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esiduals (Table 12). Ultimately, the income shares of farmers were 93% of the value added for adopters and 90% for nonadopters. The farm income of adopters is slightly less in absolute terms, although it is slightly more in terms of the proportion of value added. Tflird-season vegetable. Of the total value added in vegetable production, proportional income earned by hired laborers, capital owner, land owner, and family and exchanged labor were lower for adopters than nonadopters (Table 13). This led to higher percentages of income as a resldual(58%), and ultimately, a higher income share by the adopter farmers. In the production of vegetables, 90% of the income generated by adopters and 78% of the income of nonadopters accrued as personal income and only a small percentage was paid out. In absolute terms, the Inconies accrued to various factor owners connected to the adopters were higher because the value added for the same group is higher. Annual three-crop cycle. The values added in the three-crop annual cycles were very close in the two groups, with adopters having an additional SLR7,777/ha (Table 14). This resulted from a cancellation of the positive gains in rice and vegetable production by the negative gains in potato production. Only about 1-2% of the value added went to the capital owners and 15% went to tlie land owners from each group of farmers. Income from adopters to hired labor was 7% of value added; whereas, family and exchange labor captured 12%. For nonadopters, 11% went to hired Iabor and 8% to family and exchange labor. Except for proportions accrued to tlie farm family as payments for family labor, there are no other salient differences in distributions of personal income. Residuals that remained with the farmers amounted to 42% for adopters and 41% for nonadopters. Ultimately, adopters cry-ned a slightly higher percentage of value added (89%) as their personal income froni the production of crops within a l-yr period. Nonadopters earned only 83 %. The income of adopters froni rice production improved slightly as n result of adopting tlie technology, but the effect was nullified by greater disadvantages to the potato crop under the new farming system. The third crop of vegetables performed well under the new system and managed to equalize (in fact exceed nonadopters by a small margin) factor incon~es and personal incomes, with a slight reallocation of the cost of labor in hvor of farmers. \Velf;tre measures other than income Elidowl?tent of fan71 ar.rcts. Changes in personal income can cause changes in tlie endowment of farm and household assets. Table IS indicates that there were no consistent differences in farm assets owned by the two groups of farmers. None of the adopters owned two-wheeler tractors, but one of 18 nonadopters owned a two- wheeler. Although 65 niammoties were owned by 19 adopters, only 13 were owned by l8 nonadopters within the year under study. Milking cows were owned by 13 adopters, but only by 6 nonadopters. Storage boxes were owned by eight adopters and by three nonadopters.
E~zdowr~tcnt of l~ouselrol~f assets. Of the household assets that \\.ere considered, all adopters and 72% of nonadopters had radios (Table 16). More nonadopters o\\lned television sets than adopters. None of the nonadopters owned bicycles or motorbikes, but adopters did. A bus was owned by a nonadopter. There was no definite pattern ofdifferences in ownership of household assets. These findings are consistent with the marginally different personal incomes of adopters and nonadopters. hTzltritioti. Nutrition, which is one of the most important variables in measuring social well-being, plays a major role in enhancing health conditions and increasing the quality of labor. Calories and protein are the major components of a balanced diet. Each adopter consumed 2,126 cal/d; \\.hereas, each nonadopter consumed 2,080 cal/d. Per capita consumption of protein per d:~y was 55 g for adopters and 52 g for nonadopters. There \+.ere no significant differences in daily per capita calorie consuniption or protein consumption between adopters and nonadopters. No direct inipact of the technology on nutrition \\.;IS observecl. E.vpcnriitiir.c ur~rf .rrr\linss. Expenditures on food by both categories of farniers were very similar. Almost 40% of the total expenditure of adopters was spent on food consumption; whereas, nonadopters spent nearly 33% of their total expenditure 011 food (Table 17). Adopters had higher average savings than non:ldopters, l~ut the difference was not significant (Table 17). In the ahsence of any differe~ices in n~ltritional intake, the expenclitures and s:~vings tally well with the niargin:ll income advantage that farmers recei\.ed by adopting the new fClr~iiing sjJsterns technology. Limitations of the study The study, initiated in 1087-88, suffered :l break in d:itrl collection because of unstable conditions in the countrv. Therefore, some issues pertaining to the stability and sustainability of the te~Iiiiol6~~ could not be addressed. Howe\,er, the fact that overall cropping intensities \{,ere high, which ensured high f:lrni incomes, indicates a certain degree of stability o\.er time. The an;llysis of production functions for the crops suffered from niulticolline:~rity. Therefore, input use per hectare had to be used in some cases as a proxy for the theoretically perfect ir:put [Ice per far~ii. This restricted the analysis to structural changes, but the cstirn;~tt.d coefficients could not be interpreted as production elr~sticities of inputs, and the :lnalysis could not be extended to determine returns to scale and factor shares. Therefore, the study of factor and income shares was limited to an accounting analysis at the average level. A more detailed analysis for above-average, average, and below-average farmers would have been preferable, but could not be conducted bec:luse the samples were limited to 19 adopters and 18 nonadopters.
