Technological Adoption in Rural Cochabamba, Bolivia Author(S): Ricardo Godoy, Jonathan Morduch, David Bravo Source: Journal of Anthropological Research, Vol

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Technological Adoption in Rural Cochabamba, Bolivia Author(s): Ricardo Godoy, Jonathan Morduch, David Bravo Source: Journal of Anthropological Research, Vol. 54, No. 3 (Autumn, 1998), pp. 351-372 Published by: University of New Mexico Stable URL: http://www.jstor.org/stable/3630652 Accessed: 20/04/2010 00:53

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http://www.jstor.org TECHNOLOGICALADOPTION IN RURAL COCHABAMBA,BOLIVIA1

RicardoGodoy Departmentof Anthropology,University of Florida,Gainesville, FL. 32611-7305

JonathanMorduch and David Bravo Departmentof Economics,Harvard University, Cambridge, MA 02138-5703

A surveyof aboutone thousand smallholder households in theDepartment of Cochabamba, Bolivia,is usedto examinethe determinants of adoptionof newfarm technologies.A his- toricalanalysis shows that government policies since colonial days have made it difficultfor smallholdersto accumulateassets and improvefarm productivity.The survey is usedto identifythe ecological and socioeconomicdeterminants of theadoption of chemicalfertilizers and pesticidesamong smallholders in four altitudezones: highlands, high valleys, low valleys,and tropics.Ecological zone did notprove to be a statisticallysignificant determi- nant of adoptionin thepooled sample. Within any one altitudezone, no determinantpre- dictedthe adoption of bothtechnologies. Standard determinants of adoptionin othercoun- tries (e.g.,education, income, land tenure)did not explainadoption across zones or for eitherof thetwo technologies. The conclusion contains a discussionof therole of historyin adoptionand thepossible consequences of adoptionfor smallholdersand Bolivia.

ANTHROPOLOGISTSHAVE LONG STRESSED the ecologicalheterogeneity of the Cen- tralAndes (Murra1975). Among ecological zones in Bolivia,the valleys have been singled out as an economicallylively region because they enjoy lower climaticrisks, denser populations,larger markets, greater prevalence of pri- vate landtenure, widespread rural credit markets, and much exposure to the outsideworld since colonialdays. Lyingbetween the highlandsand the tropics, valleydwellers have lower transportcosts to reachlands either far above or far below them and can producecrops and raise animalsadapted to the ecologicalextremes. In parts of Bolivia,smallholders with access to landsin the valleys had higherincome than smallholderswith access to plots only in the highlandsor only in the lowlands(Dorsey 1975a,1975b). Owingto the more favorableecological and economicendowments of the valleys,some scholarshave notedthat the adoptionof new farmtechnologies in Bolivia(e.g., chemicals,tractors) tends to be more markedat lower eleva- tions (Zuvekas1977). Policyanalysts thus suggest that futureefforts to produce and diffusenew productiontechnologies in agriculturein Boliviashould focus on the valleys, with the highlandsreserved for grazingand the tropics for biodiversity. To explorethese ideas,we use a surveyfrom the Departmentof Cochabamba of aboutone thousandfarm households in four ecologicalzones (Figure 1). We use the survey to achieve two goals. First, we test whether ecological zone mattersin the adoptionof modernfarm technologies. In particular,we

(Journal of AnthropologicalResearch, vol. 54, 1998)

351 352 JOURNALOF ANTHROPOLOGICAL RESEARCH

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cIFIC- Political Boundary N cEAN - - Ecological Boundary PARAGUAY * Cityof Cochabamba HILEARGENTINA Figure 1. Politicaland EcologicalDivisions of Cochabamba,Bolivia (Adaptedfrom Painter 1995:146 and Mufioz1994:135) test whether smallholders who live in the valleys have a higher probabilityof adopting new technologies than smallholders who live in the highlands or than smallholders who live in the tropics. Second, we test whether conventional determinants of adoptionidentified in other countries (e.g., education) (Rogers 1995) also predict the adoption of technologies in different ecological zones of Cochabamba.By modern farm technology we mean new ways of producing crops, raising livestock, or processing and storing goods produced on the farm. The informationwe use is unique. First, unlike other departments of Bo- livia, the Department of Cochabamba straddles most vertical zones of the Andes. The survey allows us to test, with quantitative data, well-established TECHNOLOGICALADOPTION IN RURALBOLIVIA 353 ideasabout the effectsof accessto ecologicalzones. Second, the surveyis among the firstlarge rural household surveys for Bolivia; it allowsresearchers to comple- ment qualitativeand historical studies that have characterizedmuch of the past researchin ruralBolivia. Last, since the Departmentof Cochabambacontains the densestrural population of Bolivia,findings from Cochabamba can teachus somethingabout a largeportion of Bolivia'srural population.

ECOLOGICALZONES

Researchershave foundit useful to describethe ecologicalheterogeneity of the Andesby dividingit into three to fourhorizontal belts correspondingto differentaltitudes (Guillet 1981). Each belt is an idealtype with its own flora, climate,fauna, land type, etc. Since zones blendwith each other at the upper andlower limits, the patternresembles a continuumrather than a ladderwith discrete steps (see Figure 1). The highlandsof Cochabamba,about 3,500-4,000 meters above sea level, are a broadswath exhibitingmixed agropastoralproduction. Several varieties of Andeantubers and barley grow well; livestockactivities center around llamas. Agriculturaltechnology is simple:planting is donewith digging sticks. The main formof settlementis the village,which is often depopulatedafter the harvest when peoplemigrate to seek seasonalemployment (Pdrez-Crespo 1991b). The high valleys (3,000-3,500 meters) lie below the highlands.They are warmerand more fertilethan the highlandsand sustaina more intensiveand variedmix of agropastoralproduction. Cereals, squash, maize, fruits, legumes, andAndean tubers grow well in this tier. Stockraising is also broaderthan in the highlands,encompassing more European and indigenous animals. In settle- ment pattern,highlands and high valleys differin degree ratherthan in kind. In both zones, the nucleatedvillage is the essential communitytype, but vil- lages become denser as one moves downin altitude. The low valleys (2,000-3,000meters) are warmerand lusher; yet they are still semiaridand contrast with the humidtropics of the lowest zone. Pepper, maize, fruits, medicinalherbs, and cotton grow well here. Cattle and goats prevail,though sheep 'are also found. Llamasare less common,but yoked bullocksare more common.This is also the areawith the greatestirrigation. The lowlandtropics (below 2,000 meters) exhibit much ecologicalvaria- tion, from moist tropicalrain forests in the coca-growingregion known as Chapareto drierforest abuttingthe Departmentof SantaCruz. Chapare has becomea center for the productionof coca andits derivatives.

