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FEATURES The Contemporary Presidency Presidents Profiting from Disasters: Evidence of Presidential Distributive Politics NICHOLAS R. STRAMP University of Washington In what ways do presidents engage in distributive politics? I study the effects of presi- dential electoral politics on the federal government’s financial response to disasters. Specifically I ask whether swing states or safe states are more likely to receive additional disaster aid through presidentially ordered increases in the federal reimbursement rate for specific disasters. I examine four potential political factors affecting this distribution: swing states versus safe states, a president’s base states versus the opposing party’s base states, the presence of co-partisan presidents and governors, and the proximity of the next presidential election. I find that the effects vary by administration, with Bill Clinton not appearing to make partisan decisions in this way, while his successors include these factors when making the decisions. These findings demonstrate the presence of partisan political calculations in the distribution of disaster aid and also highlight differences in the ways power is handled in different presidential administrations. Large areas of northern Oklahoma were hit by severe storms and flooding in the first two weeks of June 2008. Property damage was estimated to total more than $759 million, an astounding $198 for every resident of Oklahoma. 1 That same summer Missouri also experienced severe storms and flooding. Property damage totaled $17 million, or about $3 per capita. Crop damage totaled an additional $58 million, bringing the total damage to roughly $14 per capita. Counties in both states were declared to be 1. Per capita damage is recognized in this field as the standard for assessing the economic impact of a disaster on a state. Nicholas R. Stramp is a graduate fellow at the Center for American Politics and Public Policy at the University of Washington. His research focuses on executive decision making as well as the policy-making process at both the federal and state levels. AUTHOR’S NOTE: The development of this article has benefited from comments and other assistance provided by John Wilkerson, Peter May, Chris Adolph, Matt Barreto, Becca Thorpe, Hannah Walker, Emily Gade, Jeremy Dashiell, and Kassra Oskooii. Presidential Studies Quarterly 43, no. 4 (December) 839 © 2013 Center for the Study of the Presidency

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Page 1: The Contemporary Presidency               : Presidents Profiting from Disasters: Evidence of Presidential Distributive Politics

FEATURES

The Contemporary Presidency

Presidents Profiting from Disasters: Evidence ofPresidential Distributive Politics

NICHOLAS R. STRAMPUniversity of Washington

In what ways do presidents engage in distributive politics? I study the effects of presi-dential electoral politics on the federal government’s financial response to disasters. SpecificallyI ask whether swing states or safe states are more likely to receive additional disaster aid throughpresidentially ordered increases in the federal reimbursement rate for specific disasters. I examinefour potential political factors affecting this distribution: swing states versus safe states, apresident’s base states versus the opposing party’s base states, the presence of co-partisan presidentsand governors, and the proximity of the next presidential election. I find that the effects vary byadministration, with Bill Clinton not appearing to make partisan decisions in this way, whilehis successors include these factors when making the decisions. These findings demonstrate thepresence of partisan political calculations in the distribution of disaster aid and also highlightdifferences in the ways power is handled in different presidential administrations.

Large areas of northern Oklahoma were hit by severe storms and flooding in thefirst two weeks of June 2008. Property damage was estimated to total more than $759million, an astounding $198 for every resident of Oklahoma.1 That same summerMissouri also experienced severe storms and flooding. Property damage totaled $17million, or about $3 per capita. Crop damage totaled an additional $58 million, bringingthe total damage to roughly $14 per capita. Counties in both states were declared to be

1. Per capita damage is recognized in this field as the standard for assessing the economic impact ofa disaster on a state.

Nicholas R. Stramp is a graduate fellow at the Center for American Politics and Public Policy at the Universityof Washington. His research focuses on executive decision making as well as the policy-making process at both the federaland state levels.

AUTHOR’S NOTE: The development of this article has benefited from comments and other assistance provided byJohn Wilkerson, Peter May, Chris Adolph, Matt Barreto, Becca Thorpe, Hannah Walker, Emily Gade, Jeremy Dashiell,and Kassra Oskooii.

Presidential Studies Quarterly 43, no. 4 (December) 839© 2013 Center for the Study of the Presidency

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“federal disaster areas” by President George W. Bush, making affected jurisdictionseligible for federal reimbursement of 75% for eligible recovery and rebuilding expenses.President Bush increased the federal cost share for Missouri to 90% of eligible costs a fewweeks after the flooding while Oklahoma did not receive this extra assistance.

President Bush’s decision to increase the federal reimbursement percentage sent anextra $8 million to Missouri. Why did Missouri receive more favorable treatment thanOklahoma? The Oklahoma storms had a much greater financial impact on the state,and they definitely could have used the additional assistance they would have receivedin reimbursement at the 90% level. Partisan politics provides a plausible explanation.Missouri was widely expected to be a pivotal swing state in that fall’s presidentialelection, and this proved true with only 3,903 votes separating John McCain and BarackObama. There was no danger of Republicans losing Oklahoma, which McCain ended upcarrying with a 31% margin over Obama.

I study the effects of presidential electoral politics on the federal government’sfinancial response to disasters. Specifically I ask whether states supportive of the presidentor “swing states” are more likely to receive additional disaster aid through presidentiallyordered increases in the federal reimbursement rate after specific disasters. To answer thisquestion I construct an original data set including information about presidential deci-sions regarding disaster aid for 945 disasters spanning 19 years and three presidentialadministrations (Clinton, George W. Bush, and Obama). I find that presidents are morelikely to send additional aid to swing states and most significantly that the presidents inthis study used their power in different ways, likely due in part to contrasting electoralstrategies. These findings demonstrate the presence of partisan political calculations inthe distribution of disaster aid, a power delegated to the president by Congress preciselyto avoid such occurrences.

This article begins with a theoretical overview of distributive politics and theexecutive branch. Two theories are borrowed from the congressional literature as ways inwhich policy makers may wield policy power in a partisan way. Swing voter theoryexpects policy makers to focus on swing states while coalition maintenance expects policymakers to focus on rewarding their base states as a means of ensuring high turnout.Additionally, the impact of co-partisan presidents and governors, as well as proximity ofthe next presidential election, are tested as additional partisan factors with the potentialto influence the distribution of disaster aid.

Theorizing about Presidents and Distributive Politics

Weingast, Shepsle, and Johnsen (1981) define distributive politics as policy areaswith “project-by-project orientation, the geographic concentration of benefits, and thediffusion of costs” (681). In this article distributive politics implies disproportionatebenefits relative to the burdens to geographic constituencies. This fits the nature ofdisaster relief, as disasters are inherently local or regional events, yet the federal govern-ment routinely provides relief and is expected to do so.

