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The effects of congressional appropriation committee membership on the distribution of federal research funding to universities.



I. INTRODUCTION

In 1994 members of the Republican Party pledged to seek legislation to impose term limits on members of Congress. This pledge stemmed stemmed  
adj.
1. Having the stems removed.

2. Provided with a stem or a specific type of stem. Often used in combination: stemmed goblets; long-stemmed roses.
 from the popular belief that senior members of Congress tend to promote personal interests or are more influenced by lobbying efforts that may not be representative of their constituents. Today, term limits continue to be discussed but have not been enacted; instead, many members have focused their energies toward minimizing the time spent on any particular committee of Congress, believing that tenure on a committee is a more serious concern than simple tenure in Congress. Implicit in Adj. 1. implicit in - in the nature of something though not readily apparent; "shortcomings inherent in our approach"; "an underlying meaning"
underlying, inherent
 these concerns is the issue whether as incumbent politicians plan to retire they will behave differently and, if so, whether tenure on a congressional committee exacerbates this behavior.

This article explores the role of membership on the appropriations committee In the United States government, the Appropriations Committee can refer to either:
  • the United States House Committee on Appropriations
  • the United States Senate Committee on Appropriations
 on the distribution of federal research funding Research funding is a term generally covering any funding for scientific research, in the areas of both "hard" science and technology and social science. The term often connotes funding obtained through a competitive process, in which potential research projects are evaluated and  to universities. Specifically, it explores whether funding is diverted di·vert  
v. di·vert·ed, di·vert·ing, di·verts

v.tr.
1. To turn aside from a course or direction: Traffic was diverted around the scene of the accident.

2.
 to these universities because politicians use their position on a committee to promote personal or constituent CONSTITUENT. He who gives authority to another to act for him. 1 Bouv. Inst. n. 893.
     2. The constituent is bound with whatever his attorney does by virtue of his authority.
 interests. Previous research on shirking Shirking

The tendency to do less work when the return is smaller. Owners may have more incentive to shirk if they issue equity as opposed to debt, because they retain less ownership interest in the company and therefore may receive a smaller return.
 compares the voting records of politicians on certain issues with demographic and economic characteristics of the politicians' constituents. This article explores the issue of shirking differently. I explore how membership on congressional appropriations committees affects the distribution of federal research funding to universities. I look at two types of relationships between the members and the universities. First, I consider the relationship between members and the universities that are located in the members' districts (states in the case of senators). Second, I examine the relationship between members and their undergraduate alma mater ma·ter  
n. Chiefly British
Mother.



[Latin mter; see m
. I use district representa tion to proxy favoritism that reflects a politician's constituents. Given that in most instances an alma mater affiliation is not the same as district representation, I use alma mater affiliation to proxy favoritism that reflects the politician's personal interests.

Federal research funding accounts for more than 60% of research funding received by research universities. Previous research has shown a positive impact of federal funding on research outcomes; see Adams and Griliches (1998), Arora ARORA Arkansas Regional Organ Recovery Agency  and Gambardella (1997), Connolly Con·nol·ly   , Maureen Catherine Known as "Little Mo." 1934-1969.

American tennis player who was the first to win the grand slam of U.S., British, French, and Australian women's championships (1953).

Noun 1.
 (1997), Payne
:The name may also be spelt Paine.


The surname Payne stems from paganus, see pagan. People
  • King Payne, a Seminole chief
  • A.R.
 and Siow (2002), and Payne (2001). Except for Payne and Siow (2002), however, these articles do not consider that political diversion A turning aside or altering of the natural course or route of a thing. The term is chiefly applied to the unauthorized change or alteration of a water course to the prejudice of a lower riparian, or to the unauthorized use of funds.  of funds may promote or detract from detract from
verb 1. lessen, reduce, diminish, lower, take away from, derogate, devaluate << OPPOSITE enhance

verb 2.
 research productivity as with any other federal program.

This article concentrates on the impact of membership on the House and Senate appropriations committees because they wield wield  
tr.v. wield·ed, wield·ing, wields
1. To handle (a weapon or tool, for example) with skill and ease.

2. To exercise (authority or influence, for example) effectively. See Synonyms at handle.
 the greatest power in the allocation The apportionment or designation of an item for a specific purpose or to a particular place.

In the law of trusts, the allocation of cash dividends earned by a stock that makes up the principal of a trust for a beneficiary usually means that the dividends will be treated as
 of funding. (1) Using a panel data set spanning 26 years, I explore how changes in the composition of the appropriations committees affects the distribution of research funding after controlling for the heterogeneity het·er·o·ge·ne·i·ty
n.
The quality or state of being heterogeneous.



heterogeneity

the state of being heterogeneous.
 that exists across different universities.

The results suggest that both district representation and alma mater affiliation matter. Thus there is evidence of shirking for personal interests and evidence of members representing their constituents. With respect to the representation of one's constituents, the strongest results suggest that public universities benefit from representation on both the Senate and House committees. Private universities, however, only benefit from representation in the Senate. With respect to alma mater affiliations, the results suggest again that public universities benefit from representation on both the Senate and House committees. Private universities also benefit from representation on both the Senate and House committees. The results also suggest that the tenure of the member on the committee matters, as does whether the member is a part of the majority party in power in the congressional chamber. Given that a politician is likely to favor an institution only if asked, the results also suggest lobbying efforts by public and private universities may differ.

The results suggest that members of Congress influence the distribution of federal research funding. As much as 39% of research funding is diverted for reasons associated with the representation of one's constituents. As much as 47% of funding is diverted for reasons associated with shirking. Thus, although most funding is distributed through federal agencies using a peer-reviewed process, politics has a role in diverting di·vert  
v. di·vert·ed, di·vert·ing, di·verts

v.tr.
1. To turn aside from a course or direction: Traffic was diverted around the scene of the accident.

2.
 funding that might be given to other institutions based on a more objective process. These diversions reduce the potential effectiveness of the funding on research activities. As such, similar to the finding of Alvarez Al·va·rez   , Luis Walter 1911-1988.

American physicist. He won a 1968 Nobel Prize for his study of subatomic particles.
 and Saving (1997), this study provides additional evidence that members of Congress have much more control over federal dollars than is commonly believed.

The article is set forth as follows. Section II presents a conceptual framework For the concept in aesthetics and art criticism, see .

A conceptual framework is used in research to outline possible courses of action or to present a preferred approach to a system analysis project.
, and section III provides an overview of the appropriations process as it relates to research funding. Section IV discusses the data and methodology used to measure the level of political influence over research funding. Section V discusses the results, and section VI provides a brief conclusion.

II. CONCEPTUAL FRAMEWORK

Since World War II the federal government has played a significant role in funding basic and applied research. The federal government became more heavily involved as a result of its recognition that research is important for economic growth and that the private sector was underengaged in the research process. (2) Most agencies have adopted a peer-reviewed process for distributing research funding to universities. This process attempts to elicit e·lic·it  
tr.v. e·lic·it·ed, e·lic·it·ing, e·lic·its
1.
a. To bring or draw out (something latent); educe.

b. To arrive at (a truth, for example) by logic.

2.
 information from researchers engaged in similar research about the quality of the projects for which funding is sought, seeking to minimize the politics associated with federal agencies and Congress. The agencies, however, are not completely autonomous from Congress. Thus Congress may indirectly influence the actions taken by the agencies. Because agencies receive their funding from Congress (with the approval of the president), Congress has several avenues by which to monitor and/or control an agency's actions, ex-ante and ex-post. Thus, as introduced by Miller and Mo e (1983), Congress and agencies are likely to be strategic in their actions, thereby creating a principal-agent relationship Principal-agent relationship

Occurs when one person, an agent, acts on the behalf of another person, the principal.
. (3) As discussed in Calvert Cal·vert  

Family of English colonists in America, including George (1580?-1632), First Baron Baltimore; his son Cecilius (1605-1675), Second Baron and recipient of the Maryland charter; another son, Leonard
 and Fenno (1994), the degree to which an agency reflects the preferences of Congress depends on the level of information asymmetries between Congress and the agencies.

With respect to research funding, assuming that most members lack the information needed to evaluate the quality of research proposals, potential areas of influence they may exert over an agency may include funding allocated to an agency. Thus if Congress is not satisfied with the distribution of funding to certain schools or to geographic areas, funding to agencies in future years may be affected. For example, if members believe that more research funding should be devoted to such things as cancer research or a "star wars" defense program, the budget can be adjusted to focus more funding on these areas, thus potentially minimizing the discretion an agency may have over the distribution of funding within the agency. Similarly, if a member is from a region that is known to be an expert in a particular area of research, that member may seek to promote funding for programs related to that research area.

In recent years, Congress has affected the distribution of research funding in two more direct ways. (4) First, Congress can directly appropriate funding by earmarking It has been suggested that some sections of this article be split into a new article entitled Earmark (USA).  specific amounts to particular universities. Earmarks started being allocated to universities in large numbers in the early 1980s. (5) Despite much media coverage concerning earmarks, they represent between 5% and 10% of total federal research funding. A second way Congress has affected the distribution of research funding is by encouraging agencies to develop set-aside programs, whereby agencies seek more competitive research proposals from researchers affiliated with universities that are located in states that have historically received low levels of funding. Set-aside programs were established in the early 1980s as pilot projects and have grown in the past 30 years. These programs are designed to improve the research infrastructure within the state, with the expectation that this will promote more competitive proposals by researchers locate d in the state that receives the funding. (6)

Given that there are several ways in which Congress may affect the distribution of funding, the next issue concerns for what purpose may a member of Congress seek redistribution re·dis·tri·bu·tion  
n.
1. The act or process of redistributing.

2. An economic theory or policy that advocates reducing inequalities in the distribution of wealth.
. As set forth in Peltzman (1976; 1984) and others, a politician's actions may be driven from an interest to represent all or part of his or her constituents or for personal reasons. Although these reasons could stem from the politician acting alone, in most instances, the politician's behavior is likely to stem from lobbying from the person or institution that is likely to benefit from the actions taken by the politician. If there are vehicles by which a politician is able to take actions that do not reflect the interest of his or her constituents, the politician is considered to be shirking responsibility, as discussed in Huber et al. (2001) and Rothenberg and Sanders San´ders

n. 1. An old name of sandalwood, now applied only to the red sandalwood. See under Sandalwood.
 (2000).

