Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture

【Report】

107

Babu Chittilappilly Varkey＊ and Yoshihito Itohara＊＊＊United Graduate School of Agricultural Sciences, Tottori University ＊＊Faculty of Agriculture, Yamaguchi University E-mail: babinold＠hotmail.com & gbb５０＠po.cc.yamaguchi-u.ac.jp

Abstract

Galasa is the abbreviation for“Group Approach for Locally Adapted and Sustainable Agriculture”. The present study is aimed at establishing the viewpoint that the Galasa of rice farmers in the Kerala state of India is an operationally efficient, economically productive and socially beneficial agricultural production practice. The field survey covered１２０farmers, who were operating in the Galasa rice fields and adjacent locations in the Palakkad District of Kerala state. Applying the Data Envelopment Analysis （DEA）, a non-parametric frontier tool, the study proved that Galasa is an efficient agricultural production practice in terms of all efficiency measurements such as technical, scale, cost and allocative efficiencies. Boosting the rice yield from ３，２８７ kg／ha to ６，４４９ kg／ha and ensuring four times improvement in the profit, Galasa helps sustaining rice production in the state where foodgrain deficiency rose up to８０％ of the total demand. On achieving the full-scale yield potential, Galasa can promote Kerala’s self-sufficiency on foodgrains by reducing the deficiency level to ４９％. Galasa, which insists organic farming and encourages the preservation of the remaining３１０，５２１hectares of area under rice, can con- tribute significantly to the environmental sustainability. By preventing the fast disappearance of rice fields, Galasa can also absorb ９．４９％ of the total agricultural labourers in Kerala. In summary, Galasa has to be widely adopted as a pragmatic approach for the sustenance of rice production in an economically productive manner. With its state-wide replication, Galasa could be a panacea for some of the persistent problems like foodgrain deficiency, unemployment and environmental degradation.

１．Introduction

Despite the fact that growth in global food production is greater than growth in population, about８４０ million people are underfed in the present world and about３０％ of children in poor countries are under- weighted during１９７０―９５（Suresh２０００）. Among other factors, the poor income of the people is under- stood to be the major cause of food deprivation in developing countries. For instance, although India has attained self-sufficiency in foodgrain production with ２１１ million tonnes in ２００２（Department of Agri- culture & Cooperation２００３）, the country does not ensure food security mainly because of the poor purchasing power of the people. According to the Human Development Report（UNDP ２００３）, ７９．９％ of the Indian population is living with an income below US＄２aday,and２８．６％ is living below the national poverty line. Growing unemployment, unequal distribution of productive assets, ineffective utilisa- 108 Babu Chittilappilly Varkey and Yoshihito Itohara

tion of natural and human resources, and wide disparity of income levels are the well-known causes of poverty in India. However, the problems of food security and poverty in India to a greater extent could be overcome by augmenting the contributions of agricultural sector, which accounts for３０％ of the gross domestic product（GDP）and employs over ６０％ of the population. With１６０million hectares of gross cropped area, almost the size of US farmland（Prime Minis- ter’s Council on Trade and Industry ２００３）, there is an immense potential for agricultural development in India. Galasa, the name popular for“Group Approach for Locally Adapted and Sus- tainable Agriculture，”is known to be an Fig.１ Location of Kerala in South India innovative agricultural production ap- Source: Compiled from various Government of Kerala Publica- proach in rice production, so far prac- tions ticed on an experimental basis in the Kerala state of South India. Before we make clear the production approach of Galasa, it is desirable to understand the circumstances that led to the emergence of Galasa in Kerala. Although small in size（only１．１８％ of the total geographi- cal area of India）, Kerala has to feed ３．１０％ of the total population owing to its high density of population. Rice, being the staple food as well as the major crop of Kerala, its production comes to nearly ９７％ of the total food grain produced in the state. Still, Kerala has been a food deficit state since long ago for the reason that its domestic rice production can not satisfy even one-fourth of the total demands for staple food. Fast disappearance of area under cultivation, poor productivity and lower profitability are the known causes for this situation. Fig.２ Galasa Project Area（Palakkad District） While the area under rice declined from Source: Compiled from various Government of Kerala Pu- ８７６，０００ hectares in １９７５ to ３１１，０００ blications Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 109

hectares in ２００２ indicating about ６５％ reduction in the total area, the production showed a decline of ４８％ from １，３２９，０００ tons in １９７５ to ６８９，０００ tons in ２００２（see Fig.３）. Similarly, as could be evidenced from the inter-state comparisons in Fig.４and５, rice production in Kerala has also become less competitive owing to its poor yield, negligible profit and increased production cost. An inter-crop com- parisonasinFig.６and７testifies the fact that rice is not only the crop with the highest decline in terms of area under cultivation（about１９％）but also the least remunerative crop in terms of gross return（Rs. １８，９３５／ha）. Other factors, such as plentiful supplies of rice through public distribution system, free flow of rice in the open market from other states, and relatively smaller market price for rice, might have also induced rice farmers to switch over to other more profitable crops. As a practical solution to the prevailing problems, the Government of Kerala implemented a group farming scheme in １９８９ with the goals of preventing the then declining trend of area, and improving production and productivity of rice. However, the scheme, which consumed nearly４６０million rupees of investment, could not salvage rice production from its prevalent problems（Government of Kerala １９９７）. A study on the“organizational merits of group farming scheme in Kerala，”by the same authors in ２００２, observed that although group farming scheme was an economical failure, there had existed some organizational merits. Farmers had considered their groups, at the least, as an interactive-social fo-

