Why does the American Public Support Redistributive Logrolls?
An Analysis of Policy Preferences for the 2014 Farm Bill
Stephen Ansolabehere, Harvard University
Kattalina Berriochoa, University of Massachusetts, Boston
May, 2016
Abstract
The Farm Bill, a combination of commodity price supports and food stamps, is widely cited and criticized
as one of the archetypal examples of logrolling, or divide-the-dollar, politics in Congress. Legislators
seek reelection by appealing to the rural farm vote in their districts through subsidies for agricultural
products general and for specific crops, but since different crops are grown in different areas the bill is
seen as a package deal to buy the support of a majority of legislators. Why the agricultural programs
survive into the 21st Century is puzzling, because in no Congressional District in the United States are
farmers a majority, or even 25 percent of the population; nor are poor people a majority of the
population in any Congressional District. Much of the literature on the farm bill argues that lobbying or
campaign contributing, rather than voters’ preferences, drives such pork barrel politics. We show that
support for the bill is, in fact, electorally popular, but public support for such a redistributive logroll is
not driven primarily by voter or district interests. Rather, the main drivers of public support for the Farm
Bill are voters’ ideologies, partisanship, and views other-regarding preferences about who benefits.
While we perceive the farm bill as one that impacts minority groups (family farms or the poor), in fact,
the public considers how this policy impacts the “average” person, arguably those in the middle class.
I. Introduction
The Farm Bill is at the symbolic center of food issues and food policy in the US. A combination of
commodity price supports and food stamps, it is a sweeping national policy that seeks to control prices
due to agricultural surplus while simultaneously assisting the low-income in accessing the basic
necessity of food. It is a legacy of the farm crisis of the 1920s, the New Deal of the 1930s, and the Great
Society of the 1960s (Saloutos 1974; Hansen 1991). Price supports began as a short-term fix to
fluctuations in commodity prices in the 1920s and were extended into a major piece of economic
stabilization legislature during the New Deal. With the farm population and the farm vote dwindling,
the Food Stamps program, or SNAP, was added to the agricultural price support program in order to
broaden the coalition supporting the Farm Bill. The combination of commodity programs, which
brought support from rural districts, with Food Stamps, which garnered support from inner city urban
districts, the Farm Bill became a permanent feature of US law, even though the farm population had
dropped to approximately 2 percent of all persons in the US by the 1980s.
The Farm Bill is also one of the prime examples of logrolling, or divide-the-dollar, politics. Voters in one
district benefit from one sort of expenditure, and voters in another district benefit from another sort of
expenditure. Neither program would pass on its own, but the representatives from the two districts
make a deal to create a piece of legislation that contains both districts (Buchanan and Tullock 1962;
Tullock 1970). Such logrolling has long been criticized as inefficient and counter to the public interest,
as the voters in the districts that receive money benefit, but those in other districts bear the costs
(Tullock 1998; Roosevelt Institute, 2015; Levitan, Taggart, 1976). The Farm Bill is somewhat distinctive
in terms of its beneficiaries. At least 80 percent of the revenue authorized by the Bill benefits poor
people who are eligible for the SNAP program. It is, in other words, a redistributive logroll, a piece of
pork barrel legislation that provides benefits primarily to poor people, rather than to wealthier
economic segments of society or corporations or particularistic, entrenched interests. Both New Deal
and Great Society policies have been criticized due to the involvement of government and due to their
redistributive nature (Roosevelt Institute, 2015; Levitan, Taggart, 1976).
Why does Congress pass the Farm Bill? In many ways, the Farm Bill, passed most recently in 2014,
defies conventional political science theorizing. First, it is indeed a logroll, but in no district are
beneficiaries a majority of the population or of voters. The typical divide-the-dollar game assumes that
districts or the legislators in a district support a proposal if a majority of voters in the district benefit
from the program (Tullock 1970; Baron and Ferejohn 1989; Tullock 1998). In fact, in every district the
median voter is a net payee into the commodity and food stamp program. Second, it may be the case
that agribusiness, working through lobbyists and campaign contributions, win the day (Hansen 1991;
Kau and Rubin 1979). However, the lions’ share of the money in the Farm Bill -- an estimated 80 to 85
percent -- goes not to corporate farms or agribusiness but to poor families. The continuation of the
Farm Bill and the redistributive logroll it embodies presents a puzzle; it does not fit neatly into our
theories of legislative bargaining over pork barrel projects or of interest group lobbying and influence.
