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. Author manuscript; available in PMC: 2011 Oct 1.
Published in final edited form as: Fam Relat. 2010 Oct;59(4):383–395. doi: 10.1111/j.1741-3729.2010.00610.x

Adapting to Hard Times: Family Participation Patterns in Local Thrift Economies

Spencer James 1, Ralph B Brown 2, Todd L Goodsell 2, Josh Stovall 2, Jeremy Flaherty 2
PMCID: PMC3011891  NIHMSID: NIHMS257816  PMID: 21197154

Abstract

Using survey data from a western U.S. county (N = 595), we examined how lower, middle, and higher income families negotiate a period of economic stress—the closing of a major employer in the community—through their shopping patterns. Specifically, we examined their participation in local thrift economies such as yard sales and secondhand stores. We found that lower and middle income households shop more frequently at these venues. They also tend to shop more for furniture and clothing, whereas higher income households tend to shop for antiques and trinkets. These relationships varied across the type of thrift economy examined. Overall, findings support the argument that engagement in thrift economies may constitute one mechanism families use during periods of economic stress.

Keywords: economic distress, family and social change

Downturns in the economy have meant that many families are struggling to make ends meet. Even before the large-scale collapse of the U.S. housing market in September 2008 and its devastating effects on global markets, traditional subsidies such as pensions, guaranteed health benefits, and other traditional allowances were already in decline (Ehrenreich, 2008). Americans work longer hours each week and for more years prior to retirement than just a generation ago (Jacobs & Gerson, 2004). The average U.S. family, even with multiple income earners, is less financially stable today, as indicated by higher risks of bankruptcy and greater volatility in wages and assets such as stocks, than it was in the early 1970s—a time of high inflation (Warren & Tyagi, 2004). Consequently, many families confronted by job insecurity, income loss, and increasing debt-to-asset ratio are also at risk of emotional distress, marital conflict, and anxiety because of their financial problems (Dew, 2008; Mauno & Kinnunen, 1999; Westman, Etzion, & Danon, 2001).

Although scholars have examined a variety of familial responses to economic uncertainty, many have focused on interspousal outcomes such as how economic pressure increased the risk of emotional distress (Conger, Rueter, & Elder, 1999), how changes in consumer debt predicted both the amount of time spent together and arguments over money (Dew, 2008; Rubin, 1994), and how economic distress influenced marital conflict (Papp, Cummings, & Goeke-Morey, 2009). Research on how families have attempted to negotiate a period of economic stress through an analysis of household consumption patterns has received less attention. Therefore, we examined household consumption patterns of lower, middle, and higher income-earning households, specifically as it is related to shopping in what we call thrift economies, such as yard sales and secondhand stores. Using survey data collected in a Western county of the United States, we examined both the frequency with which households participated in various local thrift economies and the types of items for which they tended to shop.

We first present how economic restructuring and financial uncertainty have created an environment where economic adaptation becomes not only desirable but also necessary. We then pursue a discussion on how participation in local thrift economies, such as yard sales and thrift stores, could constitute one particular way that families help make ends meet in times of difficult economic circumstances. Finally, the methods and results are described and analyzed, followed by a discussion regarding the role local thrift economies play in mitigating difficult economic circumstances.

Economic Restructuring and Financial Uncertainty

In their seminal work on social stratification, Blau and Duncan (1967) found evidence of “two distinctive boundaries limiting downward mobility, one between blue-collar and white-collar occupations, the other between blue-collar and farm groups” (pp. 58 – 59). These boundaries formed, in essence, a de facto safety net for blue- and white-collar workers in how far they could possibly “fall.” Today, it appears that the boundaries identified by Blau and Duncan have all but disappeared. Over the past decade or longer, economic restructuring has led to increased financial uncertainty for many U.S. households, as many formerly secure sectors in U.S. labor markets no longer guaranteed financial, occupational, or health benefits, thus leaving their workers vulnerable to potential financial distress. Hacker (2006), for example, found that the risk of losing half or more of one’s income in a given year increased by nearly 150% from 1970 to 2002 alone. Although factors such as divorce and bankruptcy contributed to this trend, job instability was primary among them.