THE VALLEYSAND TECHNOLOGICALINNOVATIONS IN BOLIVIA

Research in Bolivia suggests that valley dwellers may enjoy environmental and economic advantages in agriculturalproduction over people in the highlands or in the tropics. The valleys of Bolivia have less hail and frost than the 354 JOURNALOF ANTHROPOLOGICAL RESEARCH highlandsand fewer floods than the tropics,though the risk of droughtand pest infestationmay be greater(Thomas 1979). A gentlertopography, flatter lands,more possibilitiesfor irrigation(World Bank 1992), more privateland tenure,and a denserpopulation and network of roadshave madeit easier for valley dwellersto intensifyproduction since colonialdays (Larson1988). Case studiesfrom Bolivia show that the adoptionof modernfarm technologies has been more prominentin the valleys because of greater securityof landtenure (Dorsey 1975b),larger farm sizes (Pou 1972),more creditfacili- ties (Mufioz1994), and lower naturalrisks (Rice 1974). This situationhas allowedsmallholders in the valleys to use moderninputs (Zuvekas 1977). The economicdynamism of the valleys and lowlands,coupled with their populationdensity and their politicalclout since the Revolutionof 1952, has influencedpolicy makers' decisions about where publicinvestments in agri- cultureshould go (Schuh,Roe, andGodoy 1994; Zuvekas 1977). For instance, researchersfrom the WorldBank concluded that publicinvestments in the highlandsshould focus on reducingpoverty through better education and health, andnot so muchthrough improvements in agriculturalproductivity for smallholders,because the highlandsface a harshclimate (World Bank 1992). The authorsrecommend greater investments in agriculturalresearch, land titling, andirrigation in the highlands,but only in the shortrun; in the long run,they see smallholdersleaving the highlands.In contrast,the authorsput investments in agriculturalresearch and extensionat the core of the development for the valleys becausethe valleys do not face "natural-resourceconstraints" (WorldBank 1992). Althoughthe Boliviancountryside has two agriculturaltechnologies-an archaictechnology in the highlandsand a modem technologyin the valleys and in the lowlands-it remainsunclear the extent to which ecologicalzone matters in the adoptionof new farm technologies once we controlfor the socioeconomicattributes of differentzones. Put differently,valley dwellers may be more likely to adoptthese technologiesthan highlanders,but it is unclearwhether this reflects the ecologicaladvantages of livingin the valley or, instead,access to credit,proximity to roads,or the demographiccharac- teristicsof householdsin the valley.In the balanceof this article,we estimate the pure effect of ecology after controllingfor the socioeconomicand demographicattributes of differentzones.

THE SURVEY

We use a householdsurvey collected in the Departmentof Cochabambain 1991 by several nationaland internationalorganizations (Cuevas 1993). The survey was designed to collect informationon the determinantsof income among smallholders to gain better knowledge of the countryside because the last large rural survey in Bolivia had been done in 1987. About 1,100 households were surveyed; the response rate reached 86 percent. We use information only from farming households (n = 997). TECHNOLOGICALADOPTION IN RURALBOLIVIA 355 THE HISTORICALCONTEXT

Fromcolonial days to the present,small farmers in Cochabambahave found it difficultto increase their income and to accumulatecapital owing to discriminatorypolicies by the SpanishCrown and, later, by the Boliviangovern- ment (Pdrez-Crespo1991b).

Colonialand RepublicanEra: Taxes By the 1580s,soon afterthe conquest,Spaniards had already taken over the most fertile lands in the valleys of Cochabambaand had pushed Indiansto marginallands (Larson1988). Had Indiansbeen able to compete in colonial markets,they couldhave increasedtheir income,but the Crownmade it diffi- cult forthem to do so. The Churchestablished an inflexiblesystem of tithes in Cochabamba,by which it auctionedto large landownersthe right to tax pri- vate grain productionfrom peasantand Indiancommunities (Larson 1988). Taxes drove many small producersinto povertyand wage laborand pushed them into cities, particularlywhen droughtsstruck (Larson 1988). Taxes on small producerscontinued well into the nineteenthcentury, because the governmentrelied on such taxes for its revenues(Rodriguez Ostria 1977).The governmenttried to privatizeand tax the holdingsof peasantand Indianvillages to stimulatethe developmentof privateland markets(Klein 1988).Although attempts at privatizationmet withresistance from rural people in the highlands,the governmentcontinued to tax farmproduction in the valleys of Cochabamba,where resistance was weaker owing to greater ethnic heterogeneity(Rodriguez Ostria 1993). Writingbefore the 1952 Revolution, Thibodeaux(1946) noted that small producers did not have incentivesto adopt innovationsin farmingbecause of productiontaxes.

Colonialand RepublicanEras: Pro-Mining and Anti-AgricultureBias Besidescolluding with large landowners and taxing peasants, the Crown(and laterthe republicangovernments) helped mining entrepreneurs rather than small farmers,because it saw in mininga sourceof quickrevenues for the government. Since colonialdays, the governmenthas put in place manypolicies to lowerfood prices for minersand urban consumers at the expenseof ruralproducers.These policieshave includedprice ceilings on cropsgrown by Indians andsubsidies to importfood from neighboring countries (Rodriguez Ostria 1995). Relianceon the exportsof mineralshas producedan overvaluedexchange rate sincecolonial days and has made food imports cheaper than domestic goods. Dur- ing the late eighteenthcentury, agriculture flourished in manyof the valleysof Cochabambaand neighboringNorthern Potosi. But the prosperityended for smallholderswhen the exportsof silverores grew (Mitre 1981; Grieshaber 1986).