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Distributive Politics and Congress

The vast majority of the early work related to distributive politics focuses on theability of senators and representatives in Congress to direct funds to specific constituen-cies. Two basic theories developed. Swing voter theory indicates that parties (or legisla-tors) will target marginal constituencies, defined as the states or districts most likely tochange hands in an upcoming election (Bickers and Stein 1996; Lindbeck and Weibull1987; Stein and Bickers 2009). The other often-tested theory posits that risk-averseincumbents will direct attention toward their strongest supporters and will be referred toas coalition maintenance (Cox and McCubbins 1986).2

Distributive Politics and the Executive Branch

Evidence of geographic distributive politics in the executive branch was first putforth by Wright (1974) who found that during the New Deal, Works Progress Admin-istration jobs went disproportionately to electorally competitive states. More recentwork has continued to investigate the prevalence of distributive politics within executiveagencies. Mebane and Wawro (2002) found a modest increase in federal expenditures forbasic programs toward supporters after midterm elections (coalition maintenance). Berry,Burden, and Howell (2010) found that congressional districts transitioning from beingrepresented by a member of the opposition to a member of the president’s party enjoyincreased federal expenditures and Gersen and Berry (2010) find this affect to be largerfor agencies with a higher proportion of political appointees (maintenance of a newcoalition).

The above research indicates that executive agencies appear to use distributivepolitics for partisan advantage but does not put forth evidence that these decisions arebeing made in the White House. Gersen and Berry (2010) as well as Gordon (2011)indicate that political appointees likely play a role, but these appointees may be acting onexplicit or implicit direction of the president or simply demonstrating their own partisanbiases. This article is focused on presidential influence in this process. The next sectionidentifies specific methods by which the president may exert this influence.

Direct Presidential Distributive Powers

Although Congress holds the “power of the purse,” the president and executivebranch wield considerable power over distributive allocations (Fisher 1975). As the leaderof the executive branch, the president has the ability to influence agency decision makingthrough executive orders (Mayer and Price 2002) and involvement in the rule-makingprocess (DeMuth and Ginsburg 1986; Krent 2005). For example, Presidents John F.Kennedy, Lyndon Johnson, and Richard Nixon all used this power to require presidentialapproval of all U.S. Agency for International Development distributions over $5 million(McKeown 2005).

2. Cox and McCubbins (1986) do not provide a formal name for this theory. Coalition maintenancewill be used throughout this article for ease of reference.

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More recently Congress has taken to delegating power to the president and execu-tive agencies as the demands on its own time increase. Throughout the 1990s and 2000s,this has been most apparent in the areas of Medicaid (Thompson and Burke 2007) andenvironmental policy (Bowers 2010). The issuance of Medicaid waivers is the responsi-bility of the secretary of Health and Human Services, but the authority to grant waiversof environmental regulations varies from the Environmental Protection Agency admin-istrator to the president himself.3 The issuance of waivers and other administrativedecisions delegated to the executive branch by Congress are the areas ripest for presiden-tial involvement in distributive politics. This power is likely to be relatively unchecked,as there is a reason Congress delegated this power in the first place. These decisions maybe political risky (Arnold 1992), too technical for Congress to handle given its limitedtime (Bowers 2010), or require a speedy response to an unexpected situation (Wamsleyand Schroeder 1996).

Presidential Power and Disaster Response

The disaster relief system that has developed over the past 60 years is relativelyunique and reflects the politically sensitive, technical, and time-critical elements ofdisaster response. Since 1950, presidents have possessed the power to issue nationaldisaster declarations that then allow states to apply for federal reimbursement for apercentage of the losses caused by the disaster. The funds for this aid are appropriatedby Congress into the Presidential Disaster Relief Fund and are not earmarked for anyspecific disaster (Sylves 2008). Congress makes “deposits” into this account and theFederal Emergency Management Agency (FEMA) distributes the funds as reimburse-ment for qualifying expenses in states and counties designated as federal disaster areas.

The Disaster Relief Act of 1950 (P.L. 81-875) limited the use of federal funds forpublic assistance to the repair of public structures (no rebuilding and no private struc-tures). Over the course of the last 60 years, the scope of this aid has gradually increasedto cover almost any disaster-related damages (Sylves 2008). Although the scope hasincreased considerably the process is unchanged. After a disaster strikes, state and localgovernments are responsible for the immediate response. Once the extent of the damageis known the governor, with the assistance of local FEMA officials, requests a nationaldisaster designation from the president.4 Further information is compiled by FEMA atthe national level, and then a recommendation is made to the president if the disasterdeclaration should be approved or denied. If the declaration is approved, the state is theneligible for federal reimbursement of 75% of eligible expenses.5

3. To avoid questions of who controls the bureaucracy (Hammond and Knott 1996), this articlefocuses on decisions delegated to the president.

4. In rare circumstances, if a major disaster is imminent, the president will issue a temporary“emergency declaration” allowing the immediate allocation of federal resources. Many of these emergencydeclarations are later revised to be full disaster declarations after the fact.

5. The Mt. St. Helens disaster in 1980 was the first instance of the 75%/25% arrangement(McCarthy 2010). Before this, the cost sharing arrangement varied widely from disaster to disaster. Hearingsregarding the Mt. St. Helens disaster and funding for recovery operations provide a prime example of themessiness of appropriating federal disaster relief funds on a disaster-by-disaster basis (May 1985).

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Others have examined disaster response for political motivations and conse-quences with mixed results. This research into the politicization of disasters has exclu-sively focused on the issuance of presidential disaster declarations. Garrett and Sobel(2003) find that states that are more electorally important are slightly more likely toreceive more declarations, and that more declarations are issued in election years. Incontrast, Sylves and Búzás (2007) examined an extended period of time and did notfind any state partisanship variables to be significant. The only significant predictorfound was election year. Reeves (2011) continued this line of research, finding thatstates considered highly competitive were likely to receive nearly twice as manydeclarations as less competitive states. Healy and Malhotra (2009) also examine theelectoral impact and find more broadly that incumbents are generously rewarded fordisaster relief funding.

Not only does the president have the power to declare federal disaster areas,but also the power to increase the share of federal public assistance. The Stafford Act(42 U.S.C. §§ 5126-5206), originally passed in 1988, establishes 75% as the standardfederal reimbursement rate for qualifying expenses in a federal declared disaster area.6

The act also allows for discretionary raising of the federal cost share by the president,which occurs for a handful of disasters each year, usually weeks or months after adisaster (Moss, Schellhamer, and Berman 2009). This makes the president’s decision toincrease the federal cost share a relatively “quiet” one, as the disaster has usually fadedfrom national attention, yet this benefit is tangible and easily recognized by the receiv-ing communities.

