Ali, RubabaBarra, A. FedericoBerg, Claudia N.Damania, RichardNash, John D.Russ, Jason2015-06-022015-06-022015-05https://hdl.handle.net/10986/22003This paper addresses an old and recurring theme in development economics: the slow adoption of new technologies by farmers in many developing countries. The paper explores a somewhat novel link to explain this puzzle -- the link between market access and the incentives to adopt a new technology when there are non-convexities. The paper develops a theoretical model to guide the empirical analysis, which uses spatially disaggregated agricultural production data from Spatial Production Allocation Model and Living Standards Measurement Study survey data for Nigeria. The model is used to estimate the impact of transport costs on crop production, the adoption of modern technologies, and the differential impact on returns of modern versus traditional farmers. To overcome the limitation of data availability on travel costs for much of Africa, road survey data are combined with geographic information road network data to generate the most thorough and accurate road network available. With these data and the Highway Development Management Model, minimum travel costs from each location to the market are computed. Consistent with the theory, analysis finds that transportation costs are critical in determining technology choices, with a greater responsiveness among farmers who adopt modern technologies, and at times a perverse (negative) response to lower transport costs among those who employ more traditional techniques. In sum, the paper presents compelling evidence that the constraints to the adoption of modern technologies and access to markets are interconnected, and so should be targeted jointly.en-USCC BY 3.0 IGOLIVING STANDARDSTRADITIONAL TECHNOLOGYPURCHASE PRICECOSTS OF TRAVELPRICE OF FUELPRODUCTIONINCOMEVEHICLE SPEEDTRANSPORT INFRASTRUCTURETRANSPORTATION COSTSFREIGHT TRANSPORTELASTICITY OF DEMANDINFORMATIONLIQUIDITYELASTICITYPOLITICAL ECONOMYWELFAREINCENTIVESDIMINISHING RETURNSTRAVEL SPEEDVARIABLESMODELSSYSTEMIMPACT OF TRANSPORT COSTSHIGHWAY SYSTEMTAXINPUTSCITIESDECISIONSGROSS VEHICLE WEIGHTRETURNS TO SCALEWEALTHCODESAGRICULTURAL OUTPUTTRANSPORTATION INFRASTRUCTURETRENDSROAD TYPELITERACYPRICE INCENTIVESINCREASING RETURNS TO SCALEKNOWLEDGETRAVEL COSTSDEVELOPMENTNEW TECHNOLOGIESCHOICEVEHICLEDATAINFLUENCETOTAL FACTOR PRODUCTIVITYROADDIGITALCOSTSTRANSPORTATION NETWORKDEVELOPMENT ECONOMICSROAD NETWORKTRANSPORTIMPACT OF TRANSPORTFIXED COSTSPRODUCTIVITYEXTERNALITIESINDUSTRIALIZATIONFAILURESINCREASING RETURNSMARKETSCONNECTIVITYCOSTS PER VEHICLELEARNINGPIXELSCULTURAL CHANGERESEARCHTRAVEL TIMESUTILITYROUTEROAD QUALITYINFRASTRUCTURETECHNOLOGYPRODUCTIVITY GROWTHHUMAN CAPITALTECHNOLOGICAL CHANGERADARTRAVELTRANSPORTATIONWAGESPOLICIESECONOMIC OUTCOMESBASICPARTICIPATIONVALUEPRODUCTION FUNCTIONSELASTICITIESCREDITALTERNATIVE TECHNOLOGIESACCESSIBILITYSYSTEMSRURAL INFRASTRUCTUREUTILITY FUNCTIONAGRICULTUREDECISION MAKINGMEASUREMENTUNDERDEVELOPMENTENDOGENOUS VARIABLESPOLICYPRODUCTION FUNCTIONROADSFUNCTIONAL FORMSWALKINGHIGHWAYTRADERAILROADVEHICLE COSTGOODSTHEORYTRANSPORTATION COSTINVESTMENTCOMPARATIVE ADVANTAGETRANSACTIONS COSTSFUELCOMPETITIVE MARKETSREVENUEINVESTMENTSITNEW TECHNOLOGYATPEDESTRIANSECONOMIC GEOGRAPHYTRANSPORT COSTSTECHNOLOGIESOUTCOMESTRAVEL TIMEFUEL COSTFREIGHTATTRIBUTESINNOVATIONSENGINEERSDEVELOPMENT POLICYWorking PaperWorld Bank10.1596/1813-9450-7272