We analyze the equilibrium conditions in which contracts are desirable for firms (buyers) with various levels of management efficiencies procuring a factor input under two levels of quality from supplies. The quality of the factor input, which affects production efficiency, may be known to the buyer; the efficiency of the firm is not known to the supplier. We estimate, using principal-agent models, that firms with high-management efficiency do not have the incentive to pay a quality premium to suppliers, but firms operating with low management efficiency are willing to offer a price premium for quality. The model is applied to the question of preconditioning cattle for the feedlot.

Efficiencies of Agricultural Credit Associations of the US Farm Credit System are measured quarterly from 2005 through 2020. A slacks-based measure based on the directional distance function is used with non-performing loans included as an undesirable output. This permitted efficiency scores to be measured by type of defined input or output. Generally, most Associations were highly efficient, but there was deterioration in mean efficiency over the years 2008–2018, a period of financial difficulties in the US agriculture. Efficiencies of Associations that merged or consolidated were tracked before and after these activities. Mergers and consolidations often led to increased efficiencies.

Preconditioning cattle, a management practice of preparing cattle for feedlots as well as following a vaccination protocol for common diseases, has been shown to add value to cattle by reducing disease incidence and severity, yet it is not universally adopted. We estimated the benefits to a beef system of preconditioning weaned calves versus not preconditioning under stochastic returns. Purchasing preconditioned calves makes economic sense, but market efficiency requires complete information of the health status of the cattle, feedlot performance, along with the right market mechanisms, which may not be available in all markets.

We specify a two-tier stochastic frontier model to estimate a price equation for U.S. Rieslings and determine overpricing and underpricing of specific wines. The data is for 2000–2016. Using tasting score and tasting score squared as sole independent variables, we found evidence of overpricing and underpricing of wines. When additional location variables were entered, empirical estimates for this two-tier model were infeasible, suggesting that both underpricing and overpricing did not occur simultaneously in this market. Separate one-sided stochastic frontier models were then specified and estimated to test for either under or overpricing in this market. Results showed that overpricing exists and not underpricing, but the extent of overpricing is minor, suggesting that wineries do an efficient job pricing their wines, given tasting scores, conditional on regional location premiums or discounts. We also investigated the effect of scale on pricing for a smaller set of wineries. (JEL Classifications: C4, D4, Q1)

The objective of this study was to determine the economic value of obtaining timely and more accurate clinical mastitis (CM) test results for optimal treatment of cows. Typically CM is first identified when the farmer observes recognisable outward signs. Further information of whether the pathogen causing CM is Gram-positive, Gram-negative or other (including no growth) can be determined by using on-farm culture methods. The most detailed level of information for mastitis diagnostics is obtainable by sending milk samples for culture to an external laboratory. Knowing the exact pathogen permits the treatment method to be specifically targeted to the causation pathogen, resulting in less discarded milk. The disadvantages are the additional waiting time to receive test results, which delays treating cows, and the cost of the culture test. Net returns per year (NR) for various levels of information were estimated using a dynamic programming model. The Value of Information (VOI) was then calculated as the difference in NR using a specific level of information as compared to more detailed information on the CM causative agent. The highest VOI was observed where the farmer assumed the pathogen causing CM was the one with the highest incidence in the herd and no pathogen specific CM information was obtained. The VOI of pathogen specific information, compared with non-optimal treatment of Staphylococcus aureus where recurrence and spread occurred due to lack of treatment efficacy, was $20.43 when the same incorrect treatment was applied to recurrent cases, and $30.52 when recurrent cases were assumed to be the next highest incidence pathogen and treated accordingly. This indicates that negative consequences associated with choosing the wrong CM treatment can make additional information cost-effective if pathogen identification is assessed at the generic information level and if the pathogen can spread to other cows if not treated appropriately.

The Dixit entry/exit real option model was applied to the entry/exit decisions of New York dairy farmers. For the cost structure of a 500-cow farm, the entry milk price is $17.52 per hundredweight (cwt) and the exit milk price is $10.84. For the 50-cow farm cost structure, the entry price is higher at $23.71 per cwt, and the exit price is also higher at $13.48. If infinite numbers of representative farms enter and exit at these prices, the price of milk should range between $13.48 and $17.52 per cwt.

Agricultural production estimates have often differentiated and estimated different technologies within a sample of farms. The common approach is to use observable farm characteristics to split the sample into groups and subsequently estimate different functions for each group. Alternatively, unique technologies can be determined by econometric procedures such as latent class models. This paper compares the results of a latent class model with the use of a priori information to split the sample using dairy farm data. Latent class separation appears to be a superior method of separating heterogeneous technologies and suggests that technology differences are multifaceted.

