TECHNICAL, ALLOCATIVE, COST, PROFIT AND SCALE EFFICIENCIES IN KEDAH, MALAYSIA RICE PRODUCTION: A DATA ENVELOPMENT ANALYSIS

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1 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. TECHNICAL, ALLOCATIVE, COST, PROFIT AND SCALE EFFICIENCIES IN KEDAH, MALAYSIA RICE PRODUCTION: A DATA ENVELOPMENT ANALYSIS Sahubar Al Bn Mohamed Nadhar Khan 1, Md. Azzul Baten 1, 2 and Razamn Raml 1 1 Department of Decson Scence, School of Quanttatve Scences, Unverst Utara Malaysa, Sntok, Kedah, Malaysa 2 Department of Statstcs, School of Physcal Scences, Shahjalal Unversty of Scence and Technology, Sylhet, Bangladesh Emal: sahubar@uum.edu.my ABSTRACT Ths study estmates proft and scale effcency usng proft DEA model and techncal, allocatve, and cost effcency usng cost DEA model under both constant returns to scale (CRS) and varable returns to scale (VRS) respectvely and subsequently the determnants factors were nvestgated based on the estmated effcency usng survey data of 70 rce farmers, Kedah, Malaysa. In case of proft effcency, majorty of the rce farmers were operatng wth ncreasng returns to scale 54.29%, 34.29% decreasng returns to scale and only 11.43% wth constant returns to scale. In case of cost effcency only 4.29% of the farmers were 100% techncally effcent under CRS whle t s ncreased nto 16.90% under VRS. The average techncal, allocatve and cost effcences were estmated at 0.28, and0.255 respectvely under CRS whle they were ncreased nto 0.61, and respectvely under VRS. In case of proft effcency the performance measured n CRS and VRS are showng same whle they are performng below average n both CRS and VRS n case of cost effcency. The effcency scores are regressed aganst the wage, dsease control, producton, ncome, farmng system, cost, used n farmng operatons and dscussed. Keywords: cost DEA model, effcency, proft DEA model, tobt regresson, rce producton, Malaysa. INTRODUCTION Paddy especally s gven a greater emphass as t s a staple food for Malaysan. The government s commtted n developng ths sector to ensure that rce producton can meet the demand. Varous subsdes are provded to assst farmers n ncreasng producton, where n the Tenth Malaysa Plan the government set a target of 70% self-suffcency level. To rase farmer s effcency and productvty, t then becomes mperatve to quanttatvely measure the current level of techncal effcency and polcy optons avalable for rasng the present level of effcency, gven the fact that effcency of producton s drectly related to the overall productvty of the agrcultural sector. So, the measurement of productve effcency of agrcultural producton s an mportant ssue n Malaysa, because t gves pertnent nformaton for makng a sound management decson n resource allocaton and for formulatng agrcultural polces and nsttutonal mprovement. Lke all others parts of Malaysa, Kedah s an agro-based state of Malaysa and t produces large quantty of rce. Data envelopment analyss (DEA) s a nonparametrc mathematcal programmng technque n whch multple nputs and outputs are used to measure the relatve effcences of DMUs (Cooper et al., 2007; Duzakn and Duzakn, 2007). The orgnal DEA model was proposed by Charnes et al., (1978). A number of studes examned the techncal effcency of rce growng farmers n developng countres usng DEA nclude Battese and Broca, (1997), Shafq and Rehman (2000) n Pakstan farms, Dhungana et al (2004) n Nepal rce farms, Krasachat (2004) n Thaland rce farms, Chavas et al (2005) n Gamba farms, Battese and Coell, (1992), Battese and Coell, (1995), n Inda, Katpathomcha, (2008), n Thaland, Soures and Tabor, (1991), Brazdk, (2006), n Indonesa,Shafq and Rehman, (2000), Javed et al., (2008), n Pakstan, Rahman, (2003), Rahman, (2011), n Bangladesh, Vllano and Flemng, (2004), n the Phlppnes, and Tran et al., (1993), Huy, (2009), Kha and Yabe, (2011), n Vetnam. All of these studes ponted out substantal neffcency and the possble potentals to mprove the agrcultural productvty. There are also smlar studes that use both DEA and SFA such as Sharma et al (1999), Wadud (2003) Wadud