Impact of infestation by parasitic weeds on rice farmers productivity and technical efficiency in sub-saharan Africa

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1 Afrcan Journal of Agrcultural and Resource Economcs Volume 1 Number 1 pages Impact of nfestaton by parastc weeds on rce farmers productvty and techncal effcency n sub-saharan Afrca Smon Akahoua N cho* Internatonal Insttute of Tropcal Agrculture, Tamale, Ghana. E-mal: s.ncho@cgar.org Monque Mourts Busness Economcs, Wagenngen Unversty (WUR), Wagenngen, The Netherlands. E-mal: monque.mourts@wur.nl Matty Demont Socal Scences Dvson, Internatonal Rce Research Insttute (IRRI), Los Baños, Phlppnes. E-mal: m.demont@rr.org Patrce Y. Adegbola Insttut Natonal des Recherches Agrcoles du Benn (INRAB). E-mal: patrce.adegbola@yahoo.fr Alfons Oude Lansnk Wagenngen Unversty (WUR), Busness Economcs, Wagenngen, The Netherlands. E-mal: alfons.oudelansnk@wur.nl * Correspondng author Abstract Rce producton s crucal for food securty and ncome generaton n sub-saharan Afrca. However, productvty and techncal effcency levels n rce producton systems are severely constraned by botc constrants such as parastc weeds. Ths paper assesses the mpact of nfestaton by parastc weeds on rce farmers techncal effcency and examnes the potental role of manageral factors n mprovng techncal effcency. Household and feld survey data were collected from rce farmers n Cote d Ivore and Benn n West Afrca. A stochastc fronter producton functon was estmated, whch allows for dentfyng the levels of exogenous factors that prevent farmers from mprovng techncal effcency levels. The results suggest that farmers cope wth parastc weeds through learnng from experencng nfestatons by parastc weed. The results wll assst natonal extenson n desgnng segmented tranng programmes that are better talored to rce farmers needs and preventng food securty from beng jeopardsed by parastc weeds. Key words: ran-fed rce; parastc weeds; sub-saharan Afrca; stochastc fronter model; techncal effcency 1. Introducton Rce producton s an mportant component of strateges for food securty n sub-saharan Afrca and ncome generaton n rce-producng regons (Nakano et al. 013). However, t s faced wth many botc and abotc constrants that negatvely affect productvty. These constrants undermne the efforts made by many sub-saharan countres snce the 008 food crss to boost domestc rce producton n order to fll the gap between producton and consumpton (Demont 013). Among the botc constrants, weeds, and partcularly the parastc weeds Strga spp. and Rhamphcarpa fstulosa, are the most damagng n ran-fed rce producton envronments (Oerke & Dehne 004; Rodenburg & Johnson 009; Rodenburg et al. 016). Weeds pose a serous threat to food securty n sub-saharan Afrca (AfrcaRce 013; A. Dagne et al. 013), as average rce yeld loss due to weeds s estmated