Previous research has focused on the very public (and sometimes controversial)issuance of major disaster declarations. It would be much riskier for a president topoliticize the issuance of declarations compared to cost share increases, as there is a highdanger of being publicly accused of “playing favorites” when communities are in direneed after disasters. Hurricane Katrina is a prime example of the political danger ofmismanagement in the immediate aftermath of a disaster (Birch and Wachter 2006).Additionally, this previous research around disaster declarations is essentially focused onvery small disasters at the margins for which it is debatable whether they are deservingof a federal disaster declaration or not. Although these are significant events for thecommunities involved, they are relatively insignificant in the bigger picture. In contrast,the issuance of federal cost share increases affects the largest disasters and, as wasmentioned in the introduction, this decision can have a huge financial impact on a state(recall the examples of Oklahoma and Missouri at the outset). FEMA has established stateper capita disaster cost thresholds above which it will recommend to the president afederal cost share increase, but this only accounts for a small portion of all disasters thatreceive a federal cost share increase. Why does the president approve some federal costshare increases and not others?

6. The Stafford Act codified the 75-25 cost share as a national standard but this formula was firstused following the Mount Saint Helens eruption in 1980 (May 1985).

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Presidential Motivations

Both James Madison and Alexander Hamilton use the Federalist Papers to extol thevirtue of a unitary executive as key to accountability and counteracting mischief of factionpresent in Congress. In other words the president was designed to be an “anti-Congress”when it came to distributive politics. Significant modern scholarship is devoted to thisissue as well. Mayhew (1974) indicates that because presidents can be held individuallyaccountable for broad policy affects, they are less likely to engage in “the traffic ofparticularized benefits” (169). This line of reasoning usually compares the president toCongress and finds that playing the game of distributive politics is much more attractiveto members of Congress who face reelection frequently and have a well-efined andgeographically narrow constituency. If the president was elected via popular vote, thiswould be a fairly solid argument, as most interests throughout the country would balanceout.

The United States does not elect the president via popular vote though; instead,the electoral college renders some votes much more attractive and easily obtainable thanothers. This occurs in two ways. First, there are simply fewer residents per electoral votein some small states compared to large ones, making these votes “cheaper.” On the otherhand visits and media coverage in small states will be noticed by fewer residents and thusfewer electoral votes, so this could go the other direction. Second, long-standing partisanstrongholds have placed many states at the margins of presidential elections while otherstates receive considerable attention. McCarty (2000) puts forth a solid theory thatpresidents are electoral maximizers just like members of Congress and strategically usepolicy tools, in this case the veto power, for partisan gain by favoring certain districts.Another line of research considers presidents to be on a “permanent campaign”(Blumenthal 1980; Ornstein and Mann 2000). These scholars indicate that presidents arealways thinking about electoral incentives and consequences when making decisions.Although there has been some discussion of a difference in presidential behavior betweenfirst and second terms, this article assumes the president to be a loyal party chief who actsto ensure his party retains the office in the next election.

This section has established that partisan, electoral factors potentially play intopresidential policy making. Is there the possibility that such actions could actuallyinfluence an election? Chen (2012) found that conservative Florida residents receivinghurricane assistance in the weeks before the 2004 election were more likely to turn outto vote and to cast their vote for Bush. At the same time, liberal residents receivingassistance were less likely to turn out to vote. On a nationwide scale, Kriner and Reeves(2012) determined that counties with increased federal grant spending in a presidentialelection year were more likely to vote for the incumbent’s party.

If increased federal spending is electorally beneficial, why don’t presidentsalways increase the federal cost share? There are a couple of potential answers. First, thecongressional appropriations into the Disaster Relief Fund are designed to be sufficient tocover costs at the 75% level, and the wording of the Stafford Act clearly indicates thatthis should be the “normal” reimbursement rate. Frequent increases in the federal costshare would require the president to seek additional funding from Congress who could

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either withhold funds or curtail the power. Alternatively, this could be an issue related topolitical philosophies on the size and role of the government and intergovernmentalrelations. Those favoring smaller government and more power at the state level areunlikely to increase the federal share of disaster relief on a regular basis. This couldlead state and local governments, the primary emergency planners and responders, to relytoo heavily upon federal support. On the other hand, a president who sees the benefits(political and otherwise) of a competent government response may be more likely toincrease the federal reimbursement more frequently.

Hypotheses

The theoretical method and motivation for presidents to engage in distributivepolitics has been established, but do they exercise this power politically? This questionis answered through an investigation of presidential decisions to increase the federalcost share of disaster relief funding. Presidents continually have the opportunity toexercise this power as disasters occur and declarations are issued. This is a useful case tostudy because presidents are directly involved and issues decisions (and nondecisions)on a regular basis. By focusing on an issue with direct presidential involvement, anypatterns in the data may be attributed to the president and his advisors rather thanagency heads.

When a disaster occurs, the president is repeatedly involved in the response process.First, the president may declare a “state of emergency” in the days or hours before thedisaster strikes, which allows for immediate federal assistance in evacuation and imme-diate response. At this point a partisan bias is unlikely, as mismanagement of a disasteris perceived poorly nationwide as was evident in the aftermath of Hurricane Katrina.The second step is the issuance of a federal disaster declaration. As others have shown(Garrett and Sobel 2003; Reeves 2011; Sylves and Búzás 2007) there is the potential forpoliticization at this point in the process, but only for very small disasters. Although theneutrality of FEMA officials is debatable during certain periods, this presidential decisionis made on the recommendation of the bureaucracy in regional offices. Lastly, thesedecisions are still very public and often covered by the media. Given the sensitive natureof disasters, it is likely not a wise move for a president to make overt political decisionsat this point.

Once the disaster has faded from public memory at the national level and most ofthe cleanup and rebuilding is complete, the president has one additional opportunityto assist the affected communities. By authorizing a federal cost share increase in theweeks or months after a disaster, the president is providing a very tangible benefit to theaffected state but one that is not likely to attract the attention of a wider audience. Thisis a perfect opportunity for a president to use the power of his office for his partisangain.

This final opportunity for presidential discretion, the issuance of a federal cost shareincrease, is tested against both potential manifestations of distributive politics describedat the outset for the timespan as a whole as well as each president individually. The first

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hypothesis tests swing voter theory, which asserts that elected officials target distributivebenefits to areas with high concentrations of moderate voters. On the presidential level,we would expect this to be the classic swing states that are critical in each election.Issuing federal cost share increases in these states provides additional positive mediaexposure for the president and additional federal spending, both of which are shown tolead to an increase in popularity (Dalton, Beck, and Huckfeldt 1998, Kriner and Reeves2012). It is expected that these swing states will receive more cost share increases than“safe states” at either end of the political spectrum.

