Determinants of fertilizer use on maize in Eastern Ethiopia: A weighted endogenous sampling analysis of the extent and intensity of adoption

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1 Determnants of fertlzer use on maze n Eastern Ethopa: A weghted endogenous samplng analyss of the extent and ntensty of adopton B Fufa & RM Hassan 1 Abstract Factors nfluencng the extent and ntensty of fertlzer adopton on maze producton n Ethopa were analyzed. A Weghted Endogenous Samplng Maxmum Lkelhood estmator was used n the specfcaton of a Probt and Tobt fertlzer adopton models. The results have mportant mplcatons for the formulaton of polces and programs targeted to promoton of fertlzer use n small-scale maze producton. Those nclude mproved road nfrastructure, consderaton of weather related crop falure nsurance programs, development of drought tolerant cultvars and targetng partcular farmer groups. 1. Introducton Agrculture contrbutes about 52% of the GDP and 85% of the populaton s dependent drectly or ndrectly on agrculture n Ethopa. Whle agrculture s growng at 1.6% per annum, the populaton of the country s growng at 3% and s expected to double by year 2020 (Befekadu and Brehanu, 2000). Ths ndcates the need to ncrease productvty of agrculture to keep pace wth populaton to ensure adequate supply of food n the future. As a result, the government has embarked on a massve agrcultural extenson program snce 1994/95 to promote the use of mproved crop producton technologes, a key component of whch s chemcal fertlzers. However, adopton and ntensty of fertlzer applcaton, especally on maze grown by smallholders remaned very low despte government efforts to promote ts use. D-Ammonum phosphate (DAP) and urea are the two most mportant fertlzers that are wdely promoted by the extenson program. Consumpton of the sad two fertlzers has dropped sgnfcantly between 1995 and 1997 showng a slght ncrease of only 3% n PhD Canddate and Professor respectvely, Department of Agrcultural Economcs, Rural Development and Extenson, Unversty of Pretora, South Afrca. E-mal: akassa2000@yahoo.com. 38

2 Maze s one of the major cereals grown n Ethopa and s the man staple food n many parts of the country. Maze producton has slghtly ncreased over the past decade wth area expanson beng the man source of growth compared to neglgble yeld gans. Fertlzer has been a major component of mproved maze producton technologes beng promoted by the extenson package. It s therefore of crtcal mportance for agrcultural research and polcy desgn to better understand the reasons behnd the persstence of low fertlser adopton by farmers n the country. Ths study makes an attempt to analyse determnants of fertlser use by small-scale maze producers n Ethopa. The analytcal framework and emprcal models of technology adopton are dscussed n secton 2. The emprcal model and samplng procedures are specfed n secton 3. Secton 4 presents and dscusses fndngs and conclusons and polcy mplcatons are drawn n the last secton. 2. Analytcal framework and emprcal models of technology adopton Lmted dependant varables models have been wdely used n technology adopton studes. The sad models are based on the assumpton that, n adoptng new agrcultural technologes, the decson maker (farmer) s assumed to maxmze expected utlty (expected proft) from usng a new technology subject to some constrants (Feder et al, 1985). In the case of categorcal dependent varables (bnomal or multnomal) qualtatve choce models of adopton such as the logt and Probt are usually specfed. These models are commonly used to analyse stuatons where the choce problem s whether or not (0-1 value range) to adopt a new technology. The Probt specfcaton has advantages over logt models n small samples. The present study therefore employed a Probt model to examne determnants of farmers decson to adopt or not adopt fertlsers on maze. The Probt model specfcaton used n ths study s gven by ( + x ) F( ) AF = F α β = (1) z Where, AF s the dscrete adopton choce varable, F s the cumulatve probablty dstrbuton functon, β s the vector of parameters, x s the vector of explanatory varables and z s the Z-score of β x area under the normal curve. The expected value of the dscrete dependent varable n the Probt model condtonal on the explanatory varables s gven by [ y / x] 0[ 1 F( β )] [ ( )] ' x + F β ' x F ( β ' ) E = = (2) 39

