adapting to hard times: family participation patterns in local thrift economies

SPENCER JAMES Penn State University

RALPH B. BROWN, TODD L. GOODSELL, JOSH STOVALL, AND JEREMY FLAHERTY Brigham YoungUniversity*

Adapting to Hard Times: Family Participation

Patterns in Local Thrift Economies

Using survey data from a western U.S. county(N = 595), we examined how lower, middle,and higher income families negotiate a periodof economic stress—the closing of a majoremployer in the community—through theirshopping patterns. Specifically, we examinedtheir participation in local thrift economies suchas yard sales and secondhand stores. We foundthat lower and middle income households shopmore frequently at these venues. They also tendto shop more for furniture and clothing, whereashigher income households tend to shop forantiques and trinkets. These relationships variedacross the type of thrift economy examined.Overall, findings support the argument thatengagement in thrift economies may constituteone mechanism families use during periods ofeconomic stress.

Downturns in the economy have meant thatmany families are struggling to make ends meet.Even before the large-scale collapse of the U.S.housing market in September 2008 and its dev-astating effects on global markets, traditionalsubsidies such as pensions, guaranteed health

Department of Sociology, Penn State University 211Oswald Tower, University Park, PA 16802 ([email protected]).

*Department of Sociology, Brigham Young University,2008 Joseph F. Smith Building, Provo, UT 84602.

Key Words: economic distress, family and social change.

benefits, and other traditional allowances werealready in decline (Ehrenreich, 2008). Ameri-cans work longer hours each week and for moreyears prior to retirement than just a generationago (Jacobs & Gerson, 2004). The average U.S.family, even with multiple income earners, isless financially stable today, as indicated byhigher risks of bankruptcy and greater volatil-ity in wages and assets such as stocks, than itwas in the early 1970s—a time of high inflation(Warren & Tyagi, 2004). Consequently, manyfamilies confronted by job insecurity, incomeloss, and increasing debt-to-asset ratio are alsoat risk of emotional distress, marital conflict,and anxiety because of their financial prob-lems (Dew, 2008; Mauno & Kinnunen, 1999;Westman, Etzion, & Danon, 2001).

Although scholars have examined a varietyof familial responses to economic uncertainty,many have focused on interspousal outcomessuch as how economic pressure increased therisk of emotional distress (Conger, Rueter,& Elder, 1999), how changes in consumerdebt predicted both the amount of timespent together and arguments over money(Dew, 2008; Rubin, 1994), and how economicdistress influenced marital conflict (Papp,Cummings, & Goeke-Morey, 2009). Researchon how families have attempted to negotiatea period of economic stress through ananalysis of household consumption patterns hasreceived less attention. Therefore, we examinedhousehold consumption patterns of lower,

Family Relations 59 (October 2010): 383 – 395 383DOI:10.1111/j.1741-3729.2010.00610.x

384 Family Relations

middle, and higher income-earning households,specifically as it is related to shopping in whatwe call thrift economies, such as yard sales andsecondhand stores. Using survey data collectedin a Western county of the United States,we examined both the frequency with whichhouseholds participated in various local thrifteconomies and the types of items for which theytended to shop.

We first present how economic restructuringand financial uncertainty have created an envi-ronment where economic adaptation becomesnot only desirable but also necessary. We thenpursue a discussion on how participation in localthrift economies, such as yard sales and thriftstores, could constitute one particular way thatfamilies help make ends meet in times of difficulteconomic circumstances. Finally, the methodsand results are described and analyzed, followedby a discussion regarding the role local thrifteconomies play in mitigating difficult economiccircumstances.

Economic Restructuring and FinancialUncertainty

In their seminal work on social stratification,Blau and Duncan (1967) found evidence of‘‘two distinctive boundaries limiting downwardmobility, one between blue-collar and white-collar occupations, the other between blue-collar and farm groups’’ (pp. 58 – 59). Theseboundaries formed, in essence, a de facto safetynet for blue- and white-collar workers in how farthey could possibly ‘‘fall.’’ Today, it appears thatthe boundaries identified by Blau and Duncanhave all but disappeared. Over the past decadeor longer, economic restructuring has led toincreased financial uncertainty for many U.S.households, as many formerly secure sectorsin U.S. labor markets no longer guaranteedfinancial, occupational, or health benefits, thusleaving their workers vulnerable to potentialfinancial distress. Hacker (2006), for example,found that the risk of losing half or more of one’sincome in a given year increased by nearly 150%from 1970 to 2002 alone. Although factors suchas divorce and bankruptcy contributed to thistrend, job instability was primary among them.

Periods of large-scale economic stress poten-tially affect households of all levels of economicstatus, including higher income households.These too have become more vulnerable to eco-nomic insecurities because of restructuring in

the professional and managerial occupations,in effect making the risk of job loss moreequally distributed across all income earners(Farber, 2005). Ehrenreich (2006) reported thatas nationwide unemployment among those withprofessional credentials increased to nearly 20%of the unemployed, many in this group began toseek employment incommensurate with theirqualifications. At the same time, the steadyerosion of manufacturing jobs in the UnitedStates pushed many blue-collar workers into theever-expanding service industries, where wages,benefits, and opportunities for advancement forunskilled workers were generally far below thatof their former jobs. Increased global competi-tion in financial and labor markets appears tohave eroded many previously taken-for-grantedsafeguards, such as stable employment, reli-able benefits, and retirement programs, againstsocial and economic decline (Dobbs, 2006).Thus, insecurity has become the norm in the‘‘new’’ economy (Koeber, 2002), epitomizedby the majority of workers in the service sectorwho simply move from one low-wage job to thenext (Newman, 2000). Even before September2008, when unemployment rates were still fairlylow, ‘‘job churning’’ (the difference betweenjob loss and unemployment rates) was high andcontinues to climb (Farber).