1298 1272 1329 1087 1093 1173 875 876 742 802 953 803 678 689 722 751 471 559

347 311

Fig. ４ Yield and profit of rice in Kerala and Fig.３ Production and area of rice in Kerala other states（Average１９８１―０１） Source: Statistics for Planning and Economic Review Source: Compiled from various Govemment publica- （１９５１―２００３） tions

kg kg 3.19

Fig. ５ Production cost and price of rice in Fig. ６ Percentage change in area of princi- Kerala and other states （Average pal crops in Kerala during１９７５―０１１９８１―０１） Source: Compiled from various Govemment of Kerala publications Source: Compiled from various Govemment publications 110 Babu Chittilappilly Varkey and Yoshihito Itohara

rum in which their field experiences and operational problems are shared. Thus, there existed very high positive attitude on behavioral and or- ganization aspects of group farming, evidenced by the enhanced mutual trust, social interaction and group harmony. Farmers had also improved their interpersonal skills through their enlightened par- ticipation in the management of farmer groups. By the year１９９９, there had even a statewide network Fig. ７ Gross return from principal crops in of６，１００farmer groups（Babu and Itohara２００３）. Kerala-Average１９９５―０１（Rs. ／ha） The fact that rice farmers continue to remain in Source: Compiled from various Govemment of their groups as they are really induced to over- Kerala publications come their problems through group action despite the economic ineffectiveness of the failed group farming scheme was recognized by a voluntary group of agricultural scientists, farmer leaders and local government officials. They were determined to find out a lasting solution on the same lines of group farming but on an integrated approach that helps overcoming the deficiencies in the existing production system by adopting economically sound and environmentally friendly sustainable practices. Thus, this voluntary group in the name of‘Paddy Field Protection Movement’brought forth the concept of Galasa in１９９８as a pragmatic solution to revamp rice production by way of reducing cost, and enhancing yield and profitability（Popular Expert Committee,１９９８）. The basic approach is to mobilize and utilize natural resources for the development of locally adaptable technology in a massive way for the sustainable improvement of rice productivity（Estelitta et al., ２０００）. As a group approach, Galasa is a modified scheme of group farming that aims to take the full advantage of its prevailing organizational merits. The field level testing of Galasa was already ended up with two phases of experiments in Palakkad district during１９９９―２００１, and later on, it has been extended to Kuttanad and Thrissur rice fields of the state. By the year ２００２, the field experiments of Galasa were also reported to be completed. Based on the extensive literature survey, and the personal interviews conducted with the Galasa scientists and farmers, it is observed that Galasa encompasses many unique features in terms of both organizational and production aspects, as briefly described in Table １. As revealed in“the Methodology of Galasa，” published by Kerala Agricultural University（KAU１９９９）, Galasa scientists claim that the potential yield of Galasa under ideal conditions would be １０．３４ tons, as against ３．１８ tons of yield under the existing conditions. A square meter of area under Galasa can have ５０ rice plants with every plant has eight stalks, where one stalk has １１５ seeds, weighing one gram for ４４．５ seeds, which imply １０．３４ tons per hectare（５０×０８×１１５×１００００÷４４．５＝１０．３４ tons）. Whereas, a square meter of area under traditional farming（Non-Galasa）can have only ３０ rice plants with every plant has nine stalks, where one stalk has ７０ seeds, weighing one gram for ５９．４ seeds, which imply ３．１８ tons per hectare（３０×０９×７０× １０，０００÷５９．４＝３．１８tons）.

２．Statement of the Problem

The emergence of Galasa as an all-in-all solution in rice production is seen broadly accepted by farmers, agricultural scientists and policy makers. Some media reports suggest that Galasa has the capacity to Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 111

Table １ Features of Galasa production approach in contrast to conventional agriculture（Non- Galasa）

SL. Production Galasa Non-Galasa No. Approach Organic b Aims to recover the lost soil fertility by stimulating the activity of soil b As conventional agriculture, the farming and organisms with organic manures focus is‘green revolution’with １ production b Recycle nutrients in farms with the help of composting, green manur- increased use of chemicals, fertil- of organic ing etc. Planting of green manure trees in waste lands and production izers, pesticides etc. Organic farm- fertilizers of bio-fertilizers are taking place, though at a lesser extent ing receives less attention Integrated b Aims to control pests and disease through mechanical（removal and b Even though IPM is a widely ac- Pest Man- destruction of affected plant parts, sweeping nets, light trap, phero- cepted approach, the inactive ２ agement mone traps）,cultural（land preparation, water management etc.）bio- farmer groups have very little to （IPM） logical （Trichogramma card, fresh cowdung slurry） and chemical do with respect to mechanical and （pesticides, insecticides, fungicides, etc.）methods are adopted. biological methods of IPM Mechaniza- b Mechanization helps to correct the spacing and thereby maintaining b Almost no mechanization. Manual tion for main- optimum plant population which in turn improves maximum tiller pro- transplanting of plants does not ３ taining plant duction including the number of effective tillers ensure accuracy in spacing and the population b This also results in decreased incidence of weeds, pests and disease number of seedling per hill.