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IRRl DISCUSSION PAPER SERIES NO. 15
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RECEIVED I RECU .- r b :'.i!~atlon
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Welcome address S .P.R. Weerasinghe
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Welcome Address S. P. R. Weerasingh
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Opening Comments After 15 yr of far
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increased as well, but only nlargin
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esult in high incomes for farmers,
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Investor concerns Usually investors
Page 17 and 18:
WORKSHOP OBJECTIVES This workshop i
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Rice is the major food crop and die
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esource use and productivity varies
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Determination of ado,)tion factors
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number of active family members per
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At both sites, more than 73% of the
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Hossain A M, Nur-E-Elahi, Nazrul I
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Table 2. Crop varietal sequence sco
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Table 4. Correlation illatsix used
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- Table 6. Socioeconomic characteri
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Table 8. Extent of adoption and ave
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Table 10. Resource use and producti
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Table 12. Extent of adoption and di
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Table 14. Summary of per hectare ca
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IRlPACT OF FARMING SYSTEMS RESEARCH
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new information collected during FS
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average family owns seven heads of
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H Horticulture. To have a more regu
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improved varieties require higher l
Page 55 and 56:
The types of the training provided
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extension agency in the district, t
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m Extension and other production-su
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Table 3. Farm characteristics of th
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Table 6. Farm practices and product
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Table 8. Major crops, crop varietie
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Table 10. Production and use of mil
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Table 13. Major problems and constr
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Table 15. Training undergone by the
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Table 17. Links between farmers and
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----l CROP SUBSYSlLM rnurt L OTT tb
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West Java provincial le~el BACKGROU
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OBJECTIVES The specific objectives
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Labor requirement Labor requirement
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system models. This indicated that
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Unit prices for all items were obta
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Price elasticity. The demand for al
Page 89 and 90:
district fishery extension services
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Table 2. Production of freshwater f
Page 93 and 94:
Table 4. Level of inputs used in ea
Page 95 and 96:
Table 6. Labor requirement for each
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able 8. Income analysis of each FS
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Table 10. Nonfood expenditure patte
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Table 12. The value of assets (IRP
Page 103 and 104:
Table 15. Nonfood expenditure patte
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Table 17. Elasticities of food comm
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l Oct k Jan Feb Mar Apr May Jun Jul
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From 1980 to 1986, the Integrated R
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THE 1'\VO ;MATURE TECHNOLOGIES Dire
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Conceptual framework STUDY METHODS
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Tai. Mungbean was introduced in Dok
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Land preparation for rice. The reac
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price of mungbean was high, some fa
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manufacturers. The earlier models (