The effects of downward mobility, facilitatedby declines in real wages and benefits, havebeen compounded by rising costs of living,especially in the housing market. The cost ofhousing has risen dramatically over the pastseveral decades and remains high compared withother necessities such as food costs, even afterthe burst of the housing bubble. For example,the average American household spent twiceas much of their disposable (after-tax) incomeon housing as food in 1984, whereas todaythe ratio is closer to three times as much(Consumer Expenditure Surveys 1984, 2008).One key factor in this was the ease of obtainingcredit, which led to high consumer debt and oftenbankruptcy and financial insolvency (Sullivan,Warren, & Westbrook, 2001). Consequently,over the past two decades, many Americanshave expressed a ‘‘fear of falling’’ from theircomfortable middle-class lifestyles because ofwage and job insecurity (Ehrenreich, 2006;Newman, 1988). Global financial restructuringhas also precipitated a dramatic increase in thenumber of dual-career families during the pasttwo decades (Hochschild 1989, 1997; Neumark

Adapting to Hard Times 385

& Postlewaite, 1998). But as Warren and Tyagi(2004) made clear, many of these families arefinding that even two incomes are not enoughto keep pace with increased costs of living,adding to their financial distress. Thus, aswe move into 2010, even more families willlikely experience unemployment, loss of healthbenefits, and decreases in household income(Schmitt & Baker, 2008).

As the American cost of living increaseswhile earning potentials decline, we may observefamilies beginning to alter their consumptionpatterns to accommodate such social change.For example, the failure of income to keep pacewith rising housing costs may push individuals tolook for creative ways to stretch the family dollarwithout accumulating greater debt (Herrmann2003, 2004, 2006; Herrmann & Soiffer, 1984).

Thompson County (a pseudonym), where thisstudy was conducted, is a possible example forthese creative consumption patterns. The Hous-ing Opportunity Index (HOI), which measuresthe proportion of homes in the area affordableto a family earning the median income, wasapproximately 40. The index’s mean for theyears 1991 – 2009 was roughly 50, with a stan-dard deviation of 15, and a range of nearly 60. In2003, when the data for our study were collected,the index score was approximately 75. Duringthis time period (1991 – 2009), the median homeprice in Thompson County increased by almost200%, whereas the median income rose by lessthan 150%.

Thrift Economies

Periods of economic decline such as the onemost recently experienced should, in principle,inspire new approaches by households to helpstretch the family dollar. In fact, one approachto maintaining social standing that has recentlyreceived considerable attention in the popularpress is the increased popularity of what weterm ‘‘thrift economies,’’ generally consistingof thrift/secondhand stores and yard sales(The Associated Press 2008a, 2008b, 2009a,2009b; Overfelt, 2009; Rosenbloom, 2008).Interestingly, very little scholarly attention hasbeen devoted to this topic.

Thrift economies consist of a variety ofeconomic activities and outlets such as thriftstores, consignment shops, secondhand stores,and yard sales that are tied to the larger,more formally regulated economy but differ

from it in at least three important ways. First,such activities/outlets rarely charge sales tax.Second, such places frequently offer below-market pricing. Third, participation may bebased as much on social objectives as economicones (Herrmann 2003, 2006).

Traditionally, these types of thrift economiesfunctioned on a cycle of donations fromthe relatively wealthy and consumption bythose who are not (Horne, 2000). Thisrecycling of secondhand goods enabled less-advantaged individuals to meet basic needsand simultaneously provided more privilegedindividuals an outlet for the disposal of unwanteditems (Strasser, 2000).

Despite their ubiquity, the way in whichindividuals from varying socioeconomic back-grounds engage these thrift economies remainsa largely unexplored question (see, however,Herrmann & Soiffer, 1984 for a notable excep-tion). We do know, however, that anecdotalevidence seems to suggest that thrift economiesare becoming a more popular option. The ques-tion remains, to whom? To what degree do alllevels of household income earners participatein these thrift economies during periods of eco-nomic stress brought about by declines in realwages and loss of job security, coupled withrising costs of living? We should anticipate thata new group of ‘‘bargain hunters’’ will join theranks of existing collectors and the underprivi-leged in participating in this arena (Herrmann,2006; O’Reilly, Rucker, Hughes, Gorang, &Hand, 1984; Strasser, 2000). As they do, per-haps contrary to Veblen’s truism at the turn ofthe 20th century, the turn of the 21st centurymay see people of higher socioeconomic statuslooking down as a way to soften their fall ratherthan perpetually ‘‘looking up.’’

Indeed, there is emerging evidence that thestigma surrounding thrift stores and similar out-lets is declining. Darley and Lim (1999) noted:

In recent years, thrift stores have been seekingand receiving the acceptance of middle-classconsumers. Many consumers are turning tosecondhand stores or second-order retail outletsfor their merchandise. Thus, the demographics ofthe consumers of thrift stores are shifting from thepoverty-stricken to reflect the average consumer(p. 311; emphasis added).

By the mid-1990s, the typical thrift storeshopper was employed, between the ages of25 – 40 and had two children (Fox, 1995), a


notable shift from the early 70s, when Parker(1972), echoing Veblen (1912), wrote that,professionals and managers exhibit a closeridentification with the rich than with thoseoccupying lower social strata.

Although thrift economies are appendagesof the larger, formally regulated economy, asnoted above, they do differ from it in severalimportant ways and ‘‘represent a truly creativecultural response to the extended economicand social crises of life in advanced industrialsociety’’ (Herrmann & Soiffer, 1984). Althougha cash nexus ostensibly abounds, a purelybusinesslike motivation toward monetary gaindoes not. In fact, items are often priced (and attimes, even given away) to facilitate a sense ofcommunity among those involved (Herrmann,1996). Yet, this is by no means an indicationthat social concerns supplant instrumentalrationality. Herrmann and Soiffer identified 10types of shoppers at yard sales, ranging fromretailers whose livelihoods depended on findingresalable goods to friends, neighbors, or relativesof the seller with little to no economic interestin the sales’ outcome. People can thus haveboth economic as well as social motivationsfor participating in thrift economies as theyseek to develop methods that ‘‘satisfy theirsocially defined needs in ways that expend aslittle as possible of their discretionary funds’’(Herrmann & Soiffer). These unique aspectsmake thrift economies as manifest throughsecondhand stores, yard sales, and so on,potentially appealing to households of all socialand economic standing during times of economicstress and may be particularly relevant inthe context of social status maintenance andeconomic hardship.