We argue that the continued success of the Farm Bill lies in its popularity among voters, and that
popularity is based on party, ideology, and other-regardingness, rather than narrow, economic selfinterest. In short, people think this sort of redistribution combined with price stabilization is either good
policy, or the right thing to do, regardless of whether they benefit. And, they strongly prefer keeping
1
the program around to proposals to repeal the law outright. Against, this public backdrop, it makes
sense that Congress continues to renew and reauthorize the Farm Program, even as farm population
and the farm vote continues to decline.
We study public opinion concerning the 2014 Farm Bill, more affectionately known as the Federal
Agriculture Reform and Risk Adjustment Act of 2013. By 2013, Congress had long delayed the renewal
of the Agriculture Adjustment Act, and, if the federal law expired, the price subsidies would have
reverted to their pre-1933 levels, which were much smaller, and the Food Stamps program would have
vanished. A vocal faction, perhaps even a majority, of the Republican caucus demanded repeal of the
Food Stamps program, and at least one version of the Agriculture Act introduced into the House
proposed the end of SNAP. At the same time, Republican Congressional leaders were locked in a
showdown with the Obama Administration over the budget, and even threatened a shut-down of the
federal government and possible default of federal bonds. In short, the fate of the Farm Bill looked
bleak, and the end of both commodity subsidies and the food stamps program appeared to be at hand
in 2013. Yet, before the end of the summer of 2013, both the House and the Senate passed the Farm
Bill, and in February 2014 the Conference Committee report was approved by both Chambers of
Congress and the President signed into law a new Farm Bill, authorizing $1 trillion in spending on food
stamps and agricultural insurance over a 10-year period. It was the only piece of major legislation
passed by the 2013-2014 Congress.
From a research perspective, the farm bill offers an interesting point of examination for analyzing the
factors which drive public preferences for redistributive policy. Each piece of the farm bill (food stamps
and farm subsidies) are dependent on one other for legislative passage yet seemingly at odds on the
political spectrum. Farm subsidies have been traditionally framed as a tool to protect family farming, a
symbol of the American agrarian myth that represents hard work and independence (Lobao, Meyer,
2004). Early on, farmers were deemed “deserving” of government aid. In contrast low-income families
who utilize food stamps have been subjected to a negative public image (Schneider, Ingram, 1993). The
objective of this project is to analyze if public opinion is divided regarding the two main components of
the farm bill: supporting farms and feeding the poor.
Derived from specific literature, we seek to test three primary hypotheses:
o
o
o
Public support for this bill derived by what individuals receive in their district (Hansen
1991). Even if individual beneficiaries are not a majority, they make care very intensely,
or these programs may generate significant spillovers in the districts. Hansen (1991)
uses a cut off of 10%: If 10% of people in a district are farmers, it is a farm district.
Ideological beliefs and assessments of whether the policy is in the public good might
drive support for the Farm Bill. Alesina and Giulian (2009) argue that ideology and
demography will matter, and that demography (apart from self-interest) reflects otherregarding preferences.
Partisan alignments might determine who supports the law and who does not, with
Democrats supporting the Food Stamps program, and Republicans divided over the
agricultural programs ( Musser and White 1977)
These conjectures are not exclusive. We seek to gauge their relative importance in public support for
the 2014 Farm Bill, and for the Food Stamps and Agriculture Commodity Support Programs.
2
Through statistical analysis of the Cooperative Congressional Election Survey (CCES), we illustrate that
demographic and ideological factors are more significant in policy preferences compared to benefits
received in a district. In particular, we find that the public preferences for the farm bill are driven
primarily by income and party affiliation, rather than benefits received in a district. We interpret this
finding as contrasting evidence to the work of scholars who credit farming interest groups as the driving
forces in passing the farm bill (Hansen, 1991). In a broader sense, these findings also reevaluate our
knowledge about the farm bill and lead to greater understanding about the preferences which continue
to drive support. Finally, a forthcoming paper will draw from the following lessons and further analyze
the political economy surrounding this piece of legislation, as well as the gaming tactics that lead to
compromise and legislative deal-making.
