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Faced with risky yields and returns, risk-averse farmers require a premium to take risks. In this paper, we estimate individual farmers’ degrees of risk aversion to adjust for the risk premium in returns and to replace the farmers’ realized returns with their certainty equivalent returns in the production function. In that way, the effect of the inputs on returns will automatically be risk-adjusted, i.e., we obtain risk-adjusted marginal effects of inputs, which can be used in decision-making support of farmers’ input choices in production. Using farm-level data from organic basmati rice smallholders in India, we illustrate this method using nonparametric production functions. The results show that the input elasticities and returns-to-scale estimates change when the farmers’ degree of risk aversion is taken into consideration.
Using a sample survey from Vietnam's M&RRD, this study examines both the factors affecting smallholder households’ perceptions of climate change, and the impact of climatic change on smallholders’ income and land allocation decisions. Results show a significant and negative impact of perception of climate change on income of smallholder households. Smallholders with perceived climate changes reduce land allocated to paddy crop. Farmers make strategic decision to counter the negative effects of climate change by increasing the amount of rented land for paddy crop production, while at the same time decreasing the amount of owned land allocated to paddy crop.
The objective of this research was to describe proportional differences across time and region in management practices among southern cotton farmers who experienced glyphosate-resistant (GR) weeds on their farms earlier than those who experienced them later and among farmers who were closest to one of four historical outbreak epicenters: Lauderdale County, TN; Macon County, GA; Edgecombe County, NC; and Terry County, TX. A mail survey was conducted with cotton farmers in 2012 from 13 southern, cotton-producing states. Survey responses on practices used by farmers were classified into three broad categories of labor, mechanical/tillage/chemical (MTC), and cultural. Proportions of respondents using practices from each category were identified by time and region; across which, proportional-difference tests were conducted. Results indicated respondents encountering GR weeds earlier were more likely than farmers who experienced them later to use the three broad-category practices (labor, 98 vs. 92%; MTC, 95 vs. 89%; and cultural, 86 vs. 76%) and specific practices, including hooded sprayers (76 vs. 58%), in-season herbicide change (83 vs. 60%), and field-border management (60 vs. 35%). Also, respondents closest to Lauderdale County were more likely than farmers closest to Edgecombe County to use broad-labor practices (99 vs. 91%) and specific practices, including hand hoeing (96 vs. 84%), hand spraying (49 vs. 31%), spot spraying (76 vs. 59%), wick applicator (13 vs. 11%), and field-border management (58 vs. 39%). Education programs on weed management can be developed and tailored according to the time and regional differences to provide effective information and communication channels to farmers.
This paper uses Theil's (1979) entropy-based measure of inequality and farm-level data to examine changes in farm business wealth (farm equity) of farm households. The farms associated with farm households are grouped by state into ten regions of the United States. The Theil entropy measure is then calculated and used to decompose total inequality of farm wealth into within-state and across-states (between states) inequalities for each region. Results show that since the enactment of the 1996 Federal Agricultural Improvement and Reform (FAIR) Act, inequality in farm wealth among farms within a state has decreased relative to the number of farms per state, across all regions. Further, most of the reduction in farm wealth inequality is attributed to increased equality in the distribution of real estate assets of the farm households, a major component of farm wealth.
This study models the effects of variability in farm income and off-farm wages on farm operators' labor allocation decisions. A simple theoretical model is employed to develop hypotheses, which are then tested empirically. Variability in farm income and off-farm wages is predicted to have a positive and negative effect, respectively, on off-farm hours worked. The empirical results confirm these predictions.
The Internet may reduce constraints on a farmer's ability to receive and manage information, regardless of where the farm is located or when the information is used. Using a count data estimation procedure, this study attempts to examine the key farm, operator, regional, and household characteristics that influence the number of Internet applications used by farm households. Findings indicate that educational level of the farm operator, farm size, farm diversification, off-farm income, off-farm investments, and regional location of the farm have a significant impact on the number of Internet applications used.
The Internet is becoming an increasingly important management tool in production agriculture. Using data from the 2004 Agricultural Resource Management Survey (ARMS) and a double-hurdle estimation approach, we explore the adoption of computers with Internet access by and Internet purchasing patterns of farm households. Adoption of the Internet is positively related to age and education of the operator, off-farm work, presence of spouse, participation in government programs, farm size, and regional location of the farm. Internet purchasing patterns of farm households are positively related to the education of the operator and spouse, presence of teenagers, and regional location of the farm. Finally, farm businesses and their households are more likely to purchase a greater percentage of non-durable goods through the Internet as distances to markets increase.
Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.
Direct marketing strategies increasingly have been recognized as a viable business option in U.S. agriculture as they allow producers to receive a better price by selling products directly to consumers. The objective of this study is twofold. Using a national survey, we first estimated a zero-inflated negative binomial model to identify factors affecting the total number of direct marketing strategies adopted by farmers. Then we estimated a quantile regression model to assess the impact of the intensity of adoption of direct marketing strategies on gross cash farm income. The results show that the intensity of adoption has no significant impact on gross cash farm income and that participation in farmers markets is negatively correlated with gross cash farm income at all five quantiles estimated.
