EFFECT OF SELECTED INSECTICIDE ON WHITEFLY (Bemisia tabaci) INFESTING BRINJAL PLANTS 257 Effect of Small-scale Irrigation on the Farm Households’ Income of Rural Farmers: The Case of Girawa District, East Hararghe, Oromia, Ethiopia Beyan A., Jema H. and Adem K. P. O. box 138 Dire Dawa, Department of Agricultural Economics, College of Agriculture and Environmental Science, Haramaya University, Ethiopia Abstract Irrigation is one means by which agricultural production can be increased to meet the growing food demands in the world. This study evaluated the effect of small-scale irrigation on farm household income in production. The specific objective of this study is to identify the factors in- fluencing participation in small-scale irrigation and provides bases for policy makers in Girawa district, Eastern Hararghe zone, Oromia, Ethiopia. Both primary and secondary data were col- lected for the study. Primary data were collected from 200 sample respondents drawn from both participant and non-participant households. Preliminary statistics and econometric models were employed for data analysis. The logistic regression estimation of factors affecting participation re- vealed that age of household head, non-farm income, livestock size, size of cultivated land, dis- tance between plot and irrigation scheme, means of transportation and participation of household heads in social organization significantly affected the participation decision of households in irri- gation farming. Results showed that participation in irrigation has a significant, positive effect on farm households’ income. Therefore, policy makers should give due emphasis to the aforemen- tioned variables to increase participation in irrigation farming and improve the livelihood of rural households. Keywords: Irrigation, income, rural farm households, participation and logit model Introduction 1 Ethiopia is an agrarian country where around 95% of the country’s agricultural output is produced by smallholder farmers (MoARD, 2010). Agriculture contributes about 41% of the country’s GDP, employs 83% of total labour force and contributes 90% of exports (EEA, 2012). Despite its dominance, in 2011 alone Productive Safety Net Program supported 7.4 million people, whereas an additional 4.5 million people were requiring emergency humanitarian as- sistance (FEWS NET, 2011). Corresponding author’s Name: Beyan A. Email address: beyanhmd@gmail.com Irrigation contributes to livelihood im- provement through its direct and indirect benefits. The direct benefits of irrigations are; high productivity, lower risk of crop failure, and higher and year-round farm and non-farm employment, increased income, food security, and poverty reduction. Irriga- tion enables smallholders to adopt more di- versified cropping patterns, and diversify income base sources. Indirectly irrigation benefits as a potential to become ‘nuclei of growth’ which are attractive for inward in- vestments in other infrastructure and ser- vices such as banking to facilitate this growth (Hussien and Hanjira, 2004) The total irrigable land potential in Ethiopia is 5.3 million hectares assuming use of exist- ing technologies, including 1.6 million hec- Asian Journal of Agriculture and Rural Development journal homepage: http://aessweb.com/journal-detail.php?id=5005 mailto:beyanhmd@gmail.com Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 258 tares through RWH and ground water. There are 12 river basins that provide an estimated annual run-off of ~125 billion m 3 per year, with the potential of irrigating total of 3,731,222ha from surface water. The poten- tial available estimates for RWH range from 40,000 to 800,000 ha. The area under irriga- tion development to-date is estimated to be 640,000 hectares for the entire country which is 5% of the potential irrigable (Awu- lachew et al., 2010). Agriculture in Ethiopia is heavily dependent on rainfall, which is highly varies both spa- tially and temporally. despite Ethiopia’s agricultural enterprises, a high and grow- ing human population, recurrent droughts and periodic floods, complicated by cli- mate change that has been accompanied by severe soil and landscape degradation in some regions contributed to a situation of national food insecurity (FAO, 2011). This, therefore, calls for different interven- tions, irrigation being one of the options, which could help in adapting strategies to cope up with the challenging drought. Though agriculture remains to be the most important sector of the Ethiopian economy, its performance has been disappointing and food production has been lagging behind population growth (Demeke, 2008), which is unable to fulfil the requirement of the ever- increasing number of mouths. Poor use of modern inputs can partly explain the low productivity of the sector and the internal in- efficiency of the farmers in using the avail- able agricultural resources In the light of the foregoing this study examined farm house- hold’ income of smallholder irrigated and rain-fed farm production in Ethiopia, using Girawa district of Oromia national Regional State as a study area. Specifically, this study;  To identify factors affecting house- hold level irrigation participation of smallholder farmers.  