGE 43 4.1 Chau Thanh A District 43 4.1.1 Geography 43 4.1.2 Overview of socioeconomic context 44 4.2 Tan Phu Thanh Village 49 CHAPTER INCOME AND INCOME DIVERSIFICATION OF FARM HOUSEHOLDS IN TAN PHU THANH VILLAGE 51 5.1 Socioeconomic characteristics 51 5.2 Sources of farm households' income 52 5.3 Income diversification- Herfindahl index 54 5.3.1 Number ofhouseholds' income generating activities, households' characteristics and total income 55 v 5.3.2 Herfindahl index across quintiles of total income 56 5.4 fucome inequality of farm households 51 5.5 Factors influencing farm households' income 58 5.5.1 Land size, labour ratio and households's income 58 5.5.2 Access to credits, risks in farm production and households' income 59 5.5.3 Herfindahl index and households' income 60 5.5.4 Main features of pure farm households versus non-pure farm households 61 5.6 Factors influencing farm households' participation in non-farm activities 62 5.6.1 Labour ratio and non-farm activities 63 5.6.2 Land size and non-farm activities 64 5.6.3 Household size and non-farm activities 64 5.6.4 Farm income per capita and non-farm activities 65 5.7 Farm households' income and its significant determinants 67 5.8 Households' participation in non-farm activities and its significant determinants 70 CHAPTER CONCLUSIONS AND RECOMMENDATIONS 75 6.1 Conclusions 75 6.2 Policy recommendations 78 REFERENCES 80 APPENDIX 84 Vl LIST OF TABLES Table 2.1: Typical Variables used in Empirical Studies Explaining Household Income Diversification 27 Table 3.1: Variables of the Farm Household Income Model 36 Table 3.2: Variables of Farm Households' Participation in Non-farm Activities .40 Table 4.1: Structure of Gross Domestic Product (GDP), 1995-2002 44 Table 4.3: Trend of Land per Agriculturist in Chau Thanh A, 2000-2002 .48 Table 5.1: Socioeconomic Characteristics of the Sample 52 Table 5.2: Variety of Sources ofHouseholds' Income 53 Table 5.3: Numbers of Income-generating Activities And Households Characteristics 55 Table 5.4: Herfindahl Index across Quintiles ofFarm Households' Total Income 56 Table 5.5: Distribution of Households' Income across Diciles 57 Table 5.6: Land Size and Labour Ratio across Total Income Quintiles 58 Table 5.7: Access to Credits and Risks in Production across Total Income Quintiles 59 Table 5.8: Total Income across the quintiles ofHerfindahl Indices 60 Table 5.9: Some Different Features between Pure and Non-Pure Farm Households 61 Table 5.10: Percentage of Households' Participation in Non-Agricultural Activities, by Quintiles of Household's Labour Ratio 63 Vll Table 5.11: Percentage of Farm Households' Participation in Non-Agricultural Activities, by Cohorts of Land Size 64 Table 5.12: Percentage of Households' Participation in Non-agricultural Activities, by Number of Household Members 65 Table 5.13: Percentage of Households' Participation in Non-agricultural Activities, by Quintiles of Farm Income Per Capita 66 Table 5.14: Determinants ofFarm Households' Income 68 Table 5.15: Logistic Regression Results for Determinants ofFarm Households' Participation in Non-farm Activities 711 Table 5.16: Estimated Marginal Effects at the Mean for Household's Participation in Non-farm Activities 72 V111 LIST OF FIGURES Figure 2.1: Classification of Activities Figure 4.1: Structure of Employment in Chau Thanh A District, 2001-2002 45 Figure 4.2: Map ofChau Thanh A District .456 IX The coefficient of the variable for labour ratio is positive and significantly different from zero, suggesting that households with higher ratios of working labours are more likely to earn income from non-farm activities This is consistent with Section 3.4.2 and Section 5.6.1 Among the significant factors, labour ratio has the strongest effect on the farm households' participation in non-farm activities with the estimated marginal effect 0.30 (see Table 5.16) This means that if the labour ratio increases percent at the mean, the probability of a household participating in non-farm activities increases 0.30 This high probability of farm households to working in non-farm is resulted partly from the high dependent members ratios in households The mean labour ratio of 0.67 implies that every two labours had to support one dependant in their farm households in this village Table 5.16: Estimated Marginal Effects at the Mean for Household's Participation in Non-farm Activities7 Variables Means Coefficients Marginal effects Age 51.10377 -0.0157555 Lab ratio 0.670594 5.658177 Hhsize 5.169811 0.0710516 0.0037198 Credit 0.292453 -0 0803913 -0.0042087 Land 0.644538 -0.9435935 Nlbinc 756.6982 -0.0000753 Risk 0.674528 1.120119 ** 0.0586415 Pcfinc 1143.551 -0.0006289 ** -0.0000329 -0.0008248 *** ** 0.2962222 -0.0493999 -0.0000039 The average probability of participating in non-farm activities offarm households, P = 0.8396 Notes: *denotes significant at the 0.10 level ** denotes significant at the 0.05 level ***denotes significant at the 0.01 level This Table is calculated by using the Section 3.4.4 72 The impact ofland size (area ofland cultivated) on households' decision on working off the farm is negative and