and Whte (2000) and Lnh (2012). However, there has been lmted emprcal attenton on dentfyng the factors affectng mprovement of rce producton effcency of Malaysa. A few studes focused on the productvty analyss n agrcultural sector n Malaysa (Aknble et al 2011; Malena et al 2014; Po Lopez, 2007; Sngh et al., 1996; Jayawardane, 1996). A sgnfcant body of lterature exst dealng wth the techncal and allocatve effcency n dfferent crops and n dfferent regons (Good et al 1993; Ahmad and Bravo-Ureta 1996; Wlson et al 1998; Wadud 1999; Wang and Schmdt 2002; Larson and Plessman 2002; Vllano 2005; Abedullah et al 2007; Laha and Kur 2011; Asogwa et al 2011; Henderson 2015). Accordng to our knowledge no study dealt wth the proft and cost effcency usng proft-dea and cost-dea among rce farmers n Malaysa. The present study hopefully would fll ths gap. In DEA, effects of specfc factors of the frm on techncal effcency cannot be estmated smultaneously and one stage further after estmaton of techncal effcency use DEA s requred. Because of techncal effcency score s lmted n the nterval 0 and 1, then the Tobt regresson s most used n the second stage DEA. Ths study used the DEA approach because t does not 322

2 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. mpose parametrc restrctons on the underlyng technology (Chavas and Alber, 1993; Featherstone et al., 1997; Fletschner and Zepeda, 2002; Wu and Prato, 2006; Watkns et al., 2014). The present study attempts to measure proft and scale effcency usng proft DEA model and techncal, allocatve, and cost effcency usng cost DEAmodel of rce growng farmers n rural area of Kedah n Malaysa. After estmatng the effcency, ths paper subsequently nvestgates the determnants factors affectng the effcency scores of Malaysan rce farmers usng Tobt regresson model. The next secton focuses on the data and methodologes. Secton three presents the estmaton followed by the emprcal results. The last secton concludes the study wth the mplcatons of the fndngs. METHODOLOGY Survey area Ths study wll be conducted n Muda Agrcultural Development Authorty (MADA) regon n Kedah, Malaysa to provde a precse pcture of rce growng farmer s techncal effcency and ther determnants. The area under MADA s the locaton of the Muda Irrgaton Scheme that covers about 126,155 ha of whch 105, 851 ha are n the north-western part of Kedah State and 20,304 ha are n the southern part of Perls State. About 76 per cent of the land s under rce cultvaton (96,558 ha) and approxmately 48,500 farm famles resde there. As the country's man rce producer, Kedah contrbuted some 33 per cent of the 2,599,000 metrc tons total produced n Kedah s the 8th largest state by land area and 8th most populated state n Malaysa, wth a total land area of 9,500 km 2 (3,700 sq m), and a populaton of 1, 890, 098. In Kedah, equatoral clmate wth monsoon nfluence provdes a wet season n whch rce grows and a dry season n whch t rpens and can be harvested. Dry months of January and February allow rce felds to dry out and rce to rpen. Irrgaton from Muda Irrgaton Project allows rce felds to be flooded durng dry season and allows two rce crops per year to be grown under more ntensve modern cultvaton. Data collecton procedures The data collecton has been done wth a prmary objectve targeted to meet the objectves of ths study usng a structured questonnare. The questonnare nclude sectons on () background characterstcs of the frm households e.g. household sze, gender, ethnc group, relgon, educaton level, etc. () knowledge on rce producton or output, yeld of rce, human labor used, land area, amount of seed, amount of manure () frm-specfc nformaton about frm households. Sample sze and samplng desgn Under MADA there are 27 farmer organzatons known as Pertubuhan Peladang Kawasan (PPK) wth around farmers. Out of 27 PPK, 1 PPK named MADA Wlayah 2Jtra: Kepala Batas has been selected n ths study. From ths PPK, 70 famers were selected. The data were collected through ntervews wth heads of farm households who all worked as rce farmers n the vllage. The sample sze needed was calculated usng the