Determinants of economic well-being among U.S. farm operator households

Participation in government programs has a mild impact on the economic well‐being of U.S. farm households. Major factors that determine farm household prosperity are the primary operator's education level and ethnicity, education level of the spouse, and other characteristics such as forward purchasing of inputs, use of contract shipping of products, having a succession plan, farm ownership, and location in a metro area. This article uses the 2001 Agricultural Resource Management Survey (ARMS) as well as relative and an absolute measure to assess U.S. farm households' economic well‐being. The relative measure compares the income and wealth position of farm households relative to median income and median wealth of the general population. The absolute measure adds annualized wealth to a farm household's income.     

Welfare implications of reduced government subsidies to farm families: accounting for fringe benefits

In the past three decades, farm families have relied on government payments and off‐farm income to reduce income risk and increase total household income. Studies have shown that, as the income effect dominates, government payments tend to reduce off‐farm labor of farm operators and spouses. But that may not be true if one accounts for fringe benefits associated with off‐farm employment. Additionally, with looming budget deficits and the possibility of a reduction in decoupled government payments, farm families may be facing an altered economic environment. Our study addresses this issue by examining the links between government farm program payments and the ever‐important role of fringe benefits in the off‐farm employment of farm couples. Results from farm‐level data actually show that the marginal effect of government payments on hours worked off‐farm will decrease in magnitude when accounting for fringe benefits, ceteris paribus. These results support the notion that farm households’ welfare loss stemming from reduced decoupled payments may be overstated when models exclude fringe benefits from the estimation of off‐farm labor supply.     

Agriculture–nutrition linkages in farmers’ communication networks

To date, little is known about how information flows within farmer groups and how extension interventions could be designed to deliver combined information on agriculture and nutrition. This study uses unique network data from 815 farm households in Kenya to investigate the structure and characteristics of agricultural and nutrition information networks within farmer groups. Dyadic regressions are used to analyze the factors influencing link formation for the exchange of agricultural and nutrition information. In addition, we apply fixed‐effects models to identify the characteristics of central persons driving information exchange in the two networks, as well as potentially isolated persons, who are excluded from information networks within their farmer groups. Our results show that nutrition information is exchanged within farmer groups, although to a limited extent, and mostly flows through the existing agricultural information links. Thus, diffusing nutrition information through agricultural extension systems may be a viable approach. Our findings further suggest that group leaders and persons living in central locations are important drivers in the diffusion of information in both networks and may thus serve as suitable entry points for nutrition‐sensitive extension programs. However, we also identify important heterogeneities in network characteristics. In particular, nutrition information is less often exchanged between men and women, and some group members are completely isolated from nutrition information exchange within their farmer groups. We derive recommendations on taking these differences in network structure and characteristics into account when designing nutrition‐sensitive extension programs.     

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.     

Bias from Farmer Self‐Selection in Genetically Modified Crop Productivity Estimates: Evidence from Indian Data

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm‐level yield gains from GM crop adoption. Yet most farm‐level studies in the literature do not control for farmer self‐selection, a potentially important source of bias in such estimates. We use farm‐level panel data from Indian cotton farmers to investigate the yield effect of GM insect‐resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self‐selection. A production function is estimated using a fixed‐effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross‐sectional estimates of the yield effect of Bt cotton, which do not control for self‐selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.     

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.     

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.     

Assessing the Forecasting Performance of a Generic Bio‐Economic Farm Model Calibrated With Two Different PMP Variants

Using linear programming in bio‐economic farm modelling often results in overspecialised model solutions. The positive mathematical programming (PMP) approach guarantees exact calibration to base year data but the forecasting capacity of the model is affected by necessary but arbitrary assumptions imposed during calibration. In this article, a new PMP variant is presented which is based on less arbitrary assumptions that, from a theoretical point of view, are closer to the actual decision making of the farmer. The PMP variant is evaluated according to the predictions of the bio‐economic farm model, developed within the framework for integrated assessment of agricultural systems in Europe (SEAMLESS). The forecasting capacity of the model calibrated with the standard PMP approach and the alternative PMP variant, respectively, is tested in ex‐post experiments for the arable farm types of Flevoland (the Netherlands) and Midi‐Pyrenees (France). The results of the ex‐post experiments, in which we try to simulate farm responses in 2003 using a model calibrated to 1999 data, show that the alternative PMP variant improves the forecasting capacity of the model in all tested cases.     

