$title North-East Brazil Regional Agricultural Model (NEBRAZIL,SEQ=87) $onText This model was used to study the root causes of stagnation and poverty in the rural economy of the northeast of Brazil. It was used to quantify the effects of policy and project intervention. Kutcher, G P, and Scandizzo, P L, The Agricultural Economy of Northeast Brazil. The Johns Hopkins University Press, Baltimore and London, 1981. Keywords: linear programming, agricultural economics, policy analysis, land reform, economic development $offText $sTitle Set Definitions Set zz 'zones' / west, sertao, southeast, east, agreste / z(zz) 'zone of choice for submodel solution' zr(zz) 'zone with rotation restrictions' / sertao, west / zrc(zz) 'zones for which rotation constraint is binding' / west, sertao / f 'farm types' / fam-farm 'family farms 10-30 ha' med-farm 'medium-size farms 500-100 ha' ls-fazenda 'livestock fazenda gt 500 ha' fazenda 'sharecropping and livestock gt 500 ha' cocoa-plan 'cocoa plantation southeast only' sugar-plan 'sugar-cane plantation east only' dv-fazenda 'diversified fazenda no sharecropping' / c 'crops' / cotton-m 'cotton-moco' cotton-h 'cotton-herbaceo' cotton-v 'cotton-verdao' rice 'rice' banana 'banana' sweet-pot 'sweet-potatoe' babacu 'babacu' cacao 'cacao' cashew-nut 'cashew-nut' sugar-cane 'sugar-cane' carnauba 'carnauba' coconut 'coconut' beans-arr 'beans-de-arranca' beans-cor 'beans-de-corda' oranges 'oranges' manioc 'manioc' corn 'corn' castor-oil 'castor-oil' sisal 'sisal' other 'other crops' / *why don't we have oranges and cacao as long cycle also? cl(c) 'long cycle crops' / cotton-h , babacu , cacao cashew-nut, carnauba , coconut oranges , castor-oil, sisal / ca(c) 'annual crops' cex(c) 'export crops' / cotton-m, cotton-h , cotton-v babacu , cacao , cashew-nut carnauba, castor-oil, sisal / ct(c) 'regionally traded commodities' / rice / tm 'months' / jan, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec / p 'cropping activities' / crop-01 'cotton-moco' crop-02 'cotton-herbaceo' crop-03 'cotton-verdao' crop-04 'rice' crop-05 'banana' crop-06 'sweet potatoes' crop-07 'babacu' crop-08 'cacao' crop-09 'cashew nuts' crop-10 'sugar cane' crop-11 'carnauba' crop-12 'coconut' crop-13 'beans-de-arranca' crop-14 'beans-de-corda' crop-15 'oranges' crop-16 'manioc' crop-17 'corn' crop-18 'castor oil' crop-19 'sisal' crop-20 'cotton-moco beans-de-corda corn' crop-21 'rice beans-de-corda corn' crop-22 'rice manioc corn' crop-23 'rice corn' crop-24 'beans-de-corda manioc corn' crop-25 'beans-de-corda corn' crop-26 'manioc corn' crop-27 'cotton-moco beans-de-corda' crop-28 'cotton-moco corn' crop-29 'cotton-herbaceo beans-de-arranca corn' crop-30 'cotton-herbaceo beans-de-corda corn' crop-31 'cotton-verdao beans-de-corda corn' crop-32 'cashew-nut manioc corn' crop-33 'beans-de-arranca corn' crop-34 'beans-de-arranca corn castor-oil' crop-35 'beans-de-corda corn castor-oil' crop-36 'beans-de-arranca manioc corn' crop-37 'banana coconut' / pl(p) 'long cycle crop activities' pa(p) 'annual crop activities' g 'demand segments' / seg1*seg11 / sd 'land quality' / good 'flat and near water or humid and low-lying' medium 'hilly or more arid than good land' pasture 'cultivated pasture or tree crops' fallow 'land' / s(sd) 'land used in model' / good, medium, pasture / sc(sd) 'crop lands' / good, medium / sl(sd) 'livestock feeding alternative land types' / medium, pasture / ty 'year' / 1960*1969 / st 'states' / rio-grande, paraiba, pernambuco ceara , piaui , maranhao alagoas , sergipe, bahia / r 'livestock feeding alternatives' / rec-1*rec-3 / dr 'family consumption bundle alternatives' / one, two, three / sh(zz,f) 'sharecropping possibilites' / sertao.(med-farm,fazenda) / km 'technology characteristics' / equipment, fertilizer, seeds, sprouts, itech /; z(zz) = yes; ca(c) = not cl(c); display cl; Alias (z,zp), (s,sp); Scalar dpm 'days per month' / 25 /; $sTitle Land Data Parameter pfm(s,p) 'pasture land available in fourth yr of crop-01' / pasture.crop-01 .25 /; Table landc(zz,sd,f) 'average farm land structure (ha)' fam-farm med-farm ls-fazenda fazenda cocoa-plan sugar-plan dv-fazenda west.good 2.700 15.610 49.777 west.medium 3.300 16.910 58.433 west.pasture 3.710 39.300 217.470 west.fallow 5.330 56.630 267.690 sertao.good 2.495 14.920 44.376 sertao.medium 2.495 22.380 72.404 sertao.pasture 3.530 31.510 143.240 