As illustrated by Adler (2000), little research has examined the role of shirking with respect to the appropriations process. With respect to federal research funding, evidence of shirking as well as evidence that suggests a politician has exerted influence with respect to his or her district potentially diverts the funding away from projects that may be viewed as more socially desirable. (See Goff n. 1. A silly clown.
1. A game. See Golf.
 and Grier [1993], Greene and Munley [1981], Levitt and Snyder Snyder, city (1990 pop. 12,195), seat of Scurry co., NW Tex., in a prairie and mesquite region; inc. 1907. Oil production is the city's main industry; natural gas is also refined and processed.  [1996], Lott and Bronars [1993], and Poole Poole, town (1991 pop. 122,815), Dorset, S England, on the north side of Poole Harbour. Poole has shipbuilding, pottery-making, and other industries. It is a naval supply station and a seaplane base with considerable coastal trade. There is also a technical college.  and Romer
This page is about the cartographic mechanism called a "Romer" or "Roamer"; for people named Romer see Romer (surname)


A Romer or Roamer is a simple device for accurately plotting a grid reference on a map.
 [1993].) Thus diversions associated with district representation or alma mater affiliation represent a social cost that affects the research activities undertaken by universities.

There are several reasons why a politician may want to have funding distributed to the universities located in his or her district. First, given that research funding benefits the university by increasing the level of university resources, this will benefit the community and/or promote growth of other sectors within the district. Second, constituents may judge a politician by his or her ability to bring federal funding to the district. Thus, if politicians can affect the distribution of research funding, one should see an effect with respect to those universities located in the district represented by the politician.

Similarly, a politician may use the political process to encourage the distribution of research funding to a particular university for personal reasons. Distinguishing between the exertion exertion,
n vigorous action, a great effort, a strong influence.
 of political influence for personal reasons and using this influence to help one's constituents is difficult with respect to most types of federal funding. With respect to funding to universities, however, we can use the alma mater affiliation of the politician as a measure of shirking and use the location of universities within a member's district as a measure of representation associated with one's constituents. Provided one's alma mater is not located within one's district, there is little reason to suggest that favoring favoring

an animal is said to be favoring a leg when it avoids putting all of its weight on the limb. A part of being lame in a limb.
 one's alma mater promotes the interests of a politician's constituents. (7)

To explore the effect of political representation on the distribution of federal research funding, I examine the relationship between research and doctoral universities and the members of Congress that sit on the appropriations committee. As will be explained in more detail, for each member on the appropriations committee between 1972 and 1998, I identified the universities located in their district as well as the universities from which they received an undergraduate degree “First degree” redirects here. For the BBC television series, see First Degree.

An undergraduate degree (sometimes called a first degree or simply a degree
. In addition, I identified their party affiliation and tenure on the committee. With this information, I explore the questions of whether politicians affect the distribution of federal research funding and, if so, the extent to which the distribution is attributable to constituent interests or shirking.

III. APPROPRIATIONS PROCESS AND RESEARCH FUNDING

With respect to discretionary funding (funding that is not required to be allocated under mandatory entitlements, e.g., Social Security, Medicaid Medicaid, national health insurance program in the United States for low-income persons; established in 1965 with passage of the Social Security Amendments and now run by the Centers for Medicare and Medicaid Services. ), the appropriations committee is responsible for the budgets of all agencies. (8) Much of the discussion concerning the structure of the budget is discussed and developed by the appropriations committees and subcommittees. In addition to determining the annual appropriations, these committees also provide funding guidance to agencies. Although agencies are not required to follow this guidance, it is expected that most agencies will comply with the wishes of the appropriations committees.

The classic work discussing the role taken by members of the appropriations committee is that of Fenno (1966). Members who are appointed to the appropriations committee are prevented from serving on other standing committees, thereby emphasizing the importance of their role on the appropriations committee. In general, research suggests members of this committee exert much power over the budget. Positions on the committee and the subcommittees are coveted cov·et  
v. cov·et·ed, cov·et·ing, cov·ets

v.tr.
1. To feel blameworthy desire for (that which is another's). See Synonyms at envy.

2. To wish for longingly. See Synonyms at desire.
. Provided a member is reelected, once on the appropriations committee, the member is likely to serve several terms on the committee. Because of the complexity of the government's budget and tenure on the committee, members develop a great deal of expertise with respect to the appropriations process. Thus other members of Congress tend to defer de·fer 1  
v. de·ferred, de·fer·ring, de·fers

v.tr.
1. To put off; postpone.

2. To postpone the induction of (one eligible for the military draft).

v.intr.
 to the decisions made by the appropriations committees. The role of an appropriations subcommittee sub·com·mit·tee  
n.
A subordinate committee composed of members appointed from a main committee.


subcommittee
Noun
 can be just as important (if not more so) as the role on the appropriations committee insofar in·so·far  
adv.
To such an extent.

Adv. 1. insofar - to the degree or extent that; "insofar as it can be ascertained, the horse lung is comparable to that of man"; "so far as it is reasonably practical he should practice
 as the subcommittee is res ponsible for the initial allocation to specific federal agencies.

With respect to the mechanics of the appropriations committee, the party in power of each chamber decides the number of members that will serve on the appropriations committee. Each party selects their members to the committee. The chair of the committee determines who serves on the 13 subcommittees. The budget process starts with the president submitting a proposed budget that includes each agency's request for funding. The level of detail for agency funding varies across the different agencies. The House appropriations committee reviews and changes the budget. The Senate acts second, acting more as an appellate body for the budget. (9) In the end, the two chambers and the president must approve the budget.

As discussed, there are several ways a university may receive special treatment with respect to research funding. The influence may stem from a member of Congress seeking special treatment for a particular university through its influence over the budget or over an agency. In this case, the member of Congress is not likely to seek special treatment for a given university unless that university actively lobbies the member for special treatment. The influence, however, could also come from an agency seeking some sort of favoritism (e.g., a better budget) from Congress. We should expect that most political influence is likely to be through the appropriations committees' interaction with the agencies responsible for distributing research funding to universities. Thus congressional influence over the direction of research funding is likely to be more through indirect means. (10) The specific relationship between the role of the university and the member of Congress with respect to lobbying is left for future resea rch. (11)

IV. DATA AND METHODOLOGY

The data for this project were gathered from two sources: congressional appropriations committee data and computer aided science policy analysis and research (CASPAR Caspar: see Wise Men of the East. ) data on federal funding and institutional characteristics. (12) For information on the congressional appropriations committees, I hand-collected data on congressional membership on the appropriations committee and subcommittees for both chambers of Congress for the period 1972 to 1998. Except for the occurrence of a death or resignation, both committees may change members every two years. (13) For each member that served on the appropriations committee during this period, I identified the state represented by the member, the political party affiliation of the member, the member's position on the committee, the undergraduate alma maters of the member, and the district of representation. (14) With respect to the member's position on the committee, there are three possible positions--majority and minority chairperson chairperson Chairman The head of an academic department. See 'Chair.', Cf Chief.  and general member. The majorit y and minority chairs are usually assigned as·sign  
tr.v. as·signed, as·sign·ing, as·signs
1. To set apart for a particular purpose; designate: assigned a day for the inspection.

2.
 to the senior members on the committee affiliated with the political party in power and the political party not in power, respectively.

I concentrate on the general members serving on the committee. (15) I study four effects on the distribution of research funding: first, the effect of having a member on the committee; second, the role of these members insofar as they are also a chair of one of the subcommittees that oversee the key agencies involved in research funding; third, the role of the members being a part of the majority or minority party that controls the chamber of Congress under study; and, fourth, the role of committee tenure of these members.

Using the CASPAR data set, I use the total annual federal research expenditures reported by the universities for the period 1973 to 1999. I combined this measure with the data on congressional representation and determined those universities for which there is alma mater and/or district representation for each year during the period under study. I limit my analysis to those universities with a Carnegie Carnegie (kärnĕg`ē, kär`nəgē), borough (1990 pop. 9,278), Allegheny co., SW Pa., an industrial suburb of Pittsburgh; inc. 1894. A steel town, it has coal mines and plants that make chemicals and electrical equipment.  (1994) classification of research or doctoral university. (16) This leaves 220 universities that I can analyze. (17) Approximately 54% of these universities are classified as a research university.

Seventy-two of the universities have alma mater representation, and 186 of the universities have district representation at some point during the sample period. Of the 72 universities with an alma mater affiliation, 68 universities also have a district affiliation in the House or Senate during the sample period. Thus it is not uncommon for a university to have both district and alma mater representation during the sample period, although a given member is not likely to represent and have an alma mater affiliation with the same university. To the extent a member has both types of affiliations, this occurs most commonly with respect to representation on the Senate committees. Across chambers, a university with an alma mater affiliation with a member on the Senate committee also has an alma mater affiliation with a member on the House committee in 27% of the observations. For only 12% of these observations, however, is there a member affiliated with the majority party in power on both the House and Senate committees.

Of the 186 universities that are located in the district (or state for the Senate) represented by the committee members, 68 also have an alma mater affiliation during the sample period. Across chambers, a university with state representation on the Senate committee also has district representation on the House committee in 13% of the observations. For only 6% of these observations, however, is there a member affiliated with the majority party in power on both of the committees at the same time.

With respect to the correlation between district representation and alma mater affiliation, in most instances there is a low correlation (less than 15%) between the universities with an alma mater affiliation and a district representation in the same year. With respect to members on the Senate committee, for approximately 78% of the observations with an alma mater affiliation the university also has a member representing the state in which it is located on the committee at the same time. Thus it is likely that a fair number of these senators have an alma mater affiliation with one of the universities they are representing. A list of universities and their type of alma mater and/or district affiliation is provided in Appendix Table A-1.

Table 1 reports summary statistics on the annual federal research funding to research and doctoral universities during the period studied. (18) Across all 220 universities, the average level of funding is $41 million; the average is higher for private universities. For the universities for which there is at least one year of district representation during the sample period, the average level of funding is $44 million for the years for which there was representation and $45 million for the

years for which there was no representation. This suggests that district representation may not affect the distribution of research funding. For the universities for which there is an alma mater affiliation by a member for at least one year during the sample period, the average level of funding is higher in the years for which there was an affiliation with a member ($71 million) than in the other years ($49 million). This suggests that alma mater affiliation may affect the distribution of research funding.

Table 1 does not take into account two issues. First, it does not reflect that the level of funding allocated for research has varied over time. Second, it does not control for the heterogeneity in the universities receiving the research funding. For example, if one university has a better reputation than another, this could result in that university receiving more in research funding because its faculty submits higher quality proposals. Similarly, if a university has a medical school affiliated with it, the funding allocated to that university may be greater than the funding allocated to a university that does not have a medical school. To address these issues, Figures 1-4 reflect the average level of funding over time to universities in the years in which they have or do not have representation or an alma mater affiliation after controlling for non time-varying differences across the universities. (19) Because the averages are different for the public and private universities in Table 1, the figures depict de·pict  
tr.v. de·pict·ed, de·pict·ing, de·picts
1. To represent in a picture or sculpture.