There are clear limitations to this study. First, in our sample, there are very few individuals who identify
as farmers; only nine respondents worked in the field of agriculture. That, however, is indicative of how
small the farm population and the farm vote truly is. Yet from this analysis, we can discern factors that
drive public preferences for both policies tied together in the Farm Bill. This is a deviation from the
current literature on this piece of legislation. Much of the literature about the Farm Bill has either
focused on isolated political analysis on the continued success of this piece of legislation in an
increasingly divided political environment. Many studies ask the following question: considering the
changing relationship of agriculture in society, how can Congress continue to find support for
agricultural commodity programs instituted through the Farm Bill (Alvarez, 2005; de Gorter and
Swinnen, 2002; Swinnen, 2010). Thus, much of the focus on the Farm Bill, has been from the perspective
of congressional action. We seek to fill a gap in the literature by analyzing the Farm Bill from the
perspective of the public, rather than from the perspective of public institutions. In addition, we also ask
survey respondents about their opinions regarding different versions of the Farm Bill, allowing for a
more nuanced interpretation of the individuals who support or oppose this legislation.
II. Background
Supporting farms or feeding the poor?
In terms of numbers, farmers are increasingly becoming the minority constituent of the Farm Bill. Based
on the numbers, family farms have decreased in numbers, while the usage of the supplemental nutrition
program had been consistently increasing, since 2008 by approximately 70% (Lobao, Meyer, 2004;
Hamilton, 2014). According to 2012 Census of Agriculture, of the nearly 319 million people living in the
US, only about 2% of the total population identify as farmers (US Census, 2012). In the case of principal
operators (those primarily responsible for the day-to-day operation of the farm), the number of U.S.
farmers declined between 2007 and 2012 by 4.3 percent (Ag Census, 2012). However, average farm size
increased between 2007 and 2012 by 3.8 percent, or roughly 418 acres to 434 acres (Ag Census, 2012).
These numbers illustrate the trends in farming: farmers are decreasing, while the size of farms are
increasing.
Regardless, current views towards farming are based in depression era images of economicallydepressed farmers. According to Lobao and Meyer (2004), the myth of farming is based on the idea of
land-ownership by farmers who support families through farming as a primary economic means. This
idea has been so deeply engrained in the American understanding of farming that the occupation and
3
way of life have taken on mythological proportions—much like the “flag, democracy, and baseball”
(Lobao, Meyer, 2004, 20). In this context, the influence of farming is based on more than just organized
advocacy groups. Farming has changed as an economic endeavor, yet the power of farming in policymaking is firmly rooted in an unchanged image of farmers from the by-gone depression days.
While farming is becoming a less-likely way of life in the US, the SNAP (food support) program has grown
in size (SNAP data summary, 2014). In contrast to the numbers of farmers, the number of participants in
the SNAP program has increased from 2007 to 2012 by approximately 26 million up to 46 million
participants (SNAP data summary, 2014). In 2014 the number of participants was over 46 million—
however, due to cuts in the final farm bill legislation the number of participants in 2015 was expected to
decline by around 800,000 individuals (SNAP data summary, 2014). The SNAP program was, next to
direct payments, one of the more controversial aspects during the passage of the 2014 Farm Bill.
The largest piece of the Farm Bill pie is that dedicated to providing food for low-income families.
However in 2013, for the first time since 1973, the House passed a version of the farm bill that
completely removed food subsidies for low-income individuals and families from farm bill legislation
(Weisman, Nixon, 2013). Legislators, and groups such as the farm lobby, adamantly disagreed with the
division of food subsidies from farm subsidies (Hamilton, 2014). It would not be until 2014 when a
significantly altered and modified version of the Farm Bill would be passed. In terms of agricultural
subsidies, the 2014 version repealed direct and counter-cyclical payments to farmers, but increased
spending on crop insurance (Agriculture Act of 2014). Although it remains the largest spending
component of the bill with over 70% of all funding allocated to food subsidies, the 2014 version
decreased funding for the SNAP program by approximately 8 billion dollars between 2014 and 2023
(Nixon, 2014). Signed into law on February 8 by President Barack Obama at Michigan State University,
the 2014 farm bill reflected the changing political nature driving agricultural and food policy on the
national level. Much of the difficulty surrounding the passage of this bill was due to legislators who
generally opposed redistributive government spending, but primarily those opposed to food subsidies
for low-income families (Hamilton, 2014).
Is support for this bill derived by what individuals receive in their district?