To test if this was in fact the case, westarted with the assumption that income andother sociodemographic variables (e.g., gender,marital status, race, age, education, financialdistress, and household size) are linked to thelikelihood of household participation in variousthrift economies. Specifically, our researchexamined both the frequency (i.e., how oftenindividuals shop at these outlets) and purpose(i.e., what they shop for) of engagement in localthrift economies. We examined how higher,middle, and lower income earners stretch theirfamily dollar by the relative frequency withwhich they shop these outlets. We also examinedthe particular items for which they shop. Weassumed that higher income households are

more likely to shop for non necessities, such asantiques and trinkets, whose value is tied to itsworkmanship and history rather than its utility,which is of more importance to lower and middleincome earners (Ferrell, 1990). Consequently,less-privileged households may be more likelyto shop for quotidian necessities such as clothingand housewares.

METHOD

Sample

Data for the study were collected in 2003from a western county (Thompson County)that had recently experienced the loss of amajor employer. An 18-page survey intendedto collect personal, financial, and attitudinalinformation was mailed to a random sampleof households in Thompson County. Severalindicators in the questionnaire allowed usto examine the relationship between incomelevels and shopping in thrift economies. Thesurvey used an initial mail sample of 1,150individuals purchased from an industry-leadinglist provider. The male or female head of house(self-designated) was instructed to respond tothe survey and return it. A business replyenvelope and a $2 incentive were included. Ofthe 723 surveys returned, 595 contained validresponse data.

Many families in the county were underconsiderable economic stress due to the lossof the major employer, which affected nearlyeveryone in the county. Local businessesand services suffered, and local governmentsstruggled to find ways to compensate forloss of taxes the employer provided. Oursample represented a unique opportunity toexamine household consumption patterns intheir local markets during a period of economicstress. In other words, as Gieryn (2000)asserted, we gain a better understanding ofhow families act under certain conditions whenwe sociologically situate (or ‘‘place’’) them inthe local context. Consequently, our findings atthe very least help illustrate how householdsin this particular community responded to thiseconomic stress through their participation inlocal thrift economies. It is also possible thatthe way these families adapted to hard economictimes is a harbinger of what other householdsand communities across the United States wouldexperience during the national recession in thelatter part of the decade.


Compared with other counties in the UnitedStates, Thompson County is in some waysunique. The average household contains aboutthree and a half people compared with abouttwo and a half nationally. Socioeconomically,the county enjoys slightly higher than averagelevels of income and education. The countyhas a smaller proportion of families in povertythan the national average, although it didexperience an economic downturn in the early2000s when a major factory laid off workersand declared bankruptcy in 2002. Additionally,90% of the county belongs to the ‘‘SalvationChristian Church’’ (a pseudonym). Althoughthis is potentially problematic for our study,because many areas of the United Stateshave significantly lower levels of religioushomogeneity, Bartkowski and Regis (2003)noted that such a phenomenon is relativelycommon in some areas of the South, Midwest,Intermountain West, and the West Coast.Such religious homogeneity will, however, biasour estimates to the extent that membershipin the Salvation Christian Church is linkedto engagement in local thrift economies.This would be seen in the overall levelof participation in thrift economies (i.e., ourestimates may be systematically higher or lowerin other populations). Ironically, such highlevels of religious homogeneity would not affectthe relationships between various local thrifteconomies (e.g., yard sales and thrift stores),such as those examined here. Consequently, ourresults may or may not be similar to other regionsof the country, as families today are experiencinga more systemic economic crisis.

Models and Missing Data

We estimated two models. The first modelemployed binary logistic regression to estimatethe likelihood of purchasing certain items inlocal thrift economies. We then estimated anordinal logistic regression model to examine thefrequency of engaging local thrift economies.Our primary interest in both analyses is theeffect of household income level on engagementin local thrift economies. We controlled forother sociodemographic characteristics that maybe associated with both income levels and thelikelihood of engaging in local thrift economies.

Like most surveys, this one has missingvalues. Although the amount and proportionof missing data were small on each variable

(never more than 7% of the sample and usuallyaround 3%), missing data, or more preciselythe pattern of missing data, can affect theestimation procedures used to obtain coefficientsand standard errors (Acock, 2005). For thisreason, we generated multiple sets of plausiblevalues that represented a distribution of plausiblevalues using Stata’s ice program (Royston,2007). Plausible values were used to replaceeach missing value, allowing us to ‘‘model themissingness.’’ Thirty datasets were generatedand jointly analyzed using Stata’s micombinecommand. By combining estimates from each,coefficients and standard errors were adjusted forbias caused by missing data. After imputationand before analysis, the data were examined forirregularities that may have occurred during theimputation process. No meaningful variationswere found in the means, standard deviations,or ranges. The results remained substantivelyunchanged when we used multiple imputation,mean replacement, listwise deletion, or full-information maximum likelihood techniques todeal with missing data.

Shopping Variables

We employed two sets of dependent vari-ables. The first set contained information aboutwhether respondents shopped for specific items(furniture, clothing, trinkets, antiques, house-wares, electronics, appliances, or books) at athrift store or yard sale (1 = yes). The secondset included how frequently (0 = never, 1 =once or twice year, 2 = at least once a month)respondents shopped (for any item) at outletsin local thrift economies. Three distinct typesof outlets were examined. First, we examinedshopping patterns at Thrifties, the largest andmost frequented thrift store in Thompson Countyon which data were collected. To preserve thegreatest level of detail available in the data,we analyzed shopping patterns at Thrifties sep-arately. Second, respondents were asked howoften they shopped at all other thrift stores,excepting Thrifties. Finally, respondents wereasked how often they shopped at yard sales.(Although many thrift stores and yard sales con-tain designer products, the outlets under studyhere rarely have such items. The vast majorityof items are useable but with significant wear.Highly desirable items are unlikely to be pur-chased at these outlets, with the exception oftrinkets and antiques.)