2. To represent in words; describe. See Synonyms at represent.
 the relationship between representation and nonrepresentation at public and private universities separately.

Figures 1 and 2 depict the average level of funding for those universities that had at least one year of district representation during the sample period. I depict separately the average funding for those years in which there is representation and those years for which there is no representation. With respect to public universities (Figure 1), there is very little difference in the average level of funding based on representation over the sample period. To the extent there is a difference, this is seen in the early part of the period, prior to 1986. Given that earmarking of funding to universities became more prevalent in the latter part of the period, thus representing a more direct way of diverting research funding by Congress, it is interesting that there is little difference between the average funding when there is representation and when there is no representation subsequent to 1986.

With respect to private universities (Figure 2), for most of the sample period there is very little difference in average funding based on representation over the sample period. Subsequent to 1993, however, the gap between average funding for those universities with representation in those years and those universities without representation widens, providing some evidence that district representation may matter.

In Figures 3 and 4, I depict the average level of funding for those universities with an alma mater affiliation during the sample period. As with Table 1, both figures suggest a different relationship between alma mater affiliation and district representation with respect to the distribution of research funding. For the public universities (Figure 3) prior to 1985, the average level of funding is higher for those universities in the years without an affiliation. Between 1985 and 1989, there is very little difference between the average funding when there is and is not an affiliation. Subsequent to 1989, there appears to be a substantial premium for having an alma mater affiliation for most of the years. With respect to the private universities (Figure 4), the average level of funding is higher in the years when there is an alma mater affiliation in the early and later part of the sample, but the gap during these periods is not very big.

V. REGRESSION ANALYSIS In statistics, a mathematical method of modeling the relationships among three or more variables. It is used to predict the value of one variable given the values of the others. For example, a model might estimate sales based on age and gender.  

Table 1 and the figures suggest that alma mater affiliation matters but district representation may not, especially in the early part of the sample. To explore further the effect of committee membership further I use the following model:

(1) [G.sub.irt] = [[alpha].sub.i] + [[lambda].sub.rt] + [R.sub.irt-1][beta] + [delta][A.sub.irt-1] + [tau][O.sub.-rt] + [sigma][I.sub.r-it] + [v.sub.irt],

where G is research funding to university i, located in region r, averaged between years t and t - 1, R is the vector of Senate and House measures indicating whether the university has alma mater affiliation or district representation at time t - 1. (20)

Given that a member may have both a district and an alma mater affiliation, A indicates whether the university has a member with the other type of affiliation at time t - 1. Thus, if we are measuring the effect of an alma mater affiliation, R represents the vector of measures that identify the type of alma mater affiliation and A is a dummy variable This article is not about "dummy variables" as that term is usually understood in mathematics. See free variables and bound variables.

In regression analysis, a dummy variable
 equal to one if the university also has a member that represents the district in which the university is located.

I also include university fixed effects. The university fixed effects control for nontime-varying heterogeneity across the universities. Thus differences across universities (because some receive on average more research funding than others) will be captured by these fixed effects. Because I am including university fixed effects, however, the coefficients on the political measures represent the measurement of a change in committee membership for that university. (21)

I conduct separate analyses to measure the effect of alma mater affiliation and district representation. (22) I include only those universities with an alma mater affiliation during the sample period in the specification that looks at the effects of alma mater affiliation. Similarly, I include only those universities with district representation in the specification that looks at the effects of district representation. Because the specifications include university fixed effects, the coefficients on the political measures reflect changes in the committee composition within the university. Thus including universities that never have an affiliation would just make the estimates less precise because there is no within-university variation for these institutions.

Given that the sample period covers 26 years, one might expect the universities to have grown differently. To account for this, I could interact the university fixed effect with a time trend. This specification would allow universities to grow differently. A potential problem with this specification is if a university's growth includes changes in its relationship with politicians that are correlated cor·re·late  
v. cor·re·lat·ed, cor·re·lat·ing, cor·re·lates

v.tr.
1. To put or bring into causal, complementary, parallel, or reciprocal relation.

2.
 to movement on and off the appropriations committee, then part of the effect of having a member on the appropriations committee will be captured by the university time trend effect. Although these results are not reported in this article, for the most part the conclusions that may be drawn from the specifications that use a university time trend are similar to those reported later; the magnitude of the coefficients, however, decreases.

In equation (1), [lambda] represents a year fixed effect interacted with a set of dummy Sham; make-believe; pretended; imitation. Person who serves in place of another, or who serves until the proper person is named or available to take his place (e.g., dummy corporate directors; dummy owners of real estate).  variables representing the region in which the university is located. This effect helps control for changes in economic, demographic, or political environments across time that affect all universities in a region similarly. Such effects would include changes in the government's budget, changes in attitudes about research funding, macro-level economic changes, and changes in the political party in power in Congress and the executive office. (23)

In addition to these measures, I include measures to control for possible changes in government policy regarding research funding that may affect universities differently as well as to control for the impact of other universities on the actions taken by the university under study. The first measure is the average level of research funding to universities located outside of the region in which a university is located with the same type of ownership (public or private) and Carnegie (1994) classification. The second measure is the average level of research funding to universities located in the region in which a university is located with the same type of Carnegie (1994) classification after excluding the level of funding to the university under study. (24)

There are several ways to depict political affiliation in the regression analysis. I concentrate solely on the politicians serving as general members on the appropriations committees. As discussed above, I concentrate on whether the general member is a chair of one of the subcommittees that have a direct relationship with the agencies primarily responsible for research funding (25) whether the member is affiliated with the majority party in power in Congress, and the tenure of the member. In addition, I allow the affiliation to differ for public and private universities.

Table 2 reports the results from two specifications. The first specification measures congressional representation in the two chambers based on two measures: first, whether there is at least one member that is a chair of one of the key subcommittees, and second, the number of general members serving on the committee. The first measure is designed to capture the effect that Savage (1991) found that chairs of the subcommittees have power to block or to promote pork barrel pork barrel
n. Slang
A government project or appropriation that yields jobs or other benefits to a specific locale and patronage opportunities to its political representative.
 politics. The number of general members serving on the committee ranges from zero to two for the Senate and zero to three for the House.

Column (1) of Table 2 reports the results for the institutions with at least one year of district representation during the sample period. With respect to the Senate, the results suggest that universities benefit from having representation on the committee. On average, having a member that is a chair of a key subcommittee increases average funding by $4.7 million; having a member that serves as a general member increases funding on average by $1.9 million. Thus a university with a member that is also a chair of a key subcommittee would benefit by $6.6 million. Given that average research funding is $41.3 million, this represents a diversion of 16%. The results are different with respect to committee membership in the House of Representatives. The results suggest no effect from having a member that is a chair of a subcommittee and a negative effect from having a general member on the committee. The effect of the university also having an alma mater affiliation is small and imprecisely im·pre·cise  
adj.
Not precise.



impre·cisely adv.
 measured.

In column (6), I report the results for the set of universities with at least one year of alma mater affiliation. These results are very different from the results measuring the effect of district representation. With respect to an alma mater affiliation, the strongest results are with respect to having an affiliation with a member on the House committee. The results suggest that on average having an affiliation with a member who is a chair of one of the key subcommittees increases research funding by $10.2 million and that having an affiliation with a general member increases research funding by $4.9 million. Thus a university having a member that is also a chair of a key subcommittee would benefit by $15.1 million, representing a 37% diversion of funding. With respect to the Senate committee, the results suggest that an affiliation with a committee member decreases funding by $4.4 million. The effect of the university also having a member that represents the district in which the university is located incre ases funding to that university an average of $3.6 million.

The negative coefficients are troubling. In general, any given coefficient coefficient /co·ef·fi·cient/ (ko?ah-fish´int)
1. an expression of the change or effect produced by variation in certain factors, or of the ratio between two different quantities.

2.
 on the member measures should not be viewed in isolation. With respect to the measures reflecting whether the member is on a key subcommittee, this member would also be a general member on the appropriations committee, and thus the coefficient on the subcommittee chair reflects the additional gain from having a member who is a chair. In addition, as discussed in the last section, many universities have members on both the House and Senate committees. Also, for the alma mater sample, most of the universities with a member with an affiliation on the Senate committee also have a member that represents the state in which the university is located. Given that the measures reflecting membership on the committees should not be viewed in isolation, the negative coefficient could reflect that some members have less power than others. Even taking this into account, however, the results still suggest that the net effect may be negative.

In columns (3)-(5) and (8)-(10), I report the number of institutions with a change in representation and the number of changes for the district representation and alma mater affiliation regressions, respectively. For both measures for which the coefficient is negative, there are a fair number of universities and changes in representation, suggesting that the negative coefficients are not a problem associated with a small sample size. Another possible reason for the negative coefficients is that there is a university in the sample that is an outlier outlier /out·li·er/ (out´li-er) an observation so distant from the central mass of the data that it noticeably influences results.

outlier

an extremely high or low value lying beyond the range of the bulk of the data.
 and is driving the results. I have, however, estimated these regression regression, in psychology: see defense mechanism.
regression

In statistics, a process for determining a line or curve that best represents the general trend of a data set.
 several times after excluding groups of universities based on their size, Carnegie (1994) status, and other characteristics. Although the coefficients change based on the sample group used, they do not change dramatically, suggesting that the problem with the negative coefficient is not due to an outlier.

The next reason for a negative coefficient I have explored has to do with whether the member is affiliated with the political party in the majority in the congressional chamber to which the member belongs. In the House of Representatives, the Democratic Party was the majority party from the beginning of the sample period until 1994. In the Senate, the Democratic Party was the majority party from the beginning of the sample period until 1980 and again from 1987 to 1994. Although one would not expect a member that is affiliated with the minority party to negatively affect the distribution of funding to a university, there is likely to be a significant difference between the effect a member can have depending on the political party with whom he or she is affiliated.

In columns (2) and (7), I report the results from the specification that changes the general member measure to one that identifies the number of members that are affiliated with the majority party and adds a third measure, a dummy variable equal to one if at least one member is affiliated with the minority party. The results for both groups of universities change. With respect to district representation, the significance of the subcommittee chair in the Senate is decreased and the coefficient on the majority general member measure is greater than the coefficient when we treat all general members as the same. These results suggest that being a member that is affiliated with the majority party plays a bigger role than being the chair of a key subcommittee. With respect to the House measures, the coefficients on the majority general member and the minority member measures are both negative and statistically significant. Although, it appears there is a different effect based on whether the member is part of the m ajority or minority party, this distinction fails to explain the negative coefficient.