Hypothesis 1: Presidents issue federal cost share increases more often for disasters in swingstates.

The second hypothesis addresses the other manifestation of distributive politics:coalition maintenance. This theory asserts that presidents pay special attention to theircore supporters, rewarding them for their past support and ensuring a strong turnout inthe next election. These “ partisan base states” are the states in which the president isconfident in his party’s electoral success as the presidential level. At the other end of thespectrum are “opposing base states” that are firmly aligned with the party opposing thepresident.

Hypothesis 2: Presidents issue federal cost share increases more often for disasters in theirpartisan base states.

Another potential state-level variable of interest is the party of the governor andwhether this matches the party of the president (president-governor compatibility).Disaster declarations, as well as subsequent requests for additional funding, are writtenby the governor and addressed to the president. It is expected that when these twoindividuals belong to the same party that a cost share increase is more likely to occur.

Hypothesis 3: Presidents issue federal cost share increases more often for disasters occurringin states with governors from their political party.

The final hypothesis tests for the existence of variation in the issuance of costshare increases throughout the national election cycle. This addresses the issue of thepermanent campaign (Doherty 2007) and more broadly if federal cost share increases arehandled in systematically different ways depending on proximity of the next election. Isthere a pattern to the distribution of cost share increases based on the proximity of thenext presidential election?

Hypothesis 4: Presidents issue federal cost share increases more often in the months leadingup to a presidential election.

In addition to evaluating these hypotheses for the data set as a whole, eachhypothesis will also be tested for each president individually. It is expected that eachpresidential administration used this power differently, yet this type of nuanced exami-nation of the presidential decisions is rare.

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Methodology

These hypotheses are evaluated using a unique data set consisting of all federallydeclared disasters from 1993 through 2011. The beginning of Clinton’s first term wasselected as the start date because he was the first president to issue federal cost shareincreases on a regular basis. Although George H. W. Bush possessed this power, he onlyexercised it on two occasions late in his term.7 The data set covers the full presidenciesof Clinton and George W. Bush, as well as the first three years of Obama’s presidency.8

Logistic regression is used to compute the predicted probabilities of different factorsaffecting the issuance of a federal cost share increase. Because the issuance of cost shareincreases is relatively rare (7.4% of cases in the data set), rare events logit (King and Zeng2001) is also used to verify that the coefficients are unbiased.9 Disasters declarations areissued on a state-by-state basis, therefore each case represents one disaster in a single state.The base information for each disaster comes from FEMA’s website.

Case Selection

The entire data set includes all 1,016 major disaster declarations issued during thetime period. In 2004 and three times subsequent, Congress enacted legislation to raisethe federal cost share. These acts affected a total of 14 disasters, all of which were removedfrom the data set because the key actor under study is the president and not Congress.10

An additional 57 cases were missing key property damage data, leaving 945 cases in thefinal data set.11

The Dependent Variable

The outcome of interest, the presidential decision to issue a disaster cost shareincrease, is coded dichotomously. Any disaster receiving a federal cost share increase iscoded as 1, all other disasters are coded as 0. There is little to be gained by differentiatingthe dependent variable, as about four-fifths of the federal cost share increases were to the100% level and the remainder at the 90% level.

Key Independent Variables

The swing voter theory and coalition maintenance (Hypotheses 1 and 2) bothutilize the last presidential election as a measure of a state’s electoral value to a president.

7. Logit models of George H. W. Bush’s decisions did not converge given the very small number ofpositive cases.

8. Data for 2012 is not yet available.9. Results from the rare events logit models are in the appendix (Figures 5-7 and Tables 2-3).

10. In most cases, the president had already issued at least a temporary cost share increase beforeCongress acted.

11. The missing data primarily came from severe storms and flooding. Multiple imputation revealedno bias in the results from the omitted cases. Only two of these missing cases were issued federal cost shareincreases.

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The last election, and not an average of recent elections, is chosen because the electorallandscape changes substantially over the course of even two to three presidential elec-tions. For example, Maryland and New York could both have been considered swingstates in the 1980s but became firmly Democratic in the 1990s. It is important to notethis is only one potential measure of a president’s political interest in a state, and it isimpossible to know which states are actually of interest to the president (Gordon 2011).It is difficult to predict the political strategy and targeting of a presidential campaign,but assuming both campaigns are targeting the same areas, vote margins provide asuitable proxy. To test the swing voter theory, electoral margin is used.

ElectoralMargin PresidentVotePercent OpponentVotePi t i t k, ,= −− eercenti t k, −

For state i in year t, the electoral margin is the absolute value of the president’s vote sharein the last election (k years ago) minus his opponent’s vote share. This margin is thenlog transformed.12 Lower numbers indicate closer races, and therefore this variable isexpected to be negatively correlated with federal cost share increases. The logarithmictransformation emphasizes the differences between the smaller values (closer elections),as it is expected a difference between a 1 and 3% margin is more significant than thedifference between 15 and 18% t.

An alternative swing state indicator variable is also tested. For each election, the12 states with the smallest election margins are identified. Results for this measureare included in the Appendix. The electoral margin variable is preferred because itcaptures information about every state and a likely order of how important eachstate is to the president. On the other hand, an indicator variable excludes individualinformation for each state and assumes the researcher has a good idea what criteriaa president is using (in this case equally targeting the 12 closest states in the lastelection).

Coalition maintenance is tested using the president’s victory margin in each state.This equation is similar to the first except the absolute value is not taken, and it is notlogarithmically transformed, so high positive values indicate a president’s partisan basestates while high negative values indicate opposing base states. Sylves and Búzás (2007)use a slight variation of this measure in their study.

PresidentsMargin PresidentVotePercent OpponentVotei t i t k, ,= −− PPercenti t k, −

The effect of president-governor compatibility (Hypothesis 3) is tested with a variablecoded as 2 for years when the president and governor were from the same party, 1 if thegovernor was an independent, and 0 if the governor was from the opposing party of the

12. Third-party candidates are not included in this calculation as they do not have a direct effect onthe winner of a state’s electoral votes.

