This is a graduate course and students will be expected to research and write papers summarizing in their own words what they have found on current topics from the weekly readings. Research is a theoretical review of relevant literature and application of findings in the literature to a topic related to a specific industry, field, or business problem.
The research must be conducted using peer-reviewed trade or academic journals. While Blogs, Wikipedia, encyclopedias, course textbooks, popular magazines, newspaper articles, online websites, etc. are helpful for providing background information, these resources are NOT suitable resources for this research assignment.
Please Note: The UC Library staff are very helpful with assisting students in using the UC Online Library journal database. Please contact them if you have issues. In addition, the instructor has provided additional resources, including a research tutorial, in the “Course Resources” folder in the “Content” area of the course.
Assignment Requirements:
Choose a research topic from the chapter readings.
Research/find a minimum at least four (4), preferably five (5) or more, different peer-reviewed articles on your topic from the University of the Cumberlands Library online business database. The article(s) must be relevant and from a peer-reviewed source. While you may use relevant articles from any time frame, current/published within the last five (5) years are preferred. Using literature that is irrelevant or unrelated to the chosen topic will result in a point reduction.).
Business & Society
Ethics, Sustainability & Stakeholder
Management
10th Edition
© 2018 Cengage
1
Chapter 11
Business,
Government,
and Regulation
© 2018 Cengage
2
Learning Outcomes
1. Articulate a brief history of the changing nature of the
government’s role in its relationship with business.
2. Appreciate the complex roles of government and business.
3. Identify the elements in the complex interactions among
business, government, and the public.
4. Identify and describe the government’s nonregulatory
influences, especially the concepts of industrial policy and
privatization.
5. Identify and describe the government’s regulatory influences
on business including the major reasons for regulation, the
types of regulation, and issues arising out of deregulation.
© 2018 Cengage
3
Chapter Outline
• The Pendulum of Government’s Role in Business
• The Roles of Government and Business
• Interaction of Business, Government, and the Public
• Government’s Nonregulatory Influence on Business
• Government’s Regulatory Influences on Business
• Deregulation
• Summary
• Key Terms
© 2018 Cengage
4
Business, Government,
and Regulation
Last decade swung the pendulum of
government involvement in business from
minimal to major player.
The relationship of government to business is
one of the most hotly debated issues
today.
Business and government need each other –
government is a major stakeholder with
which business must establish an effective
working relationship to prosper.
© 2018 Cengage
5
The Pendulum of
Government’s Role in Business
The areas in which government regulates change,
and its varying roles increase the complexity
of its relationship with business. Government
can:
•
•
•
•
Determine the rules of the game
Be a major purchaser with buying power that
can affect a business’s or industry’s chances of
survival
Strengthen some businesses and weaken
others
Create new businesses and industries through
subsidization and privatization
© 2018 Cengage
6
The Roles of
Government and Business
For effective management, government’s role as a
stakeholder must be understood.
What should be the respective roles of business and
government in our socioeconomic system?
If the role of business were simply production and
distribution of goods and services, business would
need little regulation.
But other goals exist—safe working environment,
equal employment opportunities, fair pay, clean
air, safe products—which business does not
automatically factor into the business decision
making process.
As a result, it falls to government to ensure those
goals are achieved.
© 2018 Cengage
7
A Clash of Ethical Systems
Business Beliefs
Government Beliefs
Individualistic ethic
Collectivistic ethic
Maximizes concession to
self-interest
Subordinates individual
goals and self-interest to
group goals and group
interests
Minimizing the load of
obligations society
imposes on the individual
(personal freedom)
Maximizing obligations
assumed by the individual
and discourages selfinterest
Emphasizes inequalities of
individuals
Emphasizes equality of
individuals
© 2018 Cengage
8
Interaction of Business,
Government, and the Public (1 of 2)
Government-Business relationship –
•
•
Government influences business through
regulation, taxation, and more.
Business influences government by
lobbying, and more
Public-Government relationship –
•
•
Public influences government through
voting and forming special interest groups.
Government influences the public with
politicking, public policy formation, and
other political influences.
© 2018 Cengage
9
Interaction of Business,
Government, and the Public (2 of 2)
Business-Public relationship –
• Business influences the public through
advertising, public relations, and other
forms of communication
• The public influences business through
the marketplace, or by forming special
interest groups.
© 2018 Cengage
10
Interaction Among Business,
Government, and the Public
© 2018 Cengage
11
Government’s Nonregulatory
Influence on Business
Two major nonregulatory issues –
Industrial policy • Concerned with the role of government
in a national economy.
Privatization • Whether current public functions (e.g.,
public education, public transit, social
security, fire service) should be turned
over to the private (business) sector.
© 2018 Cengage
12
Industrial Policy
Industrial policy –
Every form of state intervention that affects
industry as a distinct part of the economy.
A current trend toward stronger industrial
policy is likely to continue while the world
economy works to recover from the global
financial crisis.
© 2018 Cengage
13
Privatization
Privatization –
The process of changing a public organization
to private control or ownership.
The intent is to capture the discipline of the
free market and a spirit of entrepreneurial
risk-taking.
Two functions a government might perform:
•
•
Producing a service
Providing a service
© 2018 Cengage
14
The Privatization Debate
Pro-Privatization Government has no comparative advantage in
many functions.
Government is less efficient and less flexible.
Anti-Privatization Some activities cannot be effectively handled
by the private sector.
Privatization works best when the pursuit of
profits does not work against broader
social goals or public policy.
© 2018 Cengage
15
Other Nonregulatory
Government Influences on Business
Government is:
•
•
•
A major employer
A standard setter
One of the largest purchasers
Government influences business by:
•
•
•
•
•
•
The use of Subsidies
Transfer payments
Loans and loan guarantees
Taxation
Monetary policy
Moral suasion
© 2018 Cengage
16
Government’s
Regulatory Influence on Business
Government Regulation has become the most
controversial in the business-government
relationship, affecting every aspect of how
business functions.
Most people agree that some regulation is
necessary to ensure that consumers and
employees are treated fairly, and not exposed to
hazards, and to protect the environment.
However, businesses also think that regulation
has often been too extensive in scope, too costly,
and burdensome in terms of red tape.
© 2018 Cengage
17
Regulation – What Does It Mean?
Regulation The act of governing, directing according to rule,
or bringing under the control of law or
constituted authority.
A federal regulatory agency •
•
•
•
•
Has decision-making authority
Establishes standards
Operates principally on domestic business
Has members appointed by the president
subject to Senate confirmation
Has its legal procedures governed by the
Administrative Procedures Act
© 2018 Cengage
18
Reasons for Regulation
Most regulation arises out of a market failure.
© 2018 Cengage
19
Types of Regulation (1 of 2)
© 2018 Cengage
20
Types of Regulation (2 of 2)
© 2018 Cengage
21
Comparison of
Economic and Social Regulation
Economic Regulations
Social Regulations
Focus
Market conditions;
economic variables
People in roles as
employees, consumers
and citizens
Affected
Industries
Selected (railroads, aeronautics,
communications)
Virtually all industries
Examples
CAB
FCC
Reregulation (e.g., Financial
Stability Oversight Board)
EEOC, OSHA,
CPSC, EPA
Current Trend
© 2018 Cengage
Reregulation (e.g.,
Consumer Financial
Protection Bureau)
22
Issues Related to Regulation Innovation may be affected –
When corporate budgets must focus on “defensive
research” certain types of innovation are less likely to
take place.
New investments in plant and equipment
may be affected –
To the extent that corporate funds must be used for
regulatory compliance, they are diverted from more
productive uses.
Small business may be adversely affected –
Federal regulations can have a disproportionately
adverse effect on small firms because of the (lack of)
economies of scale.
© 2018 Cengage
23
Deregulation Represents a counterforce
– aimed at keeping
the economy in balance. A continual striving
for the balance of freedom and control for
business will be best for society.
Purpose of Deregulation –
• Intended to increase competition with
hopes for greater efficiency, lower prices,
and enhanced innovation.
© 2018 Cengage
24
The Changing World of Deregulation
Deregulation which began in the 1980s had
mixed results.
Some prices fell, but more competitors were
unable to compete with the dominant
firms.
The savings and loan industry crisis cost the
government a $124 billion bailout.
Repeal of the Glass-Steagall Act caused the
global recession that began in 2008.
The dilemma is how to enhance competition
without sacrificing applicable social
regulations such as health and safety
requirements.
© 2018 Cengage
25
Key Terms
• collectivistic ethic of
government
• conservatorship
• deregulation
• direct costs
• economic regulation
• excessive
competition
• federalization
• indirect costs
• individualistic ethic
of business
© 2018 Cengage
•
•
•
•
•
•
•
•
•
•
•
induced costs
industrial policy
market failure
natural monopoly
negative externalities
privatization
regulation
reregulation
social costs
social goals
social regulation
26
Business & Society
Ethics, Sustainability & Stakeholder
Management
10th Edition
© 2018 Cengage
1
Chapter 12
Business
Influence on
Government and
Public Policy
© 2018 Cengage
2
Learning Outcomes
1. Describe the evolution of corporate political participation,
2.
3.
4.
5.
6.
including the different levels at which business lobbying occurs.
Discuss corporate political spending, and the arguments for
and against it.
Describe the different types of political action committees
(PACs), in terms of their historical growth, and the magnitude
of their activity.
Describe the agency issues involved with corporate political
spending and some of the contexts where these might arise.
Discuss the issues of corporate political accountability and
disclosure.
Outline the types of strategies for corporate political activity.
© 2018 Cengage
3
Chapter Outline
• Corporate Political Participation
• Business Lobbying
• Corporate Political Spending
• Political Action Committees
• Political Accountability and Transparency
• Strategies for Corporate Political Activity
• Summary
• Key Terms
© 2018 Cengage
4
Business Influence on
Government and Public Policy
•
•
•
Government is a central stakeholder of
business, and its interest is broad and
multifaceted.
Government’s power is derived from its legal
and moral right to represent the public in its
dealings with business.
Society would be best served if the system
maintained a balance of power, but a
controversial U.S. Supreme Court ruling
(Citizens United v. Federal Election
Commission) has left business with the power
to drive the political agenda unchecked.
© 2018 Cengage
5
Corporate Political Participation
Political Involvement • Participation in the formulation and
execution of public policy at various levels
of government.
• Two major approaches to corporate
political activity:
•
Lobbying
•
Political spending
© 2018 Cengage
6
Business Lobbying
Lobbying •
•
•
•
The process of influencing public officials to
promote or secure passage or defeat of
legislation.
Lobbyists are intensely self-interested.
Their goals are to promote legislation that is in
the interest of their organization, and to defeat
legislation that runs counter to that goal.