The Land Reform of 1953 The Revolution of 1952 did not represent a break with the past in the way that the government treated small ruralproducers (Pdrez-Crespo 1991b). The 356 JOURNALOF ANTHROPOLOGICAL RESEARCH governmentcontinued to discriminateagainst smallholders by increasingpublic investmentsin the newly nationalizedtin mines and by giving land grants, subsidies,and inexpensive credit to commercialfarmers (Eckstein 1983). The landreform of 1953 andcolonization projects in the lowlandmade it easierfor the governmentto downplayinvestments in technologicalinnovations or to redistributeassets to the poor (Gill 1987). Productionfrom smallholdersin Cochabambagrew afterthe reformof 1953 owingto greateruse of chemical fertilizers(Sanabria 1993), but the increase in productivitydid not last because of the lack of sustainedpublic investments in agriculturalresearch. After the 1953 landreform, the governmentdid not financeresearch into the productionof new farm technologiesfor smallholders,nor did it make creditavailable to smallholdersso that they couldimprove the qualityof their physicalcapital (Dandler 1984). Agricultural researchers did not pay attention to the "immediateproblems and interests of farmersin the region"and did not offer extension services to smallholders(Heath, Erasmus, and Buechler 1969:453).The only programof agriculturalresearch and extension after the 1952 Revolutionwas financedby the United States, but it ended suddenly whenthe flowof foreignaid stopped (Godoy, De Franco,and Echeverria 1993).

TheModern Era Fromthe 1970suntil the present,many of the discriminatorypolicies against agricultureand small rural producers have continued. The governmentsupported marketingboards to controlthe priceof selectedstaples until 1985,continues to dumpfood donations of wheatfrom the UnitedStates (therebydepressing do- mesticprices), and still taxedmany farm products (Flores 1984). Public investments continueto go to the lowlandsrather than to smallholdersin the valleys andhighlands (Morales 1990). The termsof tradebetween countryside and city havedeteriorated to the disadvantageof the countryside,and real rural incomes in Cochabambaand other rural areas of Boliviahave declined (Dandler 1984). The governmentof Siles Suazo (1982-1985) was an exception to these trends. It subsidizedtransport, increased public employment (and therefore the demandfor food),and imposed several restrictions on the importsof food (Godoyand De Franco1993). The policiesraised the incomeof smallholders, but at a great macroeconomiccost. In Cochabamba,stabilization and struc- turaladjustment galvanized smallholders to migrateto cities andto coca-grow- ing regions (Urioste1989). Althoughrecent governmentshave tried to reverse centuriesof discrimi- nationthrough new land tenure legislation,decentralization, and the provi- sion of credit,they have donelittle to providesmall farmers in Cochabambaor elsewherewith new technologiesfor growingcrops or raisinganimals or with more and better schooling(Mufioz and Lavadenz1997). Bolivia'spublic in- vestment in agriculturalresearch and extensionis the lowest of any country in Latin America. Bolivia's yields for staples have declined for decades and remain among the lowest in the Southern Cone (De Franco and Godoy 1993). The government is still not investing in producingtechnologies appropriateto TECHNOLOGICALADOPTION IN RURALBOLIVIA 357 the needs of smallholders.The technologiesreleased are often inappropriate and do not offer smallholderstangible economic advantages (Lagos 1994).

CopingStrategies The persistentneglect of and discriminationagainst the countrysidehave inducedsmallholders to developcoping strategies that have survivedsince colonialdays. Since the seventeenthcentury, smallholders in Cochabamba,un- ableto make ends meet, have supplementedtheir incomethrough petty trade (Larson1988), such as the sale of cornbeer (RodriguezOstria 1990), or through providinglocal transport, controlling irrigation (Larson 1988), and migration to the Chapare(Sanabria 1993). During recessions in the countryside,many large landownerssold their properties; at those times,smallholders with capital were able to buy land,but such episodeswere rare(Rodriguez Ostria 1990). Whenset againstthis largerhistorical context, the currentpattern of adoption of new farmtechnologies by smallholdersin Cochabambabecomes clearer. Smallholdershave been too poor to invest in innovationsof doubtfuluseful- ness for their farmsor for their needs (Painter1995). In the late 1980s and early 1990s, only 15 percentof smallholdersused fertilizersand only 5 percent used improvedseeds (Painter1995). The low rates of adoptionreflect the limitedcapacity of the governmentto produceappropriate technologies and the insufficientincomes of smallholdersto buy the technologies.

THE THEORETICALFOCUS

Researcherswho use quantitativemethods to studythe adoptionof new farm technologieshave drawnon three approaches.Since Griliches's1956 study, manyresearchers have used quantitativehistorical information to mappatterns of technologicaldiffusion over time. These studies have shown,for example, that smallholdersadopt new technologiesbecause of favorablechanges in the relativeprices for crops.A second groupof researchersrelies on cross-sec- tionalinformation and stresses the socioeconomicand demographicattributes of the personor household(e.g., Rogers 1995). A thirdgroup has recently started usingpanel information to studythe role of villageneighbors in learningabout andadopting new farmtechnologies (e.g., Fosterand Rosenzweig 1996). We rely on the second method-a statisticalanalysis of a cross section- becausewe do not have quantitativeinformation on adoptionor observations of individualhouseholds over time. In line with other scholarswho use the second approach,in our model, socioeconomicand demographicvariables enhance adoptionif they lower the cost (or risks) or raise the benefits of adoptionto the household.

