ADOPTION OF MODERN VARIETIES AND FERTILIZER USE ON RICE IN THE EASTERN TARAI OF NEPAL

Factors influencing the adoption of MV (modern variety) rices and fertilizer in the Tarai of southeastern Nepal were examined through multivariate probit (varietal adoption) and tobit (fertilizer adoption and use rates) regression models. This study reaffirms the finding that the adoption of modern rice technology is highest where irrigation exists. Tenure status and access to credit were significantly related to varietal adoption but family and farm size and the operator's education were not. Similar variables, in addition to fertilizer price, influenced the probability of fertilizer adoption and use rates on rice.     

Risk, uncertainty, and learning in adoption of a crop innovation

Risk and uncertainty have often been suggested as causes of poor adoption of rural innovations, but empirical evidence has been scarce. This study focuses on a new crop‐type, chickpeas, in Western Australia to gather such evidence. The empirical models developed are based on a theoretical framework that conceptualizes adoption as a dynamic decision process involving information acquisition and learning‐by‐doing by growers who vary in their managerial abilities, risk preferences, and their perceptions of the profitability and riskiness of the innovation. Learning encompasses improvements in skill as well as reductions in uncertainty. An annual face‐to‐face survey of over 100 farmers was conducted over 3 years, eliciting the farmers' risk attitudes and their subjective distributions of yields and prices. Two limited dependent variable models, Tobit and Probit, are used to estimate the empirical model. There is a high degree of goodness‐of‐fit for both models. The study provides strong empirical support for the primarily economic character of the adoption decision, and highlight the importance of economic risk in the process. The two risk‐related factors with greatest impact on the adoption decision were risk aversion and relative riskiness of the innovation. Risk aversion tended to reduce adoption, and to do so to a greater extent as relative riskiness and scale increased. Results also reveal the key role that trialing of the innovation plays in adoption.     

Spatial Modeling in Technology Adoption Decisions: The Case of Shuttle Train Elevators

This article empirically models a strategic game of technology adoption of shuttle train grain elevators with information on location of the firm and its competitors. A spatial econometric model illustrates the role of spatial interdependence of rivals' decisions as well as agronomic and competitive variables on discrete adoption decisions. The analysis assesses equilibria conditions that characterize technology adoption, in this case of shuttle train adoption, and the results provide an explanation of shuttle train adoption decisions in the grain handling industry in which spatial competition is critical.     

The Dynamics of Agricultural Biotechnology Adoption: Lessons from series rBST Use in Wisconsin, 1994–2001

This article exploits panel data from Wisconsin dairy farmers to examine the dynamics of recombinant bovine somatotropin (rBST) adoption and to identify the characteristics that distinguish among nonadopters, disadopters, and early and late adopters. Panel methods are used to control for omitted variables and endogenous regressors that call into question coefficient estimates derived from cross-section adoption models. The results, however, confirm previous findings that larger farms with complementary feeding technologies are more likely to adopt rBST, nonadopters appear quite unlikely to become adopters, and rBST adoption will remain at rather moderate levels in Wisconsin.     

Measuring Farm and Market Level Economic Impacts of Improved Maize Production Technologies in Ethiopia: Evidence from Panel Data

While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm‐ and market‐level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K‐shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm‐level maize yield and maize production costs, where the greatest effect appears to be generated when various technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K‐shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.     

Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model*

The main objective of this paper is to evaluate and analyse technical efficiency (TE) levels for hillside farmers under different levels of adoption of soil conservation in El Salvador and Honduras. A switching regression model is implemented to examine potential selectivity bias for high and low level adopters, and separate stochastic production frontiers, corrected for selectivity bias, are estimated for each group. The main results indicate that households with above-average adoption show statistically higher average TE than those with lower adoption. Households with higher adoption have smaller farms and display the highest partial output elasticity for land. Constraints in the land and credit markets are likely explanations for these differences. In addition, all estimated models show that TE has a positive and significant association with education and extension.     

The Adoption and Profitability of rbST on Connecticut Dairy Farms

This work estimates probit and tobit models of the adoption of recombinant bovine somatotropin (rbST) on Connecticut dairy farms and then endogenizes that adoption in estimates of milk production and farm profit rates. The work improves on the current literature by allowing the rbST decision to be both continuous and contingent on other technology adoption decisions. The results show that larger farms, with more productivity technologies, and with younger, more educated farmers, are more likely to adopt rbST. While rbST is shown to significantly increase milk production, there is no evidence that it increases profits on a per cow basis.     

Welfare impacts of maize–pigeonpea intensification in Tanzania

This article examines the driving forces behind farmers’ decisions to adopt improved pigeonpea and maize and estimates the causal impact of technology adoption on household welfare using data obtained from a random cross‐section sample of 613 small‐scale farmers in Tanzania. We use seemingly unrelated and recursive bivariate probit regressions to test the endogeneity and joint decision making of pigeonpea–maize production. A double hurdle model is used to analyze the determinants of the intensity of technology adoption conditional on overcoming seed access constraints. To address the impact of adoption on welfare, the article employs both propensity score matching and switching regression techniques. Results from bivariate probit models show that unobservable factors cause both decisions to be correlated but the finding does not support the conjecture that both decisions are made jointly. Overall the analysis of the determinants of adoption identifies inadequate local supply of seed, access to information, human capital, and access to private productive asset as key constraints for pigeonpea technology adoption. The causal impact estimation from both the propensity score matching and switching regression suggests that maize/pigeonpea adoption has a positive and significant impact on income and consumption expenditure among sample households.     