Impact of conservation agriculture technology on household welfare in Zambia

This article examines the determinants and impact of conservation agriculture (CA) technology adoption on farm household welfare in Zambia. To account for selection bias from both observable and unobservable factors, an endogenous switching regression model is employed to estimate the impact of the technology on continuous outcomes like farm output, throughput accounting ratio (TAR), poverty gap, and severity of poverty. A recursive bivariate probit model is however used for the estimation of impact of adoption on a binary outcome like poverty headcount. The empirical findings demonstrate that the adoption of CA technology increases maize output, and farm TAR and reduces household poverty. Moreover, the results reveal that farmers’ years of schooling, social networks, access to credit, extension services, and machinery as well as soil quality positively influence adoption of CA technology.     

On the foundation of agricultural policy research in the United States

This paper identifies three scientific research programs in agricultural economics. The farm management approach (1870-1933), the farm problem approach (1933-1982) and the domestic and global welfare approach (1982-). In respect to agricultural policy research two competitive research programs developed out of the farm crisis of the 1920s. One program argued for government intervention in agriculture. The other argued for stability in the general economy. The former program degenerated during the 1970s because of countervailing empirical evidence and a change in the understanding of positive economics. The latter program stayed progressive by adding the international dimension and by applying welfare economic analysis. Two other important factors influenced the development of agricultural policy. First, the unique institutional set up of the land grant system in which agricultural economics was founded as an applied science with a bias to help farmers. Second, the convergence of agricultural economics towards general economics that shifted the approach from applied to basic.     

Technical Efficiency among Peasant Farmers Participating in Natural Resource Management Programmes in Central America

This study examines the extent to which technical efficiency (TE) is related to activities promoted by two natural resource management programmes recently completed in Central America. Data for a total of 639 farms operating in the hillsides of El Salvador and Honduras are used to estimate a household‐level input‐oriented stochastic distance frontier simultaneously with a TE effects model. The main finding of this study is that improvements in TE are financially beneficial to farm households while also contributing to environmental sustainability. The results also reveal a positive association between productivity and output diversification, and a positive relationship between TE and off‐farm income, human capital and agricultural extension.     

Macro–micro feedback links of water management in South Africa: CGE analyses of selected policy regimes

The pressure on an already stressed water situation in South Africa is predicted to increase significantly under climate change, plans for large industrial expansion, ongoing rapid urbanization, and government programs to provide access to water to millions of previously excluded populations. This article employs a general equilibrium approach to examine the economy‐wide impacts of selected macro and water‐related policy reforms on water use and allocation, rural livelihoods, and economy at large. The analyses reveal that implicit crop‐level water quotas reduce the amount of irrigated land allocated to higher‐value horticultural crops and create higher shadow rents for production of lower‐value water‐intensive field crops, such as sugarcane and fodder. Accordingly, liberalizing local water allocation within irrigation agriculture is found to work in favor of higher‐value crops, and expand agricultural production and exports and farm employment. Allowing for water trade between irrigation and nonagricultural uses fuelled by higher competition for water from urbanization leads to greater water shadow prices for irrigation water with reduced income and employment benefits to rural households and higher gains for nonagricultural households. The analyses show difficult trade‐offs between general economic gains and higher water prices, which place serious questions on subsidizing water supply to irrigated agriculture, i.e., making irrigation subsidies much harder to justify.     

