Technical Efficiency of Boro Rice Production in Jhenaidah District of Bangladesh: A Stochastic Frontier Approach

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1 Internatonal Journal of Agrcultural Economcs 2016; 1(4): do: /j.jae Techncal Effcency of Boro Rce Producton n Jhenadah Dstrct of Bangladesh: A Stochastc Fronter Approach Mahmudul Hasan 1, Elas Hossan 1, Ataul Gan Osman 2, * 1 Department of Economcs, Unversty of Rajshah, Rajshah, Bangladesh 2 Department of Economcs, Varendra Unversty, Rajshah, Bangladesh Emal address: m.h.mthu29@gmal.com (M. Hasan), elaseco@ru.ac.bd (E. Hossan), ataul.economcs@yahoo.com (A. G. Osman) * Correspondng author To cte ths artcle: Mahmudul Hasan, Elas Hossan, Ataul Gan Osman. Techncal Effcency of Boro Rce Producton n Jhenadah Dstrct of Bangladesh: A Stochastc Fronter Approach. Internatonal Journal of Agrcultural Economcs. Vol. 1, No. 4, 2016, pp do: /j.jae Receved: August 31, 2016; Accepted: October 2, 2016; Publshed: November 3, 2016 Abstract: Rce s the domnant food crop n Bangladesh. Lke Aman and Aus varetes, Boro rce also grows n leaps and bounds n the country. The producton of Boro rce durng the dry season s welcomed as ncreasng use of rrgaton n the country s expected to rase Boro rce producton for achevng food self suffcency. Ths study estmates the techncal effcency of Boro rce farms and determnes the mportant factors affectng the level of techncal neffcency of the farms. Ths study manly uses prmary data for the analyss, collected from 112 rce producng farms of Jhenadah dstrct usng multstage random samplng technque. The Cobb-Douglas stochastc producton fronter approach s employed to estmate the techncal effcency of Boro rce farms. An neffcency effect model s also used to determne the factors that affect the level of neffcency of the Boro rce farms. The emprcal results of the Cobb-Douglas stochastc producton fronter approach show that the techncal effcency of Boro rce producton s on average Ths ndcates that the level of techncal effcency n the study area s hgh. It also fnds that cost of labor, rrgaton, seed and ploughng are the mportant factors whch affect ncreasng effcency of Boro rce producton. The results from the estmated neffcency effect model reveal that farm sze, age, educaton, tranng and credt faclty are the sgnfcant factors whch are negatvely related to techncal neffcency of Boro rce producton. Ths study suggests that steps to ncrease educaton, tranng and credt facltes are nstrumental to reduce techncal neffcency of rce producton n the study area. Keywords: Techncal Effcency, Cobb-Douglas Stochastc Producton Fronter, Rce Producton, Bangladesh 1. Introducton Agrculture s a crucal sector for economc growth and development of Bangladesh [31]. Despte gradual decrease n the drect contrbuton of the sector to the GDP of the country over tme, economc development s enhanced by ts ndrect contrbuton [20]. It provdes food for the people as well as raw materals to the agro based ndustres that help formng captal. It s also the largest source of employment and ncome generaton of the people n Bangladesh. About 47.5% of the labor forces of the country are presently engaged n agrculture sector. Bangladesh earned US$ 899 mllon by exportng agrcultural product n the fscal year [5]. In addton to the exports of tradtonal agrcultural commodtes, (e.g., raw jute, jute goods, tea, frozen foods), the government of Bangladesh has taken steps to ncrease exports of non-tradtonal agrcultural commodtes [4]. Rce, wheat, jute, pulses, vegetables, ol seeds, sugarcane and potato are the major crops grown n Bangladesh, among whch rce s the most mportant food gran as t supples two-thrd of total calore and about one-half of the total proten ntake of an average person n the country [8], [18]. It s grown n almost all ago-ecologcal zones of Bangladesh durng the three crop seasons namely Aus, Aman and Boro[25], [13]. In Bangladesh, about 82% of total agrcultural produce comes n the form of rce [3]. The volume of rce producton n the fscal year s lac metrc tons of whch Aus s lac metrc tons,

