Once referred to by President Lincoln as “The People's Department,” the United States Department of Agriculture (USDA) aids individuals in agricultural related fields. Since 1862, the USDA has financially supported farmers and low-income individuals through farm related programs. As the 2014 Farm Bill quickly reaches expiration, policy-makers are working on to allocate roughly $140 billion among USDA's programs. Yet, we often see a disconnect between American adults' preferences and decisions made by policy-makers in the United States when it comes to answering question: how much money should be allocated to the various support programs. If people feel that they have a voice in how tax money is spent, compliance and feelings about taxes could improve (Lamberton 2017).
In this paper, the big question that we explore is: if people were given a voice on how the USDA allocates their tax dollars, will their preferences differ from current budgetary priorities? We also look into two smaller questions. The first question is: does information on all USDA programs and its budget for 2018 affect people's allocation? The second question is: how do different factors such as sociodemographic characteristics, trust in the United States government, and party affiliation affect people's preferred allocation? To answer these questions, we estimate participants' preferences on USDA spending through an original survey.
Our research adds to the existing literature in numerous ways. Unlike other studies on the topic, our study incorporates farm and commodity programs with nutrition assistance, conservation and forestry, and other programs (Rural Development, Food Safety, Research, Marketing and Regulatory, and Departmental Management) into one survey. By researching overall USDA spending, we will have a better understanding on American adults' preferences on USDA spending as a whole.
The paper is structured as follows. In section 2, we discuss other authors contributions to the subject matter. In section 3, we explain how we collect our data and provide summary statistics. In section 4, we explain our method. In section 5, we discuss our findings. Lastly, we conclude our paper in section 6.
2 Literature Review
There are a variety of surveys that conduct research on individuals' preferences on United States Department of Agriculture's spending, but a majority of the studies focus particularly on farmers' preferences. For example, Zulauf, Guither, and Henderson (1987) conduct research on how much farmers and agribusinesses support farm programs. In another paper, Guither, Jones, Martin, and Spitze (1989) discuss whether farmers support farm programs that benefits small farm only, large farms only, or both small and large farms. The two surveys capture farmers' and agribusinesses' preferences on farm program spending, but they do not capture the average American's preference.
Variyam and Jordan (1991) analyze United States citizens' preferences of farm policy spending. In their results, they find that knowledge on farm sizes play a significant role in people's support of farm programs. For instance, individuals often associate small farms with being a family farm, so the individuals are more likely to support small farms, and individuals associate large farms with being a nonfamily farm. Variyam and Jordan asses how perception of farm sizes affects preferences on farm support programs. In addition, Variyam, Jordan, and Epperson (1990) evaluate how demographics play a role in preferences of farm support. In their research, they analyze how an individual's political party preference, age, income level, and gender play a role in their support of farm programs.
Ellison (2010) writes the most relevant research to my topic. In the article, Ellison and others analyze taxpayers' preferences on farm policy. Using a survey, Ellison gathers data on demographic variations and farm policy references of individuals residing in three cities. From this study, Ellison concludes that neither demographics nor political preference have a substantial effect on individuals' attitudes towards farm support. Instead, the study finds that participants' perceptions of a farmer's income play a role in an individual's support of farm policy. Ellison concludes that the average participant seeks to increase farm support for small farms and decrease subsides to large farms.
For our research, we use a fractional multinomial logit model. The model allows us to capture our dependent variable, participants' preferences for USDA spending, in multiple proportions. The model, created by Sivakumar and Bhat (2002), combines the fractional logit model and the multinomial logit model. We see the fractional multinomial logit model be applied by others (Allen 2012, Ye and Pendyala 2005; Mullahy 2010; Koch 2010). Allen (2012) uses the model to estimate the effect of household and production attributes on various crops.
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