2 at 3% (Oerke & Dehne 004). Furthermore, t was estmated that, n 008, 53% of rce farmers experenced weed problems n ther felds and about 33% of rce areas were affected by weeds (A. Dagne et al. 013). However, weed problems n sub-saharan Afrca vary across countres and across rce-producton envronments. Cote d Ivore s reported to be among the countres wth the hghest proporton of farmers experencng weed problems (74%), as well as the hghest percentage of felds affected (49%) and yeld losses (40%). Infestaton levels are comparable n Benn, where 40% of rce areas are affected (A. Dagne et al. 013). However, the reported statstcs do not dstngush between non-parastc and parastc weeds. A recent study by Rodenburg et al. (016) estmated that the most lkely economc loss nflcted by all parastc weeds n rce n Afrca was some US $00 mllon, ncreasng by US $30 mllon annually. In Benn, the most mportant parastc weed threatenng rce producton s Rhamphcarpa (N cho et al. 014), whle both were observed n Cote d Ivore, wth a hgher proporton of farmers (35%) experencng Strga spp. than Rhamphcarpa (4%). Only a few emprcal studes have analysed rce farmers techncal effcency and ts determnants n sub-saharan Afrca (e.g. Audbert 1997; Sherlund et al. 00; Sngbo & Oude Lansnk 010; M. Dagne et al. 013). Snce many rce farmers are operatng under subsstence-based producton systems, ther food securty s hghly exposed to the stochastc forces of nature. Accountng for envronmental condtons n the estmaton of techncal effcency s hence crucal. However, to our knowledge only one study has addressed ths ssue n sub-saharan Afrca. Sherlund et al. (00) observed n a sample of 464 tradtonal rce plots n Cote d Ivore that techncal effcency levels ncreased after accountng for producton envronment condtons n the producton fronter. They concluded that controllng for factors such as pests, weeds and dseases yelds more accurate estmates of techncal effcency. Smlar fndngs were reported n techncal effcency studes elsewhere (Rahman & Hasan 008; Tan et al. 010). Moreover, snce rce s produced n a stochastc envronment, t s mportant not only to assess how those factors affect techncal effcency, but also how they nfluence ts varance (Wang 00). Hgher varance n techncal effcency mples a hgher producton uncertanty, and consequently hgher rsks of food nsecurty. Another shortcomng of earler studes s that they typcally assumed a monotonc relatonshp between techncal effcency and ts determnants, whle drvers of techncal effcency can be nonmonotonc (Wang 00). Indeed, Chen et al. (003) observed n the case of Chnese gran farms that the coeffcents of determnants of techncal effcency can change over dfferent quartles n the sample and may even swtch sgns. Identfyng non-monotoncty n the determnants of techncal effcency and ts varance enables the desgn of segmented extenson programmes that are better talored to farmers needs. Ths s mportant for persstent pests, such as parastc weeds n sub- Saharan Afrca, whch severely jeopardse food securty and requre complex pest management. Therefore, the contrbuton of ths study s to present the frst evdence of the mpact of parastc weeds on sub-saharan Afrca rce farmers productvty, techncal effcency and ts varance, and to dentfy the factors and the nature of ther relatonshp that affect these mportant determnants of food securty.. Methods and data.1 Theoretcal framng and model specfcaton Ths paper uses a stochastc fronter approach to analyse the mpact of parastc weed nfestaton on rce farmers techncal effcency. Ths approach was chosen because small-scale ran-fed rce systems n sub-saharan Afrca are subjected to stochastc producton envronments. Rce s grown n varous sol types, under dfferent ranfall patterns, plant dseases, pests or weed nfestaton levels, varous nput use patterns and other envronmental condtons (Sherlund et al. 00; Rahman & Hasan 008; Tan et al. 010). Moreover, the data used may be subject to measurement errors because they 36

3 are derved from farmers perceptons. Ths may affect the estmaton of techncal effcency. Hence, Coell et al. (1998) recommend the use of stochastc fronter models for sectors that rely heavly on nature, such as agrculture, and partcularly n the context of a developng country. In the producton process, factors such as weeds, dseases, pests and pollutants, whch are known as growth-reducng factors, lower attanable producton levels to the actual (observed) yeld levels (Zhengfe et al. 006). Thus, nput use and farmers productvty may be affected by farm envronmental condtons. Omttng the producton envronment condtons from the estmaton of the producton functon leads to based estmates for the producton fronter s coeffcents, an overstatement of techncal neffcency, and based estmates for the coeffcents of the determnants of techncal neffcency (Sherlund et al. 00; Rahman & Hasan 008). Varables related to the producton envronment were therefore ncluded n the producton fronter, as follows: Y f ( X, W ) u, (1) where Y s the output (paddy producton) of farmer, X s a vector of productve nputs, W s a vector of relevant envronmental varables (producton shfters) that control producton condtons for farmer, and v s a two-sded random error assocated wth factors beyond the control of the farmer. It s assumed to be d N (0, v ), ndependent of the u, and the u s a non-negatve random varable (u 0) assocated wth neffcency n producton. In ths study, farmers mght exhbt more varaton n ther neffcency because they perform n dfferent envronmental settngs, have dfferent experence n rce farmng and dfferent nput uses. A truncated-normal dstrbuton assumpton on u proposed by Stevenson (1980), whch allows for the neffcency dstrbuton to have a non-zero mode (whch s not the case n half-normal), was adopted. Therefore, u s assumed to be ndependently dstrbuted, followng a normal dstrbuton and truncated at zero, wth mean ( Z ) and varance ( (, u N Z u) ), where Z represents a vector of manageral varables and some soco-economc characterstcs to explan the neffcency of farmer. In order to dentfy factors that can explan rce farmers neffcency, a two-stage procedure adopted by earler studes has been recognsed as based (Kumbhakar et al. 01) because of a msspecfcaton of the frst step (Kumbhakar & Lovell 000; Wang & Schmdt 00). Gven the undesrable statstcal propertes of the two-stage procedure (Wang 00; Kumbhakar et al. 01), ths study used the sngle-stage approach proposed by Battese and Coell (1995). The presence of uncontrolled heterogenety n u n the stochastc fronter models causes bas n the estmaton of the parameters descrbng both the structure of the producton fronter and techncal neffcency (Kumbhakar & Lovell 000:1). A producton fronter wth truncated-normal dstrbuton was specfed wth heteroscedastcty n u and u n a cross-sectonal settng followng Wang (00) and Kumbhakar and Wang (01) to account for possble heterogenety n the data. y x ( v u ), () ~ 0,, (3) ~,, (4) z, (5) 37

