The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan

This article employs a propensity score‐matching approach to examine the direct effects of adoption of Bacillus thuringiensis (Bt) cotton on yields, pesticide demand, household income and poverty, using cross‐sectional data from a survey of farmers in the Punjab province of Pakistan. Generally, the findings reveal that adoption of the new technology exerts a positive and significant impact on cotton yields, household income and poverty reduction, and a negative effect on the use of pesticides. The positive and significant impact of the technology on yields and household income is consistent with the potential role of new agricultural technology in directly reducing rural poverty through increased farm household income.     

The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana

This study employs the propensity score matching model to examine the impact of the adoption of water conservation and intensification technologies on farm output and income among small-scale lowland rice farmers in the Northern Region of Ghana. The matching was conducted based on the Mahalanobis distance combined with the propensity score. Balancing tests by checking the mean standardized absolute bias in the matched sample were conducted as well as a sensitivity analysis was conducted to check for hidden bias due to unobservable selection. The empirical results show a positive and significant impact of the adoption of bunds technology on input demand as well as a positive but insignificant impact on output supply and net returns. Adopters of the dibbling technology were found to have higher output supply, whereas no statistically significant difference was found between the incomes of adopters and nonadopters of dibbling seed method. The results, however, reveal a positive and significant effect on output and net returns when the dibbling method is combined with intensified weeding. The estimates were found to be relatively insensitive to hidden bias.     

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.     

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.     

Diffusion and spillover of new technology: a heterogeneous-agent model for cassava in West Africa

Understanding what determines the geographic spread of innovations can help guide the funding and implementation of research and extension programs. Our approach uses household survey data as model parameters, to simulate behavior across the entire surveyed population and avoid the aggregation bias associated with representative‐farm models. Such a “heterogeneous agent” approach allows us to infer the distribution of a technology's impacts across one set of households, and predict the potential for spreading to another set that shares similar characteristics with respect to natural resource endowments and farming systems. We apply the technique to new cassava varieties in West Africa, finding a strongly poverty‐alleviating impact, with substantial spillover potential from Nigeria to neighboring countries.     

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.     

Mobile money,agricultural marketing,and off‐farm income in Uganda

Mobile money (MM) services can contribute to welfare gains in smallholder farm households. Previous research showed that one important pathway for these MM‐related welfare gains is through higher remittances received from relatives and friends. Here, the role of other impact pathways is examined, especially focusing on agricultural marketing and off‐farm economic activities. The analysis builds on panel data from smallholder coffee farmers in Uganda. Regression models show that the adoption of MM technology has contributed to higher household incomes and consumption levels. Off‐farm income gains are identified to be an important pathway, also beyond remittances. Typical off‐farm income sources are small businesses in trade, transport, and handicrafts, which benefit from novel savings and money transfer opportunities through MM. In terms of agricultural marketing, MM users sell a larger proportion of their coffee as shelled beans to buyers in high‐value markets, instead of selling to local traders immediately after harvest. MM services help to reduce cash constraints and facilitate transactions with buyers from outside local regions. In conclusion, MM can contribute to rural development through various important pathways. Analysis of adoption patterns suggests that MM services are socially inclusive.     

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.     

Land degradation, drought and food security in a less-favoured area in the Ethiopian highlands: a bio-economic model with market imperfections

This paper presents a bio‐economic model of Andit Tid, a severely degraded crop‐livestock farming system with high population density and good market access in the highlands of Ethiopia. Land degradation, population growth, stagnant technology, and drought threaten food security in the area. Drought or weather risk appears to have increased in recent years. The bio‐economic model is used to analyse the combined effects of land degradation, population growth, market imperfections and increased risk of drought on household production, welfare and food security. We find that the indirect effects of drought on household welfare through the impact on crop and livestock prices are larger than the direct production effects of drought. Provision and adoption of credit for fertiliser, although risky in itself, may lead to increased grain production and improved household welfare and food security. Provision of credit may have a negative effect on conservation incentives but this effect may be mitigated by linking a conservation requirement to the provision of credit for fertiliser.     

The complex dynamics of smallholder technology adoption: the case of SRI in Madagascar

This article explores the dynamics of smallholder technology adoption, with particular reference to a high‐yielding, low external input rice production method in Madagascar. We present a simple model of technology adoption by farm households in an environment of incomplete financial and land markets. We then use a probit model and symmetrically censored least squares estimation of a dynamic tobit model to analyze the decisions to adopt, expand, and disadopt the method. We find that seasonal liquidity constraints discourage adoption by poorer farmers. Learning effects—both from extension agents and from other farmers—exert significant influence over adoption decisions.     

