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Several studies evaluate the agronomics of crop cultivars grown under both organic and conventional management. Most studies focus on yield differences or mean yield rankings between conventional and organic management. Their findings have been mixed for the most part. None of these studies use economic analysis to identify the best cultivars for either system. This study uses simulation and stochastic efficiency with respect to a function (SERF) to obtain ordinal rankings of rice cultivars for both organic and conventional management based on risk efficiency. The SERF analysis reveals the most dominant cultivars grown under conventional management do not match the most dominant cultivars grown under organic management. These results imply that rice cultivars ideal for conventional systems may not be ideal for organic systems, and that rice cultivars used in organic production systems should be adapted to organic rather than conventional management.

Arkansas rice production is highly dependent on energy related inputs such as water and nitrogen. This analysis uses Data Envelopment analysis (DEA) to calculate non-radial technical efficiency scores and quantifies input overuse for rice fields enrolled in the University of Arkansas, Rice Research Verification Program (RRVP), with special emphasis placed on estimation of water and nitrogen input overuse. The results reveal technical inefficiency exists in both water and nitrogen application, but other inputs may play more of a role in the overall technical inefficiency on rice fields. Average estimated overuse of water and nitrogen was 27.9% and 14.7%, respectively.

Arkansas is the top domestic rice producer, representing nearly half of total U.S. rice production. Rice is a high-cost crop relative to other field crops in Arkansas, and production costs for rice have increased significantly since the mid 2000s due to rapidly increasing fuel and fertilizer prices. More efficient rice production management is pertinent to maintaining long term profitability. This study assesses the important factors leading to higher technical, allocative, and economic (cost) efficiency in rice production using a Tobit model. The data is obtained from the 2005-2011 Rice Research and Verification Program (RRVP). Using a Clearfield hybrid seed was found to have positive statistically significant effect, as well as relatively large marginal effect on all three efficiencies.

This study examines impacts of shallow loss safety net programs proposed in S. 3240 and H.R. 6083 for 2013‐2017 with focus on Arkansas rice and the U.S. rice sector. The results suggest that the Price Loss Coverage program provides a relatively strong safety net for long‐grain rice producers.

Large expenses associated with rice production and dependence on energy related inputs like fuel and fertilizer in particular compel rice producers to use management practices that are input efficient and result in least cost. This study uses data envelopment analysis (DEA) to calculate technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) for rice production in Arkansas at the field level using data from 137 fields enrolled in the University of Arkansas, Rice Research Verification Program (RRVP) from 2005 to 2011. Efficiency scores for RRVP fields are compared with those obtained from developing rice producing countries. Economic efficiency scores are also compared across RRVP fields using alternative management practices. The results indicate the majority of RRVP fields have high TE scores with a mean TE score of 0.899. Over half the fields in the RRVP achieve full technical efficiency (TE scores equal to 1). Mean AE and EE scores for RRVP fields (AE = 0.696; EE = 0.625) fall within the range of mean AE and EE scores reported for developing countries producing rice. Alternative management practices appear to have an impact EE scores. Fields planted to hybrid, Clearfield-hybrid combinations, and medium grain varieties along with fields with a zero-grade and fields using multiple inlet irrigation produced higher EE scores relative to other RRVP fields.

Participation rates by southern irrigated crop producers in most important crop insurance programs have been relatively low. This paper empirically examines why this may be the case in Arkansas, and proposes a novel “gross margin” product specifically targeted at meeting the needs of these farmers.

Irrigation fuel costs represent a significant portion of rice production expenses. Multiple inlet (MI) irrigation represents a water saving alternative to conventional flood irrigation. This study uses simulation to calculate the range of monetary benefits to MI in rice production. Water savings from MI relative to conventional flood irrigation along with rice yields, rice prices, and prices for key production inputs (diesel and fertilizer) are simulated, and stochastic rice net returns above variable and fixed expenses are calculated for different pump lifts with and without MI. Monetary benefits to MI are measured as the difference in net returns with and without MI. The results indicate MI monetary benefits depend greatly on pump lift and the presence or absence of a yield increase. Monetary benefits to MI increase as pump lifts become larger, and relatively small increases in yield resulting from MI irrigation can greatly enhance its payoff.

Arkansas is the top domestic rice producer, representing nearly half of total U.S. rice production. Sediment is one of the major pollutants in rice producing areas of Arkansas. In order to mitigate this problem no-tillage management is often recommended. No-tillage is not well understood by farmers who believe that no-till is less profitable due to lower yields offsetting cost savings. This study evaluates the profitability and variability of no-till in the typical rice-soybean rotation used in Arkansas rice production. Crop yields, prices and prices for key production inputs (fuel and fertilizer) are simulated for the rotation, and net return distributions for rice, soybean and the two-year rotation are evaluated for no-till and conventional till using stochastic efficiency with respect to a function (SERF) analysis. The results indicate that both risk neutral and risk-averse rice producers would prefer no-till over conventional till management in the two year rice-soybean rotation, and that no-till soybeans contribute greatly to the overall profitability of the rotation.

