Consolidation may have allowed dairies to capture improved productivity and efficiency on the farm. How dairy farm size changes in response to these and other factors are important in considering future trends in farm size and their impact on milk production in the United States. My research seeks to help explain recent patterns of farm size change in the dairy industry, considering trends in operator characteristics and management, while accounting for regional differences. The share of women dairy farmers has increased. Historically, farming has been a stereotypically male occupation. Despite contributing to farm production and farm management, surveys, and censuses, have been limited in their collection of data on the contributions of women as farm operators. I hypothesize that some of growth in female contribution to farm operation is due to changes in social and gender norms in reporting. One contribution of my research is to attempt to separate, to the extent possible, changes in management and operations on dairy farms from how such activities are reported. Demographic trends in farm operation and management are important because they help researchers and policy makers get a better sense of who runs the operations in an industry by age, gender, indoor grow cannabis and other characteristics. The dairy industry remains predominately male. However, since 2002, there has been a substantial increase in the share of women dairy farm operators and an increase in the absolute number of dairy farms with at least one female operator in many places.
The share of commercial dairies with at least one female core operator has increased across all states, except New Mexico. New York saw the largest increase in the share of commercial dairies with at least one female core operator from 36% to 55%. California saw a 40% increase in the share of commercial dairies with at least one female core operator. This trend, which has occurred while dairy farm consolidation has proceeded at a similar pace suggests that the participation of female dairy farm operators may positively affect dairy farm herd size and economic viability. As noted in the previous chapter, for the statistical estimation in the thesis I will utilize data for the USDA COA. Under “Census of Agriculture Act of 1997”, The COA is a federally mandated Census of all U.S. farms and ranches every five years, and it captures individual farm-level data on production costs, operators’ characteristics, land use, number of milk cows, revenue, etc. The data and statistics resulting from this Census are reported at the county or state level and research using the individual level data is restricted to USDA research or special request for non-USDA entities. I was given special permission to have access to individual farm-level data for census years of 2002, 2007, 2012, and 2017 from the following specified states: California, Idaho, New Mexico, New York, Texas, and Wisconsin. The National Agricultural Statistics Service , which conducts the Census, attempts to gather responses from every farm in the United States, where a farm is defined as, “is any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the census year.” NASS uses a complex sampling procedure that starts with the Census Mail List .
The CML is a mailing list of all potential U.S. farms, as defined by UDSA, The CML is built and improved upon using outside sources, from government lists or different agricultural producer lists. When new names, of potential farms, are discovered they are then treated as a potential farm and added to the CML until the farm is found to not meet the USDA definition of a farm. From there Census data is collected by mail or Computer Assisted Self Interview on the Internet. The respondents submitted one of four different forms: general, short, Hawaii, or American Indian form. The COA data that I use can be described as unbalanced panel data with both attrition and replacement and with occasional errors in recognizing continuing cross-section units. Although the data used is at the individual farm level, no data presented in this thesis reveals any information concerning an individual farm or person. All present research has been subject to a disclosure review and all research using COA data follows the following guidelines, “In keeping with the provisions of Title 7 of the United States Code, no data are published that would disclose information about the operations of an individual farm or ranch. All tabulated data are subjected to an extensive disclosure review prior to publication. Any tabulated item that identifies data reported by a respondent or allows a respondent’s data to be accurately estimated or derived, was suppressed, and coded with a ‘D’. However, the number of farms reporting an item is not considered confidential information and is provided even though other information is withheld.” The survey questions asked of farmers and ranchers by the COA change slightly every Census round, although most questions remain the same across rounds. Below are descriptions of questions changes for relevant variables to the analysis. First, in 2002 and 2007, farms were asked for the total amount of milk or dairy sales in that year, but in 2012 and 2017, this question was dropped and replaced with the total amount of milk sales. Second, operator characteristic questions have become more detailed over the years and allowed more operators to be captured by the Census.