Periods of large-scale economic stress potentially affect households of all levels of economic status, including higher income households. These too have become more vulnerable to economic insecurities because of restructuring in the professional and managerial occupations, in effect making the risk of job loss more equally distributed across all income earners (Farber, 2005). Ehrenreich (2006) reported that as nationwide unemployment among those with professional credentials increased to nearly 20% of the unemployed, many in this group began to seek employment incommensurate with their qualifications. At the same time, the steady erosion of manufacturing jobs in the United States pushed many blue-collar workers into the ever-expanding service industries, where wages, benefits, and opportunities for advancement for unskilled workers were generally far below that of their former jobs. Increased global competition in financial and labor markets appears to have eroded many previously taken-for-granted safeguards, such as stable employment, reliable benefits, and retirement programs, against social and economic decline (Dobbs, 2006). Thus, insecurity has become the norm in the “new” economy (Koeber, 2002), epitomized by the majority of workers in the service sector who simply move from one low-wage job to the next (Newman, 2000). Even before September 2008, when unemployment rates were still fairly low, “job churning” (the difference between job loss and unemployment rates) was high and continues to climb (Farber).

The effects of downward mobility, facilitated by declines in real wages and benefits, have been compounded by rising costs of living, especially in the housing market. The cost of housing has risen dramatically over the past several decades and remains high compared with other necessities such as food costs, even after the burst of the housing bubble. For example, the average American household spent twice as much of their disposable (after-tax) income on housing as food in 1984, whereas today the ratio is closer to three times as much (Consumer Expenditure Surveys 1984, 2008). One key factor in this was the ease of obtaining credit, which led to high consumer debt and often bankruptcy and financial insolvency (Sullivan, Warren, & Westbrook, 2001). Consequently, over the past two decades, many Americans have expressed a “fear of falling” from their comfortable middle-class lifestyles because of wage and job insecurity (Ehrenreich, 2006; Newman, 1988). Global financial restructuring has also precipitated a dramatic increase in the number of dual-career families during the past two decades (Hochschild 1989, 1997; Neumark & Postlewaite, 1998). But as Warren and Tyagi (2004) made clear, many of these families are finding that even two incomes are not enough to keep pace with increased costs of living, adding to their financial distress. Thus, as we move into 2010, even more families will likely experience unemployment, loss of health benefits, and decreases in household income (Schmitt & Baker, 2008).

As the American cost of living increases while earning potentials decline, we may observe families beginning to alter their consumption patterns to accommodate such social change. For example, the failure of income to keep pace with rising housing costs may push individuals to look for creative ways to stretch the family dollar without accumulating greater debt (Herrmann 2003, 2004, 2006; Herrmann & Soiffer, 1984).

Thompson County (a pseudonym), where this study was conducted, is a possible example for these creative consumption patterns. The Housing Opportunity Index (HOI), which measures the proportion of homes in the area affordable to a family earning the median income, was approximately 40. The index’s mean for the years 1991 – 2009 was roughly 50, with a standard deviation of 15, and a range of nearly 60. In 2003, when the data for our study were collected, the index score was approximately 75. During this time period (1991 – 2009), the median home price in Thompson County increased by almost 200%, whereas the median income rose by less than 150%.

Thrift Economies

Periods of economic decline such as the one most recently experienced should, in principle, inspire new approaches by households to help stretch the family dollar. In fact, one approach to maintaining social standing that has recently received considerable attention in the popular press is the increased popularity of what we term “thrift economies,” generally consisting of thrift/secondhand stores and yard sales (The Associated Press 2008a, 2008b, 2009a, 2009b; Overfelt, 2009; Rosenbloom, 2008). Interestingly, very little scholarly attention has been devoted to this topic.

Thrift economies consist of a variety of economic activities and outlets such as thrift stores, 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 be based as much on social objectives as economic ones (Herrmann 2003, 2006).

Traditionally, these types of thrift economies functioned on a cycle of donations from the relatively wealthy and consumption by those who are not (Horne, 2000). This recycling of secondhand goods enabled less-advantaged individuals to meet basic needs and simultaneously provided more privileged individuals an outlet for the disposal of unwanted items (Strasser, 2000).