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president.13 Lastly, the proximity to a presidential election is measured by the number ofdays before the next presidential election that the cost share increase is issued. Thisvariable is transformed into number of years until the election but retains the precisionat the level of days. For disasters where no increase was issued, an artificial “decision date”was created based on the median number of days after a disaster that cost share increasesare issued (68 days).14

Size of disaster is the first control variable, and is expected to be a dominantpredictor in the model. FEMA bases its recommendation on per capita damage based onthe population of the state, and this is the most common measure of the magnitude ofimpact a disaster has. FEMA does not provide information on cost estimates of disasters,but the Spatial Hazard Events and Loses Database at University of South Carolina (2012)compiles information from the National Climate Center’s Storm Data for the damagecaused by all weather-related events in the United States. This database includes over800,000 weather events and is organized by county and date. Each declaration is repre-sented by several records covering different counties and different days. These records areaggregated to produce a total amount of property damage in the given state for theduration of time covered by the declaration (usually one to three days). This method mostlikely modestly overestimates the cost of many disasters, as some counties will incurdamage that is not covered by a disaster declaration. As mentioned above, for 57 disasters(primarily floods and fires) damage amounts could not be linked and these cases areomitted from the analysis. Additionally, preliminary analysis indicates that cost shareincreases are often issued in clusters for a large disaster event that affects several states. Tocontrol for this pattern, a variable, neighbor waivers, is included that counts the numberof cost share increases states neighboring the state received for disasters occurring withinone week before or after the disaster date. Finally, two state-level controls are included:population and state poverty level. The inclusion of population ensures that there is nota large-state or small-state bias in these decisions, and poverty level will serve as a proxyfor the state’s financial health and the ability of its residents to rebuild on their own.15

Descriptive Statistics and Preliminary Overview

To begin, some descriptive statistics and basic graphs illuminate interesting trends.The first two graphs (Figures 1 and 2) indicate when Presidents Clinton and George W.Bush each issued federal cost share increases for disasters.16 The state names in redindicate disasters that received a federal cost share increase and the triangles mark thedate the federal cost share increase was granted. These graphs indicate that there was a

13. Other treatments of the 21 state-years with independent governors, including assignment to partyof the president and of the opposition did not affect results. Independent governors were present in a totalof 15 cases.

14. Models with decision dates ranging from 15 to 180 days did not affect the results.15. Although congressional influence over FEMA distributions was a significant predictor for Garrett

and Sobel (2003), when similar congressional variables were included in early models they repeatedly did notprove to be significant predictors in this president-centric process.

16. The same visualization is available for Obama in the Appendix.

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Disasters plotted by date and state of occurrence. States receiving cost share increase in bold red, date of increase designated by triangle.

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FIGURE 1. Declared Disasters and Property Damage with Federal Cost Share IncreasesHighlighted (Clinton).

November 2004

States receiving cost share increase in bold red, date of increase designated by triangle.Disasters plotted by date and state of occurrence.

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FIGURE 2. Declared Disasters and Property Damage with Federal Cost Share IncreasesHighlighted (G. W. Bush).

850 | PRESIDENTIAL STUDIES QUARTERLY / December 2013

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fairly consistent pattern of disasters throughout the timeframe of study, but the imple-mentation rate of cost share waivers varied by president. Clinton consistently issuedfederal cost share increases throughout his two terms, usually relatively soon after adisaster struck to a total of 10% of all declared disasters. His first term in office beganwith flooding in the Midwest that affected nine states, all of which were granted costshare increases. Although most disasters receiving cost share increases appear at the topof the graph, there are still many notable exceptions as well as low-damage disastersreceiving extra relief funding.

George W. Bush, on the other hand, did not issue any federal cost share increasesuntil the 2004 hurricane season and only issued cost share increases for 5% of declareddisasters.17 During his reelection campaign in the fall of 2004, President Bush issuedcost share increases for hurricanes and severe storms affecting parts of Florida, Georgia,Louisiana, North Carolina, and Mississippi. Additionally, Alabama and West Virginiareceived cost share increases in the months after the 2004 election for events from thesame time frame. More specific case analyses are included in the results section.

A simple t-test reveals a difference between these two presidencies significant atthe p < .05 level. Because of this significant difference, each president will be examinedindividually as well as looking at trends over the entire 19-year period. As noted earlier,presidents are utilizing this power in ways that are not consistent with one another.Although it may be beneficial to examine their actions in total, the most informativefindings are expected to be the factors affecting each president’s decisions.

Regression Results and Interpretation

Due to the binary nature of the dependent variable, logistic regression is used totest each hypothesis. This then allows for the simulation of multiple counterfactuals todemonstrate scenarios of interest. As shown in Table 1, the first model includes the entiredata set while subsequent models examine each president’s decisions individually. Inthe Appendix, these models are replicated with rare events logit (King and Zeng 2001).For the first model with all cases, the concordance index is .92, an increase of .10 over abase model without any political variables. Similar increases in the concordance indexoccurred for Clinton and Bush’s models, .1 and .12, respectively. The political variablesonly add .02 to the concordance index for Obama’s model, in part because of the smallnumber of observations over the three years of his term included in the data set. Asexpected, the property damage caused by a disaster is a strong predictor of receipt of acost share increase on its own across all models, but as shown by the descriptive figuresabove, this is not the only factor influencing these decisions. By including this as acontrol variable, we can investigate the impact of more political factors on the issuanceof cost share increases.

17. President Bush did use this power to set the federal cost share at 100% for New York and theDistrict of Columbia for the terrorist attacks of 9/11.

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Full Model Results

The swing voter theory expects the greatest probability of receiving a federal costshare increase to be for states with an election margin near zero. The full model indicatesthat this variable has an impact on the issuance of a federal cost share increase,18 but thiseffect is much easier to see in Figure 3. These plots show the impact of various scenarioson the probability of the president deciding to grant a cost share increase in the describedscenario (left plot). The right plot displays the first difference between each scenario. Forswing voter theory, an election margin of 1% (swing state) is compared to a margin of30% (safe state).19 There are generally a few states in each election that have marginsin the 1% or less range and a couple that approach the 30% margin. For all scenariosdamage per capita is held at $150 per capita, and the remaining covariates are held at

18. This relationship is not seen for the swing state indicator variable.19. The “swing state” in these scenarios is won that the president won by 0.01 while the “safe state”

is one he lost by 0.30. Scenarios with the swing state as a close loss and the safe state as a big loss resultedin nearly identical probabilities.