In 2002, 2007, and 2012, the COA asked detailed operator characteristic questions about up to three operators, and only one operator was able to be identified as the principal operator. The COA defined a principal operator as “… the person most responsible for making day-to-day decisions on the farm, during the data collection process.” Whereas an operator is defined as “A farm operator is a person who runs the farm, making day-to-day management decisions. An operator could be an owner, hired manager, cash tenant, share tenant, and/or a partner. If land is rented or worked on shares, the tenant or renter is an operator.” However, in 2017, the COA expanded its detailed operator questions to include up to four operators and now allows for up to four operators to be identified as a principal operator. The definition of principal operator is “Demographic data were collected for up to four producers per farm. Each producer was asked if they were a principal operator or senior partner. A principal operator is a producer who indicated they were a principal operator. There may be multiple principal producers on a farm. Each farm has at least one principal producer.” Whereas operators were defined as “A non-principal is a producer who did not indicate they were a principal operator. There may be no non-principal producers on a farm.” Furthermore, in 2012, curing cannabis the COA started asking farmers and ranchers if the secondary operators were married to the principal operator. This question was then adapted in 2017 to reflect the increase in possible principal operators identified and asked if the operator was married to a principal operator. For our further data analysis, I consider farms that have substantial dairy operations. I want to leave aside those operations that meet the USDA definition of a farm but have minimal connection to commercial dairy production and revenue. To be included as a commercial dairy operation in our sample requires meeting two minimum criteria. First, the farm must have dairy or milk sales revenue above the dollars of milk sale revenue that would have been generated by 30 milk cows. Second, at least 20 milk cows were on the farm as of December 31 in the Census year. This minimum was set to remove dairy farms that had “exited” and had already removed most of their cow from the farm but still had milk or dairy sales revenue for the year above our minimum criteria. For this research I choose to analyze dairies from six states, California, Idaho, New Mexico, New York, Texas, and Wisconsin. These six states were chosen for my research because they capture the major the U.S. commercial dairy industry and therefore are a useful and representative characterization ofU.S. dairy farming. The following Chapter details the reasoning behind the selection of the six states and characterizing the U.S. dairy industry on the whole. The six states used in this research were selected because they capture a significant share of the U.S. dairy industry and reflect the overall trends. Figure 3.1 shows that these select six states make up the majority share of the total number of milk cows in the United States.
These six states made up almost 55% of total U.S. number of milk cows in 2017 and demonstrated an increasing trend in share of U.S. number of milk cows since the 2002. Figure 3.2 shows that these six states also make up the majority share of milk sales revenue in the United States, with Texas and California making the largest shares in the group. The six states are the leading milk producers in the United States. Although, there are significant differences between each state that I will discuss below, including differences in herd size trends. They represent the majority of the dairy industry, by multiple measures, and they are and representative of national distribution. As discussed in Sumner and Wolf the Eastern states are characterized with many smaller dairies than the other states, including New York and Wisconsin. Whereas, Pacific and Southern states such as, California, Idaho, and New Mexico and Texas , tend to have dairies with larger herd sizes. From 2002 to 2017, California saw a 36% decrease in the number of commercial dairies and a slight larger percentage decrease for farms with milk and/or dairy sales and farms with milk cows. Idaho saw its largest decrease in the number of commercial dairies with farms with milk or dairy sales close behind. However, farms with milk cows only decreased by 20% in Idaho. New Mexico had a very slight 3% increase in the number of farms with milk cows, but a 21% decrease in the number of farms with milk and/or dairy sales and a 26% decrease in the number of commercial dairies. New Mexico saw the smallest percent decrease in commercial dairies from 2002 to 2017 of any of the six select states. New York had about a 50% decrease in the number of commercial dairies and about a 40% decrease in the number of farms with milk cows and farms with milk and/or dairy sales. Texas had the largest percent decrease of across all definitions of dairies. Texas saw a 56% decrease in the number of commercial dairies and 60% decrease in the number of farms with milk and/or dairy sales. Interestingly, there was a 78% decrease in the number of farms with milk cows in Texas which is a significant decrease. Across all three definitions of a dairy Wisconsin had very similar trends with about 46-49% decrease in the number of dairies. In California, there tends to be an increase in larger herd sizes. Figure 3.3 shows the number of farms with milk and/or dairy sales in California for the four Census years and the share of farms with milk or dairy sales by herd size. California saw significant decreases in the smaller herd sizes. Figure 3.4 shows the share of all milk or dairy sales and number of farms with milk or dairy sales by herd size for the state of California. From 2002 to 2017, the share of revenue generated by smaller herd sizes has decreased significantly. The majority of the share of milk or dairy sales revenue has come from dairies with 1,000 or more milk cows and this share has increased to over 80% in 2017. Idaho follows a similar trend as California, Figure 3.5 shows a significant decrease in the smaller herd sizes and growth in the larger herd size groups. Furthermore, between 2002 and 2017 there was significant increase in the share of milk and/or dairy sales from farms with herd sizes greater than 1,000 milk cows . The share of sales revenue from farms with herd size smaller than 499 milk cows fell from about 15% in 2002 to less than 10% in 2017.