Despite their ubiquity, the way in which individuals from varying socioeconomic back-grounds engage these thrift economies remains a largely unexplored question (see, however, Herrmann & Soiffer, 1984 for a notable exception). We do know, however, that anecdotal evidence seems to suggest that thrift economies are becoming a more popular option. The question remains, to whom? To what degree do all levels of household income earners participate in these thrift economies during periods of economic stress brought about by declines in real wages and loss of job security, coupled with rising costs of living? We should anticipate that a new group of “bargain hunters” will join the ranks of existing collectors and the underprivileged in participating in this arena (Herrmann, 2006; O’Reilly, Rucker, Hughes, Gorang, & Hand, 1984; Strasser, 2000). As they do, perhaps contrary to Veblen’s truism at the turn of the 20th century, the turn of the 21st century may see people of higher socioeconomic status looking down as a way to soften their fall rather than perpetually “looking up.”

Indeed, there is emerging evidence that the stigma surrounding thrift stores and similar outlets is declining. Darley and Lim (1999) noted:

In recent years, thrift stores have been seeking and receiving the acceptance of middle-class consumers. Many consumers are turning to secondhand stores or second-order retail outlets for their merchandise. Thus, the demographics of the consumers of thrift stores are shifting from the poverty-stricken to reflect the average consumer (p. 311; emphasis added).

By the mid-1990s, the typical thrift store shopper was employed, between the ages of 25 – 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 closer identification with the rich than with those occupying lower social strata.

Although thrift economies are appendages of the larger, formally regulated economy, as noted above, they do differ from it in several important ways and “represent a truly creative cultural response to the extended economic and social crises of life in advanced industrial society” (Herrmann & Soiffer, 1984). Although a cash nexus ostensibly abounds, a purely businesslike motivation toward monetary gain does not. In fact, items are often priced (and at times, even given away) to facilitate a sense of community among those involved (Herrmann, 1996). Yet, this is by no means an indication that social concerns supplant instrumental rationality. Herrmann and Soiffer identified 10 types of shoppers at yard sales, ranging from retailers whose livelihoods depended on finding resalable goods to friends, neighbors, or relatives of the seller with little to no economic interest in the sales’ outcome. People can thus have both economic as well as social motivations for participating in thrift economies as they seek to develop methods that “satisfy their socially defined needs in ways that expend as little as possible of their discretionary funds” (Herrmann & Soiffer). These unique aspects make thrift economies as manifest through secondhand stores, yard sales, and so on, potentially appealing to households of all social and economic standing during times of economic stress and may be particularly relevant in the context of social status maintenance and economic hardship.

To test if this was in fact the case, we started with the assumption that income and other sociodemographic variables (e.g., gender, marital status, race, age, education, financial distress, and household size) are linked to the likelihood of household participation in various thrift economies. Specifically, our research examined both the frequency (i.e., how often individuals shop at these outlets) and purpose (i.e., what they shop for) of engagement in local thrift economies. We examined how higher, middle, and lower income earners stretch their family dollar by the relative frequency with which they shop these outlets. We also examined the particular items for which they shop. We assumed that higher income households are more likely to shop for non necessities, such as antiques and trinkets, whose value is tied to its workmanship and history rather than its utility, which is of more importance to lower and middle income earners (Ferrell, 1990). Consequently, less-privileged households may be more likely to shop for quotidian necessities such as clothing and housewares.

Method

Sample

Data for the study were collected in 2003 from a western county (Thompson County) that had recently experienced the loss of a major employer. An 18-page survey intended to collect personal, financial, and attitudinal information was mailed to a random sample of households in Thompson County. Several indicators in the questionnaire allowed us to examine the relationship between income levels and shopping in thrift economies. The survey used an initial mail sample of 1,150 individuals purchased from an industry-leading list provider. The male or female head of house (self-designated) was instructed to respond to the survey and return it. A business reply envelope and a $2 incentive were included. Of the 723 surveys returned, 595 contained valid response data.

Many families in the county were under considerable economic stress due to the loss of the major employer, which affected nearly everyone in the county. Local businesses and services suffered, and local governments struggled to find ways to compensate for loss of taxes the employer provided. Our sample represented a unique opportunity to examine household consumption patterns in their local markets during a period of economic stress. In other words, as Gieryn (2000) asserted, we gain a better understanding of how families act under certain conditions when we sociologically situate (or “place”) them in the local context. Consequently, our findings at the very least help illustrate how households in this particular community responded to this economic stress through their participation in local thrift economies. It is also possible that the way these families adapted to hard economic times is a harbinger of what other households and communities across the United States would experience during the national recession in the latter part of the decade.