To provides a base for policy makers through the comparisons of farm income of irrigation users and non-users with respect to simi- lar areas. Research methodology The study was conducted in Girawa district, Oromia National Regional State, Ethiopia. According to CSA (2010), Girawa district has a total population of 263,924 of which 133,780 are male and 130,144 are female and total area of the district is about 1109.41 km 2 with density of 237.9 (BoARD, 2012). The climate condition of the study area 48.9%, 31.1% and 20% of Girawa district is kolla, Woina dega and Dega of Agro- ecological zones, respectively. The land alti- tude ranging from 1215 to 3405 meter above sea level (m.a.s.l). The annual rainfall ranges from 550mm to 1100 mm with annual tem- perature ranging from 20 ºc - 27ºc. The pri- mary source of income is crop and chat pro- duction. Major types of crops grown in the area are sorghum, maize, common beans, highland pulses and many other vegetable crops like potatoes, onion, garlic, and leafy vegetables. Livestock rearing is the secon- dary source of livelihood for the rural people in the area (BoARD, 2012). The district has a range of water resources, which are suitable for irrigation activities. Traditional irrigation has a long history in the district whereas modern irrigation schemes are not as much. The total irrigable land potential in the district is 6113ha, out of which 4014ha from surface water potential and the remaining 2100ha estimated to be ground water potential. However the esti- mated area under irrigation to-date is 3025.5 in which traditional irrigation accounts for 1842ha, modern irrigation covers 690.5ha and the area underground water(in the form of well) is 493ha that benefits about 29,332 households. Water management was under taken by water user association themselves. As sources of information both primary and secondary data sources were used. The pri- mary data were collected using semi- structured questionnaire that was adminis- Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 259 tered by the trained enumerators. In addition to primary data, secondary data were also collected from relevant sources such as pub- lished and unpublished documents of the district and other relevant institutions (Care Gara Muleta) for general description and to augment primary data. The sampling procedure used was two stage random sampling. In the first stage out of the kebeles exist in the district two kebeles are purposively selected due to availability of ir- rigation. In the second stage, to select sam- ple respondents from the two kebeles, first the household heads in the two kebeles were identified and stratified into two strata: irri- gation users and non-users. Then the sample from each stratum was selected randomly based on probability proportion to size. Fi- nally, a total of 200 sample respondents; 100 users and 100 non-users were interviewed. Data analysis To address the objectives of the study, both preliminary statistics and econometric meth- ods were employed. For this study, prelimi- nary statistics such as mean, percentages, standard deviation, frequency of occurrence, chi-square and t-test were used. The statisti- cal significance of the variables was tested for both dummy and continuous variables using chi-square and t-tests, respectively. The logit model The logit and probit are the two most com- monly used models for assessing the effects of various factors that affect the probability of adoption of a given technology. These models can also provide the predicted prob- ability of adoption. Both models usually yield similar results. However, the logit model is simpler in estimation than probit model (Aldrich and Nelson, 1984). Hence, the logit model will be used in this study to analyze the determinant of Small- scale irrigation utilization. Following Guja- rati (2003) and Aldrich and Nelson (1984) the logistic distribution function for the utilization of small-scale irrigation schemes is specified as: (1) Where, Pt = is the probability of using the ir- rigation for the i th farmer and it takes 0 or 1. e zi = stands for the irrational number e to the power of Zi . Zi = a function of n-explanatory variables which is also expressed as: Zi = B0+B1X1+B2X2+…+BnXn (2) Where, X1 X2… Xn are explanatory variables. B0- is the intercept, B1, B2 … Bn are the logit parameters (slopes) of the equation in the model. The slopes tell how the log-odds ratio in fa- vor of using the small-scale irrigation