Adoption and Impacts of Sustainable Agricultural Practices on Maize Yields and Incomes: Evidence from Rural Zambia

This paper uses a multinomial endogenous treatment effects model and data from a sample of over 800 households and 3,000 plots to assess the determinants and impacts of adoption of sustainable agricultural practices (SAPs) on maize yields and household incomes in rural Zambia. Results show that adoption decisions are driven by household and plot level characteristics and that the adoption of a combination of SAPs raises both maize yields and incomes of smallholder farmers. Adoption of improved maize alone has greater impacts on maize yields, but given the high cost of inorganic fertiliser that limits the profitability of adoption of improved maize, greater household incomes are associated rather with a package involving SAPs such as maize–legume rotation and residue retention.     

Adoption and welfare impacts of multiple agricultural technologies: evidence from eastern Zambia

Using plot level panel data and multinomial endogenous switching regression, this article analyzes the adoption and welfare impacts of multiple agricultural technologies in eastern Zambia. We adapt a multinomial endogenous switching/treatment effect regression framework to correct for selection bias and endogeneity originating from both observed and unobserved heterogeneity. Results indicate that joint adoption of multiple agricultural technologies had greater impacts on crop yields, household incomes, and poverty than the adoption of individual components of the technology package. Our findings suggest that efforts aimed at raising household incomes and reducing poverty should focus on promoting the adoption of multiple agricultural technologies through provision of improved support services such as extension and input supply.     

Technological and policy options for sustainable agricultural intensification in eastern Uganda

This article presents a bio‐economic household model, which has been developed to assess the potential impacts of agricultural intensification efforts on economic and ecological indicators in eastern Uganda. A study region in the Lake Victoria Crescent was selected with comparative advantages for intensive agricultural production: high agricultural potential, high market access, and high population density. However, current production is characterized by low input–output systems revealing a discrepancy between development opportunities and actual development outcomes. Based on a farmer participatory research approach, production methods were introduced in the study region aimed at fostering sustainable agricultural development. Data from two community surveys, two comprehensive household and plot level surveys, and farm‐trial data were used to develop and calibrate bio‐economic models for four representative household types. Model scenarios reveal that farm households in eastern Uganda would not pursue sustainable intensification under current socio‐economic conditions. The market environment has to be improved substantially, i.e., transaction and transportation costs have to be reduced, innovative credit schemes for smallholders have to be introduced, and alternative forms of labor acquisition have to be promoted, to provide sufficient economic incentives for the adoption of environmentally sound production methods. In addition, agricultural service provision needs to be reformed and more agricultural research is needed for new and better‐targeted technologies.     

The adoption of intensive monocrop horticulture in southern Cameroon

Results from a 1997 survey of 208 households in the humid forest zone of southern Cameroon indicate that African policy makers seeking to intensify agricultural production should focus attention on the horticultural sub‐sector. The survey, which gathered information on horticultural production practices, found that the average expenditure on agro‐chemical inputs by horticultural producers using monocrop production systems was 190US$/ha, which greatly exceeds the FAO reported national average expenditure of 6.50 US$/ha. A logit model of monocrop adoption indicated that the size of land holding per household had a negative effect on adoption, congruent with population‐driven technical change and that increases in unit transportation costs significantly decreased the probability of adoption. These findings suggest that policy makers should target horticultural intensification in areas of higher population density and promote investment in rural roads. The age of the household head had a significant negative and elastic effect on adoption, which in combination with an increase in the cohort of younger farmers in the rural population induced by macro‐economic events contributed to the spread of intensified horticulture. In the study area, roughly two‐thirds of rural households also produce cocoa and the quantity of cocoa produced was positively associated with adoption of intensive horticultural systems suggesting that export crop promotion indirectly facilitated diversification of agriculture. Women's participation in intensive monocrop production was limited and efforts to promote their greater involvement are recommended.     