4 exp( z ), (6) u where x nclude the productve nput varables X and envronmental varables W defned above, and the remanng are as defned above. The δ and γ are the correspondng coeffcent vectors of the varable vector z n (5) and (6) respectvely. In ths settng, the vectors of exogenous varables are allowed to affect neffcency through the pre-truncated mean and varance of u, vz. μ and u respectvely (Wang 00; Kumbhakar & Sun 013). Models that allow exogenous varables to exert nfluence through both the mean and the varance of the pre-truncated dstrbuton yeld the most plausble estmates of the determnants of techncal neffcency (Wang 00). Ths double parametersaton (of μ and u ) enables the capturng of non-monotoncty n the relatonshp between z varables and techncal neffcency (mean of u), and varance n u measured by the uncondtonal statstcs of E(u) and V(u) respectvely (Bera & Sharma 1999; Wang 00; 01). Non-monotoncty mples that, wthn the sample, the kth element of z, zk, can have both postve and negatve effects on producton effcency, dependng on the values of zk (Wang 00). Capturng non-monotoncty s crucal for a thorough understandng of the nature of the relatonshp between techncal neffcency and manageral and soco-economc varables (z).. Emprcal specfcaton and estmaton The log-lnear form of the Cobb-Douglas stochastc producton functon was estmated. The translog specfcaton was not used because of the unsatsfactory fttng to the data. Moreover, a lkelhood rato (LR) test of the Cobb-Douglas versus the translog resulted n P = 0.16 for Benn, P = 0.08 for Cote d Ivore and P = for the pool data, n rejecton of the translog. A dummy varable of the parastc weed nfestaton status of the rce felds was ncorporated nto the producton fronter model to account for the drect mpact of parastc weeds on the productvty of rce farmers (see Sherlund et al. 00; Rahman & Hasan 008). The full specfcaton of ths model for the th farmer s wrtten as: 4 lny ln X D v u, (7) 0 j j j 1 and 8 u Z, (8) 0 d d d 1 8 u 0 d Zd d 1, (9) where D s the dummy varable representng parastc weed nfestaton status, wth a value of 1 f rce farmer has nfested felds and zero otherwse; and β s the vector of parameters to be estmated. Ths s to account for the mpact of parastc weeds on the productvty of rce farmers. For nputs contanng zero values, the zero was replaced by 1 followng Battese and Coell (1995). The unknown parameters n equatons (7), (8) and (9), n addton to u and v, were estmated smultaneously by the method of maxmum lkelhood (Wang 01). The producer-specfc techncal effcency was estmated as: TE exp( u ) (10) 38

5 The predcton of TE s based on the condtonal mean of, gven the composed error ( v u ) and model assumptons usng the JLMS estmator (Battese & Coell 1988; Jondrow et al. 198). The lkelhood functon s expressed n terms of the varance parameters s v u and u / s (see Battese & Coell 1995). The pont estmator of the techncal effcency for the th farmer s TE E[exp( u ) ] 1 [( * / * ) * ] exp( * * ), (11) ( * / * ) where * [(1 ) z ], * (1 ) s, v, and represents the dstrbuton functon of the standard normal varable. To derve the margnal effects of z varables on techncal neffcency, we followed Wang (00) and Wang and Schmdt (00). Takng nto account the parametersaton n equatons (5) and (6), the margnal effect of z k on E( u ) s Eu ( ) ( ) ( ) ( ) ( ) k 1 k (1 ) z k ( ) ( ) ( ) ( ), (1) where /, and s the probablty densty functon of a standard normal dstrbuton and s as defned above. The non-monotonc neffcency margnal effects were estmated followng Belott et al. 01 and Wang (01). The most commonly ncorporated varables n a stochastc fronter model on techncal effcency n emprcal analyses are farmer s age, educaton, experence, gender, access to nformaton, land (varous aspects) and household sze (see Wlson et al. 001; Sherlund et al. 00; Rahman & Hasan 008; Tan et al. 010; Belott et al. 01) to capture the aspect of manageral capacty of farmers as defned by Rougoor et al Three varables were added to descrbe dfferent aspects of the parastc weeds problem, namely parastc weed nfestaton status (dummy varable), frequency of rce feld nfestaton durng the last fve years, and actual area of rce feld covered (%) by the parastc weeds. The dummy accounts for the drect effect of the nfestaton of parastc weeds on productvty, whle the other two varables are ncluded n the neffcency functon to account for the management capabltes of farmers and ther ndrect effect on productvty (through techncal effcency). The statstcs of varables used are summarsed n Table 1. 39