Locally b Optimal use of resources like labour, machine and water resources b Less attention to optimal use available re- b Insistence of using few adapted varieties of seeds that maintain genetic b Farmers are free to use any seed ４ sources, ad- purity and yield better results to given local conditions. that may or may not be adaptable. apted seed b This also helps promoting group efforts in the farming operations like Farmers pay less attention to com- and meth- raising the nursery, transplanting, harvesting, quality seed production mon cultivation methods ods Group b The promotion of farmer groups is inevitable for mobilizing collective b Farmer groups are organized, ５ based en- efforts in endeavors such as IPM practices, organic manure production, though they are not very active. deavours large scale utilization of machines, water management, bulk buying of b Only water management, and other production inputs, infrastructure development and skill development very necessary group actions On-farm b Any training to improve farmers’technical know-how and skills under b Usually, off-farm training, but that training and Galasa farming is strictly provided only at farm fields. too very limited. However, agri- ６ technology b Farmers as well as agricultural laborers receive training in the opera- cultural extension personnel pro- demonstra- tion methods of modern machineries and technology, along with their vide advises on new inputs and tion field-level demonstrations. methods while they visit fields Timely ag- b Beginning from the land preparation to harvesting, all farmers in a b This is absolutely lacking. Each ７ ronomic Galasa group operate their fields at the same time period as scheduled farmer has his own schedules. practices b This helps optimizing water use, reducing weed growth, controlling Hence, no uniformity in operation pests and diseases, and facilitates overall management of farm fields and less control on pests & other Major in- b Like in any other agriculture, capital investments of land and equip- b Basic factors of production are the puts used in ment, application of human labor and machine use, and materials such same. But the usage of machines the produc- as seed, fertilizer, chemicals, irrigation and organic manures are the and organic materials are very ８ tion basic inputs. much limited. b In practice, however, machines are widely used for land preparation, b Only few farmers hire machines transplanting and harvesting. Similarly, organic matters, such as cow- for transplanting and harvesting dung, ashes, composts and green manures are also applied. Revolving b The District Local Government is extending a revolving fund of ru- b No revolving fund assistance. Still, ９ fund for or- pees ２，５００ per hectare as an initial financial help through farmer few farmers apply organic ma- ganic ma- groups to facilitate the application of organic manure at the rate of two nures. Most of them fully depend nure tons per hectare, which is a compulsory production input in Galasa on chemical fertilizers Integrated b Initially, as an experimental project（１９９９―２００１）, it was supported by b No integrated promotional network promotional the Local Government of Palakkad District（for revolving fund）,state so far. However, farmers expect １０ network agricultural department （farm-level monitoring）,Centrefor that they may also be given the Environment and Development（environmental guidance and resource opportunity with the patronage of mapping）and Kerala Agricultural University（technical assistance） Government bodies Reduced b The basic idea behind Galasa is to make rice production economically b Farmers are often complaining in- production sustainable. Therefore, care is taken to ensure resource use efficiency creased material cost and opera- cost, with respect to the usage of natural resources, manpower and other tional expenses, poor yield and de- １１ increased production inputs. When inputs are applied in proper quality, quantity clined profitability. Seeing the yield and and time, and group efforts in IPM and other actions are practiced, merits of Galasa, some farmers enhanced farmers achieve reduced cost, increased yield and enhanced profit have started replicating it profit Source:１．Compiled from extensive literature survey of Kerala Government, Kerala Agricultural University, and newspaper and other media sources ２．Personal interviews with Galasa scientists, Galasa and Non-Galasa farmers. 112 Babu Chittilappilly Varkey and Yoshihito Itohara

address not only the persistent problems of rice farmers such as poor yield, increased production cost and declining profit, but also the macro level issues of foodgrain deficiency, unemployment, poor house- hold income and environmental degradation. Still, these claims were not substantiated by any logical study. Although few reports on Galasa were published by KAU, these were mainly introductions of Ga- lasa as an experimental project. It is very disappointing to learn that there were no scientific studies conducted about an innovative agricultural practice like Galasa which has been widely adopted by farmers at the end of its experimental phase. Being regarded as the continuation of the previously failed group farming scheme, to what extent its integrated approach of combining the features of both large scale farming and scientific agronomic practices was really successful, in terms of transforming the rice production into an economically sustainable manner by reducing cost, enhancing yield and improving profit, is obviously a matter of interest for all those involved in the agricultural sector development. In this direction, when studies are initiated to exploring the economic possibilities as well as the impact of Galasa, of course, there could have many more dimensions than what we have mentioned here. How- ever, in our study, we are mainly intended to expose the unique position of Galasa as an operationally efficient, economically productive and socially significant agricultural production approach. Thus, in the realization of the analytical scope of the study, we have set the following specific objectives. １. To evaluate the operational efficiency of Galasa in comparison with traditional type agriculture （Non-Galasa）２. To evaluate the economic performance of Galasa, and appraise its contributions to the society The results generated by our study may very well be helpful to policy makers, agricultural researchers and extension personnel for these results could be the ground-level realities on the economic achieve- ments and usefulness of Galasa. The present study is also taken place at a crucial point of time where Government of Kerala is also seriously considering the need to replicate Galasa throughout the entire rice fields in the state.

３. Materials and Methods

The secondary data for the study were compiled from a number of government and other publications for the period from１９５１to２００３. With respect to primary data collection, the study area was limited to the Palakkad District of Kerala State where Galasa experiments were conducted on a large scale（２，４４５- hectare area）. The maps of the location of research are furnished as Fig．１ and ２. Using the pre-tested interview schedules, the information regarding rice farming operations, input price, input quantity, cost and output for the crop year ２００２―０３ were collected from １２０ farmers, selected at random with ６０ farmers each from Galasa farm groups and Non-Galasa farm groups, who were operating in the same ir- rigated area. Care has taken to include only those Non-Galasa farmers who are holding rice fields that are very close in location to Galasa farmers in the Palakkad district. Moreover, the personal interviews with the Galasa scientists, group leaders, and government officials, as well as the field level observations of the first author have also greatly contributed to the required data input for the study. Besides simple statistical tools of analysis, judgements based on logical reasoning also formed the method of analysis. A test of statistical significance applying independent-samples T test was also performed while compar- ing the means between two groups. In order to facilitate a quick and easy comprehension of the subject matter, a number of diagrams are substituted in the place of tabular data. Necessary procedural notes are also attached at the end of the tabular presentation of the analytical data. The exploration of data for ef- Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 113