sertao.fallow 5.610 63.880 282.540 southeast.good 7.970 18.472 283.887 163.696 southeast.medium 7.970 10.848 152.863 88.144 southeast.pasture 2.640 4.630 124.200 71.620 southeast.fallow 6.030 9.120 127.610 73.580 east.good 1.332 9.589 81.146 east.medium 2.368 11.721 91.505 east.pasture 1.670 13.790 157.750 east.fallow 2.580 15.160 222.180 agreste.good 1.615 9.004 94.048 agreste.medium 2.325 11.936 141.072 agreste.pasture 2.440 21.920 274.450 agreste.fallow 1.490 7.760 59.280; Table ldp(s,s) 'land downgrading possibilities' good medium good 1 medium -1 1 pasture -1; Table lcc(zz,s,c) 'long cycle crop land commitment (percentage)' babacu cacao cashew-nut carnauba coconut castor-oil sisal west.good 26.4 0.1 3.0 west.medium 14.0 0.1 6.9 sertao.good 0.5 1.5 0.7 0.9 sertao.medium 0.9 0.9 0.7 0.4 southeast.good 3.5 0.2 southeast.medium 3.5 0.8 east.good 6.9 east.medium 3.4 agreste.good 0.4 agreste.medium 2.5; Parameter lcct(zz,s) 'total long cycle crop land commitment (proportion)' lccp(s,f,zz,c) 'long cycle crop land limits (ha)'; lcct(zz,s) = sum(cl, lcc(zz,s,cl))/100; lccp(s,f,zz,cl) = landc(zz,s,f)*lcc(zz,s,cl)/100; display lcct, lccp; $sTitle Crop Data Table cropc(c,*) 'elasticities and expenditure data' expend engel * mill cr cotton-m 1120 .80 cotton-h 1120 .80 cotton-v 1120 .80 rice 4408 .54 banana 1179 .34 sweet-pot 1670 .50 babacu 2903 .10 cacao 85 .60 cashew-nut 2903 .75 sugar-cane 3222 .75 carnauba 1120 .80 coconut 1172 .49 beans-arr 472 .50 beans-cor 472 .50 oranges 1722 .7 manioc 1670 .27 corn 960 .25 castor-oil 1411 .65 sisal 1120 .80; Table qd(c,zz) 'reference demand 1978 (tons)' west sertao southeast east agreste cotton-m 59468 460880 cotton-h 108565 152341 cotton-v 146207 rice 274049 68147 22273 banana 1408 7012 450 5925 sweet-pot 8408 5817 babacu 621852 cacao 203098 cashew-nut 453 10549 sugar-cane 3014 21036 17482 carnauba 259045 577701 coconut 4010 1520 beans-arr 23070 32733 12 24021 beans-cor 16204 89212 35074 5513 oranges 10332 manioc 401564 974343 2358124 56913 258822 corn 166852 317932 115394 969 128891 castor-oil 21567 1861 sisal 103766; Table price0(c,zz) 'crop reference prices (cr per kg)' west Sertao southeast east agreste cotton-m 2.00 2.10 cotton-h 2.00 1.90 cotton-v 1.90 rice .52 1.50 1.50 banana 3.00 4.00 3.00 4.00 sweet-pot .24 .20 babacu 1.00 cacao 5.00 cashew-nut 1.00 1.00 sugar-cane 30. 38. 35. carnauba .80 .80 coconut .4 .4 beans-arr 2.60 2.50 2.20 2.50 beans-cor 1.50 1.60 1.80 1.50 oranges 10. manioc .22 .17 .17 .20 .17 corn .42 .53 .50 .51 .51 castor-oil 1.80 1.50 sisal 1.00; Scalar frisch 'coefficient' / -2 /; Parameter texp 'total expenditure (cr)' bs(c) 'expenditure budget share' eta(c) 'own price elasticities' price(c,zz) 'crop refenrence price (cr per ton)' td(c) 'total crop demand in base year (tons)' alpha(c,zz) 'demand curve intercept (cr per ton)' beta(c,zz) 'demand curve gradient (cr per ton2)' pmax(c,zz) 'maximum price (cr per ton)' pmin(c,zz) 'minimum price (cr per ton)' qmax(c,zz) 'maximum consumption (1000 tons)' qmin(c,zz) 'minimum consumption (1000 tons)' incr(c,zz) 'segment increment (1000 tons)' ws(c,zz,g) 'welfare segments (mill cr)' rs(c,zz,g) 'revenue segment definition (mill cr)' qs(c,zz,g) 'quantity segment definition (1000 tons)'; texp = sum(c, cropc(c,"expend")); bs(c) = cropc(c,"expend")/texp; eta(c) = -cropc(c,"engel")*(bs(c) - (1 - bs(c)*cropc(c,"engel"))/frisch); price(c,zz) = 1000*price0(c,zz); td(c) = sum(zz, qd(c,zz)); beta(c,zz)$(eta(c)*qd(c,zz)) = price(c,zz)/qd(c,zz)/eta(c); alpha(c,zz) = price(c,zz) - beta(c,zz)*qd(c,zz); pmax(c,zz) = 2*price(c,zz); pmin(c,zz) = .2*price(c,zz); qmin(c,zz)$beta(c,zz) = (pmax(c,zz) - alpha(c,zz))/beta(c,zz)/1000; qmax(c,zz)$beta(c,zz) = (pmin(c,zz) - alpha(c,zz))/beta(c,zz)/1000; incr(c,zz) = (qmax(c,zz) - qmin(c,zz))/(card(g) - 1); qs(c,zz,g) = qmin(c,zz) + incr(c,zz)*(ord(g) - 1); ws(c,zz,g) = alpha(c,zz)*qs(c,zz,g)/1000 + .5*beta(c,zz)*sqr(qs(c,zz,g)); rs(c,zz,g) = alpha(c,zz)*qs(c,zz,g)/1000 + beta(c,zz)*sqr(qs(c,zz,g)); display price, qd, eta, beta, alpha, pmax, pmin, qmax, qmin, qs, ws, rs; Table labor(p,zz,tm) 'monthly cropping labor requirements (man-days per ha)' jan feb mar apr may jun jul aug sep crop-01.west 2.93 4.11 4.62 3.28 1.64 2.06 5.60 5.14 3.00 crop-01.sertao 0.67 1.35 3.10 3.26 3.55 1.97 1.13 2.48 4.43 crop-02.sertao 2.99 2.84 5.18 4.81 6.57 8.54 7.25 7.55 5.87 crop-02.agreste 4.79 