followng formula: n = z 2 [P(1-P)/d 2 ]*D eff where, n = sample sze, z = two-sded normal varate at 95% confdence level (1.96), P = ndcator percentage, d = precson, D eff = desgn effect. To obtan data on ndcators at a 10% precson and 95% confdence nterval, assumng a desgn effect of and the most conservatve estmate of ndcator percentage (50%), the mnmum sample sze requred s 70. Therefore, at least 70 frm households wll be requred to measure effcency of rce growng farmers. It s a statstcally representatve sample. The number of frm households needed per vllage s 70 and t s expected that 70 households n a vllage s suffcent to study any sort of ndcators, because such number of households n a vllage s wdely used by UNICEF for conductng Multple Indcator Cluster Surveys (UNICEF, 1999). Respondents The respondents are the rce growng farmers of the household. Analytcal technques Effcency can be measured n two ways: parametrc econometrc method and non-parametrc Data Envelopment Analyss method. The lnear programmng technque of data envelopment analyss (DEA) n measurng techncal effcency does not mpose any assumptons about producton functonal form and does not take nto account random error hence the effcency estmates may be bas f the producton process s largely characterzed by stochastc elements. However, the advantage of DEA s to accommodate a multplcty of nputs and outputs. It s also useful because t takes nto consderaton returns to scale n calculatng effcency, allowng for the concept of ncreasng or decreasng effcency based on sze and output levels. One of the lmtatons of the DEA s that effcency s measured relatve to ths fronter, where all devatons from the fronter are assumed to be neffcent (Johanson, 2005). Coell (1996) reported that where all Decson Makng Unts (DMUs) are not operatng at optmal scale, due to a number of constrants lmtng ther ablty to do so, the use of varable returns to scale (VRS) to characterze the producton process s deal. The use of VRS specfcatons permts the calculaton of techncal effcency devod of scale effcency effects. Data envelopment analyss Data envelopment analyss (DEA) s a nonparametrc method n operatons research and economcs for the estmaton of producton fronters. It s used to emprcally measure productve effcency of decson makng unts. The framework has been adapted 323

3 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. from mult-nput, mult-output producton functons. DEA develops a functon whose form s determned by the most effcent producers. In most of them, t s very dffcult to obtan the nput prce due to unavalablty of data nformaton (prce data s necessary n order to perform econometrc approach). Essentalty for that reason, ths study uses the non-parametrc approach (DEA) to nvestgate the effcency of rce farmng households. CRS Proft DEA Let us consder n DMUs (decson makng unt) or banks, each one producng dfferent output (y) and usng dfferent nputs (x). The proft effcency of the rce farmng households assumng constant return scale (CRS) s measured as follows: Max Subject to u y j ( u y / v x ), u, v v x j 1,2,..., N u, v 0. j 0, where, x s a vector of rce farmng household nputs, y s a vector of rce farmng household output gven the nputs, u s the weghted relatve vector assocated to output, v s the weghted relatve vector assocated to nput. VRS Cost DEA Imperfect competton, constran n fnance, etc. may cause a rce farmng households to be not operatng at optmal scale, n ths case the CRS assumpton s not approprate because t assumes that rce farmng households are operatng at optmal scale. If the CRS model s used when not all rce farmng households are operatng at optmal level, the techncal effcency s confound wth scale effcency. Banker, Charnes and Cooper (1984) suggested an extenson of the above model to take nto account the varable return to scale (VRS). The dual form of the above problem as: Mn,, St Y 0, y X 0, x n j 1 1 and 0. j where X s m n nput matrx, Y s s n output matrx, s an n 1 vector of constant and s a scalar. The value of obtaned wll be the effcency score for -th rce farmng households. It