6 Table 1: Summary statstcs of varables and expected effects on productvty and techncal neffcency Expected sgn Benn (n = 17) Cote d Ivore (n = 40) Defnton of varables Mean SD Mean SD Output Rce producton (kg per farm) Input varables n producton functon Rce area cropped (ha) Labour (hours per feld) Seed (CFA per feld) Other nputs (CFA per feld) Parastc weed nfestaton status (1 = nfested, 0 = non-nfested) Manageral and soco-economc varables n neffcency functon Frequency of nfestaton (how often rce feld has been nfested n past 5 years) Land ownershps (1 = own, 0 = otherwse) Number of felds Area nfested (actual % of rce feld covered by parastc weed) Dstance from homestead (average dstance from rce feld to home n km) Gender of rce farmer (1 = female, 0 = male) +/ Experence n rce farmng (years) Household sze (person) +/ Notes: Fxed exchange rate: 1 = 656 FCFA; SD = standard devaton.3 Descrpton of data The data used were from a mult-stage stratfed sample of farmers n Benn and Cote d Ivore. Only ran-fed rce systems were consdered n ths study. For each country, rce-producng regons (three n Benn and two n Cote d Ivore) where parastc weeds occurred were selected. In the selected regons, fve dstrcts n whch parastc weeds were present were selected n Benn and eght n Cote d Ivore. Wthn the fve dstrcts n Benn, the 18 most cropped lowlands (1 nfested by Rhamphcarpa and sx wth no nfestaton) were selected. In Cote d Ivore, 4 vllages where parastc weeds occurred were selected. Fnally, rce farmers were selected randomly. Data were collected from face-to-face ntervews wth 3 farmers n Benn and 40 n Cote d Ivore n 011 and 01 respectvely. To estmate the effcency model (equatons (7) to (9)), the output was rce paddy producton n klogrammes. The paddy prce was standardsed n each country (because of the same croppng season, from June to December). A pror, ths reduces the heterogenety of products across farms n each country and leads to a more robust analyss of nput-output relatons n crop-response modellng. The nputs ncluded were land and seed cost as growth nputs, labour as facltatng nput and cost of other nputs (fertlser, herbcdes, machnery and other servces). Land was measured n hectares and labour n hours. The latter ncluded famly labour as well as hred labour. The cost of seed was used to capture the dfferences n the qualty of purchased seed (market prce) and farmers saved seed (Wlson et al. 001). The cost of farmers seeds was computed at the average prce of paddy n each country. Other nput costs were measured at ther market value, other servces at ther drect cost and agrcultural equpment at ther annual (lnear) deprecaton costs (cf. Demont et al. 007). Pror to the model s estmaton, data were scanned usng box and whsker plots to detect possble outlers. Sx outlers were dentfed and dropped n Benn. The remanng dataset was composed of 17 observatons n Benn and 40 n Cote d Ivore. Next, the presence of techncal neffcency n the 40