THE VARIABLES AND THE INFORMATION

Table 1 contains a summary and definition of the variables used in the analysis. 358 JOURNALOF ANTHROPOLOGICAL RESEARCH TABLE 1 Summary and Definition of Variables

Variable Definition N Average SD Minimum Maximum Dependent Fertilizer Expenditures(in bolivianos)a 997 43 139 0 2,100 Pesticides Expenditures(in bolivianos)a 997 38 171 0 3,000 Explanatory Ecological Highlandsb Producesonly potatoes 997 .22 .41 0 1 Highvalleyb Producesmaize/potatoes 997 .30 .45 0 1 Lowvalleyb Producesonly maize 997 .19 .39 0 1 Tropicsb Producestropical crops (e.g., cassava) 997 .13 .34 0 1 Community Irrigationb Irrigationpresent 769 .31 .46 0 1 Nearroadb <0.5 hourto reachroad 769 .76 .42 0 1 Household Maleb Sex of householdhead 997 .87 .33 0 1 Monoqb MonlingualQuechua 997 .37 .48 0 1 Absenceb >1 month/yearabsence by householdhead 997 .20 .40 0 1 Titleb 1 = title secure;0 forall others(e.g., renters, sharecroppers) 769 .66 .47 0 1 Statusb If househas tinroof, or brickwalls, or separate roomfor bathroom/ kitchen,or electricity 997 .88 .31 0 1 Animals Totalnumber of animals 997 31 35 0 356 Land Hectares/household 816 3.6 4.8 .25 25 0.50 hectares 160 19 0.75 hectares 140 17 1.50 hectares 178 22 3.50 hectares 172 21 7.50 hectares 94 12 15.00 hectares 57 7 25.00 hectares 15 2 Age Age of householdhead (years) 997 47 15 17 98 Education Maximumeducation of householdhead (years) 997 3.0 3.2 0 13 Hh size Numberof childrenand adultsin household 996 4.6 2.0 1 8 Grossinc Bolivianosafrom income earnedinside and outside the farm(thousands) 989 5.5 12 0 169 Grosofin Bolivianosafrom income earnedoutside the farm (thousands) 985 1.4 4.7 0 89 a. 5.35 bolivianos= U.S.$1.00 in 1991. b. Dummyvariable. Name of dummyvariable = 1. TECHNOLOGICALADOPTION IN RURALBOLIVIA 359 DependentVariable: Chemical Fertilizers and ChemicalPesticides We focus on chemicalsused in farmingrather than on other technologies, such as the use of tractorsor the use of improvedplant varieties, because chemicalshad greater variance and were easier to identify.It is moredifficult to decidewhether a plantvariety is modernor traditional. We used two technologies (expenditureson chemicalfertilizers and on chemicalpesticides) for three reasons. First, smallholderssplit the kit of moderntechnology and adoptinputs independentlyand often sequentially (Figueroa1993). Second, the adoptionof new technologiesin the Andestakes manyforms owing to the ecologicalheterogeneity of the area(Brush, Taylor, andBellon 1992). Last,the share of farmerswho adoptvaries by technology. Only 32 percent of the sample adoptedchemical fertilizers, but 47 percent adoptedchemical pesticides. Farmers in Cochabambatypically use chemical fertilizersto grow tubers (Lagos 1994), and a growingnumber are using in- secticides (Painter1995). A bivariateanalysis of adoptionagainst ecological zone (not shown here) suggests wide differencesin adoptionfor both innovations across zones. About half of the samplein the valley adopts,a quarterin the highlands,and only about 13 percent in the tropics. This informationwould appearto confirm casual observationsand previousresearch suggesting that adoptionoccurs mainlyin the valleys.Forty-eight percent of the adopterslive in the high and in the low semiaridvalleys, with the balancesplit between the highlandsand tropics.As we shall see however,the prominenceof the valley as a determi- nant shrinksonce we controlfor otherattributes of the zone.

ExplanatoryVariables We group explanatoryvariables into three types: ecological,community, and household. Ecological.The survey did not containinformation on altitude,so we used crops as proxies for ecologicalzones. In accordancewith previoushistorical and ecologicalresearch in Cochabamba,we definedfour ecologicalzones- highlands,high valleys, low valleys, andtropics-that correspondto the four differentaltitudes discussed above. If farmersonly grew potatoes,we classi- fied the zone as highlandbecause farmers who onlygrow potatoes tend to live in the highlands.If farmersgrew maizeand potatoes, we classifiedthe zone as a highvalley. If smallholderscultivated only maize,we classifiedthe zone as a low valley.The tropicsinclude smallholders who grew cropswhich only grow in the tropics.We also used animalsas proxiesfor ecologicalzones andcom- bined animalswith crops to define ecologicalfloors; but the results did not vary,so we decidedto only use crops. These definitionsnaturally produce crude categories for differentzones. The definitionfails to includeall the smallholderswho adoptnew technologies. About12-13 percent of adoptersdo not growpotatoes, maize, or tropical cropsand so defy our ecologicalclassification. Our approach also misclassifies smallholderswho growcrops diagnostic of one zone in anotherzone. Ethnog- 360 JOURNALOF ANTHROPOLOGICAL RESEARCH raphershave long noted the shortcomingsof using cropsor animalsto proxy for ecologicalzone because manycrops and animalscan be foundin several zones (Murra1975). Community.We took into accountwhether households had access to irri- gationand whether it took peopleless thanthirty minutes to reacha road.In Cochabamba,as in other parts of Peru, communities(rather than districts) manageirrigation (Mitchell and Guillet 1994), though before the 1952 Revolu- tion, units largerthan the communityplayed a prominentrole in irrigation. Because communitiesmanage irrigation today, irrigation is still partlya com- munityvariable; however, it also partlyreflects household attributes and thus may also proxyfor access to capitaland entrepreneurial skill. Household.The chiefhousehold variables included: (1) whetherthe householdhead was absentfor more than one monthper year,(2) herdsize, (3) farm size, (4) demographicand socioeconomic attributes of the householdhead and household,(5) humancapital attributes of the householdhead, (6) landtitling, and (7) socioeconomicstatus. We used a Tobit model because68 percentof the householdsdid not use chemicalfertilizers and 53 percent did not use chemicalpesticides. Tobit modelsare appropriatewhen the dependentvariable (chemicals for farmingin this case) containsa large share of zeros. We also ran ordinaryleast square (OLS)regressions with Huberrobust standard errors as a checkand obtained qualitativelysimilar results. Much in the same way that income can drive adoption,so too canadoption affect income. To breakthe two-waydirection of causality,we rantwo-stage ordinary least squaresusing off-farm income as an instrumentfor gross income.