wll satsfy 1, wth a value of 1 ndcatng a pont on the fronter and hence a techncal effcency rce farmng households. Scale effcency refers to the rce farmng households ablty to work at ts optmal scale. It can be proved that: TE CRS = TE VRS * SE Where TE CRS s the techncal effcency, TE VRS s the pure techncal effcency, and SE s the Scale effcency. The techncal effcency obtaned by CRS DEA model can be decomposed n two parts, one due to scale effcency, and one due to pure techncal effcency. Pure techncal effcency refers to the rce farmng households ablty to avod waste by producng as much output as nput usage allows, or by usng as lttle nput as output producton allows. Tobt regresson model of techncal effcency determnants The Tobt regresson model s an econometrc model that s employed when the dependent varable s lmted or censored at both sdes. The present study uses a censored regresson to analyze the role of soco-economc, demography and nsttutonal attrbutes n explanng techncal, allocatve, scale and cost effcency n rce producton. In order to examne the nfluence factors that can hnder the rce producton effcency, Tobt regresson analyss s used as a second stage of the relatonshp between the effcency measure and other relevant varables. Tobt analyss, a model proposed by Tobn (1958), assumed that the dependent varable has a number of ts values clustered at a lmtng value, usually zero. If the data to be analyzed contan the values of the dependent varable that s truncated or censored, the ordnary least square (OLS) s no longer applcable to the concept of the estmated regresson coeffcents. If OLS s drectly used t wll lead to based and nconsstent parameter estmaton whereby the Tobt model, that follows the concept of maxmum lkelhood, becomes a better choce to estmate a regresson coeffcent (Chu et al., 2010).Because the ordnary least square (OLS) regresson s not approprate for ths regresson analyss that the effcency score s lmted between 0 and 1, the dependent varable does not have normal dstrbuton. Tobt regresson s more convenent to have data censored at zero that at 1 (Sharma et al., 1999). Ths study employs the followng Tobt regresson model and expresses as follow: U * 0 K j 1 Z j j Denotng U as the observed dependent varables, U 1 U. U U 0 * f ; f f U * U 1; 0 U * 0. * 1; 324

4 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. where U s an effcency measures representng techncal effcency wth both CRS and VRS; allocatve effcency, cost effcency and scale effcency of the -th rce growng farmers based on DEA estmaton; U s the latent neffcency varable; * Z s a vector of explanatory varables representng of farm characterstcs; are unknown parameters to be estmated; j s the random error term that s ndependently and normally dstrbuted wth mean zero and common varance 2 2,.e., ~ NID 0,. Snce the ndvdual DEA effcency score vares between at 0.00 and 1.00, ths means the effcency scores are double-truncated or censored at 0 and 1. Tobt regresson model whch can apply for ths type of dependent varable s two-lmt Tobt model (Maddala, 1999) where 0 s lower lmt and 1 s upper lmt. The emprcal Tobt model specfcaton s wrtten as follows: U 0 1Z1 2Z2 3Z3 4Z4 5Z5 6Z6 where, represents the wage of the Kepala Batas PPK; represents the dsease control of thekepala Batas PPK; represents the producton of thekepala Batas PPK; represents the ncome of thekepala Batas PPK; represents the farmng system of thekepala Batas PPK; represents the cost of the Kepala Batas PPK; RESULTS AND DISCUSSIONS DEA Effcency analyss A survey was conducted on 70 farmers of the KepalaBatas PPK from Kedah, Malaysa. Though the sample was selected randomly, all the selected farmers are male have educaton up to UPSR and from Malay race and about 97% of them are more than 59 years old (Table-1). More than 71% of the farmng systems are ndvdual and 27% farmers are from estate system. Table-1. Background Statstcs of the selected farmers of KepalaBatas, Kedah, Malaysa. Farmng Vald percent Frequency system (%) Indvdual Estate Total Age More than Total Race Malay Educaton UPSR Sol Condton