Compared with other counties in the United States, Thompson County is in some ways unique. The average household contains about three and a half people compared with about two and a half nationally. Socioeconomically, the county enjoys slightly higher than average levels of income and education. The county has a smaller proportion of families in poverty than the national average, although it did experience an economic downturn in the early 2000s when a major factory laid off workers and declared bankruptcy in 2002. Additionally, 90% of the county belongs to the “Salvation Christian Church” (a pseudonym). Although this is potentially problematic for our study, because many areas of the United States have significantly lower levels of religious homogeneity, Bartkowski and Regis (2003) noted that such a phenomenon is relatively common in some areas of the South, Midwest, Intermountain West, and the West Coast. Such religious homogeneity will, however, bias our estimates to the extent that membership in the Salvation Christian Church is linked to engagement in local thrift economies. This would be seen in the overall level of participation in thrift economies (i.e., our estimates may be systematically higher or lower in other populations). Ironically, such high levels of religious homogeneity would not affect the relationships between various local thrift economies (e.g., yard sales and thrift stores), such as those examined here. Consequently, our results may or may not be similar to other regions of the country, as families today are experiencing a more systemic economic crisis.

Models and Missing Data

We estimated two models. The first model employed binary logistic regression to estimate the likelihood of purchasing certain items in local thrift economies. We then estimated an ordinal logistic regression model to examine the frequency of engaging local thrift economies. Our primary interest in both analyses is the effect of household income level on engagement in local thrift economies. We controlled for other sociodemographic characteristics that may be associated with both income levels and the likelihood of engaging in local thrift economies.

Like most surveys, this one has missing values. Although the amount and proportion of missing data were small on each variable (never more than 7% of the sample and usually around 3%), missing data, or more precisely the pattern of missing data, can affect the estimation procedures used to obtain coefficients and standard errors (Acock, 2005). For this reason, we generated multiple sets of plausible values that represented a distribution of plausible values using Stata’s ice program (Royston, 2007). Plausible values were used to replace each missing value, allowing us to “model the missingness.” Thirty datasets were generated and jointly analyzed using Stata’s micombine command. By combining estimates from each, coefficients and standard errors were adjusted for bias caused by missing data. After imputation and before analysis, the data were examined for irregularities that may have occurred during the imputation process. No meaningful variations were found in the means, standard deviations, or ranges. The results remained substantively unchanged when we used multiple imputation, mean replacement, listwise deletion, or full-information maximum likelihood techniques to deal with missing data.

Shopping Variables

We employed two sets of dependent variables. The first set contained information about whether respondents shopped for specific items (furniture, clothing, trinkets, antiques, housewares, electronics, appliances, or books) at a thrift store or yard sale (1 = yes). The second set included how frequently (0 = never, 1 = once or twice year, 2 = at least once a month) respondents shopped (for any item) at outlets in local thrift economies. Three distinct types of outlets were examined. First, we examined shopping patterns at Thrifties, the largest and most frequented thrift store in Thompson County on which data were collected. To preserve the greatest level of detail available in the data, we analyzed shopping patterns at Thrifties separately. Second, respondents were asked how often they shopped at all other thrift stores, excepting Thrifties. Finally, respondents were asked how often they shopped at yard sales. (Although many thrift stores and yard sales contain designer products, the outlets under study here rarely have such items. The vast majority of items are useable but with significant wear. Highly desirable items are unlikely to be purchased at these outlets, with the exception of trinkets and antiques.)

Sociodemographic Characteristics

Sociodemographic characteristics include the respondent’s gender (1 = female), marital status (1 = married, 0 = all others), race (1 = White, 0 = non-White), age (coded in 5-year increments ranging from a low of 16 and capped at 60+), education (1 = less than high school, 2 = high school graduate, 3 = some college, 4 = college degrees, 5 = postgraduate degree), household size (measured continuously and capped at seven or more people), and income. Family financial distress was a standardized, additive index (α = .90; all factor loadings were at least .80) of five questions. These questions asked how difficult (ranging from 5 = very difficult to 1 = very easy) it was to cover common family and household expenses during the past 3 months. These include mortgage and rent, medical bills, health insurance, grocery costs, and credit card bills. Annual income was measured using a piecewise linear spline with three nodes to leverage differences between income groupings. The first node represented lower income earners, operationalized as those who reported annual income is less than $30,000. Middle income earners, the second node, represented those reporting incomes between $30,000 and $79,999. Higher income earners reported making more than $80,000. To obtain each node, dummy variables for each income grouping were created. Those in the given income group were given a value of 1, whereas all others were given a value of 0. To ensure that our results were robust to a variety of alternative specifications, we also ran models employing income as a continuous measure and as an ordinal measure with cut points at each $10,000 increment. The results remained substantively similar to those reported here, so we report the results with the dummy variables only.