Sociodemographic Characteristics

Sociodemographic characteristics include therespondent’s gender (1 = female), marital status(1 = married, 0 = all others), race (1 = White,0 = non-White), age (coded in 5-year incre-ments ranging from a low of 16 and cappedat 60+), education (1 = less than high school,2 = high school graduate, 3 = some college,4 = college degree, 5 = postgraduate degree),household size (measured continuously andcapped at seven or more people), and income.Family financial distress was a standardized,additive index (α = .90; all factor loadingswere at least .80) of five questions. Thesequestions asked how difficult (ranging from5 = very difficult to 1 = very easy) it was tocover common family and household expensesduring the past 3 months. These include mort-gage and rent, medical bills, health insurance,grocery costs, and credit card bills. Annualincome was measured using a piecewise linearspline with three nodes to leverage differencesbetween income groupings. The first node rep-resented lower income earners, operationalizedas those who reported annual income is lessthan $30,000. Middle income earners, the sec-ond node, represented those reporting incomesbetween $30,000 and $79,999. Higher incomeearners reported making more than $80,000. Toobtain each node, dummy variables for eachincome grouping were created. Those in thegiven income group were given a value of 1,whereas all others were given a value of 0. Toensure that our results were robust to a varietyof alternative specifications, we also ran modelsemploying income as a continuous measure andas an ordinal measure with cut points at each$10,000 increment. The results remained sub-stantively similar to those reported here, so wereport the results with the dummy variables only.

RESULTS

Table 1 presents descriptive statistics for thestudy sample. Participation in local thrifteconomies was relatively common among sam-ple respondents with the average respondentreported shopping at thrift stores and yard salesabout once or twice a year. The sample con-sisted predominantly of White, married males.Although a gender-balanced sample would beideal, the disproportionate number of males inour sample serves to make our results more con-servative because women are more likely than

Table 1. Mean, Standard Deviation, and Range ofSociodemographic and Shopping Frequency Variables:

Descriptive Statistics (N = 595)

Variables M SD Range

Thrifties 0.86 0.66 0 – 2Thrift stores 0.51 0.65 0 – 2Yard sales 0.64 0.66 0 – 2Gendera 0.28 0.45 0 – 1Marriedb 0.85 0.36 0 – 1Racec 0.96 0.20 0 – 1Age 6.94 2.54 1 – 10Education 3.58 1.03 1 – 5Household size 3.77 1.79 1 – 7Low income 0.08 0.27 0 – 1Middle income 0.71 0.45 0 – 1High income 0.21 0.41 0 – 1Financial distress (standardized) 0.00 1.00 −1.2 to 2.4

Note: Imputed values excluded.aGender: 0 = male; 1 = female.bMarital status: 0 = divorced, separated, or single;

1 = married.cRace: 0 = non-White; 1 = White.

men to engage in the thrift economy (Herrmann,1996). The average respondent was in his or hermid-40s, had some college education, lived in ahouse with about three other people, and earnedaround $50,000 annually. The high cost of liv-ing in Thompson County (the costs of housing,transportation, food, and health care in Thomp-son County are similar to analogous costs in farlarger Western cities such as Seattle, Washing-ton, and Portland, Oregon) means that $50,000does not go very far.

Table 2 shows the results from the binarylogistic regressions that estimated whetherrespondents reported shopping for particularitems at Thrifties, other thrift stores, or yardsales. All estimates were adjusted for respon-dents’ gender, marital status, race, age, educa-tion, household size, and financial distress. Wecompared lower and middle income earners withhigh income earners to assess whether incomelevel was associated with shopping patterns ateach outlet. On average, about 16% of the sam-ple shopped for each item at each outlet. Atleast 5% of the sample shopped for each itemwith one exception—appliances at yard sales.Respondents reported shopping for each itemmost frequently at Thrifties.

In line with expectations, we found that lowerand middle income earners were more likely


Table 2. Odds Ratios From Binary Logistic RegressionEstimates of Shopping Patterns by Income Distribution,

Item Shopped for, and Venue (N = 595)

ItemIncome

Category∗ ThriftiesThriftStores Yard Sales

Furniture Lower 1.11 4.02∗ 1.41Middle 1.07 2.70∗ 2.08∗

Clothing Lower 1.88∗ 3.90∗∗∗ 1.51Middle 1.40 2.39∗ 1.29

Trinkets Lower 0.73 0.941 0.90Middle 0.70 1.57 1.21

Antiques Lower 0.31∗∗ 0.71 0.64Middle 0.44∗∗ 1.06 1.02

Housewares Lower 1.78 4.10∗ 1.45Middle 1.44 2.49 1.54

Electronics Lower 2.96∗ 3.25 1.44Middle 1.36 4.00 1.32

Appliances Lower 1.61 5.12 0.56Middle 1.22 2.73 0.98

Books Lower 1.36 2.08 0.87Middle 1.11 1.71 1.11

Note. Control variables (not shown) include gender,marital status, race, age, education, and household size.The reference category is higher income earners.

∗p < .05. ∗∗p < .01. ∗∗∗p < .001.

than higher income earners to shop for each typeof good, with the exception of antiques and trin-kets. Indeed, significant differences were foundin item-specific shopping patterns between lowerand higher income earners for five of the eightitems. The odds of shopping for furniture, cloth-ing, and housewares at thrift stores were fourtimes higher for those from the lower incomecategory than those from the higher income cat-egories. Lower income earners were also morelikely to purchase clothing and electronics atThrifties than higher income earners. Middleincome earners, for their part, appeared moresimilar to those in the lower income group thanthose in the higher income grouping. The odds ofa middle income earner shopping for furniture ata yard sale or thrift store were over twice as greatas the odds of a higher income earner doing so.They were also more likely to shop for clothingat thrift stores. As anticipated, higher incomeearners were more likely to shop for antiques atThrifties than those in other groups.