TABLE 1Logistic Regression Results Predicting Presidential Issuance of a Federal Cost Share Increase

All Clinton G. W. Bush Obama

Hypothesis 1—Swing Voter TheoryElection Margin (logged) −0.29* −0.27 −0.35 −0.60

(0.12) (0.29) (0.21) (0.38)Hypothesis 2—Coalition MaintenancePresident’s Margin −0.47 −3.03 3.99 1.87

(1.21) (2.17) (3.54) (2.86)Hypothesis 3—President-Governor Party AlignmentPresident-Governor Party Match −0.28 −0.32 0.05 −0.74

(0.17) (0.24) (0.34) (0.46)Hypothesis 4—Presidential Election ProximityProximity of Next Presidential Election (years) 0.03 0.24 −0.95* −0.26

(0.13) (0.18) (0.42) (0.49)Control VariablesDamage Per 1,000 Residents 7.11* 6.59* 9.27* 12.69*

(1.14) (1.41) (2.89) (4.94)Neighbor Waivers 1.53* 2.01* 1.46* 0.54

(0.23) (0.41) (0.40) (0.59)State Poverty Level 0.10* 0.10 0.04 0.24*

(0.04) (0.06) (0.12) (0.11)State Population −0.73* −0.97* 0.47 −4.77*

(0.35) (0.47) (0.55) (2.36)Intercept −4.94* −3.39* −5.30* −6.91*

(0.82) (1.16) (2.02) (2.33)N 945 344 393 208log L −137.81 −48.84 −12.87 1.05

Standard errors in parentheses.* Indicates significance at p < 0.05.

852 | PRESIDENTIAL STUDIES QUARTERLY / December 2013

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their respective means.20 In this scenario, swing states have an 11% greater chance ofreceiving a cost share increase compared to safe states. The confidence interval for this firstdifference is bounded away from zero, indicating this difference is significant at the 95%level. Presidents do appear to favor swing states, confirming hypothesis 1.

Coalition maintenance (Hypothesis 2) expects the greatest probability of receivinga federal cost share increase to be for states where the president won by a sizable marginand is presented as an alternative to the swing voter theory. For two extreme cases of apartisan base state (+.3 vote margin for the president) and opponent’s base state (−.3),the results are not statistically different and actually appear to be nearly the same. Thefirst two hypotheses were expected to potentially be mutually exclusive, so the lack ofsubstantiation of Hypothesis 2 is not surprising.

Next I examine whether the party of the state’s governor in relation to the presidenthas an impact on receiving a federal cost share increase (Hypothesis 3). It is the governorwho requests the disaster declaration and may follow up requesting additional funding,and therefore it is expected that governors who are co-partisans with the president maybe more successful in obtaining these waivers for their state. Although it is not statisti-cally significant at the 95% level, it appears that governors from the party opposite thepresident are slightly (2 to 3%) more likely to receive a cost share increase. It is possiblethat this variable is trending in the opposite direction as expected because governors ofthe opposing party are more likely to be “squeaky wheels” and publicly advocate for morefunds for their state. This could also simply be an anomaly of the data.

20. Per capita damages of $150 will be a common reference point during the analysis. This isapproximately the ninetieth percentile of the data set but more relevantly falls within a gray area of $100 to$200 in which 40% of disasters (8 out of 20) received a cost share increase.

0 0.1 0.2 0.3

0 0.1 0.2 0.3

Predicted Probabilities

Logit Estimates with 95% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Probability

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

0 0.1 0.2 0.3

0 0.1 0.2 0.3

First Differences

Difference in Probability for Each Pair of Scenarios

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Parties

Three Years �

FIGURE 3. Predicted Probabilities and First Differences of Receiving Federal Cost Share Increase(full data set).

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The fourth hypothesis shifts from expectation of geographic distributive politics toone based temporally on location within the presidential election cycle. The expectationis that presidents may be more active in issuing federal cost share increases when anelection is imminent in order to maximize the electoral benefit of issuing an increase. Forthe two highlighted cases, two months prior to an election and three years prior toan election, there is no significant difference in the probability of issuing a cost shareincrease. This aligns with permanent campaign theorizing, which views presidents asalways mindful of re-election.21

Are Presidents Using This Power in the Same Ways?

As identified at the beginning of the results section, Presidents Clinton and GeorgeW. Bush utilized their power to grant cost share increases in different ways, with Clintonbeing much more likely to issue cost share increases than Bush. Regression models foreach president individually are handicapped by the small number of cases, but someinteresting trends and obvious differences emerge in Figure 4.22

President Clinton

Even a quick glance at Clinton’s predicted probabilities and first differences makesit apparent that his actions do not conform to the hypotheses. He was more likely to assisthis opponent’s base states, and there was no clear effect for party of the governor orproximity to an election. Although Clinton was not engaged in the forms of distributivepolitics outlined in the hypotheses, this does mean that his motives were entirelyinnocuous. Clinton entered office right after President George H. W. Bush and FEMAwere widely criticized for their handling of the response to Hurricane Andrew. TheFEMA that Clinton inherited was often seen as a bureaucratic “turkey farm,” and itsnegative reputation put it in danger of a bureaucratic death sentence from Congress(Farazmand 2001, 411). Clinton quickly appointed James Lee Witt, a career emergencymanager, as FEMA director, and Witt worked toward establishing credibility and apositive reputation for FEMA (Roberts 2006). Clinton’s apparent strategy of sprinklingextra disaster relief funds throughout the country and throughout his tenure in office fitswell with the goals of an organization that is working on pleasing all and establishing itsown positive reputation.

President George W. Bush

Evidence from the scatter plot indicating President Bush’s tendency to issue costshare increases in close proximity to presidential elections is confirmed by the regression

21. Additional variables were tested in preliminary models controlling for first verses second term inoffice as well as looking for an impact preceding congressional elections. Neither factor had a measurableimpact on the models.

22. Confidence intervals are shown at the 90% level for the presidents individually.

854 | PRESIDENTIAL STUDIES QUARTERLY / December 2013

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0 0.1 0.2 0.3 0.4 0.5

Clinton Predicted Probabilities

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Clinton First Differences

0 0.1 0.2 0.3 0.4 0.5

G. W. Bush Predicted Probabilites

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

G. W. Bush First Differences

0 0.1 0.2 0.3 0.4 0.5

Obama Predicted Probabilities

Logit Estimates with 90% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Obama First Differences

Swing State

Partisan Base

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Opposing Party

Three Years

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Big Loss

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Big Win

Opposing Party

Three Years

FIGURE 4. Predicted Probabilities and First Differences of Receiving Federal Cost Share Increase(Each President).

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results. A disaster occurring two months before a presidential election is 12.5% morelikely to receive a cost share increase than one occurring three years before the election.There is also a small bias in favor of swing states that is not statistically significant forBush alone, but the combination of Bush and Obama led to significant results in favor ofswing states in supplemental modeling.