3 The margnal effect of each explanatory varable on the probablty of adopton s: [ y / x] ' φ( β x)β E x = Where φ (). s the standard normal densty functon. (3) Whle the Probt model s adequate for analysng adopton decsons that occur over a dscrete range such as yes or no, t does not handle the case of adopton choces that have a contnuous value range that s truncated from below. Ths s the typcal case for fertlser adopton decsons where some farmers apply postve levels of fertlser whle others have zero applcatons (non-adopters). Intensty of use s a very mportant aspect of technology adopton because t s not only the choce to use but also how much to apply that often more mportant. The Tobt model of Tobn (1958) s used to handle truncated dstrbuton dependent choce varables such as level of fertlser use. Ths study used the Tobt model specfcaton to analyse determnants of the varaton n ntensty of fertlzer use by maze farmers as gven by ( z) + σf ( z) AD = xβ + ε * AD, f 0, f AD * > AD 0 * AD < AD 0 (4) Where AD s the adopton ntensty (level of applcaton), AD 0 s the crtcal value adopton ntensty, x, β and F (z) are as defned n (1). σ s the standard error term, f ( ) x the value of the dervatve of the normal curve at a gven pont (densty functon). McDonald and Mofft (1980) showed that the margnal effect of an explanatory varable on the expected value of the censored (truncated dstrbuton) dependent varable s gven by ( ) E AD x ( ) = F z β (5) On the other hand, the change n the probablty of adopton as the explanatory varable x changes s gven by: ( ) ( ) F z f z β = x σ (6) 40

4 And the change n the ntensty of adopton among adopters as an explanatory varable changes s gven by: * ( ) ( ) β 1 ( ) ( ) ( ) AD zf z f z = 2 x F z F z 2 (7) Adopton of agrcultural technologes s nfluenced by a number of nterrelated components wthn the decson envronment n whch farmers operate. For nstance, Feder et al (1985) dentfed lack of credt, lmted access to nformaton, averson to rsk, nadequate farm sze, nsuffcent human captal, tenure arrangements, absence of adequate farm equpment, chaotc supply of complementary nputs and napproprate transportaton nfrastructure as key constrants to rapd adopton of nnovatons n less developed countres. However, not all factors are equally mportant n dfferent areas and for farmers wth dfferent soco-economc stuatons. Soco-economc condtons of farmers are the most cted factors nfluencng technology adopton. The varables most commonly ncluded n ths category are age, educaton, household sze, landholdng sze, lvestock ownershp and other factors that ndcate the wealth status of farmers. Farmers wth bgger land holdng sze are assumed to have the ablty to purchase mproved technologes and the capacty to bear rsk f the technology fals (Feder et al, 1985). Ths was confrmed n the case of fertlzer by Nkonya et al (1997) n Tanzana, Hassan et al (1998a) n Kenya and Yohannes et al (1990) n Ethopa whereas; farm sze dd not matter n Nepal (Shakaya and Flnn, 1985). The role of educaton n technology adopton has been extensvely dscussed n the lterature. Educaton enhances the allocatve ablty of decson makers by enablng them to thnk crtcally and use nformaton sources effcently. Producers wth more educaton should be aware of more sources of nformaton, and more effcent n evaluatng and nterpretng nformaton about nnovatons than those wth less educaton (Woznak 1984). Educaton was found to postvely affect adopton of mproved maze varetes n West shoa, Ethopa (Alene et al, 2000), Tanzana (Nkonya et al, 1997) and Nepal (Shakaya and Flnn, 1985). Some new technologes are relatvely labour savng and others are labour usng. For those labour-usng technologes, lke mproved varetes of seeds and fertlzer labour avalablty plays sgnfcant role n adopton. Green and Ng ong ola (1993) found regular labour to be an mportant factor that postvely nfluences adopton of fertlzers n Malaw. 41

