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During the 2008 election season, politicians from both sides of the aisle promised to rid government of lobbyists’ undue influence. For the authors of Lobbying and Policy Change, the most extensive study ever done on the topic, these promises ring hollow—not because politicians fail to keep them but because lobbies are far less influential than political rhetoric suggests. Based on a comprehensive examination of ninety-eight issues, this volume demonstrates that sixty percent of recent lobbying campaigns failed to change policy despite millions of dollars spent trying. Why? The authors find that resources explain less than five percent of the difference between successful and unsuccessful efforts. Moreover, they show, these attempts must overcome an entrenched Washington system with a tremendous bias in favor of the status quo. Though elected officials and existing policies carry more weight, lobbies have an impact too, and when advocates for a given issue finally succeed, policy tends to change significantly. The authors argue, however, that the lobbying community so strongly reflects elite interests that it will not fundamentally alter the balance of power unless its makeup shifts dramatically in favor of average Americans’ concerns.
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Lobbying and Policy Change: Who
Wins, Who Loses, and Why
Frank R. Baumgartner
Richard J. Richardson Distinguished Professor
of Political Science, UNC-CH
Presentation to Department of Public Policy
October 2, 2009
A Collaborative Project
Jeff Berry, Tufts
Marie Hojnacki, Penn State
David Kimball, University of Missouri, St. Louis
Beth Leech, Rutgers
A Looong project:
NSF grants SBR-9905159 and SES-0111224
Our web site: http://lobby.la.psu.edu
Book just published, University of Chicago
Press
Lobbying and Policy Change
98 issues, a random sample of the objects of
lobbying activity in the federal government
•214 “sides” identified across the 98 issues
•2,221 “advocates” important players
40 percent are government officials
60 percent are outside lobbyists: corporations, etc.
315 interviews, from leadership of the sides
106th (Clinton) and 107th (Bush) Congresses,
1999-2002
Secondary Data Collection
Laws, bills, congressional statements, hearing
testimonies agency rules, proposals…
News and TV stories
Press releases and organizational statements
from interest-group web sites (you’d be surprised
what is there…)
A comprehensive search for each of 98 issues
All documents are archived on our web site
•(Can be used for teaching as well as research…)
http://lobby.la.psu.edu
The Basics
There is always a status quo policy
The issues are tremendously complex
Sides are surprisingly heterogeneous
The structure of conflict is surprisingly simple
Salience is typically low (but skewed)
Change is rare but substantial, consistent with
punctuated equilibrium theory
There is always a professional community surrounding
the policy a very knowledgeable one
•“Knowledge-induced equilibrium” – reframing is hard!
Typical outcome after 4 years: No change
My Focus Today: Money
Other topics we focus on in the book:
•How hard is it to “reframe” a debate?
Why is the structure of conflict so simple?
Does the Poole-Rosenthal low dimensionality finding,
which we confirm, stem from institutional design, or is
it a broader characteristic of policy communities
surrounding various public policies?
Do elections change many policy issues?
Is issue-salience endogenous or exogenous?
•Attention scarcity (apathy, other priorities) v. “conflict
A Misguided Literature
Baumgartner and Leech (1998) noted the
contradictory nature of research into the effects of
money on policy outcomes.
Contradictory literature based on case studies
But we think a logical flaw as well:
Mobilizational bias is already reflected in the SQ.
Lobbying is about changing the status quo, which is a
different question.
Therefore, we expect no relation between lobbying
activities and outcomes.
Level v. Change Models
Lobbying is about changing public policy, not
establishing it from scratch
Virtually all the literature sets up the question as one
between lobbying resources and policy benefits, as if
there were no status quo in place
Efforts to change policy start with a status quo that
already reflects the distribution of power
If the wealthy wanted something, they should already
have achieved it in a previous round of the policy
process
No prediction for the relation between power and
changes to the status quo
Assume Power = Policy
Assume for the sake of argument that public policy is a simple
result of the mobilization of power, plus some random
component:
Policy = Power + E
It follows, then, that:
Change in Policy = Change in Power + E
If change in power is zero, as it would be during any relatively
short time period, then:
Change in Policy = E
That is, it should be random.
Adding in stochastic “disturbances” should also be random.
Long term mobilization of new interests should indeed lead to
changes in policy. But only in the long-term.
An Illustration using Exchange Rates
If a market is extremely efficient, all new
information should be immediately
incorporated into the trades.
Step one, look at levels
Step two, calculate percent changes
Step three, look at the distribution of changes
Efficient Market Thesis: Random walk >
Normal Distribution
Daily LEVEL of the Euro against the
Dollar, Jan 99 to Nov 08
Daily PERCENT CHANGE
Distribution of Percent Changes is
virtually random
Is this Professor Crazy?
Proposal: no linkage between the lobbying
resources brought to bear in DC and policy
outcomes.
Evidence: A random sample of the objects of
lobbying, including exhaustive searches for
participant resources.
Lets turn to that evidence now.