Because of the large amounts of money involved,
people will cross the legal and ethical line.
• Lawrence Lessig: “There’s all the difference in
the world between a lawyer making an
argument to the jury, and a lawyer handing
out $100 bills to the jurors.”
© 2018 Cengage
7
Organizational Levels of Lobbying
© 2018 Cengage
8
Professional Lobbying:
What do Business Lobbyists Do?
•
•
•
•
•
•
•
•
•
•
•
Get access to key legislators
Monitor legislation
Establish communication channels with regulatory
bodies
Protect firms against surprise legislation
Draft legislation, slick ad campaigns, direct-mail
campaigns
Provide issue papers on anticipated effects of
legislative activity
Communicate sentiments of association or company
on key issues
Influence outcome of legislation
Assist companies in coalition building around issues
Help members of Congress get reelected
Organize grassroots efforts
© 2018 Cengage
9
Grassroots Lobbying
Grassroots Lobbying
• Mobilizing the “grassroots,” which are
individual citizens who might be most
directly affected by legislative activity, to
political action.
Cyberadvocacy
• Using the Internet to amass grassroots
support and enable grassroots supporters
to contact their legislators.
© 2018 Cengage
10
Grassroots Lobbying (continued)
Astroturf Lobbying/Grasstops Lobbying
• Fake groups that appear to be genuinely
grassroots but are largely created and
funded by a professional organization or
trade association.
© 2018 Cengage
11
Trade Associations
• Established by individual industries to help
businesses in the same industry to interact
with each other and benefit from those
interactions.
• Association-level lobbying is common.
• Sometimes find themselves battling each
other in attempts to lobby Congress.
© 2018 Cengage
12
Umbrella Organizations
Two major U.S. umbrella organizations
• Chamber of Commerce of the United
States
• National Association of Manufacturers
(NAM)
Other umbrella organizations
• Business Roundtable
• National Federation of Independent
Businesses (NFIB)
© 2018 Cengage
13
Coalitions
• Form when distinct groups or parties
realize they have something in common
that might warrant their joining forces for
joint action.
• Standard practice for firms interested in
accomplishing political goals or influence
public policy.
• Can provide cover for a company wanting
to push their own agenda without its
name attached.
© 2018 Cengage
14
Corporate Political Spending
•
Corporations must vet requests for political
contributions to avoid “dangerous terrain.”
Arguments for Political Spending • The Supreme Court decision in Citizens United
ruled that government may not restrict corporate
political spending, equating such spending with
free speech. Unlimited spending creates an
imbalance of power.
Arguments against Political Spending •
•
Business is not likely to focus on the common
good.
The Golden Rule of Politics – He who has the
gold, rules.
© 2018 Cengage
15
Political Action Committees
• Political Action Committees (PACs) are committees organized to raise and
spend money for political candidates,
ballot initiatives, and proposed
legislation.
• Connected PAC – is associated with a
specific group or organization, and can
only raise money from that group.
• Nonconnected PAC – can accept funds
from any individual or organization,
including a connected PAC, as long as
those contributions are legal.
© 2018 Cengage
16
Top 10 PAC Contributors
to Federal Candidates
• Honeywell International
• AT&T, Inc.
• Lockheed Martin
• National Beer Wholesalers
• National Association of Realtors
• Northrup Grumman
• Credit Union Nation Association
• Blue Cross/Blue Shield
• International Brotherhood of Electrical
Workers
• American Bankers Association
© 2018 Cengage
17
The Impact of Super PACS
• Super PACS have facilitated outside spending in
politics, and the effect has been huge.
• By the end of January 2015, the top three
presidential candidates had raised over $388
million, their Super PACs had raised over $100
million.
• Super PACs are still new so their full effect is
not yet known, but sums of money that large
will certainly have a profound impact.
© 2018 Cengage
18
Agency Issues
•
Agency issues arise when actions of
managers are not in the shareholders’
best interests.
•
Corporate political spending, like all
corporate spending, should have the best
interests of the firm, its shareholders and
its stakeholders in mind.
•
Political spending should not provide an
opportunity for managers to pursue their
own agendas, or for trade associations to
pursue theirs.
© 2018 Cengage
19
Political Accountability
and Transparency (1 of 2)
•
Political accountability – an assumption of
responsibility for political actions, and a
willingness to answer for them.
•
Today, corporations have unprecedented freedom
to pursue their political agendas; restrictions on
the money they can spend are gone.
•
Multiple opportunities exist to hide the nature of
their activities from public view.
•
This freedom brings a duty for corporations to be
responsible; a movement to promote corporate
political accountability has formed.
© 2018 Cengage
20
Political Accountability
and Transparency (2 of 2)
•
•
•
•
•
Transparency– has become a major issue because
much of today’s corporate political activity is
outside public view.
Dark Money is the term which refers to the
political contributions from undisclosed donors more than $300 million in the 2012 presidential
election.
In 2016, $4.88 million in dark money expenditures
had been made in the year before the election.
Advocacy is best understood when one knows the
motives of the person making the arguments.
Voters have a right to know who is making the
arguments.
© 2018 Cengage
21
Strategies for
Corporate Political Activity
•
•
The purpose of political strategy is “to secure
a position of advantage regarding a given
regulation or piece of legislation, to gain
control of an idea or a movement and deflect
it from the firm, or to deal with a local
community group on an issue of importance.”
Three types of strategies that companies use
to interact in the political arena –
•
•
•
Information Strategy (provide information)
Financial Incentives Strategy (make
contributions)
Constituency Building Strategy (mobilizing others
to work together)
© 2018 Cengage
22
Financial Performance Outcomes
•
•
•
•
Studies to determine whether corporate
political spending influences political
decisions have mixed results.
A meta-analysis found that corporate political
activity had a consistent positive relationship
with a firm’s financial performance, but
generic results are of limited value because
the outcomes occur in a variety of contexts.
Context matters, and strategies that work in
one situation will not necessarily work in
another.
A 2013 study found a negative association
between political investments and market
performance.
© 2018 Cengage
23
Key Terms
•
•
•
•
•
•
•
•
•
•
•
501(c)(4)s
527 groups
Ad hoc coalitions
Astroturf lobbying
Carey committees
Citizens United v.
Federal Election
Commission
Coalitions
Company lobbying
Connected PAC
Cyberadvocacy
Dark money
© 2018 Cengage
(1 of 2)
• Golden Rule of Politics
• grassroots lobbying
• Independent
expenditure-only
committee
• Leadership PAC
• lobbying
• Nonconnected PAC
• Political accountability
• Political action
committees (PACs)
• Political corporate
social responsibility
(PCSR)
24
Key Terms
•
•
•
•
•
•
•
•
•
•
(2 of 2)
Political involvement
Revolving door lobbyists
Sectoral trade associations
Shadow lobbying
Stealth lobbying
Speechnow v. Federal Election Commission
Super PACs
Trade associations
Transparency
Umbrella trade associations
© 2018 Cengage
25
The Growth Machine Across the United States:
Business Actors’ Influence on Communities’
Economic Development and Limited-Government
Austerity Policies
Lazarus Adua*
University of Utah
Linda Lobao
The Ohio State University
The growth machine (GM) perspective has long guided urban research. Our study
provides a new extension of this perspective, focusing on local business actors’ influence on communities across the United States. We question whether GM-oriented
business actors remain widely associated with contemporary local economic development policies, and further, whether these actors influence the use of limitedgovernment austerity policies. Conceptually, we extend the GM framework by bringing it into dialogue with the literature on urban austerity policy. The analysis draws
from the urban-quantitative tradition of large-sample studies and assesses localities
across the nation using the empirical case of county governments. We find local
real estate owners, utilities, and other business actors broadly influence U.S. localities’ economic development policies. We also find some evidence that these actors’
influences in local governance are related to the use of such cutback policies as hiring freezes, capping of social services, expenditure cutbacks, and sale of public assets. Local Chambers of Commerce are particularly associated with cutback policies.
Overall, the findings suggest that where local GM actors are influential, communities are more likely to adopt business-oriented economic development policies, limit
the growth of social services for the less affluent, and scale-down the public sector.
INTRODUCTION
This study examines the extent to which business sector growth machine (GM) actors
influence the policy paths of communities across the United States. Our study follows
a longstanding sociological interest in the question of who governs America (Dahl 1961;
Domhoff 1990; Dye 1976; Friedland and Palmer 1984; Mills 1956; Mollenkopf 1989;
Molotch 1976; Stone 1989; Whitt 1979). A common conclusion from a segment of these
studies, the elitist tradition, is that a coterie of powerful actors (elites) essentially governs
∗ Correspondence
should be addressed to Lazarus Adua, University of Utah, Salt Lake City, UT 84112;
lazarus.adua@soc.utah.edu.
Funding: This study was supported with funding from the National Science Foundation (1259424), the National
Institute for Food and Agriculture (2007-35401-17733), and the Eunice Kennedy Shriver National Institute of
Child Health and Human Development (through the Ohio State University Institute for Population Research)
(R24-HD058484).
City & Community 18:2 June 2019
doi: 10.1111/cico.12399
C 2019 American Sociological Association, 1430 K Street NW, Washington, DC 20005
462
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
the society at all levels (Domhoff 1990, Mills 1956; Molotch 1976). Focusing on the local
state, Molotch (1976) recasts the elitist view in terms of the well-known growth machine
perspective.
Molotch (1976) explained that the GM, which can be understood as an alliance of
local-level “Millsian” power elites, drives local policy toward the singular goal of more intensive growth. The member-actors of the GM include large landowners, real estate developers, builders, and other local businesses, such as utilities, whose fortunes depend upon
the place in which they are located—along with growth-oriented local politicians/policy
makers (Logan and Crowder 2002; Logan et al. 1997; Logan and Molotch 1987; Vogel
and Swanson 1989). Molotch (1993:31) argues that GM actors “turn government into a
vehicle to pursue their material goals.” Our study provides a new examination of this concern by questioning the influence of GM business actors over key policy choices of local
governments across the nation.
The GM perspective has enjoyed widespread application in sociological studies of local
governments (Baldassare and Wilson 1996; DiGaetano and Klemanski 1991; Donovan
and Neiman 1992; Krannich and Humphrey 1983; Logan and Crowder 2002; O’Neill
et al. 2011; Vogel and Swanson 1989). Yet research gaps persist and new questions have
emerged.
An open question is the degree to which the GM perspective can be generalized across
localities in the United States. Logan et al. (1997) and Logan and Crowder (2002) report that evidence supporting the influence of GMs has come almost entirely from single
or small-sample community studies. They advocate the need for large-sample, nationally
representative studies. Few subsequent researchers have ever taken up this charge.