Results

Table 1 presents descriptive statistics for the study sample. Participation in local thrift economies was relatively common among sample respondents with the average respondent reported shopping at thrift stores and yard sales about once or twice a year. The sample consisted predominantly of White, married males. Although a gender-balanced sample would be ideal, the disproportionate number of males in our sample serves to make our results more conservative because women are more likely than men to engage in the thrift economy (Herrmann, 1996). The average respondent was in his or her mid-40s, had some college education, lived in a house with about three other people, and earned around $50,000 annually. The high cost of living in Thompson County (the costs of housing, transportation, food, and health care in Thompson County are similar to analogous costs in far larger Western cities such as Seattle, Washington, and Portland, Oregon) means that $50,000 does not go very far.

Table 1.

Mean, Standard Deviation, and Range of Sociodemographic and Shopping Frequency Variables: Descriptive Statistics (N = 595)

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

a

Gender: 0 = male; 1 = female.

b

Marital status: 0 = divorced, separated, or single; 1 = married.

c

Race: 0 = non-White; 1 = White.

Table 2 shows the results from the binary logistic regressions that estimated whether respondents reported shopping for particular items at Thrifties, other thrift stores, or yard sales. All estimates were adjusted for respondents’ gender, marital status, race, age, education, household size, and financial distress. We compared lower and middle income earners with high income earners to assess whether income level was associated with shopping patterns at each outlet. On average, about 16% of the sample shopped for each item at each outlet. At least 5% of the sample shopped for each item with one exception—appliances at yard sales. Respondents reported shopping for each item most frequently at Thrifties.

Table 2.

Odds Ratios From Binary Logistic Regression Estimates of Shopping Patterns by Income Distribution, Item Shopped for, and Venue (N = 595)

Item Income
Category* 		Thrifties Thrift
Stores		 Yard Sales
Furniture Lower 1.11 4.02* 1.41
Middle 1.07 2.70* 2.08*
Clothing Lower 1.88* 3.90*** 1.51
Middle 1.40 2.39* 1.29
Trinkets Lower 0.73 0.941 0.90
Middle 0.70 1.57 1.21
Antiques Lower 0.31** 0.71 0.64
Middle 0.44** 1.06 1.02
Housewares Lower 1.78 4.10* 1.45
Middle 1.44 2.49 1.54
Electronics Lower 2.96* 3.25 1.44
Middle 1.36 4.00 1.32
Appliances Lower 1.61 5.12 0.56
Middle 1.22 2.73 0.98
Books Lower 1.36 2.08 0.87
Middle 1.11 1.71 1.11
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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.

In line with expectations, we found that lower and middle income earners were more likely than higher income earners to shop for each type of good, with the exception of antiques and trinkets. Indeed, significant differences were found in item-specific shopping patterns between lower and higher income earners for five of the eight items. The odds of shopping for furniture, clothing, and housewares at thrift stores were four times higher for those from the lower income category than those from the higher income categories. Lower income earners were also more likely to purchase clothing and electronics at Thrifties than higher income earners. Middle income earners, for their part, appeared more similar to those in the lower income group than those in the higher income grouping. The odds of a middle income earner shopping for furniture at a yard sale or thrift store were over twice as great as the odds of a higher income earner doing so. They were also more likely to shop for clothing at thrift stores. As anticipated, higher income earners were more likely to shop for antiques at Thrifties than those in other groups.

Table 2 provides some evidence of differential engagement in the local thrift economies by income level. As expected, we found that one’s income level predicted the items for which respondents shopped in thrift economies, net of controls. Lower and middle income earners appeared to be more likely to shop for necessities like clothing, furniture, and electronics, whereas higher income earners were more likely to shop for antiques. Note, however, the variation in this pattern across each respective outlet. We found relatively few differences across shoppers at yard sales, a moderate amount among shoppers at Thrifties, and quite a few among those shopping at other thrift stores. For example, we found no differences between income categories in the likelihood of purchasing clothing at yard sales. At Thrifties, we found that being in the lower income category was associated with a 88% increase in the odds of shopping for clothing. At other thrift stores, however, we found that those from both lower and middle income groups were more likely than those from the higher income group to purchase clothing there. Such nuances should be kept in mind throughout the article.