Agritourism is an alternative source of farm income. We examine farmers’ participation in agritourism activities to assess the impact of participation on farm household income and return to assets using a large farm-level survey. The results reveal that older, educated, and female operators are more likely to participate in agritourism. However, government subsidies and the population of the county are negatively correlated with agritourism. Of the types of farm operations examined, small-scale farms that involved agritourism generated the greatest household incomes and returns to assets. For operators of small farms, agritourism can boost the economic well-being of farm households.
Rice, may be of a high- or low-quality type, based on the size and shape of the rice grain and variety. Thus, perhaps with an increase in income, consumers might not only switch from rice to other high-value-added foods, but also shift away from short-and-bold-grain to long-and-slender-grain rice. Using the case of Bangladesh, this article examines the drivers of change in rice grain-type preferences by households. We econometrically demonstrate that educated, rich, and urban households in Bangladesh are increasingly consuming fine-grain (i.e., long-and-slender-grain) rice, by replacing ordinary-grain (i.e., short-and-bold-grain) rice.
This study investigates the factors likely to affect an individual’s decision to enter farming after and/or while participating in an off-farm employment activity. Additionally, an ordered multivariate regression procedure was used to analyze the degree of importance of selected motivating reasons that were drivers of individuals’ decision to enter farming. Results indicate that individuals with lower education, children in the household, and older family members were more likely to have entered farming as an occupation. Findings further suggest that federal policies in the form of farm program payments may provide retired nonfarm workers incentives to enter farming in later life.
This study examines the return on agricultural assets relative to nonfinancial corporate assets in the general economy using aggregate Bureau of Economic Analysis data. Our results indicate that the rate of return on nonfarm assets dominates the rate of return on agricultural assets. The average rate of return on nonfarm assets is higher than the average rate of return on farm assets, and the variance of the rate of return on nonfarm assets is lower than the variance of the rate of return on farm assets. Furthermore, the rate of return on agricultural assets only exceeds the rate of return in the nonfarm sector in 1992.
The objective of this study was to identify factors which contribute to the earnings' success of cash grain farms in the United States. The study analyzes three measures of success including net farm income per dollar of asset, operators' returns to labor and management, and operators' management income. Logit regression analysis shows that controlling variable costs, ownership, management ability, technology adoption, and diversification are important factors that influence success.
Using a model of farm household resource allocation and data from the USDA-ERS Agricultural Resource Management Survey (ARMS), this study compares the effects of various categories of farm program payments on time allocation by farm operators and spouses. Results suggest that agricultural market transition payments (AMTA) increase leisure hours of both farm operators and spouses. Loan deficiency payments (LDP) and payments that combine market loan assistance (MLA) and disaster payments are shown to reduce leisure. The study also finds that AMTA payments exhibit a much higher degree of income transfer efficiency than the LDP and MLA payments.
The substitution of capital for labor and new labor-saving technologies has reduced the labor required for farming, yet many farms today depend on hired labor in some form. Common in the literature is the assumption of perfectly substitutable farm labor. This has implications for the operator's off-farm labor decision. Intuitively, different forms of farm labor have different impacts on production. We use the Agricultural and Resource Management Survey to estimate the elasticity of substitution between hired and family labor. The results provide little evidence to support the popular homogeneity assumption and find labor can be unitary and complimentary under certain scenarios.
Long-term tillage and fertilizer experiments were conducted in rice in kharif followed by lentil in dry subhumid Inceptisols at Varanasi and Faizabad; horse gram at Phulbani and linseed at Ranchi in moist subhumid Alfisols in rabi during 2001 to 2010. The study was conducted to assess the effect of conventional tillage (CT), low tillage + interculture (LT1) and low tillage + herbicide (LT2) together with 100% N (organic) (F1), 50% N (organic) + 50% N (inorganic) (F2) and 100% N (inorganic) (F3) on productivity, profitability, rainwater and energy use efficiencies. The results at Varanasi revealed that CT was superior with mean yield of 2389 kg ha−1, while F1 was superior with 2378 kg ha−1 in rice. At Faizabad, CT was superior with mean rice yield of 1851 kg ha−1 and lentil yield of 977 kg ha−1, while F1 was superior with 1704 and 993 kg ha−1 of rice and lentil, respectively. At Phulbani, F2 was superior with rice yield of 1170 kg ha−1. At Ranchi, F2 with rice yield of 986 kg ha−1 and F3 with linseed yield of 224 kg ha−1 were superior. The regression model of crop seasonal rainfall and yield deviations indicated an increasing trend in rice yield over mean (positive deviation) with increase in rainfall at all locations; while a decreasing trend (negative deviation) was found for lentil at Faizabad, horse gram at Phulbani and linseed at Ranchi. Based on economic analysis, CTF1 at Varanasi and Faizabad, CTF2 at Phulbani and LT2F2 at Ranchi were superior.
This paper uses microlevel data from the Agricultural Resource Management
Survey to examine the changes in the distributions of household wealth and
to assess the role farm subsidies play, among other factors, in affecting
these distributions. The empirical analysis relies on the concept of the
adjusted Gini coefficient and on fixed-effect regression procedures.
Coefficients from fixed-effects estimation indicate a negative correlation
between government payments and wealth dispersion, with the effect shifting
toward more of a positive relation when government payments were allowed to
interact with regional dummies.
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