Household welfare implications of sustainable land management practices among smallholder farmers in Ghana

This study employs farm household data to examine the impact of adoption of sustainable land management practices on consumption and poverty outcomes using multivalued treatment effects approaches. The generalized propensity score approach was employed to account for selectivity bias due to observed characteristics among households. Using a doubly robust treatment effects estimator, we found that increasing intensity of adoption improved per capita consumption expenditure, reduced poverty headcount and poverty gap among farm households. The results of the multivalued treatment effects approach revealed significant differences between adopters of different adoption intensities, a finding that is not possible with binary treatment effect approaches. The findings also revealed that the average treatment effect of moving from low intensity to high intensity adoption levels differed across quantiles of per capita consumption. We also use a dose-response function to demonstrate that the treatment effect of intensity of adoption on per capita consumption and poverty outcomes is nonlinear, with optimal adoption level occurring between 60–70 % of adoption intensity dose. It is therefore recommended that initial government support in sustainable land management is necessary to sustain and upscale individual household efforts towards investment in sustainable land management.     

Is off-farm income reforming the farm? Evidence from Mexico

Does access to off-farm income complement or compete with agricultural production? This article explores the effect of off-farm income on agricultural production activities, using data from the 2003 Mexico National Rural Household Survey. We first discuss the theoretical conditions under which access to off-farm income may influence production in an agricultural household model. Instrumental-variable (IV) estimation methods are then used to test whether agricultural production activities, technologies, and input use differ between households with and without access to off-farm income. We find that off-farm income has a negative effect on agricultural output and the use of family labor on the farm, but a positive impact on the demand for purchased inputs. There is also a slight efficiency gain in households with access to off-farm income. Findings offer insights into how household production evolves as rural households increasingly engage in off-farm income activities.     

Adding value to spatially managed inputs by understanding site-specific yield response

Many mechanized crop producers and agribusinesses are fascinated with precision agriculture technology, but adoption has lagged behind the expectations. Among the reasons for slow adoption of precision agriculture technology is that initial users focused excessively on in‐field benefits from variable‐rate fertilizer application using regional average fertilizer recommendations. This article illustrates how greater use of site‐specific crop response information can improve variable rate input application recommendations. Precision agriculture is spatial information technology applied to agriculture. The technologies include global position systems (GPS), geographic information systems (GIS), yield monitoring sensors, and computer controlled within‐field variable rate application (VRA) equipment. Experimentation with these technologies is occurring everywhere there is large scale mechanized agriculture. Commercial use has been greatest in the US, where 43% of farm retailers offered VRA services in 2001. Except for certain high‐value crops like sugar beet, farmer adoption of VRA has been modest. The farm level profitability of VRA continues to be questionable for bulk commodity crops. The theoretical model and illustration presented here suggest that VRA fertilization has not yet reached its profitability potential. Most VKA field trials to date have relied upon existing state‐wide or regional input rate recommendations. Unobserved soil characteristics can potentially interact with an input to make its effect on yield vary site‐specifically within fields. Failure to use site‐specific response functions for VRA applications may lead to a misallocation of inputs just as great as that which results from using uniform applications instead of VRA. Agricultural economists have a long history of estimating output response to input applications. Several have started to develop tools to estimate site‐specific responses from yield monitor and other precision agriculture data. Likewise, agricultural economists have developed an important body of research results on information value based on managing variability—typically in temporal settings. With these tools, a major potential exists to develop further benefits from precision agriculture technologies that permit truly spatially tailored input applications.     

Policies for sustainable development in the hillside areas of Honduras: a quantitative livelihoods approach

In this article, we use data for 376 households, 1,066 parcels, and 2,143 plots located in 95 villages in the hillside areas in Honduras to generate information needed by decision makers to assess the needs and opportunities for public investments, and design policies that stimulate natural resource conservation. We develop a quantitative livelihood approach, using factor and cluster analysis to group households based on the use of their main assets. This resulted in seven household categories that pursue similar livelihood strategies. We use a multinomial logit model to show that livelihood strategies are determined by comparative advantages as reflected by a combination of biophysical and socioeconomic variables. While 92% of the rural hillsides population in Honduras lives on US$1.00/capita/day or less, households that follow a livelihood strategy based on basic grain farming are the poorest because they often live in isolated areas with relatively poor agro‐ecological and socioeconomic conditions. Opportunities for off‐farm work tend to be limited in these areas and household strategies that combine on‐farm work with off‐farm work earn higher incomes. Per capita incomes can be increased by improving road infrastructure, widening access to land, policies that reduce household size and dependency ratios, and adoption of sustainable land management technologies that restore soil fertility. We used probit models to show that the latter can be promoted by agricultural extension programs and land redistribution. Investments in physical assets should be directed toward households that pursue livelihood strategies based on off‐farm employment or coffee production, while agricultural training programs are best focused on livestock producers.     

Cash crop liberalization and poverty alleviation in Africa: evidence from Malawi

This article uses the case of burley tobacco liberalization in Malawi to investigate the efficacy of cash crop liberalization as an instrument for poverty alleviation in sub‐Saharan Africa. The principal justification for cash crop liberalization is that markets allow farm households to increase their incomes by producing that which provides the highest return to their productive resources and use the cash to buy consumption goods. Using a latent welfare model, we find that households that selected to grow cash crops had higher incomes than those that did not grow cash crops. However, we also find that due to the lumpiness and seasonality of cash crop incomes, higher household incomes, while increasing food purchases did not significantly affect per capita food intake. Irrespective of participation in cash crops, for much of the cropping season rural households seem to rely more on nonfarm income for expenditure and consumption smoothing.     