ficiency measurements is achieved through the DEA method. A very short description of its application is as follows. Data Envelopment Analysis（DEA）and stochastic frontiers are the commonly used methods for efficiency measurements, which involve mathematical programming and econometric methods respectively. DEA involves the use of linear programming（LP）methods to construct a non-parametric surface（or frontier）over the data, so as to be able to calculate efficiencies relative to this surface. Realizing the flexibility of DEA approach with respect to producing a number of operational efficiency indicators such as technical, scale, cost and allocative efficiencies, we have chosen DEA for measuring the efficiency of Galasa. In this regard, we made use of a DEA computer software called“DEAP”Version ２．１, written by Tim Coelli（１９９６）with its Windows interface“Win４DEAP”Version ０．９．９, con- structed by Michel Deslierres（２００２）. The concepts and formulas relating to different efficiency indicators used in our study are briefly explained below. １. Technical Efficiency（TE）is the ability of a firm（individual producer as a decision-making unit）to obtain maximum output from a given set of inputs. In calculating the technical efficiency, the Vari- able Returns to Scale（VRS）technology is applied on the assumption that not all firms are operating at an optimal scale. ２. Both Constant Returns to Scale（CRS）and Variable Returns to Scale（VRS）DEA models have been involved in the calculation of scale efficiency（SE）. This is because SE is measured as the difference between CRS TE and VRS TE in the form of a ratio. That is, SE ＝ CRS TE ／VRS TE ３. Cost Efficiency（CE）: The total cost efficiency is estimated based on a cost minimisation objective using the price information of the inputs. ４. Allocative Efficiency（AE）is the ability of a firm to use the inputs in optimal proportions, given their respective price information and the production technology. It is calculated residually from the cost and technical efficiencies using the formula, AE ＝ CE／TE The data inputs for the DEA were the quantity of rough rice produced in kg as the dependent variable, and the seven components of the total production cost as the independent variables. These were total labour use in days, fertilizers and lime in kg, seed in kg, organic manures in kg, cost of machine use in rupees（Rs.）, chemicals and pesticides in Rs., and other materials and supplies in Rs. Additionally, the respective prices of these variables were used for the measurement of cost efficiency. The specifica- tion of DEA, using which the DEAP software is analysing the data, is briefly stated as in Table２.

４．Results and Discussion

In this section of our paper, at first, we examine the strength of Galasa with respect to its operational efficiency in comparison with Non-Galasa. This helps to understand how well Galasa is regarded as an efficient agricultural practice in terms of its technical efficiency, cost efficiency and other related efficiency indicators. After we generated the efficiency measurements for each Decision Making Unit（each farmer as each DMU）by performing the DEA for all１２０farmers together in the same data set, we cat- egorised the DMUs into two groups and computed the efficiency averages separately for６０Galasa and ６０ Non-Galasa farmers as given in Table ３. These figures prove that Galasa has attained a superior standing in all relative efficiencies such as technical（９５．５％ in VRS）, scale（９７．９％）,cost（３９．８％） and allocative（４１．５％）efficiencies. Further, there are significant differences between Galasa and Non- Galasa in terms of their respective values. As shown in Table４, the efficiency differentials between Ga- 114 Babu Chittilappilly Varkey and Yoshihito Itohara

Table２ Application of Linear Programming for Data Envelopment Analysis of Operational Effi- ciencies

Firstly, the input-oriented CRS DEA model is where θ is a scalar and λ is a N×１vector of constra- explained here. Assuming K inputs and M outputs ints. The value of θ obtained will be the efficiency for each of N firms, these data for the i-th firm are score for the i-th firm.

represented by the column vectors xi and yi, respec- Secondly, the VRS DEA model can be modified from tively. The K×N input matrix, X, and M×N output the CRS LP problem by adding the convexity con- matrix, Y, represent the data for all N firms. A ra- straint: N１′λ＝１to equation（２．３）to provide:

tio of all outputs over all inputs will then be ob- minθ，λθ,

tained, such as u′yi／v′xi,whereuisaM×１ vector st －yi＋Yλ＞－０， of output weights and v is a K×１ vector of input θxi－Xλ＞－０， weights. The optimal weights are obtained by solv- N１′λ＝１ ing the mathematical programming problem: λ＞－０，（２．４） maxu,v（u′yi／v′xi）， Note: min＝minimise st u′yj／v′xj－＜１,j＝１,２,.....,N, where N１ is a N×１ vector of ones. This approach u,v－＞０．（２．１） forms a convex hull of intersecting planes which enve- Note: max＝maximise; st＝subject to lope the data points more tightly than the CRS conical However, the problem of infinite number of solu- hull and thus provides technical efficiency scores which tions from this measure could be avoided by im- are greater than or equal to those obtained using the

posing the constraint v′xi＝１, which provides: CRS model. Further, Modifying the equation（２．４）,the

maxμ，ν（μ′yi）, cost minimisation DEA is obtained by: * st ν′xi＝１， minλ，xi* wi′xi , μ′yj－ν′xj－＜０,j＝１,２,....,N, st －yi＋Yλ＞－０，＊ μ,ν＞－０, （２．２） xi －Xλ＞－０， where the change of notation from u and v to μ N１′λ＝１ and ν is used to stress that this is a different LP λ＞－０，（２．５）

problem. Using the duality in LP, an equivalent where w′i is a vector of input prices for the i-th firm and ＊ envelopment form is obtained as: xi （which is calculated by the LP） is the cost-

maxθ，λθ, minimising vector of input quantities for the i-th firm,

st －yi＋Yλ＞－０， given the input prices wi and the output levels yi.The θxi－Xλ＞－０， total cost efficiency of the i-th firm is calculated as CE ＊ λ＞－０，（２．３）＝w′ixi ／w′ixi. That is, CE is the ratio of minimum cost to observed cost for the i-th firm.