As Figure 2 demonstrated, Bush issued zero cost share increases during his first threeyears, 11 in 2004 (two after the election), none in 2005, one in 2006, three in 2007, andsix in2008.Bushdidexperience relatively fewlargedisasters comparedtoClinton,but thereare still some very likely candidates for cost share increases including flooding in early 2001in North Dakota and the 2001 Nisqually earthquake in Washington State, both occurringbefore 9/11. After the attacks of 9/11, FEMA’s attention was directed away from “natural”disasters and toward terrorism. This terrorism focused continued as FEMA was absorbedinto the newly created Department of Homeland Security in 2003 and did not really changeuntil after Hurricane Katrina in 2005 (Rubin 2007). Even during this time of a terrorism-centered FEMA, Bush still issued many cost share increases just prior to the 2004 election.The complete lack of cost share increases in the first three years of his term, followed by thesudden utilization of this power before the election (and before the refocusing of FEMA inthe aftermath of Hurricane Katrina), provide strong circumstantial evidence that politicswere a contributing factor in these decisions.

InBush’s secondterm,HurricaneKatrinawasastrongwake-upcall for the importanceof disaster management. However, this does not appear to have resulted in a substantialchange in Bush’s pattern of distributing cost share increases. The only two increases issuedin the first two years of his second term were for hurricane damage in Alabama (issued inearly2005for2004damage)andsevere storms inPennsylvania (June2006).NewYorkStatewas hit by the same series of storms as Pennsylvania, and each state sustained approximately$50 per capita property damage. Pennsylvania received a cost share increase allowingfederal funds to cover 100% of qualifying public expenses while New York did not. In the2006 congressional elections, the incumbent, Rick Santorum, was defeated by Bob Casey,Jr. Although Casey won by 17% on election day, polls showed a much closer race in lateJune when the cost share increase was issued. On the other side of the border in New York,Hillary Clinton was running for reelection in a race that was never close. Although theyshare a long border, Pennsylvania and New York are different political landscapes, and itis possible that the impending congressional elections played a role in Bush’s decision tosend extra disaster relief funds to Pennsylvania and not New York.

A final interesting case that looks prime for a cost share increase at first glance is theremnants of Hurricane Ike, which swept through Ohio in mid-September 2004 causingwidespread damage across rural areas of the state and Columbus. Damage in Ohioamounted to $65 per capita. None of the states affected by Hurricane Ike received costshare increases before the election, indicating caution on the part of the Bush adminis-tration, which waited for damage estimates before issuing waivers for Texas and Louisianaon November 26, 2004.23 Without a doubt Texas and Louisiana were the states hardest

23. These cases are not on the scatterplots as Congress subsequently legislated the cost share increase,removing it from the president’s control.

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hit, so it is not surprising that based on Bush’s tendency to issue cost share increasesbefore the election, Ohio was left out once the election had passed.

President Obama

With only three years in office, Obama has faced fewer declared disasters (208) andapproved only a few cost share increases (13). Even with this small number of cases, thesimulations indicate that under Obama swing states are 12% more likely to receive costshare increases than safe states (though not bounded away from zero at a confidence levelof 90% for the election margin variable, this result is significant at the 90% level for theswing state indicator variable). Obama appears to slightly favor opposing governors butit is worth noting that most of the swing states identified in the 2008 election hadRepublican governors for most or all of Obama’s first term. It is not possible to conclu-sively determine if Obama shares Bush’s tendency to issue more cost share increases inelection years because full data for 2012 is not yet available. However, preliminaryevidence does not indicate an election proximity bias. Obama issued four cost shareincreases in the 12 months before the election. One went to Vermont in May 2012 (severeflooding), the others went to New York, New Jersey, and Connecticut on November 1,the Thursday before election day and two days after Hurricane Sandy struck the eastcoast. The Sandy cost share increases narrowly applied to emergency power restorationand public transportation assistance. Subsequent funding of Hurricane Sandy has largelybypassed the conventional disaster declaration and funding system due to specific,supplemental appropriations by Congress.

Conclusion

The findings in this article provide preliminary evidence in support of increasedpresidential attention to swing states for supplemental disaster relief under the Bushand Obama administrations. Swing states were much more likely to receive additionalassistance in the aftermath of disasters above and beyond the federal government’sminimum obligation. No evidence is found linking cost share increases to a president’sbase states or to states with governors of the same party as the president. Evidenceof presidential election proximity playing a role was only present during the Bushadministration.

A second important finding is that presidential administrations use this powerin different ways. Clinton did not conform to any of the partisan hypotheses posed. Thiseither highlights an overtly universalistic strategy on his behalf or may indicate that themeasures utilized did not reflect his electoral strategy. President George W. Bush reacteddifferently depending on proximity of the next presidential election, and Obama favorsswing states. These findings indicate a need to look for differences in the way powers areutilized by various administrations when studying presidential decision making. Notablyabsent from Reeves (2011) and other studies of presidential distributive politics areexaminations of presidents one at a time. Small numbers of cases may make this type of

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analysis more challenging, but the results in this article underscore the importance ofconsidering the possibility that different presidential administrations utilize power indifferent ways. Although all three presidents were operating under the same generaldisaster response framework, each president still was able to use this power in hispreferred manner.

This article began with a simple question: In what ways do presidents use theirpolicy power for partisan political gain? This research indicates that presidents engagein distributive politics in a field as politically dangerous as disasters. They are able to dothis by taking action once the national attention fades by sending extra relief funds topolitically important swing states, taking the burden off of state and local governmentsand receiving positive local press in the process. Only one potential instance of presi-dential distributive politics was investigated in this article, and future research is neededto perform similar investigations into other presidential powers in order to establish acredible pattern of this type of behavior across a wide range of presidential decisions.

Appendix

Additional Models and Graphs

Disasters plotted by date and state of occurrence. States receiving cost share increase in bold, date of increase designated by triangle.

Dam

age P

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FIGURE 5. Declared Disasters and Property Damage with Federal Cost Share IncreasesHighlighted (Obama).