conformable to Section 3.4.2 and Section 5.6.2 This is also consistent with the finding that larger landholding will generate higher income for farm households (see Section 5.8) The marginal effect ofland size on the decision to engage in non-farm of farm households is 0.05 This reflects the fact that farmers in the village not have enough land to cultivate and the abundance in labours induces them to participate in non-farm work Another significant factor causing farmers to seek income from non-farm work is the farm income per capita The negative coefficient of this factor shows that if the farm income per capita reduces, farm households will participate in non-farm activities Because farm revenue is the main source of the farm households' income, fluctuations in agricultural income stir up the farmers' balanced budgets and hence they have to collect income off-farm income to smooth their living However, this effect is small Besides, farm households' participation in non-farm activities is depended on risks in agricultural production The positive effect of this factor explains that farm households will tackle the difficulties in farm production by joining in non-farm work This implies that farmers are risk-averse and it is consistent with Section 2.2.2 Combining the above factors will help us to explain the diversification of income more logically High ratio of labours but the scarcity of land for production leads to labour abundance Agricultural production is risky and so reduces the farm income Therefore, households will simultaneously face the problems of inadequate money for expenditures but much idle employment, and this in tum makes them more favor in off-farm activities 73 Out of the explanatory variables, household size, non-labour income, access to credits, and age of household head insignificantly affect on farm households' participation in non-farm activities Larger household size though statistically induces working in nonfarm activities, its insignificance can be resulted from the effect of higher number of dependents Non-labour income and borrowed loans from banks are considered as substitutes of non-farm income source in farm households It is statistical to keep farm households out of non-farm work However, since there exist some other options for farm to borrow money, i.e., access to informal credits, this cause the insignificant effects of these variables on farm households' decision to participate in non-farm work Finally, insignificant effect of age of households' heads on working off the farm of farm households is because deciding on participating in non-farm work of individual members is depended strongly on themselves rather than the heads' decision This model, in general, set out the determinants of farm households' participation in non-farm activities Labour is the most decisive factor inducing the diversification of income out of the farm Besides, factors relevant to agricultural production, particularly land size, farm income per capita and risks forced farm households to participate in nonfarm activities These effects are consistent with theoretical expectations In summary, this chapter analyzed determinants of farm households' income and income diversification for the case of Tan Phu Thanh Village Analyzing farm households' portfolios of income, the study shows that non-farm income occupies the larger share of total income Households engaged in non-farm activities obtained higher income than others did not The higher level of diversification is associated with the higher income derived Importantly, labour factor plays the most decisive role in generating farm households' income and income diversification in the village 74 CHAPTER6 CONCLUSIONS AND RECOMMENDATIONS 6.1 CONCLUSIONS The study has investigated different income portfolios of farm households based on the cross-sectional data on 217 farm households in the Tan Phu Thanh Village Farm households are classified into pure and non-pure farm households in which pure farm households are those not participate in non-farm activities Theories of farm household economics and livelihood diversification are first reviewed to form a theoretical background for the study A log-linear model of farm households' income and a logit model of farm households' participation in non-farm activities are then specified to understand the determinants of farm households' income and income diversification Farm households' total income are devided into farm income, non-farm income and non-labour income On-farm income accounts for only one-third of the households' total income (31.83 percent) Among on-farm activities, fruit production provides the highest share of income derived from agriculture (15.51 percent) In the mean while, paddy production contributes a small share of income from agriculture This implies that investing in fruit production will bring higher profits to farm households than paddy production Therefore, changing cropping pattern from rice-monoculture production to paddy-fruit production will yield higher income for farm households Participating in non-farm activities