Federal Milk Marketing Orders Research Articles

Dairy pricing policy, production, and water quality: Application to the Chesapeake Bay watershed

AbstractThis study assesses the economic and water quality impacts of implementing a dairy pricing policy under Federal Milk Marketing Order system designed to alleviate milk prices plummet occurred at the beginning of pandemic. Using a 12‐region, positive mathematical programing model of livestock production in the Chesapeake Bay watershed, we find that pricing policy induces significant expansions in dairy sectors, generates higher level of total net revenue in regions having large base‐period dairy sectors. For water quality, we find that policy leads to an increase in nitrogen emissions but a decrease in phosphorus emissions for the livestock industry as a whole in most studied regions.

Volatility in US dairy futures markets

US dairy futures markets of Class III milk, butter, cheese, and dry whey exhibit unique volatility patterns under the Federal Milk Marketing Order pricing system. We find that dairy volatilities have a relatively low connectedness among themselves and the overall commodity market. We develop a price information uncertainty measure to investigate dairy markets’ response to government-released information. Dairy futures markets respond to government-released information with increased trading activity. The price information uncertainty measure has a strong positive impact on price volatility across all dairy commodities. We provide evidence that the COVID-19 pandemic increases volatility in dairy commodities. The pandemic also significantly reduces the impact of information uncertainty on volatility.

Opportunity Cost: An Economic Concept That May Improve the Functioning of Federal Milk Marketing Orders and the U.S. Dairy Industry

AbstractIn the United States, over 70% of milk production is priced under Federal Milk Marketing Orders (FMMOs). A primary purpose of FMMOs is to facilitate orderly allocation of milk as a limited, perishable resource among alternative uses. Fundamental to FMMOs are the regulatory prices applicable to milk used in cheese and whey (Class III), and nonfat dry milk and butter (Class IV). This work examines a novel milk pricing method based on the concept of opportunity cost for milk used in cheese and whey. This novel method may improve the functioning of FMMOs and the U.S. dairy industry.

Cow's milk still leads in the United States: The case of cow's, almond, and soy milk

AbstractWhile cow's milk and plant‐based milk are often hypothesized to be substitutes, much remains unknown about the impacts that plant‐based milks have on the retail price for cow's milk, if any. We explore the individual retail price relationship between two plant‐based milks, almond and soy, with cow's milk. If the markets are cointegrated, and shocks in the plant‐based markets affect the cow's milk market, it can add volatility to cow's milk prices, which could have implications for costs and benefits of the USDA Dairy Margin Coverage Program and price calculations by the Federal Milk Marketing Orders (FMMO). However, while we find evidence that plant‐based milk prices react to shocks in cow's milk prices, we do not find evidence that cow's milk prices respond to changes in plant‐based milk prices.

Negative producer price differentials in Federal Milk Marketing Orders: Explanations, implications, and policy options

In Federal Milk Marketing Orders (FMMO), which use multiple component pricing schemas, farmers are paid for delivered quantity of butterfat, protein, and other solids, plus a producer price differential (PPD). The PPD captures the difference between the total handler obligations to the pool and the total component value of milk. In 2020, record negative PPD caused widespread frustration among dairy farmers. The primary objective of this research was to provide a comprehensive analysis of factors that affect PPD and to quantify their relative importance. We examined FMMO data from the past 10 yr including prices, utilizations, and tests. By decomposing the PPD, we were able to isolate the drivers of negative values. We found that long-term trends in usage, most importantly declining beverage milk and rising component tests, including both butterfat and protein, have substantially reduced PPD over the past decade. Class I milk pricing reform of 2018 exacerbated negative PPD in 2020, but we found that the PPD would have been negative even without that reform. The greatest contributor to recent negative PPD was the spread between cheese and milk powder prices, caused by shifts in demand due to the COVID-19 pandemic and USDA intervention cheese purchases. A range of policy modifications proposed to address negative PPD was evaluated.