Table 2 provides some evidence of differentialengagement in the local thrift economies byincome level. As expected, we found that one’sincome level predicted the items for which

respondents shopped in thrift economies, netof controls. Lower and middle income earnersappeared to be more likely to shop for necessitieslike clothing, furniture, and electronics, whereashigher income earners were more likely to shopfor antiques. Note, however, the variation inthis pattern across each respective outlet. Wefound relatively few differences across shoppersat yard sales, a moderate amount among shop-pers at Thrifties, and quite a few among thoseshopping at other thrift stores. For example, wefound no differences between income categoriesin the likelihood of purchasing clothing at yardsales. At Thrifties, we found that being in thelower income category was associated with a88% increase in the odds of shopping for cloth-ing. At other thrift stores, however, we foundthat those from both lower and middle incomegroups were more likely than those from thehigher income group to purchase clothing there.Such nuances should be kept in mind throughoutthe article.

To assess the robustness of the relationshipbetween income level and participation in localthrift economies, we move from an examinationof the particular item respondents reportedlyshopped for to an analysis predicting howfrequently respondents shopped at Thrifties,other thrift stores, and yard sales. We regressedthe outcome variable, frequency of shopping ateach of the three outlet types, on our splines forincome level while controlling for other factorsthought to be associated with both income leveland engaging in local thrift economies. Resultsare presented in Table 3, which displays thelogits, their standard errors, and the odds ratios(obtained by exponentiating the logit) associatedwith each of the three dependent variables.A value less than one indicates a negative effect,whereas a value greater than one signifies apositive effect.

The first three columns display resultsfrom the equation that predicted frequency ofshopping at Thrifties. We found that householdsize and income were the two best predictorsof moving from one frequency category tothe next. Being in the lower income categorywas associated with a doubling of the odds ofmoving to the next higher frequency categoryof shopping at Thrifties. Being in the middleincome category increased the odds by 45%relative to the higher income group. Eachone-person increase in household size was


Table 3. Ordinal Logistic Regression Model Predicting Frequency of Engaging in Three Thrift Economies, With RobustStandard Errors (N = 595)

Thrifties Other Thrift Stores Yard Sales

B SE eB B SE eB B SE eB

Female −0.02 0.11 0.98 −0.10 0.12 0.91 0.02 0.11 1.02Married 0.23 0.16 1.25 −0.05 0.16 0.95 0.03 0.15 1.03White 0.11 0.22 1.12 0.07 0.29 1.07 −0.21 0.24 0.81Age 0.03 0.02 1.03 0.003 0.02 1.00 −0.04 0.02 0.96Education −0.06 0.05 0.94 −0.03 0.05 0.98 −0.11∗ 0.05 0.90Household size 0.13∗∗∗ 0.03 1.14 0.09∗∗ 0.03 1.10 0.11∗∗∗ 0.03 1.12Lower income 0.74∗∗∗ 0.22 2.10 0.30 0.22 1.36 0.39 0.23 1.48Middle income 0.37∗∗ 0.13 1.45 0.26 0.14 1.30 0.31∗ 0.13 1.37Financial distress 0.05 0.06 1.05 0.15∗∗ 0.06 1.17 0.07 0.06 1.08Cut points

1 0.56 0.37 0.67 0.42 0.19 0.392 2.16∗∗∗ 0.38 1.85 0.43 1.21∗∗ 0.40

χ2 220.734 220.664 221.846df 11 11 11

Note: eB = exponentiated B. Reference categories are male, not married, non-White, and high income. Age, education,family size, and financial distress are measured continuously. About 70% of the sample reported shopping at least once a yearat Thrifties. The analogous numbers for other thrift stores and yard sales are 45 and 55%, respectively. The proportional oddsassumption was met.

∗p < .05. ∗∗p < .01. ∗∗∗p < .001.

associated with a 14% increase in the frequencyof shopping at this particular outlet.

The next three columns demonstrated a some-what different pattern. This time both incomecategories failed to reach traditional signifi-cance levels, though the coefficient for middleincome earners was trending (p = .063). Rather,it appeared that those with higher levels offinancial distress were more likely to shop atthrift stores other than Thrifties. Each one-unitincrease in household financial distress wasassociated with a 17% increase in the oddsof shopping more frequently at thrift stores. Weagain found evidence for a robust, positive effectfor household size.

The final three columns of Table 3 displayedthe same predictive model as before, this timeemploying frequency of shopping at yard salesas the outcome. We found that middle incomeearners were more likely to shop frequently atyard sales. Having an income in the middlerange of the sample was associated with 37%higher odds of shopping more frequently at yardsales than those in the high income category.The coefficient for the lower income groupingwas trending toward significance (p = .089) andpositive as well, indicating a greater likelihood

of shopping at yard sales than those in the higherincome category. Household and education weresignificant as well.

Taken together, our results provided evidencethat one’s income level was negatively linked tothe likelihood of engagement in thrift economiesand provided support for the position that hardeconomic times may encourage people to engagein this particular adaptive strategy to make endsmeet while maintaining social status. There isvariation in this relationship, however, acrossthe particular types of local thrift economies. AtThrifties, for example, income appeared to be astrong predictor of the frequency of shoppingat this particular thrift store. This was notthe case at other thrift stores. Rather, it wasfinancial distress that appeared to predict howfrequently a given respondent shopped there.Note, however, that Thrifties enjoyed the largestmarket share among the county’s thrift store (asillustrated by the fact, noted above, that 70%of the sample reported having shopped there atleast once, compared with just 45% at other thriftstores). It is possible, therefore, that the resultsfor Thrifties yield a better indication of therelationship between income and participationin local thrift economies in Thompson County.