5 On the other hand, age of the household head s an mportant factor affectng adopton of agrcultural technologes. The conventon approach to adopton study consders age to be negatvely related to adopton based on the assumpton that wth age farmers become more conservatve and less acceptable of new deas. On the other hand, t s also argued that wth age farmers gan more experence and acquantance wth new technologes and hence are expected to have hgher ablty to use new technologes more effcently. Some studes found age to be an mportant determnant of adopton (Hassan et al, 1998b) whle others ddn t (Voh, 1982; Nkonya et al, 1997; Chlot et al, 1998). The effect of famly sze on adopton can be ambguous. It can hnder the adopton of technologes n areas where farmers are very poor and the fnancal resources are used for other famly commtments wth lttle left for purchase of farm nputs (Voh, 1982; Shakya and Flnn, 1985). On the other hand, t can also be an ncentve for adopton of new technologes as more agrcultural output s requred to meet the famly food consumpton needs (Yonannes et al, 1989) or as more famly labour s requred for adopton of labour ntensve technologes (Hassan et al, 1998a). In addton, adopton of new agrcultural technologes depends on a number of nsttutonal factors. The ntroducton of new technologes creates demand for nformaton useful n makng decsons (Woznak, 1984). Agrcultural extenson organzatons supply useful nformaton about new agrcultural technologes. Access to such sources of nformaton can be crucal n adopton of mproved varetes (Nkonya et al, 1997; Hassan et al, 1998b; Chlot et al, 1998). Furthermore, rsk assocated wth the adopton of agrcultural technologes s another mportant factor n adopton decsons (Parkh and Bernard, 1988; Yohannes et al, 1990; Shyan et al, 2002; Hassan et al, 1998). The studes revewed above show nconsstent results about the determnants of adopton of new technologes by farmers. In addton, none of the above studes addressed how adopton of fertlzer s affected by farmers perceptons about the expected ranfall condtons, the percepton of farmers about the current prces of fertlzers and the topographc condtons of maze farm plots. 3. Specfcaton of the emprcal model In lght of the results of prevous emprcal research, ths study consdered a number of explanatory varables n modellng the fertlser adopton behavour of maze farmers n Ethopa. Soco-economc factors such as age of the head of the household head, famly sze, lteracy, land holdng sze and 42

6 wealth status of the farmer were consdered mportant determnants of adopton. The age of the household head (Age) s measured n years, total land holdng sze (Land) s measured n Qund 2 and lteracy (Ltd) takes a value of one f the farmer s lterate and zero otherwse. Household sze (Housz) s measured by the number of people lvng n the household. Income from T chat 3 (T chatd) and off farm ncome (Offncd) were ncluded to reflect the fnancal ablty of the farmer to buy external nputs, both take the value of one f the farmer earns ncome from the respectve actvtes and zero otherwse. Furthermore, to analyse the effect of the expected proftablty of fertlzer adopton, farmers percepton about the current prce of fertlzer (Fertpd) was ncluded. Ths takes value of one f the farmer feels the prce s too hgh and zero otherwse. The topographcal nature of land (Slopd), whch takes the value of one f the plot s flat and zero otherwse was ncluded. Furthermore, to see the effect of rsk assocated wth the use of fertlzer, farmers percepton about the expected ranfall condton durng the producton year (Rand) was ncluded. Ths s measured as one f the farmer perceved the ranfall s good and zero otherwse. Dstance of the home of the farmer (Mktd) from the nearby market and the resdence of the extenson worker (Extd) both measured n mnutes of walkng dstance were selected to capture the mpact of nsttutonal constrants on fertlzer adopton n the area. The above explanatory varables were used to estmate the Probt and Tobt models of fertlser adopton as specfed below AF = β + β Age+ β Land + β Ltd + β Rand + β T ' chatd + β Offncd β slopd + β Housz + β Fertpd + β Mktd + β Extd (8) Where AF takes the value of one for adopters or zero for non-adopters n the case of the Probt model and s the level of fertlser used n kg per qund of land n the Tobt model. 4. Study area and samplng procedure The study was conducted n Dadar dstrct, located n the Eastern Hararghe zone of the Oromya regonal state of Ethopa. Beng part of the Ethopan hghlands, the area receves an average annual ranfall of more than 900 mm. Maze and sorghum are the major cereals grown n the area. Maze s the man staple food crop n the dstrct. Beng one of the major maze producng 2 Qund s a local measure of land holdng. One hectare s equvalent to eght qunds. 3 T chat s a perennal shrub grown wdely by farmers n East Hararghe. The leaves of the shrub are chewed by humans for stmulaton purposes. 43

