Farm Size Distribution Research Articles

Estimating the carbon footprint of digital agriculture deployment: A parametric bottom‐up modeling approach

AbstractDigitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environmental effects of deploying digital devices on a large scale. We propose a bottom‐up method to estimate the carbon footprint of digital agriculture scenarios considering deployment of devices over a diversity of farm sizes. It is applied to two use‐cases and demonstrates that digital agriculture encompasses a diversity of devices with heterogeneous carbon footprints and that more complex devices yield higher footprints not always compensated by better performances or scaling gains. By emphasizing the necessity of considering the multiplicity of devices, and the territorial distribution of farm sizes when modeling digital agriculture deployments, this study highlights the need for further exploration of the first‐order effects of digital technologies in agriculture.

Spatial distribution of poultry farms using point pattern modelling: A method to address livestock environmental impacts and disease transmission risks.

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.

Using the evolution of knowledge to explain changes in farm size distribution and specialization

AbstractThis study developed a theoretical model to explain the consolidation of farmland and specialization in agriculture. In the model, farmers are assumed to be endowed with knowledge regarding the production of each crop, which evolves through learning. Knowledge across crops is substitutable to various degrees. The farm size distribution and specialization are shown to be equilibrium outcomes determined by the distribution of knowledge. A simulation example based on farm‐level acreage data from California is presented to show the relevance of learning mechanisms and test model implications.

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Making a living from a small farm is difficult in sub-Saharan Africa. In this paper, we quantify how difficult, using a simple, robust, relation between per capita daily income from farming (FPDI), land per capita and whole-farm net profitability per hectare. This relation allows the calculation of the land area required to generate various levels of household income as a function of farm performance. We use nationally representative household data for Tanzania to investigate the range of whole-farm profitability and to estimate an upper limit for it. For 6818 cases where households with land reported figures for gross crop and livestock revenues and for costs in any of the three years 2009, 2011 or 2013, actual median whole-farm net profitability was only $454/ha/y even without including the opportunity cost of family labour. When those were considered, median net profitability was negative $238/ha/y, i.e. a net loss. The maximum whole-farm profitability achieved was $4485/ha/y without family labour costs and $2742/ha/y with it. We evaluated actual and potential farm performance for their ability to generate a range of values of FPDI up to $10 per person per day. Most farms are not very profitable, particularly when household labour costs are considered, and few would be considered economically prosperous. Our analysis underscores the fact that improving their operations or adopting new technologies alone is unlikely to lift many smallholder farmers out of poverty in developing countries, given typical farm size distributions and reasonable assumptions about the realized economic returns to adoption of currently available agricultural technologies. While continued agricultural R&D investments are certainly worthwhile, such efforts alone will be insufficient to meaningfully address welfare needs of the world's rural poor. This suggests that agricultural development programs should expand their attention to incorporate off-farm and non-farm components of the rural economy.

Can North Carolina small rural farms succeed equally? Quantifying racial and gender disparities in acres, markets, and incomes

While small rural farms have long been the foundation of the United States' agricultural landscape, the historic context of gender and racial disparities within this sector has been understudied. This study aims to illuminate gender and racial disparities among small rural farms in North Carolina across operated acres, owned acres, market access, and farm income. Uncovering these dimensions provides valuable insights to promote equity in agricultural development. Using data from North Carolina small farms, we employ the Oaxaca-Blinder decomposition with Recentered Influence Functions to analyze the extent and sources of disparities. We find four key results. First, White-operated farms have 161% more land, are 2.88 miles closer to markets, and earn $174,000 more than Black-operated farms annually. Second, male-operated farms have 150% more acres and $126,000 higher gross income versus female-operated farms. Third, racial and gender disparities are most pronounced at higher ends of farm size and income distributions. Additionally, disparities stem from endowment and structural effects, with structural factors more prevalent at higher outcome levels. To address such disparities, policymakers should implement targeted initiatives to improve education, market access, and outreach for minority and women farmers while also reforming systems to dismantle structural barriers and enable equitable prosperity. Shedding light on racial and gender inequality is imperative for cultivating an inclusive, just food system where all small rural farmers can succeed.

Farm size distribution in the Canadian livestock sector

This study quantified the distribution of animals by farm size for portions of the dairy, beef, swine, and poultry sectors using the 2016 Census of Agriculture. Results showed that the distribution of farm sizes and animal populations were skewed or bimodal and varied by livestock type and by province. Thus, the average farm size has little meaning. Recognizing farm size diversity is important for developing effective policies and programs, conducting appropriate research, and developing practices and technologies to support farms of all sizes.