Price Discovery in the United States Dairy Industry

Abstract The organized Exchange spot (cash) cheese market is a private industry institution that has historically performed a primary price discovery function in the U.S. dairy industry. In addition to affecting cheese prices in contract cheese market, the Exchange spot cheese prices have influenced prices paid for milk at the farm level that are set within the system of Federal Milk Marketing Orders (FMMOs). The effects that the Exchange spot cheese market has on FMMOs milk pricing attract increased attention in light of the recent concerns about increasing milk price volatility and its effect on the dairy farm profitability. While the design of milk pricing within FMMOs has evolved over the last three decades, the effects of the Exchange spot cheese prices on FMMOs milk pricing have intensified. The research analyzes the conduct and performance of the Exchange spot cheese market during three FMMOs milk pricing regimes (Minnesota-Wisconsin price regime, Basic Formula Price and modern Multiple Component Pricing regime), with a particular focus on the Exchange spot cheese price behavior.

Performance and income over feed costs when feeding alfalfa or grass hays and corn or wheat grains to high-producing dairy cows

The objective of this study was to evaluate the production performance, nutrient digestibility, and income over feed cost (IOFC) of high-producing dairy cows consuming diets containing alfalfa or grass hays with either corn or wheat grain. Twenty-four Holstein cows were randomly assigned to 1 of 4 diets in a replicated 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments (hay and grain types) and 21-d periods. Diets were formulated using a least-cost approach. To determine revenues from milk produced, the amount of ECM (kg·d −1 ) was multiplied by $0.303·kg −1 (i.e., class III milk price; US Federal Milk Marketing Order 5). The cost of the ration provided by the formulation software ($·cow −1 ·d −1 ) was divided by the predicted DMI (kg·cow −1 ·d −1 ) to obtain the cost of feed ($·kg −1 ), which was then multiplied by DMI (kg·cow −1 ·d −1 ) to provide the actual daily feed cost ($·cow −1 ·d −1 ). Cows consuming diets containing alfalfa hay consumed more DM than cows consuming diets with grass hay (27.1 vs. 24.4 kg·d −1 ). Cows consuming diets containing alfalfa hay produced more milk than cows consuming diets containing grass hay (47.5 vs. 44.7 kg·d −1 ). Milk from cows consuming diets containing grass hay had greater fat concentrations than milk from cows consuming diets containing alfalfa hay (4.22 vs. 3.89%). Using hay prices of $418 and $154∙t −1 , respectively, for alfalfa and grass hays, diets containing grass hay resulted in greater IOFC than diets containing alfalfa hay ($8.39·d −1 vs. $7.68·d −1 , respectively). Results of this study showed that IOFC can be supported when feeding grass hay using a least-cost ration formulation approach.

Annual rhythms of milk synthesis in dairy herds in 4 regions of the United States and their relationships to environmental indicators

The annual rhythms of milk and milk component yields are not well described and are important to dairy management. Recent analysis of federal milk marketing orders in the United States observed that the amplitude and time at peak (acrophase) of the rhythms of milk fat and protein concentration differ among regions, but the rhythms of milk and milk component yields are not well described. Our objective was to determine the annual rhythms of milk and milk component production from 4 US regions at the herd level and examine potential environmental factors entraining these rhythms. Monthly Dairy Herd Improvement Association records of all available herds in Pennsylvania (PA), Minnesota (MN), Texas (TX), and Florida (FL) from the years 2003 to 2016 were obtained from Dairy Records Managements Systems. Milk yield, fat and protein yield, and fat and protein concentration were fit to the linear form of the cosine function with a 12-mo period using a linear mixed effects model. Additionally, the fit of models containing either the cosine function or environmental temperature were compared using an F-test. Milk yield and fat and protein yields and concentrations fit a cosine function in all 4 states, indicating an annual rhythm. The amplitude (peak to mean) of the rhythm of milk yield varied by state and was lower in PA (1.2 kg) and MN (1.2 kg) compared with TX (3.1 kg) and FL (3.3 kg). Fat and protein yields similarly showed greater amplitudes in the southern versus northern states. The amplitudes of the rhythms of fat and protein concentration were opposite by region, with greater amplitudes occurring in MN and PA than in TX and FL. The acrophases of milk yield and milk fat and protein yields and concentrations also varied by state, but all peaked between October and March. An annual rhythm fit the data better than changes in environmental temperature for all responses in all states, except for fat and protein concentrations in FL, which exhibited lower amplitude seasonal rhythms. The yearly pattern of milk yield closely followed the fixed yearly pattern of the day to day changes in day length, whereas the rhythms of milk fat and protein concentrations followed the yearly pattern of absolute day length. Results suggest that the region of the United States in which a herd is located affects their annual rhythms of production, with a greater yearly variation in milk, fat, and protein yields occurring in the southern United States. The consistency of annual rhythms across years and herds allowed development of regression equations to adjust expectations across the year to account for the annual rhythm.