schemes changes as an independent variable changes. The unobservable stimulus index Zi assumes any values and is actually a lin- ear function of factors influencing adoption decision of small-scale irrigation schemes. It is easy to verify that Zi ranges from -∞ to ∞, Pi takes 0 or 1 and that Pi is non-linear re- lated to the explanatory variables, thus satis- fying two requirements:  As Xi increases Pi increases but never steps outside the 0 and 1 interval; and  The relationship between Pi and Xi is non-linear, i.e., one which approaches zero at slower and slower rates as Xi gets small and approaches one at slower and slower rate as Xi gets very large. But it seems that in satisfying these requirements, an estimation problem has been created because Pt is not only non-linear in Xi but also in the B’s as well, as can be seen clearly below. Pt = 1 (3) 1 + e -(B 0 +B 1 X 1 + B 2 X 2 + . . . +B n ) Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 260 This means the familiar OLS procedure can- not be used to estimate the parameters. But this problem is more apparent than real be- cause this equation is intrinsically linear. If Pt is the probability of adopting a given small- scale irrigation scheme then (1- Pt), the probability of not adopting, can be writ- ten as: 1- Pt = 1 (4) 1 + e Z i Therefore, the odds ratio can be written as: = = (5) Now is simply the odds ratio in favor of adopting small-scale irrigation schemes. It is the ratio of the probability that the farmer would adopt the utilization of small- scale irrigation schemes to the probability that he/she would not adopt it. Finally, tak- ing the natural log of equation 15, the log of odds ratio can be written as: Li = = = =Bo + (6) Where, Li is log of the odds ratio in favor of small-scale irrigation schemes adoptions, which is not only linear in Xi , but also lin- ear in the parameters. Thus, if the stochastic disturbance term (ui), is introduced, the logit model becomes: Zi =B0+B1X1+B2X2+…+Bn Xn+ ui (7) This model can be estimated using the itera- tive maximum likelihood (ML) estimation procedure. In reality, the significant explana- tory variables do not have the same level of impact on the adoption decision of farmers. The relative effect of a given quantitative explanatory variable on the adoption deci- sion is measured by examining adoption elasticity’s, defined as the percentage change in probabilities that would result from a percentage change in the value of these variables. To calculate the elasticity, one needs to select a variable of interest, compute the associated Pt, vary the Xi of in- terest by some small amount and re-compute the Pi, and then measure the rate of change as where d Xi and d Pi stand for per- centage changes in the continuous explana- tory variable (Xi) and in the associated prob- ability level (Pt), respectively. When d Xi is very small, this rate of change is simply the derivative of Pt with respect to Xi and is expressed as follows (Aldrich and Nelson, 1984): = = (8) The effect of each significant qualitative ex- planatory variable on the probability of adoption is calculated by keeping the con- tinuous variables at their mean values and the dummy variables at their most frequent values (zero or one). Results and discussions Results of analysis of socio-economic char- acteristics of the surveyed households are presented in Table 1. They show that farm income of irrigation users were Birr 87290.45 and the average for the non-users were Birr 67983.62. The t-test analysis re- vealed that the mean annual farm income of the two groups was statistically significant at less than 1 % probability level. The average Crop income of irrigation users were Birr 19718 and the average for the non-users were Birr 12899. The t-test analysis revealed that the mean annual crop income of the two groups was statistically significant at less than 1 % probability level. The average live- stock income of irrigation users were Birr 5257 and the average for the non-users were Birr 4034. The t-test analysis revealed that the mean annual crop income of the two groups was statistically significant at 5% probability level. The average annual non/off-farm income of irrigation users was Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 261 1694.48 birr while the annual average for non-users was 404birr. The t-test showed that there was statistically significant mean difference between the two groups at 5 % probability level. The average age of users and non-users were 39 and 44 years respectively. From the sta- tistical analysis performed, it is found out that there was statistically significance mean difference between users and non-users at less than 1 % probability level. The result indicates that irrigation users (4) had more average years of formal schooling than non- users (2). The mean difference of the two groups was statistically