The Political Consequences of Big-Box Retail: Wal-Mart Target, Costco, and Political Efficacy

 
Brown, Lawrence, Sokhey

  The Political Consequences of Big-Box Retail: Wal-Mart
            Target, Costco, and Political Efficacy

                                         David S. Brown
                                       Associate Professor
                               Institute of Behavioral Science and
                                 Department of Political Science
                                University of Colorado at Boulder
                                     dsbrown@colorado.edu

                                       Duncan Lawrence
                                         PhD Candidate
                                 Department of Political Science
                                University of Colorado at Boulder
                                Duncan.Lawrence@colorado.edu

                                         Anand Sokhey
                                      Assistant Professor
                                 Department of Political Science
                                University of Colorado at Boulder
                                  Anand.Sokhey@colorado.edu

Paper prepared for the annual meeting of the Western Political Science Association, San
Antonio, TX, April 21-23, 2011.

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INTRODUCTION

       Over the last few decades, big-box retail has become the dominant form of

economic activity in the United States, and in a number of countries throughout the

world. In the US, the retail sector employs approximately 15.5 million workers, more

than in all of manufacturing (Lichenstein 2009; L. 202). Wal-Mart itself regularly tops

the Forbes Fortune 500 list in terms of total revenue, beating out Exxon Mobile

depending on the price of oil. As the country‘s largest retailer and revenue generating

concern, Wal-Mart has over 6,000 stores in the US, employing approximately 20 times

the number of workers as the biggest oil company (Lichenstein 2009; L. 202). Target--

number 33 on the Fortune 500 in 2007--has over 1,753 stores in the US (through 2007),

with Costco coming in at 414 warehouses (through 2010). In short, the way we buy

things today differs markedly from how business was conducted 30-40 years ago.

Regular interaction with proprietors is for many a thing of the past. Instead, purchases

are made during all hours of the day and night in large, sprawling warehouses located

miles from the city‘s center. Transactions in this new world are impersonal and rarely

involve any meaningful communication between buyer and seller.

       At the same time, the local business class has experienced strain in many

communities. For example, during Wal-Mart‘s first decade, the state of Iowa alone lost

555 groceries, 298 hardware stores, 293 building supply stores, 158 women‘s apparel

shops, 116 drugstores, and 153 shoe stores (Stone 1995; cited in Lichenstein 2009).

Whether going out of business, experiencing a serious decline in revenue, or having to

work the extra hours to compete in the new 24 hour-day associated with big-box retail,

small businessmen and women are increasingly unable to participate in social, civic, or

philanthropic organizations. As their numbers dwindle or their time devoted to civic

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matters declines, many of the organizations and services communities took for granted

several decades ago are disappearing (Putnam 2000).

       Previous work establishes an empirical connection between the presence of big-

box retail – as operationalized by Wal-Mart stores – and participation in civic

organizations and voter turnout. Specifically, research by Goetz et al. establishes a

significant negative correlation between Wal-Mart stores and political participation

(Goetz and Rupasingha 2006). Yet others remain skeptical that big-box retail has a

salient influence on politics. Examining Wal-Mart store locations and membership in

civic an social organizations, Carden et al. (2009) find little evidence of a relationship.

Although they find Wal-Mart stores are correlated with declining voter turnout, they

find no evidence that Wal-mart has a negative or positive effect on membership in civic

organizations.     Consequently, the current state of the empirical work can best be

described as inconclusive.

       To move the debate forward, we broaden the examination to other retail outlets

(Target and Costco), while sharpening the focus on a key facet of membership in

associational activity and political participation: political efficacy. And, given the usual

narrative of big-box retail battles and the contemporary political climate, we also

examine the correlation between big-box retail and attitudes toward labor unions. In

the analysis that follows, we merge an expanded data set tracking the existence of Wal-

Mart, Target, and Costco stores at the county level to an ANES panel study that tracks

political efficacy and attitudes toward labor unions between 2000 and 2004. We then

estimate whether the presence of a new store influences survey responses to questions

about political efficacy and attitudes towards unions, utilizing a clean, individual-level,

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―before and after‖ design. To anticipate our results, we find big-box retail has real effects

on efficacy and affect toward labor, but that not all big-box retail is the same.

       The paper proceeds as follows: In section I, we review both the theoretical and

empirical literature on big-box retail and political participation, and in section II we

present the data and models. Section III reports our results and provides several

robustness checks. Finally, sections IV and V discuss the implications of the results and

end with some concluding remarks.

PREVIOUS WORK

Theory

       The standard story emerging from the popular press is as follows: when a big-box

retailer comes to town, normal patterns of contact between individuals are disrupted.

