Listing a female farm operator among all the farm operators may be at least correlated with a willingness to adopt new technology, diversify sales, or increase vertical integration on the dairy farm. This is a feasible hypothesis because the presence of a female operator may indicate that the farm is more open to change than many peers in the industry. Part-time farming is common in crop and beef cow-calf operations, whereas commercial dairy farm operators tend to be full-time operators. Also, in the dairy industry, a female operator of dairy farms is likely to be married to a principal operator. Having both spouses as farm operators likely implies less off-farm income and, therefore, higher financial reliance on the dairy farm’s success than for families with more diversified income sources. Moreover, dairy farms tend to have more concentrated farm incomes with crop and dairy enterprises vertically integrated rather than the diversification common among crop farms. This changes the incentives of the spousal operators to remain economically viable because it likely increases risk aversion leading to diversification of sales and mitigation of feed price volatility risk by increasing economies of scope. The COA finding of an increase in the share of women dairy operators and farms with women operators reflects three things: an actual increase in women operators playing a more prominent role, their male associates being more likely to recognize and report female operators, weed drying room and changes in COA questions that better collect previously unmeasured management activity by women.
The increase in the share of female dairy farms must be considered against the broader pattern of dairy farm consolidation, changes in dairy farm size distribution, farm characteristics, and geographic shifts . This research seeks to provide statistical evidence of differences in farm size of dairies operated by dairies with at least one female operator relative to all male operators, the share of female operators, and those operated by spouses. By considering farms with at least one female operator and/or married operators as a “treatment” group, I compare the herd size, milk or dairy sales, and total value of production, between the two treatment groups, while holding location and year constant. This chapter is structured as follows: a brief overview of previous literature on the intersection of women and agriculture, a description of COA data related to women and farm operators, a discussion of statistics, empirical method, and results, and then a brief conclusion. Research on the intersection of women and agriculture has tended to be limited in scope and by academic discipline. Previous research on the topic from an agricultural economic perspective has focused on the intersection of women and agriculture in developing countries or limited its analysis to some demographic statistics on female farm operators without much commodity distinction within the agricultural industry. Industry distinction is important because of generally held assumptions about particular commodity farms, including that dairy farms are run by spouses. Moreover, although there have been many anthropology and sociology research studies that have been done on the intersection of women and agriculture in both developing and developed countries, these have tended to be on a case study basis that are limited in geographic scope. I found little empirical agricultural economics research on the patterns over time and across states of female farmers, and I found no prior research on the economics of patterns of female operators in the dairy industry, specifically.
A recent article by Schmidt et al. summarizes the current literature on the intersection of women and agriculture, specifying that most economic literature on this subject focuses on developing nations. The article calls for further research on this topic to further characterize the change in gender demographics and collect information on influences in the economy that may have impacted or continue to impact the number of female farm operators in agriculture. Schmidt et al. outline three possible influences on the share of female farmers, including push-pull factors, characteristics of local agriculture, and the type of farming practiced. Push-pull factors refer to the influence of off-farm employment wages that may influence an individual’s decision to be an entrepreneur or push them to seek off farm employment. For this analysis, this influence could be considered on an individual basis or at a spousal level. The change incentives when both spouses’ incomes come from farming could change and push or pull one or both spouses into off-farm employment or to stay on the farm. Characteristics of local agriculture describe the general state of the region’s agricultural economy. This is accounted for by holding constant location and presenting statistics by state. Finally, Schmidt et al. suggest the influence that the type of farming might have, or farming characteristics may influence, as their results find that farms run by women tended to be smaller. There is some association of dairy farms being family-run, or spousal run, this claim is one that we provide evidence on for the dairy industry, specifically. The characterization of such influences provides insight into the possible impacts of female representation on farms across different industries. Again, the agricultural economic literature on the intersection of gender and agriculture has tended to be limited to developing countries. However, in a recent article by USDA Economic Research Service , ERS released statistics about the characteristics of U.S. female-run farms and female operators based on the 1978 to 2007 COA . Their results focus mostly on statistics of characteristics of overall U.S. female-run farms and female farm operators.