This study evaluated the impacts of farm size and stochastic return variability on no-till (NT) rice profitability at the whole-farm level. Mixed integer programming was used to determine optimal machinery complements, fuel consumption, and machinery labor requirements for conventional till (CT) and NT rice-soybean farms of 1200, 2400, and 3600 acres in size. Crop yields, market prices, and prices for key production inputs were simulated to construct stochastic whole-farm net returns for each farm size under CT and NT management, and both first and second degree stochastic dominance analysis were used to rank cumulative distribution functions of whole-farm returns according to specified risk preferences. The results indicate NT farms exhibit second degree stochastic dominance over CT farms regardless of farm size, and high input prices have less downward effect on the profitability of NT farms relative to CT farms.

This study evaluates both the profitability and risk efficiency of grazing stocker steers on conservation tillage winter wheat pasture using simulation and stochastic efficiency with respect to a function (SERF). Average daily gains are simulated for steers grazed on conventional tillage (CT), reduced tillage (RT) and no-till (NT) winter wheat pasture. Steer price distributions and prices for key production inputs such as diesel, fertilizer, and glyphosate are also simulated. Stocker steer net return distributions by tillage treatment are constructed and ranked for risk efficiency using SERF. The results indicate the NT system is the most profitable and most risk efficient of the three tillage systems, followed by the RT system. Both conservation tillage systems dominate the CT system under risk aversion based on SERF analysis and generate positive risk premiums for risk-averse cattle producers above the CT system.

No-till (NT) has been shown to reduce fuel, labor, and machinery costs compared to conventional-till (CT) but very few rice producers in Arkansas practice NT. The low adoption rate is most likely due to difficulties in management but also limited information on the profitability and risk of NT. Most rice producers are knowledgeable on NT costs savings but consider it less profitable due to yield reductions offsetting costs savings. This study evaluates production costs, crop yields, and economic risk of both NT and CT in five rice-based cropping systems (continuous rice, rice-soybean, rice-corn, rice-wheat, and rice-wheat-soybean-wheat). Yields, crop prices, and key input prices are simulated to create net return distributions. Stochastic efficiency with respect to a function (SERF) is used to evaluate profitability and risk efficiency. Results indicate that a risk-neutral and risk-averse producer in either NT or CT would prefer a rice-soybean rotation. NT would be preferred over CT in the rice-soybean rotation across all risk preferences. Overall, risk-neutral producers would prefer NT in four of five cropping systems while risk-averse producers would prefer NT in three of five cropping systems.

Rice is a major cash crop in eastern Arkansas, but most rice acres are intensively cultivated and grown on rented land. No-till is an effective means of sequestering soil carbon and reducing greenhouse gas emissions, and economic incentives exist for no-till in the form of carbon credits. Studies evaluating the economic potential of carbon credits focus on producers only and do not take into consideration the landlord’s perspective. This analysis evaluates the profitability and risk efficiency of no-till management and carbon credits in Arkansas rice production from the prospective if the landlord using simulation and stochastic efficiency with respect to a function (SERF). The results indicate carbon credits may have potential to enhance preference for no-till in rice production by risk-averse landlords.

Rice production generally involves intensive cultivation. The profitability of no-till rice has been investigated but solely from the producer’s perspective. Most farmed cropland is owned by someone else. This study evaluates the risk efficiency of no-till rice from the landlord’s perspective using stochastic efficiency with respect to a function (SERF).

Rice production in Arkansas usually involves intensive tillage. No-till rice has been studied, but the focus has been limited to impacts on yields and per acre returns. This study uses mixed integer programming to model optimal machinery selection and evaluate whole-farm profitability of no-till management, for rice-soybean farms. Results indicate that lower machinery ownership expenses combined with lower fuel and labor expenses do enhance the profitability of no-till management, but the monetary gains appear to be modest, implying that other incentives may be necessary to entice producers to use the practice.

Rice in Arkansas is typically produced using intensive tillage. No-till rice has been studied, but the research focus has been limited to impacts on yields and per acre net returns. This analysis evaluates the profitability of no-till rice at the whole-farm level using both enterprise budget analysis and linear programming.

Western Agricultural Economics Association Conference, Colorado Springs CO, July 12-15, 1992

Large expenses associated with rice production and dependence on energy related inputs like fuel and fertilizer in particular compel rice producers to use management practices that are input efficient and result in least cost. This study uses data envelopment analysis (DEA) to calculate technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) for rice production in Arkansas at the field level using data from 137 fields enrolled in the University of Arkansas, Rice Research Verification Program (RRVP) from 2005 to 2011. Efficiency scores for RRVP fields are compared with those obtained from developing rice producing countries. Economic efficiency scores are also compared across RRVP fields using alternative management practices. The results indicate the majority of RRVP fields have high TE scores with a mean TE score of 0.899. Over half the fields in the RRVP achieve full technical efficiency (TE scores equal to 1). Mean AE and EE scores for RRVP fields (AE = 0.696; EE = 0.625) fall within the range of mean AE and EE scores reported for developing countries producing rice. Alternative management practices appear to have an impact EE scores. Fields planted to hybrid, Clearfield-hybrid combinations, and medium grain varieties along with fields with a zero-grade and fields using multiple inlet irrigation produced higher EE scores relative to other RRVP fields.