Hansen (1991) offers a historical perspective as to the early days of farm power in Congress and the
eventual entangling of food and farm policy in the 1970s. According to the author, the passage of the
original Agricultural Adjustment Act in 1933 was the culmination of years fighting for growing influence
in Congress by the farm lobby. At that time, the problems devastating agriculture were both salient and
held a competitive advantage (Hansen, 1991, 97). Through the following years, the farm lobby, primarily
the Farm Bureau, held the demanding attention of Congress; a fact that produced institutionalized
agricultural supports, rather than temporary policy approaches.
This influence of the farm lobby and the farm vote was fated to wane. Migration from farms to cities in
the fifties onward, shifted influence from rural representative to those from urban communities.
Changing social demands in the 1960s eventually forced together urban and rural advocates, both of
which were dealing with growing hunger issues in America. Ideologically, the two groups were on odd
ends of the spectrum; however, the union of urban and rural interests resulted in the inclusion of food
stamps into the 1964 farm bill. According to Hansen, joining the two items together under one
legislative banner reaffirmed congressional access and influence by the Farm Bureau (1991). In addition,
4
rural regions benefited from the food stamp program, which doled out funding based on national
eligibility requirements, meaning all states received similar dollar amounts from the program.
Hansen uses the farm bill as a case study into how groups access influence over time. He concludes that
interest groups are a form of elite influence, representing only some constituents (Hansen, 1991, 230).
Political elites, in fact, are those with open access to interest groups in the policy-making process.
Support for public policy, then, is rooted in the elite and interest groups that effectively advocate for a
specific issue.
We contest this notion. Hansen (1991) builds a theory of access between the farming and consumer
lobbies based on their competitive advantage over one another, effectively illustrating the failure of the
consumer lobby in the 1970s. Hansen states that the goal of “interest groups is amplifying voices,
articulating demands, and promoting common interests” (1991, 230). We build on this idea that
interests groups are only vessels for public support, but deviate from Hansen’s findings that farm lobby
holds competitive advantage over the consumer lobby. Evidence for this finding is based in the statistical
analysis of public opinions for the farm bill, which are most significantly driven by the income related
factors.
What specific demographic characteristics drive policy preferences?
In our model, we seek to draw out support and opposition for the farm bill. We maintain the design of
this model in the broader context of the interest groups (farm versus consumer) that would support
individuals. The model of preferences for the Farm Bill is thought of as a feedback loop of redistribution;
interest groups represent individuals, inform elected officials, and bring back to districts redistributive
benefits. However, preferences are also driven by other factors such as experience, status, and
demographic characteristics.
Our model for public preferences is informed by economic models of where preferences originate.
Richard and Meltzer Model (1981) argue that, within the median-voter model, as we observe a widening
gap between the average and median income leading to an increase in redistributive policy
arrangements. In response to this model, Alesina and Giuliano (2009) illustrate that preferences for
redistribution are based on future income mobility. Thus, we build an argument that the Farm Bill is not
really a bill of interest groups, but rather a bill of poverty alleviation (both current and potentially in the
future) and social insurance. Effectively, redistribution is not a function of benefits but rather a function
of income mobility (past and future). Thus, the consumer lobby (those fighting for food stamps) could
have a greater competitive advantage in congress – an argument which will be tested in a future paper.
These findings play into our common sense understanding of the farm bill. Indeed, no congressional
district has a majority who is benefiting from farm subsidies; however, nearly all districts benefit from
the SNAP program (SNAP community characteristics, 2015). The policy implication from this analysis of
the farm bill changes the current conversation about this piece of legislation. The reality is that the farm
bill is indeed a social insurance policy, driven by the preferences of individuals but primarily based on
their experiences of income insecurity and their beliefs about what sort of social insurance policy
America needs to have.
5
III. Data and Methods
We analyzed data from the 2014 Cooperative Congressional Election Survey (CCES) in conjunction with
data collected from GovTrack, the United States Department of Agriculture (USDA) and the
Environmental Working Group's farm subsidy database. CCES provided two important sources of
information, one being the Common Content Survey Data and the other a supplemental survey
specifically asking questions about agricultural policy. GovTrack was the source for all data related to
congressional vote records (113th Congress, 2013–2015; signed into law 2014) and the two latter
sources provided data about the 2012 distribution of Farm Bill funding to congressional districts. The
CCES public opinion survey consisted of a sample of 56,200 cases and contained approximately 120
questions. Interviews were administered in two waves, before and after the 2014 election. In using the
individual panel data to test our theories about the Farm Bill, we further concentrated the data into the
1,524 participants who were asked about this particular policy issue. Respondents of the survey were
asked about their support for four forms of the Farm Bill.