Consequently, lines of communication among peers can be disrupted, reducing the

ability for individuals to coordinate and exchange information.           Ultimately, these

developments degrade both civic engagement and political activity. For those who argue

that political participation is based on some form of rational calculation made by

individuals, that lack of coordination and communication makes it difficult to sanction

individuals who fail to contribute to the collective good. Big-box retail‘s disruptive

presence reduces participation in civic and social groups: groups that can encourage

individuals to vote—either through selective benefits or sanctions. In communities

where citizens no longer interact on the city sidewalks or in public halls, the fabric of

society is torn, producing a more disaffected and disempowered electorate.

       The story above connects directly to two prominent literatures in political science

and sociology. The first seeks to understand the impact increasing economic scale in

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retail establishments—or capitalism more generally—has on social activity and political

participation. The second directly addresses the relationship between civic engagement

and voter turnout. Boiled down to its essence, the literature on capitalism‘s impact

seeks to understand how an evolving consumer behavior affects social interaction. In

turn, political scientists and sociologists have been interested in how those changes

affect politics. The argument is fairly straight forward: as retail enterprise moves away

from more centralized business districts, opportunities to interact with others diminish,

disrupting established forms of communication. Stan Humphries refers to a literature

called ―New Urbanism‖ that warns against the loss of community inherent in the move

towards big box retailers (Humphries 2001). Although not always referring to big-box

retailers specifically, much of the New Urbanism literature emphasizes suburban sprawl

and how it influences social life and political participation (Verba and Nie 1972; Berger,

Berger et al. 1973). As commercial activity becomes geographically dispersed, social

networks are interrupted or broken altogether, leaving individuals increasingly isolated.

Without central gathering places or community ‗focal‘ points, the social life of a

community is forever changed. Derivatives of the argument are found in accounts of

Wal-Mart‘s impact on communities (Dicker 2005; Mitchell 2006). Still, connecting the

dots between big-box retail, its economic impact, and the political health of a

community is incomplete. There are, however, more concrete reasons to believe big-box

retail has an impact. We argue that an important connection tying big-box retail to

political participation involves its impact on the local business class. Put simply, when a

local business class is under siege, philanthropy, political organization, and a range of

public goods are put at risk. Under these conditions lower political participation (lower

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voter turnout) and civic engagement (decreasing participation in civic and social

organizations) are the consequence.

       The other prominent stream of previous work involves civic and social

organizations and their relationship to political participation (Almond and Verba 1963;

Scoble 1968; Olsen 1972; Buchanan 1978; Denney 1979; Uhlaner 1986; Uhlaner 1989;

Coleman 1990; Knack 1992; Verba et al. 1995; Burns et al. 2001). For these scholars,

membership in civic and social organizations teaches individuals how to be effective

advocates for a range of important causes.         As their experience grows, their self-

confidence (what is often referred to as internal political efficacy) increases, raising

their expectations that their actions in the community matter. Perhaps the most well-

known passage comes from Almond and Verba‘s classic A Civic Culture:

        ―The belief in one‘s competence is a key political attitude. The self-confident
        citizen appears to be the democratic citizen. Not only does he think he can
        participate, he thinks others ought to participate as well. Furthermore, he does
        not merely think he can take part in politics; he is likely to be more active‖
        (Almond and Verba 1963; p. 257 quoted in Kahne 2006).

       In addition to an individual‘s level of internal political efficacy, attitudes towards

political participation are influenced by views citizens have on the responsiveness of

their representatives or government bureaucrats. Do individuals feel as though they

have a voice in government or do their political representatives care about their views?

Although the empirical relationship between external efficacy and political participation

is not as well established (Kahne 2006), there are good theoretical reasons to expect the

connection between big-box retail and external efficacy could be strong. Store openings

usually are well-advertised and discussed in all communities.             Central to those

discussions are the exact location of the store, whether the city has granted the store any

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tax breaks or provided subsidies, and whether the store is needed or wanted by the

community in the first place. Decisions by local officials to encourage or prohibit entry

of big-box retail can dominate the pages of the local paper and often lead to standing-

room-only city council meetings (Ortega 1998). Whether a local community‘s interests

are reflected in the final outcome--either a new store comes to town or is forced to look

elsewhere--has the potential to figure prominently in an individual‘s overall assessment

of ―whether politicians care about people like themselves.‖

       Some scholars marry rational choice theory to the importance of social and civic

organizations, arguing that smaller groups (local party affiliates, the PTA, Rotary Club,

etc.) can level sanctions on members who do not tow the party line or support

candidates that benefit the group. As Stephen Knack (1992) argues, declines in voter

turnout are not necessarily due to changing characteristics of individuals in the

population. Rather, as society changes—more mobility, declining face-to-face contact—

the sanctions and incentives that once were in place to generate higher levels of turnout

are no longer present.

        We argue that Big-box retail‘s influence on political participation can be linked to

its impact on the business class. Big-box retailers centralize entrepreneurial activity. In

effect, they take advantage of scale economies: once the infrastructure is developed for

general merchandise (clothing, sports equipment, etc.,), the knowledge acquired in

those enterprises is used to develop expertise in pharmaceuticals and groceries.