Moderate Table-2 presents proft effcency of selected farmers of PPK KepalaBatas, Kedah, Malaysa. Mnmum effcency from constant return to scale and varable return to scale s almost same whch s and by the same farmers. Among the selected 70 farmers, seven of them are showng perfect relatve performance n constant return to scale. However, eleven of them are showng perfect relatve performance n varable return to scale. In scale effcency, 26 farmers are showng decreasng return to scale and 37 farmers are showng ncreasng return to scale. The resource - use effcency, measured n terms of returns to scale, classfed nto ncreasng, decreasng and constant returns to scale (IRS, DRS, CRS) s shown n Table-2 and Fgure-1. In case of proft effcency measurement majorty of the rce farmers were operatng wth ncreasng returns to scale 54.29%, 34.29% decreasng returns to scale and only 11.43% wth constant returns to scale. Ths shows that majorty of the rce farmers are operatng wth IRS. The result mples that only 11.43% of the rce farmers were operatng at ther optmal scale, whle 34.29% were operatng above ther optmal resource utlzaton. The result s consstent wth Oref, (2011). Only 10% farmers were found to be full proft effcent n case of CRS assumpton and t s ncreased nto 15.71% whle assumes VRS and 11.43% farmers were observed for scale effcency. 325

5 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. Farm Constant return to scale Table-2. Proft effcency of selected farmers of Kepala Batas, Kedah, Malaysa. Varable return to scale Proft effcency Scale effcency Indcator Farm Constant return to scale Varable return to scale Proft effcency Scale effcency Indcator drs rs drs rs rs rs rs rs rs rs rs rs drs drs drs drs rs rs rs rs rs rs rs drs rs rs rs rs drs rs drs rs drs drs drs drs rs rs drs rs drs rs rs drs drs drs drs drs rs rs drs rs drs rs rs rs rs drs drs rs rs rs *drs and rs ndcates decreasng return to scale and ncreasng return to scale 326

6 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. Fgure-1 s showng proft effcency assumng CRS and VRS of the selected farmers. Performance measured n CRS and VRS are showng same for most of the farmers. About 10 farmers are performng below 0.6 and rest others are performng hgher relatve performance. Ths conforms to the results of Balcombe et al. (2008) and Rahman (2003). 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, CRS VRS Fgure-1. Proft effcency of the selected farmers of Kepala Batas, Kedah. Fgure-2 presents the scale effcency of the selected farmers of Kepala Batas, Kedah, Malaysa. Scale effcency s obtaned by dvdng the aggregate effcency by the techncal effcency. A decson makng unt s sad to be scale effcent when ts sze of operatons s optmal. From the analyss, t s found that 8 out of 70 farmers are scale effcnt, that s, these farmers are usng ther sze perfectly. The rest other farmers have opportunty to optmze ther sze. It s also found that the average scale effcency s Ths results conforms wth the fndng by Coell et al (2002) and Lnh (2012) where they fnd the average scale effcency values of and respectvely. 1 0,9 0,8 0,7 Scale Effcency 0, Fgure-2. Scale effcency of the selected farmers of Kepala Batas, Kedah. Table-3 and Table-4 are showng Cost effcency assumng CRS and VRS respectvelyof the selected farmers of PPK Kepala Batas from Kedah, Malaysa. Only three and sx farmers are showng relatvely perfect performance (cost effcent) n CRS and VRS respectvely. Techncal Effcency (TE) whch s just the proportonal reducton n nputs possble for a gven level of output n order to obtan the effcent nput use, and Allocatve Effcency (AE) whch reflects the ablty of the farm to use the nputs n optmal proportons, gven ther respectve prces. Except effcent farmers n the all three aspect (TE, AE and CE), there s four farmers whch are techncally effcent. Due to low techncal effcency, cost effcency are nfluenced n both CRS and VRS.The dstrbutons of techncal effcency under CRS and VRS are presented n Table-3, Table-4 and Fgure-2. In case of cost effcency measurement only 4.29% of the farmers were 100% techncally effcent n resource utlzaton 327