RATIONALEFOR THE CHOICEOF COMMUNITYAND HOUSEHOLD EXPLANATORYVARIABLES

As discussed earlier,explanatory variables take on a positive sign if they lower the costs (or risks) or raise the benefits of the adoptionof new farm technologies. Irrigationshould encourage adoption in part because it lowersrisks and comple- ments the use of chemicals,although it mayalso maskunobserved attributes of the land(Mukhopadhyay 1994). In Cochabamba,irrigation is foundin all zones, thoughit is more prevalentin the low valleys;it is used with all crops,but principallywith cash crops.Larson's (1988) research shows that since colonial days,access to irrigationhas allowedproducers to lowervariability in yieldsand to increaseproduction. P6rez-Crespo's (1991a) contemporary research echoes these findings.We expect thatpeople with access to irrigationwould be more likelyto intensifyproduction and to use chemicalsin farming. Farm size may or may not matter depending on whether the technology is divisible or neutral to scale (Barham,Carter, and Sigelko 1995). Farm size can mask access to credit, modern inputs, access to information,and capacityto bear risk. In general, in Cochabamba,larger farms are associated with greater wealth. TECHNOLOGICALADOPTION IN RURALBOLIVIA 361 Researchershave shown that educationbeyond a thresholdof aboutfour years speeds the adoptionof improvedplant varieties, though the threshold seems higher in LatinAmerica or for other technologies(Phillips 1991). In the Departmentof Beni, educationspeeds the adoptionof modernrice seed- ers (Godoy,Franks, and Alvarado 1997) because education makes it easier for adoptersto obtaininformation about the innovation.In ruralCochabamba, we expect that smallholderswith more educationwould find it easier to readthe instructionson the use of chemicalsand thus to adoptthem beforeilliterate smallholders. Age mayinfluence people's willingness to bearrisk andso mayaffect adoption (Barham,Carter, and Sigelko 1995). Some researchersfind that younger farmersare morelikely to adopt(Huffman and Mercier 1991), but othershave foundweaker evidence for the effectsof age (Brush,Taylor, and Bellon 1992). We includeage as a control. Proximityto roadsshould enhance adoption because it lowers the costs of inputsand raises the price of outputs,thus makingadoption more profitable (Brush,Taylor, and Bellon 1992). Proximitymay also serve as a proxyfor a household'sdegree of isolation.This situationwill also yield a positive asso- ciationof adoptionand nearness. The absenceof the householdhead from the farmcould produce ambiguous results on adoption.Absence could encouragethe adoptionof labor-saving technology.These technologies,however, also often have labor-intensiveas- pects. Moreover,absence could also rob the householdof entrepreneurial talent and dull its dynamism.We includethe absenceof the householdhead becauseseasonal migration historically has been an importantpart of the cop- ing strategiesof ruralhouseholds in Cochabamba. We hypothesizethat monolingual speakers of Quechuashould adopt less fre- quentlythan bilingual speakers of Spanishand Quechuabecause monolingual speakerswould find it harderto get informationabout new technologiessuch as chemicals.Monolingual speakers would also findit harderto readinstructions on how to use chemicals.Bilingualism goes hand-in-handwith othersocioeco- nomicattributes (e.g., income).Since we alreadycontrol for these covariatesof monolingualism,the estimatedcoefficient on monolingualismshould give us the relativelypure effect of languageability on adoption.Several studies of bi- lingualismamong Indian populations in Bolivia,Peru, and Guatemala have shown thatlanguage ability affects school performance and income, even aftercontrol- ling for many of the socioeconomiccovariates of bilingualism(Patrinos and Psacharopoulos1992). Following those findings,we expect that languageability mightalso affectthe choiceof technology. Wealthaccumulated over time, proxiedby herd size and housing quality (Muiioz 1994), should facilitate adoption because it makes farmers less averse to risk and makes it easier for them to get credit or to self-finance new investments. Last, secure property rights to land should enhance adoption (Feder, Just, and Zilberman 1985). People with secure tenure feel safer about investing in 362 JOURNALOF ANTHROPOLOGICALRESEARCH their propertiesto raise productionand the valueof theirhomesteads (Alston, Libecap,and Schneider1996).

RESULTS

Tables 2-3 containthe regressionresults for the full sample.Tables 4-7 containthe results of Tobitand OLS regressions for each of the fourecologi- cal zones. In the discussionbelow, we focuson determinantswhich are statisticallysignificant at the 90 percentconfidence level or above.

TheDeterminants of Adoptionin theFull Sample The results shownin Tables2 and3 suggest that in none of the modelsdo ecologicalzones matter once we control for the covariatesof altitude.Al- though the size of some of the coefficientsis relativelylarge, none of the ecologicalvariables was statisticallysignificantly different from zero. Further- more,none of the determinantsexplained the adoptionof bothchemical fertilizers andpesticides. Only proximity to roadssignificantly drives the adoption