Mobilizing the Midstream for Supporting Smallholder Intensification

Most policies and incentives that aim to enable smallholder farmers towards the intensification of their agri-food production systems focus on supply-side strategies, such as training, technical assistance or credit services. Far less attention is usually given to demand-side drivers, such as the role of midstream value chain actors supporting smallholder’s investments in primary production. This explorative paper provides new insights on the value addition in the production vs. the midstream segments of agri-food value chains. It focusses attention on the influence of value chain integration on smallholders’ production and investment opportunities, and the implications for the structure of primary production. We use data from several value chains in sub-Saharan Africa to illustrate how farmers link to commercial midstream actors are able to enhance resource productivity, efficiency and profitability. In addition, we show that a larger role of the midstream in value added creation is associated with a more equal farm size distribution.

Measuring the American farm size distribution

AbstractThis paper develops a measure of farm size as a share‐weighted sum of farm sizes, called the Share Weighted Size Index (SWSI), which introduces new evidence of farm consolidation from 1959 to 2017. Our Share Weighted Size Index provides more reasonable estimates of the entire farm size distribution than simple averages and is useful for comparing farm size across crops at one point in time or for comparing farm sizes for a given crop over time. Although previous measures have relied on confidential or hard‐to‐access farm‐level records, the Share Weighted Size Index is derived exclusively from publicly available Census of Agriculture data. Unlike average farm size, the Share Weighted Size Index reveals consistent evidence of rising farm size, the importance of returns to scale for most commodities, and the rising importance of specialization on a small number of crops within farms. Contrary to past studies that argued rising off‐farm wages increase farm size, we find evidence that proximity to off‐farm opportunities results in smaller farms.

Changing Farm Size Distributions and Agricultural Transformation in Sub-Saharan Africa

We review the literature on the distribution of farm sizes in sub-Saharan Africa, trends over time, drivers of change in farm structure, and effects on agricultural transformation and present new evidence for seven countries. While it is widely viewed that African agriculture is dominated by small-scale farms, we show that medium-scale farms of 5 to 100 hectares are a nontrivial—and rapidly expanding—force that is influencing the nature and pace of food systems transformation in Africa. The increased prevalence of medium-scale holdings is associated with farm labor productivity growth and underappreciated benefits to smallholder farmers. However, the rise of African investor farmers is also contributing to the commodification of land, escalating land prices, and restricted land access for most local people. A better understanding of these trends and linkages, which requires new data collection activities, could help resolve long-standing policy debates and support strategies that accelerate agricultural transformation.

Land market distortions and aggregate agricultural productivity: Evidence from Guatemala

Farm size and land allocation are important factors in explaining lagging agricultural productivity in developing countries. This paper examines the effect of land market imperfections on land allocation across farmers and aggregate agricultural productivity. We develop a theoretical framework to model the optimal size distribution of farms and assess to what extent market imperfections can explain non-optimal land allocation and output inefficiency. We measure these distortions for the case of Guatemala using agricultural census microdata. We find that due to land market imperfections aggregate output is 19% below its efficient level for both maize and beans and 31% below for coffee, which are three major crops produced nationwide. We also observe that areas with higher distortions show higher land price dispersion and less active rental markets. The degree of land market distortions across areas co-variate to some extent with road accessibility, ethnicity, and education.

Effect of farm structure on rural community well-being

The current crisis in US agriculture has seen a growing number of farm bankruptcies. The result has been a “hollowing out” of the middle in the distribution of farm size, with growth in the number of both very large and small farms. A growing number of farms are operated by part-time farmers whose primary occupation is no longer farming. What are some implications of these changes for the well-being of rural communities? Using U.S. non-metropolitan (rural) county level data, we explore how the changing nature of farming has affected community well-being as understood through seven diverse measures. In general, we find conflicting evidence on the impact of farm structure on community well-being. In the end our results suggest that the logical conclusion of what has become known as the Goldschmidt hypothesis line of thinking that the movement to fewer and larger farms will necessarily harm the well-being of the larger community is not supported by the data.

