MEASURING TECHNICAL EFFICIENCY OF ONION (Allium cepa L.) FARMS IN BANGLADESH M. A. BAREE 1. Abstract

Transcription

1 ISSN Bangladesh J. Agrl. Res. 37(1): , March 2012 MEASURING TECHNICAL EFFICIENCY OF ONION (Allum cepa L.) FARMS IN BANGLADESH M. A. BAREE 1 Abstract An attempt was made to determne the overall farm-specfc techncal effcency or neffcency of onon farms of Bangladesh. Farm-level data were used for the estmaton of the parameters of Cobb-Douglas stochastc fronter producton functon. The model for techncal neffcency effects n the stochastc fronter ncluded age, experence, educaton, and farm sze. The elastcty of output wth respect to land, labour, and captal cost was estmated to be postve values of , , and , respectvely, and also sgnfcant. Wth respect to seed and rrgaton, t was found to be nsgnfcant wth negatve values of and It ndcates that per hectare yeld of onon decreases f the amount of seed and rrgaton hour ncrease. The coeffcents of age, experence, and farm sze were sgnfcant wth expected negatve sgns, whch means that the neffcency effects n onon producton decreases wth ncrease n age, experence, and farm sze. The techncal effcency of onon farms vared from 58% to 99% wth mean value of 83%. It denotes that there s a scope to ncrease output per hectare of onon farm by 17% through the effcent use of producton technology wthout ncurrng any addtonal costs. Keywords: Techncal effcency, onon n Bangladesh. Introducton Onon s the most mportant herbaceous bulb and spce crop n Bangladesh as well as n the world. It ranks frst and second among other spces and condment crops grown n respect of producton and area n Bangladesh, respectvely (BBS, 2004). Onon s grown n all dstrcts of Bangladesh and wdely cultvated n commercal scale n the greater dstrcts of Fardpur, Pabna, Rajshah, Dhaka, Dnajpur, Jessore, Kushta, and Rangpur. The area under onon producton s hectares wth producton of 589 thousand metrc tons and 6.83 metrc tons per hectare n Bangladesh (BBS, 2005). As a mnor crop, onon plays an mportant role n the economy of Bangladesh. It offers a consderable promse n terms of generatng ncreased rural employment opportuntes because ts producton s more labour ntensve than other crops. The demand for onon s world wde for ts multpurpose uses as spces, vegetables, salad, dressng, etc. It s used to prepare almost every food tem by all classes of people. It also releves head sensaton and nsect btes due to ts medcnal propertes. Onon contans vtamn B and a trace of vtamn C and also trace of ron, calcum, and volatle ol 1 Assocate Professor, Department of Crop Scence and Technology, Unversty of Rajshah, Bangladesh.

2 172 BAREE known as allylpropyl-dsulphde (Yawalkar, 1985). Approxmately a shortage of 323 thousand tons of onon per year s exsted. To meet up the ncreasng demand, Bangladesh has to mport onon from Inda and Pakstan every year at the cost of hard earned foregn currency. It s dffcult to ncrease onon producton by ncreasng the area of land under cultvaton due to the lmtaton of land. But, there s an opportunty to ncrease producton of onon by mprovng the exstng producton technology. Farmers may be relatvely neffcent due to land fragmentaton, less experence, llteracy, etc. If farmers are found to be techncally neffcent, producton can be ncreased to a large extent usng the exstng level of agrcultural nputs, the agrcultural extenson servces and the avalable technology. In the past, so far, the author's knowledge s concerned, there was no study on techncal effcency of onon producers. Ths study was undertaken to fnd out the overall farmspecfc techncal effcency or neffcency of onon farms. The study may be helpful for polcy makers n ths feld to draw a strategc plannng for ncreasng producton of onon farm. Materals and Method Data source, samplng The feld survey was conducted coverng the 15 vllages of Santha Upazla of Pabna dstrct of Bangladesh durng the perod from January 2004 to July A total of 225 sample farmers were selected from all farm groups by usng stratfed random samplng technque. Face to face ntervewng respondents' method was followed for data collecton. The collected data ware scrutnzed, edted, tabulated, and analyzed carefully to acheve the meanngful nterpretaton. The margnal analyss of varables was the bass of analyss for ths study. The varables were measured functonally usng stochastc fronters producton functon. The parameters of respectve varables were estmated usng the statstcal package FRONTIER 4.1 (Coell, 1996). Model specfcaton The Cobb-Douglas stochastc fronter producton functon model has been specfed to estmate the level of overall techncal effcency of onon farms. The Cobb-Douglas producton functon specfcaton provdes an adequate representaton of the producton technology. The specfcaton of the Cobb- Douglas stochastc fronter producton functon model can be wrtten as: InY = β = 1 β INx + V U InY = β + β In X ) + β In( X ) + β In( X ) + β In( X ) + In( X ) + V U (1) 0 1 ( β 5 5