Entrepreneurial opportunities in regions dominated by big-box merchandisers, as a

result, become relatively limited. Consequently, young entrepreneurial talent either

leaves the area or is reluctant to set up shop. To the extent that big-box retailers

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accelerate an entrepreneurial brain drain, individuals who would otherwise play an

important role in political activity are absent.

       In addition to an entrepreneurial brain drain, big box retailing can have a very

subtle but no less important impact on the ability for store owners and others to

participate in politics. Although big-box stores can often lead to the very rapid demise

of many smaller retailers, they can have a more subtle yet equally profound impact.

Most big-box store‘s ability to keep store hours that generally extend past 10:00pm puts

increasing pressure on smaller establishments to keep longer hours.        This means

proprietors must either extend the number of hours they work, or find qualified help.

Suddenly, the available time to attend a Rotary Club function or school board meeting

decreases, robbing those organizations of important voices that would have otherwise

played an important role—both financially and otherwise—in their activities.

       Finally, there is an additional mechanism tying big-box retail to less political

participation in terms of associational activity and voter turnout. A common theme

running throughout commentary on Wal-Mart is its stance on union activity. Wal-

Mart‘s aggressive tactics towards unions can have an important effect on all union

activity. According to a figure quoted by Lichenstein, Wal-Mart was responsible in some

way for the closure of 13,000 traditional supermarkets and the bankruptcy of 25

regional grocery chains between 1992 and 2003 (Lichtenstein 2009; L. 2945). Given

that one of the most powerful unions in the country is the United Food and Commercial

Workers International Union (UFCW), many potential sites to organize were in effect

taken away. In addition, the UFCWs power to bargain on behalf of its workers is

circumscribed when other employers avoid paying union wages and benefits.

Companies that do employ union workers and compete with Wal-Mart are increasingly

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forced to ask for concessions that erode union wages and benefits. The grocery clerk

strike of 2003 in Southern California was in part a failure because of the pressure big-

box grocery chains were placing on regular supermarket chains and their workers

(Lichtenstein 2009). In starker terms, the inability to organize in the largest retailer has

severely circumscribed UFCW activity which, in turn, can stunt the development of

associational activity.

       To summarize, there are a number of mechanisms that link big-box retail to

declining associational activity and political participation.     From more sociological

theories that posit a disruption in communications and associational linkages, to voting

turnout models based on individuals‘ political efficacy, to elite models that suggest the

glue that holds local communities together through organizational and philanthropic

work, to the direct impact of Wal-Mart‘s anti-labor policy, there are reasons to think

that the big-box revolution has produced declines turnout, decreases in political efficacy,

and declines in political participation more generally. Over the last ten years, empirical

work has begun to test whether big-box retail influences the theoretical mechanisms

described above.

Empirical Work

       Despite the large amount of press coverage and attention in popular media, a

relatively small amount of work has appeared in the scholarly press and journals. Voter

turnout has received extensive attention over the last few decades primarily for two

reasons, one theoretical the other empirical. Theoretically, political scientists wonder

why people vote. This is a paradoxical question since some argue it is not ‗rational‘ for

people to do so. Empirically, the United States has witnessed a secular decline in voter

turnout, causing concern among those who argue an active and engaged citizenry forms

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the bedrock of a country‘s democracy. From the classic 1980 book ―Who Votes?‖ by

Raymond E. Wolfinger and Stephen J. Rosenstone to others that followed (Nagler 1991;

Nagler 1992; Burden 2000; Highton 2000; Gimpel, Morris et al. 2004; Nardulli 2005;

Geys 2006; Highton 2008), a substantial empirical effort seeks to explain why

individuals participate in elections. The universe of explanations ranges from

socioeconomic characteristics of the individual (e.g., race, sex, income, education, age),

to characteristics of the individual‘s environment (e.g., stability of the population

(transient/stable), social networks, social capital).     Mechanics of voting have also

received attention – i.e., the degree to which registration laws make voting easy. In a

recent review of the literature, 83 empirical studies were surveyed in an attempt to

identify a set of causes upon which most can agree (Geys 2006). In that study, three

classes of explanations form the basis of what Benny Geys calls a ‗core‘ model of voting

turnout: the stability of the population (transient/stable); whether the election is close;

and finally, the pre-existing voting habits of the population.

       Work that directly examines big-box retail‘s impact on political participation is in

its infancy. Although Kenneth Stone (Stone 1995) conducted some of the first work on

Wal-Mart in the mid-1990s, it has only been in the last 10 years that a growing number

of statistical studies have begun to appear. Emek Basker has been responsible for kick-

starting much of the empirical work by authoring a number of studies using a data set

she had constructed that recorded where and when Wal-Mart stores were opened in the

United States (1972-2001). With that data, economists have tried to understand the

impact Wal-Mart has on wages, unemployment, prices, and social capital (Basker 2005;

Basker 2005; Neumark, Zhang et al. 2005; Goetz and Rupasingha 2006; Goetz and

Swaminathan 2006; Basker 2007; Carden, Courtemanche et al. 2009).