10.89 18.70 9.83 8.03 20.95 15.67 15.48 11.35 crop-03.sertao 4.43 4.81 5.92 6.87 4.46 2.72 2.47 3.76 3.64 crop-04.west 16.70 12.78 9.89 9.57 8.91 7.97 3.53 2.63 3.44 crop-04.sertao 13.35 11.69 11.64 9.09 11.12 10.91 5.87 3.10 3.46 crop-04.southeast 7.50 18.75 1.88 18.75 19.38 13.13 5.88 crop-05.west 10.79 3.92 5.36 4.03 6.63 7.00 7.31 3.07 2.71 crop-05.sertao 4.22 5.23 5.44 5.33 7.69 6.50 7.23 4.11 3.72 crop-05.east 10.76 10.48 3.52 7.46 4.50 12.00 10.12 3.76 9.17 crop-05.agreste 8.24 0.89 5.43 3.31 11.13 10.33 3.27 2.65 5.47 crop-06.sertao 2.61 3.55 5.59 2.29 9.37 8.50 9.00 4.22 10.79 crop-06.east 8.29 4.38 4.50 4.13 5.64 3.71 2.13 3.24 16.00 crop-07.west 1.05 0.94 0.89 0.71 0.42 0.53 1.03 1.25 4.10 crop-08.southeast 1.30 0.62 4.58 3.40 1.54 2.04 3.82 2.74 2.62 crop-09.west 0.95 0.45 2.10 0.38 1.23 2.39 0.15 1.57 0.96 crop-09.sertao 0.14 0.25 1.49 0.82 0.58 1.40 1.61 2.07 2.63 crop-10.sertao 3.11 5.52 8.19 8.28 2.92 6.67 2.21 5.50 9.51 crop-10.east 4.41 6.10 4.68 4.73 3.25 6.31 3.99 7.73 6.45 crop-10.agreste 5.78 3.37 4.03 7.09 4.64 5.91 7.67 9.23 5.93 crop-11.west 0.13 0.52 0.01 0.01 0.02 5.10 4.04 7.31 crop-11.sertao 0.10 0.12 0.01 0.31 1.39 2.04 crop-12.sertao 0.75 1.33 2.62 3.03 5.20 3.62 2.19 1.38 1.16 crop-12.east 4.03 1.63 3.03 2.83 2.34 2.18 2.69 2.06 3.50 crop-13.sertao 4.72 2.17 5.36 7.27 4.64 4.44 4.43 4.53 3.13 crop-13.east 16.67 19.33 5.67 19.42 5.80 9.50 10.33 6.67 3.17 crop-14.west 10.01 10.15 12.37 8.08 5.42 9.27 7.98 5.18 3.05 crop-14.sertao 4.06 4.06 8.19 7.52 4.13 4.19 2.27 5.22 2.32 crop-15.agreste 2.00 2.36 4.13 2.13 7.18 5.88 3.21 9.20 6.89 crop-16.west 5.89 5.66 6.46 2.96 2.40 1.97 3.72 6.04 5.54 crop-16.sertao 3.69 3.99 5.14 5.20 5.13 3.77 3.07 5.48 5.55 crop-16.southeast 5.52 3.30 3.88 2.47 3.87 5.06 5.57 5.54 5.81 crop-16.east 2.79 6.83 5.88 7.80 7.79 3.25 7.75 7.93 7.18 crop-16.agreste 5.71 7.60 7.28 8.15 8.48 10.71 9.34 12.76 8.93 crop-17.west 5.05 6.04 3.71 2.03 1.46 2.00 2.73 1.70 3.95 crop-17.sertao 4.60 4.80 7.75 7.35 1.27 3.83 5.42 6.20 1.64 crop-17.agreste 9.19 14.42 10.59 12.01 3.47 10.75 5.88 7.30 4.14 crop-18.sertao 6.00 6.35 6.76 2.14 6.35 7.20 1.23 6.77 8.76 crop-19.agreste 1.22 1.11 0.56 0.78 1.19 0.44 1.89 3.04 2.93 crop-20.west 9.08 11.11 6.28 3.04 3.15 6.60 5.86 6.29 5.33 crop-20.sertao 7.94 6.48 7.92 6.35 5.36 4.08 2.36 4.12 4.77 crop-21.west 12.07 13.15 7.62 6.38 10.12 10.47 9.18 12.05 5.11 crop-22.west 13.99 12.91 9.40 7.29 11.82 12.71 6.48 7.56 6.16 crop-23.west 13.46 14.66 9.24 7.45 12.29 8.73 4.71 6.40 6.72 crop-24.west 13.47 12.11 8.88 7.47 4.45 4.32 3.24 6.61 6.81 crop-24.sertao 7.41 11.11 9.84 7.79 7.93 6.05 5.21 4.94 3.05 crop-25.west 16.14 11.94 8.54 2.91 4.69 6.07 5.96 4.35 5.45 crop-25.sertao 7.96 10.08 12.01 8.10 6.49 4.91 2.99 2.40 3.18 crop-25.southeast 21.67 3.65 6.55 2.36 1.98 3.62 4.15 8.33 2.92 crop-25.agreste 12.46 11.35 24.38 22.03 16.91 9.47 10.97 9.70 4.93 crop-26.west 22.99 11.34 7.40 4.03 3.79 9.17 6.06 2.37 18.73 crop-27.sertao 7.48 3.55 5.95 5.92 5.72 4.09 4.85 3.67 5.10 crop-28.sertao 8.10 5.21 12.49 8.77 5.83 3.80 2.21 5.09 5.34 crop-29.sertao 4.31 5.95 4.62 8.79 9.48 8.04 4.57 4.89 4.33 crop-29.agreste 5.54 10.30 9.24 8.97 15.82 13.00 14.74 10.64 5.64 crop-30.sertao 17.99 12.30 12.45 10.45 11.70 8.54 7.02 8.11 6.15 crop-30.agreste 9.18 3.94 16.15 23.69 28.12 20.58 17.73 15.06 4.58 crop-31.sertao 9.30 8.53 9.42 5.91 4.57 4.06 4.19 5.04 7.20 crop-32.sertao 3.78 9.07 3.68 6.42 3.63 8.67 3.42 2.88 2.35 crop-33.sertao 3.34 3.20 5.34 6.45 5.92 6.77 3.89 5.87 5.72 crop-33.southeast 4.19 8.81 5.30 4.67 5.12 6.86 0.55 4.84 8.19 crop-33.east 9.19 6.30 11.96 26.07 25.52 25.74 21.85 19.72 9.59 crop-33.agreste 6.87 10.19 10.61 9.14 18.38 11.50 9.22 13.36 3.85 crop-34.sertao 2.16 8.62 6.18 9.21 6.37 11.72 6.36 8.11 9.63 crop-34.southeast 4.74 0.88 0.59 7.79 3.79 7.12 5.26 4.98 12.03 crop-35.sertao 10.13 13.75 11.40 12.42 8.62 8.08 5.43 5.26 3.75 crop-36.southeast 4.51 9.52 13.22 5.36 4.35 3.66 7.33 4.13 9.80 crop-36.agreste 7.44 10.21 9.63 16.18 20.11 16.86 14.86 14.00 8.04 crop-37.east 3.17 6.40 1.19 2.59 4.31 1.17 8.43 7.79 4.59 + oct nov dec crop-01.west 1.81 2.65 1.96 crop-01.sertao 3.73 1.52 0.50 crop-02.sertao 4.67 4.69 2.50 crop-02.agreste 8.38 8.23 4.54 crop-03.sertao 3.35 2.14 1.41 crop-04.west 3.29 5.58 8.27 crop-04.sertao 2.20 4.07 2.80 crop-04.southeast 16.38 8.50 11.13 crop-05.west 3.84 1.62 1.77 crop-05.sertao 3.44 3.64 2.40 