A MODEL OF NEW ZEALAND APPLE SUPPLY RESPONSE TO TECHNOLOGICAL CHANGE*

A supply response model for New Zealand apples is specified and equations for new plantings, removals, yields and adoption of an innovation are estimated. The model expands on perennial crop models previously estimated by incorporating the time pattern of adoption of a planting innovation and formulation of a measure of yield expectations given technological change.     

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.     

Heterogeneous information exposure and technology adoption: the case of tissue culture bananas in Kenya

Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low. We employ the average treatment effects approach to account for selection bias and extend it by explicitly differentiating between awareness exposure (having heard of a technology) and knowledge exposure (understanding the attributes of a technology). Using a sample of Kenyan banana farmers, we find that estimated adoption parameters differ little when comparing the classical adoption model with one that corrects for heterogeneous awareness exposure. However, parameters differ considerably when accounting for heterogeneous knowledge exposure. This is plausible: while many farmers have heard about TC technology, its successful use requires notable changes in cultivation practices, and proper understanding is not yet very widespread. These results are also important for other technologies that are knowledge‐intensive and require considerable adjustments in traditional practices.     

Technology Adoption and Pest Control Strategies Among UK Cereal Farmers: Evidence from Parametric and Nonparametric Count Data Models

This paper examines the intensity of technology adoption and integrated pest management strategies employed by UK farmers, using both parametric and nonparametric methods. We employ a unique survey dataset collected from UK cereal farmers to assess the determinants of technology adoption in relation to pest management. Our preferred model specification is nonparametric, with models estimated yielding broadly similar results, with some important qualitative differences. All models indicate that total area farmed is positively related to the number of technologies adopted, whereas the number of years of experience of the farmer is negatively related. We also find evidence with our nonparametric specification of significant statistical differences for number of adoptions by region across the UK.     

Modelling the adoption of organic horticultural technology in the UK using Duration Analysis

Duration Analysis, which allows the timing of an event to be explored in a dynamic framework, is used to model the adoption of organic horticultural technology in the UK. The influence of a range of economic and non-economic determinants is explored using discrete time models. The empirical results highlight the importance of gender, attitudes to the environment and information networks, as well as systematic effects that influence the adoption decision over the lifetime of the producer and over the survey period.     

Predicting technology adoption to improve research priority—setting

This paper presents an improved approach for predicting the speed and ceiling of technology adoption, which is a crucial information for research priority setting. In the models it is assumed that both the speed and ceiling of adoption depend on the perceived characteristics of technologies. Knowing the characteristics that have determined adoption in the past provides relevant information about the characteristics which will enable new technologies to be quickly and widely adopted in the future. Using a case study from Meru District in Kenya, it is shown that relative investment, relative risk and relative complexity significantly influenced the speed and ceiling of adoption of dairy technologies in the past. These empirical results are used to predict the speed and ceiling of adoption of potential new dairy technologies to be developed by the Dairy Cattle Research Programme (DCRP) of the Kenya Agricultural Research Institute (KARI). The approach is theoretically sound and based on empirical evidence. It clearly distinguishes promising technologies from less promising technologies and is transparent to participants in priority setting exercises. Allowing for the participation of all interest groups within the research system, the approach improves the quality of the assessment and hence the credibility of results.     

Household adoption behaviour of improved soil conservation: the case of the North Pare and West Usambara Mountains of Tanzania

The mountains in the northeastern part of Tanzania have been experiencing declining soil fertility and severe soil erosion due to increased cultivation and other factors attributed to population pressure. This study gives the main results of an analysis of household adoption behaviour towards the use of improved soil conservation measures. An interdisciplinary analytical framework for analyzing household adoption behaviour is presented. The framework links three components of the adoption decision process: the perception of the erosion problem, the decision to use improved conservation measures and the level of investment or effort devoted to soil conservation among adopters. Data collected from a random sample of 300 heads of households was used to estimate logit models of perception of the erosion problem and of adoption of improved conservation measures, and a Poisson regression model of effort devoted to conservation. The results show that participation in promotional activities of soil and water conservation (SWC) programmes influences the adoption decision process at all three stages. Also, ranking of soil erosion as the priority problem in agricultural production, participation in labour-sharing groups and having off-farm income influence the willingness and ability to use improved soil conservation technologies and the level of soil conservation effort.     