Other scholars question the contemporary applicability of the GM perspective, given
the national shift to a more neoliberal (pro-market) political economic environment that
has increased fiscal pressures, austerity tendencies, and the power of nonlocal business
elites (Donald et al. 2014; Jessop et al. 1999). Some posit the GM perspective is losing
its explanatory steam (Kirkpartick and Smith 2011). For example, in the contemporary period, local governments face increased pressures from extra-local forces including state/federal governments, bond market holders, and credit agencies; moreover, the
traditional policy stance of some business actors may have shifted more in the rightward
direction (Donald et al. 2014; Kirkpartick and Smith 2011; Mizruchi 2013).
Finally, researchers question the extent to which the GM perspective can be extended
beyond its traditional relevance for growth policies. Although antigrowth policies have
been scrutinized (O’Neill et al. 2011), other policy domains could offer new evidence
for theoretical elaboration. Consistent with this, Logan et al. (1997) and Molotch (1999)
had called for examining the GM’s effect on distributional policies that affect local residents’ well-being, and more recently, researchers have raised a connection with neoliberal limited-government austerity policies (Donald et al. 2014; Peck 2014). Yet to our
knowledge, while case studies exist, no nationally representative empirical work analyzes
GM actors’ influence on policies that aim to cut government.
This study takes a fresh look at the GM literature by examining new questions and research gaps. We provide a conceptual extension and partial test of the GM perspective
that centers on its private-sector, business-actors component. We analyze both policies
favoring business interests and those designed to cut or limit the scope of local government. To what extent do GM business actors influence the use of business incentives and
other economic development policies across the United States? Do business actors have
463
CITY & COMMUNITY
an even broader influence on local governments, orienting them toward the use of cutback policies? Conceptually, we address these two questions by bringing the GM literature
into dialogue with another longstanding urban literature on fiscal austerity (Clark 2000;
Clark and Walter 1991; Donald et al. 2014; Peck 2014). Empirically, we offer a new look
at the GM perspective by examining a range of localities across the United States using
a large, nationally representative sample of counties (N > 1,700). The research design
follows a longstanding urban sociological tradition that analyzes cutback and other policies by collecting primary data from local governments, such as cities and counties (Clark
2000; Logan and Crowder 2002). As a unit of local government, we use the county, which
captures communities across the nation’s urban–rural continuum.1
In the following section, we discuss the GM perspective and its empirical findings. Then
we explain the limited-government austerity literature and its potential link to the GM.
Next we discuss our data, methods, and results. In brief, based on our findings for business actors,2 we conclude that the GM perspective holds enduring explanatory power
and provides important insights about efforts to reduce the scope of local governments
nationally.
GM, BUSINESS, AND GROWTH-PROMOTION POLICIES
The GM perspective remains sociology’s best-known framework on local policy and governance, emerging as one of several structural responses to the older pluralist camp (Friedland and Palmer 1984).3 It asserts that the primary goal of American localities is growth,
the pursuit of which is spearheaded by the GM (Molotch 1976). The GM is an alliance of
local pro-growth power elites such as real estate developers/owners, builders, other local
businesses (especially utility companies and media), and “captured” political leaders (Logan and Crowder 2002; Logan et al. 1997; Logan and Molotch 1987; Molotch 1976; Vogel
and Swanson 1989). Although the precise configuration of GM actors varies from place
to place, their economic interests are tightly tied to the dynamism of the local economy
as served by land-use intensification (Friedland and Palmer 1984).
According to Logan et al. (1997), the GM perspective originally advanced two propositions: (1) local politics in the United States is dominated by local pro-growth power actors
(the GM) and (2) the urban future (or the future of the community, more broadly) is
shaped by the influence of the pro-growth coalition on local policy. The GM strives for
growth in both economic activity and population (Feiock 1991; Logan et al. 1997; Lyon
et al. 1981). In terms of economic activity, Friedland and Palmer (1984:401) stress that
external business attraction is a major goal: The GM paves the way by “participating in all
decisions that affect local land use—taxation, zoning, pollution control, infrastructural
development, and siting.”
How does the GM pursue its policy agenda? First, local governments tend to have willing ears at the outset. Scholars tend to view U.S. localities (overall) as historically having a
pro-growth agenda (Logan and Molotch 1987; Peterson 1981, 1995). Local governments
must balance budgets and grow the tax base to provide goods and services and to support
public workers. Analysts note this pro-growth agenda picked up steam from the Reagan
era onward as U.S. government became further decentralized: Increased responsibilities
but not necessarily revenues continue to be passed down to local governments (Lobao,
Adua, and Hooks 2014; Reese and Rosenfeld 2002; Warner 2006). Concern with fiscal
464
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
vulnerability and competition from other localities for jobs are major prompts for local
governments to embrace policies such as business incentives, infrastructure investments,
and external business attraction (even though such policies may be ineffective in the long
run; Lobao et al. 2014; Logan et al. 1997; Reese and Rosenfeld 2002).4 Second, in terms
of inside strategies, GM actors pursue their growth agenda by “capturing” and influencing
public officials who come to stake their careers on this agenda (Logan and Molotch 1987;
Molotch 1976; Vogel and Swanson 1989). With continual formal and informal interaction
with public officials, business actors “seek to harness local government—its legislative, fiscal, and legitimating powers—to protect and pursue their interests” (Jonas and Wilson
1999:6). Third, GM actors not only advocate for pro-growth policies, they also work to
thwart any emergent antigrowth politics (Vogel and Swanson 1989). Finally, GM actors’
dogged interest in growth is argued to displace attention away from other policies (Logan et al. 1997; Molotch 1999). For example, Molotch (1999:258) observes that cities do
so little for the poor partly because their policy spaces have been taken up by the growth
agenda.
Based on the foundational literature, we should expect that business actors will influence economic development policies broadly across the nation. Nevertheless, other
research provides theoretical and empirical reasons for why GM actors may not have any
strong or consistent influence across U.S. localities today.
Most broadly, some researchers reject the view that the primary essence of local governments is growth and that pro-growth coalitions dominate local politics. Researchers
working from the urban regimes perspective, for instance, argue that the GM is just one
of several possible governing regimes and that policy paths depend on which regime
wields the most influence (Kerstein 1993; Stone 2003; Stone and Sander 1987; Turner
1992). Nonetheless, urban regime theory, along with its applications in empirical studies,
affirms that in localities where the GM is dominant, local policies tend to favor growth
(see DiGaetano and Klemanski 1991; Kerstein 1993; Logan and Crowder 2002). Further,
there is evidence that pro-growth coalitions are quite dominant in a large number of U.S.
localities (DiGaetano and Klemanski 1991; Logan and Crowder 2002; Logan et al. 1997).
Yet even localities characterized by high involvement of GM actors may vary little in
policy direction relative to other localities for several reasons. As noted earlier, localities
face increased governance pressures from extra-local forces, such as upper-level governments, the global economy, and credit agencies. These forces increase fiscal stress and
make it more problematic to cater to traditional local pro-growth elites (Kirkpatrick and
Smith 2011). Second, it cannot be taken for granted that highly involved actors will have
their way. Using the case of real estate actors, Kimelberg (2011) shows that building internal government support is rife with challenges and by no means guarantees outcomes
favorable to business. Relatedly, researchers have long noted the potential for antigrowth
pushbacks (Logan and Moloch 1987; O’Neill et al. 2011). Finally, researchers observe
that pro-growth policies are often selected even where no active coalitions can be identified (Cochrane 1999). For example, the widespread use of business attraction policies
suggests that localities may aim to signal a pro-growth climate regardless of any specific
actors (Reese and Rosenfeld 2002). Thus, we might expect little policy variation across
the United States irrespective of whether GM business actors are more or less involved in
some communities over others.
Although ample reasons exist for why GM dynamics may not strongly differentiate U.S. localities today, past studies indicate that GM actors are important drivers of
465
CITY & COMMUNITY
growth policies. A number of researchers report positive relationships between the presence/influence of local power elites constituting GM member-actors and the adoption of
growth-serving policies (Clingermayer and Feiock 1990; DiGaetano and Klemanski 1991;
Kerstein 1993; Logan and Crowder 2002; Logan et al. 1997). For example, Logan and
Crowder (2002) using a survey of government officials from 300 suburbs conducted in
1983–1984 found that hegemonic growth regimes were more likely to implement policies
aimed at local business and population growth as measured by a general policy index.
Reese and Rosenfeld (2002) in a survey of 350 city officials conducted in 1994 found that
where growth elites were more dominant, cities tended to be more focused on business
attraction. More commonly, researchers using quantitative survey-based studies have analyzed general local business input into government decision-making (rather than analyzing specific GM actors). Insofar as local businesses incorporate GM actors, these studies
further support a link with business promotion. Greater business input has been associated with greater use of business loan and marketing programs by cities (Reese and
Rosenfeld 2002) and business attraction policies by county governments (Lobao et al.
2014).
For our study, although recent research provides little information about GM actors
broadly across the United States, consistent with the GM perspective and much of the
past empirical work, we would expect that where business actors are more involved in
governance, localities should be more likely to adopt policies favoring business interests.
In the next section, we extend this relationship by questioning the influence of GM actors
on policies aimed at limiting government.
GM BUSINESS ACTORS AND LIMITED-GOVERNMENT
AUSTERITY POLICIES
Pressures to limit the scope of government widely concern scholars. At the local level,
analysts refer to the policies designed to do so as urban austerity policies (Donald et al.
2014; Lobao and Adua 2011; Peck 2012) or cutback management strategies (Scorsone
and Plerhoples 2010). Policies that limit the scope of government, such as reducing or
freezing labor costs, service caps, expenditure decreases, and selling assets, are of key
concern because scholars assume public well-being will decline if government is cut.
Research on local austerity policies dates back to the 1980s (see Clark 2000). Three
waves of use of these policies across U.S. localities can be identified. First, researchers
often interpret contemporary cutback pressures as part of the ongoing shift toward neoliberal governance from the Reagan era onward. This shift has reduced the Keynesian
social safety net and funding for localities, and led states and the federal government to
increasingly decentralize responsibilities often in the form of unfunded mandates (Donald et al. 2014; Gotham and Greenberg 2014; Lobao and Adua 2011; Peck 2012). Analysts
see the neoliberal turn as exerting pressure on localities to raise own-source funds and to
adopt pro-growth policies. Second, after 2000, with the post-September 11th downturn
and Bush presidency, Scorsone and Plerhoples (2010) argue a new period emerged where
localities altered the mix of policies used to address fiscal shortfalls. Localities moved
from a roughly similar use of both revenue-seeking strategies (such as tax increases)
and cutback strategies more toward the latter. Lobao and Adua (2011) found a switch
to greater use of service cuts and selling assets and somewhat decreased use of revenue
466
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
augmentation policies (such as raising taxes) by U.S. localities over the 2000 decade. Finally, the 2007–2009 Great Recession is argued to have ushered in an ideological effort to
popularly legitimize the use of austerity policies (Donald et al. 2014; Peck 2012, 2014).