7 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. under CRS whle 16.90% of the farmers were found 100% techncally effcent n resource utlzaton under VRS. It revealed that about 17% of the farmers were 100% techncally effcent n resource utlzaton under VRS, whle only 4.29% of the rce farmers were 100% techncally effcent n resource utlzaton under CRS. The average techncal, allocatve and cost effcences of farmers were calculated as 0.28, and respectvely operatng by CRS whle they were ncreased nto 0.61, and respectvely by operatng VRS. Total optmum cost requrement was found to be about 53.3%; showng that 46.7% of nput costs could be saved f the farmers follow the results recommended by ths study. Ths results conforms wth the fndng by Coell et al (2002) where they reported smlar techncal, allocatve and cost effcency values. Table-3. Cost effcency assumng CRS of the selected farmers of Kepala Batas, Kedah. Techncal Allocatve Cost Techncal Allocatve Cost Farm Farm effcency effcency effcency effcency effcency effcency Mean

8 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. Table-4. Cost effcency assumng VRS of the selected farmers of Kepala Batas, Kedah. Techncal Allocatve Cost Techncal Allocatve Cost Farm Farm effcency effcency effcency effcency effcency effcency Mean Techncal effcency assumng CRS and VRS of the selected farmers are shown n Fgure-3. For few farmers the techncal effcency s same for both assumptons however, n most of the case the effcency from VRS s greater than that of CRS. In CRS, almost half of the farmers have techncal effcency very close to zero and only three farmers have perfect effcency. 329

9 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. 1 0,8 0,6 0,4 0, CRS VRS Fgure-3. Techncal effcency of the selected farmers. Allocatve effcency s found almost same for the most of the farmers revealed n Fgure-4. Few farmers have less than 0.6 allocatve effcency assumng VRS however, there s no farmers have effcency less than 0.6 assumng CRS. 1 0,9 0,8 0,7 0,6 0, CRS VRS Fgure-4. Allocatve effcency of the selected farmers. Cost effcency of the selected farms s presented n Fgure-5. About 20 farmers have relatve performance 0.1 or less than that n CRS. Most of the farmers are performng below average n both CRS and VRS. Though the petern of relatve effcency n both scale s same, performance n CRS s showng better compare to performance n VRS. In CRS, most of the farmers have relatve performance below 0.6 except 5 farmers. 330

10 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, CRS VRS Fgure-5. Cost effcency of the selected farmers. The Tobt model results on the determnants of resource use neffcency In order to dentfy key determnants of resource use neffcency under CRS, VRS and scale, allocatve, techncal, and cost neffcency scores are separately regressed on selected demographc, soco economc and nsttutonal varables. The mpacts of the factors whch could have nfluenced the rce effcency are analyzed by usng the Tobt regresson model. Ths model was appled to CRS, VRS and Scale effcency as a dependent varable and some key soco-economc ndependent varables related to neffcency. Table 5 dsplays the results of Tobt regresson functon for the CRS, VRS and Scale effcency. The effcency scores are regressed aganst the wage, dsease control, producton, ncome, farmng system, cost, used n farmng operatons. The dsease control of the sample farmers has a negatve effect under CRS and VRS, but a postve effect on effcency ndexes on scale even though t s not sgnfcant related to the effcency ndexes. Agan ncome of the sample farmers has a postve effect under CRS, VRS and scale on effcency ndexes. Farmng System has sgnfcant mpact on the effcency assumng VRS and CRS as well as on Scale effcency. It means one more unt of farmng system used n rce producton; the effcency score wll ncrease and the utlzaton of farmng system dsplays the ncrease n effcency n ths sample area. Wage has postve sgnfcant mpact on Scale effcency. On effcency assumng VRS, cost has negatve mpact whch s