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, grow tables 4×8 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, 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.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 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, ebb flow tray 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. New Mexico saw an increase in the number of farms with milk and/or dairy sales between 2002 to 2007, but then subsequent decreases in 2012 and 2017 . Overall, there was a decrease in farms with herd sizes between 200-999 milk cows. Figure 3.8 show the relative decrease in farms with milk and/or milk sales in New York and the decrease in the share of dairies with 1-199 milk cow herd size. There was an increase in the number of farms with a herd size greater than 1,000 milk cows. Figure 3.9 shows a decrease in the number of dairies with milk and/or dairy sales with significant decrease in the share of farms with a 1-199 milk cow herd size between 2002 to 2017 in Texas. There was also an increase in the number of farms with herd sizes greater 1,000 milk cows. Figure 3.10 shows that between 2002 and 2017 Texas farms with a herd size greater than 1,000 milk cows saw a significant increase in the share of milk or dairy sales revenue, from about 40% in 2002 to almost 90% in 2017. The majority of Wisconsin farms have a small herd size, although there has been a decrease from 2002 to 2017. There has been an increase in the number of farms with larger milk cow herd sizes . Figure 3.12 shows that the majority of milk and/or dairy revenue in Wisconsin used to come from farms with smaller milk cow herd size but has shifted overtime towards farms with larger milk cow herd sizes.The size distribution of farms in the U.S. has been a topic of economic research and discussion for decades. Changes in farm size along with reductions in farm numbers have raised concerns based on it the possible impact on rural communities, particularly movement out of certain regions leading to a possible decrease of employment opportunities in that region. Moreover, accurate and descriptive analysis of farm size is often used to inform agricultural policy and discussion, particularly in the dairy industry. In both industry discussion and policy-based decision-making, surrounding farm size, the trend of consolidation is central to the discussion on the future of the dairy industry. Some suggest that the trend of farm size is characterized by consolidation with an increase in large farms, and fewer small farms remaining. One assumption is centered around the idea of the disappearing middle, mid-sized farms, in agriculture with some arguing that the farm size distribution can be considered bimodal. This language can be vague and detailed analysis by state is needed for a clear characterization of farm size. Wolf and Sumner find that the argument of U.S. farms being bimodal is not the case for the dairy industry in 1989 and 1993. This thesis research aims to expand on this finding by discussing correlations related to farm size changes, kernel density plots of herd size and using parametric statistical density functions to characterize the herd size by state, utilizing recent Census of Agriculture data. The COA is a representative sample of all farms in the United States. This is individual farm level data across six states and four years which is a unique sample for research studies. This research looks at individual farm-level characteristics including farm size and operator characteristics and discuss the shifts across time and states. The trend of dairy consolidation in the United States has been characterized by a decrease in the number of dairies with the number of milk cows remaining relatively stable . Using the COA data, the number of milk cows on a commercial dairy has remained relatively stable with most states seeing slight increases in the number of milk cows, except New York . Whereas the number of commercial dairies has decreased significantly across all six states, except New Mexico which only decreased slightly . California and Idaho both had about a 36-37% decrease in the number of commercial dairies, while in New York, Texas, and Wisconsin the number of commercial dairies decrease by about 50%. Farm size distribution remains a prevalent agricultural policy issue, as characterization of the dairy industry’s farm size is used to inform legislation and often characterizes colloquial discussion about the state of the industry. This is in part due to firm size growth’s correlation with innovation and technology, as well as the firm’s ability to capture economies of scale.