increases the farm households' total income remarkably The data shows that non-farm income accounts for 64.33 percent of farm households' total income Total income of the non-pure farm households is greater than 75 two times that of the pure farm households on average This wide difference is resulted completely from amount of income derived from non-farm activities This is consistent with the result of econometric approach that if the pure farm households engage in nonfarm work, their total income will increase 0.59 percent Farm households' income is strongly affected by labour ratio and area of cultivated land Out of the significant factors, labour ratio is the strongest positive effect of farm households' income with the elasticity of 0.63 Similarly, farm households with larger landholding will derive higher income Therefore, it is clear that labour and land are the two important inputs of farm production; and expanding area of cultivated land and/or growing in labour ratio will improve the farm income and households' total income as well In addition, households with higher labour ratio can allocate their labour endowment in more activities, including non-farm activities and then increase their tot~l income The most important finding is that diversification is positively associated with the farm households' total income Descriptive analysis illustrates the positive relationship between the number of activities farm households engaged in and the total income derived The econometric approach also highlights this significant effect This implies that the more diversified the household, the higher income the household derived Consequently, diversifying farm households' endowments into different activities is considered as an effective strategy for farm households to increase their income Access to credit and difficulties in farm production are insignificant factors of farm households' income in this case It is even more interesting that risks in farm production increases the farm households' total income This can be explained by the offset effect ofhigher non-farm income, which is derived from participating in non-farm activities 76 There is a number of factors influencing income diversification of farm households The findings show that labour ratio, land size, farm income and risks in agricultural production are significant factors affected on farm households' participation in non-farm activities Labour ratio is the strongest positive factor inducing farm households to participate in non-farm activities This means that farm households with higher labour ratio are more likely to derive additional amounts of income from working in non-farm work The positive effect of labour ratio on both farm households' income and income diversification implies that given the recent land endowment, agricultural activities cannot absorb full labour endowment of farm households Therefore, when labour ratio increases, farm households' labours need to work off the farm The study also points out the negative effect of landholding on farm households' decision to participate in non-farm activities This means that households with higher area of cultivated land are ready to work in farm activities only The positive effect of landholding on farm households' income is useful to explain for their choice of working in farm work only Because of larger landowning, most of farm households' labour endowment is used on their farms and so, they are unlikely to work off the farm Besides, low level of agricultural income per capita is also a factor pushing farm households' labours to participate in non-farm activities Farm income is the principal source that farm households rely on for both food consumption and in-cash expenditures Due to this necessity, whenever this amount of income is lower than that of farm households expected, they have to work in non-farm to balance their income Lastly, farm households' taking up non-farm activities is partly affected by risks in agricultural production The result shows that farm households recently faced risks in their 77 production are more likely to engage in non-farm activities Since the marginal effect of risk on farm households' participation in non-farm activities is relatively strong, it is essential to include risk in to study its effect on income diversification In conclusion, farm households' income diversification is affected by labour ratio, land size, agricultural income and difficulties in non-farm production Farm households' income is affected by labour ratio, land size, participating in non-farm activities and especially level of diversification hnportantly, the main finding of the study is that diversification increases significantly farm households' income Based on these findings, the following section suggests some recommendations for local authority in making strategies on the development of Chau Thanh A District 6.2 POLICY RECOMMENDATIONS In the context of the limitation of cultivated land but labour abundance, diversifying income-generating activities is a predominant strategy to absorb the labour and to secure the farm