This is undergirded by right-wing organizations, such as the American Legislative
Exchange Council (ALEC), that attempt to frame the recession as stemming from local
government largesse rather than private sector failure and financial debauchery (Peck
2014).5
In sociology, large-sample austerity studies first emerged in the 1980s with the University of Chicago’s urban fiscal austerity project (Clark 2000). Since then, studies spanning
various states and sometimes the nation have been conducted across the social sciences.
Throughout decades of research, the major consistent determinant of austerity policies
are the common economic pressures faced by localities in the Federalist system, especially when measured by officials’ own reports of declines in the tax base and intergovernmental revenues (Clark and Walter 1991; Clingermayer and Feiock 2001; Lobao and
Adua 2011; Maher and Deller 2007; Scorsone and Plerhoples 2010). Economic distress as
reported by officials is thought to be a bellwether indicator as it reflects more nuanced fiscal conditions that local bureaucracies perceive in the course of decision-making. Larger
governments with greater capacity tend to be the ones most likely to cut back; such governments tend to be more activist overall in service provision and thus forced to cut
expansive agendas earliest (Clark and Walter 1991; Clingermayer and Feiock 2001). Finally, although researchers often question whether the use of austerity policies is greater
in bastions of Republican Party support, past studies do not tend to find any consistent
difference between the nation’s Democratic and Republican leaning communities (Clark
and Walter 1991; Lobao and Adua 2011; Scorsone and Plerhoples 2010).
Can the GM literature that has shed light on economic development policies across
wide-ranging communities be extended to austerity policies across the nation? We identify
two interrelated channels by which GM actors may influence cutback policies.
First, GM actors’ influence could emerge from a more indirect or covert process that
institutionalizes a local context of poor policy choices. That is, Molotch (1999:258) notes
GMs work in their broadest sense by eroding the “capacity to collectively solve problems.”
Other agendas that serve local citizens are swamped as local governments take up the
call for business growth (Logan et al. 1997). In this context, planning for the future becomes more problematic. Communities may follow path-dependent routes where alternative policy choices that could be used to better manage downturn or create growth are
increasingly closed off. For example, Reese and Rosenfeld (2002) in a large-sample study
report that once policy paths are selected, they tend to be continued (even without evidence of effectiveness) because they become woven into the fabric of local government.
In a study of New York and New Orleans, Gotham and Greenberg (2014:227) note such
path-dependent-like behavior: Growth coalitions that had pushed the two cities into less
sustainable, inequitable development later steered disaster funding toward policies that
pursued the same direction.
Second, GM actors’ influence may be more direct. Logan and Molotch’s (1987) classic
formulation stressed that GM actors have fundamental exchange-value interests in communities as opposed to citizens’ use-value interests in quality of life, and that GM actors
bend policy agendas to serve their direct interests. Thus Logan et al. (1997) and Molotch
(1999) note the GM is likely to divert resources away from citizens’ needs or redistribution toward business needs. Local governments with scarce resources and strong GMs also
467
CITY & COMMUNITY
may be more willing to limit social services and spending as this provides an ideological
signal of a “better business” climate (Peterson 1981). A limited portfolio of social services
is assumed to drive out the poor relative to more affluent populations who better contribute to local growth and the tax base (Kantor 1995; Oakley and Logan 2007; Peterson
1981). On the other hand, GM business actors need local officials to serve the growth
agenda, providing some reason why they may not champion direct staff cutbacks. Finally,
there is some evidence that the U.S. business sector has become more antigovernment
over time (Mizruchi 2013). The U.S. Chamber of Commerce has increasingly opposed
government regulations that support workers, families, and the environment and it has
strong ties to ALEC (Hakim 2016; Nocera 2014; SourceWatch 2015).6 Communities of
course have distinct local Chambers that do not necessarily follow in their parent organization’s footsteps. Nevertheless, this raises a provocative question about the degree
to which local Chambers of Commerce (CoC) may do so with regard to contemporary
austerity policy.
SUMMARY AND EXPECTED RELATIONSHIPS
Our study takes a new look at the GM literature by providing a nationwide analysis of GM
actors and their relationship to both business-friendly and limited-government policies.
Analysts see both sets of policies as reflective of neoliberal governance, raising concerns
about the potential to harm communities (Peck 2012; Schram 2006). Based on the available literature, we expect business member-actors of the GM, if influential in any locality,
to impact policies that directly serve local growth interests. Given the lack of generalizable research, whether GM actors influence policies that rollback local government is
unclear. Our conceptual extension of the GM literature explains why we might expect
this relationship.
DATA AND METHODS
Our research design follows a longstanding urban sociological tradition that employs
large samples of local governments (i.e., cities or counties) to analyze local policies, a
design developed by the University of Chicago’s Fiscal Austerity and Urban Innovation
Project (Clark 2000). This research design employs data on local governments collected
by surveying government officials, such as city mayors and county commissioners (for
examples, see Clark and Walter 1991; Clingermayer and Feiock 1990; Lobao et al. 2014;
Logan and Crowder 2002; Reese and Rosenfeld 2002).7 Primary data are necessary due
to the lack of secondary sources that provide direct listings of policies across U.S. localities and to document locally unique dynamics. We also use data from secondary sources
such as the Census of Governments and Census of Population to capture other local
characteristics.
Studies of localities’ policies are based on city or county governments. Both are general
purpose governments that make and implement a variety of public policies (Benton
2002).8 For our study, counties offer several advantages. As counties cover metropolitan
and nonmetropolitan areas (including small unincorporated communities), both urban
and rural communities can be studied and national representation is greater. Counties
are also important local governments. They are the fastest growing general purpose
468
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
governments due to suburban migration and because welfare and related social programs have been increasingly devolved to counties (Benton 2002; Lobao et al. 2014).
Finally, by working with the National Association of Counties (NACo; the equivalent of
the National League of Cities), we were able to collect the most nationally representative
information to date on local austerity policies.
The primary data come from a survey of county governments conducted under the
auspices of the NACo in 2007/2008. NACo identified county government officials substantively knowledgeable about their respective counties to report on existing policies/programs. These officials were key informants used in other NACo studies and
included county commissioners, county managers, auditors, and clerks. Following Dillman’s (1978) survey methodology approach, surveys were mailed to approximately 3,000
county governments (including parishes in Louisiana) in all the 46 contiguous states with
county governments.9 For more information about the methodology employed consult
Lobao, Adua, and Hooks (2014). The survey’s response rate was 60% (1,756 counties).
This is a considerably high response rate for local government studies; as noted earlier,
ICMA response rates are generally about 30%.
The construction of policy variables and statistical modeling is consistent with other
studies using this methodology (Clark and Walter 1991; Lobao et al. 2014; Logan and
Crowder 2002; Reese and Rosenfeld 2002; Sun 2010). Studies that obtain government information from officials have limitations. These studies generally are limited to collecting
data with dichotomous response categories such as the use/nonuse of a policy and other
information that officials can more readily provide. This affects the construction of variables: Researchers typically use dichotomous variables or count-variables of the number
of policies adopted. Potential response bias due to localities’ or officials’ characteristics
can also be a concern. We discuss this issue further under the section on data diagnostics.
We now describe our measures.
DEPENDENT VARIABLES: BUSINESS GROWTH PROMOTION
AND LIMITED-GOVERNMENT POLICIES
To analyze pro-business growth policies, we employ measures of general business
incentives, budgeting for business attraction, and infrastructure provision. Localities’
use of these policies is informed by the assumption that businesses receiving incentives
or industrial recruitment packages help create jobs within the local economy and/or
broaden the tax base, consistent with GM objectives. General business incentives is measured by a count-index (1 = use or 0 = nonuse) of 13 programs targeted at new and
expanding businesses. These include low-cost loans, employee training, free land or land
write-downs, industrial revenue bonds, infrastructure improvements, locally designated
enterprise zones, relocation assistance, screening of job applicants, special assessment
districts, subsidized buildings, tax increment financing, tax abatements, and utility rate
reduction. See Reese and Rosenfeld (2002) and Lobao et al. (2014) for construction of a
similar count-measure. To measure budgeting for business attraction, we used the proportion
of the economic development budget devoted to outside business attraction. Here, local
officials were asked to indicate the budget share devoted to outside business attraction
using the following response categories: 0%, 1–20%, 21–40%, 41–60%, 61–80%, and
81–100%. Each response option is recoded to its category midpoint. The budget devoted
469
CITY & COMMUNITY
to outside business attraction contrasts with support for small and existing businesses
and indicates more competitive pursuit of growth objectives (Reese and Rosenfeld
2002). Business infrastructure provision is measured with an item that asked whether the
county constructed “special buildings to attract businesses” in the prior 5 years, with the
response options 1 (yes) and 0 (no).
Policies that limit the scope of government are measured with five variables—hiring
freezes, staff layoffs, social service caps, expenditure cuts, and divestiture of assets. Consistent with other urban austerity government-survey studies (Clark 2000; Clark and Walter
1991; Lobao and Adua 2011; Sun 2010), we measure hiring freezes, staff layoffs, expenditure
cuts, and sale of assets with questions that asked officials to indicate whether their counties
had used employee hiring freezes, staff layoffs, expenditure cuts, and the sale of county
assets “in the past 3 years to balance recent budgets.” Responses are coded 1 = yes and 0
= no. We measure social service caps with survey items that tap the failure to increase social
services. These items span 10 key social services—homeless shelters, housing assistance,
child care, elder care, shelter for battered persons, drug–alcohol rehabilitation, mental health programs, nutrition programs, senior citizens programs, and public housing
programs—that counties report making “no effort” to increase in the previous 5 years.
Due to skewness, the resulting count-index of “no effort” responses was recoded into a
dichotomy, with one representing failure to increase the provision of at least one of the
10 services making up the index. Researchers argue that nonincrease of services, especially given the growth in public need, represents the contemporary form of much of
the welfare-state retrenchment (Hacker 2004; Starke 2006). Service caps are viewed as
“stealth” social service cuts (Starke 2006). Summary statistics for all variables are shown
in Table 1.
INDEPENDENT VARIABLES
Three sets of independent variables are included in our analyses. The first include the
GM pro-growth business actors and the remaining sets are statistical controls.