7 data was tested usng D Agostno and Pearson s (1973) and Coell s (1995) tests. Both tests n Benn (p < 0.05) and D Agostno and Pearson s test n Cote d Ivore (P < 0.1) confrmed the presence of neffcency n the data. Hence, a SF specfcaton was requred (Kumbhakar & Lovell 000:73; Rahman & Hasan 008). 3. Results and dscusson 3.1 Estmaton of fronter functon and mpact of parastc weeds on productvty The estmated parameters of the terms of the stochastc fronter producton (7) and of the parameters of the neffcency (8) and varance effects equatons (9) are reported n Table for both countres. These results (Table ) show that output was postvely and sgnfcantly (P < 0.1) correlated wth all nputs except seed (P > 0.1) n Benn. Land was the most productve factor n both countres (53% n Benn and 46% n Cote d Ivore), followed by labour (1%) n Benn and seed (18%) n Cote d Ivore. Parastc weed nfestaton negatvely and sgnfcantly (P < 0.01 and P < 0.1) affects rce productvty n both countres, as expected. Smlar fndngs were reported by Sherlund et al. (00) n Cote d Ivore, where t was found that rce output decreased wth above-average weed densty and hgh rates of plant dsease. In Benn, Rhamphcarpa nfestaton reduced rce productvty (P < 0.01) by 3% and, n Cote d Ivore, both Strga and Rhamphcarpa reduced productvty (P < 0.10) by 18%. These values correspond to the unrealsed outputs due to parastc weed nfestaton of rce felds. The negatve mpact of parastc weed nfestaton on rce producton mples a reducton n food avalablty n the sub-saharan Afrca countres concerned, and a threat to food securty n the regon. In the neffcency models, all parameter estmates had the expected sgns, except for land ownershp n both countres and area share nfested n Benn. Land ownershp, dstance of rce felds from the homestead and household sze sgnfcantly (P < 0.05) and postvely affected neffcency,.e. they corroded techncal effcency. The number of felds and experence n rce farmng, n contrast, were sgnfcantly (P < 0.05) and negatvely assocated wth neffcency,.e. they enhanced techncal effcency. In the regresson of equaton (9), all parameter estmates have the expected sgn, except for the parameter of the area nfested n Cote d Ivore. The number of felds, dstance of felds from homestead and household sze were sgnfcantly (P < 0.1) and negatvely related to the varance of techncal neffcency. However, the effect of household sze was sgnfcant only for Cote d Ivore, meanng that larger households ceters parbus have less varaton n techncal neffcency n rce producton. Cultvatng a larger set of felds was also found to be rsk-reducng n both countres. These fndngs are consstent wth Tan et al. (010) and can be explaned by dversfcaton effects. Farmers can share avalable farmng labour and other productve resources among ther dfferent felds throughout the croppng season. Thus, they can adapt the choce of rce varetes, sowng perod, sowng methods and other croppng methods to local agro-clmatc condtons and thereby reduce the varance of techncal neffcency. Fnally, despte ncreased techncal effcency levels, varaton n techncal neffcency was found to ncrease towards the homestead. Ths s because, n most rural areas n sub-saharan Afrca, pressure on land use and croppng ntenstes ncrease towards the vllage, wth concomtant hgher rsks of pests and dseases (see Demont et al. 007). 41

8 Table : Maxmum lkelhood jont estmates of producton fronter and neffcency functon Varables Benn Cote d Ivore Stochastc fronter Ln land 0.59*** 0.464*** (0.074) (0.048) Ln labour 0.116* 0.114** (0.068) (0.049) Ln seed *** (0.047) (0.051) Ln other cost 0.073*** 0.131*** (0.07) (0.037) Parastc nfestaton -0.30*** * Constant Ineffcency effects on E(u ) Frequency of nfestaton Land ownershp Number of felds Area nfested (%) Dstance from home Female farmer Experence n rce farmng Household sze Ineffcency effects on sgma V(u ) 4 (0.117) 5.598*** (0.647) (0.445) 1.64*** (0.48) -0.17* (0.07) (0.158) 0.171** (0.07) (0.56) *** (0.039) 0.036*** (0.014) (0.095) 3.68*** (0.678) (0.65) 1.07** (0.448) * (0.186) (0.014) 0.094* (0.058) (0.454) *** (0.055) 0.074* (0.040) Frequency of nfestaton (0.168) (0.376) Land ownershp (0.371) (0.553) Number of felds * (0.081) (0.5) Area nfested (%) 0.015** (0.008) (0.01) Dstance from home -0.71*** -0.1 (0.3) (0.137) Female farmer (0.33) (0.55) Experence n rce farmng 0.051** 0.100*** (0.00) (0.05) Household sze ** (0.030) (0.058) Prob > ch Log-lkelhood Sgnfcance level are ndcated wth *** (P < 0.01), ** (P < 0.05) and * (P < 0.1); standard errors are n parenthess 3. Techncal effcency scores Table 3 shows the overall techncal effcency scores and frequency dstrbutons. Predcted techncal effcency scores ranged from 8% to 93% for Benn and from 16% to 100% for Cote d Ivore. The mean values were 64% n Benn and 85% n Cote d Ivore. These results ndcate that rce farmers can stll ncrease ther producton by as much as 36% n Benn and 15% n Cote d Ivore through the