Table 1. Support for four proposed versions of the Farm Bill
Version 1
Version 2
Version 3
Renew Farm Supports / Renew SNAP (food
Renew Farm Supports
Renew SNAP (food
stamps) /Eliminate
/Eliminate SNAP (food
stamps)
Farm Supports
stamps)
Version 4
Eliminate Farm
Supports/ Eliminate
SNAP (food stamps)
Yes
56%
38%
26%
25%
No
42%
57%
69%
69%
Source: CCES 2014, Harvard University Module A, N=1500
This paper focuses on the first and fourth version of the bill, equal funding for both programs and no
funding for either program. Additionally, we also ask respondents about the actual 2014 Farm Bill deal,
stating that this deal “Ends price supports for corn, wheat, sugar and other agricultural products.
Creates a federally subsidized crop insurance program. Reauthorizes the food stamp program, but cuts
10% of the program's funding” (Ansolabehere, 2014).
For the analysis of data, we used OLS regression methods to analyze three basic models for each version
of the Farm Bill. Data is weighted in the models and clustered by state. The first model is based in
benefits received by congressional districts, in particular, the amount of farm subsidies received in 2012
and the amount of SNAP funding received per district. For the second model, we add variables that
capture ideology and party affiliation. For the third model, we add demographic variables including
income, age, gender, education, and race. Each model was regressed on the first version of the Farm Bill
(equal funding for both programs) and the fourth version of the bill (zero funding for both programs).
Finally, we also include the regression results for the actual 2014 farm bill legislative deal. The following
are descriptive statistics of the variables of interest in this dataset.
Table 2 presents the descriptive statistics of the key independent variables in the analysis. The
variables that measure beneficiaries of the farm bill are amounts of money (in tens of millions of dollars)
6
received for commodity subsidies in the district, Farm Subsidy Dollars, and the number of households (in
ten thousands) receiving SNAP payments, SNAP Households. The mean value of Farm Subsidy Dollars of
1.71 means that the mean amount of subsidy per CD was 17.1 million dollars, and 15 percent of districts
received zero dollars of subsidy. The mean number of SNAP Households is 36,000 (a mean value of
3.59), and every CD had some households receiving Food Stamps. In addition, 13 percent of
respondents are poor, meaning below the level eligible for food stamps.
Table 2. Descriptive Statistics
Variables
Mean
Farm Subsidy Dollars
1.71
(in ten millions)
No Farm Subsidy Dollars
0.15
SNAP Households
3.59
(in ten thousands)
Democrat
0.44
Republican
0.35
Ideology (1=Lib, 5=Cons)
3.33
Missing Ideology
0.10
Poor
0.13
Family Income
15.12
Income Missing
0.11
Education
3.63
White
0.73
Black
0.12
Hispanic
0.07
Gender
1.53
Age (by ten years)
5.02
N=1,524
Std. Dev.
4.24
Min
Max
-0.02
31.29
0.36
1.54
0.00
0.53
1.00
11.97
0.50
0.48
1.37
0.30
0.34
27.18
0.32
1.49
0.44
0.33
0.26
0.50
1.65
0.00
0.00
1.00
0.00
0.00
1.00
0.00
1.00
0.00
0.00
0.00
1.00
1.80
1.00
1.00
6.00
1.00
1.00
97.00
1.00
6.00
1.00
1.00
1.00
2.00
9.20
7
IV. Findings
To gauge preferences regarding the Food Bill, we examine the structure of public attitudes on two
different proposed farm bills: (1) a proposed package deal, which would renew both programs, and (2)
a proposed repeal of both programs. The first asks whether support respondents a logroll; the latter
asks whether respondents want to eliminate the logroll. Keep in mind a majority of people are net
payees in support of Food Stamps and Farm Subsidies, yet, as we showed in Table 1, a majority of 56
percent of respondents support the logroll, and an even larger majority, 69 percent of respondents,
oppose the elimination of both programs.
For each proposal we proceed in three steps. First, we address the traditional characterization of public
preferences on the farm bill as rooted in the immediate benefits received by voters from the program.