crop-05.east 7.00 11.71 4.81 crop-05.agreste 3.67 3.18 1.44 crop-06.sertao 5.79 2.55 4.61 crop-06.east 2.38 5.27 15.49 crop-07.west 3.81 1.89 3.50 crop-08.southeast 3.37 4.44 3.95 crop-09.west 0.72 2.48 1.19 crop-09.sertao 3.68 2.69 1.03 crop-10.sertao 12.68 6.79 4.74 crop-10.east 8.38 7.41 6.56 crop-10.agreste 9.05 7.59 6.37 crop-11.west 9.85 8.69 9.90 crop-11.sertao 0.96 5.44 0.48 crop-12.sertao 2.54 1.95 1.41 crop-12.east 3.05 1.64 1.49 crop-13.sertao 0.38 0.64 0.51 crop-13.east 7.50 5.00 1.25 crop-14.west 3.08 4.50 3.53 crop-14.sertao 1.64 2.46 1.71 crop-15.agreste 3.30 9.70 8.87 crop-16.west 4.77 3.45 3.18 crop-16.sertao 3.93 2.88 2.95 crop-16.southeast 5.98 7.96 10.32 crop-16.east 5.78 6.56 7.65 crop-16.agreste 10.22 6.18 8.34 crop-17.west 2.77 6.37 5.98 crop-17.sertao 3.38 0.52 1.09 crop-17.agreste 4.25 3.49 2.11 crop-18.sertao 10.82 1.68 2.73 crop-19.agreste 4.99 7.73 9.44 crop-20.west 4.77 4.00 6.67 crop-20.sertao 3.89 2.94 1.63 crop-21.west 6.37 6.01 8.96 crop-22.west 4.31 4.72 4.99 crop-23.west 6.37 5.89 7.97 crop-24.west 6.97 7.24 6.42 crop-24.sertao 1.88 1.08 0.74 crop-25.west 6.45 9.03 9.11 crop-25.sertao 1.70 1.78 1.78 crop-25.southeast 8.47 8.94 21.62 crop-25.agreste 6.41 0.53 0.89 crop-26.west 10.39 10.83 7.32 crop-27.sertao 3.28 0.76 0.68 crop-28.sertao 3.52 2.26 0.30 crop-29.sertao 3.53 2.54 1.04 crop-29.agreste 4.90 4.73 4.92 crop-30.sertao 2.99 1.34 1.20 crop-30.agreste 9.76 7.39 2.67 crop-31.sertao 6.02 1.55 1.23 crop-32.sertao 4.25 2.78 crop-33.sertao 3.09 1.74 2.50 crop-33.southeast 5.03 6.92 3.71 crop-33.east 3.63 4.00 4.43 crop-33.agreste 3.87 2.65 1.09 crop-34.sertao 12.46 5.04 2.15 crop-34.southeast 9.17 9.73 15.56 crop-35.sertao 4.41 6.05 4.76 crop-36.southeast 2.73 6.43 3.73 crop-36.agreste 6.69 5.49 5.26 crop-37.east 5.86 5.07 5.05; $sTitle Livestock Data Parameter lpasm(tm) 'labor requirements:pasture maintenance (man-days per ha)' / jan 3, feb 2, (nov,dec) 5 / pricel(zz) 'livestock price (cr per head)' / west 103, sertao 186, southeast 108, east 310, agreste 211 / llive(r,tm,zz) 'labor requirements: livestock (man-days per head)' Scalar lpas 'labor for pasture maintenance (man-month per head???)' / .04 / vetpr 'livestock vetinary cost (cr per head)' / 1 /; Table lland(s,r,zz) 'livestock feeding alternative components (ha per head)' west sertao southeast east agreste medium.rec-1 1.186 1.005 1.274 .795 1.407 medium.rec-2 .449 .205 .507 .269 .611 medium.rec-3 .508 .267 .449 .366 .631 pasture.rec-1 .756 .617 .422 .464 .209 pasture.rec-2 3.310 6.100 1.383 2.051 2.030 pasture.rec-3 1.417 1.623 .487 .943 .910; Table lfrat(r,zz) 'purchased rations for lvstk feed recipes' west sertao southeast east agreste rec-1 1.729 6.179 2.839 8.596 5.141 rec-2 2.863 12.444 3.701 12.876 21.646 rec-3 7.567 61.068 9.304 37.974 49.845; llive(r,tm,zz) = lpas + lland("pasture",r,zz)*lpasm(tm); display llive; $sTitle Farm Data Table fnum0(zz,f) 'number of farms' fam-farm med-farm ls-fazenda fazenda cocoa-plan sugar-plan dv-fazenda west 37001 113651 14569 sertao 62599 252912 11221 southeast 26824 76574 4766 5208 east 11964 17623 1314 agreste 69580 68545 5168; Table famsize(zz,f) 'family sizes (adult worker equivalents)' fam-farm med-farm ls-fazenda fazenda cocoa-plan sugar-plan dv-fazenda west 1.930 1.870 1.750 sertao 2.220 2.610 2.490 southeast 1.970 1.420 1.220 1.220 east 1.790 1.660 1.140 agreste 2.680 2.820 1.770; Parameter spr(c) 'propreitor s share of cropper production (proportion)' / (cotton-m,cotton-h,cotton-v,rice) .5 (sweet-pot,beans-arr,beans-cor,manioc,corn) .3 / fnum(zz,f) 'number of farms (1000s)'; fnum(zz,f) = fnum0(zz,f)/1000; $sTitle Yield Data: Survey Parameter yield(c,p,s,zz) 'yield estimates (tons per ha)'; Table yield0(c,p,s,zz) 'stratified yield estimates (kg per ha)' *xcept sugar-cane: tons per ha oranges: hundreds of fruits good.west good.sertao good.southeast good.east good.agreste medium.west medium.sertao cotton-m.crop-01 174 171 139 146 cotton-m.crop-20 119 160 108 157 cotton-m.crop-27 153 153 cotton-m.crop-28 297 264 cotton-h.crop-02 552 848 552 cotton-h.crop-29 120 269 167 cotton-h.crop-30 227 403 cotton-v.crop-03 380 266 cotton-v.crop-31 331 181 rice.crop-04 1176 1245 770 985 1283 rice.crop-21 997 721 rice.crop-22 840 797 rice.crop-23 1196 1098 banana.crop-05 351 184 221 147 83 banana.crop-37 57 sweet-pot.crop-06 4446 2896 babacu.crop-07 722 306 cacao.crop-08 898 