They find that 58% of all female operators have no reported off-farm labor, and that female operators of dairy farms tend to be younger than the U.S. female operators’ average age. Griffin et al. utilize the COA data over five Census rounds and discuss the impact of farm operators’ demographics on farm exit rates. They find that larger farms are less likely to exit, and those female operators are more likely to exit than male operators. However, their study includes all farms with no industry limitations. Furthermore, research on female operators’ impact and representation within the dairy industry is a point of interest because, historically, it was not uncommon for dairy farms to be run by spouses and because off-farm employment is less likely on a dairy farm than it is on other farms. Sander finds that women working on dairy farms tend to have less off-farm employment than other farm types. He outlines the role of income variability on farms run by spouses’ decision to be both spouses’ main income with off-farm work as a possible risk mitigation strategy for farms run by spouses when farm revenue is highly variable. Schultz detailed some economic theories related to women focusing mainly on developing nations. Specifically, drying rack for weed the role of family dynamics in economic choices on farms and female influence on such outcomes. Rather than taking a theoretical approach, Zeuli and King provide detailed statistics of the characteristics of farmers and their commercial farms in 13 states. They find that in 1991 the average age of females relative to males is insignificant, but that the women in their sample tended to have a higher level of schooling. Interestingly, they found contradicting results, at least based on acreage, to other studies stating that women tend to manage smaller farms, with women operating more acreage on average, but this could be heavily influenced by what they grow and location. Sociology and anthropology research on female farm labor and agriculture tends to report findings based on case studies of specific regions and industries . These papers tend to discuss social incentives, norms, or barriers that influence the gender demographics of the industries of interest and, therefore, influence female representation and the impact of management decisions on the farm. Brasier et al. discuss the history of how women identify their labor on farms. Historically, female participation in farming communities was accessed through family or marriage. Typically, women involved in agriculture were either born into a family that farmed or married a farmer. In the past women often viewed their role on the farm as farm homemakers or farm helpers, following gender norms of the times, and often because they had off-farm income or only participated in farm labor seasonally . This way of thinking about farm labor could have influenced the representation of female operators of farms. Other sociology research has documented trends in farm management through case studies on regions. Trauger finds that women are more likely to adopt sustainable agriculture. Trauger limits its scope to a few farms in Pennsylvania, finding that there may be a trend of female-operated farms to adopt socially minded practices, i.e., community education. This research helps build evidence that supports our claim that the presence of female operators can be considered a proxy variable for being adaptable to change.
It seems like a basic assumption, but there was, and remains, a large share of women that participate in farm labor that were/are married to principal operators; this trend continues today. Therefore, the research on the relationship between gender and agriculture would not be complete without mentioning research done on agricultural spouses. A large share of female operators are the spouses of a farm operators. Barlett details the typical marriage models of agricultural spousal relationships, characterizing how farm labor related to agricultural spousal relationships is defined from a social perspective and may have influenced how women viewed their labor on the farm and subsequently the data representing farm labor, historically. The role of identity for female farmers and the professional connections can be a pivotal part of female farmer participation. This research provides evidence of the change in gender demographics based on farm size for the dairy industry. It adds to the literature detailed agricultural economic analysis on the intersection of women and agriculture for the dairy industry and discusses the change in data collection and availability by one of the most prevalent data sources for agricultural data, the COA. The survey questions asked of farmers and ranchers by the COA change slightly every Census round, although most remain the same across time. 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 dairy sales in that year, but in 2012 and 2017, this question was dropped and replaced with the total amount of milk sales. Furthermore, whether the dairy farm had any level of organic production was only asked 2007, 2012, and 2017. Second, operator characteristic questions have become more detailed over the years and allowed more operators’ data to be collected. 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. 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. 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 Census collects two categories of operators. The first category is for which detailed operator characteristics and for which at most three operators are listed per farm in 2002-2012 and at most four operators per farm are listed in 2017. Going forward, the operators for which the number per farm is limited and detailed information is provided will be referred to the “core operators”. The second category has no limit to the number listed per farm and only gender of each operator and the number per farm is provided in the data. This section detail statistics and characteristics of female commercial dairy farm operators and their commercial dairies. The number of commercial dairies with at least one female core operator increased in every state, except New Mexico, which experienced no change from 2002 to 2017 . In 2017, every state, but New Mexico, has more than 40% of the commercial dairies reporting at least one female core operator. Although these states demonstrate significant increases in the representation of female core operators, the addition of a fourth core operator for the 2017 Census could distort these results.