For each policy proposal we gauge the extent to which support for the proposal is driven by personal
interest – that is by the level of expenditures in each Congressional District or eligibility for food stamps.
Second, we introduce partisan and ideological considerations. Finally, we examine the importance of
demographic characteristics and beliefs about who benefits from the program. Following Alesina and
Giuliano (2009) we capture the other regarding aspects using demographics as well as measures of who
respondents think benefits from the proposal.
Renew Both Programs
Table 3 presents OLS regressions predicting support for the package deal combining food stamps and
commodity price supports for each of the three analyses. The first model examines how much selfinterest alone explains support for the farm bill; the second and third models add in the other factors.
From the first model, we see little support for the view that there is a farm bill logroll sustained by a
coalition of beneficiaries. The amount of money received by a district in farm subsidies is uncorrelated
with support for a proposal to renew the both the food stamps and agricultural commodity programs.
The number of SNAP beneficiaries is positively associated with support for the bill, but that effect is
weak. The .04 coefficient implies that 10,000 additional SNAP recipients in a district corresponds with 4
percent higher level of support for renewing the existing deal. A one-standard deviation difference in
the number of SNAP recipients corresponds to only 6 percent higher level of public support for the
program. And, these variables explain only 5 percent of the total variation in support for the proposed
renewal of the program. In short, this is not a compelling story, and to the extent that the logroll
reflects private benefits within districts, that support is only realized through the SNAP program. Higher
expenditures on the agricultural program bring no additional support for the logroll in this model.
Party and ideology, by comparison, have substantial power in explaining support for the proposed deal.
And, the main story in Model 2 is the isolation of Republicans. Democrats and Independents express
higher support – by 25 percentage points – than Republicans. Very Liberal respondents are more likely
to support the proposed deal than Very Conservative respondents, by 25 percentage points.
Model 3 adds demographic controls, similar to the Alesina and Giuliano (2009) cross-national analysis of
support for welfare programs. Demographic factors carry substantial weight in this model. Rather
8
than discuss them in isolation, we draw attention to their implications in terms of the three distinct
accounts of the nature of political preferences for redistribution.
First, the full model presented in Model 3 provides somewhat more evidence of self-interest in
evaluations of the program. In particular, we include variables indicating whether the person is Poor
and measuring level of Income. Poor has a significant and positive coefficient of .045, meaning the
individuals whose income is low enough to qualify for the program were 4.5 percentage points more
likely to support the program than those who did not. Income has a significant negative effect,
showing that people who pay more into the program express less support for the package deal of price
supports and food stamps. This is entirely consistent with the self-interest account.
However, the estimated effects of Farm Subsidies and SNAP Households in the CDs are inconsistent with
the self-interest story. Controlling for partisan, ideological, and demographic characteristics, those who
live in CDs that receive higher amounts of commodity subsidies are less likely to support the logroll than
those who live in CDs that receive lower amounts of commodity subsidies. This finding is quite
important because the measure of Farm Subsidies is the most commonly used measure of electoral
benefits and electoral support for the program in studies of roll call voting behavior on the Agricultural
Acts (references to be added). Further, those who live in CDs that have higher numbers of SNAP
Households are not more likely to support the program, controlling for income, partisanship and other
factors. In other words, the amount of money received by the districts from this program, and the
possible spill over effects of that money, did not correlate with higher levels of support for the proposed
logroll. Only the respondents’ immediate self interests – their incomes – matter in this model, and that
only sharpens the puzzle, because most people are payees into the program rather than beneficiaries of
it.
The factors that did have substantial effects on support include party, ideology, education, race, and
gender. As in Model 2, Democrats and Independents are much more supportive of this logroll than
Republicans are, and liberals are more supportive than conservatives. The education variable offers
interesting insight into public preferences for redistribution. We find that as education increases, we
observe opposition to this funding both food stamps and commodity price supports. We also find that
race and gender matter in supporting redistribution. In particular, for both the white and black variables,
we expect support for this version of the bill. The Hispanic variable is not significant in this model. From
the gender variable, we observe that women are more likely to support this version of the bill than men.
This echoes the findings that women are more supportive of redistributive policy than men (Alesina,
Guiliano, 2009).