With respect to alma mater affiliation, the results for the general members in the Senate also suggest that having a general member on the committee reduces funding. There is a greater reduction if the member is affiliated with the minority party. In the House, all three coefficients are positive, suggesting that regardless of party affiliation, membership affects the distribution of funding positively.

Despite separating the effects from party affiliation of the members, there are still negative coefficients. One aspect the discussion has not focused on is the fact that in most instances, to receive special treatment from Congress one has to ask for it. In this instance, if the members of Congress are able to influence agency behavior to distort the distribution of funding based on politics, most likely the member exerting the influence was lobbied to do so. If the efforts expended ex·pend  
tr.v. ex·pend·ed, ex·pend·ing, ex·pends
1. To lay out; spend: expending tax revenues on government operations. See Synonyms at spend.

2.
 by the universities toward lobbying are relatively constant, the fixed effects in the empirical specification will control for differences across universities in the efforts expended. The specification, however, does not control for lobbying efforts that change over time. Plausibly plau·si·ble  
adj.
1. Seemingly or apparently valid, likely, or acceptable; credible: a plausible excuse.

2. Giving a deceptive impression of truth or reliability.

3.
, universities might change their lobbying efforts depending on who is in office as well as on the basis of their needs. For example, if a member affiliated with the majority party is replaced by a member that is affiliated with the minority party, a un iversity may choose to reduce its lobbying efforts. Similarly, the seniority of the committee member could affect lobbying efforts. If there is a correlation between lobbying effort and changes in the committee composition (as measured by the political variables), the coefficient on the political measures will capture the effect of both the change in composition and change in lobbying effort. To explore this further, however, we would need more information on the lobbying efforts of universities, as well as by associations that represent certain groups of universities. Until recently this information was not collected; thus, further investigation of this hypothesis will be quite difficult. (26)

The third specification starts with the second but allows the effect of committee membership to vary based on whether the university is public or private. Columns (1a)-(1c) of Table 3 report the results from this specification for the sample of universities with district representation. Interestingly, there are different effects from membership on the committees based on the ownership of the university. Private universities benefit from having a member that is a chair of one of the key subcommittees in both the Senate and the House. Public universities only benefit from members serving on the Senate committee and benefit more from those members that are affiliated with the majority party but are not a chair of one of the key subcommittees. The source of these differences are potentially attributable to differences in lobbying by public and private universities.

Columns (la)-(lc) of Table 4 report the results for the sample of universities with an alma mater affiliation. In the House, both types of universities benefit from having a member on the committee who is also a chair of one of the key subcommittees. Public universities also benefit from having a general member on the committee. In the Senate, the negative coefficient reported in Table 2 is driven by alma mater affiliations by public universities. This latter point raises an interesting question. Given that the universities with an alma mater affiliation with a member on the Senate committee are likely to be in a state also represented by the member, why does this result in a lower amount funding to the public universities than the funding distributed to the public universities that do not have an alma mater affiliation?

The last specification builds on the specification that allows for differences between public and private universities and between members affiliated with the majority and minority parties to study the effects of committee tenure on the distribution of funding. In this specification, I use three groups of measures to reflect the tenure of the members. Each measure identifies the number of majority party members on the appropriations committee based on the number of years the member has been on the committee. The first measure is for those members with 0 to 3 years on the committee, the second measure is for those members with 4 to 11 years on the committee, and the third measure is for those members with more than 11 years on the committee. Given that the preferences of members are likely to vary based on tenure and issues related to seeking reelection, the effects of lobbying and other activities on the actions taken by members are also likely to vary. Similarly, efforts toward seeking favoritism by universi ties may also vary with tenure. For example, if a member is concerned about reelection in the early years, we might see a preference away from shirking and toward representing one's constituents.

Columns (2a)-(2c) of Table 3 report the results with respect to district representation. Interestingly, the distribution of funding is diverted to public and private universities in the early years of committee membership. For public universities, on average, $3.6 million is diverted to universities if the member has less than 4 years of tenure and $2.1 million if the member has between 4 and 10 years of tenure. For private universities, on average, $8.0 million is diverted to universities if the member has less than 4 years of tenure and $10.1 million if the member has between 4 and 10 years of tenure. For both groups of universities, the coefficient for the members with more than 10 years of tenure is small and imprecisely measured. As in the other specifications, the effect in the House is imprecisely measured for the public universities and negative for the private universities. The negative coefficients are stronger for the more senior members.

Columns (2a)-(2c) of Table 4 report the results with respect to alma mater affiliation. For the Senate, the distribution of funding for public and private universities is negatively affected with members that have between 4 and 11 years of tenure. Private universities, however receive a large increase in funding by the members with more than 10 years of tenure. There are, however, only 3 private universities during the sample period with representation at this level. As such, this result should be treated gingerly gin·ger·ly  
adv.
With great care or delicacy; cautiously.

adj.
Cautious; careful.



[Possibly alteration of obsolete French gensor, delicate
. In the House, the distribution of funding to public universities is positively affected by members with more than 3 years of tenure. On average, funding is increased by $5.9 million if the member has between 4 and 11 years of tenure and by $13 million if the member has more than 10 years of tenure. The distribution of funding to private universities is positively affected by members with between 4 and 11 years of tenure. On average, funding is increased by $8.7 million.

All of the tables illustrate that membership on the committee has an effect on the distribution of research funding. Moreover, the characteristics of the politician's membership as well as the ownership of the university affects the average level of funding that is distributed to the university. Focusing first on public universities with district representation, the average effect of representation by a general member serving on the Senate committee is $2.9 million, representing an average diversion of 8%. The effect from representation on the House committee is imprecisely measured. With respect to alma mater affiliation, the average effect of an affiliation on the Senate committee is negative but very close to zero if we take into account that many members with an alma mater affiliation on the Senate committee also represent the university. The average effect in the House of a general member is $5 million, representing an average diversion of 14%. The average effect in the House of a general member that is also a chair of a key subcommittee is $17.4 million, representing an average diversion of 47%. Thus with respect to public universities, it is interesting to note that district representation is important in the Senate and alma mater affiliation is important in the House.

With respect to private universities, district representation has the biggest effect on the distribution of funding by members that are a chair of a key House subcommittee. On average, the effect is $19.1 million, representing an average diversion of 39%. With respect to alma mater affiliation, the biggest effect is by members that are a chair of a key House subcommittee and by members that are affiliated with the minority party in the House. On average, the effect from having an affiliation with a subcommittee chair is $6.6 million, representing an average diversion of 13%. Thus with respect to private universities, there appears to be a stronger effect from alma mater affiliation than district representation. Given that private universities on average are more active than public universities in keeping close ties with its alumni, this result should not be that surprising.

VI. CONCLUSION

This article supports the theoretical literature that Congress and agencies behave strategically. This study suggests that research funding to universities is diverted to and from universities due to politics. Thus this work illustrates that as with any other discretionary program that requires appropriations from Congress, because of lobbying from agencies, research universities, or other entities, research funding may be diverted for political purposes.

This article finds that both alma mater affiliation and district representation of universities matter. With respect to district representation, membership on the Senate committee plays a bigger role than membership on the House committee. The net effect from representation on the Senate committee is approximately $4 million. On average, private universities benefit more from this type of representation than do public universities. The more junior members serving on the committee divert di·vert  
v. di·vert·ed, di·vert·ing, di·verts

v.tr.
1. To turn aside from a course or direction: Traffic was diverted around the scene of the accident.

2.
 more funding for both groups of universities.

With respect to alma mater affiliation, membership on the House committee plays a bigger role than does membership on the Senate committee. The net effect of representation by a general member on the House committee is approximately $4 million. The net effect of representation by a member that is also a chair of one of the subcommittees responsible for the budget of the key agencies involved in research funding is approximately $15 million. On average, public universities benefit more from this type of affiliation than do private universities. More senior members on the committee, however, divert more funding for both groups of universities.

These results illustrate that members can influence the diversion of funding for both his or her constituents and his or her personal interests. In a broader context, this article illustrates the potential problems that develop when members of Congress have a long tenure on a committee. The diversions of funding associated with the more senior members on the committee are biggest for those universities with a personal affiliation (as measured by alma mater status), especially in the House. Thus this article provides further support to the notion that senior members are more susceptible than junior members to shirking. How this shirking compares with the advantage senior members may have on the committee because of their experience with the appropriations process, however, is left for future research.
APPENDIX TABLE A-1