DISCUSSION

Using data collected from a western county thathad recently experienced the loss of a majoremployer, we explored the relationship betweenincome and the likelihood of participating inlocal thrift economies, which we defined asshopping at thrift stores and yard sales. Wefound that both lower and middle incomeearners were more likely to shop at thesevenues than those making higher incomes.They were also more likely to shop for itemssuch as furniture and clothing. Conversely,higher income earners were more likely to shopfor antiques and trinkets. These relationships,however, varied across the type of thrifteconomy. The relationship between income andparticipation in thrift economies was generallynegative and significant, with higher incomelevels being associated with a lower likelihoodof engagement in thrift economies.

On the basis of Table 3, the relationship,however, appears to be the strongest at Thriftiesand weakest at other thrift stores, with yard salesfalling in between the two extremes. Althoughthere is at least some evidence that income isassociated with the frequency of shopping ateach outlet type, the evidence is weakest whenpredicting the frequency of shopping at thriftstores other than Thrifties, where only middleincome earners appear to be more likely to shopfrequently; this conclusion, however, is based ontrending significance. Thrifties does, however,maintain the unquestionably largest market shareof the three thrift economies examined; it isprobable, therefore, that the relationship betweenincome and participation in thrift economies inThompson County mirrors the results displayedregarding Thrifties than the other two outlets.Other thrift stores and yard sales clearly play animportant role in the local thrift economy.

These findings support the motivatingpremise of this article that one mechanismfor economic adaptation of households to hardfinancial times may be engagement in localthrift economies. When housing and other costsincrease without a concomitant augmentationof salary or wages, families may obtain moreitems in such places, where sales tax is gener-ally not charged, and merchandise is typicallypriced below retail value. Both of these strate-gies can aid households in their efforts to stretchthe family dollar. We observe, however, thatthis does not occur uniformly across all outletsexamined here. Income differences are observed

at all three outlet types, being less pronounced atyard sales than at thrift stores (when consideringall thrift stores together). One reason for thismay be the privileged position social ties areaccorded over economic concerns at yard sales,as noted by Herrmann and Soiffer (1984). Theoverall trend, however, demonstrated a negativeeffect of income on participation in local thrifteconomies.

Such efforts will likely become morenecessary and pronounced if current economictrends, characterized by increasing income andwealth stratification, continue in the future.Recent work by Dew and colleagues, forexample, demonstrates the impact of changesin family financial status on family relations(Dew, 2007, 2008). Families may thereforeseek to alleviate such pressures by makingconscious decisions to maintain social statusvia engagement in local thrift economies.

Rather than following Veblen (1912) inperpetually looking upward, many families maynow be looking downward for the softestpossible landing. In light of our findingsregarding participation in local thrift economiesby higher, middle, and lower income earners,assumptions about class aspirations and desiresmay need to be tailored to current social andeconomic circumstances. For many, Veblen’sobservation that individuals bend their energiesto live up to the ideal prescribed by those in thenext highest social stratum may be increasinglydifficult to achieve. As participation in localthrift economies is added to the already longand creative list of how Americans adapt todifficult economic conditions (see the remainderof this journal issue), a simple analysis ofparticipation in a thrift store-based economy mayspeak volumes about how Americans redefinethemselves in the new global economy. Shiftingeconomic and social structures may make thecentury-old dictum of ‘‘looking-up’’ the socialladder increasingly difficult, as many in themiddle and higher income brackets appear tobe glancing downward trying to calculate thesoftest possible landing.

The duration and intensity of economic down-turns may determine whether such downwardglances constitute a reshuffling of the socioeco-nomic landscape or simply a temporary, adaptivebehavior quickly jettisoned upon the return ofa more family-friendly economic climate. Inother words, families may return to purchas-ing new items at more traditional outlets. This


question merits further investigation. A realisticperception of consumption patterns during timesof economic distress may be important to pol-icymakers interested in jump-starting the econ-omy after such times. Whether such behavioris permanent or transitory, the shift from amanufacturing to a service-based economy hascreated fewer secure jobs. Declining job secu-rity and fewer opportunities for advancementmay inhibit upward mobility (Dudley, 2000;Ehrenreich, 2006; Rubin, 1994). The reductionin ‘‘white-collar’’ jobs has led to less secu-rity (Kreml, 1997), precipitating even greaterdownward mobility.

Interestingly, we also found that middleincome earners’ consumption patterns weremore similar to those of lower income earn-ers than were higher income earners. Middleincome earners tended to shop, similar to theirlower income counterparts, for consumer goodssuch as furniture and clothing. This articleprovides quantitative evidence, then, for whatothers have observed anecdotally—that thoseearning middle incomes participate in localthrift economies. Such venues are no longerreserved as avenues simply for meeting eco-nomic need but may now function as placeswhere middle income earners negotiate statusmaintenance during hard economic times. Inlight of such findings, we may need to expandour scope to include the important role such out-lets may play in the economic life of families andhouseholds.

The fact that these data were collected duringa period of relative economic prosperity atthe national level provides particular theoreticalleverage. At the time of data collection, the HOIwas about 75, meaning 75% of the homes inthe area were affordable to a family earningthe median income. It is likely, therefore, thatour estimates of participation in local thrifteconomies are conservative. Individuals andfamilies may be even more likely to engagelocal thrift economies in areas and circumstanceswhere family finances experience higher levelsof strain. Households confronting financialdifficulty look for ways to maintain socialstanding, and they may very well do so outsidethe normal bounds of the traditional market(Venkatesh, 2006). In this particular county,distinguished by large families, engagement inlocal thrift economies may be seen first as analternative and then become more mainstreamfor people from all income levels because

of the need to provide for additional familymembers. Thus, shopping in these outletscould become more normative—nonstigmatizedbecause everyone finds it necessary even innonfinancially distressed times such as whenthese data were drawn.