significant at 1% probability level. Similarly on average irri- gation users contacts extension gents (26 times) than non-users (13times). The t-test indicated that there was statistically signifi- cant difference between two groups in terms of frequency of extension contact f at 1% probability level. The study also showed that out of the 200 sample households 190 own (rear) livestock. The mean livestock holding for user households was 4.296 TLU and 2.987 TLU for non-users. The mean differ- ence of the two groups was statistically sig- nificant at 1% probability level. Table 1: Preliminary statistics for continuous variables Variables All sample (N=200) Participants (N=100) Non –participants (N=100) t- value Mean SD Mean SD Mean SD Income 77637 27529 87290 28098 67984 23358 -5.28*** Crop income 16309 11780 19718 14647 12899 11630 -4.27*** Liv income 4646 3763 5257 4471 4034 2778 -5.28*** Age 41.59 11.59 38.96 11.57 44.22 11.05 3.288*** Education 3.08 3.98 4.18 4.23 1.99 3.39 -4.037*** Extension 19.58 23.5 26 28.4 13.2 14.9 -4.004*** Livestock 3.64 2.43 4.30 2.53 2.99 2.15 3.945*** N-F income 1049.2 3819 1694.48 4924.42 404 2057.4 -2.418*** Irrigation dist 25.38 11.94 20.97 11.80 29.78 10.93 5.604*** Whether road dist 92.32 33.47 80.10 28.87 104.55 33.42 5.537*** Source: Own survey result.*, **, *** significant at 10%, 5%and 1% probability level respectively The result also revealed that irrigation users had on average less weather road distance (80) than non-users (104) in minutes. The mean difference between the two groups with regard to distance from the weather road was statistically significant at 1% prob- ability level. The result also shows that irri- gation users had significantly less distance (20.97) of irrigation source than non-users (29.78) in minutes. Table 2 shows that irrigation users (42%) have had significantly more fertile land than non-users (22%) according to their opinion. Similarly irrigation users were more partici- pated (24.5%) in leadership of social organi- zations, than non-users (10%). The chi- square test between the two groups was found to be significant at 1% probability level. Finally the result also revealed that 35.5 percent of the users and 41.5% of non- users transport their produce on back ani- mals. Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 262 Table 2: Preliminary statistics for discrete variables Variables Irrigation-users (N=100) Non-users (N=100) Total (N=100) χ2- value Number % Number % Number % Soil fertility Fertile 84 42 44 22 128 64 Not fertile 16 8 56 28 72 36 34.722*** Social status Participated 49 24.5 20 10 69 34.5 Not-part 51 25.5 80 40 131 65.5 18.608*** Transportation Pack animals 71 35.5 83 41.5 154 77 Otherwise 29 14.5 17 8.5 46 23 4.065*** Source: Own survey result.***,* significant at 1% and 10% probability level Determinants of participation in small- scale irrigation In the estimation data from the two groups; namely, participant and non-participant households were pooled such that the de- pendent variable takes a value 1 if the household was irrigation user (treated) and 0 otherwise. As it was indicated in Table 4, the results indicated that participation is significantly influenced by seven explanatory variables. Age of household head, means of transporta- tion, participation in social organization, non-farm income, and cultivated land area and distance from weather road and distance from irrigation scheme were significant variables which affect the participation of the household in small-scale irrigation scheme utilization. Age was negatively and significantly related with probability of participation at 5% probability level. The odds ratio of 0.96 im- plies that, other things being constant, the odds ratio in favor of using irrigation de- creases by a factor of 0.96 as age increase by one year. The reason was that older farmers are less likely to adopt innovations and thought to be more conservative in imple- menting modern technologies. This result is consistent with the findings of Bigsten and Abebe (2003) and Hilina (2005). Irrigation distance has a negative and sig- nificant effect on probability of participation at 5% probability level. The odds ratio of 0.96 for irrigation distance implies that, other things being constant, the odds ra- tio in favor of using irrigation water in- creases by a factor of 0.96 as irrigation dis- tance decreases by one unit (in minutes). Within the same topography, this could be households who are situated in nearby places do not incur much cost to access the irrigation scheme; therefore, they quickly decide to participate in the scheme. This re- sult is consistent with the findings of Abonesh (2006), Yenetila (2007) and Asayehegn et al. (2011). Transportation has been found to be nega- tively related to the probability of being par- ticipated at 1 % significant level. The