                                            Carnegie
Universities Analyzed                State   Class

University of Alabama                 AL       D1
University of Alabama in Huntsville   AL       D2
University of Alabama at Birmingham   AL       R1
Auburn University                     AL       R2
University of Arkansas                AR       R2
Northern Arizona University           AZ       D1
Arizona State University Main         AZ       R1
University of Arizona                 AZ       R1
Loma Linda University                 CA       D2
Pepperdine University                 CA       D2
San Diego State University            CA       D2
University of San Diego               CA       D2
University of the Francisco           CA       D2
University of the Pacific             CA       D2
California Institute of Technology    CA       R1
Stanford University                   CA       R1
University of California--Berkeley    CA       R1
University of California--Davis       CA       R1
University of California--Irvine      CA       R1
University of California--            CA       R1
Los Angeles
University of California--San Diego   CA       R1
University of California--            CA       R1
San Francisco
University of California--            CA       R1
Santa Barbara
University of Southern California     CA       R1
University of California--Riverside   CA       R2
University of California--            CA       R2
Santa Cruz
University of Denver                  CO       D1
University of Northern Colorado       CO       D1
Colorado School of Mines              CO       D2
Colorado State University             CO       R1
University of Colorado                CO       R1
University of Connecticut             CT       R1
Yale University                       CT       R1
University of Delaware                DE       R2
Florida Institute of Technology       FL       D1
Nova Southeastern University          FL       D1
Florida Atlantic University           FL       D2
Florida International University      FL       D2
University of Central Florida         FL       D2
Florida State University              FL       R1
University of Florida                 FL       R1
University of Miami                   FL       R1
University of South Florida           FL       R2
Georgia State University              GA       D1
Emory University                      GA       R1
Georgia Institute of Technology       GA       R1
University of Georgia                 GA       R1
Iowa State University                 IA       R1
University of Iowa                    IA       R1
Idaho State University                ID       D2
University of Idaho                   ID       R2
Illinois Institute of Technology      IL       D1
Illinois State University             IL       D1
Loyola University of Chicago          IL       D1
Northern Illinois University          IL       D1
De Paul University                    IL       D2
Northeastern University               IL       R1
Mississippi State University          MS       R2
University of Mississippi             MS       R2
Montana State University--Bozeman     MT       D2
University of Montana                 MT       D2
University of North Carolina          NC       D1
 at Greensboro
Wake Forest University                NC       D2
Duke University                       NC       R1
Nort Carolina State University        NC       R1
University of North Carolina at       NC       R1
 Chapel Hill
North Dakota State University         ND       D2
University of North Dakota            ND       D2
University of Nebraska at Lincoln     NE       R1
Dartmouth College                     NH       D2
University of New Hampshire           NH       D2
New Jersey Institute Technology       NJ       D2
Seton Hall University                 NJ       D2
Stevens Institute of Technology       NJ       D2
Princeton University                  NJ       R1
Rutgers the State University of NJ    NJ       R1
New Mexico State University           NM       R1
University of New Mexico              NM       R1
University of Nevada--Reno            NV       D2
Adelphi University                    NY       D1
Fordham University                    NY       D1
Hofstra University                    NY       D1
St. John's University                 NY       D1
Clarkson University                   NY       D2
Columbia University                   NY       R1
Cornell University                    NY       R1
New York University                   NY       R1
Rockefeller University                NY       R1
SUNY at Buffalo                       NY       R1
SUNY at Stony Brook                   NY       R1
Univesity of Rochester                NY       R1
Yeshiva University                    NY       R1
Rensselaer Polytechnic Institute      NY       R2
SUNY at Albany                        NY       R2
Syracuse University                   NY       R2
Bowling Green State University        OH       D1
Miami University                      OH       D1
University of Akron                   OH       D1
University of Toledo                  OH       D1
Cleveland State University            OH       D2
Wright State University               OH       D2
Case Western Reserve University       OH       R1
Ohio State University                 OH       R1
University of Cincinnati              OH       R1
Kent State University                 OH       R2
Ohio University                       OH       R2
University of Tulsa                   OK       D2
Oklahoma State University             OK       R2
University of Oklahoma                OK       R2
Portland State University             OR       D2
Oregon State University               OR       R1
University of Oregon                  OR       R2
Drexel University                     PA       D1
Indiana University of PA              PA       D1
University of Chicago                 IL       R1
University of Illinois at Chicago     IL       R1
University of Illinois                IL       R1
 at Urbana--Champaign
Southern Illinois University          IL       R2
Southern Illinois University--        IL       R2
 Carbondale
Ball State University                 IN       D1
Indiana State University              IN       D2
Indiana University                    IN       R1
Purdue University                     IN       R1
University of Notre Dame              IN       R2
Wichita State University              KS       D2
University of Kansas                  KS       R1
Kansas State University               KS       R2
University of Kentucky                KY       R1
University of Louisville              KY       R2
Louisiana Tech University             LA       D2
University of New Orleans             LA       D2
University of Southwestern            LA       D2
 Louisiana
Louisiana State University            LA       R1
Tulane University                     LA       R1
Boston College                        MA       D1
Clark University                      MA       D2
Worcester Polytechnic Institute       MA       D2
Boston University                     MA       R1
Harvard University                    MA       R1
Massachusetts Institute of            MA       R1
 Technology
Tufts University                      MA       R1
Brandeis University                   MA       R2
Northeastern University               MA       R2
University of Maryland                MD       D2
 Baltimore County
Johns Hopkins University              MD       R1
University of Maryland                MD       R1
 at College Park
University of Maine                   ME       D2
Andrews University                    MI       D1
Western Michigan University           MI       D1
Michigan Technological University     MI       D2
University of Detroit Mercy           MI       D2
Michigan State University             MI       R1
University of Michigan                MI       R1
Wayne State University                MI       R1
University of Minnesota               MN       R1
University of Missouri, Kansas City   MO       D1
University of Missouri, Rolla         MO       D1
University of Missouri, St. Louis     MO       D2
University of Missouri, Columbia      MO       R1
Washington University                 MO       R1
St. Louis University                  MO       R2
University of Southern Mississippi    MS       D1
Allegheny University of               PA       D2
 the Health Sciences
Duquesne University                   PA       D2
Carnegie Mellon University            PA       R1
Pennsylvania State University         PA       R1
Temple University                     PA       R1
University of Pennsylvania            PA       R1
University of Pittsburgh              PA       R1
Lehigh University                     PA       R2
Brown University                      RI       R1
University of Rhode Island            RI       R2
Clemson University                    SC       R2
University of South Carolina          SC       R2
University of South Dakota            SD       D1
University of Memphis                 TN       D1
Middle Tennessee State University     TN       D2
Tennessee State University            TN       D2
University of Tennessee at            TN       R1
 Knoxville
Vanderbilt University                 TN       R1
Southern Methodist University         TX       D1
Texas Woman's University              TX       D1
University of North Texas             TX       D1
University of Texas at Arlington      TX       D1
University of Texas at Dallas         TX       D1
Baylor University                     TX       D2
Texas Christian University            TX       D2
Texas Southern University             TX       D2
Texas A&M University                  TX       R1
University of Texas at Austin         TX       R1
Rice University                       TX       R2
Texas Tech University                 TX       R2
University of Houston                 TX       R2
University of Utah                    UT       R1
Utah State University                 UT       R1
Brigham Young University              UT       R2
College of William and Mary           VA       D1
Old Dominion University               VA       D1
George Mason University               VA       D2
University of Virginia                VA       R1
Virginia Commonwealth University      VA       R1
Virginia Polytechnic Institute        VA       R1
 and State University
University of Vermont                 VT       R2
University of Washington--Seattle     WA       R1
Washington State University           WA       R2
Marquette University                  WI       D1
University of Wisconsin--Madison      WI       R1
University of Wisconsin--Milwaukee    WI       R2
West Virginia University              WV       R1
University of Wyoming                 WY       R2


[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]
TABLE 1

Summary Statistics on Federal Research Funding to Universities

                            # of Observations  Mean   SD   SD/Mean

All universities                 5,671         41.3  65.2    1.6
  Public universities            3,424         37.0  49.9    1.3
  Private universities           1,947         48.9  85.1    1.7
Universities with some
  district representation
District representation          2,634         43.9  72.5    1.7
  Public universities            1,646         39.2  53.7    1.4
  Private universities             988         51.6  95.5    1.8
No district representation       2,027         45.0  62.7    1.4
  Public universities            1,209         40.2  50.5    1.3
  Private universities             818         52.0  76.7    1.5
Universities with some
  alma mater affiliation
Alma mater affiliation             972         71.2  65.3    0.9
  Public universities              663         66.5  65.0    1.0
  Private universities             309         81.2  65.0    0.8
No alma mater affiliation          874         49.1  57.8    1.2
  Public universities              625         39.4  42.3    1.1
  Private universities             249         73.4  80.1    1.1

                            Median  Maximum

All universities             16.5    741.7
  Public universities        17.4    351.1
  Private universities       14.5    741.7
Universities with some
  district representation
District representation      17.3    741.7
  Public universities        17.8    351.1
  Private universities       16.0    741.7
No district representation   18.6    615.9
  Public universities        20.7    301.2
  Private universities       16.7    615.9
Universities with some
  alma mater affiliation
Alma mater affiliation       51.0    351.1
  Public universities        45.8    351.1
  Private universities       63.2    279.9
No alma mater affiliation    25.4    337.6
  Public universities        23.5    233.4
  Private universities       37.4    337.6

Notes: All dollars are reported in millions ($1996). Universities
studied are those with a Carnegie (1994) classification of research or
doctoral universities.

TABLE 2

Regression Analysis District Representation and Alma Mater Affiliation

Dependent Variable: Federal                               District
  Research Expenditures             Universities with  Representation
  (2-Year Average)                         (1)              (2)

Senate appropriations
  At least 1 subcommittee chair           4.68              2.51
                                         (2.07)            (1.89)
  General member                          1.92
                                         (0.80)
  General member in majority party                          4.01
                                                           (0.83)
  Representation in minority party                          0.18
House appropriations
  At least 1 subcommittee chair           3.09              3.29
                                         (2.09)            (2.07)
  General member                         -5.55
                                         (1.45)
  General member in majority party                         -6.49
                                                           (1.75)
  Representation in minority party                         -3.11
                                                           (1.60)
F-test on all political measures         10.38              7.28
(p-value)                                (0.00)            (0.00)
District/alma mater representation        0.74              0.73
                                         (0.95)            (0.95)
Average funding outside of region         0.65              0.64
                                         (0.08)            (0.08)
Average funding within region             0.34              0.34
                                         (0.06)            (0.06)
University fixed effects                   Yes              Yes
Regional year effect                       Yes              Yes
# of observations                         4,227            4,227
# of Schools                               186              186
R-squared                                0.9241            0.9244

Dependent Variable: Federal         # Universities w/  # Changes on
  Research Expenditures              Representation     Committee
  (2-Year Average)                         (3)             (4)

Senate appropriations
  At least 1 subcommittee chair            67              131

  General member                           157             338

  General member in majority party         154             374

  Representation in minority party         141             352
House appropriations
  At least 1 subcommittee chair             4               8

  General member                           82              150

  General member in majority party         64              112

  Representation in minority party         43               62

F-test on all political measures
(p-value)
District/alma mater representation

Average funding outside of region

Average funding within region

University fixed effects
Regional year effect
# of observations
# of Schools
R-squared

Dependent Variable: Federal                            Alma Mater
  Research Expenditures             Universities with  Affiliation
  (2-Year Average)                         (5)             (6)

Senate appropriations
  At least 1 subcommittee chair           0.27           -2.26
                                         (1.87)          (2.05)
  General member                         -4.38
                                         (1.09)
  General member in majority party                       -2.18
                                                         (1.32)
  Representation in minority party                       -6.98
House appropriations
  At least 1 subcommittee chair          10.19           10.51
                                         (2.39)          (2.53)
  General member                          4.85
                                         (0.90)
  General member in majority party                        4.34
                                                         (1.23)
  Representation in minority party                        6.24
                                                         (1.41)
F-test on all political measures         21.35           15.99
(p-value)                                (0.00)          (0.00)
District/alma mater representation        3.60            3.84
                                         (0.87)          (0.87)
Average funding outside of region         0.41            0.41
                                         (0.06)          (0.06)
Average funding within region             0.50            0.50
                                         (0.06)          (0.06)
University fixed effects                   Yes             Yes
Regional year effect                       Yes             Yes
# of observations                         1,678           1,678
# of Schools                               72              72
R-squared                                0.9624          0.9628