9 more effcent use of producton factors and the control of parastc weeds. These results are n lne wth the observaton of Sherlund et al. (00) that ncludng the parastc weed-nfestaton factors rased the average techncal effcency scores compared to most prevous effcency studes on rceproducton systems n sub-saharan Afrca (e.g. Audbert 1997; M. Dagne et al. 013). Table 3: Estmated techncal effcency scores and dstrbuton Items Benn Cote d Ivore Overall techncal effcency score Mean Standard devaton Mnmum Maxmum Techncal effcency dstrbuton (%) Up to and above Sources of techncal neffcency Table 4 presents the sample means of the margnal effects of manageral varables on neffcency and producton uncertanty, as well as the average margnal effects of the frst and the last quartle of some of the varables. The change n sgn of the margnal effects of varables wth non-monotonc effects on techncal effcency happens only n the fourth quartle, except n the case of the varable experence, for whch t happens n the thrd and the fourth quartle. Snce the focus s on the change n sgn between quartles, only the values of the frst and fourth quartle are reported (Table 4). After the estmaton of the ndvdual margnal effects of the manageral varables, a bootstrap procedure was used to buld confdence ntervals n order to get ther sgnfcance levels (Wang 00). The bootstrapped standard errors (BSE), along wth the statstcal sgnfcance, are also reported (BSE n parenthess). BSEs were computed based on bas-corrected and accelerated confdence ntervals wth 000 replcatons. Except for a few varables, all margnal effects were sgnfcant at 5% (Table 4). The two varables descrbng the mpact of parastc weed nfestaton on techncal effcency (frequency of nfestaton and area nfested) have sgnfcant (P < 0.01) margnal effects on neffcency, E(u) and on the varance of the neffcency term, V(u). Rce farmers techncal neffcency and varance of techncal neffcency ncrease monotoncally wth the area nfested by parastc weeds. Every percentage ncrease n the nfested area rases neffcency by 0.5% n Benn and 0.% n Cote d Ivore, and ths s equvalent to an addtonal output loss of the same magntude, snce E(ln y) / nfarea E( u) / nfarea (Wang 00) (nfarea s area nfested). At the current nfestaton levels of 35% n Benn and 13% n Cote d Ivore (Table 1), the addtonal output losses due to neffcency amount to 17.5% and.6% respectvely, and ceters parbus these losses would reach 50% and 0% respectvely f the entre areas were nfested. If the producton losses are added, staggerng fgures of the average loss due to parastc weeds are found of 50% (3% %) n Benn and 1% (18% +.6%) n Cote d Ivore. Snce farmers perceved the severty of nfestaton to be ncreasng progressvely startng from the frst tme manfested (N cho et al. 014), these fgures gve a frst-hand ndcaton of the mmnent threat of parastc weeds on food securty n sub-saharan Afrca. 43

10 Table 4: Margnal effects on neffcency Varables Benn Cote d Ivore Margnal effects on E(u) (neffcency) Female farmer *** 0.167*** (0.004) (0.01) Land tenure 0.93 *** 0.045** (0.01) (0.018) Number of felds 0.081*** 0.083*** (0.00) (0.006) Frequency of nfestaton 0.117*** 0.047*** (0.007) (0.003) Area nfested (%) 0.005*** 0.00*** (0.000) (0.0001) Household sze Sample avg *** 0.005** (0.0007) (0.00) 1 st quarter avg. 0.00* (0.001) (0.004) 4 th quarter avg ** (0.001) (0.003) Dstance Sample avg *** 0.017*** (0.011) (0.003) 1 st quarter avg. 0.44*** 0.038*** (0.014) (0.009) 4 th quarter avg * (0.01) (0.004) Experence Sample avg *** 0.006** (0.00) (0.00) 1 st quarter avg *** 0.037*** 4 th quarter avg. Margnal effects on V(u) (producton uncertanty) (0.005) 0.014*** (0.00) (0.006) 0.017*** (0.004) Female farmer 0.067*** 0.09*** (0.005) (0.08) Land tenure 0.099*** 0.057** (0.005) (0.08) Number of felds 0.057*** 0.044*** (0.004) (0.013) Frequency of nfestaton 0.048*** 0.031** (0.00) (0.010) Area nfested (%) 0.004*** 0.001*** (0.0003) (0.0003) Household sze 0.00*** 0.011** (0.0003) (0.004) Dstance 0.198*** 0.04** (0.016) (0.009) Experence Sample avg *** 0.008** (0.0009) (0.004) 1 st quarter avg. 0.00*** 0.001*** (0.0008) (0.0004) 4 th quarter avg *** 0.08* (0.004) (0.015) Standard errors and sgnfcance test are based on bootstrap results of 000 replcatons (bas-corrected and accelerated). For many varables, margnal effects can take dfferent sgns and values n the sample. The 1 st and the 4 th quartle values were reported only for varables wth non-monotonc effcency effects (varables havng opposte effects n dfferent quartles). Sgnfcance levels are ndcated wth *** (P < 0.01) and ** (P < 0.05); bootstrap standard errors are n parenthess; avg. = average 44