households' subsistence income The diversification can be applied in both farm and non-farm sectors In agriculture, farm households can increase their total income by maximizing profits from diversified activities on their farm Since income from only paddy production (even intensive cultivation) cannot enrich farm households, taking full advantage of land use in generating more agricultural sources of income will improve their livings A part of their landowning should be used for fruits production In addition, farmers should apply some systems ofrotational crops on their farming land, such as: paddy and freshwater aquatic products (anabas, snake-heads, catfish, etc.), paddy and prawn, paddy and vegetable, three crops of premature maize and beefs breeding, etc These sys- 78 terns will increase farm households' income and keep land fertilized Diversifying such activities also mitigate risk and reduce the variation in farm households' income In the Mekong River Delta, since most of farm households are holding small areas of cultivated land (0.1-0.2 ha/person) and farm production is scattered and inefficient, it is more effective to fuse small farms into a large farm to cultivate in combinations of production With a large farm, co-farmers can be active in irrigation, technology, seeds, capital, etc and selling their products Therefore, the final profits per area of cultivated land in combinations of production will be higher than that in individual farm households' production Besides, expanding non-farm activities is more convincible Since non-farm activities are considered as lower risk and higher revenue than farm activities, working in nonfarm can stabilize and increase income of farm households The local authority should stimulate the development of industrial establishments in the district The development of foodstuff processing industry will not only absorb the agricultural outputs as its inputs but also provides jobs for local labours Therefore, farm households' labours, especially the idle labours in farm households can work for these manufactories and hence increase their total income In general, income diversification is necessary for farm households to increase their to- tal income This study has already pointed out some effects of households' characteristics on income diversification of farm households However, the study still left some other factors such as interternporal effects of these factors on diversification, effects of macro-policies, etc as well as effects of income diversification on social management (i.e migration from rural to urban for seeking income, etc.) Therefore, it is better to study these effects in a further research 79 REFERENCES Abdulai, A and A CroleRees (200 1) 'Determinants of Income Diversification 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Working Paper Block, S and P Webb (2002) 'The Dynamics of Livelihood Diversification in PostFamine Ethiopia' Working Paper Tufts University 80 Can Tho Statistical Office (CSO) (2002), Statistical Yearbook 2002, Can Tho City: Can Tho Statistical Office Press Chau Thanh A Statistical Office (2002), Statistical Yearbook 2002, Can Tho City: Can Tho Statistical Office Press Dang Kim Son (1998) 'Development of Agricultural Production Systems in the Mekong Delta', in Vo Tong Xuan and S Matsui (eds.) 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Development of Farming Systems in the Mekong Delta of Vietnam Ho Chi Minh City: Ho Chi Minh City Publishing House Norton (1993) Introduction to Economics of Agricultural Development New York: McGraw-Hill Inc Reardon, T (1997) 'Using Evidence of Household Income Diversification to Inform Study of the Rural Non-farm Labour Market in Africa,' World Development 25(5): 735-748 Reardon, T., Barrett, C., Kelly, V., and K Savadogo (1999) 'Policy Reforms and Sustainable Agricultural Intensification in Africa' Development Policy Review 17 (4) December Reardon, T., Crawford, E and V Kelly (1994) 'Links between Non-farm Income and Farm investment in African Households: Adding the Capital Market Perspective,' American Journal of Agricultural Economics Volume 76, No (December): pp 1172-76 82 Reardon, T., Stamoulis, K., Balisacan, A., Cruz, M.E., Berdegue, J., and B Banks (1998) 'Rural Non-farm Income in Developing Countries,' Special Chapter in The State of Food and Agriculture 1998 Rome: Food and Agricultural organization of the United Nations Savadogo, K., Reardon, T and K Pietola (1998) 'Adoption of Improved Land-Use Technologies to Increase Food Security in Burkina Paso: Relating Animal Traction, Productivity and Non-farm Income' Agricultural Systems 598 The People Committee of Chau Thanh A District (PCC) (2002a) Report on Socio- economic Development Strategy in the period of 2005 - 2010 (Bao cao Dinh huong Phat trien Kinh te - Xa hoi giai an 2005 - 201 0) The People Committee of Chau Thanh A District (PCC) (2002b) The Master Plan on Socio-economic Development of Chau Thanh A District, Can Tho Province up to 2010 (Quy Roach Tong The Phat Trien Kinh Te- Xa Hoi Huyen Chau Thanh A Tinh Can Tho Thoi Ky Den Nam 2010) Vo Quang Minh, Le Quang