Structural Changes in Israeli Family Farms: Long-Run Trends in the Farm Size Distribution and the Role of Part-Time Farming

Israeli agriculture has experienced rapid structural changes in recent decades, including the massive exit of farmers, a resulting increase in average farm size, a higher farm specialization and a higher reliance on non-farm income sources. The higher farm heterogeneity makes it necessary to examine changes in the entire farm size distribution rather than the common practice of analyzing changes in the average farm size alone. This article proposes a nonparametric analysis in which the change in the distribution of farm sizes between two periods is decomposed into several components, and the contributions of subgroups of farms to this change are analyzed. Using data on Israeli family farms, we analyze the changes in the farm size distribution in two separate time periods that are characterized by very different economic environments, focusing on the different contributions of full-time farms and part-time farms to the overall distributional changes. We found that between 1971 and 1981, a period characterized by stability and prosperity, the farm size distribution has shifted to the right with relatively minor changes in higher moments of the distribution. On the other hand, between 1981 and 1995, a largely unfavorable period to Israeli farmers, the change in the distribution was much more complex. While the overall change in the size distribution of farms was smaller in magnitude than in the earlier period, higher moments of the distribution were not less important than the increase in the mean and led to higher dispersion of farm sizes. Between 1971 and 1981, the contributions of full- and part-time farms to the change in the size distribution were quite similar. Between 1981 and 1995, however, full-time farms contributed mostly to the growth in the average farm size, while the average farm size among part-time farms actually decreased, and their contribution to the higher dispersion of farm sizes was quantitatively larger. This highlights the need to analyze the changes in the entire farm size distribution rather than focusing on the mean alone, and to allow for differences between types of farms.

US federal farm payments and farm size: Quantile estimation on panel data

AbstractThe marginal effect of government payments on farm size of US corn/soy and wheat producers is currently contested. This paper uses a quantile estimator with a restricted access panel dataset. Payments are positively associated with farm size; the association is statistically significant at select percentiles of the farm size distribution, but the statistical significance is not systematically related to farm size. Although the marginal effect is qualitatively larger for bigger farms, their differences are not statistically significant. This study does not provide any empirical evidence to suggest that federal farm dollars cause (i) only large farms to grow bigger or (ii) large farms to grow more than small farms.

Changing Farm Size Distributions and Agricultural Transformation in Sub-Saharan Africa

Changing Farm Size Distributions and Agricultural Transformation in Sub-Saharan Africa

Medium-scale commercial agriculture in Zimbabwe: the experience of A2 resettlement farms

ABSTRACTThe emergence of medium-scale farms is having important consequences for agricultural commercialisation across Africa. This article examines the role of medium-scale A2 farms allocated following Zimbabwe's land reform after 2000. While the existing literature focuses on changing farm size distributions, this article investigates processes of social differentiation across medium-scale farms, based on qualitative-quantitative studies in two contrasting sites (Mvurwi and Masvingo-Gutu). Diverse processes of accumulation are identified across commercial, aspiring and struggling farmers, and linked to contrasting patterns of agricultural production and sale, asset ownership, employment and finance. The ability to mobilise finance, influenced by the state of the macro-economy, as well as forms of political patronage, is identified as a crucial driver. Contrary to assertions that A2 farms are largely occupied by ‘cronies’ and that they are unproductive and under-utilised, a more differentiated picture emerges, with important implications for policy and the wider politics of Zimbabwe's countryside following land reform.

Status quo of adoption of precision agriculture enabling technologies in Swiss plant production

This paper presents the state of application of Precision Agricultural enabling Technology (PAT) in Swiss farms as an example for small-scale, highly mechanised Central European agriculture. Furthermore, correlations between farm and farmers’ characteristics and technology adoption were evaluated. Being part of a comprehensive and representative study assessing the state of mechanisation and automation in Swiss agriculture, this paper focuses on the adoption of Driver Assistance Systems (DAS) and activities in which Electronic Measuring Systems (EMS) are used. The adoption rate of DAS was markedly higher compared to EMS in all agricultural enterprises. The adoption rate was highest for high-value enterprise vegetables and surprisingly low for the high-value enterprise grapes. The results of a binary logistic regression showed that farmers located in the mountain zone were less likely to adopt PAT compared to farmers in the valley. Small farm size correlated with low adoption rates and vice versa showing adoption happens country-specific in the upper farm size distribution. The results show the potential for novel technologies to be adopted by farmers of high-value products. Furthermore, technologies have been partially used to reduce physical workload but not yet to evaluate crop or management performance to support decisions. However, automatic collection and forwarding of data is a fundamental step towards Smart Farming realizing its full potential in the future.

Farm Size, Technology Adoption and Agricultural Trade Reform: Evidence from Canada

AbstractUsing detailed census data covering over 30,000 farms in Alberta, Saskatchewan and Manitoba, Canada, we document the vast and increasing farm size heterogeneity, and analyse the role of farm size in adapting to the removal of an export subsidy in 1995. Consistent with the Alchian‐Allen hypothesis, the increase in per‐unit trade costs due to the reform was associated with farms of all sizes shifting their production of crops from low value wheat to higher value canola. We find that switching to new labour‐saving tillage technologies and away from summerfallow in response to the large negative shock to grain prices caused by the reform varied across the farm size distribution. We develop a theory of heterogenous farms and technology adoption that can explain our findings.