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       Although still in its infancy, the empirical literature on Wal-Mart and its

influence on politics (usually in terms of social capital and voter turnout), stands at an

important cross-roads. Some work finds a negative relationship between Wal-Mart and

social capital while there is evidence that no empirical relationship exists between the

big-box behemoth and membership in civic and social organizations. Goetz et al. have

shown in a collection of studies on the subject that there is a negative relationship

between the presence of Wal-Mart and political participation (measured by voter

turnout and membership in civic organizations). In a 2006 study, they find a negative

relationship between Wal-Mart presence and the number of civic associations, voter

turnout in the 2000 presidential election, number of tax-exempt organizations, and

participation in the 2000 Census. Carden et al. employ similar data to show there is no

relationship between Wal-Mart and the accumulation of social capital. Combining US

Census data on civic organizations with the DDB Needham Survey and the Saguaro

Survey on Social Capital, the authors conclude there is no systematic effect. Subjecting

the Goetz and Rupasingha findings to a rigorous test, they find that once a slightly

different independent variable is used (the log of Wal-Mart years per 10,000

population) and state fixed-effects are introduced into the regression, Goetz and

Rupasingha‘s results go away. It is important to note, however, that although there is no

relationship between Wal-Mart and membership in civic and social organizations, they

do find there is a negative and statistically significant relationship between their

measure of Wal-Mart and voter turnout. Hopkins (2004), using zip-code level retail

data, finds that the presence of large retailers diminishes the likelihood of various forms

of political participation. As work progresses along these lines it is becoming

increasingly clear that one‘s conclusions depend fundamentally on the econometric

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technique used and the specification of the model.             Consequently, the empirical

literature risks devolving into a debate about econometric techniques where often the

latest estimator determines the outcome.

       To move the debate forward, we focus our attention on two causal mechanisms

for which the ANES panel from 2000-2004 has useful data: two measures of external

political efficacy, and an affective thermometer measuring feelings toward labor unions.

Importantly, we also expand the investigation of big-box retail beyond what has been

the only subject of empirical scrutiny to day – i.e., Wal-Mart.

           Hypothesis 1: in counties where either a Wal-Mart, Costco, or Target open a
           store in 2002, 2003, or 2004, an individual’s sense of political efficacy will
           decline.

           Hypothesis 2: in counties where either a Wal-Mart, Costco, or Target open a
           store in 2002, 2003, or 2004, individuals will lower their evaluation of labor
           unions.

MODEL AND DATA

       We merged data on Wal-Mart, Costco, and Target stores with an American

National Election Survey (ANES) panel study conducted in 2000 and 2004. Our aim is

to examine whether individual responses to a battery of questions on political efficacy

and labor unions (from 2000 to 2004) depend on receiving a ― treatment‖ – that is, on

having a Wal-Mart, Target, or Costco open in the (survey respondent‘s) county during

the intervening time period.

       The research design is as follows:

Pre Big-Box Retail Exposure
Measures on panelists             Big-Box retail exposure       Post Big-Box Retail
                                                                  Measures on panelists.

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       Because Wal-Mart does not choose its locations randomly, we adopted

instrumental variables estimation when examining Wal-Mart‘s impact on individual

attitudes.    Economists have relied on a variable that records the distance from

Bentonville as an instrument to obtain unbiased estimates (Neumark, Zhang et al. 2005;

Goetz and Rupasingha 2006; Goetz and Swaminathan 2006). We follow that practice

in equations including Wal-Mart store openings as a regressor. We also use matching to

test the robustness of our Wal-Mart estimates, as well as to estimate the impact Target

and Costco stores have on political efficacy and attitudes towards unions.

Instrument

Since big-box stores do not locate in random fashion, endogeneity is a concern: if Wal-

Mart stores appear primarily where political activity is low, any correlation between

Wal-Mart and political efficacy would be spurious in the sense that Wal-Mart would not

be the cause, it would merely be the symptom. Since the mid to late-1980s when local

challenges to Wal-Mart first materialized, high levels of social capital may have enabled

some cities to keep Wal-Mart out. Under that scenario, we would observe Wal-Marts

only in counties with low levels of social capital, generating biased OLS estimates. In

order to obtain unbiased estimates of big-box retail‘s impact on a variety of

phenomenon, scholars have established a number of different ways to account for the

selection criteria Wal-Mart uses to locate a store. In a recently published paper in Social

Science Quarterly, Stephan J. Goetz and Hema Swaminathan use a number of

socioeconomic variables in a selection equation to predict the probability that Wal-Mart

will locate in a given county. Using population density, average commute time, number

of female-headed households, and the percentage of the population with only high

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school degrees, the two scholars attempt to account for the endogeneity between store

location decisions and county poverty rates (Goetz and Swaminathan 2006).