TABLE 2 Determinants of Adoption with Full Sample: Pesticides

Tobit OLS 2SLS Variable Coefficient t Coefficient t Coefficient t Grossinc .00 .02 .00 .04 -.00 -0.25 Irrigation 28 .84 -9 -.53 -9.8 -0.51 Near road 81 2.1* 32 2.64* 33 1.64** Absence -26 -0.65 1.1 0.04 1.40 0.06 Animals .51 1.13 .17 .39 .24 0.71 Land -.28 -0.08 -.15 -.07 -.22 -0.12 Male 60 1.14 31 1.43 34 1.18 Education 1.9 .34 .65 .35 .38 0.12 Age .47 .46 .24 .27 .23 0.41 Monoq -28 -0.87 -18 -1.31 -19 -1.06 Hh size 3.15 0.41 2.85 0.76 2.66 0.63 Title 4.75 0.14 20 1.40 20 1.10 Status -119 -2.15* -72 -1.21 -74 -2.29* Highlands 4.67 0.10 -1.3 -0.04 -6.0 -0.21 High valley -47 -1.08 -27 -1.24 -32 -1.19 Low valley 5.02 0.10 4.8 0.20 .55 0.02 Left-censored 327 n/a n/a Uncensored 280 n/a n/a N 607 607 603a Pseudo R2 0.0036 -0.0049 -0.0051 Note: Regressions include constant. OLS includes Huber robust standarderrors. Two-stage least square includes off-farmincome as instrumentalvariable for gross income. Regular R-square for OLS. n/a = not applicable. a. Differences in the sample size between 2SLS and Tobit and OLS are due to missing values in instrumental variable. * ** = significant at <5%; = significantat < 10%. TECHNOLOGICALADOPTION IN RURALBOLIVIA 363 TABLE 3 Determinants of Adoption with Full Sample: Fertilizer

Tobit OLS 2SLS Variable Coefficient t Coefficient t Coefficient t Grossinc -.00 -0.38 -.00 -0.12 .00 0.12 Irrigation 166 4.37* 55 3.16* 55 3.78* Nearroad 82 1.84** 13 1.20 12 0.81 Absence -117 -2.49* -40 -3.50* -41 -2.45* Animals -.31 -0.54 -.07 -0.66 -.10 -0.39 Land -2.47 -0.62 -.36 -0.31 -.35 -0.25 Male -65 -1.15 -7.9 -0.62 -8.01 -0.36 Education 14 2.31* 5.8 1.68** 5.89 2.45* Age -.84 -0.71 -.43 -0.82 -.43 -0.99 Monoq -38 -1.03 -23 -2.26* -23 -1.71** Hh size -10 -1.21 -1.41 -0.54 -1.42 0.43 Title 91 2.30* 28 2.72* 29 2.00* Status -15 -0.24 3.73 0.22 3.48 0.14 Highlands 22 0.43 7.95 0.43 9.33 0.43 Highvalley 28 0.58 13 0.77 15 0.73 Lowvalley 28 0.51 19 1.21 20 0.95 Left-censored 419 n/a n/a Uncensored 188 n/a n/a N 607 607 603a PseudoR2 0.0158 0.0391 0.0382 Note: Regressionsinclude constant. OLS includes Huber robust standard errors. Two-stage least squareincludes off-farm income as instrumentalvariable for gross income. Regular R-square for OLS.n/a = not applicable. a. Differencesin the samplesize between2SLS and Tobit and OLS are due to missingvalues in instrumentalvariable. * ** = significant at <5%; = significant at <10%. of pesticides,while irrigation,education, secure propertyrights, and the con- tinualpresence of the householdhead drivethe adoptionof fertilizers. Monolingualismin Quechuain ruralCochabamba is associatedwith lower adoptionof chemicals,but the results are statisticallyinsignificant for pesticides andare statisticallysignificant only for some of the econometricmodels of fertilizers.Language ability neither hindersnor facilitatesadoption after we controlfor other variables,such as wealth,proximity to town, or education. Monolingualspeakers probably rely on relatives and friendsin the village to get informationabout new technologieswithout needing to read in- structionsdirectly or to speakto extensionagents. Althougheducation and titles have a statisticallysignificant, positive effect on the adoptionof chemicalfertilizers, they have a muchweaker (though still positive)role in the adoptionof chemicalpesticides. The weak results likely reflect differencesbetween "effective"property rights-which, for example, may be associatedwith length of tenure-and the legal definitionused here. Gaugingthe enforceabilityof legal (andinformal) rights is impossiblewith the availabledata. 364 JOURNALOF ANTHROPOLOGICAL RESEARCH TheDeterminants of Adoptionacross Ecological Floors No determinantconsistently explains the adoptionof bothtechnologies within each zone. In the highlands(Table 4), bilingualismencourages the adoptionof both technologies,but the results are sensitive to the model used. Variables such as educationand irrigationare associatedwith greateruse of fertilizers, but not of pesticides,and even then the resultshold only for the Tobitmodel. In the valleys,we foundeven weakerdeterminants. In the highvalleys (Table 5), onlyroads seem to be associatedwith greater adoption of pesticides,but only in the Tobitmodel. Land titling and prolonged absence from the householdseemed to discouragethe adoptionof pesticidesor fertilizers,but the resultswere sensitive to the modelused. In the low valleys(Table 6), we onlyfound one determi- nantthat playeda statisticallysignificant role in adoption:irrigation. Irrigation was associatedwith greater adoption of fertilizersin bothmodels. In the tropics(Table 7), householdand herd size bore a positiveand statisticallysignificant relation to the adoptionof chemicalpesticides. The absence of the householdhead discouragedthe use of pesticides.Except for house- holdsize, the findingsare sensitiveto the modelused. The adoptionof chemical fertilizersbore a negative and a statisticallysignificant relation to farm size and a positive and statisticallysignificant relation to irrigation,but the results were not robustto model specifications.