Source: Compiled from“An Introduction to Efficiency and Productivity Analysis”（Tim Coelli, et al.１９９８） lasa and Non-Galasa are also tested statistically significant. The DEA technique suggests that efficiency values obtained under this method of analysis will nor- mally be ranged from zero to one. When the obtained values are closer to one, there will have utmost efficiency, but when these values are approaching zero, there will have poor efficiency. Although technical efficiency（CRS and VRS）and scale efficiency values are closer to one in the case of both Galasa and Non-Galasa, the net differences of these values confirm that Galasa is a highly efficient production approach. The similar is the case with those of cost and allocative efficiencies, wherein the net differences in the values also suggest the cost efficient nature of Galasa compared to Non-Galasa. However, Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 115

Table３ Efficiency measurements of rice production under Galasa and Non-Galasa（２００２―０３）

DMU Galasa Non-Galasa TE TE SE CE AE TE TE SE CE AE （N＝６０）（CRS）（VRS）（CRS）（VRS）１．９８８．９９１．９９７．２５１．２５３．８６３．９１７．９４１．２８９．３１６２１．０００１．０００１．０００．５６３．５６３１．０００１．０００１．０００．３４８．３４８３．７６８．７８２．９８２．２３５．３００．９７５．９８３．９９２．２５０．２５４４１．０００１．０００１．０００．２６６．２６６．６５５．６９５．９４２．１８７．２７０５．９６１．９９８．９６３．３６６．３６７．６２１．６５８．９４４．２２５．３４１６．９２０．９６６．９５２．３２７．３３８．７０８．８２３．８６０．１７８．２１６７１．０００１．０００１．０００．３８３．３８３．５８６．８３３．７０３．４１３．４９６８．８２７．８２９．９９８．３６９．４４４．９１５．９２１．９９３．２５９．２８１９．８０９．８２３．９８３．３４４．４１８．４５０．４６８．９６２．１６２．３４５１０１．０００１．０００１．０００．３０４．３０４．４９１．４９５．９９２．０８２．１６７１１．９３１．９４６．９８４．２４９．２６３．４２３．４２８．９８８．１５６．３６３１２１．０００１．０００１．０００．２９９．２９９．３８８．４５７．８４９．２０２．４４３１３１．０００１．０００１．０００．３５３．３５３．５８４．６０７．９６２．１７４．２８６１４．８５１．８８０．９６７．３００．３４１．５１３．５８５．８７７．２０３．３４７１５１．０００１．０００１．０００．４１６．４１６．５３５．５３８．９９４．２８４．５２８１６．９１２．９１７．９９５．２９９．３２６．５７７．６４５．８９５．２１７．３３７１７１．０００１．０００１．０００．３１９．３１９１．０００１．０００１．０００．３５５．３５５１８．９４５．９４８．９９７．３８７．４０９．７８６．８０２．９８０．１６０．１９９１９．８９４．９２６．９６５．３６７．３９７１．０００１．０００１．０００１．０００１．０００２０．８１３．８２１．９９０．４４６．５４４１．０００１．０００１．０００．３６４．３６４２１１．０００１．０００１．０００．２６１．２６１．７９６．８６７．９１８．１６９．１９５２２１．０００１．０００１．０００．３６１．３６１．４６１．４６３．９９６．１３０．２８０２３．９８１１．０００．９８１．２８７．２８７．５４６．５７６．９４８．１８７．３２５２４．８４８１．０００．８４８．４３９．４３９．５３７．５９０．９１０．１７２．２９２２５．８８５１．０００．８８５．３７７．３７７．５５９．５７９．９６５．１０９．１８８２６．８８７．９１４．９７０．２６２．２８６１．０００１．０００１．０００．２８２．２８２２７．７５４．８５０．８８７．２９０．３４１．５９８．６０２．９９３．１１３．１８８２８．８８９．８９３．９９６．２８９．３２４．８８９．９２９．９５７．１６３．１７５２９．８３２．８８１．９４４．２６２．２９７．６６６．７５０．８８８．１２７．１６９３０．８３４．８３６．９９８．２６３．３１４．６２５．６５９．９４８．１６１．２４４３１１．０００１．０００１．０００．９７６．９７６．６６３．７１１．９３２．１２５．１７７３２．８４９１．０００．８４９．３１８．３１８１．０００１．０００１．０００．３６１．３６１３３１．０００１．０００１．０００．３８４．３８４．６５２．６５２１．０００．１９８．３０３３４．８３６．９０２．９２７．３１８．３５２．６１７．６３０．９７９．２０１．３２０３５１．０００１．０００１．０００．４４６．４４６．３８２．４０７．９３９．２１３．５２２３６．９７７１．０００．９７７．３６３．３６３１．０００１．０００１．０００．２７７．２７７３７．８８６．８９８．９８７．３５９．４００．６３６．６４８．９８１．２０１．３１０３８１．０００１．０００１．０００．５１７．５１７．６１９．６８０．９１０．２３９．３５１３９．８６２．９１３．９４４．４７１．５１５．６３４．６９０．９１９．１９３．２８０４０．８５０．８７８．９６８．２８８．３２８．５６４．５８６．９６２．１９４．３３１４１．９０１．９９７．９０４．３７４．３７５１．０００１．０００１．０００．９１０．９１０４２．９３６．９４４．９９２．２９８．３１５．９０１．９５９．９４０．２２５．２３４４３．９５４．９６６．９８８．３３２．３４４１．０００１．０００１．０００．６６１．６６１４４．８６１．８７１．９８９．４００．４５９．９８５１．０００．９８５．６３０．６３０４５１．０００１．０００１．０００．３７６．３７６．８４４．８７６．９６３．０９８．１１２４６１．０００１．０００１．０００．６４８．６４８．６４６．６８２．９４７．２３８．３４８４７．９２９．９３８．９９０．３６０．３８４．７６９．７７０．９９９．３４４．４４７４８．９２２．９２６．９９６．３１８．３４４．７１６．７２６．９８６．３２６．４４９４９１．０００１．０００１．０００．３７９．３７９１．０００１．０００１．０００．２９０．２９０５０１．０００１．０００１．０００．８０２．８０２．８６３．９１７．９４１．２８９．３１６５１１．０００１．０００１．０００．９２５．９２５．９８４．９８５．９９９．４１７．４２３５２１．０００１．０００１．０００１．０００１．０００１．０００１．０００１．０００．２６７．２６７５３１．０００１．０００１．０００．７４４．７４４１．０００１．０００１．０００．３６１．３６１５４１．０００１．０００１．０００．５５４．５５４．６３８．６５１．９８０．１３１．２０１５５．９３６．９７３．９６２．３２５．３３４１．０００１．０００１．０００．２２３．２２３５６．９６０．９６１．９９９．３８２．３９７．６０８．６１０．９９７．２１３．３４９５７１．０００１．０００１．０００．３０５．３０５．８５１．８７９．９６８．４３６．４９６５８１．０００１．０００１．０００．３６７．３６７．８５５１．０００．８５５．４４２．４４２５９．９２８．９３８．９８９．３３１．３５３１．０００１．０００１．０００．１５９．１５９６０１．０００１．０００１．０００．２９３．２９３．８８４１．０００．８８４．１７５．１７５ Mean ０．９３５０．９５５０．９７９０．３９８０．４１５０．７５１０．７８２０．９５８０．２６９０．３３９ Source: Data collected through field survey Note: DMU＝Decision Making Unit（Nfarmers）,TE（CRS）＝Technical Efficiency（Constant Returns to Scale）,TE（VRS）＝ Technical Efficiency（Variable Returns to Scale）,SE＝Scale Efficiency, CE＝Cost Efficiency, and AE＝Alllocative Efficiency 116 Babu Chittilappilly Varkey and Yoshihito Itohara