       Questioning the assumptions that allow Goetz and Swaminathan to identify their

system of equations, Neumark et al. offer an alternative (Neumark, Zhang et al. 2005).

By all accounts (even that of Sam Walton himself), Wal-Mart expanded during the 70s,

80s, and 90s by building stores in close proximity to already existing Wal-Marts,

saturating areas before moving on to outlying areas. Using that information, Neumark

and associates propose interacting time with distance from Bentonville, Arkansas to

identify the system of equations they use to generate instrumental variable estimates.

The Neumark study, in turn, has been criticized by Emek Basker who argues that the

instrument used (distance from Bentonville) can be correlated with many of the

dependent variables economists are interested in: prices, employment, and income.

Carden et al. note that some previous empirical findings are not stable with respect to

different specifications of the instrumental variable models: introducing a non-linear

term (distance squared) reduces the magnitudes of the coefficient and the statistical

significance (below all acceptable levels) of the Wal-Mart variable. Consequently, we

evaluate the stability of the results with respect to distance as the instrument. In

addition to demonstrating the stability of the results with respect to the instrument, we

use matching to show the results are not dependent on our choice of instrument and

specification of the model.

       For most of the analysis, we use the distance of the county‘s geographic centroid

from Bentonville as the instrument. A good instrument for the location of Wal-Mart

stores must meet the following two criteria: 1) it is a variable correlated with the location

decision of Wal-Mart executives; 2) it is not correlated with the errors when regressing

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the dependent variable on Wal-Mart. The distance from Bentonville describes the basic

pattern of diffusion that characterizes Wal-Mart‘s early growth in the 70s and 80s. The

first store was established in Rogers, Arkansas in 1962.        From there, Sam Walton

managed his empire by frequent visits to each store by car. Eventually, Walton obtained

his pilot‘s license, allowing him to extend the empire into Texas, Oklahoma, Missouri,

and Kansas (Ortega 1998). Thereafter, expansion evolved in close proximity to large

distribution centers.      Walton attempted to postpone establishing large distribution

centers to the fullest extent possible, keeping a larger percentage of the merchandise in

the store or in route (Ortega 1998). To follow that strategy, stores were established in

locations that were adjacent to already existing stores, cutting down transportation and

warehousing costs. Consequently, the growth of the Wal-Mart empire started in the

middle of the country and spread outward in all directions.

       Therefore, the distance from Bentonville serves as a good predictor of both the

timing and location of a new store. The distance from Bentonville is also uncorrelated

with social capital and political participation – there is no reason to suspect that voter

turnout is distributed in concentric circles drawn around Bentonville: it is unlikely that a

county 200 miles East of Bentonville will have equal levels of turnout to a county 200

miles to the West. The correlation between distance and voter turnout in the 2004

elections is low (0.14). To estimate the association between Wal-Mart‘s presence in a

county with voter turnout and a number of different proxies that capture various forms

of social capital, we use the following system of equations:

       (1) Efficacy2004 = a + b1(Wal-Mart2002-2004) + b2(Individual and Contextual
              Controls) + e1

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         (2) Wal-Mart2002-2004 = a + b1(Distance from Bentonville) + b2(Individual and
               Contextual Controls) + e2

         Although we understand Costco and Target do not randomly assign stores, there

is less concern that their decisions to locate are related to the dependent variable.

However, we use matching to account for any endogeneity that might exist between

political efficacy, attitudes towards unions, and the location of Target and Costco stores. 1

RESULTS

In Table 1, we report the probability of agreeing with the following two statements: 1)

―Public officials don't care much what people like me think‖; and 2) ―People like me

don‘t have any say about what the government does.‖ Given the way both statements

are framed, a positive response is indicative of less (external) political efficacy.

Estimates reflect the effect of being ―exposed‖ to a new Wal-Mart(s) in 2002, 2003, and

2004, controlling for the placement of Wal-Mart (via the instrument of distance from

Bentonville), pre-treatment values on the dependent variable (i.e., agreeing with this

item in 2000), and a host of individual and contextual characteristics (including the

number of ―superstores‖ in a respondent‘s county before 2001). We find that the results

do not depend on the use of instrumental variables. A simple probit model without the

use of a second equation indicates the result is stable to the specification of the model.

When Wal-Mart comes to town, we see a systematic shift of political attitudes: the

probability of agreeing with the above two statement increases, even after having

1
 Hopkins (2004) uses a similar matching procedure to evaluate the robustness of results indicating that large retailer
presence decreases political participation.

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controlled for how that question was answered in the 2000 survey. The probit results

for the ―People like me don‘t have any say...‖ question is significant at the .10 level.