cashew-nut.crop-09 223 195 55 126 cashew-nut.crop-32 149 10 sugar-cane.crop-10 20 48 45 10 carnauba.crop-11 1069 3336 876 6247 coconut.crop-12 12 50 118 coconut.crop-37 16 beans-arr.crop-13 454 216 beans-arr.crop-29 193 285 174 beans-arr.crop-33 292 284 329 274 171 beans-arr.crop-34 188 275 beans-arr.crop-36 305 288 beans-cor.crop-14 437 386 386 224 beans-cor.crop-20 250 124 101 142 beans-cor.crop-21 89 28 beans-cor.crop-24 109 93 90 60 beans-cor.crop-25 207 194 170 251 203 226 beans-cor.crop-27 90 173 beans-cor.crop-30 77 115 beans-cor.crop-31 180 171 beans-cor.crop-35 227 147 beans-cor.crop-36 oranges.crop-15 92 manioc.crop-16 4853 4766 6891 3795 4456 4283 4005 manioc.crop-22 2262 1072 manioc.crop-24 994 3714 1963 3060 manioc.crop-26 1124 manioc.crop-32 4334 1928 manioc.crop-36 3361 3408 corn.crop-17 399 583 725 1137 corn.crop-20 399 286 183 266 corn.crop-21 298 255 corn.crop-22 311 225 corn.crop-23 395 303 corn.crop-24 329 239 313 60 corn.crop-25 493 407 318 373 397 290 corn.crop-26 287 corn.crop-28 484 489 corn.crop-29 485 536 237 corn.crop-30 463 361 corn.crop-31 287 202 corn.crop-32 264 250 corn.crop-33 297 490 369 594 304 corn.crop-34 386 255 corn.crop-35 296 302 corn.crop-36 230 503 castor-oil.crop-18 336 324 castor-oil.crop-34 291 264 castor-oil.crop-35 315 148 sisal.crop-19 2244 + medium.southeast medium.east medium.agreste cotton-h.crop-02 569 cotton-h.crop-29 149 cotton-h.crop-30 133 banana.crop-05 803 174 banana.crop-37 39 cacao.crop-08 616 sugar-cane.crop-10 42 30 coconut.crop-12 25 coconut.crop-37 18 beans-arr.crop-13 165 beans-arr.crop-29 221 beans-arr.crop-33 152 260 beans-arr.crop-34 61 beans-arr.crop-36 72 287 beans-cor.crop-25 178 211 beans-cor.crop-30 352 manioc.crop-16 4584 5822 3964 manioc.crop-36 3083 1031 corn.crop-17 563 corn.crop-25 278 264 corn.crop-29 544 corn.crop-30 212 corn.crop-33 477 442 corn.crop-34 74 corn.crop-36 147 328 castor-oil.crop-34 128 sisal.crop-19 1666; yield(c,p,s,zz) = yield0(c,p,s,zz)/1000; Set xposs(s,zz,p) 'cropping possibilities' fposs(f,zz) 'farm type possibilites' cpossn(c,zz) 'commodity consumption possibilities' cposs(c,f,zz) 'commodity farm possibilites' cpossp(c,zz) 'commodity production possibilities' cpl(c,p) 'long cycle crop-cropping activities' lposs(s,zz,c,p) 'long cycle cropping activites'; xposs(s,zz,p) = yes$sum(c, yield(c,p,s,zz)); fposs(f,zz) = yes$sum(s, landc(zz,s,f)); cpossn(c,zz) = yes$qd(c,zz); cpossp(c,zz) = yes$sum((p,s), yield(c,p,s,zz)); cposs(c,f,zz) = yes$(cpossp(c,zz)*fposs(f,zz)); cpl(cl,p) = yes$sum((s,zz)$lcc(zz,s,cl), yield(cl,p,s,zz)); pl(p) = sum(cl,cpl(cl,p)); pa(p) = not pl(p); lposs(s,zz,cl,pl) = yes$(xposs(s,zz,pl)*cpl(cl,pl)); display xposs, fposs, cpossn, cposs, cpossp, pl, pa, cpl, lposs; $sTitle Revenue Data: Risk Table weightsz(st,zz) 'weights-states to zones (farmed land ha)' west sertao southeast east agreste rio-grande 3295774 471259 897568 paraiba 3492833 340369 1149786 pernambuco 3433932 999385 1995194 ceara 12467943 piaui 13114766 maranhao 23271544 alagoas 195356 1050967 929588 sergipe 371134 1683415 bahia 7306239 8110834 12610111 ; Table crev(st,c,ty) 'crop revenue series by state (cr per ha)' 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 rio-grande.cotton-m 434 453 491 438 508 506 350 513 463 444 rio-grande.rice 610 649 1066 1105 834 953 726 945 838 644 rio-grande.banana 7205 9081 10732 9164 11311 11415 8231 10772 9093 9579 rio-grande.cashew-nut 1681 2105 2008 1425 1688 1107 1134 1328 1244 2890 rio-grande.sugar-cane 2189 2505 2551 2766 2415 2507 1868 2395 2203 2801 rio-grande.beans-cor 445 460 951 552 321 495 607 399 411 483 rio-grande.manioc 590 716 1139 799 712 684 946 1222 920 757 rio-grande.corn 226 286 400 300 218 248 273 336 293 270 paraiba.cotton-m 1710 1795 3117 1555 2140 1900 1609 2077 2121 2043 paraiba.rice 786 818 1235 1094 649 1347 925 1143 1191 916 paraiba.banana 9841 15642 14831 12811 11072 9423 7071 10016 9101 8284 paraiba.cashew-nut 1694 1787 2860 1964 1205 1432 1834 1894 2076 2024 paraiba.sugar-cane 2194 2351 2451 2374 2623 2606 1799 2679 2580 2083 paraiba.beans-cor 508 529 1019 644 405 694 517 582 444 555 paraiba.manioc 1175 1734 2050 1728 1702 1689 1494 1733 1260 1417 paraiba.corn 373 414 622 429 372 523 383 361 318 353 pernambuco.cotton-m 517 538 433 378 442 529 402 523 539 448 pernambuco.rice 1327 967 1500 1554 1256 1161 1205 1534 1347 1294 pernambuco.banana 5315 6024 7735 