To assess the robustness of the relationship between income level and participation in local thrift economies, we move from an examination of the particular item respondents reportedly shopped for to an analysis predicting how frequently respondents shopped at Thrifties, other thrift stores, and yard sales. We regressed the outcome variable, frequency of shopping at each of the three outlet types, on our splines for income level while controlling for other factors thought to be associated with both income level and engaging in local thrift economies. Results are presented in Table 3, which displays the logits, their standard errors, and the odds ratios (obtained by exponentiating the logit) associated with each of the three dependent variables. A value less than one indicates a negative effect, whereas a value greater than one signifies a positive effect.

Table 3.

Ordinal Logistic Regression Model Predicting Frequency of Engaging in Three Thrift Economies, With Robust Standard 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 1.02
Married 0.23 0.16 1.25 −0.05 0.16 0.95 0.03 0.15 1.03
White 0.11 0.22 1.12 0.07 0.29 1.07 −0.21 0.24 0.81
Age 0.03 0.02 1.03 0.003 0.02 1.00 −0.04 0.02 0.96
Education −0.06 0.05 0.94 −0.03 0.05 0.98 −0.11* 0.05 0.90
Household size 0.13*** 0.03 1.14 0.09** 0.03 1.10 0.11*** 0.03 1.12
Lower income 0.74*** 0.22 2.10 0.30 0.22 1.36 0.39 0.23 1.48
Middle income 0.37** 0.13 1.45 0.26 0.14 1.30 0.31* 0.13 1.37
Financial distress 0.05 0.06 1.05 0.15** 0.06 1.17 0.07 0.06 1.08
Cut points
 1 0.56 0.37 0.67 0.42 0.19 0.39
 2 2.16*** 0.38 1.85 0.43 1.21** 0.40
χ 2 220.734 220.664 221.846
df 11 11 11
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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 year at Thrifties. The analogous numbers for other thrift stores and yard sales are 45 and 55%, respectively. The proportional odds assumption was met.

*

p < .05.

**

p < .01.

***

p < .001.

The first three columns display results from the equation that predicted frequency of shopping at Thrifties. We found that household size and income were the two best predictors of moving from one frequency category to the next. Being in the lower income category was associated with a doubling of the odds of moving to the next higher frequency category of shopping at Thrifties. Being in the middle income category increased the odds by 45% relative to the higher income group. Each one-person increase in household size was associated with a 14% increase in the frequency of shopping at this particular outlet.

The next three columns demonstrated a some-what different pattern. This time both income categories failed to reach traditional significance levels, though the coefficient for middle income earners was trending (p = .063). Rather, it appeared that those with higher levels of financial distress were more likely to shop at thrift stores other than Thrifties. Each one-unit increase in household financial distress was associated with a 17% increase in the odds of shopping more frequently at thrift stores. We again found evidence for a robust, positive effect for household size.

The final three columns of Table 3 displayed the same predictive model as before, this time employing frequency of shopping at yard sales as the outcome. We found that middle income earners were more likely to shop frequently at yard sales. Having an income in the middle range of the sample was associated with 37% higher odds of shopping more frequently at yard sales than those in the high income category. The coefficient for the lower income grouping was trending toward significance (p = .089) and positive as well, indicating a greater likelihood of shopping at yard sales than those in the higher income category. Household and education were significant as well.

Taken together, our results provided evidence that one’s income level was negatively linked to the likelihood of engagement in thrift economies and provided support for the position that hard economic times may encourage people to engage in this particular adaptive strategy to make ends meet while maintaining social status. There is variation in this relationship, however, across the particular types of local thrift economies. At Thrifties, for example, income appeared to be a strong predictor of the frequency of shopping at this particular thrift store. This was not the case at other thrift stores. Rather, it was financial distress that appeared to predict how frequently a given respondent shopped there. Note, however, that Thrifties enjoyed the largest market share among the county’s thrift store (as illustrated by the fact, noted above, that 70% of the sample reported having shopped there at least once, compared with just 45% at other thrift stores). It is possible, therefore, that the results for Thrifties yield a better indication of the relationship between income and participation in local thrift economies in Thompson County.