858 | PRESIDENTIAL STUDIES QUARTERLY / December 2013

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TABLE 2Logistic Regression Results Predicting Presidential Issuance of a Federal Cost Share IncreaseSwing State Indicator Variable

All Clinton G. W. Bush Obama

Hypothesis 1—Swing Voter TheorySwing State Indicator −0.28* −0.24 −0.31 −0.50

(0.12) (0.28) (0.20) (0.36)Hypothesis 2—Coalition MaintenancePresident’s Margin −0.48 −2.92 3.38 2.15

(1.20) (2.12) (3.46) (2.74)Hypothesis 3—President-Governor Party AlignmentPresident-Governor Party Match −0.26 −0.28 0.08 −0.54

(0.16) (0.24) (0.33) (0.44)Hypothesis 4—Presidential Election ProximityProximity of Next Presidential Election (years) 0.04 0.22 −0.78 −0.30

(0.13) (0.18) (0.41) (0.47)Control VariablesDamage Per 1,000 Residents 6.67* 5.86* 8.20* 8.39*

(1.13) (1.38) (2.83) (4.74)Neighbor Waivers 1.48* 1.88* 1.25* 0.59

(0.23) (0.40) (0.39) (0.56)State Poverty Level 0.09* 0.09 0.05 0.21

(0.04) (0.06) (0.11) (0.11)State Population −0.70* −0.94* 0.53 −3.66

(0.34) (0.45) (0.53) (2.26)Intercept −4.83* −3.19* −4.99 −6.01*

(0.81) (1.13) (1.98) (2.23)N 945 344 393 208

Standard errors in parentheses.* Indicates significance at p < 0.05.

0 0.1 0.2 0.3

0 0.1 0.2 0.3

Predicted Probabilities

Logit Estimates with 95% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Probability

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

0 0.1 0.2 0.3

0 0.1 0.2 0.3

First Differences

Difference in Probability for Each Pair of Scenarios

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Parties

Three Years

FIGURE 6. Predicted Probabilities and First Differences of Receiving Federal Cost Share IncreaseSwing State Indicator (full data set).

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0 0.1 0.2 0.3 0.4 0.5

Clinton Predicted Probabilities

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Clinton First Differences

0 0.1 0.2 0.3 0.4 0.5

G. W. Bush Predicted Probabilites

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

G. W. Bush First Differences

0 0.1 0.2 0.3 0.4 0.5

Obama Predicted Probabilities

Logit Estimates with 90% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Obama First Differences

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Party

Three Years

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Party

Three Years

Swing State

Big Loss

Same Party

Two Months

Safe State

Big Win

Opposing Party

Three Years

FIGURE 7. Predicted Probabilities and First Differences of Receiving Federal Cost Share Increasefor each President Swing State Indicator.

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Figures 8 and 9 below replicate Figures 3 and 4 with the coefficients resulting fromthe rare events logit models.

Data Sources

Disaster Declarations: A comprehensive list of disaster declarations including basicinformation about the type and location of the disaster was obtained from FEMA(http://www.fema.gov).

Federal Expenditures for Each Disaster: This information was obtained from the PublicEntity Risk Institute (http://www.peripresdecusa.org/mainframe.htm) for disastersthrough 2008. Figures for 2009 and 2010 were manually recorded from FEMA’swebsite. Although not included in the model, this data was used for the case presentedin the introduction.

TABLE 3Rare Events Logit Regression Results Predicting Presidential Issuance of a Federal Cost ShareIncrease

All Clinton G. W. Bush Obama

Hypothesis 1—Swing Voter TheorySwing State Indicator 0.21 −0.56 −0.17 1.65

(0.36) (0.54) (0.93) (0.99)

Hypothesis 2—Coalition MaintenancePresident’s Margin −0.95 −2.76 1.58 2.50

(1.10) (2.18) (2.85) (3.14)

Hypothesis 3—President-Governor Party AlignmentPresident-Governor Party Match −0.25 −0.34 0.07 −0.52

(0.16) (0.24) (0.33) (0.45)

Hypothesis 4—Presidential Election ProximityProximity of Next Presidential Election (years) −0.00 0.25 −1.07* 0.21

(0.13) (0.18) (0.43) (0.52)

Control VariablesDamage Per 1,000 Residents 7.63* 6.69* 10.21* 12.64*

(1.16) (1.44) (2.72) (4.55)Neighbor Waivers 1.52* 2.00* 1.39* 0.54

(0.23) (0.40) (0.39) (0.57)State Poverty Level 0.09 0.09 0.01 0.32*

(0.05) (0.06) (0.12) (0.14)State Population −0.56 −1.03* 0.49 −3.63

(0.32) (0.47) (0.48) (1.91)Intercept −4.15* −3.87* −3.61* −7.76*

(0.75) (0.94) (1.83) (2.86)N 945 344 393 208

Standard errors in parentheses.* Indicates significance at p < 0.05.

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Damage Amounts: As noted in the text, the Spatial Hazard Events and Losses Databasefor the United States, part of the Hazards and Vulnerability Risk Institute (HazardsVulnerability Research Institute 2012), includes damage amounts for 800,000weather events in the United States. This information was compiled at to the statelevel to approximate damage caused by each disaster.

Federal Cost Share Increases: Francis McCarthy’s Congressional Research Service article(2010) provided a list of federal cost share increases through 2008. Cost share increaseinformation for 2009-11 were found by keyword searches through the federal register(www.federalregister.gov).

State Demographics: Poverty level as well as state population (used to create per capitaamounts) was downloaded from the U.S. Census (http://www.census.gov).

Election Data: The U.S. Election Atlas (http://uselectionatlas.org/RESULTS/) was usedfor election results by state.

0 0.1 0.2 0.3

0 0.1 0.2 0.3

Predicted Probabilities

Logit Estimates with 95% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Probability

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

0 0.1 0.2 0.3

0 0.1 0.2 0.3

First Differences

Difference in Probability for Each Pair of Scenarios

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Parties

Three Years

FIGURE 8. Rare Events Logit: Predicted Probabilities and First Differences of Receiving FederalCost Share Increase (full data set).

862 | PRESIDENTIAL STUDIES QUARTERLY / December 2013

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0 0.1 0.2 0.3 0.4 0.5

Clinton Predicted Probabilities

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Clinton First Differences

0 0.1 0.2 0.3 0.4 0.5

G. W. Bush Predicted Probabilites

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

G. W. Bush First Differences

0 0.1 0.2 0.3 0.4 0.5

Obama Predicted Probabilities

Logit Estimates with 90% confidence intervals shown. Damage held at $150 per capita, other covariates held at their respective means for each simulation.

Swing Voter

Theory

Coalition

Maintenance

President−Governor

Party Match

Proximity of Next

Presidential Election

−0.2 0 0.2 0.4 0.6

Obama First Differences

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Party

Three Years

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Party

Three Years

Swing State

Partisan Base

Same Party

Two Months

Safe State

Opponent's Base

Opposing Party

Three Years

FIGURE 9. Rare Events Logit: Predicted Probabilities and First Differences of Receiving FederalCost Share Increase for Each President.

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