Annual rhythms of milk and milk fat and protein production in dairy cattle in the United States

An annual pattern of milk composition has been well recognized in dairy cattle, with the highest milk fat and protein concentration observed during the winter and lowest occurring in the summer; however, rhythms of milk yield and composition have not been well quantified. Cosinor rhythmometry is commonly used to model repeating daily and annual rhythms and allows determination of the amplitude (peak to mean), acrophase (time at peak), and period (time between peaks) of the rhythm. The objective of this study was to use cosinor rhythmometry to characterize the annual rhythms of milk yield and milk fat and protein concentration and yield using both national milk market and cow-level data. First, 10 yr of monthly average milk butterfat and protein concentration for each Federal Milk Marketing Order were obtained from the US Department of Agriculture Agricultural Marketing Service database. Fat and protein concentration fit a cosine function with a 12-mo period in all milk markets. We noted an interaction between milk marketing order and milk fat and protein concentration. The acrophase (time at peak) of the fat concentration rhythm ranged from December 4 to January 19 in all regions, whereas the rhythm of protein concentration peaked between December 27 and January 6. The amplitude (peak to mean) of the annual rhythm ranged from 0.07 to 0.14 percentage points for milk fat and from 0.08 to 0.12 percentage points for milk protein. The amplitude of the milk fat rhythm generally was lower in southern markets and higher in northern markets. Second, the annual rhythm of milk yield and milk fat and protein yield and concentration were analyzed in monthly test day data from 1,684 cows from 11 tiestall herds in Pennsylvania. Fat and protein concentration fit an annual rhythm in all herds, whereas milk and milk fat and protein yield only fit rhythms in 8 of the 11 herds. On average, milk yield peaked in April, fat and protein yield peaked in February, fat concentration peaked in January, and protein concentration peaked in December. Amplitudes of milk, fat, and protein yield averaged 0.82 kg, 55.3 g, and 30.4 g, respectively. Milk fat and protein concentration had average amplitudes of 0.12 and 0.07, respectively, similar to the results of the milk market data. Generally, milk yield and milk components fit annual rhythm regardless of parity or diacylglycerol O-acyltransferase 1 (DGAT1) K232A polymorphism, with only cows of the low-frequency AA genotype (5.2% of total cows) failing to fit rhythm of milk yield. In conclusion, the yearly rhythms of milk yield and fat and protein concentration and yield consistently occur regardless of region, herd, parity, or DGAT1 genotype and supports generation by a conserved endogenous annual rhythm.

An Analysis of Milk Pricing in the United States Dairy Industry

ABSTRACTThe performance of the system of milk pricing within Federal Milk Marketing Orders (FMMOs) has recently attracted increased attention. A dramatic increase in the volatility of milk prices received by dairy farmers has adversely affected dairy farm profitability. Furthermore, the effects that the private Exchange spot cheese market has on FMMOs milk pricing have raised concerns, mostly due to an imperfectly competitive nature of competition process in this market. This research analyzes the behavior of Class III milk price, which is the mover of the overall FMMOs pricing structure, during three milk pricing regimes: Minnesota–Wisconsin price series (1960s–1995), Basic Formula Price (1995–1999), and Multiple Component Pricing (2000–present). The empirical evidence presented in the article indicates that changes in the level of Class III milk price were rather minor in magnitude. However, changes in the milk price volatility were dramatic. There is empirical evidence indicating that the private Exchange spot cheese price is the main determinant of the Class III milk price, which is consistent with the design of Class III milk pricing during the analyzed FMMOs milk pricing regimes. [JEL Classifications: L1; Q1; K2].