not sgnfcant; however, t has postve sgnfcant mpact on effcency assumng CRS and on scale effcency. Producton has postve sgnfcant mpact on effcency assumng CRS whereas t has negatve nsgnfcant mpact on effcency assumng VRS and on scale effcency. Estmated standard devatons of the resduals are , and for the model VRS, CRS and Scale. Table-5. Results of Tobt regresson analyss under VRS, CRS and scale effcency. VRS CRS Scale Estmate Std. error Estmate Std. error Estmate Std. error Intercept *** *** *** Wage *** Dsease control Producton * Income Farmng System * *** *** cost *** *** Log(Sgma) *** *** *** ***, ** and * ndcates 1%, 5% and 10% level of sgnfcance respectvely 331

11 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. In Tobt regresson, when scale effcency and effcency assumng VRS and CRS are consdered as dependent varable 8, 11 and 7 observatons respectvely are rght censored (Table-6). That s, estmated values of these observatons were more than one whereas effcency cannot exceed one. To keep the estmated values wthn lmt these observatons were rght censored however, there are no left censored observatons n the analyss. Table-6. Censored observaton to Tobt regresson effcency under VRS, CRS and scale. Observatons Total Left-censored Uncensored Rght-censored VRS CRS Scale Table-7 presents the estmated parameter to regress Allocatve Effcency, Techncal Effcency and Cost Effcency usng Tobt regresson. Producton has negatve nsgnfcant mpact on allocatve effcency however the mpact on techncal effcency and cost effcency s postve and sgnfcant only on techncal effcency. Wage has negatve nsgnfcant mpact on all these three type of effcency - allocatve effcency, techncal effcency and cost effcency. The ncome and dsease control of the sample farmers has a postve mpact wth allocatve effcency whle they have postve mpact wth techncal and cost effcency ndexes though they are not sgnfcant. Farmng System has postve nsgnfcant mpact on the allocatve, techncal and cost effcency. It means one more unt of farmng system used n rce producton; the effcency score wll ncrease once the farmng system utlzes properly n ths sample area. Income and dsease control cost has negatve mpact on techncal and cost effcency whereas mpact on allocatve effcency s postve; however mpacts are not sgnfcant. Estmated standard devatons of the resduals are , and for allocatve effcency, techncal effcency and cost effcency. Table-7. Results of Tobt regresson analyss. Allocatve effcency Techncal effcency Cost effcency Estmate Std. error Estmate Std. error Estmate Std. error Intercept *** *** *** Producton *** Wage Income Dsease Control Farmng System Log(Sgma) *** *** *** ***, ** and * ndcates 1%, 5% and 10% level of sgnfcance respectvely Number of censored observatons from the Tobt regresson s shown n Table-8. There are no left censored observatons n the estmaton of allocatve effcency, techncal effcency and cost effcency. However, there are 6, 12 and 6 rght censored observatons to predct allocatve effcency, techncal effcency and cost effcency respectvely. Table-8. Censored observaton to Tobt regresson wth allocatve, techncal and cost effcency. Observaton Total Left-censored Uncensored Rght-censored Allocatve Effcency Techncal Effcency Cost Effcency

12 ARPN Journal of Agrcultural and Bologcal Scence Asan Research Publshng Network (ARPN). All rghts reserved. CONCLUSIONS Ths study s concerned wth the measurement of effcency for the rce growng farmers usng both cost Data Envelopment Analyss (DEA) and proft DEA as well as focuses on the emprcal nvestgaton of the factors affectng rce producton effcency n Malaysa, usng the Tobt analyss. The prmary data s collected from PPK KepalaBatas of Kedah, Malaysa wth a number of 70 farmers whch are randomly selected to estmate cost effcency and proft effcency usng DEA. The techncal and scale effcency estmates were made also for the rce farmers n PPK KepalaBatas of Kedah, Malaysa. Accordng to proft effcency, most of the farms are performng on an average however and cost effcency of the farmers s below of the average. However, proft and