8330 6463 5944 5790 6074 6426 6828 pernambuco.cashew-nut 2873 2750 2362 3047 2538 2331 1989 2730 3540 2429 pernambuco.sugar-cane 1668 1873 1707 2513 2389 2119 1206 1835 1942 2009 pernambuco.beans-cor 602 599 995 612 451 718 558 576 544 866 pernambuco.manioc 939 1695 2458 1250 873 1132 1282 1543 1410 1628 pernambuco.corn 251 388 553 354 362 400 324 364 323 412 ceara.cotton-m 587 610 679 483 591 521 379 550 651 669 ceara.rice 1034 1231 1613 1283 1199 1116 1190 1497 1281 1138 ceara.banana 5590 5798 7239 6118 6071 5249 4528 6096 5744 6888 ceara.cashew-nut 1131 1239 1042 810 603 490 376 548 1502 1359 ceara.sugar-cane 1365 1480 1386 1254 1214 1039 1112 1569 1477 1334 ceara.beans-cor 387 358 780 479 289 599 510 479 454 453 ceara.manioc 878 1017 1862 1325 1077 972 950 1093 1255 1294 ceara.corn 261 338 536 375 349 361 310 344 332 340 piaui.cotton-m 337 476 717 369 715 521 280 490 543 462 piaui.rice 493 620 909 813 578 530 554 771 721 608 piaui.banana 7319 7178 7077 6885 7607 8598 7379 8041 6589 6967 piaui.cashew-nut 425 461 628 449 336 476 478 574 427 456 piaui.sugar-cane 650 798 1347 996 835 1163 692 873 892 905 piaui.beans-cor 431 593 863 435 257 510 398 463 397 423 piaui.manioc 719 724 758 657 852 402 587 820 856 655 piaui.corn 232 288 364 300 278 354 269 297 279 278 maranhao.cotton-m 219 317 423 313 387 319 232 278 317 335 maranhao.rice 464 565 1011 765 502 448 554 585 622 521 maranhao.banana 4983 5012 5597 4579 3947 3616 3623 4154 4364 6645 maranhao.cashew-nut 1645 1398 1386 1107 1050 796 2654 2455 1430 539 maranhao.sugar-cane 1080 801 857 871 731 787 895 1164 1386 1400 maranhao.beans-cor 661 665 759 591 496 632 770 716 597 663 maranhao.manioc 515 561 576 549 483 496 539 543 573 526 maranhao.corn 216 231 328 248 306 295 237 279 280 293 alagoas.cotton-m 517 607 540 340 394 524 392 539 533 544 alagoas.rice 884 859 2370 1978 901 734 1150 1079 1202 1079 alagoas.banana 5248 6896 8143 7919 8080 6911 4700 3743 7455 8678 alagoas.cashew-nut 2366 2075 2170 1826 1799 1822 1821 2096 3044 2778 alagoas.sugar-cane 1921 1908 1884 2536 2718 2181 1945 1937 1972 2098 alagoas.beans-cor 784 863 1230 663 576 727 681 446 442 1105 alagoas.manioc 1030 1609 1898 1254 976 1022 1028 1371 1342 1522 alagoas.corn 204 397 532 238 273 248 243 262 211 301 sergipe.cotton-m 365 487 652 429 526 415 332 451 507 506 sergipe.rice 1325 1950 3802 2530 1941 1479 1642 1995 1659 1734 sergipe.banana 5537 5920 6915 6045 5866 5194 4742 4791 5753 7356 sergipe.cashew-nut 2038 2215 2744 2788 1503 2388 1911 2436 1997 2572 sergipe.sugar-cane 888 1292 1405 1343 1545 1338 1200 1171 1189 1169 sergipe.beans-cor 427 518 1253 748 557 463 677 507 642 778 sergipe.manioc 1100 1637 4539 2701 1416 2033 1753 2309 2405 2105 sergipe.corn 272 381 562 297 316 287 301 270 291 342 bahia.cotton-m 591 587 582 440 512 535 543 541 658 644 bahia.rice 1382 1213 1256 1280 1015 979 1463 2109 1161 892 bahia.banana 5169 5454 5789 5027 4793 4354 4451 4888 4637 5159 bahia.cacao 1643 1487 1221 1032 1018 812 774 861 1145 2218 bahia.cashew-nut 2146 2717 3167 2350 1214 1709 1664 2504 2647 2742 bahia.sugar-cane 1825 1745 1505 1676 1580 2141 1663 1710 1728 1666 bahia.beans-cor 1091 900 1522 878 631 879 1206 1000 882 1268 bahia.manioc 1106 1465 1595 1139 926 897 1198 1377 1297 1341 bahia.corn 351 343 587 332 260 283 392 404 319 358 bahia.other 722 636 562 426 592 514 378 378 612 822; Table phi(zz,f) 'risk factors' fam-farm med-farm ls-fazenda fazenda west 2.000 1.500 1.000 sertao 2.000 1.500 1.000; Parameter revz(c,ty,zz) 'crop revenue series by zone (cr per ha)' revm(c,zz) 'mean zone revenue for crops (cr per ha)' prdev(c,ty,zz) 'propreitor crop price deviations (cr per ton)'; revz(c,ty,zz) = sum(st, weightsz(st,zz)*crev(st,c,ty))/sum(st, weightsz(st,zz)); revm(c,zz) = sum(ty, revz(c,ty,zz))/card(ty); prdev(c,ty,zz)$revm(c,zz) = price(c,zz)*(revz(c,ty,zz)/revm(c,zz) - 1); display spr, crev, revz, revm, prdev; $sTitle Misc Data Table teche(p,zz,km) 'cropping technology costs (cr per ha)' equipment fertilizer seeds sprouts crop-01.west 26 24 crop-01.sertao 3 crop-02.sertao 23 28 84 crop-02.agreste 31 91 crop-03.sertao 12 7 16 crop-04.west 32 21 crop-04.sertao 12 2 6 crop-04.southeast 50 crop-05.west 1 69 crop-05.sertao 1 53 crop-05.east 18 2 164 crop-05.agreste 45 crop-06.sertao 4 284 crop-06.east 5 425 crop-08.southeast 123 9 1 crop-10.sertao 15 crop-10.east 231 crop-10.agreste 36 crop-12.sertao 