2 104 Mahmudul Hasan et al.: Techncal Effcency of Boro Rce Producton n Jhenadah Dstrct of Bangladesh: A Stochastc Fronter Approach Aman s lac metrc tons and Boro s lac metrc tons. Thus, Boro s the sngle largest crop n Bangladesh wth respect to volume of producton [5], [9]. It s also observed that the productvty of Boro rce producton s hgher than Aus and Aman rce producton [13]. Although the overall rce producton n Bangladesh has been ncreased due to adopton of modern agrcultural technologes, the country stll needs to mport a small amount of fne qualty rce from other countres every each year [25]. Moreover, the country occasonally faces shortfall of rce by small amounts due to clmatc reasons. The amount of rce mport n fscal year s 2.96 lac metrc tons [5]. Wth ncrease n populaton and rse of per capta ncome of the people, demand for rce ncreases every year. However, the rate of growth of rce producton lags behnd the rate of ncrease n demand n the country [15]. Rce producton could not keep pace wth ts demand due to certan producton neffcences. Producton neffcency n rce producton s beleved to exst for several reasons such as low level of educaton, lack of extenson servces and tranng facltes. Another most mportant reason of producton neffcency s the lack of proper utlzaton of modern technologes and ths s happenng due to the exstng fragmented state of agrcultural land. Therefore, the man objectve of ths paper s to estmate techncal effcency and determne the factors affectng the techncal neffcences of rce producton n Bangladesh focusng on the Boro varety of rce. The measurement of effcency s an mportant ssue to make effectve management decson of resource allocaton and formulate dfferent knds of polces for the mprovement of rce producton n the country [20]. 2. Lterature Revew There are many emprcal studes e. g. [30], [26], [32], [17], [21], [2], [10], [1], [6], [7], [33], [22], [19], [28], [4] and [11] conducted to measure techncal effcency of rce producton. Most of these studes used producton functon technques suted to cross secton data. There are few studes n Bangladesh that measured techncal effcency of rce producton. Studes such as [15], [13], [20], [27] and [9] examned techncal effcency of rce producton n Bangladesh. They used Stochastc Fronter approach to determne the level of techncal effcency. The study, [15] showed that the mean techncal effcency of rce farmng n Naogaon dstrct of Bangladesh s 0.80, and n that case techncal neffcency s negatvely nfluenced by factors lke age, educaton, farmng experence and agrculture polcy. [20] nvestgated techncal effcency usng the Cobb- Douglas Producton fronter approach and found that the mean techncal effcency was [13] found that labor cost, fertlzer and pestcde cost, and rrgaton cost are the sgnfcant factors affectng the level of techncal effcency of rce producton. [29] found that educaton s postvely related to techncal effcency. Moreover, [27] examned that how land fragmentaton and resource ownershp affect productvty and techncal effcency of rce producton. There are few studes whch explore farm level techncal effcenc of Boro varetes n Bangladesh, focusng on specfc study area. The present study s an endeavor to fulfll ths gap n the lterature. 3. Methodology 3.1. Study Area and Data Collecton The present study s based on prmary data that are collected from Jhenadah dstrct of Bangladesh. Agrculture s the man lvelhood strategy of the people of Jhenadah dstrct and the dstrct s domnated by rce farmng. The survey has been conducted n 2016 on the producton years. The survey has been conducted wth great care whch covers dfferent soco-economc nformaton of 112 small, medum and large farmers. The selecton of the respondents has been made usng the multstage smple random samplng procedure. At the frst stage, two out of sx upazlas under Jhenadah dstrct are selected usng smple random samplng. The upazlas are Kotchandpur and Kalgonj. There are 6 and 11 unons under Kotchandpur and Kalgonj upazlas, respectvely. At the second stage, usng random samplng technque, from each upazla two unons are chosen whch are Elang and Bolabaraunon of Kotchandpur upazla and Trechandpur and Rakhalgach of Kalgonjupazla. At the thrd stage, two vllages under each unon are selected usng random samplng technque. Fnally, a lst of farmers of the selected vllages are collected from the upazla agrculture offce and chosen 14 respondents from each vllage usng smple random samplng technque whch accounts a total of 112 respondents Method of Analyss Techncal effcency s the maxmum possble output obtaned from a gven set of nputs [24]. Accordng to [12], wthn a gven level of nputs and technology the maxmum possble output of a frm can be shown by the fronter producton functon. The present study uses stochastc fronter producton functon for measurng techncal effcency of Boro rce farmng n the study area The Emprcal Model In the stochastc fronter approach, two functonal forms of producton functon are often used to estmate techncal effcency. These are Cobb-Douglas producton functon and translog producton functon. In the present study, Cobb- Douglas producton functon s used to estmate the techncal effcency of rce farms. The model used n ths study s defned by the followng equaton. ln Y = β + β (ln X ) + β ln( X ) + β ln( X ) + β ln( X ) β ln( X ) + β ln( X ) + V µ Where, Y = Total market value of Boro rce output of th