GM: Local Pro-Growth Business Actors
We use several indicators to measure the influence of local pro-growth power actors in
U.S. counties. For the real estate industry, we use a gradient measure that asked responding officials to indicate the level of involvement of owners of commercial and industrial real estate
in setting the county’s economic development agenda. The response-scale options are as follows:
1 (little or none), 2 (some), 3 (moderate), and 4 (high). We measure the influence of
other business actors with items that requested officials to indicate whether or not the
Chamber of Commerce, utility companies, and local businesses (i.e., those “selling primarily to
the local market”) “engage in the county’s economic development planning and implementation activities.” Responses are coded as 1 (yes) and 0 (no). Our operationalization
of the GM perspective in terms of the involvement of member-actors of the GM is consistent with previous quantitative evaluations of the theory (Clingermayer and Feiock 1990;
Lyon et al. 1981).10 Although researchers note the precise composition of GM actors
varies by context, they typically include the business actors identified above as constituent
members (Logan and Crowder 2002; Molotch 1976; Vogel and Swanson 1989).
470
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
TABLE 1. Summary Statistics for Variables Analyzed1
Local policies (dependent variables)
Business growth promotion:
General business incentives (number offered)
Percent economic development funds allocated to business attraction
Provided special business infrastructure (yes = 1)2
Limited-government austerity policies
Hiring freeze (yes = 1)2
Staff layoffs (yes = 1)2
Social services cap (yes = 1)2
Expenditures cuts (yes = 1)2
Assets sold (any public assets sold?) (yes = 1)2
Local pro-growth business actors’ involvement
Real estate owners’ involvement in economic development agenda setting (scale)
Chamber of commerce involvement in economic development planning (yes = 1)2
Utility companies’ involvement in economic development planning (yes = 1)2
Local businesses involvement in economic development planning (yes = 12
Statistical controls: economic pressures and government attributes
Decline in tax base
Index of general fiscal problems
Competition with other localities for businesses (yes = 1)2
Government size (number of employees)
Administrative centralization (manager/executive, yes = 1)2
Staff capacity (grant writer, yes = 1)2
Statistical controls: community context
Percent Republican voting (2004 elections)
Percent family poverty (poverty rate, 2000)
Metro county (yes = 1)2
Population of county (2000)
Percent black
1
2
Mean/
Percent
Standard
deviation
2.47
19.17
14.48
2.59
21.19
24.33
10.30
37.80
82.44
24.70
2.01
77.76
33.92
40.54
0.83
1.85
9.10
36.10
328.00
53.30
32.40
0.83
2.35
61.56
10.33
32.20
71264.7
7.21
461.40
11.90
5.46
268327.30
12.77
Statistics reported pertain to county governments in 2008, N = 1756.
Categorical variables, percent of counties reporting.
As discussed, we expect the GM indicators to be related to policies oriented toward
business interests that are assumed to augur well for growth, the primary goal of the GM.
By extension, we also expect these GM indicators to be related to limited-government
policies. In the case of the Chamber of Commerce, given its national shift to the right
(Dunlap and McCright 2013; Nocera 2014), we are particularly interested in whether
there is a local-level disposition toward limited-government policies.
Consistent with previous studies (see DiGaetano and Klemanski 1991; Logan et al.
1997), our data demonstrate the direct involvement of local pro-growth power actors
in communities across the United States (see Table 1). Local CoC are major players in
economic development planning and implementation for the majority (78%) of counties. Local businesses participate in economic development planning in 41% of counties,
while utility companies are engaged in 34% of counties. Overall, the mean value for the
involvement of real estate owners in “setting counties’ economic development agenda”
is 2.01 (on a scale of 1–4), which indicates “some involvement” in most counties. About
22% of counties report moderate to high level of involvement of real estate owners.
471
CITY & COMMUNITY
Control Variables: Economic Pressures, Governmental Attributes,
and Community Context
Our models use key variables identified in other large-sample community policy studies
that we treat as control variables. The first set measures local governments’ economic
pressures and other governance factors. As discussed, economic pressures from fiscal vulnerability and competition from other localities for jobs are usually major determinants
of business promotion policies (Logan et al. 1997; Reese and Rosenfeld 2002). Fiscal vulnerability is also a well-recognized determinant of austerity policies (Clark and Walter
1991; Kirkpatrick and Smith 2011). Measures of economic pressures include: the severity
of any general decline in the county’s tax base on its finances (coded as 1 = not important
financial problem, 2 = somewhat important, and 3 = very important); number of general
fiscal problems (a count-index of four items from the NACo survey)11 ; and competition with
other localities for businesses (whether or not a county experienced competition from other
local governments in the prior 5 years, coded 0/1). We also control for governmental
institutional capacity, a well-recognized influence on policy choices. As already noted,
larger, more professionalized governments are more active in policy making. But they
tend to be among the first to use cutbacks because their service agendas are generally
more extensive in the first place and they have more professionalized staff to smooth
over cutbacks (Clark and Walter 1991; Lobao et al. 2014). We measure capacity in terms
of size, administrative organization, and professional staff. Government size is measured by
the number of full-time staff (logged), a commonly used capacity indicator (Reese and
Rosenfeld 2002). Administrative organization is measured by whether or not the county
utilizes an executive/administrative head. This form of organization indicates more centralized administration where one designated officer manages the county governing board.
It reflects greater leadership capacity, which augurs well for policy activities of all types
(Benton 2002). We also control for whether the county has an in-house staff grant writer,
a factor that increases capacity to access external resources such as state/federal funds
(Reese and Rosenfeld 2002).
Finally, we control for community context, using political-economic and population
variables that are lagged in time prior to the dependent variables in order to control
for the longstanding context of local decision-making. These variables include: percent
Republican voting in the 2004 general election; the poverty rate (census estimates of
family poverty rates); the metropolitan character of the county (metro = 1; nonmetro =
0); population size (logged); and proportion of county residents identifying as black.12
Such local contextual conditions are often included as control variables in large-sample
studies of local policies (Clark and Walter 1991; Reese and Rosenfeld 2002; Lobao et al.
2014).
DATA DIAGNOSTICS AND MODEL ESTIMATION
A potential data quality issue associated with using government surveys can be response
bias from both responding localities and specific officials. We tested for differences in responding and nonresponding counties’ characteristics on a range of socioeconomic and
demographic variables. No significant differences between responding and nonresponding counties were found. As our data cover the majority of U.S. counties, metro as well as
nonmetropolitan, it would be expected that any differences would be minimal. To check
472
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
for response bias from specific officials, we reanalyzed the eight models in this study
by including the responding officials’ education, length of time in county employment,
elected/appointed status, and two variables measuring the officials’ own policy stance
(e.g., views on county spending for the poor). No systematic differences for officials’
attributes across the models were found. However, we found one respondent attribute
significant in one of the models, responding officials’ education (in the model for social
services cap).13 We therefore include that variable as an additional control in the social
services model (see Table 3, Model 3). Further, with regard to data quality, there tended
to be few missing cases (under 3% for most of these variables). Finding that these cases
were missing completely at random, we excluded them from the multivariate analysis.
We conducted other diagnostics focused on the potential for multicollinearity, endogeneity, and interaction effects. Correlation coefficients among the independent variables are low to moderate; variance inflation factors also reveal no levels of high collinearity in any model. We applied Hausman tests to assess potential endogeneity, that is,
whether the predictors in our models can be considered as mutually causally related. The
Hausman tests revealed no evidence of endogeneity. Finally, we checked for potential interaction effects among the variables considered in the study. We found one significant
interaction effect between the CoC’s involvement in local governance and Republican
voting in the budget for business attraction model (Table 2, Model 2).
For our analytic models, we use both linear and nonlinear (logit) fixed-effects (FE) by
state regression analysis. Since counties, our unit of analysis, are nested in states, withinstate correlation of the error variances is to be expected. Also, interstate variability in
the measures can be assumed to exist. For example, counties (like cities) are administratively connected to their state governments. Although ordinary least squares (OLS)
regression is more parsimonious, in the context of our data, it will be suboptimal. Key
assumptions of OLS do not hold in the context of hierarchical data (counties nesting in
states). Lagrange multiplier tests applied to the models also confirmed that the use of
OLS regression would yield significant bias. The FE estimation technique thus controls
for state-level influences while estimating the impacts of the regressors on within-state
variability in the dependent variables. In effect, the technique accounts for the fact that
county governments’ policies are influenced by state decisions.14
RESULTS
This section presents our findings from multivariate models. The first set of models addresses business growth policies (Table 2) and the second, limited-government policies
(Table 3). It should be stressed that like other large-scale surveys of local governments,
the findings are based on data reported by government officials. In our discussion below,
we focus primarily on the central question raised in this research—the extent to which
GM actors remain a potent force in local governance.
BUSINESS GROWTH-PROMOTION POLICIES
Consistent with the GM perspective, results from the models indicate that the involvement of local pro-growth actors in the governance activities of U.S. counties influences the
extent to which counties adopt pro-growth economic development policies (see Table 2).
473
CITY & COMMUNITY
TABLE 2. Fixed-Effects Regression Models: The Impacts of Growth Machine Business-Actors and Other Local
Attributes on Counties’ Growth-Promotion Policies1
Independent variables
Model 1:
General business
incentives; b
(SE)
Local pro-growth actors’ involvement
Real estate owners
0.20 (0.05)***
Chamber of Commerce2
−0.05 (0.11)
Utility companies2
1.14 (0.15)***
Local businesses2
0.37 (0.13)**
Economic pressures and government attributes
Decline in tax base
0.06 (0.08)
General fiscal problems, index
0.05 (0.02)*
Competition with other
1.42 (0.16)***
localities for businesses2
Government size
0.21 (0.08)*
Administrative centralization2
0.28 (0.13)*
Staff capacity2
0.56 (0.13)***
Community Context
Percent Republican voting
0.21 (0.54)
Family poverty rate
0.00 (0.01)
Metro county2
−0.14 (0.14)
Population (logged)
−0.00 (0.07)
Percent black
0.01 (0.01)
Statistical interactions
Chamber of Commerce*
Percent Republican voting
Model statistics
Log-likelihood
–
N
1,677
Model 2: Percent
budget for
business
attraction; b (SE)
Model 3:
Business
infrastructure; b
(SE)
0.13 (0.05)*
−1.26 (0.54)*
0.30 (0.10))**
0.13 (0.09)
−0.07 (0.10)
−0.05 (0.20)
0.18 (0.17)
0.58 (0.16)***
−0.07 (0.07)
0.02 (0.02)
0.69 (0.12)***
−0.06 (0.11)
−0.01 (0.04)
0.58 (0.17)***
0.15 (0.08)+
0.06 (0.13)
0.23 (0.10)*
−0.20 (0.14)
−0.09 (0.18)
0.49 (0.17)**
−0.82 (0.84)
0.00 (0.01)
−0.14 (0.09)
0.02 (0.05)
0.01 (0.00)
−0.43 (1.00)
−0.04 (0.02)
−0.37 (0.20)+
−0.00 (0.12)
0.01 (0.01)
1.94 (0.89)*
–
1,569
−514.66
1,640
1
The models reported here are from fixed-effects by state regression analysis; they control for the effects of state, the
grouping variable. Models 1 and 2 are linear models. Model 3 is a logit model; coefficients reported are log odds.