Table４ Efficiency Differentials between Galasa and Non-Galasa Group Statistics Independent-samples test（T-Test） Efficiency Variables Std. Std. Error Sig. Mean Std. Error of N Mean tdf Deviation of Mean （２-tailed） Difference Mean Difference Technical Efficiency（CRS） Galasa ６００．９３５０．０７１０．００９６．７５１１１８０．０００＊＊０．１８４０．０２７ Non-Galasa ６００．７５１０．１９９０．０２７ Technical Efficiency（VRS） Galasa ６００．９５５０．０６００．００８６．６１９１１８０．０００＊＊０．１７３０．０２６ Non-Galasa ６００．７８２０．１９３０．０２５ Scale Efficiency Galasa ６００．９７９０．０３６０．００５２．５２８１１８０．０１３＊０．０２１０．００８ Non-Galasa ６００．９５８０．０５４０．００７ Cost Efficiency Galasa ６００．３９８０．１７２０．０２２４．１０２１１８０．０００＊＊０．１２９０．０３１ Non-Galasa ６００．２６９０．１７２０．０２２ Allocative Efficiency Galasa ６００．４１５０．１６７０．０２２２．５３４１１８０．０１３＊０．０７６０．０３０ Non-Galasa ６００．３３９０．１６２０．０２１ Note: ＊and ＊＊indicate the level of significance at１％ and０．０１％ respectively there is still room for improvement in Galasa in terms of both cost and allocative efficiencies, as these efficiency values are relatively smaller than those of technical and scale efficiencies. In summary, Galasa is a sound agricultural production practice with exceptional operational efficiency. Besides operational efficiency, an attempt is also made to demonstrate the economic performance of Galasa in comparison with Non-Galasa in Palakkad district and with Kerala state average（see Table５）. Following the line of enhanced operational efficiency, Galasa has also outperformed Non-Galasa with respect to yield, cost and profit. With the increased yield of ６，４４９ kg／ha and reduced production cost of１６，５６２Rs.／ha, Galasa could produce one kg rough rice at the rate of Rs.２．５７, which is about２８％ lower than that of non-Galasa. As the result, Galasa enjoyed a highest profit-cost ratio of１．７４:１with a profit of Rs.２８，７９１from one hectare of rice area, which is about double the Non-Galasa profit. Thus, from our comparative analyses of efficiency measurement and economic performance, it could be safely inferred that the production approach of Galasa is not only economically beneficial but also operationally efficient. As our study is also aimed to highlight the social significance of Galasa, in the following part of this paper an effort is also made to appraise the contributions of Galasa to the farmers and labourers in par- ticular, as well as to the society in general. In this direction, we try to expose the possible income improvement for rice farmers and the employment support for agricultural labourers, which may have a positive impact on their purchasing power. From the comparison of Galasa performance with that of average performance at state level, as shown in Table ５, it is observed that there would be about four times improvement in the profit of rice farmers（from Rs.７，０７４to Rs.２８，７９１）, if Galasa got extended throughout the Kerala state. At the prevailing cropping intensity of１７９％, their annual income from one hectare of rice would be increased to Rs.５１，５３５, which is then more or less comparable to the income from other alternative profitable crops. The realization of this objective will in turn enhance the confidence of farmers in rice production. Therefore, along with the enhancement of confidence in rice pro- Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 117

Table５ Comparison of economic performance of Galasa with non-Galasa in Palakkad district, and with Kerala state average（２００２―０３）（Rs. ／ha） Palakkad District Kerala State Items Galasa Non-Galasa Difference State Average Difference ¸ ¹ （１－２） º （１－３） Rice value ４３，８５５．６２３１，３７８．１９１２，４７７．４３２２，３５１．６０２１，５０４．０２ Rice yield（kg ／ha）（6,449.36）（4,768.72）（1,680.64）（3,287.00）（3,162.36） Straw value １，４９６．８９１，２９５．７４２０１．１５２，７６８．００－１，２７１．１１ Gross return（A）４５，３５２．５１３２，６７３．９３１２，６７８．５８２５，１１９．６０２０，２３２．９１