3 Internatonal Journal of Agrcultural Economcs2016; 1(4): farm; X 1 = Total cost of labor (Taka, Bangladesh currency); X 2 = Total cost of fertlzer (Taka); X 3 = Total cost of rrgaton (Taka); X 4 = Total cost of seed (Taka); X 5 = Total cost of pestcde (Taka); X 6 = Total cost of ploughng (Taka); V = random varable assocated wth dsturbances n producton whch captures the randomness outsde the control of the farmers; µ = stochastc dsturbance term that represents farm specfc or socoeconomc characterstcs related to producton effcency that captures randomness under the control of the farmers. To dentfy the socoeconomc and farm level characterstcs that contrbute to neffcency of the farms, the neffcency effect model s constructed as follows. µ = δ + δz ++ δz + δz + δz + δz + δz δz + δz + δz + ω Where, µ represents the neffcency that s related to dfferent exogenous or farm specfc socoeconomc factors of rce producton; δ s are unknown parameters to be estmated; Z 1 = total farm sze; Z 2 = household sze; Z 3 = age of the household head; Z 4 = educaton; Z 5 = experence of the farmer; Z 6 = tranng; Z 7 = land fragmentaton; Z 8 = extenson servces; Z 9 = credt faclty; ω = stochastc dsturbance term Explanaton of the Varables used n the Model Farm output s defned as the total market value of produced Boro rce n producton year. Labor cost ncludes the total cost ncurred by both famly and hred labor employed n the producton. Fertlzer cost ncludes the cost of buyng organc and norganc fertlzers. Irrgaton cost s calculated as the total cost of rrgaton for rce farms n the Boro season. Seed cost ncludes the cost of usng both local and mproved varetes of seeds. Pestcde cost ncludes total cost of pestcde used n the producton. Total ploughng cost s measured by the cost of ploughng the Boro plots by power tller and bullocks. The measurement of varables and the summary statstcs of the explanatory varables used n the stochastc fronter model are shown n Table1: Table 1. Summary Statstcs of the Varables Used n the Stochastc Fronter Model. Vara-bles Unt Mn. Max. Mean Std. Devaton Output Taka/bgha Labor Cost Taka/bgha Fertlzer Cost Taka/bgha Irrgaton Cost Taka/bgha Seed Cost Taka/bgha Pestc-de Cost Taka/bgha Plough-ng Cost Taka/bgha Source: Feld survey data It s also mentoned n dfferent lterature that there are some mportant factors that affect the techncal neffcency of Boro rce farms n the study area. In order to dentfy that factors, the neffcency effect model uses the followng varables whch are shown n Table2. Table 2. Varables used n Estmaton of the Ineffcency Effect Model. Varables Farm sze Household sze Age Educaton Experence Tranng Land fragmentaton Extenson servce Credt faclty Unt of Measurement Area whch s cultvated by a sngle Boro rce farmer (n bgha) Number of famly members Age of the farmer calculated n years Level offormal educaton of the farmer measured n the number of years Length of growng rce actvtyby the farmer measured n the number of years 1= f the farmer receved any agrcultural tranng, and 0 otherwse Number of plots cultvated by the farmers 1=f the farmer get any extenson servce, and 0 otherwse Amount of money taken by the farmer from dfferent nsttutons 4. Results and Dscusson The parameters of the Cobb-Douglas producton fronter s estmated by usng the Maxmum Lkelhood (ML) estmaton method and the results are presented n Table 3. The obtaned results revealed that the value of gamma s Ths ndcates that 60% dfference exsts between observed and maxmum producton fronter output. The coeffcents of labor cost, rrgaton cost and seed cost are 0.78, 0.03 and 0.14, respectvely, and they are statstcally sgnfcant. These ndcate that one percent ncrease n labor cost, rrgaton cost and seed cost may ncrease the total value of Boro rce producton by 0.78%, 0.03% and 0.14%, respectvely. These results are smlar to the obtaned results found n [24] and [13]. On the other hand, the coeffcents of fertlzer and pestcde cost are negatvely sgnfcant to explan the techncal effcency of Boro rce producton. Ths ndcates that one percent ncrease n fertlzer and pestcde cost may cause to decrease the total value of rce by 0.43%