3 TECHNICAL EFFICIENCY OF ONION FARMS 173 Where the subscrpt refers to the -th farmer, In represents the natural logarthm, Y represents the per hectare output (kg), X 1 s the land use cost per hectare (Tk.), X 2, X 3, X 4, and X 5 represent the total quantty of labour/ha (mandays), amount of seed/ha (kg), rrgaton hour/ha (hour), and captal cost/ha (Tk.), respectvely. The V are assumed to be ndependently and dentcally dstrbuted random errors, havng N(0, σv 2 ) dstrbuton, and the U are non-negatve random varables, called techncal neffcency effects, assocated wth the techncal neffcency of onon producers nvolved. It s assumed that the neffcency effects are ndependently dstrbuted and U arse truncaton (at zero) of the normal dstrbuton wth mean, µ, and varance, σ 2, where µ can be specfed and defned as: µ = δ 0 + δ 1 Z 1 + δ 2 Z 2 + δ 3 Z 3 + δ 4 Z 4 Where Z 1 denotes the age of farm operator, Z 2 represents the experence of farm operator, Z 3 s the year of schoolng of farmer and Z 4 represents the farm sze of onon. The β and δ are unknown parameters to be estmated together wth the varance parameters, whch are expressed n terms of: σ 2 s = σ 2 v + σ 2 u and γ = σ 2 2 u / σ s Where the y-parameter has the value between zero and one. The parameters of the stochastc fronter producton functon model are estmated by the method of maxmum lkelhood, usng the computer program, FRONTIER Verson 4.1 (Coell, 1996). The techncal neffcency model for the neffcency effects (2) can only be estmated f the neffcency effects are stochastc. Hence, there s an nterest n testng the null hypotheses that the neffcency effects are not present; H 0 : γ = δ 0 = δ 1 = δ 2 = δ 3 = δ 4 = 0; and The coeffcents of the varables n the model for the neffcency effects are zero, H 0 : δ 1 = δ 2 = δ 3 = δ 4 = 0. These null hypotheses are tested by usng the generalzed lkelhood-rato statstcs γ that s defned by γ = - 2In [L(H 0 )/ L(H 1 )]= - 2 [In{L(H 0 )} In {L(H 1 )}] (3) Where L (H 0 ) and L (H 1 ) are the values of the lkelhood functon under the specfcatons of the null and alternatve hypotheses H 0 and H 1, respectvely. If the null hypothess s true, then γ has approxmately a Ch-square (or a mxed Ch-square) dstrbuton (Coell, 1995). Gven the specfcatons of the stochastc

4 174 BAREE fronter model (1) and (2), the techncal effcency of -th farmer can be shown to be equal to: TE = exp(-u ) Thus, the techncal effcency of a farmer s between zero and one and s nversely related to the neffcency effect. The effcences are predcted usng the predctor that s based on the condtonal expectaton of exp(uj) (Battese and Coell, 1993). Results and Dscusson The stochastc fronter model nvolves nput varables lke land, labour, seed, rrgaton, and captal cost, and soco-economc varables lke age, experence, educaton and farm sze are consdered n the neffcency model. The maxmum lkelhood estmates of the coeffcents of parameters n the Cobb-Douglas stochastc fronter and neffcency model, defned by equatons (1) and (2), s presented n Table 1. The comparatve sgnfcance of nputs of producton s predcted by the elastcty estmates from the stochastc fronter producton functon. The coeffcents of land, labour, and captal cost were found to be postve and also sgnfcant. The elastcty of output wth respect to land, labour, and captal cost was estmated to be postve values of , , and , respectvely. Thereby we can say that f the land areas, number of labourers, and captal cost are ncreased by one per cent, per hectare yeld of onon wll be ncreased by percent, percent, and percent, respectvely. The coeffcents of seed and rrgaton are found to be negatve and also nsgnfcant whch ndcates that per hectare yeld of onon decreases f the amount of seed and rrgaton hour ncrease. From the results of stochastc fronter model, we see that f the nputs of whch coeffcents have postve sgn are ncreased by one percent, the total yeld per hectare of onon s estmated to ncrease percent. Land occuped the hghest elastcty of output that ndcates the most domnant factor of producton. But land s scarce to the farmers n Bangladesh. Land s not a sngle factor that nfluences the output, but other nfluencng factors lke labour and captal cost of whch margnal productvty are dmnshng have postve effect on producton. The margnal productvty of seed and rrgaton s negatve, whch have negatve effect on producton. The return to scale of onon producton (summaton of all nput coeffcents) ndcates the decreasng returns, whch means that farmers produce ther producton on the non-optmal level of operaton.