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Net farm income per household The a
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that although adopters were better
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W It produced a good stand of rice
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Table l. The promising technologies
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Table 3. Mungbean before rice areas
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Table 5. Number of farm households
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Table 7. Area planted to mungbean,
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Table 9. Area planted to mungbean,
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Table 11. Area under dry seeded ric
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continued.. . Table 12. Socioeconom
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continued.. . Table 12. Socioeconom
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l~ndicative figures only. '~ature t
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composition, increases in income ca
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not be captured if the criteria for
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crops (rice, maize, and mungbean) a
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The explanatory Lwiable, nitrogen (
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of the ratio of actual intake and r
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Farming Systems Research and Extens
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Table 3. Input levels and productiv
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Table 5. Comparison of annual house
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Table 7. Comparison of annual nonfo
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Table 9. Comparison of percentage p
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Table 11. Log-linear models of impa
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INSTITUTIONALIZING THE FARILIIIVG S
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agricultural production system by i
Page 173 and 174: In the midwest plain, where there a
Page 175 and 176: Varietal irnprovernent. This compon
Page 177 and 178: solutions to problems under the bas
Page 179 and 180: Table 2. Rice farming systems in Ca
Page 181 and 182: Table 5. Component-technology studi
Page 183 and 184: Wangwacharachul (1984) examined the
Page 185 and 186: household basis on an income and ex
Page 187 and 188: first crop. In 1989-90, the adopter
Page 189 and 190: Nonfarm expenses constituted the bu
Page 191 and 192: Herbicide is essential for DSR. How
Page 193 and 194: o The classification of farmers on
Page 195 and 196: Table 1. List of \,ariables idc~l~l
Page 197 and 198: Table 3. Conlparison of cash flow o
Page 199 and 200: Table 5. Level of input use for the
Page 201 and 202: Table 7. Production elasticities of
Page 203 and 204: FROXl GREEN REVOLUTION TO FARhlING
Page 205 and 206: ainfed areas. The RIARS project app
Page 207 and 208: stability and sustainability. 1nsti
Page 209 and 210: o Limited feedback at all levels. A
Page 211 and 212: Table l. Chronological sequcnce of
Page 213 and 214: Table l. Chronological sequence of
Page 215 and 216: Impact studies A number of studies
Page 217 and 218: some simple statistical tests to as
Page 219 and 220: assets). Patterns of food consumpti
Page 221 and 222: Production functions for first-seas
Page 223: and nonadopters indicate that there
Page 227 and 228: variety, inadequate attention was p
Page 229 and 230: Table 1. Farming system research si
Page 231 and 232: Table 4. Comparison of levels of in
Page 233 and 234: Table-6. Compariso~i of le\.els of
Page 235 and 236: Table 9. Estimated production funct
Page 237 and 238: Table 11. Factor shares of first-se
Page 239 and 240: Table 13. Factor slirlres of third-
Page 241 and 242: Table 15. Endownlent of farm assets
Page 243 and 244: IAIPACT ASSESShlEhT OF FARMING SYST
Page 245 and 246: Depending on the adequacy of rainfa
Page 247 and 248: Demograpllic cllaractehtics. The co
Page 249 and 250: The major farm implements owned by
Page 251 and 252: Effect of RWCS on household cash fl
Page 253 and 254: Table 1. Average cash expenses per
Page 255 and 256: Table 5. Selected clia~~acteristics
Page 257 and 258: Table 7. Comparative pcrforinance o
Page 259 and 260: hiem bers Discussion and Recommenda
Page 261 and 262: Guideline 4: FSR impact projects sh
Page 263 and 264: hlem bers o The need to improve doc
Page 265 and 266: Members what is right depends on po
Page 267 and 268: Decentralization and farming system
Page 269 and 270: o More program and less project fun
Page 271 and 272: Bangladesh Mr. RaGqul Islam Banglad
Page 273 and 274: Dr. N.F.C. Ranawecru Di\ision of .-
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CFTSSF CLSU CSD CSSAC CVIADP CVRP-I
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PIADP PCA PCARRD PHARLAP PSC PTA RA
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Production Team Editor : Michael Gr
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