2
Dichotomous independent variables.
Standard errors in parentheses.
+
p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001.
Counties where owners of commercial and industrial real estate (b = 0.20), utility companies (b = 1.14), and businesses aimed at the local market (b = 0.37) are involved in the
economic development planning process (i.e., governance) are significantly more likely
to provide business incentives (Model 1). Further, counties devote significantly larger
shares of their economic development budgets to business attraction where real estate
owners play a stronger role in setting the overall economic development agenda and
also where local utility companies participate in development planning (Model 2). Local
business involvement is further associated with counties constructing special buildings to
attract businesses (Model 3).
There is also evidence that the CoC’s participation in county governance affects the
funds allocated to business attraction (Table 2, Model 2). This relationship, however,
varies by the political leaning of the county. Counties that lean Republican (that is, voted
at higher rates for the Republican Party in the 2004 presidential elections) and have
local chapters of the CoC devoted a larger proportion of their economic development
474
−841.77
1,621
0.47 (0.73)
−0.03 (0.02)
0.06 (0.16)
0.01 (0.09)
−0.01 (0.01)
0.44 (0.13)***
−1.18 (1.04)
0.01 (0.03)
0.27 (0.24)
−0.09 (0.14)
−0.00 (0.01)
–
−395.91
1,432
0.16 (0.10)
0.33 (0.14)*
0.18 (0.13)
−0.24 (0.08)**
0.08 (0.03)**
−0.16 (0.13)
0.32 (0.12)**
0.10 (0.05)*
0.13 (0.21)
0.10 (0.15)
0.20 (0.21)
0.29 (0.19)
0.16 (0.07)*
−0.03 (0.15)
0.37 (0.13)**
0.25 (0.12)*
Model 3: Social
services cap; b
(SE)
−0.12 (0.12)
0.47 (0.24)+
−0.13 (0.20)
−0.41 (0.19)*
Model 2: Staff
layoff; b (SE)
−584.09
1,601
−0.63 (0.88)
0.00 (0.02)
−0.02 (0.19)
−0.05 (0.11)
0.01 (0.01)
–
−0.16 (0.12)
0.13 (0.18)
−0.08 (0.17)
0.39 (0.11)***
0.13 (0.03)***
0.24 (0.17)
0.26 (0.10)**
0.18 (0.18)
−0.10 (0.17)
0.24 (0.16)
Model 4:
Expend.
decrease; b (SE)
−793.47
1,656
0.56 (0.76)
−0.01 (0.02)
0.22 (0.16)
−0.09 (0.09)
0.02 (0.01)*
–
0.01 (0.11)
−0.17 (0.15)
−0.05 (0.14)
0.22 (0.08)**
0.03 (0.03)
0.18 (0.14)
0.03 (0.08)
0.38 (0.16)*
0.00 (0.14)
0.06 (0.13)
Model 5: Sold
county assets; b
(SE)
The models reported here are from fixed-effects by state regression analysis; they control for the effects of state, the grouping variable. All models are logit models;
coefficients are log odds.
2
Dichotomous independent variables.
Standard errors in parentheses.
+
p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001
1
Local pro-growth actors’ involvement:
Real estate owners
0.00 (0.08)
Chamber of Commerce2
0.47 (0.18)**
−0.11 (0.15)
Utility companies2
Local businesses2
−0.02 (0.14)
Economic pressures & government attributes
Decline in tax base
0.36 (0.09)***
General fiscal problems, index
0.12 (0.03)***
Competition with other localities for
0.18 (0.15)
businesses2
Government size
0.29 (0.11)**
Administrative centralization2
0.19 (0.16)
Staff capacity2
0.01 (0.15)
Community context
Percent Republican voting
0.29 (0.82)
Family poverty rate
0.02 (0.02)
Metro county2
0.09 (0.17)
Population (logged)
−0.07 (0.10)
Percent black
0.00 (0.01)
Education of responding official
–
(college or higher)2
Model statistics
Log-likelihood
−694.31
N
1,651
Independent variables
Model 1: Hiring
freeze; b (SE)
TABLE 3. Fixed-Effects Logit Models: The Impacts of Growth Machine Business-Actors and Other Local Attributes on Counties’ Limited-Government Austerity
Policies1
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
475
CITY & COMMUNITY
budgets to business attraction. This finding suggests that although the Republican Party
and the national Chamber of Commerce have become ideological bedfellows, local political context allows this relationship to flourish or diminish. Counties whose populations
are more sympathetic to the Republican Party appear to provide a more facilitative context for engaged local CoCs to steer development funds toward more competitive growth
as opposed to supporting small, existing local businesses.
With regard to the control variables (Table 2), there are several noteworthy relationships. Pressures from competition with other localities to attract business (bidding wars)
is significantly associated positively with use of all the three economic development policies considered (Models 1, 2, and 3), a relationship expected from the economic development literature. Pressures from general fiscal problems are significantly related to the
greater use of business incentives (Model 1). Government capacity also makes a difference. Counties with grant writers are significantly more likely to adopt the policies analyzed (Models 1, 2, and 3) affirming the importance of capacity in local policy making
and implementation. Larger governments are also more likely to provide incentives. Net
of GM actors, pressures, and capacity variables, contextual variables have little relationship to economic development policy. This lack of relationship for contextual variables
is observed in other studies where analysts note that pursuit of economic growth has become so ubiquitous across U.S. localities that contextual factors have mattered less over
time (Lobao et al. 2014; Reese and Rosenfeld 2002).
In sum, our findings for business-oriented economic growth policies indicate GM business actors remain a potent force across the United States. The changes experienced by
communities in recent years do not appear to have doused these actors’ influence.
LIMITED-GOVERNMENT AUSTERITY POLICIES
Does the involvement of member-actors of the GM in county governance extend to influencing the degree to which counties adopt government-limiting policies? We find some
evidence that this is the case (see Table 3). The involvement of the CoC in development
planning is positively associated with hiring freezes (b = 0.47, p < 0.01), staff layoffs (b
= 0.47, p < 0.10), and the divestiture of county assets (b = 0.38, p < 0.05; Models 1, 2,
and 5 respectively). Further, the involvement of real estate owners, utility companies, and
local businesses in county governance is significantly positively related to the use of social
service caps (Table 3, Model 3). As discussed, urban austerity researchers have long noted
that local elites may view social service caps as a policy tool that encourages the growth
of business and more affluent populations just as it pushes out the poor (Kantor 1995;
Peterson 1981). Real estate owners’ involvement is also positively related to spending cuts
(Model 4). The relationships above support the argument that austerity policies tend to
be championed by private sector elites and advocates of neoliberal governance because
these policies reflect a favorable business climate that emphasizes economic growth and
a decreased role for the public sector (Kantor 1995; Peck 2014).
Although the findings above provide statistically significant relationships between the
influence of the GM member-actors and the use of certain government-limiting policies,
we note two caveats. First, we find that the influence of locally centered businesses is negatively associated with local government layoffs (Table 3, Model 2). As discussed earlier,
insofar as GM actors work through and need local officials to support their agenda, we
476
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
might find less consistent results for direct staff cutbacks, a pattern that is suggested here.
Second, as previously noted, in no model except for social service caps did we find any
association between responding officials’ characteristics and local policies: In this model,
more highly educated officials are more likely to report the use of service caps (Model 3).
Officials with higher education may be representative of a broader indicator, their counties’ level of institutional capacity. In brief, higher capacity governments tend to be more
susceptible to cutbacks as their overall portfolio of services tends also to be greater (Clark
and Walter 1991; Lobao and Adua 2011). Although officials’ education is included in the
social service model as a control variable to mitigate any effect on the relationships, the
results for this model should be interpreted more cautiously.
Turning briefly to the control variables, we find ample evidence that economic pressures experienced by local governments influence the use of cutback policies. For example, reported declines in a county’s tax base are positively related to hiring freezes,
staff layoffs, expenditure cuts, and the sale of county assets (see, respectively, Models 1,
2, 4, and 5). However, counties that experienced tax base declines are more likely to
have increased rather than capped social services, suggesting a positive, counter-cyclical
response to citizens’ needs. General fiscal problems are further related to the use of austerity policies. Net of the GM indicators and other economic pressures, few other control
variables have statistically significant relationships, although there is also some evidence
that higher capacity governments (size and centralized management) are more likely
to utilize cutback strategies. In sum, the economic pressures faced by U.S. localities significantly contribute to the adoption of austerity policies as expected from the urban
austerity literature.
CONCLUSIONS
The GM perspective has long guided urban research (Logan and Crowder 2002; Logan
et al. 1997; Logan and Molotch 1987; Molotch 1976). Member-actors of the GM are expected to support policies that favor business interests and those more broadly assumed
to augur well for local area growth. Our study provides a partial conceptual and empirical
extension of this perspective that focuses on GM business actors’ influence.
From a conceptual standpoint, by analyzing business actors we address the degree to
which the GM perspective remains relevant across the nation and whether it can be extended to inform the use of policies aimed at reducing the scope of government. To
do so, we brought the GM perspective into dialogue with the longstanding literature on
urban austerity policy. Empirically, we extended the GM perspective by addressing a longneeded approach of going beyond small sample studies (Logan et al. 1997; Logan and
Crowder 2002). Our research is grounded in the urban quantitative tradition of largesample survey-based studies of local governments. By analyzing the majority of U.S. counties, the study provides generalizability over the range of urban and rural communities
across the nation.
Overall, the findings tend to be consistent with the GM perspective. The analyses show
that involvement in county governance by the GM member-actors considered in this study
is associated with pro-business economic development policies. Owners of commercial
and industrial real estate, local utility companies, and general businesses that focus on the
local market are each positively related to counties’ use of one or more of the pro-business
477
CITY & COMMUNITY
development policies analyzed. Further, consistent with observations of an increasingly
closer relationship between the Republican Party and the CoC in recent years, we find
that the influence of local area CoC on budgeting for business attraction is stronger and
more positive in Republican-leaning counties.