                                          -Table 1 about here-

        The same results hold when using matching instead of the instrumental variables

framework. In Table 2, we present the results from pre-processing the data using

matching.       We first matched five versions of the data based on the following

characteristics thought to be related to big box store placement: income per capita 2000,

population (logged)2000, number of superstores2000, and the number of universities2000. We

then took the matched data , and ran a full logit regression on the weighted data

(weights are derived from the matching procedure). The full specification includes a

host of individual controls that shouldn‘t be related to store placement, but that need to

be controlled in modeling individual-level opinion.2

        The results from Table 2 correspond with the findings reported in Table 1: Wal-

Mart has a significant impact on efficacy. A Wal-Mart store opening increases the

probability that respondents will agree with the statement ―Public officials don‘t care

much what people like me think.‖ In table 2a, the estimates indicate the same is true for

Target. The results are both substantive and statistically significant. For the Wal-Mart

equation, the first differences in expected values for a Wal-Mart opening is

approximately 17 percent. Opening a new Wal-Mart increases the likelihood that a

respondent will agree that ―public officials don‘t care much what people like me think‖

2
 Matching was done in R using MatchIt (Ho et al. 2009). Imputation (which must precede matching) was done
using Amelia II (Honaker et al. 2009).

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by 17 percent.       The first differences in expected values for a Target opening is

approximately 29 percent; the coefficient for the Costco variable was negative and

insignificant (not reported).

                                       -Table 2 and 2a about here-

       As we noted in the theory section, another possible mechanism that ties big-box

retail to declining political participation involves the sector‘s impact on unions.

Included in the ANES survey is a question that asks respondents ―how would you rate

labor unions?‖ The thermometer rates from zero (low) to one hundred (high). In tables

3 and 3a we present the estimates from the same matching methods used in Tables 2

and 2a. As tables 3 and 3a indicate, both Wal-Mart and Target store openings have a

dampening impact on people‘s views towards labor unions.              The results are both

statistically and substantively significant. When a Target opens a store, the labor union

thermometer drops a full 4 percentage points; when Wal-Mart comes to town, the labor

union thermometer drops over 7 percentage points. Costco‘s impact on the labor union

thermometer was indistinguishable from zero (not reported).

                                       -Tables 3 and 3a about here-

DISCUSSION AND CONCLUSION

       This paper moves beyond previous work by examining how big-box retail

influences attitudinal changes within a panel survey conducted by the ANES in 2000

and 2004. Examining the relationship in a before-and-after framework (where there is

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a clear treatment between the two surveys) represents a rigorous test. In this paper, we

identified two possible causal connections that link big-box retail to declining political

participation. First, the arrival of a big-box store may signal to individuals important

changes in their community will take place regardless of their opinions. Second, big-box

retail has an important impact on how individuals rate labor unions.

       Our results suggest that the opening of Wal-Mart and Target stores produce

drops in rates of individual political efficacy. We also find that Wal-Mart and Target

store openings are associated with declining views towards labor unions. As discussed

previously, these developments are likely to hold negative consequences for political

participation in communities dominated by big-box retail.

       Although we have moved closer to connecting big-box retail to important trends

in political participation, there is an important limit to our study. Missing from our

analysis is the direct link from a respondent‘s awareness of big-box retail presence to

their political attitudes. Until surveys are conducted that explicitly link big-box stores to

people‘s attitudes, we must remain cautious with respect to our results and what they

say. Nevertheless, there is evidence that previous results – mostly focused on Wal-Mart

and its impact on political participation and civil society – are founded on some

important micro-foundations. Even after having taken steps to deal with selection

problems, and after having controlled for an individual‘s response to the same question

in 2000 along with a number of individual characteristics and contextual factors

(income per capita, population, number of superstores), Wal-Mart and Target store

openings are associated with important attitudinal changes.          Though we can only

speculate at this point, declining views of union activity could hold negative implications

for other kinds of associational activity. Understanding that big-box retail certainly

The Political Consequences of Big-Box Retail                                            - 19
Brown, Lawrence, Sokhey

represents numerous benefits for society, we have potentially identified some concrete

costs for democratic functioning.