Issues by Topic Area: The Lobbying Agenda
Topic Frequency
Health 21
Environment 13
Transportation 8
Banking, Finance, and Commerce 7
Defense and National Security 7
Science, Technology, and Communication 7
Foreign Trade 6
Education 5
Energy 5
Law, Crime, and Family Policy 5
Government Operations 3
Labor, Employment, Immigration 3
Community Development and Housing 2
Macroeconomics and Taxation 2
Social Welfare 2
Agriculture 1
International Affairs and Foreign Aid 1
Total 98
Topic areas are based on the coding scheme used in the Policy Agendas Project (www.policyagendas.org).
Table 11.1 Summary of Policy Outcomes
Policy outcome Initial
2-year cycle Subsequent
2-year cycle
No change (status quo) 68 58
Modest policy change 13 13
Significant policy change 17 27
Number of issues 98 98
Interest Group Advocates
33
14
26
21
15
11
15
26
5645
1
16
0
10
20
30
40
Percent in Sample
CorporationsTradeProfessional
Citizen groups
Unions
Govt. associations
Other
Issue identifiers Major participants
Policy “Sides”
A Side: set of advocates pursuing the same policy
goal
10 major participants on a side, on average
214 sides in our study
130 pursuing policy change
84 defending the status quo
16 issues had just one side
60 issues had two opposing sides
22 issues had three or more sides
This simplicity of mobilization contrasts with the
substantive complexity of the policy issues discussed
Which side won? A simple question.
Measuring Material Resources
For every lobbying organization, we looked up:
Total campaign contributions (hard and soft)
Total lobbying expenditures
Number of in-house lobbyists
Number of contract lobbyists
Number of “covered officials”
Number of issue areas on which they lobby
Organizational resources (index of budget, staff,
assets, and income)
Business resources (index of sales, income,
employees)
Reliability measure (alpha): advocates (.75), sides (.92)
Resources of Advocates and Sides
Sides: Organizations sharing the same policy
goal
Simple idea: Compare the total resources
controlled by the advocates on each side, and
see which side got more of what they wanted
Simple question: Do the wealthy win?
Distribution of Advocate Resources
PhRMA
ACT UP
0
100 200 300 400
Number of advocates
-1 0 1 2
Advocate resource index
N = 1243 non-governmental advocates
Do the Wealthy Lobby with Wealthy Allies?
Control of resources by individual lobbying organizations is
highly skewed
(We expect to win no prize for this finding…)
An Open Question: Do the wealthy lobby with wealthy allies? Or are
the sides active on our sample of issues relatively heterogeneous?
If policy were: a) uni-dimensional or b) created from a blank slate, we
might expect the sides to be homogeneous
But policies are highly complex, affecting diverse constituencies.
Efforts to change established policies may attract diverse
constituencies and also mobilize into action diverse constituencies who
may be worried about the effects of such changes
All members of a side, by definition, will achieve the same outcome
Therefore, if the sides are diverse with respect to control of resources,
resources cannot, mathematically, be related to outcomes
Correlations among control of various resources and the
aggregate resources controlled by one’s allies
Annual Sales+
Annual Income+
.26*
.24*
Number of Employees+
Lobbying Expenditures+^
.23*
.16*
Number of Former Officials Lobbying+^
PAC Contributions+^
.13*
.22*
Membership Size^
Organizational Assets^
.05
.11*
Annual Budget^
Total Staff Size^
.13*
.22*
Index of Organizational Resources^
Index of Corporate Resources+
.14*
.30*
N = 1,258 * p < .01 + measure available for corporations ^ measure
available for organizations
Distribution of Resources per Advocate
PhRMA
ACT UP
0
100 200 300 400
Number of advocates
-1 0 1 2
Advocate resource index
N = 1243 non-governmental advocates
Distribution of Resources per Side
Against compulsory licensing
For compulsory licensing
020 40 60
Number of sides
-6 -4 -2 0 2
Comparative resource advantage
N = 214 policy sides
Resources for Change vs. Status Quo
-1 01234
Resources Supporting the Status Quo
-1 0 1 2 3 4
Resources for Policy Change
45-degree line superimposed on graph
N = 80 issues; Pearson's r = 0.44
Correlations with Policy Success
Number of members in the side (size)
.10
Number of Fortune Power 25 Members
-.02
Resource Index Score
.08
N = 214 sides
None of the correlations is statistically significant
Resources Mobilized in 48 Cases where the
Status Quo Remained in Place
0
2
4
6
Resources Supporting the Status Quo
0 1 2 3 4 5
Resources for Policy Change
Resources Mobilized in 32 Cases where Change
Occurred
Government Allies Matter More
than Material Resources
Type of Resource
Percent of Issues
where the Wealthier
Side Won
Number
of Issues
High-level Government Allies
Number of Covered Officials
Mid-Level Government Allies
Business Financial Resources Index
Lobbying Expenditures
Association Financial Resources Index
Campaign Contributions
Membership
78*
63*
60*
53
52
50
50
50
23
35
48
34
58
58
58
58
P< .01
Cell entries show the percent of the issues in which the side with the greatest
control of that resource achieved its policy goal. N’s vary because cases are included only
if at least one of the sides controlled the resource in question, there was no tie, and there
was an opposing side.