cost effcency are showng that most of the farmers have opportunty to ncrease ther relatve effcency. Techncal effcency s low, that s, t s possble to reduce nputs for all the farmers to be effcent. Allocatve effcency s better than techncal effcency; however, stll the farmers have opportunty to allocate the nputs accordng to ther cost. The result showed low level of effcency n resource utlzaton by the farmers. Majorty of the farmers were experencng ncreasng returns to scale. By operatng on an optmal scale (CRS), nput wastage could be reduced. From the results, the scale effcences of rce farmers at 0.85 above mpled that essentally the average farms are very close to optmal scale. The lower CRS and VRS effcency scores are compared to the scale effcency and t s suggested that the neffcences are mostly due to neffcent management. Therefore, the analyss on factors affectng the effcency s conducted by Tobt regresson analyss. The determnants of effcency scores are regressed aganst the wage, dsease control, producton, ncome, farmng system, cost, used n farmng operatons and dscussed. Farmng System has postve sgnfcant mpact on the effcency under CRS, VRS and Scale whle wage has postve sgnfcant mpact on Scale effcency only. Agan cost has postve sgnfcant mpact on effcency under both CRS and scale but Producton has postve sgnfcant mpact on techncal effcency under CRS only. Accordng to the theoretcal assumpton of the DEA approach, the farm whch possesses the hghest effcency score s stuated on the producton fronter lne and so, the estmated results from DEA ndcate that the neffcent samples farmers can mprove ther rce producton effcency to catch up the effcent sample farmers n ths northern regon, Malaysa. Ths study suggested that the exstence of some neffcency may be reduced through polcy nterventons, adopton, and spread of mproved agrcultural mechanzaton. In partcular, knowledge of factors drvng rce producton effcency and contrbutons of producton effcency to economc performance could provde support for polcy makers. ACKNOWLEDGEMENTS Ths study was supported by the Research Acculturaton Grant Scheme, S/O Code: 12715, Unverst Utara Malaysa and Mnstry of Hgher Educaton Malaysa. REFERENCES Abedullah Bakhsh, K. and Ahmad B Techncal Effcency and ts Determnants n Potato Producton, Evdence from Punjab, Pakstan. The Lahore Journal of Economcs. 11(2): Ahmad M. and Bravo-Ureta B.L Techncal Effcency Measures for Dary Farm Usng Panel Data: A Comparson Alternatve Model Specfcatons. Journal of Productvty Analyss. 7(4): Aknble C.O., Abd-El-Latf K.M., Abdullah R. and Yusoff M.S Rce Producton and Water use Effcency for Self-Suffcency n Malaysa: A Revew. Trends n Appled Scences Research. 6(10): Asogwa B.C., Ihemeje J.C. and Ezhe J.A.C Techncal and Allocatve Effcency Analyss of Ngeran Rural Farmers: Implcaton for Poverty Reducton. Agrcultural Journal. 6(5): Balcombe K., I. Fraser Latruffe L., Rahman M. and Smth L An applcaton of the DEA double bootstrap to examne sources of effcency n Bangladesh rce farmng. Appl. Econ. 40(15): Banker R., Charnes A., Cooper W.W Some models for estmatng techncal and scale neffcences n data envelopment analyss. European Journal of Operatonal Research. 30(9): Battese G. E. and Coell T.J Fronter Producton Functons, Techncal Effcency and Panel Data: Wth Applcaton to Paddy Farmers n Inda. Journal of Productvty Analyss. 3(1-2): Battese G. E. and Coell T.J A Model for Techncal Effcency Effects n a Stochastc Fronter Producton Functon for Panel Data. Emprcal Economcs. 20(2): Battese G.E. and Broca G.S Functonal form of stochastc fronter producton functons and models for techncal effcency effects: a comparatve study for wheat farmers n Pakstan. Journal of Productvty Analyss. 8: Brazdk F Non-Parametrc Analyss of Techncal Effcency: Factors Affectng Effcency of West Jawa Rce Farms. Center for Economc Research and Graduate Educaton, Charles Unversty. Workng Paper Seres. Charnes A., Cooper W.W. and Rhodes E Measurng the effcency of decson makng unts. Eur. Jurnal of Oper. Res. 2(6):

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