Tri and Ryuichi Yamada (2002) 'GIS and Multicriteria Evaluation Techniques for Land Use Allocation: A Case Study of Tan Phu Thanh Village, Chau Thanh A District, Cantho Province', in JIRCAS-CTUCLRRI-SOFRI (2002) Development of New Technologies and Their Practice for Sustainable Farming Systems in The Mekong Delta pp 302-15 Proceedings of the 2002 annual Workshop of JIRCAS Mekong Delta Project Can Tho: Can Tho University 83 APPENDIX Appendix 1: OLS Regression Results of The Linear Model of Farm Households' income (Equation 3.3) reg income land labratio divlevel hhtype credit risk if income F R-squared Adj R-squared Root MSE 212 13.43 0.0000 0.2822 0.2612 9875.6 income I Coef Std Err t [95% Conf Interval) P>ltl -+ -land 2513.942 1489.218 69 0.093 -422.206 5450.09 labratio 16664.84 3445.924 4.84 0.000 9870.844 23458.83 divlevel -7998.82 3299.608 -2.42 0.016 -14504.34 -1493.302 hhtype 8191.448 2045.701 4.00 0.000 4158.137 12224.76 credit -1971 99 1507.594 -1.31 0.192 -4944.368 1000.388 risk 25.76354 1546.969 0.02 0.987 -3024.247 3075.774 cons 4777.586 3684.123 30 0.196 -2486.044 12041.22 hettest Cook-Weisberg test for heteroskedasticity using fitted values of income Ho: Constant variance chi2(1} 6.95 Prob > chi2 0.0084 ovtest Ramsey RESET test using powers of the fitted values of income Ho: model has no omitted variables F(3, 202) 0.36 Prob > F = 0.7812 84 \' Appendix 2: OLS Regression Results of The Log-Linear Model of Farm Households' income (Equation 3.3) reg lnincome lnland lnlbratio lndivlevel hhtype credit risk if lnincome >7.5(*) df ss MS Source I -+ -Model Residual I I 28.6865518 56.2558895 203 Number of obs F( 6, 203) Prob > F R-squared Adj R-squared Root MSE 4.78109196 277122609 -+ -Total I lnincome I 84.9424413 Coef 209 406423164 Std Err P>ltl t 210 17.25 0.0000 0.3377 0.3181 52642 [95% Conf Interval) -+ -lnland lnlbratio lndivlevel hhtype credit risk cons 1012844 6336913 -.2333736 5680249 -.1005477 0348446 9.47448 0499973 1180181 0836186 1169201 0812322 0845483 1542244 2.03 5.37 -2.79 4.86 -1.24 0.41 61.43 0.044 0.000 0.006 0.000 0.217 0.681 0.000 0027039 4009927 -.3982459 3374912 -.2607148 -.1318608 9.170393 199865 8663899 -.0685012 7985585 0596194 2015501 9.778567 (*) using if to drop some outliners in the sample Note: hettest Cook-Weisberg test for heteroskedasticity using fitted values of lnincome Ho: Constant variance chi2(1) 0.00 Prob > chi2 0.9958 ovtest Ramsey RESET test using powers of the fitted values of lnincome Ho: model has no omitted variables F(3, 200) 0.26 Prob > F = 0.8533 corr, coef lnland lnlbratio lndivlevel hhtype credit risk cons -+ lnland lnlbratio lnherfind hhtype credit risk cons 1.0000 -0.1087 1.1277 0.2176 -0.0699 -0.2788 -0.2137 1.0000 -0.0719 -0.3935 0.0669 -0.0483 -0.5585 1.0000 0.0345 -0.0401 0.1867 0.2925 vif Variable I VIF 1/VIF -+ -lnland lnlbratio lndivlevel hhtype credit risk 1.18 1.20 08 23 01 1.16 0.849343 0.832815 0.928125 0.811028 0.989933 0.863774 -+ -Mean VIF I 1.14 85 1.0000 -0.0395 -0.0852 -0.5881 1.0000 -0.0180 -0.1234 1.0000 -0.3308 1.0000 Appendix 3: Logit Regression Results of Farm Households' Participation in Nonfarm Activities (Equation 3.4) legit hhtype age labratio nlbinc credit hhsize risk pcfinc land if pcfinc chi2 Pseudo R2 Logit estimates Log likelihood= -70.169123 212 46.35 0.0000 0.2483 -hhtype I Coef Std Err z P>lzl [95% Conf Interval] -+ -age labratio nlbinc credit hhsize risk pcfinc land cons -.0157555 5.658177 -.0000753 - 0803913 0710516 1.120119 -.0006289 -.9435.935 -.4125802 016181 1.279547 000064 4902822 1580709 478606 0002497 4477035 309376 -0.97 4.42 -1.18 -0.16 0.45 2.34 -2.52 -2.11 -0.32 0.330 0.000 0.240 0.870 0.653 0.019 0.012 0.035 0.753 lfit Logistic model for hhtype, goodness-of-fit test number of observations number of covariate patterns Pearson chi2(203} Prob > chi2 212 212 204.77 0.4520 lstat Logistic model for hhtype Classified I True -D -D I Total -+ + 174 + 24 10 1 198 14 -+ + Total 178 34 I 212 Classified + if predicted Pr(D} >= True D defined as hhtype -= Sensitivity Specificity Positive predictive value Negative predictive value Pr( +I D) Pr( -1-D} Pr( Dl +} Pr(-DI -} 97.75% 29.41% 87.88% 71.43% False False False False Pr ( + 1-D} Pr( -1 D) Pr(-DI +} Pr( Dl -} 70.59% 2.25% 12.12% 28.57% + rate for true -D - rate for true D + rate for classified + - rate for classified - 86.79% Correctly classified 86 -.0474697 3.15031 -.0002008 -1.041327 -.2387617 1820684 - 0011184 -1.821076 -2.97891 0159588 8.166044 0000502 8805442 3808649 2.058169 -.0001394 - 0661109 2.153749 ... determinants of farm households' income and income diversification in the case of Tan Phu Thanh Village, Chau Thanh A District, Can Tho Province Both qualitative and quantitative analyses are used in the... for analyzing farm households' income and determinants of income Results of OLS and Logistics regression and interpretations will be displayed in line with data description and bivariate analysis... gain additional amounts of income by participating in non -farm activities and farm households having income diversification are called non-pure farm households, otherwise are pure farm households