Farm size and gender distribution of land: Evidence from Ethiopian land registry data

Land is an essential asset for the livelihood and welfare of rural households in agriculture-based rural economies. This study utilizes land registry data from the First and Second Stage Land Registration (FSLR and SSLR) Reforms that took place in 1998 and 2016 in Tigray region of Ethiopia, the first region in Ethiopia to implement land registration and certification. Second Stage Land Registration and Certification (SSLR&C) provided households with parcel-based certificates with names of all holders. We assess the changes in farm sizes and gender distribution of land using mean and median sizes, Gini coefficients, and cumulative distribution graphs. The SSLR data facilitate detailed gender-disaggregated analysis after aggregating parcel data by gender to household level and categorizing households in male- and female-headed households. The data came from 11 municipalities in four districts, covering 78,700 parcels, a total area of about 30,000 ha, allocated to 31,150 households (SSLR). Average farm size declined from 1.15 to 0.90 ha and median farm size from 0.88 to 0.63 ha from 1998 to 2016. The Gini coefficient for land per capita increased from 0.42 in 1998 to 0.57 in 2016. The female landholding share for this land was as high as 48.8% in 2016. Compared to female-headed households, male-headed households had on average 27% and 35% more land per household in 1998 and 2016. The study demonstrates the relevance of land registry data for the monitoring of farm sizes and gender distribution of land and the findings are of relevance for the Sustainable Development Goal 1.4.

Land Market Distortions and Aggregate Agricultural Productivity: Evidence From Guatemala

Farm size and land allocation are important factors in explaining lagging agricultural productivity in developing countries. This paper examines the effect of land market imperfections on land allocation across farmers and aggregate agricultural productivity. We develop a theoretical framework to model the optimal size distribution of farms and assess to what extent market imperfections can explain non-optimal land allocation and output in-efficiency. We measure these distortions for the case of Guatemala using agricultural census microdata. We find that due to land market imperfections aggregate output is 19% below its efficient level for both maize and beans and 31% below for coffee, which are three major crops produced nationwide. The regions with higher distortions show a higher dispersion in land prices and less active rental markets. We also find that the degree of land market distortions across locations co-variate with road accessibility and ethnicity and, in a lower extent, with education.

Poultry population dynamics and mortality risks in smallholder farms of the Mekong river delta region

BackgroundPoultry farming is widely practiced by rural households in Vietnam and the vast majority of domestic birds are kept on small household farms. However, smallholder poultry production is constrained by several issues such as infectious diseases, including avian influenza viruses whose circulation remains a threat to public health. This observational study describes the demographic structure and dynamics of small-scale poultry farms of the Mekong river delta region.MethodFifty three farms were monitored over a 20-month period, with farm sizes, species, age, arrival/departure of poultry, and farm management practices recorded monthly.ResultsMedian flock population sizes were 16 for chickens (IQR: 10–40), 32 for ducks (IQR: 18–101) and 11 for Muscovy ducks (IQR: 7–18); farm size distributions for the three species were heavily right-skewed. Muscovy ducks were kept for long periods and outdoors, while chickens and ducks were farmed indoors or in pens. Ducks had a markedly higher removal rate (broilers: 0.14/week; layer/breeders: 0.05/week) than chickens and Muscovy ducks (broilers: 0.07/week; layer/breeders: 0.01–0.02/week) and a higher degree of specialization resulting in a substantially shorter life span. The rate of mortality due to disease did not differ much among species, with birds being less likely to die from disease at older ages, but frequency of disease symptoms differed by species. Time series of disease-associated mortality were correlated with population size for Muscovy ducks (Kendall’s coefficient τ = 0.49, p-value < 0.01) and with frequency of outdoor grazing for ducks (τ = 0.33, p-value = 0.05).ConclusionThe study highlights some challenges to disease control in small-scale multispecies poultry farms. The rate of interspecific contact and overlap between flocks of different ages is high, making small-scale farms a suitable environment for pathogens circulation. Muscovy ducks are farmed outdoors with little investment in biosecurity and few inter-farm movements. Ducks and chickens are more at-risk of introduction of pathogens through movements of birds from one farm to another. Ducks are farmed in large flocks with high turnover and, as a result, are more vulnerable to disease spread and require a higher vaccination coverage to maintain herd immunity.