Productivity of U.S. farmers by age is measured by non-parametric programming using 1992 Census data, decomposed into efficiency and technology Malmquist index components.

Productivity increases slightly with age and then decreases. In most states productivity variations are from technology use rather than efficiency differences.

Short-run and long-run technical and allocative efficiencies were computed for 395 New York dairy farms using data envelopment or nonparametric procedures on 1990 Dairy Farm Business Summary data. The farms were, on average, more allocatively efficient in the short run than in the long run, but were more technically efficient in the long run than in the short run. Stanchion barns were as efficient as milking parlors, and milking more than two times per day did not increase efficiency.

This paper explores the role of managerial ability in determining efficiency in New York dairy farms. Using an unbalanced panel of farm data from 1993 through 2004, we estimate outputoriented technical efficiencies using stochastic distance frontier functions. We find that both lagged net farm income and farmers’ own estimates of the value of their labor and management as proxies for managerial ability impact measured efficiency. Efficiency increases with operator education, farm size, and extended participation in a farm management program, but decreases with operator age.

Monte-Carlo simulation of nonparametric efficiency shows that even when the number of firms is large, defining ten or more inputs results in most firms being measured as efficient. Comparison of the simulated results with any empirical results may suggest that the dimension of the problem, rather than actual efficiencies, determines computed efficiencies.

The diversity of cropping patterns on smallholder farms in southern Malawi was analysed using a framework that explicitly incorporates the extent of intercropping in each field. Diversity is defined as the relative abundance of each crop in the overall cropping pattern. Six indices of diversity were constructed for 208 farms and used in a model of a welfare-maximizing farm household to examine the reasons for diversity in cropping patterns; multiple regression techniques were used to determine the effect of different household characteristics on diversity. The results suggest that an increase in labour availability over the production period is associated with a more diverse cropping pattern. Landholding size also influences diversity, which rises to a maximum and then falls as the area cultivated per capita increases. Farmers who grow a non-food cash crop (tobacco) have more diverse cropping patterns than those who do not. As diversity increases, farmers use intercrop patterns that are more substitutive than additive.

A conceptual model is formulated that shows that a downward sloping supply function may exist for a profit maximizing firm facing a cash-flow constraint. The necessary requirement is that at least one factor must be a non-cash input. The model is tested using analysis of variance on two groups of producers from farm record data, one group facing a binding budget constraint the other group not. The results indicate that farms facing a cash flow constraint increase output more than farms not restricted by a cash flow constraint in response to a price decrease.

The technical efficiencies of New York dairy farms were estimated using a frontier production function. The average farm was 69 percent efficient. Individual farm efficiency was regressed on variables not considered inputs to explain why a farm was not on the frontier. Favorable location in the state and larger size (cows) as proxies for technology lead to greater efficiency. Participation in the Dairy Herd Improvement Cooperative and use of mail-in computerized records as proxies for management result in a reduction in efficiency. However, only 9 percent of variation in farm efficiency could be explained.

First-degree and second-degree stochastic dominance were used to separate a panel of 112 dairy farms with ten annual observations per farm into successful and less successful groups using four different performance measures. Logit regression using 16 independent variables was then used to determine important farm characteristics leading to farm success. High milk production and controlling hired labor and purchased feed expenses were important. The selective adoption of new technologies was also important. Optimal debt-asset ratios varied over the 10-year period.

The price and quantity effects of a forthcoming biotechnology product, bovine growth hormone (bGH), are explored in a simple partial equilibrium model. The model is based on previous theoretical work on technological change but is developed in terms of a sector output. A particular output curve is estimated using data from a random sample of New York State dairy farms. Information on the farm level production effects of bGH is used to shift the output curve and to solve for equilibrium levels of price and output. The model projects the bGH may lead to the exit of 5,400 New York dairy farms and a 20 percent reduction in herd size. Consumers will benefit from an approximately 30 percent drop in milk price. The effect on gradual diffusion of bGH on farm numbers is considered. To accommodate this technology policies encouraging an orderly transfer of resources out of the dairy sector should be examined.

This study empirically compares the retirement values of dairy farm investments to tax-deferred retirement investments that are funded with bank certificates of deposit or common stock. For a successful dairy farm, the results indicate that tax-deferred retirement plans that generate rates of return similar to certificates of deposit or common stock mutual funds are probably not as good an investment as reinvesting farm earnings back into the farm business.

This paper presents empirical measures of the efficiency of the New York family dairy farm over its life cycle. The increase and then decrease in farm efficiency with age is only minor. Factors not correlated with age are much more important in determining efficiency. Exiting farmers who appear not to have children to take over the family farm are managing and maintaining the farm as well as exiting farmers who have potential future farming children.