possi- ble justification is that most of the sample households use pack animals as a means of transportation due to lack of transportation facilities and unavailability of good roads. The odds ratio of the variable indicated that other things remain constant; the probability of the household being par- ticipated would decrease by a factor of 0.316 if this means of transportation be- come pack animals. Tracey-White (2005) puts idea of lack of transportation facilities and unavailability of good road hampered the farmers’ decision and in turn agricultural productivity. The result also showed that access of family members in non-farm income source had a Positive and statistically significant relation Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 263 with probability of participation at 10% probability level. Its odds ratio effect shows that, participation of family members in non/off-farm income increase probability of participation in irrigation farming by 1.001, other variables being constant. The implica- tion of this result is that, irrigation farming like any other business requires financial capital. It also needs chemicals, seeds, fertil- izers and in certain instances irrigation pipes and sprinklers. This result is consistent with the findings of Asayehegn et al. (2011), Yenetila (2007) and Haji (2003). Cultivated land area was found to be posi- tive and significantly affect probability of participation. The reason for this could be that fragmentation of cultivated land is a problem of crop diversification for most of the farmers in the study area. The odds ratio implies that if other factors are held con- stant, the odds ratio in favor of using ir- rigation water increases by a factor of 7.83 as farm size increase by one unit (ha). This result is consistent to the findings of Beyene et al. (2000), Hirko (2009) and Be- lay et al. (2010). Similarly, weather road distance was found to be negative and statistically significant at 5% probability level with probability of par- ticipation. The reason for this could be that, transport operators are in most cases reluc- tant to reach such areas and some of the farmers fail to get their produce to the mar- ket in time. This tends to disadvantage communal farmers to participate in the re- cent boom in irrigation farming. The values of odds ratio also implies that if other factors are held constant, the odds ratio in favor of using irrigation water decreases by a factor of 0.983 as weather road distance increase by one unit (minute). This result is consis- tent with the findings of Beyene et al. (2000) and Takele (2008). Social organization, this variable has a posi- tive and significant relationship to the prob- ability of participation at 1% probability level. This is because those farmers that have position in social organization are parts that responsible in managing and resolving irrigation related conflicts, and therefore, it might be due to influential power over oth- ers. The odds ratio of the variable indi- cated that other things remain constant; the odds ratio in favor of using irrigation in- crease by a factor of 3.836 as the farmers being participated in social organization. This result is consistent with the findings of Haji (2003) and Yenetila (2007). Table 3: Logistic regression results for determinants of participation in irrigation Variables Coefficient Odds Ratio SE Z Constant 4.119** 1.894 2.17 Age -0.039** 0.962 0.017 -2.32 Sex 1.018 2.766 0.657 1.55 Education 0.03 1.031 0.075 0.4 Non-farm income 0.00012* 1.00012 0.0001 1.74 Family size -0.094 0.91 0.122 -0.77 Economic active force 0.031 1.031 0.222 0.14 Cultivated land 2.058* 7.832 1.084 1.9 Livestock holding 0.03 1.03 0.092 0.33 Irrigation distance -0.042** 0.959 0.021 -2.02 Farmers training 0.144 1.155 0.454 0.32 Extension 0.005 1.005 0.02 0.26 Transportation -1.151*** 0.316 0.452 -2.55 Social status 1.344*** 3.836 0.402 3.35 Soil fertility 0.175 1.192 0.496 0.35 Weather road distance -0.017** 0.983 0.008 -2.18 Number of obs = 200 Pseudo R 2 = 0.2778 Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 264 Prob > chi 2 = 0.0000 Log likelihood = -100.12 LR chi 2 (15) = 77.01 Source: own survey result. *, ** and *** mean significant at 10%, 5% and 1% probability levels, respec- tively Summary and conclusion This study was carried out to examine the effect of small scale irrigation on farm households’ income. For this study, both primary and secondary data were used. The primary data source was gathered from 200 sample households (100 users and 100 non- users) using semi-structured questionnaires. Secondary data were collected from differ- ent sources to support primary data. Data analysis was carried out using preliminary statistics and econometric techniques. The logistic regression result shows that Par- ticipation is significantly influenced by seven explanatory variables. The