Dependent Variable: Federal         # Universities w/  # Changes on
  Research Expenditures              Representation     Committee
  (2-Year Average)                         (7)             (8)

Senate appropriations
  At least 1 subcommittee chair            18               36

  General member                           38               71

  General member in majority party         34               79

  Representation in minority party         29               64
House appropriations
  At least 1 subcommittee chair            10               15

  General member                           53              102

  General member in majority party         44               72

  Representation in minority party         40               69

F-test on all political measures
(p-value)
District/alma mater representation

Average funding outside of region

Average funding within region

University fixed effects
Regional year effect
# of observations
# of Schools
R-squared

Notes: Robust Standard errors in parentheses, except where noted;
General Member = number of members on the appropriations committee,
excluding the majority leader and ranking minority member on the
committee; Average Funding Outside of Region = average federal research
funding for universities with same type of ownership (public or private)
and Carnegie (1994) Classification (Research I, II, Doctoral I, II)
located outside of the region; Average Funding Within Region = Average
federal obligations for universities with same type of Carnegie (1994)
classification located in the same region as the university under study;
Regional Year Effect = dummy variable indicating which region (out of
four) the university under studied is located interacted with a set a of
year dummy variables; the District/Alma Mater Representation: a dummy
variable equal to one if the university under study also has a member on
the committee with an alma mater affiliation if the regression reflects
the effect of representation on the distribution of funding and equal to
one if the university under study also has a member on the committee
representing the district/state in which the university is located if
the regression reflects the effect of an lma mater affiliation on the
distribution of funding. Coefficients in bold indicate p-value < 0.05;
coefficients in italies indicate p-value < 0.10.

TABLE 3

Regression Analysis District Representation: Differences Based on
Ownership of University and Tenure on the Appropriate Committee


Dependent Variable: Federal
Research Expenditures               Public    Private
(2-Year-Average)                      (la)       (1b)

Senate appropriations
  At least 1 subcommittee chair      -2.43      21.63
                                     (1.35)     (6.78)
  General member in majority party    2.94      -2.51
                                     (0.85)     (1.51)
  Representation in minority party              -0.54
                                                (1.30)
  Tenure <4 years

  Tenure 4-11 years

  Tenure 11 + years

House approriations
  At least 1 subcommittee chair       2.54       4.37
                                     (2.99)     (2.01)
  General member in majority party   -1.29      -9.83
                                     (1.15)     (3.12)
  Representation in minority party              -2.55
                                                (1.61)
  Tenure <4 years

  Tenure 4-11 years

  Tenure 11 + years

F-test on all political measures                 4.07
  (p-value)                                     (0.00)
# of Observations                                4,227
# of Schools                                      186
R-squared                                        0.9256


Dependent Variable: Federal         Private = Public
Research Expenditures                    F-test       Public
(2-Year-Average)                          (1c)         (2a)

Senate appropriations
  At least 1 subcommittee chair      11.57
                                     (0.00)
  General member in majority party    0.34
                                     (0.56)
  Representation in minority party

  Tenure <4 years                                      3.60
                                                      (0.96)
  Tenure 4-11 years                                    2.14
                                                      (1.02)
  Tenure 11 + years                                    0.38
                                                      (1.91)
House approriations
  At least 1 subcommittee chair      10.72
                                     (0.00)
  General member in majority party    5.65
                                     (0.02)
  Representation in minority party

  Tenure <4 years                                     -1.74
                                                      (1.69)
  Tenure 4-11 years                                   -1.47
                                                      (1.49)
  Tenure 11 + years                                    2.84
                                                      (2.59)
F-test on all political measures
  (p-value)
# of Observations
# of Schools
R-squared


Dependent Variable: Federal                    Private = Public
Research Expenditures               Private         F-test
(2-Year-Average)                     (2b)            (2c)

Senate appropriations
  At least 1 subcommittee chair

  General member in majority party

  Representation in minority party    -0.44
                                      (1.28)
  Tenure <4 years                      8.02          2.09
                                      (3.12)        (0.15)
  Tenure 4-11 years                   10.13          4.02
                                      (4.06)        (0.05)
  Tenure 11 + years                    0.75          0.02
                                      (2.69)        (0.90)
House approriations
  At least 1 subcommittee chair

  General member in majority party

  Representation in minority party    -3.61
                                      (1.64)
  Tenure <4 years                     -3.62          0.09
                                      (5.19)        (0.76)
  Tenure 4-11 years                  -16.52           .32
                                      (5.70)        (0.02)
  Tenure 11 + years                  -11.39         12.47
                                      (3.14)        (0.00)
F-test on all political measures       3.86
  (p-value)                           (0.00)
# of Observations                      4,227
# of Schools                            186
R-squared                              0.9254

                                    # of Universities with
                                        Representation
Dependent Variable: Federal
Research Expenditures                             Public
(2-Year-Average)                                   (3a)

Senate appropriations
  At least 1 subcommittee chair                      49

  General member in majority party                  102

  Representation in minority party                   85

  Tenure <4 years                                    91

  Tenure 4-11 years                                  83

  Tenure 11 + years                                  34

House approriations
  At least 1 subcommittee chair                       2

  General member in majority party                   31

  Representation in minority party                   24

  Tenure <4 years                                    30

  Tenure 4-11 years                                  20

  Tenure 11 + years                                   8

F-test on all political measures
  (p-value)
# of Observations
# of Schools
R-squared

                                    # of Universities with
                                        Representation
Dependent Variable: Federal                                # changes on
Research Expenditures                             Private   Committee
(2-Year-Average)                                   (3b)        (3c)

Senate appropriations
  At least 1 subcommittee chair                      18        131

  General member in majority party                   52        374

  Representation in minority party                   56        352

  Tenure <4 years                                    48        304

  Tenure 4-11 years                                  42        300

  Tenure 11 + years                                  12         76

House approriations
  At least 1 subcommittee chair                       2         8

  General member in majority party                   35        112

  Representation in minority party                   19         62

  Tenure <4 years                                    32        110

  Tenure 4-11 years                                  22         83

  Tenure 11 + years                                  16         47

F-test on all political measures
  (p-value)
# of Observations
# of Schools
R-squared

Notes: see note on Table 2. In addition, for each regression, the
results are reported over several columns. The tenure measures represent
the number of years serving on the appropriations committee. Although
not reported, all regressions include the same fixed effects and other
control measures reported in Table 2. The coefficients on the control
measures are not different from the coefficients reported in Table 2.

TABLE 4

Regression Analysis Alma Mater Affiliation: Differences Based on
Ownership of University and Tenure on the Appropriations Committee

Dependent Variable: Federal
  Research Expenditures             Public         Private
  (2-Year Average)                   (1a)            (1b)

Senate appropriations
  At least 1 subcommittee chair     -4.85            2.91
                                    (2.52)          (3.64)
  General member in majority party  -2.39           -2.16
                                    (1.84)          (1.47)
  Representation in minority party                  -7.47
                                                    (1.43)
  Tenure <4 years

  Tenure 4-11 years

  Tenure 11+ years

House appropriations
  At least 1 subcommittee chair     12.41            6.61
                                    (3.17)          (3.47)
  General member in majority party   5.01            2.95
                                    (1.46)          (2.43)
  Representation in minority party                   6.12
                                                    (1.42)
  Tenure <4 years

  Tenure 4-11 years

  Tenure 11+ years

F-test on all political measures                    10.93
  (p-value)                                        (0.05)
  # of Observations                             1,678
  # of Schools                                     72
  R-squared                                     0.963

Dependent Variable: Federal         Private=Public
  Research Expenditures                 F-test      Public
  (2-Year Average)                       (1c)        (2a)

Senate appropriations
  At least 1 subcommittee chair          3.02
                                        (0.08)
  General member in majority party       1.46
                                        (0.23)
  Representation in minority party

  Tenure <4 years                                   -2.53
                                                    (1.90)
  Tenure 4-11 years                                 -7.20
                                                    (1.73)
  Tenure 11+ years                                   0.21
                                                    (2.83)
House appropriations
  At least 1 subcommittee chair          0.01
                                        (0.92)
  General member in majority party       0.51
                                        (0.48)
  Representation in minority party

  Tenure <4 years                                    2.00
                                                    (1.67)
  Tenure 4-11 years                                  5.93
                                                    (1.66)
  Tenure 11+ years                                  13.14
                                                    (2.60)
F-test on all political measures
  (p-value)
  # of Observations
  # of Schools
  R-squared

Dependent Variable: Federal                      Private=Public
  Research Expenditures                Private       F-test
  (2-Year Average)                       (2b)         (2c)

Senate appropriations
  At least 1 subcommittee chair

  General member in majority party

  Representation in minority party       -6.22
                                         (1.36)
  Tenure <4 years                         0.55        1.59
                                         (1.58)      (0.21)
  Tenure 4-11 years                      -5.37        0.39
                                         (2.41)      (0.53)
  Tenure 11+ years                       17.56       21.87
                                         (2.59)      (0.00)
House appropriations
  At least 1 subcommittee chair

  General member in majority party

  Representation in minority party        6.71
                                         (1.46)
  Tenure <4 years                         2.39        0.01
                                         (4.07)      (0.93)
  Tenure 4-11 years                       8.67        0.97
                                         (2.14)      (0.33)
  Tenure 11+ years                       -1.53       14.79
                                         (2.77)      (0.00)
F-test on all political measures         13.04
  (p-value)                              (0.00)
  # of Observations                   1,678
  # of Schools                           72
  R-squared                          0.9641

Dependent Variable: Federal           # of Universities
                                     with Representation
  Research Expenditures              Public
  (2-Year Average)                    (3a)

Senate appropriations
  At least 1 subcommittee chair         12

  General member in majority party      24

  Representation in minority party      20

  Tenure <4 years                       22

  Tenure 4-11 years                     20

  Tenure 11+ years                       7

House appropriations
  At least 1 subcommittee chair          7

  General member in majority party      30

  Representation in minority party      26

  Tenure <4 years                       25

  Tenure 4-11 years                     18

  Tenure 11+ years                      14

F-test on all political measures
  (p-value)
  # of Observations
  # of Schools
  R-squared

Dependent Variable: Federal         # of Universities with  # Changes on
                                        Representation
  Research Expenditures             Private                Committee
  (2-Year Average)                    (3b)                   (3c)

Senate appropriations
  At least 1 subcommittee chair        6                      36

  General member in majority party    10                      79

  Representation in minority party     9                      64

  Tenure <4 years                      8                      65

  Tenure 4-11 years                    8                      57

  Tenure 11+ years                     3                      19

House appropriations
  At least 1 subcommittee chair        3                      15

  General member in majority party    14                      72

  Representation in minority party    14                      69

  Tenure <4 years                     12                      72

  Tenure 4-11 years                   10                      61

  Tenure 11+ years                     5                      35

F-test on all political measures
  (p-value)
  # of Observations
  # of Schools
  R-squared

Notes: See note to Table 2. In addition, for each regression, the
results are reported over several columns. The tenure measures represent
the number of years serving on the appropriations committee. Although
not reported, all regressions include the same fixed effects and other
control measures reported in Table 2. The coefficients on the control
measures are not different from the coefficients reported in Table 2.