These results provide some limited insightinto possible strategies for family practitionersand policymakers. A realistic perception offamily consumption patterns during timesof economic distress may be important topolicymakers because increased support to thriftstores, whether by providing financial support,publicity, or a venue for such sales, couldgenerate needed income and employment tostruggling communities. These venues couldalso provide jobs and job training for theun(der)employed. Furthermore, to the extent thatthose interested in community development areable to organize or facilitate community-runyard sales or thrift stores, similar to the wayreligious organizations such as the SalvationArmy and Goodwill (whose original fundingcame primarily from the Methodist church) do,collective efficacy, which has been tied to amultitude of positive individual and communitylevel outcomes (Odgers et al., 2009), can befostered via increased opportunities for socialnetworking. These outlets also supply additionaloptions for purchasing household goods. Thismay become increasingly salient as interrelatedissues such as financial problems, a weakeningeconomy, and high levels of credit may driveshopping at outlets like those described hereinto the normative category, instead of theexceptional category, for family consumerbehavior.

In such an economic environment, we shouldexpect such social norms to emerge, norms thatare more fitting the economic and social real-ities of today. Opportunity costs for scouringthrift stores and yard sales are small in thecontext of reduced employment opportunities.Our analysis of thrift economy participation pat-terns by income groupings may shed some lightnot only on emerging strategies of how Amer-icans are stretching their purchasing power butalso on an emerging gestalt that is redefiningtheir social and economic orientation. Manymay now be looking for the softest landing pos-sible instead of aspiring to compete with theJoneses.

Finally, another important issue is the extentto which a local thrift economy becomes an


integral component to an increasingly largesegment of the local population. When thishappens, the line between the more formaleconomy and local thrift economies maybecome increasingly blurred. Consequently,communities may actually become economicallydependent on their local thrift economy. Ifand when this occurs, it potentially opens anew relationship of regulation and oversightfrom local governments. It also potentiallyredefines the responsibilities of large-scaleparticipants—such as Thrifties—in the overalllocal economy.

Several limitations in the present researchshould be noted. The data are drawn from justone county at one point in time. Although wecan demonstrate associations between incomeand accessing local thrift economies, we cannotaddress issues of causality or change. Largerand more diversified samples are needed. Thefindings would also be strengthened by sam-pling thrift economy participation patterns bothbefore and after economic hardship. Our sampleis also drawn from a religiously homogenouspopulation and consists of a disproportionatenumber of males. It is unlikely that a dif-ferent sample from a different location wouldsubstantially alter our results because religioushomogeneity, to the extent that it is tied to par-ticipation in local thrift economies, would onlyshift the overall level of participation in localthrift economies and not the relationship amongthe various local thrift economies themselves.As we are aware of no scholarly evidence indi-cating the direction of the relationship betweenparticipation in thrift economies and religiousaffiliation, we encourage future research toexplore this topic. Furthermore, because pre-vious research has shown that women are morelikely to engage in thrift economies (Herrmann,1996), the disproportionate number of malesin our sample likely puts a conservative biasto our results. Another limitation concerns thequestions available for analysis. We measuredwhat people state they shop for, not necessarilywhat they actually purchase. Although shop-ping and purchasing patterns are empiricallycorrelated, one is not necessarily a proxy forthe other. Future data collection efforts shouldcollect data on both purchases and shoppingpatterns.

In spite of these limitations, ThompsonCounty may be a harbinger of current andfuture trends. Declining economic fortunes may

motivate people to look for new, creative ways tostretch the family dollar. Local thrift economiesmay be beginning to occupy an essential placein mainstream America’s cultural repertoirefor economic adaptation to hard economictimes.

REFERENCES

Acock, A. C. (2005). Working with missing val-ues. Journal of Marriage and Family, 67,1012 – 1028.

The Associated Press. (2008a). Thrift stores: We’reseeing more middle-class shoppers. RetrievedOctober 6, 2008, from http://www.cnn.com/2008/LIVING/wayoflife/10/06/thrift.shops.ap/index.html?iref=topnews

The Associated Press. (2008b). While economy dives,thrift shops thrive. Retrieved August 4, 2009, fromhttp://today.msnbc.msn.com/id/27070237/

The Associated Press. (2009a, July 24). More turningto yard sales that stretch for miles. The New YorkTimes.

The Associated Press. (2009b). Need a few extrabucks? Hold a yard sale. Retrieved July 24, 2009,from http://www.msnbc.msn.com/id/32128645/ns/business-consumer news/from/ET

Bartkowski, J. P., & Regis, H. A. (2003). Charitablechoices: Religion, race, and poverty in the post-welfare era. New York: New York UniversityPress.

Blau, P. M., & Duncan, O. D. (1967). The Americanoccupational structure. New York: Wiley.

Conger, R. D., Rueter, M. A., & Elder G. H., Jr.(1999). Couple resilience to economic pressure.Journal of Personality and Social Psychology,76(1), 54.

Consumer Expenditure Surveys. (1984). Table 7.Housing tenure and race of reference person:Average annual expenditures and characteristicsof all consumer units, Consumer ExpenditureSurvey, 1984. Washington, DC: U. S. Bureau ofLabor Statistics.

Consumer Expenditure Surveys. (2008). Table 7.Housing tenure and race of reference person:Average annual expenditures and characteristicsof all consumer units, Consumer ExpenditureSurvey, 2008. Washington, DC: U. S. Bureau ofLabor Statistics.

Darley, W. K., & Lim, J. S. (1999). Effects of storeimage and attitude toward secondhand storeson shopping frequency and distance traveled.International Journal of Retail & DistributionManagement, 27, 311 – 318.

Dew, J. (2007). Two sides of the same coin? Thediffering roles of assets and consumer debt inmarriage. Journal of Family and Economic Issues,28(1), 89 – 104.


Dew, J. (2008). Debt change and marital satisfactionchange in recently married couples. FamilyRelations, 57(1), 60 – 71.