Tenure security, resource poverty, public programs, and household plot-level conservation investments in the highlands of northern Ethiopia

Land degradation poses a serious problem for the livelihoods of rural producers. Furthermore, there is rarely enough private investment taking place to commensurate the scale of the problem. This article examines the role of tenure insecurity, resource poverty, risk and time preferences, and community‐led land conservation on differentiated patterns of household investment in land conservation in northern Ethiopia. We control for biophysical, household characteristics, market access conditions, and village level factors. Investments in soil bunds and stone terraces are specifically studied so as to capture the link between these various factors and the durability of conservation investments. We introduce the distinction between the determinants of the decision to invest and how much to invest in conservation. Regression results show that publicly led conservation programs seem to significantly stimulate private investment. A host of plot‐level variables and household perceptions of returns on conservation investments, expressed in terms of perceived improvements in land quality and increased crop yields, were found to be critical to the decision to invest and intensify soil conservation. The evidence on the significance of households' attitudes toward risk aversion suggests the important role of risk and the household's risk‐bearing capacity in the decision to intensify conservation measures. At the same time, tenure security indicators and households' resource endowments (resource poverty) had weaker effects in increasing willingness to invest and the level of investment made. The policy implications of these results point to the importance of agricultural research and extension efforts that target technologies which reduce household risk and poverty while enabling sustainable investments in conservation measures by individual households.     

Potential Conflict and Inefficiencies Arising in Agri‐environmental Management

We characterise the welfare implications of uncoordinated policy decisions in the presence of multiple externalities, illustrated with an aquifer. We concentrate on the problem of coordination that can occur when distinct agricultural and water authorities implement their respective policies (to optimise food production and groundwater use) with environmental concerns in mind. We represent this problem as an open‐loop Nash game, which compares the game‐theoretical solution to a centrally planned solution. We show that the inefficiencies arise from differences in the account taken of relevant costs by different authorities. We demonstrate that the magnitude of the inefficiency generated by the absence of coordination of our authorities varies depending on the weights put on environmental benefits by each authority, and discuss the implications of analysis for future research and policy.     

Poverty Reduction Effects of Agricultural Technology Adoption: The Case of Improved Cassava Varieties in Nigeria

We use DNA‐fingerprinting to estimate the poverty reduction effect of adoption of improved cassava varieties in Nigeria. We estimate the counterfactual household income distribution of cassava producers by combining farm‐level treatment effects with a market‐level model. Our results suggest that adoption of improved cassava varieties has led to a 4.6 percentage point reduction in poverty, though this is sensitive to the measurement of adoption status. Therefore, accurate measurement of adoption is crucial for a more credible estimate of the poverty reduction effect of adoption. Our analysis also suggests that farmers who are more likely to be adopters are also likely to face higher structural costs. Addressing structural barriers that make improved technologies less profitable for the poor would therefore be important to increase the poverty reduction effect of improved cassava varieties.     

Effective dimensionality and factors affecting crop-livestock integration in West African savannas: a combination of principal component analysis and Tobit approaches

Crop‐livestock integration (CLI) to improve natural resource management for increased productivity is evolving in Nigeria and West Africa. Processes in the evolution and factors that influence it still need to be well understood. This article proposes and tests a new framework for measuring the multiple dimensionality of CLI. The framework derives a CLI index using the principal components of its most common single measures; it develops geographic information systems (GIS)‐based village‐level ecological and market factors; and it estimates parameters of factors affecting CLI using the derived index as the dependent variable in a Tobit model. The framework is tested using empirical data from 634 farm households in 11 geo‐referenced villages in the Sudan savanna (SS) and northern Guinea savanna (NGS), Nigeria. Along a north–south (SS to NGS) axis, CLI initially increases, peaking around 11.2°N, and then declines. This latitude probably identifies the boundary below which disease challenge constrains traditional livestock production and CLI. This polynomial pattern of CLI is contrary to an expected linear increase along lines of perceived potentials for rain‐fed crop production. Household resources, GIS‐derived village‐level market factors, and institutional factors also significantly affect CLI. Ecological and institutional factors have most impact on the probability of adoption and use intensities of CLI. The incorporation of GIS‐derived market factors with household and institutional variables in an econometric model offers new opportunities for assessing patterns of evolution of CLI, comparing results across sites, and targeting recommendation domains objectively. A comparison with results from more common methods of running independent models for individual indicators of CLI shows that this new framework is an effective way of reducing the multiple dimensionality of CLI to gain quicker, well‐focused knowledge of the processes of agricultural intensification.     

Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia

Adoption of improved crop varieties can lead to multiple benefits to farm households, including increased productivity, incomes, and food consumption. However, possible impacts of adoption on child nutrition outcomes are rarely explored in the literature. This article helps bridge this gap through an impact assessment of the adoption of improved maize varieties (IMVs) on child nutrition outcomes using a recent household survey from rural Ethiopia. The conceptual linkage between IMV adoption and child nutrition is first established using an agricultural household model. Instrumental variable estimation suggests the overall impacts of adoption on child height‐for‐age and weight‐for‐age z‐scores to be positive and significant. Quantile instrumental variable regressions further reveal that such impacts are largest among children with poorest nutrition outcomes. Finally, by combining a decomposition procedure with system of equations estimation, it is found that the increase in own‐produced maize consumption is the major channel through which IMV adoption affects child nutrition.     

Market imperfections,access to information and technology adoption in Uganda: challenges of overcoming multiple constraints

Limited empirical evidence exists on how multiple binding constraints influence the adoption of improved technologies by smallholder farmers. This article uses the case of groundnut variety adoption in Uganda to investigate the role of information, seed supply, and credit constraints in conditioning technology uptake. New data from a household survey in seven groundnut growing districts (n = 945) indicate that 8% of farmers lack information on new varieties, while 18% and 6% of farmers, respectively, cannot adopt mainly due to seed supply and capital constraints. A tobit‐type specification that considers all nonadopters as being uninterested in the technology (i.e., corner solutions) would lead to inconsistent parameter estimates and incorrect conclusions in this context. We therefore estimate a modified multi‐hurdle specification of demand for new varieties, taking into account how information, seed supply, and capital constraints jointly determine adoption probability and intensity. The study reveals new empirical insights on why agricultural technology adoption in Africa has lagged behind: slow uptake is not mainly due to a lack of economic incentives, but rather a reflection of information, seed supply, and credit constraints that prevent farmers from translating their desired demand into adoption of modern varieties. Policy implications are discussed.     

Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement

Policy makers and interest groups have many questions about the use of improved technologies in developing country agriculture. These include the roles of policies, institutions, and infrastructure in the adoption of improved technologies and their impact on productivity and welfare. Most micro‐level adoption studies, however, cannot address these important policy issues. Drawing on an extensive review of the literature on the adoption of agricultural technologies, this article suggests alternative approaches for designing technology adoption studies to make them useful for policy makers. It explores the generic limitations of cross‐sectional adoption studies carried out in small numbers of communities and discusses some problems faced in conducting such studies. Recommendations include the use of sampling approaches that allow data from microstudies to be generalized to higher levels of aggregation, adherence to clearly defined terms that are standardized across studies, and careful examination of the assumptions that often underlie such studies.     

Resource saving and productivity enhancing impacts of crop management innovation packages in Ethiopia

Crop management innovations are often not discrete fixed stand‐alone options—and their adoption may imply various combinations and adaptations. This potentially confounds their impact assessment. This article assesses the resource saving and productivity enhancing impacts of a crop management package revolving around minimum tillage in maize‐based farming systems in northwest Ethiopia. An endogenous switching regression model was applied to plot‐ and household‐level survey data collected from 290 rural households operating 590 maize plots during the 2012 production year. Controlling for variations in plot and household characteristics, the average effect of minimum tillage package (minimum tillage package) on maize productivity is 0.44 t/ha. Compared to conventional practice (CP), adoption of the MTP decreased the average male and female labor use in maize production by 14.4 and 8.2 person‐days per ha, respectively. Similarly, MTP adoption decreased draft power use for land preparation by 13.2 pair of oxen‐days per ha. Compared to CP, in general, there is a considerable short‐run maize productivity gain and reduction in labor and draft power use under MTP.     