(1.) Others have studied the effect of politics on the distribution of funding, but only Lichtenberg This article is about the district in Berlin. For other uses, see Lichtenberg (disambiguation).
Lichtenberg is a borough of Berlin, Germany. In 2001, it absorbed the former borough of Hohenschönhausen. Lichtenberg now has an area of 52.
 (1998), Lazear (1996), and Savage (1991) have studied the distribution of research funding. Lichtenberg (1998) studies the allocation process of biomedically funded research, examining the relation between the distribution of funds to research projects and the expected life-years lost associated with the diseases on which the research is being conducted. Lazear (1996) studies the incentives provided by agencies to researchers in the structure of their allocation process. Using an overlapping generations model
For the population genetics model, see Overlapping generations.''
An overlapping generations model, abbreviated to OLG model, is a type of economic model in which agents live a finite length of time and live long enough to endure into at least one
, he examines such questions as what topics should be funded, whether small and large awards should be made, to what extent past research experience should be considered, and whether junior and senior researchers should be treated differently. Savage (1991; 1999) explores issues concerning congressional earmarking of funds to universities, focusing on the relationship between key members on the appropriati ons subcommittees. His study suggests that the chairs of the appropriations subcommittees possess the power to prevent or minimize the extent of pork pork, flesh of swine prepared as food, one of the principal commodities of the meatpacking industry. Pork has long been a staple food in most of the world, although religious taboos have limited its use, especially among Jews and Muslims.  barreling in the appropriations bills with respect to earmarked funding.

(2.) A 1945 government report by Vannevar Bush (person) Vannevar Bush - Dr. Vannevar Bush, 1890-1974. The man who invented hypertext, which he called memex, in the 1930s.

Bush did his undergraduate work at Tufts College, where he later taught.
 recommended the establishment of a single agency that would be responsible for allocating all federal funding appropriations for research. Although the National Science Foundation (NSP (1) (Network Service Provider) An organization that provides a high-speed Internet backbone to ISPs and other service providers. Sprint, MCI and UUNET are examples of NSPs. See Internet backbones. ) was established as a result of the report, it did not become the sole agency responsible for allocating research funding.

(3.) Similar in this vein is the transaction cost framework. Huber and Shipan (2000) provide a discussion of how this framework explains legislative control of bureaucratic bu·reau·crat  
n.
1. An official of a bureaucracy.

2. An official who is rigidly devoted to the details of administrative procedure.



bu
 behavior.

(4.) Feller (2000) provides a complete description of the different methods used to allocate To reserve a resource such as memory or disk. See memory allocation.  federal research funding.

(5.) Savage (1991; 1999) documents and explores the issues surrounding sur·round  
tr.v. sur·round·ed, sur·round·ing, sur·rounds
1. To extend on all sides of simultaneously; encircle.

2. To enclose or confine on all sides so as to bar escape or outside communication.

n.
 earmarked funding.

(6.) Lambright (2000), Payne (2002), and www.epscorfoundation.org See .org.

(networking) org - The top-level domain for organisations or individuals that don't fit any other top-level domain (national, com, edu, or gov). Though many have .org domains, it was never intended to be limited to non-profit organisations.

RFC 1591.
 provide information about set-aside programs.

(7.) One argument against this is if one's constituents are interested in a particular type of research and the best research is being conducted at the member's alma mater institution. For example, if a particular district or state has experienced an epidemic epidemic, outbreak of disease that affects a much greater number of people than is usual for the locality or that spreads to regions where it is ordinarily not present.  of some disease relative to other districts or states, and the best research related to the epidemic is being conducted by a university in another district that happens to be the member's alma mater. Although this scenario is certainly plausible, given the distribution of alma mater affiliated universities and the empirical specification used in this article, the likelihood of this type of phenomenon being the primary explanation of a relationship between alma mater affiliation the distribution of research funding is very low.

(8.) Detailed accounts of the appropriations process may be found in Fenno (1966) and Ferejohn and Krehbiel (1987). A history of the research funding process and the role of the federal government may be found in Drew (1985), Geiger (1993), and Kleinman Kleinman is a common surname:
  • Arthur Kleinman (born 1941), American psychiatrist and medical anthropologist of China
  • Daniel Kleinman, British computer graphics artist
  • Fay Kleinman (born 1912), American painter
  • Pablo Kleinman (born 1971), American journalist
 (1995).

(9.) Although the U.S. Constitution dictates that revenue raising measures must be initiated in the House of Representatives, there is no such provision with respect to the appropriations process.

(10.) Congress, the president, and/or agencies could initiate this influence. The common perception is that a member of Congress may initiate a request for favoritism. Favoritism, however, could be initiated by the agency. Under the assumption that most agencies desire more funds for their activities, one way to "justify" a bigger budget could be through awarding grants to universities affiliated with the members of the appropriations committee. This article does not distinguish between favoritism initiated by members of Congress and favoritism initiated by agencies or other governmental entities. Similarly, universities may or may not seek favoritism from Congress members, either directly or through collective lobbying groups. Savage (1999) discusses reasons why a university may seek favoritism from Congress. Although it is common for a university or group of universities to maintain lobbyists in Washington to keep informed about proposed changes that would affect the operation of their universities, this ar ticle does not distinguish between those universities that actively seek special treatment from those that do not.

(11.) See Dc Figueiredo Figueiredo is a common Portuguese surname, and also the name of many parishes in Portugal. It can also mean:
  • João Batista Figueiredo, the last president of the dictatorial period in Brazil.
  • Paulo José Figueiredo, an Angolan footballer.
 and Silverman Silverman is the surname of:
  • Ben Silverman, an American TV producer
  • Bernard Silverman
  • Beverly Sills (born Silverman)
  • Billy Silverman
  • Brian Silverman, professor
  • Craig Silverman
  • David Silverman, an animator
 (2002) for an analysis of lobbying expenditures by universities and earmarking to universities.

(12.) CASPAR includes several data sets collected by the NSF NSF - National Science Foundation , National Center for Education Statistics, and other federal agencies. Information on CASPAR may be found at www.nsf.gov See .gov and GovNet.

(networking) gov - The top-level domain for US government bodies.
.

(13.) This is due to the fact that there are elections for both chambers every two years. In the House of Representatives, all members must be elected or reelected every two years. In the Senate, one-third of the members are elected or reelected every two years because a given member holds office for six years.

(14.) In some of the larger metropolitan areas, it was difficult to distinguish which members represented which universities. Therefore, I was over-inclusive in assigning as·sign  
tr.v. as·signed, as·sign·ing, as·signs
1. To set apart for a particular purpose; designate: assigned a day for the inspection.

2.
 the universities to representatives. For example, if there is a member on the House appropriations committee that serves a part of Manhattan Manhattan, indigenous people of North America
Manhattan (mănhăt`ən), indigenous people of North America of the Algonquian-Wakashan linguistic stock (see Native American languages).
, then Columbia University Columbia University, mainly in New York City; founded 1754 as King's College by grant of King George II; first college in New York City, fifth oldest in the United States; one of the eight Ivy League institutions.  and NYU NYU New York University
NYU New York Undercover (TV show) 
 university (and all other universities located in Manhattan) would be treated as part of the member's district.

(15.) I do not look at the effect of being a minority or majority chair of the entire committee because during the sample period, there are few changes in these positions, thus providing little variation in the data analysis.

(16.) Research universities are defined as those that give high priority to research and award at least 50 doctoral degrees each year. Doctoral universities differ from research universities in that they do not meet minimum requirements with respect to federal research support or the number of doctorate degrees awarded. Though there are universities that have obtained the research or doctoral institution status subsequent to 1972, there is little or no attrition Attrition

The reduction in staff and employees in a company through normal means, such as retirement and resignation. This is natural in any business and industry.

Notes:
 of universities from these classifications.

(17.) I excluded the following universities from my analysis because of inconsistencies in the data: City University of New York The City University of New York (CUNY; acronym: IPA pronunciation: [kjuni]), is the public university system of New York City. , International College, SUNY SUNY - State University of New York  College of the Environment and Forestry, United States United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area.  International University, University of Massachusetts The system includes UMass Amherst, UMass Boston, UMass Dartmouth (affiliated with Cape Cod Community College), UMass Lowell, and the UMass Medical School. It also has an online school called UMassOnline.  at Amherst, Texas Amherst is a city in Lamb County, Texas, United States. The population was 791 at the 2000 census. Geography
Amherst is located at  (34.012515, -102.414424)GR1.
 A&M at Commerce, Claremont Colleges Claremont Colleges, at Claremont, Calif.; including five liberal arts and sciences colleges and two graduate schools; founded 1925, known until 1961 as the Associated Colleges at Claremont. Their history began with Pomona College (inc. , New School for Social Research New School for Social Research: see New School Univ. , Clark Atlanta University Clark Atlanta University (CAU) is a prestigious, private institution of higher education in Atlanta, Georgia. It is an historically black university formed in 1988 by the consolidation of Clark College (est. 1869) and Atlanta University (est. 1865). , Polytechnic University
  • Polytechnic University located in Brooklyn, NY
  • The Hong Kong Polytechnic University located in Kowloon, Hong Kong
  • Institute of technology is an institution focused on technology
, University of Massachusetts at Lowell Lowell, city (1990 pop. 103,439), a seat of Middlesex co., NE Mass., at the confluence of the Merrimack and Concord rivers; settled 1653, set off from Chelmsford 1826, inc. as a city 1836. , Pace University, Biola University History
Originally located in downtown Los Angeles at the corner of Sixth St. and Hope St., the university moved south to its present location in suburban La Mirada, California, in 1959.
, Union Institute, and University of Laverne Laverne can refer to:
  • Marc Laverne, Communist revolutionary and one of the founding militants of the International Communist Current
  • Lauren Laverne, English disc jockey and television presenter
  • One of the eponymous characters in the television series
.