4 106 Mahmudul Hasan et al.: Techncal Effcency of Boro Rce Producton n Jhenadah Dstrct of Bangladesh: A Stochastc Fronter Approach and 0.08%, respectvely. These results are consstent wth the results of [16], [20] and [13]. The other varable, ploughng cost, used n Cobb-Douglas producton fronter, s found statstcally nsgnfcant to explan the techncal effcency of Boro rce producton. Table 3. Maxmum Lkelhood Estmates of Cobb-Douglas Stochastc Producton Fronter. Varables Coeffcent Std. Devaton t-rato Constant ln labor cost 0.78 *** ln fertlzer cost *** ln rrgaton cost 0.03 *** ln seed cost 0.14 *** ln pestcde cost *** ln ploughng cost Ineffcency Model Constant Farm sze *** Household sze Age *** Educaton *** Experence * Tranng ** Land fragmentaton Extenson servce credt faclty *** Sgma-squared 0.36 *** Gamma Source: Author s own calculatons; Note: *, **and *** ndcate 1%, 5% and 10% level of sgnfcance The results of neffcency model show that the coeffcents assocated wth age, educaton, experence and tranng are negatve and they are statstcally sgnfcant. Ths ndcates that one percent ncrease n these varables may decrease the level of techncal neffcency of Boro rce producton by 0.51%, 1.05% and 0.71%, respectvely. Ths results are smlar to the fndngs of [25], [9], and [11]. The coeffcent of farm sze s negatvely related to techncal neffcency whch ndcates that a 1% ncrease n farm sze may decrease the level of techncal effcency by 0.55% whch contrasts to the result obtaned by [15]. The coeffcent assocated wth land fragmentaton s postve. Ths mples that more and more land fragmentaton may ncrease the level of neffcency. The coeffcent assocated wth credt faclty s negatvely related to techncal neffcency and statstcally sgnfcant to explan neffcency of the Boro rce farmers. Ths mples that one percent ncrease n credt faclty may decrease the level of neffcency by 1.52%. The varables lke household sze, experence and extenson servce are negatvely related to the level of neffcency but statstcally nsgnfcant. 5. Concluson The man objectve of ths study s to estmate the level of techncal effcency and determne the factors affectng on techncal neffcency of Boro rce producton usng Cobb- Douglas Stochastc fronter approach. It s observed that the Boro rce farms n the study area run ther operaton wth less than full potentals as the mean techncal effcency of the farmers s found to be 92%. Ths mples that output of the farm can be ncreased by 8% under the gven technology wthout ncreasng any addtonal nputs. The estmaton results clearly suggest that farm sze, age, educaton, tranng and credt faclty are the crucal factors whch can reduce the exstng techncal neffcency n Boro rce producton. Based on the results, the study suggests that government should take necessary steps to ncrease the educaton level, tranng facltes and extenson servces of the farmers as well as mprove the credt faclty of the farmers. References [1] Battese, G. E. and Coell, T. J. (1992). Fronter producton functons, techncaleffcency and panel data wth applcaton to rce farmers n Inda. The journal ofproductvty analyss, 3(2), [2] Battese, G. E., Malk, S. J. and Gll, M. A. (1996). An nvestgaton of techncalneffcences of producton of wheat farmers n four dstrcts of Pakstan. Journal ofagrcultural economcs, 47(4), [3] BBS, (2004). Statstcal Year Book n Bangladesh. Bangladesh Bureau of Statstcs, Statstcs Dvson, Mnstry of Plannng, Government of the people s Republc of Bangladesh, Dhaka. [4] BBS, (2013). Statstcal Year Book n Bangladesh. Bangladesh Bureau of Statstcs, Statstcs Dvson, Mnstry of Plannng, Government of the people s Republc of Bangladesh, Dhaka. [5] BBS, (2014). Statstcal Year Book n Bangladesh. Bangladesh Bureau of Statstcs, Statstcs Dvson, Mnstry of Plannng, Government of the people s Republc of Bangladesh, Dhaka. [6] Bnam, J. N., Toyne, J., Wandj, N., Nyamb, G. and Akoa, M. (2004). Factorsaffectng the techncal effcency among smallholder farmers n the slah and burnagrcultural zone of Cameroon. Food polcy, 29(5), [7] Bravo-Ureta, B. E. and Pnhero, A. E. (1997). Techncal, economc and allocatveeffcency n peasant farmng: Evdence from the Domncan Republc. The DevelopngEconomes, 35(1), [8] BRKB (Bangladesh Rce Knowledge Bank), (2016). Rce n Bangladesh.Tranng Dvson, Bangladesh Rce Research Insttute (BRRI), Gazpur. Avalable at: [9] Chowdhury, D. M. K. I., Rum, S. F. and Rahman, D. M. M. (2013). Effcency of rce farms durng Boro perod n Bangladesh: An econometrc approach. Global journal of management and busness research fnance, 13(6), [10] Coell, T. J. and Battese, G. E. (1996). Identfcaton of factors whch nfluence thetechncal effcency of ndan farmers. Australan journal of agrcultural economcs, 40(2), [11] Donkoh, S. A., Ayambla, S. and Abdula, S. (2013). Techncal effcency of rce producton at the Tono rrgaton scheme n northern Ghana. Amercan journal of expermental agrculture, 3(1),

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