37 crop-12.east 19 31 crop-13.sertao 2 72 crop-13.east 68 crop-14.west 56 6 crop-14.sertao 13 6 45 1 crop-15.agreste 106 1 184 crop-16.west 1 crop-16.east 2 7 crop-16.agreste 20 crop-17.west 6 crop-17.sertao 8 crop-17.agreste 42 55 crop-20.sertao 4 18 2 crop-21.west 5 crop-22.west 7 8 crop-23.west 17 crop-24.west 5 crop-25.west 64 crop-25.sertao 20 4 10 crop-26.west 6 crop-27.sertao 15 37 crop-28.sertao 33 crop-29.sertao 106 3 60 crop-29.agreste 4 22 19 crop-30.sertao 104 crop-30.agreste 27 crop-31.sertao 26 23 crop-32.sertao 20 crop-33.sertao 39 4 crop-33.southeast 9 crop-33.east 117 crop-33.agreste 11 42 crop-34.sertao 12 crop-35.sertao 8 crop-36.southeast 34 crop-36.agreste 98 6 1; $sTitle Consumption Data Table cbndl(c,zz,dr) 'consumption bundle alternatives (tons per family)' one two three rice.west .313 .145 .158 beans-arr.sertao .166 .057 .059 beans-arr.southeast .159 .067 .065 beans-arr.east .173 .090 .094 beans-arr.agreste .225 .152 .150 beans-cor.west .143 .269 .156 beans-cor.sertao .188 .294 .183 beans-cor.southeast .051 .141 .051 manioc.southeast 1.280 1.320 3.160 manioc.east 1.385 3.045 1.465 manioc.agreste .965 2.640 .935 corn.west .165 .165 .576 corn.sertao .232 .224 .660 corn.east .155 .155 .455 corn.agreste .235 .232 .581; $sTitle Regional Data Scalar mktmarg 'marketing margin of sales retained by propreitor' / .25 / fwage 'family wages (cr per man-month)' / 75 / sfs 'sharecropper family size' / 2.2 /; Parameter rlabsup(zz) 'regional labor supply (1000 workers)' / west 947.7 sertao 1481.2 southeast 811.6 east 158.4 agreste 612.6 / twage(zz) 'temporary worker wage (cr pe man-month)' / (west,sertao) 200 (east,agreste) 250 southeast 225 / pwage(zz) 'permanent worker wage (cr per year)' / west 1492 sertao 1532 southeast 1825 east 2097 agreste 2054 / vsc(zz) 'value of on-farm consumption (cr)' / west 518 sertao 767 southeast 770 east 785 agreste 934 / sps(zz) 'sharecropper plot size (ha)' / west 12 sertao 7 / pcost(p,zz) 'cropping activity cost (cr per ha)'; pwage(zz) = pwage(zz)*0.9 ; pcost(p,zz) = sum(km, teche(p,zz,km)); display pcost; Set cd1 'error possibly in crop comm and zone data' cd2 'error in crop comm' cd3 'error in labor for cropping' cd4 'error in long cycle comm' cd5 'error in cropping costs'; cd1(c) = yes$((sum(z, qd(c,z)) <> 0) and (cropc(c,"expend") = 0)); cd2(c,z) = yes$(qd(c,z) = 0 and price(c,z) <> 0); cd3(p,z) = yes$(sum(tm, labor(p,z,tm)) = 0 and sum((s,c,f), yield(c,p,s,z)) <> 0); cd5(p,z) = yes$(sum((km,tm), teche(p,z,km)) = 0 and sum((s,c,f), yield(c,p,s,z)) <> 0); display cd1, cd2, cd3, cd5; $sTitle Model Definition Variable xcrop(p,s,f,zz) 'cropping activities: total (1000 ha)' xcrops(p,s,f,zz) 'cropping activities: sharecropper (1000 ha)' xprodc(c,zz) 'crop production (1000 tons)' xlive(r,f,zz) 'livestock activity defined on feed techniques (1000 head)' xprodl(f,zz) 'livestock production (1000 head)' lswitch(s,f,zz) 'land downgrading (1000 ha)' consp(dr,f,zz) 'on-farm consumption: propreitor (1000 families)' conss(dr,f,zz) 'on-farm consumption: sharecropper (1000 families)' salesp(c,f,zz) 'crop sales: propreitor (1000 tons)' saless(c,f,zz) 'crop sales: sharecropper (1000 tons)' export(c,zz) 'crop exports (1000 tons)' regcon(c,zz) 'regional consumption (1000 tons)' regq(c,zz,g) 'regional consumption' flab(f,tm,zz) 'family labor (man-days)' tlab(f,tm,zz) 'temporary labor (man-days)' plab(f,zz) 'permanent labor (workers)' nsc(f,zz) 'number of sharecroppers (units)' rationr(f,zz) 'livestock ration requirements (mill cr)' pdev(f,zz,ty) 'positive price deviations (1000 cr)' ndev(f,zz,ty) 'negative price deviations (1000 cr)' cps 'consumer producer surplus (1000 cr)' adc(zz) 'area under the demand curve (mill cr)' revexp(zz) 'revenue from exports (mill cr)' revliv(zz) 'revenue from livestoick sales (mill cr)' vscdef(zz) 'value aof self-consumption (mill cr)' cropcost(f,zz) 'accounting: cropping activities cost (mill cr)' hlcost(f,zz) 'accounting: hired labor costs (mill cr)' rescost(f,zz) 'accounting: reservation labor costs (mill cr)' vetcost(f,zz) 'accounting: vetinary services cost (mill cr)'; Positive Variable xcrop, xcrops, xlive, xprodc, xprodl, lswitch, saless, salesp, export conss, consp, flab, tlab, plab, pdev, ndev, regcon, regq, nsc; Equation landb(s,f,zz) 'land balance (ha)' landl(s,f,zz,c) 'land balance: long cycle crops (ha)' dprodl(f,zz) 'livestock