An analysis of bargaining power for milk cooperatives and milk processors in Florida

The Florida dairy market has a few fluid milk processors and many dairy farmers. The dairy farmers are represented in negotiation with the processors by a cooperative. This research builds a theoretical model of bargaining between the processors and a cooperative. The model is applied to the Florida dairy market to examine price negotiations between Florida milk processors and a dairy cooperative. An expectation maximization (EM) algorithm along with maximum likelihood estimation is used to estimate the econometric disequilibrium model with time series data for the period of October 1998 to May 2009. The results show that the class I price set by the Federal Milk Marketing Order is the major factor influencing the cooperative’s supply reservation price. Negotiated quantity and production seasonality affect the processors’ demand reservation price. The processors appear to be more patient and have higher average bargaining power (0.8804) than the cooperative (0.1196). The highest (lowest) bargaining power for the cooperative (processors) occurred in 2008 and the lowest (highest) bargaining power for the cooperative (processors) occurred in 2001.

Milk payment systems in the United States

Payment for milk in the United States is primarily controlled by the federal government. Federal Milk Marketing Orders have been in place for a century, and continue to dominate the payment for milk in the United States. The last major revision of the process was implemented in January 2000, and this system still controls payment in 60% of the milk in the United States. Milk is so essential to health that it was controlled to ensure an adequate supply of fresh milk. Essential to ensuring an adequate supply of fresh milk, producer milk pricing processes were developed to help producers survive financially. The paper describes the history and current role of milk marketing orders in the US.

Estimating Market Power of U.S. Dairy Cooperatives in the Fluid Milk Market

A structural econometric model of vertical relationships is adopted to identify pricing behavior in the supply chain for fluid milk in the United States. The model consists of a system of equations that allows estimation of oligopoly power of dairy co‐operatives and downstream firms, exploiting federal milk marketing order regulations to identify co‐operatives’ marginal cost. A key finding is that co‐operatives use their market power to raise the farm price of milk by almost 9% above marginal cost, resulting in an income transfer of more than $600 million per year in markets regulated by federal milk marketing orders.

Consequence of alternative standards for bulk tank somatic cell count of dairy herds in the United States

Noncompliance with current US and European Union (EU) standards for bulk-tank somatic cell count (BTSCC) as well as BTSCC standards recently proposed by 3 US organizations was evaluated using US Dairy Herd Improvement Association (DHI) herds and herds supplying milk to 4 Federal Milk Marketing Orders (FMO). Herds with 15 to 26 tests (frequently monthly) from January 2009 through October 2010 were included. Somatic cell scores (SCS) from 14,854 herds and 164,794 herd-tests were analyzed for DHI herds with ≥10 cows for all tests. Herd test-day SCC was derived as a proxy for BTSCC and was the basis for determining noncompliance and percentage of the milk it represented. For FMO herds, actual milk marketed and BTSCC were available from 27,759 herds and 325,690 herd-tests. A herd was noncompliant for the current EU BTSCC standard after 4 consecutive rolling 3-test geometric means (geometric method) were >400,000 cells/mL. A herd was noncompliant for the current US BTSCC standard after 3 of 5 consecutive monthly BTSCC shipments (frequency method) were >750,000 cells/mL. Alternative proposed standards (600,000, 500,000, or 400,000 cells/mL) also were examined. A third method designated noncompliance when a single 3-mo geometric mean of >550,000 or >400,000 cells/mL and a subsequent test exceeded the same level. Results were examined based on herd size or milk shipped by month. Noncompliance for the current US standard for the 12 mo ending October 2010 in DHI and FMO herds was 0.9 and 1.0%, respectively, compared with 7.8 and 16.1% for the current EU standard. Noncompliance was always greater for the frequency method than for the geometric method and was inversely related to herd size or milk shipped. Using the frequency method at 400,000 cells/mL, noncompliance was 19.1% for DHI herd-tests in herds with <50 cows compared with 1.1% for herds with ≥1,000 cows. For FMO herds shipping <900 t, noncompliance was 44.5% using the frequency method at 400,000 cells/mL compared with 8.0% for herds marketing >9,000 t. All methods proposed increased the percentages of herds and shipped milk that exceeded the regulatory limit. Producers will need to place more emphasis on reducing the incidence and prevalence of subclinical mastitis through known management practices such as proper milking techniques, well-functioning milking machines, postmilking teat disinfectant, dry cow treatment, and culling of problem cows to meet any of the proposed new standards.