Dobbs, L. (2006). War on the middle class: Howthe government, big business, and special interestgroups are waging war on the American dreamand how to fight back. New York: Viking Adult.

Dudley, K. M. (2000). Debt and dispossession: Farmloss in America’s heartland. Chicago: Universityof Chicago Press.

Ehrenreich, B. (2006). Bait and switch: The (futile)pursuit of the American dream: New York: OwlBooks.

Ehrenreich, B. (2008). Nickel and dimed: On (not)getting by in America. New York: Holt.

Farber, H. S. (2005). What do we know aboutjob loss in the United States? Evidence fromthe Displaced Workers Survey, 1984 – 2004.Economic Perspectives, 2Q, 13 – 28.

Ferrell, J. (1990). Degradation and rehabilitation inpopular culture. Journal of Popular Culture, 3,89 – 100.

Fox, B. (1995). The new momentum in usedmerchandise. Chain Store Age, 71(8), 23 – 32.

Gieryn, T. F. (2000). A space for place in sociology.Annual Review of Sociology, 26, 463 – 496.

Hacker, J. (2006). The great risk shift: The assaulton American jobs, families, health care, andretirement and how you can fight back. Oxford:Oxford University Press.

Herrmann, G. M. (1996). Women’s exchange inthe US garage sale: Giving gifts and creatingcommunity. Gender and Society, 10, 703 – 728.

Herrmann, G. M. (2003). Negotiating culture: Con-flict and consensus in U.S. yard-sale bargaining.Ethnology, 42(3), 237 – 252.

Herrmann, G. M. (2004). Haggling spoken here:Gender, class, and style in US garage salebargaining. Journal of Popular Culture, 38(1),55 – 81.

Herrmann, G. M. (2006). Garage sales make goodneighbors: Building community through neighbor-hood sales. Human Organization, 65(2), 181 – 191.

Herrmann, G. M., & Soiffer, S. M. (1984). For funand profit: An analysis of the American garage sale.Journal of Contemporary Ethnography, 12(4),397.

Hochschild, A. R. (1989). Second shift: Workingparents and the revolution at home. New York:Viking.

Hochschild, A. R. (1997). The time bind: When workbecomes home and home becomes work. NewYork: Metropolitan.

Horne, S. (2000). The charity shop: Purpose andchange. International Journal of Nonprofit andVoluntary Sector Marketing, 5(2), 113 – 124.

Jacobs, J., & Gerson, K. (2004). The time divide.Cambridge, MA: Harvard University Press.

Koeber, C. (2002). Corporate restructuring, downsiz-ing, and the middle class: The process and meaningof worker displacement in the ‘‘new’’ economy.Qualitative Sociology, 25(2), 217 – 246.

Kreml, W. P. (1997). America’s middle class: Fromsubsidy to abandonment. Durham, NC: CarolinaAcademic Press.

Mauno, S., & Kinnunen, U. (1999). The effects ofjob stressors on marital satisfaction in Finnishdual-earner couples. Journal of OrganizationalBehavior, 20, 879 – 895.

Neumark, D., & Postlewaite, A. (1998). Relativeincome concerns and the rise in married women’semployment. Journal of Public Economics, 70(1),157 – 183.

Newman, K. (1988). Falling from grace: Theexperience of downward mobility in the Americanmiddle class. New York: Free Press.

Newman, K. (2000). No shame in my game: Theworking poor in the inner city. New York: VintageBooks.

Odgers, C. L., Moffitt, T. E., Tach,L. M., Sampson,R. J., Taylor, A., Matthews, C. L., & Caspi, A.(2009). The protective effects of neighborhoodcollective efficacy on British children growingup in deprivation: A developmental analysis.Developmental Psychology, 45, 942 – 957.

O’Reilly, L., Rucker, M., Hughes, R., Gorang, M., &Hand, S. (1984). The relationship of psychologicaland situational variables to usage of a second-order marketing system. Journal of the Academyof Marketing Science, 12(3), 53 – 76.

Overfelt, M. (2009). Secondhand stores shine in weakretail market. Retrieved August 4, 2009, from http://money.cnn.com/2008/12/31/smallbusiness/secondhand sales up.smb/index.htm

Papp, L. M., Cummings, E. M., & Goeke-Morey,M. C. (2009). For richer, for poorer: Money asa topic of marital conflict in the home. FamilyRelations, 58(1), 91 – 103.

Parker, R. (1972). The myth of the middle class:Notes on affluence and equality: New York: HarperCollins.

Rosenbloom, S. (2008, September 10). Thrift shopsprosper amid U.S. economic woes. The New YorkTimes.

Royston, P. (2007). Multiple imputation of missingvalues: Further update of ice, with an emphasis oninterval censoring. Stata Journal, 7, 445.

Rubin, L. B. (1994). Families on the fault line:America’s working class speaks about the family,the economy, race, and ethnicity. New York:Harper Collins.

Schmitt, J., & Baker, D. (2008). What we’re in for:Projected economic impact of the next recession.Challenge, 51(3), 27 – 42.

Strasser, S. (2000). Waste and want: A social historyof trash. New York: Macmillan.


Sullivan, T. A., Warren, E., & Westbrook, J. L.(2001). The fragile middle class: Americans indebt. New Haven, CT: Yale University Press.

Veblen, T. (1912). The theory of the leisure class: Aneconomic study of institutions. New York: VikingAdult.

Venkatesh, S. A. (2006). Off the books: The under-ground economy of the urban poor. Cambridge,MA: Harvard.

Warren, E., & Tyagi, A. W. (2004). The two-income trap: Why middle-class mothers andfathers are going broke. New York: BasicBooks.

Westman, M., Etzion, D., & Danon, E. (2001). Jobinsecurity and crossover of burnout in marriedcouples. Journal of Organizational Behavior, 22,467 – 481.

adapting to hard times: family participation patterns in local thrift economies

Documents