TABLE 4 Determinants of Adoption of Chemicals in Highlands

Pesticide Fertilizer Tobit OLS Tobit OLS Variable Coefficient t Coefficient t Coefficient t Coefficient t Grossinc .001 .243 .001 .837 -.010 -.642 -.0003 -.422 Irrigation 84.0 1.043 28.8 .792 241 2.61* 66.63 1.38 Nearroad 57.8 0.612 47.6 1.21 -21.5 -0.20 -17.2 -.698 Absence 98.1 1.016 75.2 .838 -347 -2.57* -77.5 2.24* Animals -.277 -.283 -.148 -.54 -3.03 -1.52 -.273 -1.50 Land 8.95 1.111 -1.91 -.74 2.81 .284 .172 .066 Male 114 0.744 .106 .003 -103 -.636 -64.6 -1.58 Education 4.69 0.354 4.17 .715 30.7 2.03* 6.643 1.34 Age -1.04 -0.42 -1.47 -1.77** 1.22 0.44 -.983 -.814 Monoq -208 -2.31* -79.0 -1.50 -219 -2.02* -43.1 -1.32 Hh size -3.44 -0.18 .061 .009 -26.6 -1.28 -1.81 -.320 Title 60.6 0.75 55.7 1.33 116 1.22 25.1 .939 Status -269 -2.1* -220 -.976 -136 -0.92 -19.2 -0.46 Left-censored 72 n/a 95 n/a Uncensored 70 n/a 47 n/a N 142 142 142 142 Pseudo R2 0.0141 0.1160 0.0338 0.0700 Note: Regressionsinclude constant. OLS includes Huber robust standard errors. Regular R-square for OLS. n/a = not applicable. ** * = significant at <5%; = significant at <10%. TECHNOLOGICALADOPTION INRURAL BOLIVIA 365 TABLE 5 Determinants of Adoption of Chemicals in High Valleys Pesticide Fertilizer Tobit OLS Tobit OLS Variable Coefficient t Coefficient t Coefficient t Coefficient t Grossinc .001 .429 -.0005 -.95 -.0006 -.076 -.0001 -.047 Irrigation 20.5 .808 9.88 .714 116 1.37 44.5 1.07 Nearroad 67.1 2.17* 20.8 1.60 58.1 0.58 5.06 0.15 Absence 1.98 0.06 9.09 0.53 -199 -1.75* -40.9 -1.19 Animals -.160 -.456 -.002 -0.02 -.323 -0.27 -.166 -.709 Land 4.24 1.47 3.73 0.92 -7.01 -0.66 -2.48 -1.23 Male -4.62 -.110 -6.13 -.331 -111 -0.86 17.4 0.77 Education 2.43 .564 1.31 .398 24.1 1.72* 14.0 1.10 Age .121 .151 -.158 -.55 -.295 -0.11 -.273 -.239 Monoq -27.1 -1.10 -16.7 -1.37 -34.6 -.424 -28.7 -1.57 Hh size 2.39 0.42 .038 .014 14.1 .758 5.36 1.00 Title -38.8 -1.56 -23.7 -1.70** 110 1.27 26.2 1.09 Status -2.29 -0.05 11.1 0.71 111 .790 25.1 0.84 Left-censored 94 n/a 118 n/a Uncensored 77 n/a 53 n/a N 171 171 171 171 PseudoR2 0.0113 0.0817 0.0164 0.0861 Note: Regressionsinclude constant. OLS includes Huber robust standard errors. Regular R-square forOLS. n/a = not applicable. ** * = significant at <5%; = significant at < 10%.

TABLE 6 Determinants of Adoption of Chemicals in Low Valleys Pesticide Fertilizer Tobit OLS Tobit OLS Variable Coefficient t Coefficient t Coefficient t Coefficient t Grossinc -.012 -1.24 -.002 -.95 -.006 -.79 -.001 -1.15 Irrigation -71.4 -0.61 -66.6 -1.4 219 2.34* 70.5 1.71** Nearroad 114 .89 43.6 1.63 118 1.07 29.1 1.44 Absence -187 -1.46 -60.7 -1.23 -8.23 -0.08 -37.6 -1.59 Animals 1.15 0.62 -.468 -1.02 -.60 -.361 -.23 -.55 Land -2.83 -.24 -1.98 -.738 4.60 .526 2.89 .60 Male 246 1.61 69.4 1.02 -21.4 -.19 21.8 .78 Education 14.0 .816 .410 .091 11.6 .80 1.03 .31 Age 4.30 1.47 2.96 .687 -.303 -.125 .204 .15 Monoq 131 1.21 -13.2 -.28 25.3 .290 -21.0 -.68 Hh size 4.25 .160 -9.76 -.75 -14.2 -.655 -7.14 -.87 Title 97.7 .861 51.3 1.55 117 1.24 32.0 1.42 Status -174 -914 -16.4 -0.21 -52.9 -.35 -1.91 -.04 Left-censored 62 n/a 80 n/a Uncensored 52 n/a 34 n/a N 114 114 114 114 PseudoR2 0.0157 0.0776 .0262 0.1188 Note: Regressionsinclude constant. OLS includes Huber robust standard errors. Regular R-square forOLS. n/a = not applicable. * = significantat <5%;** = significantat <10%. 366 JOURNALOF ANTHROPOLOGICAL RESEARCH TABLE 7 Determinants of Adoption of Chemicals in Tropics

Pesticide Fertilizer Tobit OLS Tobita OLS Variable Coefficient t Coefficient t Coefficient t Coefficient t Grossinc -.00 -1.01 -.00 -0.77 -.00 -0.17 Irrigation 10 0.10 -17 -0.49 56 2.03* Near road 8 0.08 -.45 -0.01 -8.97 -0.35 Absence -86 -0.81 -102 -1.68** -2.65 -0.14 Animals 3.55 2.78* 2.78 1.20 .54 1.15 Land 7.35 0.96 6.00 0.82 -1.92 -1.92** Male -148 -0.55 -59 -0.79 6.42 0.23 Education -2.24 -0.15 -8.93 -1.08 4.98 1.24 Age -5.50 -1.52 -1.90 -1.20 -1.32 -1.37 Monoq 55 0.61 38 0.72 -3.92 21 Hh size 36 1.90** 27 1.69** -1.51 -0.27 Title 20 0.21 43 1.35 29 1.26 Status 52 0.20 -20 -0.30 31 0.87 Left-censored 52 n/a n/a Uncensored 42 n/a n/a N 94 94 94 Pseudo R2 0.0185 0.1080 0.0226

Note: Regressions include constant. OLS includes Huber robust standarderrors. Regular R-square for OLS. n/a = not applicable. a. The sample size was too small. Therefore, convergence was not achieved in the estimation. * ** = significant at <5%; = significant at <10%.