Milk Marketing Order Winners and Losers

AbstractDetermining the impacts on consumers of governmental policies that affect the demand for food products requires a theoretically consistent micro‐level demand model. We estimate a system of demands for weekly city‐level dairy product purchases by nonlinear three‐stage least squares to account for joint determination between quantities and prices. We analyze the distributional effects of federal milk marketing orders, and find results that vary substantially across demographic groups. Families with young children suffer, while wealthier, childless couples benefit. We also find that households with lower incomes bear a greater regulatory burden due to marketing orders than those with higher income levels.

Comments for the United States Departments of Agriculture and Justice Workshops on Competition Issues in Agriculture

The Department of Justice and the Department of Agriculture have combined to hold a series of workshops related to the competitive issues affecting America's farmers and ranchers. These comments summarize the competitive issues merit attention in this process. On the farm output side they include the use and abuse of the Federal Milk Marketing Order System as well as other agricultural market orders. These orders are being abused in various ways that harm both producers and consumers. Some of these problems stem directly from the way the USDA has failed to police the ways in which the orders have been written while other problems stem from the failure of antitrust enforcement to control concentration at both the processing and retailing stages of the dairy industry as well as policing the exclusionary practices of dominant cooperatives and milk processors. With respect to livestock and poultry, the competitive problems come primarily from the failure of the USDA to use its authority under the Packers and Stockyards Act to facilitate fair, efficient and open competition in the changing contexts of the poultry and livestock industries, but the DOJ has also failed to limit the increase in concentration on the buying side of these markets which has contributed to the problem of anti-competitive conduct and exploitation. In crop markets, the problems that are emerging relate to the increased concentration of the buying markets, again the result of lax merger enforcement as well as the misuse of market orders in some fruits. Finally, on the input side, there are serious problems for competition resulting from the dominance of important new genetically modified seed technologies by a firm that has used its power to impose unjustified burdens on farmers and is now acting to frustrate technological competition. More generally, farmers are victims of higher input prices resulting from increased concentration in all of the markets providing their inputs.

Prediction of Future Uniform Milk Prices in Florida Federal Milk Marketing Order 6 from Milk Futures Markets

This study assessed the accuracy of 3 methods that predict the uniform milk price in Federal Milk Marketing Order 6 (Florida). Predictions were made for 1 to 12 mo into the future. Data were from January 2003 to May 2007. The CURRENT method assumed that future uniform milk prices were equal to the last announced uniform milk price. The F+BASIS and F+UTIL methods were based on the milk futures markets because the futures prices reflect the market's expectation of the class III and class IV cash prices that are announced monthly by USDA. The F+BASIS method added an exponentially weighted moving average of the difference between the class III cash price and the historical uniform milk price (also known as basis) to the class III futures price. The F+UTIL method used the class III and class IV futures prices, the most recently announced butter price, and historical utilizations to predict the skim milk prices, butterfat prices, and utilizations in all 4 classes. Predictions of future utilizations were made with a Holt-Winters smoothing method. Federal Milk Marketing Order 6 had high class I utilization (85±4.8%). Mean and standard deviation of the class III and class IV cash prices were $13.39±2.40/cwt (1 cwt = 45.36kg) and $12.06±1.80/cwt, respectively. The actual uniform price in Tampa, Florida, was $16.62±2.16/cwt. The basis was $3.23±1.23/cwt. The F+BASIS and F+UTIL predictions were generally too low during the period considered because the class III cash prices were greater than the corresponding class III futures prices. For the 1- to 6-mo-ahead predictions, the root of the mean squared prediction errors from the F+BASIS method were $1.12, $1.20, $1.55, $1.91, $2.16, and $2.34/cwt, respectively. The root of the mean squared prediction errors ranged from $2.50 to $2.73/cwt for predictions up to 12 mo ahead. Results from the F+UTIL method were similar. The accuracies of the F+BASIS and F+UTIL methods for all 12 fore-cast horizons were not significantly different. Application of the modified Mariano-Diebold tests showed that no method included all the information contained in the other methods. In conclusion, both F+BASIS and F+UTIL methods tended to more accurately predict the future uniform milk prices than the CURRENT method, but prediction errors could be substantial even a few months into the future. The majority of the prediction error was caused by the inefficiency of the futures markets to predict the class III cash prices.