Adoption of Multiple Sustainable Agricultural Practices in Rural Ethiopia

The adoption and diffusion of sustainable agricultural practices (SAPs) has become an important issue in the development‐policy agenda for sub‐Saharan Africa, especially as a way to tackle land degradation, low agricultural productivity and poverty. However, the adoption rates of SAPs remain below expected levels. This study analyses the factors that facilitate or impede the probability and level of adoption of interrelated SAPs, using recent data from multiple plot‐level observations in rural Ethiopia. Multivariate and ordered probit models are applied to the modelling of adoption decisions by farm households facing multiple SAPs, which can be adopted in various combinations. The results show that there is a significant correlation between SAPs, suggesting that adoptions of SAPs are interrelated. The analysis further shows that both the probability and the extent of adoption of SAPs are influenced by many factors: a household’s trust in government support, credit constraints, spouse education, rainfall and plot‐level disturbances, household wealth, social capital and networks, labour availability, plot and market access. These results imply that policy‐makers and development practitioners should seek to strengthen local institutions and service providers, maintain or increase household asset bases and establish and strengthen social protection schemes in order to improve the adoption of SAPs.     

Adoption of alternate wetting and drying (AWD) irrigation as a water-saving technology in Bangladesh: Economic and environmental considerations

Managing scarce irrigation water poses a major challenge globally because of changing climate and a rising population. Alternate wetting and drying (AWD) is widely regarded as a water-saving irrigation technology capable of contributing to sustainable water-use. Existing literature lacks rigorous quantitative analysis of the determinants and effects of AWD adoption. In contrast, applying logit, propensity score matching and multiple regression models to survey data from two drought-prone and groundwater-depleted areas in Bangladesh, this study identifies determinants and effects of AWD adoption and explores policy implications. Age and education-level of household head, access to prior weather information, landownership, topography, and soil-type are found to be significant determinants of AWD adoption. AWD is found to be water-saving, irrigation cost-decreasing and crop yield-increasing. However, AWD adoption in Bangladesh is not widespread. Major policy implications include information dissemination about the use and benefit of AWD through farmers’ education and training for widespread adoption and diffusion of water-saving technologies. A rationally coordinated system of policy measures including significant strengthening of institutional support services, scientific research, rethinking of the cropping-mix and greater use of information technology constitute a sine qua non for achieving sustainable water management.     

The impact of social networks on hybrid seed adoption in India

This article adds to the literature about the impact of social networks on the adoption of modern seed technologies among smallholder farmers in developing countries. The analysis centers on the adoption of hybrid wheat and hybrid pearl millet in India. In the local context, both crops are cultivated mainly on a subsistence basis, and they provide examples of hybrid technologies at very different diffusion stages: while hybrid wheat was commercialized in India only in 2001, hybrid pearl millet was launched in 1965. The analysis is based on surveys of wheat and millet farmers in the state of Maharashtra. Comprehensive data on farmer characteristics and social interactions allow for identifying individual networks, thereby improving upon previous research approaches that employed village-level variables as proxies for network effects. Using econometric models, we find that individual social networks play an important role for technology adoption decisions. While village-level variables may be used as suitable proxies at later diffusion stages, they tend to underestimate the role of individual networks during early phases of adoption.     

Duration Analysis of Technological Adoption in Ethiopian Agriculture

Duration analysis has been used to examine the impact of time‐varying and time‐invariant variables on the speed of adoption of fertiliser and herbicide by smallholder farmers in East and West Shewa in the central highlands of Ethiopia in the 25 years preceding 1996. The estimated models suggest that economic incentives were the most important determinants of the time farmers waited before adopting new technologies; traction power in the form of oxen and infrastructural factors (in particular proximity to markets) also appear to have been important influences, but less so than prices. Other agricultural inputs (area of farmland, labour, credit), extension services and farmers' personal characteristics (education, gender, age) appear to have had little, if any, effect on adoption behaviour. There is also evidence that the speed of adoption of herbicide, on both tef and wheat, was slower than that of fertiliser.     

Oil Palm Expansion among Smallholder Farmers in Sumatra,Indonesia

Many tropical regions are experiencing a rapid growth of oil palm cultivation. In Indonesia, the world's leading palm oil producer, in addition to large companies, smallholder farmers are increasingly engaged in the oil palm sector. Smallholder oil palm cultivation may contribute to income gains and socio‐economic development. However, land‐use decisions by smallholders are not well understood. Without appropriate policies, negative social and environmental consequences can also occur. To improve the knowledge base, we use data about present and past land‐use decisions from a survey of farm households in Sumatra. Employing duration models, we analyse the determinants and dynamics of oil palm adoption among smallholders. We find that independently operating farmers are currently driving growth rates in the oil palm sector. Smallholder adoption decisions are mainly attributable to regional and village level factors. While the current adoption primarily occurs outside of contracts, previous contractual ties between companies and other farmers in the same village play an important role for individual decisions. Beyond initial adoption, we also analyse later expansion decisions. While expanding the oil palm area subsequent to initial adoption is common among all types of adopters, those without previous contracts are found to expand significantly faster. We conclude that the concessions the government has allocated to palm oil companies in the past have initiated oil palm adoption in the small farm sector, but that the ensuing land‐use dynamics are mostly beyond government control. Some wider implications are discussed.