Ex post impacts of improved maize varieties on poverty in rural Ethiopia

Public agricultural research has been conducted in Africa for decades. While many studies have examined its aggregate impacts, few have investigated how it affects the poor. This paper helps fill this gap by applying a new procedure to explore the ex post impacts of improved maize varieties on poverty in rural Ethiopia. Plot‐level yield and cost changes due to adoption are first estimated using instrumental variable and marginal treatment effect techniques where possible heterogeneity is carefully accounted for. A backward derivation procedure is then developed to link treatment effect estimates with an economic surplus model to identify the counterfactual household income that would have existed without improved maize varieties. Poverty impacts are finally estimated by exploiting the differences between observed and counterfactual income distributions. Improved maize varieties have led to a 0.8–1.3 percentage drop of poverty headcount ratio and relative reductions of poverty depth and severity. However, poor producers benefit the least from adoption due to the smallness of their land holdings.     

Supply response in Ethiopia: accounting for technical inefficiency

Few empirical studies of supply response using the profit function have accounted for technical inefficiency. Using farm‐level panel data from Ethiopia, this study examines the effect of incorporating technical inefficiency in estimating the supply response of peasant farmers. Two systems of output supply and input demand equations are estimated and compared: the conventional model in which technical efficiency is assumed and another in which technical inefficiency is explicitly incorporated. The model with technical inefficiency is preferred on grounds of theoretical consistency and improved estimates, although model comparison tests are not conclusive. Incorporation of inefficiency generally increases the magnitudes and the statistical significance of own price elasticities, substantially so in the case of fertilizer and fertilizer‐intensive crops, and alters the priority attached to nonprice factors. An important result is that only the specification with inefficiency reveals a significant effect of access to extension services on output. Only this specification finds that output increases with household size, which one expects as the farms in the sample are largely subsistence and producing for own consumption. Furthermore, the results demonstrate that farmers' response to incentives is considerably restricted by inefficiency, suggesting that the traditional model would overstate response by excluding the efficiency variable.     

Estimating returns to soil conservation adoption in the northern Ethiopian highlands

Land degradation in the form of soil erosion and nutrient depletion presents a threat to food security and sustainability of agricultural production in many developing countries. Governments and development agencies have invested substantial resources to promote soil conservation practices as part of an effort to improve environmental conditions and reduce poverty. However, limited rigorous empirical work has been done on the economics of soil conservation technology adoption. This article investigates the impact of stone bunds on value of crop production per hectare in low and high rainfall areas of the Ethiopian highlands using cross-sectional data from more than 900 households, with multiple plots per household. We have used modified random effects models, stochastic dominance analysis (SDA), and matching methods to ensure robustness. The parametric regression and SDA estimates are based on matched observations obtained from the nearest neighbor matching using propensity score estimates. This is important, because conventional regression and SDA estimates are obtained without ensuring that there actually exist comparable conserved and nonconserved plots on the distribution of covariates. We use matching methods, random effects, and Mundlak's approach to control selection and endogeneity bias that may arise due to correlation of unobserved heterogeneity and observed explanatory variables.
We find that the three methods tell a consistent story. Plots with stone bunds are more productive than those without such technologies in semi-arid areas but not in higher rainfall areas, apparently because the moisture conserving benefits of this technology are more beneficial in drier areas. This implies that the performance of stone bunds varies by agro-ecology type, suggesting the need for designing and implementing appropriate site-specific technologies.     

Technology adoption,impact, and extension in developing countries’ agriculture: A review of the recent literature

Given the stagnant agricultural productivity and persistent food insecurity in low-income countries—notably in sub-Saharan Africa (SSA)—there has been continued interest in the adoption of new technology and its impact on productivity in these regions. To increase crop yields and sustain yield gains, recent case studies of technology adoption unanimously recommend the adoption of integrated farm management systems, particularly in SSA. On the other hand, there have been increasing numbers of studies on social network or farmer-to-farmer technology extension. These studies explore more efficient extension systems than traditional public-sector extension approaches. This article reviews both recent case studies of technology adoption and its productivity impacts as well as studies on agricultural extension to identify common findings, shortcomings, and major remaining issues.     

The impact of integrated aquaculture–agriculture on small-scale farms in Southern Malawi

Sustainable agricultural intensification is an urgent challenge for Sub-Saharan Africa. One potential solution is to rely on local farmers' knowledge for improved management of diverse on-farm resources and integration among various farm enterprises. In this article, we analyze the farm-level impact of one recent example, namely the integrated aquaculture–agriculture (IAA) technologies that have been developed and disseminated in a participatory manner in Malawi. Based on a 2004 survey of 315 respondents (166 adopters and 149 nonadopters), we test the hypothesis that adoption of IAA is associated with improved farm productivity and more efficient use of resources. Estimating a technical inefficiency function shows that IAA farms were significantly more efficient compared to nonadopters. IAA farms also had higher total factor productivity, higher farm income per hectare, and higher returns to family labor.