Discussion

Using data collected from a western county that had recently experienced the loss of a major employer, we explored the relationship between income and the likelihood of participating in local thrift economies, which we defined as shopping at thrift stores and yard sales. We found that both lower and middle income earners were more likely to shop at these venues than those making higher incomes. They were also more likely to shop for items such as furniture and clothing. Conversely, higher income earners were more likely to shop for antiques and trinkets. These relationships, however, varied across the type of thrift economy. The relationship between income and participation in thrift economies was generally negative and significant, with higher income levels being associated with a lower likelihood of engagement in thrift economies.

On the basis of Table 3, the relationship, however, appears to be the strongest at Thrifties and weakest at other thrift stores, with yard sales falling in between the two extremes. Although there is at least some evidence that income is associated with the frequency of shopping at each outlet type, the evidence is weakest when predicting the frequency of shopping at thrift stores other than Thrifties, where only middle income earners appear to be more likely to shop frequently; this conclusion, however, is based on trending significance. Thrifties does, however, maintain the unquestionably largest market share of the three thrift economies examined; it is probable, therefore, that the relationship between income and participation in thrift economies in Thompson County mirrors the results displayed regarding Thrifties than the other two outlets. Other thrift stores and yard sales clearly play an important role in the local thrift economy.

These findings support the motivating premise of this article that one mechanism for economic adaptation of households to hard financial times may be engagement in local thrift economies. When housing and other costs increase without a concomitant augmentation of salary or wages, families may obtain more items in such places, where sales tax is generally not charged, and merchandise is typically priced below retail value. Both of these strategies can aid households in their efforts to stretch the family dollar. We observe, however, that this does not occur uniformly across all outlets examined here. Income differences are observed at all three outlet types, being less pronounced at yard sales than at thrift stores (when considering all thrift stores together). One reason for this may be the privileged position social ties are accorded over economic concerns at yard sales, as noted by Herrmann and Soiffer (1984). The overall trend, however, demonstrated a negative effect of income on participation in local thrift economies.

Such efforts will likely become more necessary and pronounced if current economic trends, characterized by increasing income and wealth stratification, continue in the future. Recent work by Dew and colleagues, for example, demonstrates the impact of changes in family financial status on family relations (Dew, 2007, 2008). Families may therefore seek to alleviate such pressures by making conscious decisions to maintain social status via engagement in local thrift economies.

Rather than following Veblen (1912) in perpetually looking upward, many families may now be looking downward for the softest possible landing. In light of our findings regarding participation in local thrift economies by higher, middle, and lower income earners, assumptions about class aspirations and desires may need to be tailored to current social and economic circumstances. For many, Veblen’s observation that individuals bend their energies to live up to the ideal prescribed by those in the next highest social stratum may be increasingly difficult to achieve. As participation in local thrift economies is added to the already long and creative list of how Americans adapt to difficult economic conditions (see the remainder of this journal issue), a simple analysis of participation in a thrift store-based economy may speak volumes about how Americans redefine themselves in the new global economy. Shifting economic and social structures may make the century-old dictum of “looking-up” the social ladder increasingly difficult, as many in the middle and higher income brackets appear to be glancing downward trying to calculate the softest possible landing.

The duration and intensity of economic downturns may determine whether such downward glances constitute a reshuffling of the socioeconomic landscape or simply a temporary, adaptive behavior quickly jettisoned upon the return of a more family-friendly economic climate. In other words, families may return to purchasing new items at more traditional outlets. This question merits further investigation. A realistic perception of consumption patterns during times of economic distress may be important to policymakers interested in jump-starting the economy after such times. Whether such behavior is permanent or transitory, the shift from a manufacturing to a service-based economy has created fewer secure jobs. Declining job security and fewer opportunities for advancement may inhibit upward mobility (Dudley, 2000; Ehrenreich, 2006; Rubin, 1994). The reduction in “white-collar” jobs has led to less security (Kreml, 1997), precipitating even greater downward mobility.

Interestingly, we also found that middle income earners’ consumption patterns were more similar to those of lower income earners than were higher income earners. Middle income earners tended to shop, similar to their lower income counterparts, for consumer goods such as furniture and clothing. This article provides quantitative evidence, then, for what others have observed anecdotally—that those earning middle incomes participate in local thrift economies. Such venues are no longer reserved as avenues simply for meeting economic need but may now function as places where middle income earners negotiate status maintenance during hard economic times. In light of such findings, we may need to expand our scope to include the important role such outlets may play in the economic life of families and households.