11 On the other hand, more frequent nfestatons over tme sgnfcantly decrease (P < 0.01) rce farmers techncal neffcency and varance of techncal neffcency thanks to growng awareness of the pest and some experence wth ts management (N cho et al. 014). Every addtonal nfestaton boosts rce farmers techncal effcency levels, enablng them to recover potental producton losses at a rate of 11.7% n Benn and 4.7% n Cote d Ivore. At the current average nfestaton frequency of.16 n Benn and 1.0 n Cote d Ivore (Table 1), and wthout ths effect of the learnng experence, the actual mpact of parastc weed would have been about 75% (50% + 5.3%) n Benn and 6% (1% + 4.8%) n Cote d Ivore. Ths suggests that urgent acton needs to be taken n order to mprove farmers awareness and knowledge of parastc weeds n sub-saharan Afrca. Fnally, ownershp reduces techncal effcency levels n both countres, but the effect on the varance of techncal neffcency s mxed. The opposte was found n Bangladesh by Rahman and Rahman (008), who observed that land owners performed sgnfcantly better than tenants or part-tme tenants. They argued that ths may be due to the fact that tenants typcally receve lower qualty land from the landlords, whch may lead to lower effcency. Croppng more felds ncreases techncal effcency, whch s consstent wth the general fndngs of Sherlund et al. 00 and Tan et al Non-monotonc effcency effects of manageral and soco-economc varables The varables dstance from the homestead and household sze n Cote d Ivore, and experence n rce farmng n both countres, were found to affect effcency non-monotoncally (Wang 00). Plottng neffcency aganst zk values n two-dmensonal graphs provdes a frst vsual ndcaton of the crtcal pont at whch the swtch occurs (Fgures 1a to 1h). Farmers techncal neffcency decreases wth rce farmng experence. For example, 10 years farmng experence decreases farmers techncal neffcency by 10% n Benn and by 6% n Cote d Ivore on average, whle t ncreases the varance of techncal neffcency by 4% n Benn and 8% n Cote d Ivore. However, the margnal effects of experence change over quartles, suggestng that farmers wth less experence (represented by the frst quartle) acheve hgher techncal effcency levels and face lower varance n techncal neffcency. Ths was expected, as n areas wth tradtonal farmng systems the more experenced farmers are generally older (Tan et al. 010). Thus, ncreasng age may lead to a decreasng labour force dmnuton of physcal abltes and farmng abltes,.e. a hgher rsk averson to nvest sgnfcantly n producton due to possble deterorated physcal and mental capablty (Asfaw & Admasse 004; Kumbhakar et al. 01). Hence, startng from lower values of experence, an ncrease n experence helps to mprove effcency. However, above a certan crtcal level of about 0 years, a further ncrease n years of rce-farmng experence becomes counterproductve and mpars effcency. Ths was observed n both countres, startng n the 3 rd quartle. The effect s translated nto an ncrease n techncal neffcency and also an ncrease n the varance of techncal neffcency (Wang 00; Kumbhakar et al. 01). Snce E(ln y)/ exp erence E( u)/ experence (Wang 00), the effect results n an output ncrease of 3.1% for Benn and 3.7% for Cote d Ivore n the frst quartle, whle n the fourth quartle t results n an output loss of 1.4% for Benn and 1.7% for Cote d Ivore. 45

12 Fgure 1a: Margnal effects of experence on E (u), Benn Fgure 1b: Margnal effects of experence on V (u ), Benn Fgure 1c: Margnal effects of experence on E (u ), Cote d Ivore Fg. 1d Margnal effects of experence on V (u ), Cote d Ivore Fgure 1e: Margnal effects of dstance on E (u ), Cote d Ivore Fgure 1f: Margnal effects of dstance on V (u ), Cote d Ivore 46