The involvement of private sector GM member-actors in county governance also has
some association with the use of limited-government austerity policies. Linking the GM
framework to the urban austerity literature, we noted two channels by which business actors could foster the use of these policies: indirectly by institutionalizing a context of poor
policy choices that steers localities toward emphasizing growth over redistribution; and
directly because these actors may have vested interests in reducing government’s scope
and diverting resources away from the poor under the assumption that these strategies
promote local area growth. CoC’s involvement in local governance is related to the use of
hiring freezes, selling assets, and layoffs. We also find that where the real estate industry,
utility companies, and local business involvement is present, counties are more likely to
have capped social services, suggestive of efforts to drive out the poor. These findings
provide support for the argument by some researchers that austerity policy is often presented and/or perceived by private sector elites and advocates of neoliberal governance
as signaling favorable business climate where communities are reoriented toward global
competition and away from serving public needs (Kantor 1995; Peck 2014).
To the best of our knowledge, our study of business actors provides the most recent
nation-wide analysis of the GM perspective. The study, however, has limitations as discussed earlier. As with all quantitative survey-based studies of local governments, there is
the potential for response bias and the types of variables that can be constructed are limited. As noted, we tested for responding government officials’ characteristics and found
one model that required a control variable. Still we believe the general consistency of the
findings speaks to the enduring power of the GM perspective.
Although not of theoretical essence to our mission in this paper, we note several findings related to the control variables. Our study shows that localities’ unique pressures
and government attributes influence policy responses in a manner expected from the literature. For example, counties that experience fiscal problems and declines in their tax
bases are significantly more likely to use austerity policies, whereas counties forced into
business recruitment bidding wars are more likely to use competitive growth policies.
Findings for government attributes provide some evidence that larger, higher capacity
governments have had to cut back more over time.
Overall, our study indicates that the GM perspective remains relevant for understanding policy development across the United States. Moreover, the framework can be extended to inform questions about redistribution as Logan and Molotch (1987) posited
long ago and as demonstrated in our findings for cutback-government policy. Where local
GM actors are more influential, U.S. communities are more likely to adopt competitive
economic development policies, limit the growth of social services for the less affluent,
and scale down the public sector. In essence, contemporary urban austerity policy can be
seen as a de facto GM-driven policy.
Notes
1 Molotch (1993) stressed that the focus of the GM perspective is on the place system and localities. It is
applicable to places that have “a government corresponding in jurisdiction to the geographical borders of the
478
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
territory [where] the elite can mobilize the government to bolster economic growth” (Logan and Molotch
1987:35). Intense GM action often occurs outside municipal boundaries (Logan and Molotch 1987:118–119;
O’Neill et al. 2011).
2 At the outset, we stress that although business actors are the core segment of the GM, they do not capture the full range of power relationships, actors, or combinations of growth coalitions across U.S. localities.
Other recent studies also have focused on specific business actors in partial exploration of the GM perspective
(Kimelberg 2011). The contribution of our study is to examine the influence of GM business actors on local
governments’ policies across the United States, which to our knowledge no recent study has explored.
3 Mollenkopf (1989:120) contrasts the two camps, noting that pluralists observe the organization of local
power and influence is “more complicated than any model of direct control by a unified economic or status
elite could allow.”
4 Scholars have long noted that the adoption of growth-oriented policies does not necessarily lead to actual
growth (Krannich and Humphrey 1983; Logan and Crowder 2002; Logan et al. 1997; Schneider 1992; see also
Gotham and Greenberg 2014).
5 It is not clear whether U.S. localities more strongly embraced austerity policies during/after the recession.
This is because to our knowledge no nationally representative studies exist on this point. Although cases such as
Detroit, San Bernardino, and San Diego might be suggestive (Peck 2014), other research underscores why most
localities are not likely to have experienced dramatic change (Lobao et al. 2014; Warner and Clifton 2014).
Nationally, local government employment peaked in August 2008, then went into decline (Dadayan and Boyd
2013) and is now rebounding.
6 The Chamber’s rightward turn became especially pronounced when Thomas J. Donahue became president
in 1997 and it moved further as a stalwart supporter of the Republican Party (Hakim 2016; SourceWatch 2015).
Eighty-nine percent of the organization’s 2012 political campaign contributions went to Republican candidates
(Piaker 2014).
7 The survey-based method is the most common approach for collecting data on large numbers of governments. Studies using this method are also described in Logan and Molotch (1987), Logan and Crowder (2002)
and Logan et al. (1997). Today, the most commonly used scholarly source for local policy data is the surveys
conducted by the International City/County Management Association (ICMA). However, these surveys tend to
have low response rates (typically around 30%) and they underrepresent small cities and counties and particularly rural localities.
8 Although a division of labor between cities and counties exists, functions often overlap (Benton 2002).
Counties generally provide: services that pertain to public welfare, health, highways, police, judicial and legal
affairs, corrections, elections, tax assessment, and collection; services that require county-wide planning responses, such as sewers and solid waste, airports, and transit; and some municipal-like services. Municipalities
are more likely to provide services such as education, fire protection, utilities, and libraries. Both cities and
counties engage heavily in economic development activities and the GM literature is composed of empirical
studies of both governments.
9 Connecticut and Rhode Island do not have county governments.
10 See Logan, Whaley, and Crowder’s (1997) review article for operationalization of the growth machine that is
also consistent with the measures we use here.
11 To measure this variable, officials were asked to indicate how important four problems (loss of federal
revenue; loss of state revenue; state tax, revenue, or expenditure limits; and mandated costs from federal/state
governments) have been to county government’s finances (1=not important; 2=somewhat important; 3=very
important). We summed across these four items to create an index of general financial problems which ranges
from 4-12. The alpha-coefficient for the reliability of this measure=.77.
12 Our analysis initially included percent Hispanic population, but there were no significant relationships
found in any model.
479
CITY & COMMUNITY
13 That is, out of 40 coefficients for officials’ characteristics (five per each of eight models), one coefficient
(responding officials’ education) was statistically significant and this is found only in the model for social services cap.
14 The FE procedure requires intrastate (that is, within group) variation in the dependent variable. Staff
layoff, the dependent variable for Model 2 (Table 3), has no intrastate variation in 13 states, consisting of 245
counties. For that reason, these 245 counties cannot be included in the staff-layoff model.
REFERENCES
Baldassare, Mark, and Georjeanna Wilson. 1996. “Changing Sources of Suburban Support for Local Growth
Controls.” Urban Studies 33(3):459–71.
Benton, J. Edwin. 2002. Counties as Service Delivery Agents. Westport, CT: Praeger.
Clark, Cal, and B. Oliver Walter. 1991. “Urban Political Cultures, Financial Stress, and City Fiscal Austerity
Strategies.” The Western Political Quarterly 44(3):676–97.
Clark, Terry Nichols. 2000. “Old and New Paradigms for Urban Research: Globalization and the Fiscal Austerity
and Urban Innovation Project.” Urban Affairs Review 36(1):3–45.
Clingermayer, James C., and Richard C. Feiock. 1990. “The Adoption of Economic Development Policies by
Large Cities: A Test of the Economic, Interest Group, and Institutional Explanations.” Policy Studies Journal
18(3):539–52.
———. 2001. Institutional Constraints and Policy Choice: An Exploration of Local Governance. Albany, NY: SUNY
Press.
Cochrane, Allan. 1999. “Redefining Urban Politics for the Twenty-First Century.” Pp. 109–24 in The Urban Growth
Machine: Critical Perspectives Two Decades Later, edited by Andrew E. G. Jonas and David Wilson. Albany, NY:
State University of New York Press.
Dadayan, Lucy, and Donald J. Boyd. 2013. The Depth and Cuts in Local Government Employment is Unprecedented. Albany, NY: Rockefeller Institute, The State University of New York. Retrieved January 4, 2016
(http://www.rockinst.org/pdf/government˙finance/2013-01-09-State-Local˙Government˙Employment.pdf).
Dahl, Robert A. 1961. Who Governs? Democracy and Power in an American City. New Haven, CT: Yale University
Press.
DiGaetano, Alan, and John C. Klemanski. 1991. “Restructuring the Suburbs: Political Economy of Economic
Development in Auburn Hills, Michigan.” Journal of Urban Affairs 13:137–58.
Dillman, Don. 1978. Mail and Telephone Surveys: The Total Design Method. New York, NY: John Wiley.
Domhoff, G. William. 1990. The Power Elite and the State: How Policy is Made in America. Hawthorne, NY: Aldine de
Gruyter.
Donald, Betsy, Amy Glasmeier, Mia Gray, and Linda Lobao. 2014. “Austerity in the City: Economic Crisis and
Urban Service Decline?” Cambridge Journal of Regions, Economy, and Society 7(1):3–15.
Donovan, Todd, and Max Neiman. 1992 “Citizen Mobilization and the Adoption of Local Growth Control.” The
Western Political Quarterly 45(3):651–75.
Dunlap, Riley, and Aaron M. McCright. 2013. “The Climate Change Denial Campaign.” Scholars Strategy Network. Retrieved November 20, 2014 (http://www.scholarsstrategynetwork.org/sites/default/files/
ssn˙key˙findings˙dunlap˙and˙mccright˙on˙climate˙change˙denial.pdf).
Dye, Thomas R. 1976. Who’s Running America? Englewood Cliffs, NJ: Prentice-Hall.
Feiock, Richard C. 1991. “The Effects of Economic Development Policy on Local Growth.” American Journal of
Political Science 35(3):643–55.
Friedland, Roger, and Donald Palmer. 1984. “Park Place and Main Street: Business and the Urban Power Structure.” Annual Review of Sociology 10:393–416.
Gotham, Kevin Fox, and Miriam Greenberg. 2014. Crisis Cities: Disaster and Redevelopment in New York and New
Orleans. New York, NY: Oxford University Press.
Hacker, Jacob S. 2004. “Privatizing Risk Without Privatizing the Welfare State: The Hidden Politics of Social
Policy Retrenchment in the United States.” American Political Science Review 98(2):243–60.
Hakim, Danny. 2016. “U.S. Chamber Out of Step with Board.” New York Times, June 6, 2016, B2.
Jessop, Bob, Jamie Peck, and Adam Tickell. 1999. “Retooling the Machine: Economic Crisis, State Restructuring,
and Urban Politics.” Pp. 141–59 in The Urban Growth Machine: Critical Perspectives Two Decades Later, edited by
Andrew E. G. Jonas and David Wilson. Albany, NY: State University of New York Press.
480
THE GROWTH MACHINES’ INFLUENCE ON U.S. COMMUNITIES
Jonas, Andrew, and David Wilson. 1999. “The City as Growth Machine: Critical Reflections Two Decades Later.”
Pp. 3–18 in The Urban Growth Machine: Critical Perspectives Two Decades Later, edited by Andrew E. G. Jonas and
David Wilson. Albany, NY: State University of New York Press.
Kantor, Paul. 1995. The Dependent City Revisited: The Political Economy of Urban Development and Social Policy. Boulder, CO: Westview Press.
Kerstein, Robert. 1993. “Suburban Growth Politics in Hillsborough County: Growth Management and Political
Regimes.” Social Science Quarterly 74(3):614–30.