The Political Consequences of Big-Box Retail                                       - 20
Brown, Lawrence, Sokhey

       Table 1. IV and Probit Regressions of External Efficacy on Wal-Mart Treatment
                          People like me don’t have any say Public officials don't care about
                          in what government does (Yes=1)           what people like me think
                                                                              (Yes=1)
                                 IV Regression         Probit        IV Regression       Probit
                            2nd Stage     1st Stage             1st Stage    2nd Stage
Wal-Mart                    1.9416***                  0.2172                2.6642*** 0.6789***
                             (0.5496)                 (0.1326)                (0.0629)  (0.1037)
Respondent's Age           0.0508*** -0.0019** 0.0657*** -0.0026*** 0.0148*** 0.0247***
                             (0.0131)    (0.0009)     (0.0055)  (0.0009)      (0.0033)  (0.0043)
Male = 1                    0.9287***      -0.0113   1.2442*** -0.1234*** 0.7768*** 1.3087***
                            (0.2864)      (0.0262)    (0.1756)  (0.0243)      (0.1198)  (0.1232)
White = 1                  -2.0999*** 0.8085*** -0.9343*** 0.7084*** -2.4072*** -1.9201***
                             (0.3513)     (0.0434)    (0.2685)  (0.0459)      (0.1703)  (0.2071)
Church Attendance            -0.0993     0.0700***     0.0716  0.0674*** -0.2083*** -0.0852**
                             (0.0771)     (0.0083)    (0.0583)  (0.0085)     (0.0248)   (0.0368)
Respondent's Education      0.2187*** -0.0251*** 0.2336***        0.0098       0.0302  0.1668***
                             (0.0479)     (0.0078)    (0.0434)  (0.0069)     (0.0260)   (0.0361)
Respondent's Income           -0.0241    0.0387*** 0.0613*** 0.0437*** -0.0804*** 0.0757***
                             (0.0379)     (0.0029)    (0.0188)  (0.0030)      (0.0134)  (0.0159)
Respondent's commute        -0.1678**      -0.0168  -0.2422***    0.0065       -0.0257   0.0319
                            (0.0838)      (0.0130)   (0.0808)    (0.0131)     (0.0387)  (0.0596)
Superstores in County         0.0358      -0.0003      0.0296  0.0390***        0.0114 0.2212***
                             (0.0667)     (0.0148)   (0.0823)   (0.0145)      (0.0481)  (0.0690)
No Say (2000)              0.8658*** -0.3069***        0.3673
                             (0.2148)     (0.0351)    (0.2289)
County Population
                            0.3475***   -0.1104***   0.1857   -0.1324***    0.5129***   0.5489***
(logged)
                             (0.0969)       (0.0181) (0.1152)   (0.0206)      (0.0710)  (0.1002)
Universities in County     -0.0737*** 0.0297*** -0.0302*** 0.0304*** -0.0940*** -0.0670***
                             (0.0139)      (0.0021)  (0.0109)   (0.0021)     (0.0069)   (0.0088)
2000 superstore            -0.3308*** 0.1843***      -0.0020   0.1833*** -0.4579***      -0.0327
                             (0.1169)       (0.0101) (0.0565)   (0.0106)     (0.0346)   (0.0461)
Income per capita (logged)     0.5757     -0.3139***  -0.1788 -0.3770*** 1.2115***       0.4896
                             (0.4367)       (0.0751) (0.4264)   (0.0789)      (0.2363)  (0.3453)
Party Identification          -0.0184     -0.0348*** -0.0961* -0.0265***      -0.0206  -0.2408***
                             (0.0553)      (0.0091)  (0.0497)   (0.0096)     (0.0348)   (0.0403)
Distance from Bentonville                 -0.0000***          -0.0000***
                                           (0.0000)             (0.0000)
Politicians Care (2000)                                          -0.0147      -0.0640    -0.0874
                                                                (0.0364)      (0.1071)   (0.1611)
Constant                   -16.1768*** 4.7933*** -8.5362** 5.2339*** -18.7955*** -15.2937***
                             (3.5435)       (0.6776) (3.9914)   (0.6964)      (2.2781)  (3.2480)
/athrho                     -0.8215**                          -1.7140***
                             (0.4068)                           (0.2350)
/lnsigma                   -0.9816***                         -0.9634***
                             (0.0176)                           (0.0176)
Number of observations                1,610            1,610             1,609            1,609
Adjusted R2                                            0.795                              0.574
note: *** p
Brown, Lawrence, Sokhey

Table 2. Logit Regression on Matched Data: Wal-Mart Treatment
(“Public officials don’t care about what people like me think”; Yes = 1)

Variable                               Coeff.        Std. Error        t ratio
(Intercept)                            -82.44           10.26           -8.04

Wal-Mart (2002, 2003, 2004)             4.88            0.66            7.42

Party ID                                -0.26           0.10            -2.67

White                                   -2.07           0.55            -3.74

Income (2000)                           0.20            0.07            2.80

Education (2000)                         0.15           0.10            1.49

Age (2000)                               0.01           0.02            0.83

Church Attendance (2000)                 0.16           0.09            1.79

Male                                     2.65           0.40            6.65

Attention to Local News (2000)           4.12           0.32            13.01

Efficacy (2000)                          0.73           0.52            1.41

Political Knowledge (2000)              -0.38           0.28            -1.35

Commute (2000)                           0.37           0.14            2.62

# of Superstores (2000)                 -0.13           0.11            -1.17

# of Universities (2000)                -0.05           0.02            -2.42

Pop. (logged)                            1.87           0.30            6.26

Income per cap. (2000)                   3.92             1.01          3.87
*Estimates are averaged across five, matched data sets. Data was matched on
population in 2000, income per capita in 2000, the number of superstores, and the
number of universities.