production definition' mbalcp(c,f,zz) 'material balance: propreitor (tons)( )' mbalcs(c,f,zz) 'material balance: sharecropper (tons)' spd(f,zz) 'sharecropper-plotsize definition (ha)' combp(f,zz) 'on farm consumption definition: propreitor (100l tons)' dem(c,zz) 'regional demand balance (1000 tons)( )' demreg(c,zz) 'regional demand definition (1000 tons)' combs(f,zz) 'on farm consumption definition: sharecropper (tons)( )' conv(c,zz) 'regional consumption convexity (1000 ons)( )' labcp(f,tm,zz) 'labor supply-demand relation ( )' labcs(f,tm,zz) 'labor supply-demand relation ( )' ratr(f,zz) 'ration requirements (mill cr)' labrc(tm,zz) 'regional labor constraint ( )' ddev(f,zz,ty) 'crop price deviation definition ( )' obj 'farm income definition ( )' aexp(zz) 'accounting: revenue from exports (mill cr)' aliv(zz) 'accounting: revenue from livestock sales (mill cr)' aadc(zz) 'accounting: area under demand curve ( )' avsc(zz) 'accounting: value of self-consumption ( )' acrop(f,zz) 'accounting: cropping cost definition ( )' ahlc(f,zz) 'accounting: hired labor cost (mill cr) ( )' ares(f,zz) 'accounting: reservation labor cost (mill cr) ( )' avet(f,zz) 'accounting: vetinary costs (mill cr)'; landb(s,f,z)$landc(z,s,f).. sum(pa$xposs(s,z,pa), xcrop(pa,s,f,z)) + sum(sp$landc(z,sp,f), ldp(s,sp)*lswitch(sp,f,z)) + sum(r, lland(s,r,z)*xlive(r,f,z)) =l= (1 - lcct(z,s))*fnum(z,f)*landc(z,s,f) + sum(pl$xposs(s,z,pl), pfm(s,pl)*xcrop(pl,s,f,z)); landl(s,f,z,cl)$landc(z,s,f).. sum(pl$lposs(s,z,cl,pl), xcrop(pl,s,f,z)) =l= fnum(z,f)*lccp(s,f,z,cl); *need to add ginning constraint for cottons mbalcp(c,f,z)$cposs(c,f,z).. sum((s,p), yield(c,p,s,z)*(xcrop(p,s,f,z) - (1-spr(c))*xcrops(p,s,f,z)$sh(z,f))) + mktmarg*saless(c,f,z)$sh(z,f) =g= salesp(c,f,z) + sum(dr, cbndl(c,z,dr)*consp(dr,f,z)); mbalcs(c,f,z)$(cposs(c,f,z)*sh(z,f)).. (1 - spr(c))*sum((s,p), yield(c,p,s,z)*xcrops(p,s,f,z)) =g= saless(c,f,z) + sum(dr, cbndl(c,z,dr)*conss(dr,f,z)); *dprodc(c,z)$cpossp(c,z).. xprodc(c,z) =e= sum((p,s,f), yield(c,p,s,z)*xcrop(p,s,f,z)); dprodl(f,z)$fposs(f,z).. xprodl(f,z) =e= sum(r, xlive(r,f,z)); ratr(f,z)$fposs(f,z).. rationr(f,z) =e= sum(r, lfrat(r,z)*xlive(r,f,z))/1000; labcp(f,tm,z)$fposs(f,z).. sum((p,s)$xposs(s,z,p), labor(p,z,tm)*(xcrop(p,s,f,z) - xcrops(p,s,f,z)$sh(z,f))) + sum(r, llive(r,tm,z)*xlive(r,f,z)) =l= flab(f,tm,z) + tlab(f,tm,z) + dpm*plab(f,z); labcs(f,tm,z)$sh(z,f).. sum((p,s)$xposs(s,z,p), labor(p,z,tm)*xcrops(p,s,f,z)) =l= dpm*sfs*nsc(f,z); spd(f,z)$sh(z,f).. sum((p,s)$xposs(s,z,p), xcrops(p,s,f,z)) =e= sps(z)*nsc(f,z); labrc(tm,z).. sum(f$fposs(f,z), tlab(f,tm,z)/dpm + plab(f,z) + sfs*nsc(f,z)$sh(z,f)) =l= rlabsup(z); *combp(f,z)$fposs(f,z).. sum(dr, consp(dr,f,z)) =e= fnum(z,"fam-farm"); combp(f,z)$fposs(f,z).. sum(dr, consp(dr,f,z)) =e= fnum(z,f); combs(f,z)$sh(z,f).. sum(dr, conss(dr,f,z)) =e= nsc(f,z); dem(c,z)$cpossn(c,z).. regcon(c,z) + export(c,z)$cex(c) =e= sum(f$cposs(c,f,z), salesp(c,f,z) + (1 - mktmarg)*saless(c,f,z)$sh(z,f)); demreg(c,z)$cpossn(c,z).. regcon(c,z) =e= sum(g, qs(c,z,g)*regq(c,z,g)); conv(c,z)$cpossn(c,z).. sum(g, regq(c,z,g)) =e= 1; ddev(f,z,ty)$phi(z,f).. sum(c$cpossp(c,z), prdev(c,ty,z)*(salesp(c,f,z) + (1 - mktmarg)*saless(c,f,z)$sh(z,f))) =e= pdev(f,z,ty) - ndev(f,z,ty); aadc(z).. adc(z) =e= sum((c,g)$cpossn(c,z), ws(c,z,g)*regq(c,z,g)); aliv(z).. revliv(z) =e= sum(f$fposs(f,z), pricel(z)*xprodl(f,z))/1000; aexp(z).. revexp(z) =e= sum(cex, price(cex,z)*export(cex,z))/1000; avsc(z).. vscdef(z) =e= vsc(z)*sum((f,dr)$fposs(f,z), consp(dr,f,z) + conss(dr,f,z)$sh(z,f))/1000; acrop(f,z)$fposs(f,z).. cropcost(f,z) =e= sum((p,s)$xposs(s,z,p), pcost(p,z)*xcrop(p,s,f,z))/1000; ahlc(f,z)$fposs(f,z).. hlcost(f,z) =e= (twage(z)*sum(tm, tlab(f,tm,z))/dpm + pwage(z)*plab(f,z))/1000; ares(f,z)$fposs(f,z).. rescost(f,z) =e= fwage*sum(tm, flab(f,tm,z))/dpm/1000; avet(f,z)$fposs(f,z).. vetcost(f,z) =e= vetpr*xprodl(f,z)/1000; obj.. cps =e= sum(z, revexp(z) + revliv(z) + adc(z) + vscdef(z) - sum(f$fposs(f,z), hlcost(f,z) +rescost(f,z) + rationr(f,z) + vetcost(f,z) + cropcost(f,z) + phi(z,f)*sum(ty, pdev(f,z,ty) + ndev(f,z,ty))/card(ty)/1000)); flab.up(f,tm,z) = dpm*fnum(z,f)*famsize(z,f); Model brazil / all /; z(zz) = no; loop(zz, z(zz) = yes; solve brazil maximizing cps using lp; z(zz) = no; option limRow = 0, limCol = 0; ); display landb.m, xprodl.l, salesp.l, saless.l, regcon.l, export.l, regq.l;