An Ordinal Logit Model of Success in
Protecting The Status Quo
Independent Variables
Policy success
after two years
Policy success
after four years
Comparative resource advantage for status quo
1.24**
(.50)
.64#
(.39)
Mid-level government allies defending status quo
.34#
(.20)
.28#
(.16)
Executive branch promoting policy change
-3.10**
(.89)
-1.61*
(.65)
Members of Congress promoting policy change
.22
(.73)
.51
(.59)
Organized interests promoting change
.37
(1.00)
.32
(.82)
Other obstacles to status quo position
-.52
(.47)
-.65
(.42)
N
R2
63
.29
63
.16
Interpreting the Coefficients
A. Protecting the Status Quo:
Resource Advantage Likelihood of Success
20th percentile .76
80th percentile .94
Administration actively seeking change?
Yes .29
No .88
(All other variables at their means/medians)
An Ordinal Logit Model for Success
in Challenging the Status Quo
Independent Variables
Policy success
after two years
Policy success
after four years
Comparative resource advantage for challengers
.54*
(.30)
.02
(.22)
Mid-level government allies promoting policy
change
.02
(.08)
.09
(.08)
Executive branch opposition to policy change
-1.88*
(.84)
-1.01#
(.62)
Members of Congress opposed to policy change
.57
(.52)
.46
(.47)
Organized interests opposing policy change
Lack of attention
.21
(.57)
.90
(.54)
-.16
(.52)
.42
(.48)
Other obstacles to policy change
-.32
(.25)
.02
(.21)
N
R2
107
.09
107
.04
Interpreting the Coefficients
B. Changing the Status Quo:
Resource Advantage Likelihood of Success
20th percentile .17
80th percentile .32
Administration actively opposed?
Yes .06
No .24
(All other variables at their means/medians)
These models don’t work very well
Comparative resource advantage helps, but is not
overwhelming
Policy success does not go to the wealthiest lobbyists
They fight within heterogeneous teams
Government officials themselves play a key role
The position of the President matters
Policy stability is the norm, so lobbying comes to a
stand-still, protecting the status quo
However, 42 percent of the cases led to change
When change occurred it was usually substantial
Our Concerns about Lobbying may
be Misplaced
Mobilization of bias is probably a more serious
problem for democratic representation than the
actions of lobbyists themselves
The bias is not that the wealthy lobbyists defeat
the poorer coalitions; we have shown that
Rather, the lobbying community does not reflect
Americans’ values:
The Concerns of Lobbyists v. the
Concerns of the Public
0 5 10 15 20 25 30
Law, Crime, and Family Policy
Macroeconomics and Taxation
International Affairs and Foreign Aid
Education
Health
Social Welfare
Government Operations
Defense and National Security
Civil Rights
Environment
Energy
Labor, Employment, Immigration
Science, Technology, and Communication
Transportation
Banking, Finance, and Commerce
Foreign Trade
Community Development and Housing
Agriculture
Public Lands and Interior Affairs
Lobbying
MIP
Figure shows the percentage of lobbying by issue area compared to answers to the
Gallup question: What is the most important problem facing the country today?
Totally confused?
-Don’t buy the argument that change
models aren’t the same as level models?
-Think the literature’s supposition that
money buys power is correct, but all
previous studies have been flawed by
research design, explaining mixed
results?
Ask a question now or email me at:
Frankb@unc.edu
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Techniques of modern lobbying provide organized interests a variety of tactical options. How does the mix of tactics employed by groups vary across different lobbying campaigns? When, and why, will groups use some tactics and not others? Prior research points to organizational structure and resources, features of the issue, and institutional forces as crucial determinants of lobbying. We analyze patterns of advocacy using data from a survey of interest groups about their activities on 15 federal nominations for judicial and related offices considered by the U.S. Senate from 1984 through 1991. We find that the overall amount of advocacy varies across nominations according to the importance of the office, as do the types of organizations involved—but lobbying tactics do not. We also find that organizational resources have some effects on the use of some tactics, but overall these effects are quite limited. Organizations of all types engage in multiple, often disparate, tactics. The absence of strong organizational constraints helps to account for the regularities we observe across lobbying campaigns.
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“Winnowing” is the pre-floor process by which Congress determines the small percentage of bills that will receive committee attention. The vast majority of proposals languish in this vital agenda-setting stage, yet our understanding of winnowing is nascent. Why do some bills move forward while most fail? I examine that question here by developing and testing a theoretical framework of winnowing grounded in bounded rationality, which includes institutional and sponsor cues and also incorporates the unique issue milieu. A heteroskedastic probit model is utilized to analyze the winnowing fate of all bills introduced across five issue areas in the House and Senate from 1991 to 1998. The findings counter much received wisdom and suggest that the process is indeed cue based. The majority party helps structure this critical process in both chambers, though party effects appear stronger in the House. Contrary to recent work on the rise of Senate individualism, the seniority of the sponsor has significant effects in both the Senate and House, but again exhibits a stronger effect in the House. Surprisingly, presidential proposals are no more likely to survive than typical bills. The findings further suggest that the entrepreneurial efforts of bill sponsors breathe life into this process.