Beginning in the 1970s, economic researchers began to study the potential impacts of bans on the use of sub-therapeutic antibiotics on the pork, poultry, and beef sectors and on U.S. consumers, but there has been little study of how heterogeneity impacts antibiotic use, and in turn, how it impacts returns to using antibiotics in U.S. livestock operations. I concentrate on U.S. pork and poultry operations since they are the largest users of sub-therapeutic antibiotics by volume in the U.S., and explore the existing literature on the economics of sub-therapeutic antibiotic use for glimpses of heterogeneity in the returns to antibiotic use. Perhaps the most interesting source of heterogeneity in returns to antibiotic use may be heterogeneity in management and/or the use of potential substitutes for antibiotics, such as improved sanitation practices and more modern facilities. Productivity and use of technologies that substitute for STA use vary amongst producers, and likely by region and farm size. Thus, the marginal abatement costs of reducing STA use vary across industries, producers, production systems, and regions.In more developed countries such as the United States, the face of agriculture was once that of the small family farmer. Today, the agricultural landscape in developed—and to some extent developing— countries is dominated by agribusiness and large farming operations. While many of these operations are still family-owned and farm size, management, and production methods remain diverse, on the whole, farms are larger and more mechanized and specialized than ever before . This transition is a direct result of the increase in relative price of labor and changes in domestic and global agricultural policies , and was spurred by dramatic improvements in agricultural productivity, and a shift from more labor-intensive agriculture to more capital- and technology-intensive agricultural practices that employed new varieties,growing vegetables in vertical pvc pipe synthetic inputs, and irrigation.
While agricultural production in much of Asia, Africa, and Latin America is more heterogeneous and more labor-intensive in general, specialization, mechanization, and technological change have increased productivity of agricultural commodity crops such as soybeans and sugarcane in Brazil, wheat and rice in China and India, palm oil in Indonesia and Malaysia, and others . Incorporating and disseminating technological advances that improve productivity and incomes in smallholder farming systems remains a challenge throughout the developing world . In spite of—or perhaps in response to—this shift toward specialization and mechanization, there has been renewed momentum on the part of a vocal contingent of consumers, producers, researchers, and policy makers who draw attention to the social, environmental, and economic implications of this transition . They envision a new model of agriculture that employs fewer synthetic inputs, incorporates practices which enhance biodiversity and environmental services, and takes into account the social implications of production practices, market dynamics, and product mixes. Components of this movement are taking hold in the economic and cultural mainstream in the United States, Europe and other countries. Evidence of this shift includes the rise of organic, “fair trade”, and other production and certification schemes, and the growth of consumer willingness-to-pay for these differentiated food products. The prevalence of local farmers’ markets and slow and local food movements, and the emergence of Payments for Ecosystem Services and multifunctional agriculture within agricultural landscapes are also supporting this change . While closely related to the concepts of sustainable, multifunctional and organic agriculture, diversified farming systems have emerged as a separate agricultural model.
Diversified farming systems share much in common with sustainable, multifunctional, organic and local farming systems, but are unique because they emphasize incorporating functional biodiversity at multiple temporal and spatial scales to maintain ecosystem services critical to agricultural production. These ecosystem services include but are not limited to pollination services, water quality and availability, and soil conservation . Our aim is to provide an economists’ perspective on how a range of existing and emerging factors drive profitability of DFS at the farm level and how these relate to the adoption and emergence of diversified farming systems at larger scales. We begin with an overview of the factors that impact the profitability of agricultural systems, follow with a discussion of the economic factors that support and run counter to diversified farming systems, and conclude with our thoughts on how technological innovation and market trends must continue to evolve if DFS are to become economically sustainable and widespread.How profitable is it to farm? The answer depends upon the choices a farmer makes about what crops to grow and where, what technologies to use, and many other short- and long-term management decisions. Economists assume that farmers make choices so as to improve their utility, or well-being. In particular, farmers tend to pursue activities that increase their income, reduce their financial and physical risk, reduce labor requirements, and are convenient or enjoyable. A variety of constraints play into farmers’ decisions, including constraints with respect to available production technologies, biophysical or geophysical constraints, labor and input market constraints, financial and credit constraints, social norms, intertemporal trade offs, policy constraints, and constraints to knowledge or skills . The literature on technology adoption at the farm level tells us that many factors—in particular, variables that vary across farms and are sources of heterogeneity—influence farmers’ choices about what crops to grow, whether to use a new technology, and how to manage their land. Just as individual consumers have different preferences about products they consume, farmer characteristics, asset endowments, risk preferences, and intertemporal considerations affect their choices.