Adoption of farm‐based irrigation water‐saving techniques in the Guanzhong Plain,China

This article analyses adoption of farm‐based irrigation water saving techniques, based on a cross‐sectional data set of 357 farmers in the Guanzhong Plain, China. Approximately 83% of the farmers use at least one farm‐based water‐saving technique. However, the traditional, inefficient techniques border and furrow irrigation are still prevalent whereas the use of advanced, more efficient techniques is still rather rare. We develop and estimate an adoption model consisting of two stages: awareness of water scarcity and intensity of adoption. We find that awareness of water scarcity and financial status enhance adoption of more advanced techniques whereas access to better community‐based irrigation infrastructure discourages it. We furthermore find both community‐based irrigation infrastructure and farm‐based irrigation water‐saving techniques have mitigating effects on production risk. From the results it follows that adoption can be stimulated via financial support and via extension aimed at enhancing awareness of water scarcity.     

Integrated assessment of water framework directive nitrate reduction measures

This article illustrates a statistical approach for deriving farm economic impacts of policy options aiming to reduce nitrate diffuse pollution. Building upon Fezzi et al. (2008) , who assess the costs of Water Framework Directive‐related measures on farm accounts data, we estimate regression models allowing such costs to be predicted for any region for which land use patterns and livestock numbers are known. We derive economic impacts in terms of changes in farm gross margin for (a) reducing inorganic fertilizer application, (b) reducing livestock stocking rates, and (c) converting arable land to ungrazed grassland. A case study of the agriculturally diverse Yorkshire Derwent catchment, in the North of England, demonstrates the overall approach. In addition, for this illustration, we combine these cost estimates with prediction of the water quality changes arising from each measure, derived via an integrated hydrological model of the Derwent. This allows a comparison of cost‐effectiveness. Finally, we implement our spatially explicit approach to target the measures to specific subcatchments identified as being of particular environmental policy interest.     

Non-parametric estimation of decision makers' risk aversion

A new non‐parametric method to estimate a decision maker's coefficient of absolute risk aversion from observed economic behaviour is explained. The method uses the expected value‐variance (E‐V) framework and quadratic programming. An empirical illustration is given using Norwegian farm‐level data.     

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.     

Internal and contextual drivers of dairy restructuring: evidence from French mountainous areas and post‐quota prospects

The end of the milk quota system in Europe has resulted in substantial structural changes to the dairy industry, calling its future into question, especially in mountainous areas. This study analyzes the internal and contextual factors that influence dairy restructuring in French mountainous areas. Three complementary logit models are used to specify farmer decisions (e.g., dairy production exit, stability, and growth). Original and exhaustive geo‐located administrative datasets are combined to create a farm longitudinal dataset and characterize farm‐restructuring patterns on a fine geographical scale. Farm size, corporate legal status, and specialization are positively associated with farm growth. Viable diversification strategies through either farm processing or agro‐environmental scheme contracting are also highlighted. Farm sustainability is supported by the economic success of the local industry and the propensity to adopt extensive practices. With respect to public policy, dairy policy appears to have the strongest impact. Thus, the liberalization of dairy policy threatens the future of dairy farming, particularly in areas with low milk density and no production under labels. This work calls for a policy that promotes the collective dimension of dairy farm performance. The current rural development policy alone may be insufficient to support farms’ long‐term sustainability.     

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.     

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.     

Determinants of herbicide use in rice production in the Philippines

This study identifies farm‐specific and market factors affecting the adoption of herbicides and the level of herbicide use by rice farmers in the Philippines. This requires the application of a modified version of Heckman's two‐step method to estimate a random‐effects double‐hurdle model for unbalanced panel data. The age of the farmer, household size, and irrigation use are significant determinants of the decision of farmers to adopt herbicides as an alternative to manual weeding, while economic variables such as the price of herbicides, total income, and access to credit determine the level of herbicide use. Determinants of both adoption and level are land ownership, farm area, and the method of crop establishment. These results are potentially relevant when designing policies to reduce excessive herbicide use or to encourage the adoption of alternative weed control methods such as integrated weed management.