Kirkpatrick, L. Owen, and Michael P. Smith. 2011. “The Infrastructure Limits to Growth: Rethinking the Urban
Growth Machine in Times of Fiscal Crisis.” International Journal of Urban and Regional Research 35(3):477–503.
Kimelberg, Shelley McDonough. 2011. “Inside the Growth Machine: Real Estate Professionals on the Perceived
Challenges of Urban Development.” City & Community 10(1):76–99.
Krannich, Richard, and Craig Humphrey. 1983. “Local Mobilization and Community Growth: Toward an Assessment of the ‘Growth Machine’ Hypothesis.” Rural Sociology 48: 60–81.
Lobao, Linda, and Lazarus Adua. 2011. “State Rescaling and Local Governments’ Austerity Policies Across the
USA, 2001–2008.” Cambridge Journal of Regions, Economy and Society 4(3):419–35.
Lobao, Linda, Lazarus Adua, and Gregory Hooks. 2014. “Privatization, Business Attraction, and Social Services
Across the United States: Local Governments’ Use of Market-Oriented, Neoliberal Policies in the Post-2000
Period.” Social Problems 61(4):644–72.
Logan, John R., and Kyle D. Crowder. 2002. “Political Regimes and Suburban Growth, 1980–1990.” City &
Community 1(1):113–35.
Logan, John R., and Harvey L. Molotch.1987. Urban Fortunes: The Political Economy of Place. Berkeley, CA: University of California Press.
Logan, John R., Rachel B. Whaley, and Kyle Crowder. 1997. “The Character and Consequence of Growth
Regimes: An Assessment of 20 Years of Research.” Urban Affairs Review 32(5):603–30.
Lyon, Larry, Lawrence G. Felice, M. Ray Perryman, and E. Stephen Parker. 1981. “Community Power and Population Increase: An Empirical Test of the Growth Machine Model.” American Journal of Sociology 86(6):1387–
400.
Maher, Craig S., and Steven C. Deller. 2007. “Municipal Responses to Fiscal Stress.” International Journal of Public
Administration 30: 1549–572.
Mills, C. Wright. 1956. The Power Elite (New Edition). New York, NY: Oxford University Press.
Mizruchi, Mark S. 2013. The Fracturing of the American Corporate Elite. Cambridge, MA: Harvard University Press.
Mollenkopf, John. 1989. “Who (or What) Runs Cities, and How?” Sociological Forum 4(1):119–37.
Molotch, Harvey. 1976. “The City as a Growth Machine: Toward a Political Economy of Place.” American Journal
of Sociology 82(2):309–32.
———. 1993. “The Political Economy of Growth Machines.” Journal of Urban Affairs 15(1):29–53.
———. 1999. “Growth Machine Links: Up, Down, and Across.” Pp. 247–65 in The Urban Growth Machine: Critical
Perspectives Two Decades Later, edited by Andrew E. G. Jonas and David Wilson. Albany, NY: State University of
New York Press.
Nocera, Joe. 2014. “Chamber of Commerce Lost Its Way in Right Turn.” New York Times. Retrieved November
20, 2014 (http://nyti.ms/1uoXV2o).
Oakley, Deirdre, and John R. Logan. 2007. “A Spatial Analysis of the Urban Landscape: What Accounts for
Differences Across Neighborhoods.” Pp. 215–30 in The Sociology of Spatial Inequality, edited by Linda Lobao,
Gregory Hooks, and Ann Tickamyer. Albany, NY: State University of New York Press.
O’Neill, Karen M., Thomas Rudel, and Melanie H. McDermott. 2011. “Why Environmentally Constrained
Towns Choose Growth Controls.” City & Community 10(2):111–29.
Peck, Jamie. 2012. “Austerity Urbanism: American Cities Under Extreme Economy.” City 16(6):626–55.
———. 2014. “State Failure, Municipal Bankruptcy and the Crisis of Fiscal Federalism in the United States.”
Cambridge Journal of Regions, Economy, and Society 7(1):17–44.
Peterson, Paul E. 1981. City Limits. Chicago, IL: The University of Chicago Press.
——— 1995. The Price of Federalism. Washington, DC: Brookings Institution Press.
Piaker, Zachery. 2014. “U.S. Chamber of Commerce.” Retrieved November 30, 2016 (http://www.factcheck.
org/2014/02/u-s-chamber-of-commerce-2/).
Reese, Laura A., and Raymond A. Rosenfeld. 2002. The Civic Culture of Local Economic Development. Thousand
Oaks, CA: Sage.
Schneider, Mark. 1992. “Undermining the Growth Machine: The Missing Link Between Local Economic Development and Fiscal Payoffs.” The Journal of Politics 54(1):214–30.
481
CITY & COMMUNITY
Schram, Sanford F. 2006. Welfare Discipline: Discourse, Governance, and Globalization. Philadelphia, PA: Temple.
Scorsone, Eric A., and Christina Plerhoples. 2010. “Fiscal Stress and Cutback Management Amongst State and
Local Governments: What Have We Learned?” State and Local Government Review 42:176–87.
SourceWatch. 2015. “U.S. Chamber of Commerce.” Retrieved July 3, 2016 (http://www.sourcewatch.org/
index.php?title=U.S.˙Chamber˙of˙Commerce).
Starke, Peter. 2006. “The Politics of Welfare State Retrenchment: A Literature Review.” Social Policy and Administration 40(1):104–20.
Stone, Clarence N. 1989. Regime Politics Governing Atlanta, 1946–1988. Lawrence, KS: University of Kansas Press.
——— 2003. “Power and Governance in American Cities.” Pp. 126–47 in Cities, Politics, and Policy: A Comparative
Analysis, edited by John P. Pelissero. Washington, DC: CQ Press.
Stone, Clarence N., and Heywood T. Sanders. 1987. The Politics of Urban Development. Lawrence, KS: University
of Kansas Press.
Sun, Jinping. 2010. “Budget Strategy: A Survey of California County Governments.” The California Journal of
Politics and Policy 2(1):1–17.
Turner, Robyne S. 1992. “Growth Politics and Downtown Development: The Economic Imperative in Sunbelt
Cities.” Urban Affairs Quarterly 28(1):3–21.
Vogel, Ronal K., and Bert E. Swanson. 1989. “The Growth Machine Versus the Anti-Growth Coalition: The Battle
for Our Communities.” Urban Affairs Review 25(1):63–85.
Warner, Mildred E. 2006. “Market-Based Governance and the Challenge for Rural Governments: U.S. Trends.”
Social Policy and Administration 40(6):612–31.
Warner, Mildred, and Judith Clifton. 2014. “Marketization, Public Services, and the City: The Potential for
Polanyian Counter-Movements.” Cambridge Journal of Regions, Economy, and Society 7(1):45–61.
Whitt, Allen J. 1979. “Toward a Class-Dialectic Model of Power: An Empirical Assessment of Three Competing
Models of Political Power.” American Sociological Review 44(1):81–99.
482
US companies and political influence: how
business can read the government
landscape better
Michael Greiner and Jaegul Lee
he Watergate scandal of the 1970s dramatically changed politics in the USA. Where
government relations had once been a staid process of powerful people negotiating
policy with each other behind closed doors – still much the way it is done in many
other countries – public outrage over the scandal fueled reforms that opened up the policy
process to transparency as well as growing cynicism on the part of the voters regarding
the honesty and integrity of those in power. These changes dramatically increased the
competitiveness of the American political scene. To further complicate matters, just at the
time the rules of the game of political advocacy were changing, the size of the federal
government and its impact on business were growing. Based upon growing public
concern, government moved from pure “economic regulation,” such as trade policy and
securities laws, to more burdensome “social regulations,” such as environmental and
consumer protection. These changes were occurring at the same time that structural
changes in the American economy were disrupting workers and further stoking their anger
and frustration. It would not be unreasonable to say that the 1970s and 1980s represented a
watershed period in the American relationship between business and government.
T
Michael Greiner is based at
the Department of
Management, Oakland
University School of
Business Administration,
Rochester, Michigan, USA.
Jaegul Lee is based at the
Department of
Management, Wayne State
University, Detroit,
Michigan, USA.
In response to this unsettled environment, businesses dramatically increased their investment
in government relations while also changing their approach to follow new rules. Where once
business leaders met with government officials behind closed doors, now firms had to
establish political action committees and actively work to frame the issues in the public’s
consciousness that affect the business. Where once managers saw the government relations
function as largely a marketing effort, now firms develop an overall political strategy and hire
professional lobbyists to help them achieve it. Despite its importance, many executives dislike
political activism; empirical research has been unsatisfying, failing to even demonstrate
whether political activity is a good investment for business (Hadani and Schuler, 2013).
The US political environment appears to be again undergoing rapid and dramatic change that
has clear implications for business. Court decisions have made it possible for corporations to
have even greater impact on the political process than in the past, while requiring strict
adherence to complex rules. Regulatory uncertainty has made it difficult for businesses to
assess the risk of entering potential new markets. For the first time in a generation, the
consensus view about trade has been under attack. Income inequality has increased public
hostility toward top executives, and a populist revolt against capitalism threatens. Given these
circumstances, it is not surprising that executives view government with apprehension.
In this article, we provide a map for executives, one that details the landscape businesses
must negotiate in their effort to manage the challenge that government presents. This map
DOI 10.1108/JBS-09-2019-0178
VOL. 42 NO. 1 2021, pp. 69-75, © Emerald Publishing Limited, ISSN 0275-6668
j JOURNAL OF BUSINESS STRATEGY j PAGE 69
has been subjected to empirical testing, and our research supports these ideas. We
describe a step-by-step procedure that businesses can use to assess the political
environment. In this way, we hope to provide some clarity to executives who look at
government developments with concern.
Mapping the political landscape
Think of the political environment as a challenging terrain that politicians, including
legislators, regulators and other public officials, as well as businesses seeking to influence
them, must negotiate. In crossing this landscape, politicians must consider various
topographical features that create barriers to their passage. These topological features are
based upon the motivation of the politicians, namely their ideology, the political trends of
their constituency and their prior relationships. As the basic features motivating the behavior
of politicians, these three features constrain their conduct. If politicians’ actions are
constrained by these features, then these features will also limit the potential results
businesses can achieve. However, businesses can also influence these features. If a
business is successful in changing one of these features, then it forces the politician to act
in a different way than the politician might have been originally inclined to, often in a way
that is more beneficial to the business. Successful efforts to remake the landscape are the
essence of successful political advocacy.
The starting point for this analysis is certainly the politician’s ideology. Research has shown
that by far the most important motivating factor that induces a candidate to run for office is
an ideological interest in one ...
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