5 TECHNICAL EFFICIENCY OF ONION FARMS 175 Table 1. Maxmum lkelhood estmates for parameters of Cobb-Douglas stochastc fronter producton functon and techncal neffcency model for onon farms. Varables Parameter Coeffcents T-rato Stochastc Fronter: Constant (x 0 ) β ** Land (x 1 ) β ** Labour (x 2 ) β * Seed (x 3 ) β Irrgaton (x 4 ) β Captal cost (x 5 ) β * Ineffcency Model: Constant δ ** Age (Z 1 ) δ * Experence (Z 2 ) δ * Educaton (Z 3 ) δ Farm sze (Z 4 ) δ ** Varance Parameters: σ 2 s = σ 2 v + σ 2 u ** γ = σ 2 u /σ 2 s * Log-lkelhood Functon: **Sgnfcant at 5%; *Sgnfcant at 10% Ineffcency effects The estmated δ-coeffcents assocated wth the explanatory varables n the stochastc fronter model for techncal neffcency effects had to be analyzed due to the effect of these varables on the capablty of farmers. The sgns on the δ- parameter n the neffcency effect model are expected to be negatve. The coeffcents of age, experence, and farm sze are estmated to be negatve sgn and sgnfcant. The estmated results ndcate that the techncal neffcency of onon producers decreases f the age, experence, and farm sze of farmer ncrease. The coeffcent of educaton s nsgnfcant wth postve sgn, whch means that the techncal neffcency effect ncreases wth the ncrease n educaton of farmer. It s unexpected but not entrely surprsng snce most of the educated farmers have alternatve ncome sources and they do not completely rely on agrculture for ther lvelhoods. If the farmers wth more formal educaton have alternatve ncome sources, or they are not attentve wth farmng practces and rely more on fxed labourer those are not educated, may have postve effect upon the neffcency effects.

6 176 BAREE The γ-parameter assocated wth the varance n the stochastc fronter model s to be estmated at , whch s sgnfcantly dfferent from zero. It ndcates that neffcency effects have a sgnfcant contrbuton n determnng the level and varablty of output of onon farms. The tests of null hypotheses are that the techncal neffcency effects are not present and the coeffcents of the varables n the model for the neffcency effects are zero. Formal tests of null hypotheses are tested by usng the generalzed lkelhood-rato test statstc. The estmated LR statstcs are and 22.12, whch are greater than the crtcal values of and 9.49 at 5 percent level of sgnfcance. Thus both the null hypotheses are strongly rejected. Farm-specfc techncal effcency It s more useful for polcy makers to measure the ndvdual farm-specfc techncal effcency than the average techncal effcency estmates. Indvdual farm-specfc effcency measures facltate dentfcaton of the determnants of effcency ratng among farms. Then approprate polces can be formulated to decrease effcency dfferences of farms, whch s mportant to accelerate the overall growth of farms. Table 2 dsplays the frequency dstrbuton of farmspecfc techncal effcency estmates of onon farms from the Cobb-Douglas stochastc fronters. Table 2. Dstrbuton of techncal effcency of onon farms. Effcency (%) No. of farms Percentage of farms Total number of farms Mnmum 58 Maxmum 99 Mean 83 Standard Devaton 11

7 TECHNICAL EFFICIENCY OF ONION FARMS 177 The study reveals that only percent of total sample farmers were found to have receved outputs whch were very close to the maxmum fronter outputs mantanng the effcency level 90 percent to 100 percent and percent of total sample farmers were observed to produce output lyng on the effcency level 80 percent to 90 percent, whle percent of total sample farmers produced outputs followng the effcency level 0 percent to 80 percent. The maxmum and mnmum techncal effcences were observed to be 99 percent and 58 percent, respectvely, where standard devaton was mantaned at 11. The mean of techncal effcency was found to be 83 percent. From the result, t can be nterpreted that on average, there appears to be 17 percent (= ) techncal neffcences among the sample farmers of onon farms. Ths mples that the output per hectare of onon farm can be ncreased, on average, by 17 percent through the effcent use of exstng producton technology wthout ncurrng any addtonal producton costs. References Battese, G.E. and T. J. Coell A Stochastc fronter Producton Functon Incorporatng a Model for Techncal Ineffcency Effects, Workng Papers n Econometrcs and Appled Statstcs, No. 69, Department of Econometrcs, Unversty of New England, Armdale, pp.22. BBS Statstcal Yearbook of Bangladesh, Bangladesh Bureau of Statstcs, Mnstry of Plannng, Govt. of the People's Republc of Bangladesh, Dhaka, pp BBS Monthly (December) Statstcal Bulletn. Bangladesh Bureau of Statstcs. Statstcs Dvson, Mnstry of Plannng, Govt. of the People's Republc of Bangladesh, pp.54. Coell, T.J A Monte Carlo analyss of the stochastc fronter producton functon, Journal of Productvty Analyss 6: Coell, T. J A Gude to Fronter Verson 4.1: A Computer Program for Stochastc Fronter Producton and Cost Functon Estmaton, CEPA Workng Paper 7/96, Centre for Effcency and Productvty Analyss, Unversty of New England, Armdale, pp Farrell, M.J The measurement of productve effcency Journal of the Royal Statstcal Socety, Seres A 120: Yawalker, K. S Vegetable Crops n Inda. Agr-Hortcultural Publshng House, Nagpur, pp

8 178 BAREE Appendx Table 1. Summery statstcs of the varables used n the model. Varables Mean value Mnmum value Maxmum value Standard Devaton Return (Tk./ha) Land (rental value, Tk./ha) Labour (man-days/ha) Seed (kg/ha) Irrgaton (hour/ha) Captal cost (Tk./ha) Age of farmer (years) Experence (years) Educaton (years) Farm sze (ha) Source: Feld survey, 2004