The impact of marketing systems on soil sustainability of agriculture in developing countries: a method and an application

This article is concerned with soil‐sustainability problems of agriculture in developing countries, in particular with soil erosion. The aim of our study is to develop a comprehensive model that explains the adoption of sustainable agricultural practices with respect to soil conservation. Our approach includes the following special features: (a) the model is comprehensive in that it includes a large number of institutional, personal–social, economic, and physical explanatory variables; (b) particular attention is paid to the influence of marketing systems on the adoption of sustainable agricultural practices, which to our knowledge has been neglected in past research; (c) the concept of adopting sustainable agricultural practices (ASAP) is differentiated into a limited number of basic components of soil conservation; and (d) the model is estimated by Principal Component Regression, which enhances efficient estimation of the impact of many explanatory variables on ASAP. Our model is applied to Cabuyal hillside farming in Colombia. The application demonstrates the usefulness of the proposed model. ASAP is differentiated into three basic components: soil‐disturbance control, soil‐protection practices, and run‐off control. It appears that soil‐disturbance control is particularly influenced by farmers' characteristics, such as education and managerial variables. The second component, soil‐protection practices, appears to be strongly influenced not only by farmers' managerial variables but also by their relationship with their environment, in particular marketing institutions. The third soil‐conservation component, run‐off control, is influenced by the physical characteristics of the plot and by the available farm labor. Our empirical results demonstrate the usefulness of the proposed model in designing agricultural policies, because it can determine which variables are more likely to influence the adoption of a specific type of soil conservation.     

The Economics of Sustainable Land Management Practices in the Ethiopian Highlands

This article uses data from household‐ and plot‐level surveys conducted in the highlands of the Tigray and Amhara regions of Ethiopia. We examine the contribution of sustainable land management (SLM) practices to net value of agricultural production in areas with low vs. high agricultural potential. A combination of parametric and non‐parametric estimation techniques is used to check result robustness. Both techniques consistently predict that minimum tillage (MT) is superior to commercial fertilisers (CFs), as are farmers’ traditional practices (FTPs) without CFs, in enhancing crop productivity in the low agricultural potential areas. In the high agricultural potential areas, in contrast, use of CFs is superior to both MT and FTPs without CFs. The results are found to be insensitive to hidden bias. Our findings imply a need for careful agro‐ecological targeting when developing, promoting and scaling up SLM practices.     

Farmers' perceptions of benefits and factors affecting the adoption of improved dual-purpose cowpea in the dry savannas of Nigeria

This study links participatory research methods, geographic information systems (GIS) techniques, village and household‐level surveys, and a tobit analysis to examine the adoption and impact issues related to a new technology, improved varieties of dual‐purpose cowpea (IDPC), developed by International Institute of Tropical Agriculture (IITA) and International Livestock Research Institute (ILRI) and recently released in Nigeria. The article analyzes factors affecting the adoption and impact of the technology across different socioeconomic domains as defined by degree of market access and population density. The results show multiple benefits from this flexible leguminous crop, many of which relate to the fodder and soil fertility‐enhancing aspects of IDPC rather than higher grain yields per se. The intensity of adoption was affected by different village‐ and household‐level factors in each socioeconomic domain, allowing more sharply defined recommendation domain‐targeting strategies. The multiple research approaches taken also provided useful lessons at different system levels regarding the benefits of, and perceived problems with, this technology for researchers, development practitioners, and policy makers. The collaborative research approaches taken in this study are helping to close the “feedback loop” from farmers back to researchers and others attempting to disseminate the technology, and by doing so, should contribute to faster and more widespread uptake of this technology.     