7 dstrcts n the zone, the area has been ncluded n the government s agrcultural extenson package snce 1996/97. Purposve samplng of a total of 100 farm households was surveyed. Accordngly, 50% the surveyed farmers were from those who have chosen to jon the extenson package and the remanng 50% were from farmers chosen not to partcpate n the extenson package. In studes nvolvng lmted dependent varable models, sometmes the observed sample of the dependent varable s delberately skewed n favour of one outcome or the other. In estmatng models for such studes, the bas n the sample could easly be transmtted to parameter estmates. Mansk and Lerman (1997) proposed a Weghted Endogenous Samplng Maxmum Lkelhood (WESML) method of correctng for ths bas. Ther estmator requres that the true populaton proporton w 1 and w 2 and sample proportons p 1 and p 2 be known. Then the estmator s obtaned by maxmzng the weghted lkelhood gven by Log n ' ( q β x ) L = w log F (9) w w 1 2 Where, w + ( ) = y 1 y p1 p2 The second step nvolves the correcton of the approprate covarance matrx of the estmator. Whte s (1982a) robust sandwch estmator for the asymptotc covarance matrx of the quas-maxmum lkelhood estmator s gven by 1 1 Est. asy.var β = H β H (10) Where, H s the Hessan matrx of the parameters. However, the shortcomngs of WESML and choce based samplng estmator are the very large standard error of the parameters that are obtaned at the end (Greene, 2000). The sample sze ndcated above s used n ths study by makng modfcatons followng the above procedure. Secondary sources from the dstrct level offce of agrculture show that about 25% of the farmers n the area use fertlzer n maze producton. So the weghtng varable for the estmaton of the model s gven by w = y1 + (1 y1) (11) 44

8 Where, y 1 s the value of the dependent varable, whch takes values of one and zero n the Probt model. Where as n the Tobt model, y 1 s censored at zero for non-adopters and takes contnuous values greater than zero for adopters. The correcton for the asymptotc covarance matrx of the Probt model s made followng the procedure n the second step above. The Tobt model was estmated by usng the weghtng varable only, as there s no procedure developed so far for the correcton of the covarance of the estmated parameters. 5. Results and dscusson 5.1 Probt model results The explanatory varables of the Probt model reported n Table 1 had the expected sgn. Age was negatvely and sgnfcantly related to adopton of fertlzer suggestng that old farmers are more conservatve wth respect to fertlzer use than young farmers n the study area. Farmers expectaton of a good ranfall season was postvely and sgnfcantly assocated wth fertlzer adopton. Farmers percepton that the current fertlzer prce s hgh was negatvely and sgnfcantly related to adopton. The removal of fertlzer subsdy n the country snce 1997 has ncreased the actual prce of fertlzer by more than 20%. Table 1: Estmated results of probt model of adopton of fertlzer Varable Coeffcent Standard error P-value Margnal effect Constant Age * Land Ltd Rand * T chatd Offncd Slopd Housz Fertpd ** Mktd Extd Restrcted log lkelhood ; Ch-Square ; ** Sgnfcant at 1% ; * Sgnfcant at 5% The margnal effect values of the Probt model n Table 1 show the change n the probablty of adopton of fertlzer for each addtonal unt ncrease n ndependent varables. Farmers wth the percepton of good ranfall condtons had 21% hgher probablty of adopton than farmers who perceved a bad season. Farmers who thought that the prce of fertlzer was hgh had 45% less 45