Table 3. OLS Regression Results for Equal Funding for Farms and Food
Variables
Model 1
Model 2
Adj. R2= 0.05
Adj. R2= 0.17
Farm Subsidy Dollars
-0.01
-0.01
(in ten millions)
(0.00)
(0.00)
No Farm Subsidy Dollars
0.08
0.06
(0.04)
(0.04)
SNAP Households
0.04***
0.023**
(in ten thousands)
(0.01)
(0.01)
Democrat
0.06
(0.04)
Model 3
Adj. R2=0.25
-0.01**
(0.00)
0.11***
(0.04)
0.02
(0.01)
0.04
(0.03)
9
Republican
-0.25***
(0.04)
-0.05***
(0.02)
0.198***
(0.07)
Ideology (1=Lib, 5=Cons)
Missing Ideology
Poor
Family Income
Income Missing
Education
White
Black
Hispanic
Gender
Age (by ten years)
Intercept
0.45
0.72
-0.20***
(0.04)
-0.06***
(0.01)
0.16**
(0.07)
0.045
(0.04)
-0.02***
(0.00)
1.99***
(0.46)
-0.035***
(0.01)
0.102**
(0.05)
0.27***
(0.06)
0.03
(0.06)
0.08***
(0.02)
-0.01
(0.01)
0.88
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Eliminate Both Programs
Our initial analysis is of who supports the logroll. The flipside of that record is who supports elimination
of the logroll. In a separate question we asked whether respondents supported a proposal to end both
the Food Stamps Program and the Commodity Price Support Program. That proposal was introduced
into the House in 2013 (and in earlier Congresses). In many ways we expect this to be mirror the
analysis of support for the logroll, but it is possible that there are some groups who want to uncouple
the programs or are strongly opposed to one piece of the legislation but not the other.
In the first regression model for eliminating funding for both programs, we observe that both the
amount of dollars received through farm subsidies and districts with no funding through farm subsidies
are statistically significant. The variable farm subsidy dollars offers an interesting insight into policy
preferences. In this case, districts receive higher amounts in farm subsidy funding are more likely to
support the elimination of both programs. The reverse is true for districts which receive no funding
through farm subsidies. We find that they are more likely to oppose the elimination of both programs.
Indeed, these findings hold true for all three models. The number of SNAP Households is unrelated to
support for the elimination of both programs. This finding runs counter to the self-interest account of
the Farm Bill and the Farm vote.
Model 2, in which we incorporate ideology and party affiliation, supports our common sense
understanding of preferences based on party and ideology. Democrats and Independents are more
likely to oppose the elimination of both programs than Republicans. Furthermore, as ideology moves
across the spectrum from liberal to conservative, we observe that individuals are more likely to support
eliminating both food and farm subsidies through the Farm Bill.
In the full model, our findings from the previous two models are upheld. In terms of demographic
characteristics, a similar picture to that shown in Table 3 emerges, but with some slight differences. We
observe that Poor, Income, Hispanic, and Gender are statistically significant, but Education is not.
Consistent with our findings in Table 3, the variable for poor indicates that individuals who identify as
poor are more likely to oppose eliminating both subsidy programs. Also, the higher an individual’s
income the more likely they are to support eliminating the package all together. Consistent with Alesina
and Giuliano (2009), men are more likely to support elimination of both programs, but, curiously, so are
Hispanics.
Table 4. OLS Regression Results for Eliminate Funding for Farms and Food
Variables
Model 1
Model 2
Adj. R2= 0.04
Adj. R2= 0.16
Farm Subsidy Dollars
0.01***
0.01 ***
(in ten millions)
(0.00)
(0.00)
No Farm Subsidy Dollars
-0.09**
-0.06
(0.04)
(0.04)
Model 3
Adj. R2=0.19
0.01***
(0.00)
-0.1***
(0.03)
11
SNAP Households
(in ten thousands)
Democrat
0.00
(0.01)
0.02
(0.01)
-0.1***
(0.03)
0.13 ***
(0.04)
0.07***
(0.01)
-0.34***
(0.06)
0.26
-0.01
Republican
Ideology (1=Lib, 5=Cons)
Missing Ideology
Poor
Family Income
Income Missing
Education
White
Black
Hispanic
Gender
Age (by ten years)
Intercept
0.02**
(0.01)
-0.07**
(0.03)
0.12***
(0.04)
0.07***
(0.01)
-0.31***
(0.06)
-0.08**
(0.04)
0.01*
(0.00)
-0.66
(0.45)
-0.00
(0.01)
0.01
(0.05)
-0.06
(0.06)
0.13**
(0.06)
-0.1***
(0.02)
0.00
(0.01)
0.06
2014 Farm Bill Deal
The version of the bill, passed in 2014, was a by-product of negotiation and compromise between both
parties driven by the amount of funding cuts impact the food program, SNAP. Participants were asked
about support of the policy with the following wording: “ends price supports for corn, wheat, sugar and
other agricultural products. Creates a federally subsidized crop insurance program. Reauthorizes the
food stamp program, but cuts 10% of the program's funding” (Ansolabehere, 2014).