Nontraditional crops,traditional constraints: The long‐term welfare impacts of export crop adoption among Guatemalan smallholders

This article documents the long‐term welfare effects of household nontraditional agricultural export (NTX) adoption. We use a panel dataset that spans the period 1985–2005, and employ difference‐in‐differences estimation to investigate the long‐term impact of nontraditional agricultural export adoption on changes in household consumption status and asset position in the Central Highlands of Guatemala. Given the heterogeneity in adoption patterns, the analysis differentiates the impact estimates based on a classification of households that takes into account the timing and duration of nontraditional agricultural export adoption. The results show that while, on average, welfare levels have improved for all households irrespective of adoption status and duration, the extent of improvement has varied across groups. Long‐term adopters exhibit the smallest increase in the lapse of two decades, in spite of some early gains. Conversely, early adopters who withdrew from nontraditional agricultural export production after reaping the benefits of the boom period of the 1980s are found to have fared better and shown greater improvements in durable asset position and housing conditions than any other category.     

Challenging Small‐Scale Farming: A Non‐Parametric Analysis of the (Inverse) Relationship Between Farm Productivity and Farm Size in Burundi

We use a non‐parametric approach to investigate the (inverse) relationship between farm productivity and farm size. A kernel regression is used on data of mixed cropping systems to study the determinants of production including different factors that have been identified in literature as missing variables in the testing of the inverse relationship such as soil quality, location and household heterogeneity. Household data on farm activities and crop production were gathered from 640 households in 2007 in two Northern provinces of Burundi. Our results do not reject the findings of an inverse relationship between farm size and productivity. However, we find that size returns vary substantially with farm size, that is, between 0.2 for the smallest farms and 0.8 for the largest farms. Other factors that significantly affect production include soil quality. Finally, we find a significant positive association between food security and farm size.     

Improving the speed of adoption of agricultural technologies and farm performance through farmer groups: evidence from the Great Lakes region of Africa

The article examines the effect of membership in farmer groups (MFG) on adoption lag of agricultural technologies and farm performance in Burundi, the Democratic Republic of Congo and Rwanda. We use duration and stochastic production frontier models on farm household data. We find that the longer the duration of MFG, the shorter the adoption lag and much more so if combined with extension service delivery. Farmer groups function as an important mechanism for improving farm productivity through reduced technical inefficiency in input use. We discuss policy implications under which farmer groups are a useful channel to reduce adoption lag, and the means through which improved farm performance can be achieved.     

Agricultural diversification and integrated pest management in Bangladesh

We study factors associated with a shift toward diversified, high‐valued vegetable crops and the incentives associated with the use of IPM methods for vegetable producers in Bangladesh. The primary objective is to measure how IPM technologies affect the crop and technology choices of low‐income rice farmers. A three‐season household optimisation model is used to study crop and technology choice under price and yield uncertainty. The model is parameterised using data from vegetable farms and experimental IPM trials conducted in Bangladesh. Simulation results show that access to IPM technology and IPM availability combined with access to credit increase household welfare and lead to higher rates of vegetable adoption. Off‐farm employment opportunities work against vegetable cultivation and IPM use by risk‐averse farmers. Implications for policy and extension efforts are highlighted.     

Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data

We estimate a spatially explicit model of the forest clearance process among smallholder farmers in an agricultural frontier of southern Mexico. Our analysis takes as its point of departure a simple utility‐maximising model that suggests many possible determinants of deforestation in an economic environment characterised by missing or thin markets. Hypotheses from the model are tested on a data set that combines a time series of satellite imagery with data collected from a survey of farm households whose agricultural plots were geo‐referenced using a global positioning system (GPS). We implement a survival analysis to identify the effect of household level explanatory variables on the probability of deforestation. This approach allows us to introduce a measure of the time until clearance as a covariate, thereby affording a control for the effect of potentially important explanatory variables that vary through time but are not directly observable. In addition to identifying several variables relevant for policy analysis, including household demographics, proximity to roads, and government provision of agricultural support, model results suggest that the deforestation process is characterised by non‐linear duration dependence, with the probability of forest clearance first decreasing and then increasing with the passage of time.