The fact that these data were collected during a period of relative economic prosperity at the national level provides particular theoretical leverage. At the time of data collection, the HOI was about 75, meaning 75% of the homes in the area were affordable to a family earning the median income. It is likely, therefore, that our estimates of participation in local thrift economies are conservative. Individuals and families may be even more likely to engage local thrift economies in areas and circumstances where family finances experience higher levels of strain. Households confronting financial difficulty look for ways to maintain social standing, and they may very well do so outside the normal bounds of the traditional market (Venkatesh, 2006). In this particular county, distinguished by large families, engagement in local thrift economies may be seen first as an alternative and then become more mainstream for people from all income levels because of the need to provide for additional family members. Thus, shopping in these outlets could become more normative—nonstigmatized because everyone finds it necessary even in nonfinancially distressed times such as when these data were drawn.

These results provide some limited insight into possible strategies for family practitioners and policymakers. A realistic perception of family consumption patterns during times of economic distress may be important to policymakers because increased support to thrift stores, whether by providing financial support, publicity, or a venue for such sales, could generate needed income and employment to struggling communities. These venues could also provide jobs and job training for the un(der)employed. Furthermore, to the extent that those interested in community development are able to organize or facilitate community-run yard sales or thrift stores, similar to the way religious organizations such as the Salvation Army and Goodwill (whose original funding came primarily from the Methodist church) do, collective efficacy, which has been tied to a multitude of positive individual and community level outcomes (Odgers et al., 2009), can be fostered via increased opportunities for social networking. These outlets also supply additional options for purchasing household goods. This may become increasingly salient as interrelated issues such as financial problems, a weakening economy, and high levels of credit may drive shopping at outlets like those described here into the normative category, instead of the exceptional category, for family consumer behavior.

In such an economic environment, we should expect such social norms to emerge, norms that are more fitting the economic and social realities of today. Opportunity costs for scouring thrift stores and yard sales are small in the context of reduced employment opportunities. Our analysis of thrift economy participation patterns by income groupings may shed some light not only on emerging strategies of how Americans are stretching their purchasing power but also on an emerging gestalt that is redefining their social and economic orientation. Many may now be looking for the softest landing possible instead of aspiring to compete with the Joneses.

Finally, another important issue is the extent to which a local thrift economy becomes an integral component to an increasingly large segment of the local population. When this happens, the line between the more formal economy and local thrift economies may become increasingly blurred. Consequently, communities may actually become economically dependent on their local thrift economy. If and when this occurs, it potentially opens a new relationship of regulation and oversight from local governments. It also potentially redefines the responsibilities of large-scale participants—such as Thrifties—in the overall local economy.

Several limitations in the present research should be noted. The data are drawn from just one county at one point in time. Although we can demonstrate associations between income and accessing local thrift economies, we cannot address issues of causality or change. Larger and more diversified samples are needed. The findings would also be strengthened by sampling thrift economy participation patterns both before and after economic hardship. Our sample is also drawn from a religiously homogenous population and consists of a disproportionate number of males. It is unlikely that a different sample from a different location would substantially alter our results because religious homogeneity, to the extent that it is tied to participation in local thrift economies, would only shift the overall level of participation in local thrift economies and not the relationship among the various local thrift economies themselves. As we are aware of no scholarly evidence indicating the direction of the relationship between participation in thrift economies and religious affiliation, we encourage future research to explore this topic. Furthermore, because previous research has shown that women are more likely to engage in thrift economies (Herrmann, 1996), the disproportionate number of males in our sample likely puts a conservative bias to our results. Another limitation concerns the questions available for analysis. We measured what people state they shop for, not necessarily what they actually purchase. Although shopping and purchasing patterns are empirically correlated, one is not necessarily a proxy for the other. Future data collection efforts should collect data on both purchases and shopping patterns.

In spite of these limitations, Thompson County may be a harbinger of current and future trends. Declining economic fortunes may motivate people to look for new, creative ways to stretch the family dollar. Local thrift economies may be beginning to occupy an essential place in mainstream America’s cultural repertoire for economic adaptation to hard economic times.

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