Operational cost １１，１１５．４７１２，０４６．７６－９３１．２９１０，３６０．０４７５５．４３ Material cost ５，４４６．４６５，００４．１９４４２．２７７，６８５．７４－２，２３９．２８ Production cost（B）１６，５６１．９３１７，０５０．９５－４８９．０２１８，０４５．７８－１，４８３．８５ Production cost（Rs. ／kg）（2.57）（3.58）（−1.01）（5.49）（−2.92）

Profit（A ― B）２８，７９０．５８１５，６２２．９８１３，１６７．６０７，０７３．８２２１，７１６．７６ Profit-Cost Ratio （1.74：1）（0.92：1）（0.82：1）（0.39：1）（1.35：1） Source: While the entire data for the Palakkad district were collected through our field survey, the cost data for the Kerala state were compiled from the ICAR survey for１９９５―９６（Suresh ２０００）, and the others from Kerala Government publications（２００２―０３）. Note: １. The production cost for the year １９９５―９６ were substituted for ２００２―０３ at the total inflation rate of ４１．２％ for the seven-year period. ２. Rice yield refers to rough rice or paddy. It is the rice retaining its husk after threshing. duction driven by the attractive profit, the present trend of declining rice area could be gradually brought under control. Galasa is also indirectly helpful in sustaining employment in Kerala where unemployment is２０．９７％, the highest compared to the all-India average of ７．３２％（Gupta ２００３）. Unlike rubber, coconut and other tree crops, rice enjoys the credit of absorbing more labourers at lesser investment cost, as it provides １４４ labour days under traditional farming and １２６ labour days under Galasa from a hectare area of operation. Galasa will hopefully be an inspiring force for the continuance of rice farming, and therefore it can ensure regular employment to １５６，５０３ workers, which constitutes ９．４９％ of the total agricultural workforce in the state（see Table６）. Galasa advocates for the balanced use of machine and labour resources from the point of view of optimising the use of locally available resources. The drop of １８ labour days compared to the traditional practice, however, could be compensated by the additional activities proposed by Galasa in the form of planting of green manure trees, organic manure production, special nursery treatment for mechanised transplanting etc. After having recognized the usefulness of Galasa to farmers and farm workers, the next task is to as- sess the extent to which Galasa can overcome the problem of foodgrain shortage in the state. The information furnished in Fig.８confirms the fact that over a half-century period, Kerala has never been self- reliant in producing the required quantity of rice. By the year２００１, only２０％ of the requirement is met through the self-production, and of the shortage of ８０％, ３６％ is managed through the public distribu- 118 Babu Chittilappilly Varkey and Yoshihito Itohara

Table ６ Labour absorption capacity of rice production in tion system of the Central Gov- Kerala（２００２―０３） ernment and the rest ４４％ is channelled through the traders Items Value from the neighbouring states（see Gross cropped area ３１０，５２１hectares Fig. ９）. Obviously, a huge Labour absorption under Galasa １２６labour days／ha amount of money is flowing out Labour absorption under non-Galasa １４４labour days／ha of Kerala to other states as pro- * Regular employment under Galasa １５６，５０３workers curement price of rice, which in ９．４９％ Rice labourers to total agricultural workforce turn may affect the state’s econ- Agricultural workforce to total workforce １６．０７％ omy adversely. Through the trad- Source: Data collected through field survey, and compiled from the ers only, it amounts to roughly Published documents of Government of Kerala and others ３４９ million USD for the year ＊ Note: A worker is considered to be regularly employed when he ２００１. works for２５０days a year As could be seen in Table ７, Fig.１０and１１,wehavemadean attempt to foresee the Galasa’s potential contribution to rice supply on the basis of the different yield levels. The district-wise expecting yield levels under Galasa, both as per our field survey and the estimate of Kerala Agricultural University（KAU）, are apparently very realistic compared to the yields ac- tually attained on crop competition（lowest and highest）in １９８６―８７.AsperFig.１１, at the yield level of６，４４９kg／ha Galasa can meet３５％ of the total rice requirements, bringing down the deficiency level to６５％. If not achieving the full potential of１０．３４tons, at a reasonable higher performance, say for instance at９，３２０kg／ha（the highest competition yield level）, Galasa can lead the Kerala state into half- way to self-sufficiency, by satisfying５１％ of the demand. This, in fact, could be regarded as the great- est contribution of Galasa to this chronically food deficit state. The environmental impact of Galasa, though not verified in our study, may also be praise-worthy. Rice fields in Kerala are acting 3033 as reservoirs and function as water storage 2403 751 agent. Since paddy area declines without pre- 1200 1060 serving and percolating water, flood in mon- 1334 3784 885 3463 soon and drought in summer are very fre- 722 2534 1607 quently occurring in the state. Galasa, which 2910 3180 1350 2130

20％ 44％ Fig. ８ Requirement, production and deficiency of 36％ rice in Kerala Source: １．Report of the Task Force On Field Crops, Govemment of Kerala（１９９７） Self Production Central Government Traders ２．Source: Staistics for Planning and Economic Re- view（１９５１―２００３） Fig. ９ Source-wise share of supply Note: The quantity required is based on the actual consump- of rice in Kerala（２００１） tion of rice eslimaled for the year １９９６.Itwas３３０ Source: Derived from various Govemment of grams per day per person, resulted in１１９kg per year Kerala publications Operational Efficiency, Economic Performance and Social Significance of GALASA Style Rice Production in Indian Agriculture 119

Table ７ District-wise area, actual yield and expecting yield of Rice in Kerala （kg／ha） Competition Yield Expecting yield Area Actual （１９８６―８７） under Galasa Districts （ha） yield As per field As per KAU （２００２―０３） Lowest Highest （２００２―０３） survey estimate