DISCUSSION

The results of the study highlightthree significantlessons for policymakers andfor studentsof Boliviaand other Andeancountries.

EcologicalZone Does Not SeemTo Matter The use of the pooledsample suggests that ecological zoneperse only weakly affectsadoption once researcherscontrol for the covariatesof ecologicalzone. We foundthat smallholdersin the valleys are not intrinsicallymore likely to adoptnew technologiesthan smallholders in the highlandsor thansmallholders in the tropics.Future public investments in agriculturalresearch and extension in Bolivia(and perhaps in otherAndean countries as well) shouldprovide greaterbalance in the productionand diffusion of new farmtechnologies to all ecologicalfloors, not just to the valleys.

TheAbsence of PrimeMovers An analysisinformed by the ecologicaland technologicalheterogeneity of ruralCochabamba produces a mosaic of determinants,with no clear prime moverfor bothtechnologies or for all ecologicalzones. Even more surprising are the negativefindings of this analysis.Rogers (1995) and others (Feder, Just,and Zilberman 1985) have reviewedstudies of adoptionin manydevelop- ing countriesand have foundthat variables such as wealth,social status, edu- TECHNOLOGICALADOPTION IN RURALBOLIVIA 367 cation,and landtitling tend to enhanceadoption. But in Cochabamba,ortho- dox determinantsfail to explainadoption either in the full sample,in different ecologicalzones, or across differenttechnologies.

Implicationsof ResearchFindings for PublicPolicies The absenceof clear-cutprime movers suggests that policymakers in Bo- livia,and perhaps in otherAndean countries with similarecological heterogeneity, may not have at their disposalan easy lever to pull to promotethe diffusionof differenttechnologies across all ecologicalfloors. Policies to dif- fuse differenttechnologies will have to be tailoredto the specific needs of smallholdersin differentzones. Andeancountries such as Boliviathat have long discriminatedagainst the countrysidecan gainby increasinginvestments in the productionof new farmtechnologies for smallholders.But it may be necessaryto decentralizethose investmentsto respondto the needs of con- stituents of differentzones and socioeconomiccharacteristics. The results above are stronglysuggestive, but they shouldbe replicated with other data sets before they serve as reliableguides for policy reform. The data set we used is one of the most comprehensivesurveys currently available,but, like all ruralsurveys, the dataare measuredwith error.This situationmay partly explain the weakresults, and future data sets maybe able to providesharper answers. This study highlightsseveral key issues on which futurework shouldfo- cus. First, the absence of the householdhead for part of the year reduces technologicaladoption in a numberof instances.Absence is generallymoti- vatedby pursuitof alternativeincome-generating activities. The results show the hiddencosts of mobility.Such mobilityis far more commonin ruralBo- livia than in ruralAsia, for example,and policies to enhance adoptionwill likely fail if they are not sensitive to this context. The weakfindings on the role of educationreflect the generallylow level of educationand lack of variationacross households. Such a situationis proneto result in "noisy"(i.e., not statisticallysignificant) estimates. Improvements in educationmay still yieldpositive benefits for rates of adoption,but to deter- mine this will requirea more focusedinquiry (e.g., Jamisonand Lau 1982).A similarargument holds for the role of propertyrights. The present results suggest that simple,legalistic notions of propertyrights are likely insufficient and that rights shouldbe reformulatedin a broadereconomic and socialcon- text. In muchof Cochabamba,titling by itself is probablynot enoughto confer a feeling of securityover propertyor to increaseinvestments. In the tropical lowlandsat least, much of that feeling of security probablyhas more to do with whether a smallholder cultivates coca.

CONCLUSION

We conclude by speculating on the possible long-term consequences for smallholders and for a country such as Bolivia of adopting new farm technolo- 368 JOURNALOF ANTHROPOLOGICAL RESEARCH gies for producing staples. The large-scale adoption of new farm technologies for producing staples suited to the needs of smallholders will probably produce mixed effects in the Bolivian countryside. The technologies will increase productivity and the income of smallholders who can adopt. By increasing yields, new farm technologies will likely lower food prices. Faced with lower food prices, those smallholders who cannot adopt will see their incomes drop and may be forced to move to cities or to increase off-farmlabor. This side of the story has been well documented in countries such as India and Indonesia, which have implemented far-reaching changes in the technology for producing staples (Lansing 1991). But there is a parallel,"macro" side to the story that often is ignored.New farm technologies for staples increase productivityand lower food prices. Lower food prices benefit all consumers, particularlythe urbanpoor who spend large propor- tions of their time and income obtainingfood. Lower food prices also enhance the real exchangerate, make exports more competitive,and increase real wages when nominal wages remain constant. The massive adoptionby smallholdersof new farm technologies for producingstaples will hurt those who cannot adopt,but it will help many firms, many people outside of agriculture(mainly the urbanpoor), and many adoptersin the countryside(Hazell and Ramasamy1991). It may be premature to speculate how a technological transformation in smallholder agriculture will play itself out in rural Bolivia or other Andean countries and how different social groups will benefit or suffer from such a transformation. But before holding such a debate, the Bolivian government must reverse centuries of indifference to smallholders and to the rural poor by focusing on technologies that smallholders will find worth adopting.

NOTE

1. We wouldlike to thankE. Perez,J. Barragin,and G. Gray-Molinafor stimulating us throughoutthe preparationof this article.M. Painterhelped us analyzethe historical context of adoptionin Cochabamba,and H. Klein providedmany useful biblio- graphicleads. M. Painter,D. Guillet,and J. Mufiozcommented on an earlierdraft of the article.We wouldalso like to acknowledgethe supportof LuisCarlos Jemio, former directorof the Unidadde Anilisis de PoliticasEcon6micas (UDAPE), Ministry of the Economy,and Federico Martinez, former director of the Unidadde Anilisis de Politicas Sociales(UDAPSO), Ministry of HumanDevelopment, Bolivia. Last, we wouldlike to thankthree anonymousreviewers for their comments.

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