(18.) All dollar amounts are reported in 1996 dollars. I use the higher education deflation deflation: see inflation.
deflation

Contraction in the volume of available money or credit that results in a general decline in prices. A less extreme condition is known as disinflation.
 index provided by CASPAR.

(19.) To get this measure, I ran a fixed-effects regression whereby I use a set of dummy variables that identify the university to allow for the average level of funding at each university to vary based on the nontime-varying differences. I then graph the average of the residuals of this regression. Thus, the residuals will capture aspects of the funding distributed to the universities that are not accounted for in the university fixed effects.

(20.) Because a research grant may be awarded in one year but then be distributed over several years, I average the funding over a two-year period to reflect this. The results, however, do not differ dramatically based on whether I do a two-year average, a three-year average, or do not average the data. I report the results from the two-year average because the standard errors are smaller with the average than when I do not average the research funding.

(21.) If fixed effects are not included in the regression, the results suggest a very strong affiliation between membership on the appropriations committee and alma mater or district representation.

(22.) One potential issue concerns the correlation between the alma mater and the district political measures. If many of the observations contain both alma mater and district representation then the coefficients may not be interpretable because of multicollinearity.

(23.) The following states are covered within each region. Region 1: Connecticut Connecticut, state, United States
Connecticut (kənĕt`ĭkət), southernmost of the New England states of the NE United States. It is bordered by Massachusetts (N), Rhode Island (E), Long Island Sound (S), and New York (W).
, Massachusetts, Maine, New Hampshire New Hampshire, one of the New England states of the NE United States. It is bordered by Massachusetts (S), Vermont, with the Connecticut R. forming the boundary (W), the Canadian province of Quebec (NW), and Maine and a short strip of the Atlantic Ocean (E). , Rhode Island Rhode Island, island, United States
Rhode Island, island, 15 mi (24 km) long and 5 mi (8 km) wide, S R.I., at the entrance to Narragansett Bay. It is the largest island in the state, with steep cliffs and excellent beaches.
, Vermont Vermont (vərmŏnt`) [Fr.,=green mountain], New England state of the NE United States. It is bordered by New Hampshire, across the Connecticut R. , New Jersey, New York New York, state, United States
New York, Middle Atlantic state of the United States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of
, and Pennsylvania Pennsylvania (pĕnsəlvā`nyə), one of the Middle Atlantic states of the United States. It is bordered by New Jersey, across the Delaware River (E), Delaware (SE), Maryland (S), West Virginia (SW), Ohio (W), and Lake Erie and New York . Region 2: Illinois Illinois, river, United States
Illinois, river, 273 mi (439 km) long, formed by the confluence of the Des Plaines and Kankakee rivers, NE Ill., and flowing SW to the Mississippi at Grafton, Ill. It is an important commercial and recreational waterway.
, Indiana Indiana, state, United States
Indiana, midwestern state in the N central United States. It is bordered by Lake Michigan and the state of Michigan (N), Ohio (E), Kentucky, across the Ohio R. (S), and Illinois (W).
, Michigan Michigan (mĭsh`ĭgən), upper midwestern state of the United States. It consists of two peninsulas thrusting into the Great Lakes and has borders with Ohio and Indiana (S), Wisconsin (W), and the Canadian province of Ontario (N,E). , Ohio, Wisconsin Wisconsin, state, United States
Wisconsin (wĭskŏn`sən, –sĭn), upper midwestern state of the United States. It is bounded by Lake Superior and the Upper Peninsula of Michigan, from which it is divided by the Menominee
, Iowa, Kansas, Minnesota Minnesota, state, United States
Minnesota (mĭn'ĭsō`tə), upper midwestern state of the United States. It is bordered by Lake Superior and Wisconsin (E), Iowa (S), South Dakota and North Dakota (W), and the Canadian provinces
, Missouri Missouri, state, United States
Missouri (mĭzr`ē, –ə), one of the midwestern states of the United States.
, North Dakota North Dakota, state in the N central United States. It is bordered by Minnesota, across the Red River of the North (E), South Dakota (S), Montana (W), and the Canadian provinces of Saskatchewan and Manitoba (N). , Nebraska Nebraska (nəbrăs`kə), Great Plains state of the central United States. It is bordered by Iowa and Missouri, across the Missouri R. (E), Kansas (S), Colorado (SW), Wyoming (NW), and South Dakota (N). , and South Dakota South Dakota (dəkō`tə), state in the N central United States. It is bordered by North Dakota (N), Minnesota and Iowa (E), Nebraska (S), and Wyoming and Montana (W). . Region 3: Delaware Delaware, state, United States
Delaware (dĕl`əwâr, –wər), one of the Middle Atlantic states of the United States, the country's second smallest state (after Rhode Island).
, Florida, Georgia Georgia, country, Asia
Georgia (jôr`jə), Georgian Sakartvelo, Rus. Gruziya, officially Republic of Georgia, republic (2005 est. pop. 4,677,000), c.26,900 sq mi (69,700 sq km), in W Transcaucasia.
, Maryland Maryland (mâr`ələnd), one of the Middle Atlantic states of the United States. It is bounded by Delaware and the Atlantic Ocean (E), the District of Columbia (S), Virginia and West Virginia (S, W), and Pennsylvania (N). , North Carolina North Carolina, state in the SE United States. It is bordered by the Atlantic Ocean (E), South Carolina and Georgia (S), Tennessee (W), and Virginia (N). Facts and Figures


Area, 52,586 sq mi (136,198 sq km). Pop.
, South Carolina South Carolina, state of the SE United States. It is bordered by North Carolina (N), the Atlantic Ocean (SE), and Georgia (SW). Facts and Figures


Area, 31,055 sq mi (80,432 sq km). Pop. (2000) 4,012,012, a 15.
, Virginia Virginia, state, United States
Virginia, state of the south-central United States. It is bordered by the Atlantic Ocean (E), North Carolina and Tennessee (S), Kentucky and West Virginia (W), and Maryland and the District of Columbia (N and NE).
, West Virginia West Virginia, E central state of the United States. It is bordered by Pennsylvania and Maryland (N), Virginia (E and S), and Kentucky and, across the Ohio R., Ohio (W). Facts and Figures


Area, 24,181 sq mi (62,629 sq km). Pop.
, Alabama, Kentucky Kentucky, state, United States
Kentucky (kəntŭk`ē, kĭn–), one of the so-called border states of the S central United States. It is bordered by West Virginia and Virginia (E); Tennessee (S); the Mississippi R.
, Mississippi Mississippi, state, United States
Mississippi (mĭs'əsĭp`ē), one of the Deep South states of the United States. It is bordered by Alabama (E), the Gulf of Mexico (S), Arkansas and Louisiana, with most of the border formed by
, Tennessee Tennessee, state, United States
Tennessee (tĕn`əsē', tĕn'əsē`), state in the south-central United States.
, Arkansas Arkansas, river, United States
Arkansas (ärkăn`zəs, är`kənsô'), river, c.1,450 mi (2,330 km) long, rising in the Rocky Mts., central Colo.
, Louisiana Louisiana (ləwē'zēăn`ə, lē'–), state in the S central United States. It is bounded by Mississippi, with the Mississippi R. , Oklahoma, and Texas. Region 4: Arizona Arizona (âr'əzō`nə), state in the southwestern United States. It is bordered by Utah (N), New Mexico (E), Mexico (S), and, across the Colorado R., Nevada and California (W). , Colorado, Idaho, Montana, New Mexico New Mexico, state in the SW United States. At its northwestern corner are the so-called Four Corners, where Colorado, New Mexico, Arizona, and Utah meet at right angles; New Mexico is also bordered by Oklahoma (NE), Texas (E, S), and Mexico (S). , Nevada, Utah, Wyoming, California California (kăl'ĭfôr`nyə), most populous state in the United States, located in the Far West; bordered by Oregon (N), Nevada and, across the Colorado River, Arizona (E), Mexico (S), and the Pacific Ocean (W). , Oregon Oregon, city, United States
Oregon, city (1990 pop. 18,334), Lucas co., NW Ohio, a suburb adjacent to Toledo, on Lake Erie; inc. 1958. It is a port with railroad-owned and -operated docks. The city has industries producing oil, chemicals, and metal products.
, and Washington.

(24.) By including these measures in the specification, the coefficients--in particular those on the alma mater measures decrease--suggesting these additional measures are picking up a time-varying measure that is correlated with research funding and the political measures.

(25.) NSF, National Institutes of Health, Department of Defense, and Department of Agriculture.

(26.) See De Figueiredo and Silverman (2002).

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RELATED ARTICLE: ABBREVIATIONS

CASPAR: Computer Aided Science Policy Analysis and Research

NSF: National Science Foundation

A. ABIGAIL PAYNE *

* I would like to thank Marie Rekkas, Patti Tilson, Gordon Davis, and Max Hollett for excellent research assistance. I also thank Tom Carsey, James Klukinski, Therese MeGuire, Angelo Melino, Barry Rundquist, James Savage, Aloysius Siow, and participants of the University of Toronto's SWEAT workshop for comments on earlier drafts. This article was funded through grants from the Andrew W. Mellon Foundation The Andrew W. Mellon Foundation is a foundation endowed with wealth accumulated by the late Andrew W. Mellon. It is the product of the 1969 merger of the Avalon Foundation and the Old Dominion Foundation.  and the Social Sciences and Humanities Research Council of Canada The Social Sciences and Humanities Research Council of Canada (French: (le) conseil de recherches en sciences humaine en Canada) (SSHRC/CRSH) is a Canadian federal agency which supports university-based training and research and training in the humanities and social .

Payne: Assistant Professor, University of Illinois, and Associate Professor, Department of Economics, McMaster University McMaster University, at Hamilton, Ont., Canada; nondenominational; founded 1887. It has faculties of humanities, science, social sciences, business, engineering, and health sciences, as well as a school of graduate studies and a divinity college. , 1280 Main St. W, KTH KTH - Kungliga Tekniska Högskolan  426,Hamilton Hamilton, city, Bermuda
Hamilton, city (1990 est. pop. 3,100), capital of Bermuda, on Bermuda Island. It is a port at the head of Great Sound, a huge lagoon and deepwater harbor protected by coral reefs.
, ON L8S 4M4, Canada. Phone 1-905-529-9140 ext 23814, Fax 1-905-521-8232, E-mail paynea@mcmaster.ca
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