Thiruvanathapuram ６，４２３６，３７０９，２００３，２８１６，４３７７，２７２ Kollam １１，４５７― ― ３，１５４６，１８８６，９９１ Pathanamthitta ５，４３１６，６８０６，９００３，７１６７，２９１８，２３６ Alappuzha ２９，６３５５，９２０８，２３０４，６１２９，０４９１０，２２２ Kottayam １２，２６４６，２８０９，３１０３，７５８７，３７３８，３２９ Idukki ３，７８５７，４９０８，２４０３，３８１６，６３４７，４９４ Ernakulam ３２，０７２６，４９０９，９８０２，８３３５，５５８６，２７９ Thrissur ３７，２７４４，５２０７，７８０３，４９４６，８５５７，７４４ Palakkad １１５，９１０７，０５０１５，９００３，１４０６，１６１６，９６０ Malappuram １９，６７８６，６２０７，２１０２，９５７５，８０２６，５５４ Kozhikode ５，０８５６，４２０９，０１０２，１０３４，１２６４，６６２ Wayanad １２，９８８― ― ３，６００７，０６３７，９７９ Kannur １１，３２３７，２２０９，８８０２，７４０５，３７６６，０７３ Kasargod ７，１９６９，１００１０，１９０３，２４５６，３６７７，１９２

State Average 310,521 6,680 9,320 3,287 6,449 7,285

Source: Data collected through field survey, and compiled from the Published documents of Government of Ker- ala and Kerala Agricultural University（KAU２００２） Note:１. Rice yield refers to rough rice or paddy（the rice retaining its husk after threshing）２. The district-wise expecting yields are computed by multiplying the district-wise actual yield with the ratio between state average yield and Galasa yields.

9320 7285 6449

3287 59.96 51.22 48.78 40.04 35.44 64.56 18.05 81.95

Fig.１０ YieldofriceinKerala（kg／ha） Fig.１１％production and % deficiency to total Source: Data collected through field survey, and rice requirement at different yield lev- compiled from the Published Govemment els documents and Kerala Agnicultural Univer- Source: Data derived using the data source in Fig.８and sity（KAU２００２）１０. Note: Rice yield refers to rough rice or paddy 120 Babu Chittilappilly Varkey and Yoshihito Itohara

insists organic farming and encourages the preservation of entire area under paddy, may also help preventing the subsequent environmental degradation in the state.

５．Conclusion

Our study inferences are in agreement with the supposition that Galasa could successfully overcome the economic ineffectiveness of the previously failed group farming scheme by integrating scientific agronomic practices and group based endeavours in an innovative manner. The results obtained through DEA empirical analysis confirm that Galasa is a technologically sound, cost effective and operationally efficient agricultural production practice. Galasa is helpful not only in overcoming many persistent problems in rice production, such as poor yield, increased production cost and declining area, but also in improving the income of farmers and agricultural labourers. Considering the potentialities of Galasa as a strategy to address the macro level issues of foodgrain deficiency, unemployment, environmental problems etc, the Government of Kerala has to hold the primary responsibility for the proper propagation of Galasa.

References Babu, C.V., and Yoshihito Itohara. ２００３.“Organisational Merits of Group Farming Scheme: A Case of Rice Production in Kerala, India．”Journal of Rural Economics. Special Issue２００３. pp.４６５―４７０. Department of Agriculture and Cooperation. ２００３.“Fourth Advance Estimates of Foodgrains Production for ２００２―０３．”Government of India, New Delhi. http:／／agricoop.nic.in ／statistics ／advesti１.htm（March １８, ２００３）. Estelitta, S., Elsy, C.R., and Jayasree, S.２０００.“GALASA for sustenance of rice culture in Kerala．”The Inter- national Conference on Democratic Decentralisation. Trivandrum: Kerala State Planning Board. Government of Kerala.１９９７. Report of the Task Force on Field Crops. Trivandrum: Government of Kerala. Gupta, S.P.２００３.“Gupta Panel on Targeting Employment．”Centre for Indian Trade Union. http:／／citu.org.in ／ wclass_nov０２_a８.htm（March５, ２００３） Kerala Agricultural University.１９９９. The Methodology of Galasa. Thrissur: Kerala Agricultural University. Kerala Agricultural University.２００２. Galasa Second Phase Report. Thrissur: Kerala Agricultural University. Michel Deslierres.２００２.“Win４Deap Version ０．９．９．”http:／／www.umoncton.ca ／desliem ／dea ／install.htm（May ７,２００４） Popular Expert Committee.１９９８. Study Report Summary １９９８. Kerala: Paddy Field Protection Movement. Prime Minister’s Council on Trade and Industry.２００３.“Report on Food & Agro Industries Management Policy, Executive Summary．”Government of India, New Delhi. http:／／www.nic.in ／pmcouncils ／reports ／food ／ esum.htm（February２４,２００３）. State Planning Board. １９５１―２００３. Statistics for Planning and Economic Review. Trivandrum: Government of Kerala. State Planning Board. ２００２. “Agriculture and Allied Sectors．” Government of Kerala. http:／／www. keralaplanningboard.org ／html ／Xchapter３.１html（February１７,２００３）. Suresh, K.A.２０００. Group Management Approach to Agricultural Development―A Case Study of Rice Farming in Kerala. Thrissur: Indian Council of Agricultural Research（ICAR）. Tim Coelli.１９９６.“A Guide to DEAP Version２．１．”http:／／www.uq.edu.au／¯uqtcoell／deap.htm（April２,２００４） Tim Coelli, Prasada Rao, S., and George E. Battese. １９９８. An Introduction to Efficiency and Productivity Analysis. Boston: Kluwer Academic Publishers. UNDP. ２００３.“Human Development Indicators ２００３．”United Nations Development Programme. http:／／www. undp.org ／global ／２００３／indicator ／cty_f_IND.html（June２０,２００４）.