Public health, cooperatives, local regulation, and the development of modern milk policy: the Chicago milkshed, 1900–1940

Agricultural policy in the United States is often structured around conflicts and relationships within particular production regions. These regional solutions may evolve into national policies. This paper explores a historical example of this, the development of fluid milk policy and the fluid milk economy in the Chicago milkshed between 1900 and the New Deal. This example is particularly interesting because it was part of the rise of the post-World War II modern food system. Both urban and rural groups were important in this development. Urban groups took a particular interest in milk production and regulation due to its importance as a nutritious but highly perishable staple. Rural groups responded to urban attempts to control production practices by organizing cooperatives. Negotiations and strikes resulted in an agreement in 1929 that was positive for farmers, the Chicago Department of Health, and other major entities in the milkshed. It attempted to place regulatory barriers around the milkshed. However, it soon failed due to improvements in transportation technology and new distribution systems that allowed for cheaper retail prices. The group then proposed a marketing plan to the USDA, which became the ancestor of the federal milk marketing order program. This story sheds light on the manner in which local interest groups and internal politics within the U.S. Department of Agriculture combined to shape New Deal agricultural legislation.

Economic Returns to Holstein and Jersey Herds Under Multiple Component Pricing

This study analyzed component data from herds participating in the Mideast Federal Milk Marketing Order from 2000 through 2002, and its implications for herd profitability. A monthly simulation model was developed to evaluate the economic returns for a representative Holstein and Jersey herd in Pennsylvania under multiple component pricing. Component levels were highly seasonal and variable from farm to farm. A third of the herds during the course of a year realized a 1- to 3-mo temporary reduction in milk fat or protein greater than one standard deviation. Consistently producing milk fat and protein one standard deviation below the mean reduced the Class III value by $0.82/cwt (100 pounds), or 7.09%. The simulation model indicated that a herd of 100 Holstein cows generated $31,221 more income over feed costs (IOFC) a year than a herd of 100 Jersey cows. Although Jersey milk had greater gross value than Holstein milk due to higher component levels, total volume of milk and components produced by Holsteins offset this difference. Simulation results confirm that increasing milk fat and protein percentages by one standard deviation increased IOFC 7.7% for Holsteins and 9.2% for Jerseys relative to the baseline IOFC, with similar losses for component reductions. Increasing milk yield by one standard deviation increased IOFC by 19.6% for Holsteins and 23.9% for Jerseys relative to the baseline IOFC, again with similar losses for reductions in milk production. In all of the scenarios analyzed, the most important factor affecting IOFC was total amount of milk fat and protein produced, not the component percentage levels.

The Effect of the Northeast Dairy Compact on Producers and Consumers, with Implications of Compact Contagion

We model and measure the effects of the Northeast Dairy Compact on prices, quantities, and producer and consumer welfare, underscoring the distribution of these effects across regions and among producer and buyers. Using 1999 as a base year, simulations show that the Compact raised the farm price of milk in the Northeast by $0.45/cwt., lowered the farm price of milk in the rest of the country by $0.02/cwt., and transferred income from producers outside the Compact region and buyers in the Compact region to producers in the Compact region. Non-Compact producer losses exceeded Compact producer gains. Similar results are found for a scenario of Compact contagion— extension of the Compact to include additional states. In both cases, the Compact changed the distribution of the costs and benefits of price discrimination as practiced by milk marketing orders. The implication is that the regional distribution of the Compact's welfare effects raises again the question of the organization of a government-sponsored milk marketing plan such as the federal milk marketing order system.