variables age of household head, distance to irrigation scheme, size of cultivated land, non-farm in- come, means of transportation, distance to weather road and household head participa- tion in social organizations were the signifi- cant variables which affect the participation of the household in irrigation farming. Recommendations Small-scale irrigation is important develop- ment effort to ensure farm income if prop- erly implemented. Based on the empirical findings reported in this thesis, the following recommendations are forwarded: This study has found evidence that the irri- gation in the study area has shown that par- ticipant households have more farm income than non-participant households. This has an encouraging message for program designers, implementers, and funding agents to take proper action to achieve the intended goals of securing households food security by im- proving efficiency in production. The findings indicate that irrigation access is an important factor for increase farm house- holds’ income. Concerned bodies should give attention for promoting access to irriga- tion to encourage household farm efficiency. Access to irrigation through irrigation de- velopment for rural households will have major impacts. These are not only an in- crease in household production, income and reduction of dependency on food aid, but also have a significant positive impact on the overall rural economy. Therefore, government and other stake- holders should provide support through the establishment of more irrigation project and other agricultural production increasing pro- jects that can assist farmers to produce their own food and be food secured. Policy mak- ers need to promote irrigation development so that farmers can irrigate more crops, fruits, vegetables and other fresh produce. The age of the household head has a nega- tive and significant effect on the adoption of irrigation farming. Age happens to be one of the human capital characteristics that have been frequently associated with non- adoption in most adoption studies. Among the several reasons that could explain the negative effect of age on adoption is the fact that older farmers tend to stick to their old production techniques and are usually less willing to accept change. In addition young people are associated with a higher risk- taking behavior than the elderly. So devel- opment agents and younger members should have to aware the elders the benefit of new technology in agricultural production through practical demonstration. Nearness to the water source is also nega- tively related to participation in irrigation. Those households that are situated near the water source are willing to participate. Therefore, the construction of small scale ir- rigation should consider the distance be- Asian Journal of Agriculture and Rural Development, 4(3)2014: 257-266 265 tween the water source and villages for a better use of the schemes by households. Farmer’s position in local organizations has a positive influence on the adoption of water technology. This tends to reveal that farmers with positions are more likely to have easy access to information due to their influential power over others. So it is neces- sary to correct such biased flow of informa- tion towards positioned farmers and ensure evenly dissemination of information on new agricultural technologies through farmers’ local organizations. Size of cultivated land and household par- ticipation in irrigation farming are positively and significantly related indicating larger farm size improves household participation. Households with large farm size are found to be participated more than others however; there may not be a possibility of expanding cultivated land size anymore because of in- creasing family size and degradation of the existing farm land. Therefore, household must be trained as to how to increase pro- duction per unit area (productivity). Farmers cannot adopt technologies if roads and transport are inadequate and poor for them to acquire technology-related inputs, or to market their produce. The infrastructure issue typically illustrates that the adoption process does not only depend on the farm- ers’ willingness, but partakes to an overall sustainable rural development process. So in this empirical findings distance from the main (all weather) road negatively and significantly influences the participation of farmers in irrigation technology. Therefore, the government should strengthen recent ef- forts of expanding rural road networks in or- der to open-up market for irrigated crops and the provision of necessary inputs for irri- gated agriculture. The study revealed that means of transporta- tion used in the study area negatively and significantly influenced farmers’ small-scale irrigation utilization. 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