13 Fgure 1g: Margnal effects of household sze on E (u ), Cote d Ivore Fg. 1h Margnal effects of household sze on E (u ), Benn Fgure 1: Vsualsaton of the non-monotonc neffcency effects of exogenous varables on neffcency (E (u )) and ts varance (V (u )) n Benn and Cote d Ivore The average margnal effects of dstance of rce felds from homestead on neffcency were negatve and sgnfcant (P < 0.01) for both countres. Ths means that, on average, a one klometre ncrease n dstance between farmers rce felds and ther homesteads contrbutes to an ncrease n farmers techncal effcency of 19.1% n Benn and 1.7% n Cote d Ivore. These results for Benn are not consstent wth those of Tan et al. (010), who found that dstance of felds from homestead has a negatve mpact on techncal effcency. Ths may be due to the average short dstance (average of 1. km and maxmum of 7 km) of surveyed rce farms from ther homestead n Benn. In Cote d Ivore, however, these effects were negatve n the frst quartle and postve (although nsgnfcant) n the fourth quartle. Fgure 1e vsualses how farmers are able to capture a dstance premum by achevng hgher techncal effcency levels on remote rce felds. However, beyond a crtcal dstance of 10 km from ther homestead, dstance becomes counterproductve and erodes techncal effcency. An overall postve mpact on techncal effcency mples that the dstance premum ( varaton effect ) exceeds negatve effects on farm management (Tan et al. 010). Beyond the crtcal dstance, commutng takes more tme and farm management becomes more challengng. Analogously to the lterature, ths study found mxed results for household sze (see Audbert 1997 and Tan 010). The average margnal effects suggest that larger households foster effcency n Cote d Ivore (at a rate of 0.5% per famly member) and hamper effcency n Benn (at a rate of 0.3%). Fgures 1g and 1h vsualse how the margnal effects of household sze are spread among the postve and negatve quadrants n the same quartle. A possble explanaton for these mxed effects s that, although larger farm households may beneft from a larger famly work force (Rahman & Rahman 008), they also requre more housekeepng n order to feed all household members, and some of them (chldren and elderly people) may not be avalable for feld work. Fnally, t was observed that the margnal effects on E(u) and V(u) of some manageral and socoeconomc varables had the same sgn. For nstance, frequency of nfestaton, number of felds and dstance reduce E(u) and V(u) n both countres; household sze reduces E(u) and V(u) n Cote d Ivore; and land tenure ncreases E(u) and V(u) n Benn. Smlar to the fndngs of Bera and Sharma (1999), ths observaton mples that, when farmers move towards the producton fronter (ncreasng techncal effcency), they smultaneously manage to reduce the varance of techncal neffcency (Wang 00). However, other varables, such as experence, land tenure and household sze (n Benn), had opposng effects on E(u) and V(u) (Table 4). 47

14 4. Concluson and polcy mplcatons Ths paper provdes an emprcal estmate of the mpact of the nfestaton of parastc weeds on the productvty and techncal effcency of rce farmers n Benn and Cote d Ivore who farm under ranfed condtons. The stochastc fronter models used revealed that experence n rce farmng, dstance of rce felds from homestead and household sze affect the techncal effcency of these rce farmers non-monotoncally. The results also show that all factors do not have the same effect on neffcency and ts varance. These fndngs have mportant polcy mplcatons. The negatve mpact of parastc weed nfestaton on rce producton mples a reducton n food avalablty and a threat to food securty n the countres concerned n sub-saharan Afrca. The dentfcaton of optmal values for factors affectng effcency non-monotoncally, the observaton that factors decreasng farmers techncal neffcency levels do not necessarly reduce ther varance and that factors may have non-smlar margnal effects on neffcency for dfferent countres wll help to desgn more specfc and country-targeted polces and programmes to reduce productvty losses due to parastc weeds. Parastc weed management polces and programmes amng to ncrease techncal effcency should account for the optmal level of nfluence of farmng experence, land sze and dstance of rce plot from homestead on techncal effcency. The specfcaton of the model wth the non-monotonc effcency effects provdes a better understandng of the effects of the key factors, allowng for specfc polcy mplcatons. The model also allowed quantfyng, for the frst tme, the effectve producton gap due to nfestaton by parastc weeds n rce-farmng systems n sub-saharan Afrca. Furthermore, one of the mportant contrbutons of ths paper to the lterature s that the analytcal approach used allows for the decomposton of the total mpact nto ts drect (through producton fronter) and ndrect effects (through the neffcency effects functon). Acknowledgements The authors apprecate the valuable support and collaboraton of feld techncans and farmers from the two sampled countres. Ths research was fnanced by the Netherlands organsaton for scentfc research through Scence for Global Development (NWO-WOTRO) and the CGIAR Research Programme on Clmate Change, Agrculture and Food Securty (CCAFS). Ther fnancal support s gratefully acknowledged. References AfrcaRce, 013. Afrca Rce Center (AfrcaRce) Annual Report 01: Afrca-wde rce agronomy task force. Cotonou, Benn: AfrcaRce. Asfaw A. & Admasse A, 004. The role of educaton on the adopton of chemcal fertlser under dfferent socoeconomc envronments n Ethopa. Agrcultural Economcs 30: Audbert M, Techncal neffcency effects among paddy farmers n the vllages of the Offce du Nger, Mal, West Afrca. Journal of Productvty Analyss 8: Battese GE & Coell TJ, Predcton of frm-level techncal effcences wth generalzed fronter producton functon and panel data. Journal of Econometrcs 38: Battese GE & Coell TJ, A model for techncal neffcency effects n stochastc fronter producton functon for panel data. Emprcal Economcs 0: Belott F, Dadone S, Ilard G & Atella V, 01. Stochastc fronter analyss usng Stata. Research paper seres 10(1): 51, CEIS Tor Vergata. Bera AK & Sharma SC, Estmatng producton uncertanty n stochastc fronter producton functon models. Journal of Productvty Analyss 1:

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