9 probablty of adopton. The probablty of adopton decreases by 0.79% for every year of age. The probablty of adoptng fertlzer by farmers cultvatng medum to steep maze plots was 15% hgher than for farmers cultvatng flat maze plots. 5.2 Tobt model results The results of the Tobt model reported n Table 2 show that all the varables have the expected sgn. The margnal effects show that for each addtonal year of age, the use of fertlzer declnes by 0.87kg/ha for the entre sample and by 1.6kg/ha for adopters. Postve expectaton about the ranfall condton ncreased the use of fertlzer by 22.07kg/ha and 41.92kg/ha for the entre sample and among adopters, respectvely. The percepton of hgh prce reduced the use of fertlzer by 46.2kg/ha and 87.79kg/ha for the entre sample and for adopters, respectvely. Farmers plantng maze on flat land tend to use about 29 kg of fertlzer less than those plantng on slopes. Ths can be attrbuted to the fact that farmers cultvatng flat land experence less leachng of fertlzer compared to steep slopes land. Table 2: The Tobt model of fertlzer adopton n Dadar dstrct Varable Coeffcent Standard error P-value Total change E( AD) x Change n probablty F( z) x Change among adopters ( AD) Constant Age * Land Ltd Rand ** T chatd Offncd Slopd Housz Fertpd ** Mktd Extd Log lkelhood functon ; σ = ; ** Sgnfcant at 1%; * Sgnfcant at 5%; z = ; Censored observatons = 50 ; Uncensored observatons = 50; F( z ) = 0.76 ; f( z ) = x 6. Conclusons and polcy mplcatons Fertlzer s consdered the most mportant nput for the achevement of ncreased agrcultural productvty and food securty status of farm households n Ethopa. However, fertlzer adopton remans very low, 46

10 especally among small-scale farmers n the country. The results of ths study showed that the age of the farmer, farmers expectatons of ranfall condtons and farmers percepton of the prce of fertlzer sgnfcantly affect the use and ntensty of adopton of fertlzer n the study area. In stuatons where the expected ranfall (weather) condton s bad, farmers are unwllng to use fertlzer. Ths s because farmers are not nsured aganst losses as a result of bad weather and forced to pay the cost of fertlzer they receved on credt. Due to the fact that crop loss nsurance schemes are nonexstent n countres lke Ethopa, agrcultural research has to focus on the development of mosture stress tolerant and early maturng varetes. In addton, the expanson of small-scale rrgaton projects n rural areas can help overcome the adverse effects of ranfall shortage experenced by most parts of the country. On the other hand, dependng on the expected ranfall condton durng a partcular year fertlzer demand may be hgh or low. Thus, agrcultural extenson and supplers of agrcultural nputs (publc or prvate) should adjust the prce and the servces they provde accordngly. Increased fertlzer prces and the concomtant decrease n output prces have been the most mportant factors assocated wth use of new agrcultural technologes n Ethopa recently. Part of the ncrease n fertlzer prces to farmers s the ncreased transportaton cost for the movement of fertlzer from the central market. Due to poor road condtons, runnng costs for transport operators s very hgh. The development of rural roads reduces the transacton cost assocated wth acquston of farm nputs and sale of farm products. Ths enables farmers to buy farm nputs at lower prces and sell ther produce at compettve prces. More effort n expandng roads n rural areas s therefore needed. References Alene AD, Poonyth D & Hassan RM (2000). Determnants of the adopton and ntensty of use of mproved maze varetes n the central hghlands of Ethopa: A Tobt analyss. Agrekon 39(4): Befekadu D & Brehanu N (2000). Annual report on the Ethopan economy. The Ethopan Economc Assocaton. Volume 1. Chlot Y, Shapro BI & Mulat D (1998). Factors nfluencng adopton of new wheat technologes n Walmara and Adds Alem areas of Ethopa. Ethopan Journal of Agrcultural Economcs 1(1):

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