From the following models, we observe that in each model the amount of SNAP households in a
congressional district is a driving predictor of preferences for this policy version. Holding all other
variables constant, an increase in the number of SNAP households in a district, decreases support for
2014 bill. This is understandable as this version of the bill decreased funding for the SNAP program. In
the second model, we find that party affiliation is a driving factor in preferences. For both of the party
12
variables, we observe opposition to the 2014 bill version. We can speculate that opposition for
Democrats is due to funding decreases for SNAP. Whereas for Republicans, opposition is could be driven
by insufficient funding decreases. In the full model, we observe that the variable for poor is again a
driving factor in preferences for this bill. Holding all variables constant, we find support for this version
of the bill for individuals who identify as poor. This could be a “better than nothing” approach to this
policy outcome. As SNAP funding was on the line for cuts, those who benefit from the program, would
be more likely to support a deal which did not fully eliminate all support for food subsidies.
Table 5. OLS Regression Results for 2014 Farm Bill Deal
Variables
Model 1
Adj. R2= 0.02
Farm Subsidy Dollars
0.002
(in ten millions)
(0.01)
No Farm Subsidy Dollars
0.003
(0.06)
SNAP Households
-0.037***
(in ten thousands)
(0.01)
Democrat
Republican
Ideology (1=Lib, 5=Cons)
Missing Ideology
Model 2
Adj. R2= 0.03
0.002
(0.01)
0.01
(0.06)
-0.04***
(0.01)
-0.1*
(0.06)
-0.17***
(0.06)
-0.003
(0.02)
0.1
(0.1)
Poor
Family Income
Income Missing
Education
White
Black
Hispanic
Gender
Age (by ten years)
Intercept
1.57
1.68
Model 3
Adj. R2=0.04
-0.00
(0.01)
0.03
(0.06)
-0.05***
(0.01)
-0.09
(0.05)
-0.12**
(0.06)
-0.01
(0.02)
0.06
(0.1)
0.21***
(0.06)
-0.01
(0.01)
0.55
(0.7)
-0.00
(0.01)
0.05
(0.07)
0.06
(0.09)
0.14
(0.1)
0.01
(0.04)
-0.03***
1.8
13
Summary
These models offer insight into what factors play the most significant roles in determining the
preferences of individuals. Unsurprisingly, we find that party affiliation is significantly impacting the
support of individuals for redistributive policies. However, we find it interesting that opposition based
on the Republican variable is not solely confined to food supports but also extends to farm subsidies.
Arguably, this could be the double-edge of logrolling policies such as food and farm supports.
In terms of benefits received in a congressional district, we do not find that support is derived from
benefits by the farm support side of the bill. Rather, we see that support is related to the number of
SNAP households in a district. This is understandable as SNAP is a more broadly based program with
more recipients than farming supports. However, this also questions the narrative that the Farm Bill is
indeed a “farm” bill aimed at economic stability in agriculture. In reality, the Farm Bill is a social
insurance bill aimed at food issues derived from poverty and economic instability of households.
Finally, we find support for the argument that preferences for redistribution are based on incomerelated factors (Alesina, Giuliano, 2009). Those who identify as poor are more likely to support the Farm
Bill, both equal funding for both programs and the actual 2014 deal. We also find that as income
increases, support for the Farm Bill decreases. This indicates that while income-related preferences for
redistribution are significant, we speculate that the marginal effect of this relationship may decline past
a certain income level.
From our models, we find that public preferences appear to be a function of endogenous characteristics
rather than exogenous benefits. Income is a driving variable in these models for preference, with an
interesting division between increasing income and those who identify as poor. We argue that the drive
for redistributive policy, like the Farm Bill, is not solely a function of interest group’s gaining access
through information (Hansen, 1991). This bill is also a social insurance policy designed to respond to
income changes and arguably, driven by the economic insecurities felt by the low to middle income.
14
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