Farmer attitudes, resource availability, and education and knowledge are especially important; farmers may be risk-averse toward making changes in cropping decisions or adopting new agricultural practices, or might have very conservative attitudes toward technology or lower or higher levels of concern for the natural environment . A farmer’s income or resource base and ability to obtain credit will also influence his/her choice of crops, farming systems, and willingness to invest in new crops, systems, or technologies . A risk-averse farmer or one who is credit or income-constrained may be less likely to adopt new technologies, even if they are likely to reduce his susceptibility to risk or increase productivity or income over the long-run . Lack of knowledge and information about the costs and benefits of adopting new technologies or conservation practices or lack of knowledge about how to implement such technologies or practices will also affect a farmer’s propensity to adopt them . Even if farmers have full information and can implement new technologies efficiently and at low cost, differences in intertemporal preferences or credit constraints may mean that farmers are unwilling to sacrifice current profits or income for long-term improvements in soil fertility, risk-reductions, or improved yields . Biological and geophysical factors and input and output market conditions are important variables that also impact farmer decision-making and adoption of land use practices or technologies. Biological and geophysical factors that influence production can include water availability, soil fertility, and risks of floods, droughts, frost, or pest or weed infestations, and the importance of each of these factors varies with the types of crops planted. Input market conditions can shape farmer production decisions in a number of ways; dynamics of local and seasonal labor availability may mean that it is not profitable to grow a crop with a very narrow harvesting window in a month where the overall demand for agricultural labor is high in the region .
Input price volatility and economies of scale with respect to inputs or technologies can also contribute to farmers planting different mixes of crops, or planting more land in one crop than another.Similarly, output market conditions including prices, price variability, transportation costs, and supply chain transactions costs are important determinants of how profitable it is for farmers to grow a crop. Many of these variables are influenced by location; Rogers notes that communities closer to urban centers are likely to adopt new technologies more quickly. Consumer attitudes and willingness to pay for differentiated crops or particular attributes, such as organic or local production or pesticide-free varieties,vertical greenhouse also affect the agricultural systems that emerge in response to the demands of a changing market. Finally, policies and regulations can impact the profitability and evolution of different agricultural systems by facilitating or hindering trade in particular types of agricultural products, by influencing farmer decisions about what crops to grow or how much land to farm using policies such as price supports or set-aside programs, or by making different types of production or land use relatively more or less “expensive” via regulations, taxes and subsidies, or standards . In addition, many policies that do not specifically target agriculture, such as labor and immigration or water policies, have a significant effect on the costs of agricultural production. For example, laws such as those that regulate pesticide usage and application or limit water use can make it more costly to produce using synthetic pesticides or inefficient irrigation systems . While in the short-run such regulations may have a negative impact on farmer welfare, they also serve to stimulate innovation and adoption of new technologies in order to comply with regulations and reduce the costs of production . How can we describe trends in adoption and diffusion of agricultural technologies at landscape, regional, or global scales? Early studies on adoption noticed that the number of adopters, or the cropped area of using the new technology, were S-shaped as a function of time. They explained this pattern by imitation behavior among farmers; adoption is slow until enough farmers begin using the technology, and then rates of adoption speed up rapidly before they plateau.
The more profitable the new technology, the faster the rate of adoption and the higher the level of adoption after the diffusion process has played out . Farmers are heterogeneous, however, which impacts how and when they make decisions. In light of this heterogeneity, David and Feder et al. introduced the threshold model of adoption which characterized adoption within a community as a dynamic process whereby farmers make decisions according to explicit economic decision rules. Differences in when and how farmers adopt new technologies, then, arise due to heterogeneity among farmers and differences in other factors, such as their location and land quality. Larger farmers, for example, are often early adopters of mechanized technologies that exhibit increasing returns to scale. There is an interplay between farmer heterogeneity and the biological and geophysical factors that influence adoption that we mentioned earlier in this section; farmers in areas with soils with lower water-holding capacity will reap greater benefits from adopting irrigation technologies, and pest control strategies are adopted first in regions with high pest pressures. Over time, technologies and practices diffuse as producers gain knowledge and experience, or “learning by doing,” and as more and more farmers begin to use the technology, or “learning by using.” More and more farmers will adopt a technology as the fixed costs of adoption decline with time, and for some technologies, the gains from adoption increase with time as the network of producers using the technology increases in size . These basic principles that guide producer adoption choices provide a background for analyzing the factors that will affect whether farmers adopt diversified farming systems. Within the context of farmer decision making, there are a number of ways that diversified farming systems can help farmers maximize their utility, including through their roles in mitigating different types of risks, providing complementary inputs and optimizing production in the face of different biophysical or input and output market constraints, and through providing income or non-pecuniary benefits from ecosystem services or other benefits of using DFS practices. In this section, we focus on how these factors might make diversification an economically optimal choice for the farmer. Farmers are typically risk-averse . They face many different types of risk including price risk , yield risk , input supply risk and other types of risks . Many of these types of risk contribute directly to profit risk, which is ultimately most important to the producer. Farmers and their families can respond to risks in many ways, and can respond ex ante in precautionary ways, or ex post to try and minimize their losses. Strategies for coping with risk include finding off-farm employment , saving or using credit markets, informal borrowing , adopting risk-reducing technologies such as seed varieties with properties such as drought or herbicide resistance that emerged during the green revolution , engaging in contracts such as those that ensure that the farmer will have a buyer for his product at the end of the season at a set price , and diversification of production.