The Political Consequences of Big-Box Retail                                                      - 22
Brown, Lawrence, Sokhey

       Table 2a. Logit Regression on Matched Data: Target Treatment
    (“Public officials don’t care about what people like me think”; Yes = 1)

Variable                                       Coeff.     Std. Error        t ratio
(Intercept)                                    -15.41        15.23            -1.01

Target (2002, 2003, 2004)                       6.66          0.74            9.02

Party ID                                       -0.31          0.11           -2.83

White                                          -1.88          0.63           -2.98

Income (2000)                                   0.17          0.09            1.85

Education (2000)                               0.02           0.11            0.21

Age (2000)                                      0.01          0.02            0.81

Church Attendance (2000)                       0.02           0.12            0.17

Male                                            2.68          0.49            5.50

Attention to Local News (2000)                  4.82          0.39           12.50

Efficacy (2000)                                 0.63          0.62            1.02

Political Knowledge (2000)                     -0.60          0.33           -1.84

Commute (2000)                                  0.21          0.17            1.28

# of Superstores (2000)                         0.23          0.16            1.42

# of Universities (2000)                       -0.03          0.03           -1.07

Population in 2000 (logged)                    -2.88          0.76           -3.81

Income per capita in 2000 (logged)             3.40             1.13          3.00
*Estimates are averaged across five, matched data sets. Data was matched on population
in 2000, income per capita in 2000, the number of superstores, and the number of
universities.

The Political Consequences of Big-Box Retail                                                   - 23
Brown, Lawrence, Sokhey

Table 3: Logit Regression on Matched Data: Wal-Mart Treatment
(Union Thermometer 2004)

Variable                                     Coeff.      Std. Error        t ratio
(Intercept)                                -76.44837      26.70309         -2.8629

Wal-Mart (2002, 2003, 2004)                -7.35963        2.51761        -2.92326

Party ID                                       1.25248     0.3289          3.80811

White                                          8.67992     3.09709         2.8026

Income (2000)                                  0.25601     0.16677         1.53504

Education (2000)                               2.36379     0.81759         2.89116

Age (2000)                                 -0.04208        0.05244        -0.80251

Church Attendance (2000)                   -1.43423        0.19073        -7.51986

Male                                       4.38802          1.2767         3.43701

Attention to Local News (2000)             -4.58274        0.75329        -6.08364

Union Thermometer (2000)                       0.60179     0.0535         11.24894

Political Knowledge (2000)                 -4.00491        0.67683        -5.91714

Commute (2000)                             -5.65579        0.73048        -7.74252

# of Superstores (2000)                        -0.138      0.36641        -0.37664

# of Universities (2000)                   0.08683         0.06768         1.28284

Population in 2000 (logged)                    0.02114     1.12931         0.01872

Income per capita in 2000 (logged)          7.48678          2.95622       2.53255
*Estimates are averaged across five, matched data sets. Data was matched on population
in 2000, income per capita in 2000, the number of superstores, and the number of
universities.

The Political Consequences of Big-Box Retail                                                   - 24
Brown, Lawrence, Sokhey

        Table 3a. Logit Regression on Matched Data: Target Treatment

(Union Thermometer 2004)

Variable                               Coeff.      Std. Error          t ratio
(Intercept)                           -93.585       42.8328            -2.1849

Target (2002, 2003, 2004)            -4.33186        1.61878           -2.676

Party ID                              1.3997         0.32541           4.3013

White                                 7.91717        2.57936           3.0694

Income (2000)                        0.25268         0.15492            1.6311

Education (2000)                     2.33309          0.7292           3.1995

Age (2000)                           -0.05912        0.04006            -1.476

Church Attendance (2000)             -1.75241        0.26756           -6.5496

Male                                 3.19674         1.60496           1.9918

Attention to Local News (2000)       -3.24325        0.78161           -4.1495

Union Thermometer (2000)             0.63402         0.0492            12.8861

Political Knowledge (2000)           -4.14462        0.71495           -5.7971

Commute (2000)                        -6.3674        0.6892            -9.2388

# of Superstores (2000)              0.17302         0.60187           0.2875

# of Universities (2000)             0.03453         0.08613            0.401

Pop. (logged)                        -0.75696        2.92351           -0.2589

Income per cap. in 2000 (logged)      9.75381           3.1676         3.0792
*Estimates are averaged across five, matched data sets. Data was matched on
population in 2000, income per capita in 2000, the number of superstores, and the
number of universities.

The Political Consequences of Big-Box Retail                                                       - 25
Brown, Lawrence, Sokhey

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The Political Consequences of Big-Box Retail                                        - 27
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