Millions of workers labor in nonstandard employment relationships, such as part-time and temporary jobs. Yet little is known about how the job search process is influenced by such positions. This article examines the ways that job seekers' application pools and search processes are shaped by nonstandard employment relationships. Among our findings is evidence that job seekers are more likely both to perceive nonstandard positions as being below their skill level and to receive job offers for those positions, presenting many workers with a complex trade-off between obtaining a job and working in a position that is poorly matched to their skill level. Together, our findings demonstrate how the job search process is shaped by nonstandard employment relationships with broad consequences for labor market inequality.

Keywords

nonstandard work, job search, labor markets, inequality

The U.S. economy has faced numerous changes in recent decades, including the increased use of technology in the workplace, the decline of organized labor and unionization, the polarization of job quality, as well as the utilization of nonstandard employment relationships (Claw-son and Clawson 1999; Hyman 2018; Kalleberg 2000, 2009, 2011; Smith 1997). Indeed, millions of workers in the United States now labor in part-time and temporary positions (Bureau of Labor Statistics 2018a, 2018b; Katz and Krueger 2016). In response, a significant body of scholarship has emerged to understand the underlying forces that drive the prevalence and use of nonstandard labor (Autor 2003; Kalleberg, Reynolds, and Marsden 2003). Researchers have also examined the consequences of nonstandard labor for workers' material and subjective well-being as well as their career trajectories (Epstein et al. 1999; Kalleberg, Reskin, and Hudson 2000; [End Page 130] Pedulla 2016). This research has provided valuable insights into the causes and consequences of nonstandard employment in the United States and beyond.

Limited scholarship, however, has investigated the ways that the prevalence of nonstandard employment relations shape the job search process. Yet, given that these positions occupy a large role in the economy, interesting questions emerge about who applies for these jobs and the methods used to find nonstandard employment. Additionally, questions arise about how workers perceive the quality of the nonstandard positions to which they apply and why they might submit applications for these types of positions. In this article, we address four sets of issues at the nexus of nonstandard employment and the job search process.

The first set of questions centers on the application pools to which job seekers submit applications. Scholars have found compelling evidence of racial and ethnic, gender, age, and other sociodemographic differences in the workers who actually labor in nonstandard employment positions (Bureau of Labor Statistics 2018b; Katz and Krueger 2016). Yet we have limited information about whether workers from different sociodemographic backgrounds are more likely to apply for part-time and temporary positions. It is possible that these groups of workers are more likely to be in nonstandard jobs due to the positions for which they receive job offers rather than due to the positions for which they actually submit applications. Thus, this article explores sociodemographic differences in the employment relationships of the job openings to which job seekers submit applications.

Additionally, we ask whether job seekers' application pools focus on one employment relation type—full time, standard, or nonstandard—or whether their application pools are better characterized by a mixed status, whereby a single job seeker applies for multiple job types. Specifically, we ask whether job seekers apply for full-time, standard positions, and nonstandard positions simultaneously. It is possible that during the search for work, individuals know what type of job they want and search entirely for jobs that have a single type of employment relationship. However, given the prevalence of nonstandard employment, job seekers' application pools may in fact be more complex.

Second, we probe the search methods that are used during the job search process and how these relate to applications for nonstandard positions. The search methods—network-based, informal methods versus formal methods, for example—may differ between applications to standard and nonstandard positions. Perhaps workers are more likely to rely on family, friends, and acquaintances to find out about nonstandard positions but use the internet and other formal sources to learn about full-time, standard jobs. Understanding these issues will assist in better conceptualizing the matching process between workers and job openings in the labor market, where nonstandard jobs make up a significant share of the available positions.

Third, we examine how job seekers perceive the quality of the nonstandard positions to which they apply. Part-time and temporary jobs tend to be of lower quality. On average, they offer lower wages and are less likely to provide health and pension benefits than full-time, standard positions (Kalleberg, Reskin, and Hudson 2000), although variation in these positions is significant. Yet we know little about how job seekers perceive the quality of the nonstandard jobs to which they are submitting applications. Thus, we examine whether job seekers perceive nonstandard jobs to which they submit applications as being beneath their skill level, an important component of job quality.

Finally, we ask whether applying for nonstandard jobs may be a way for workers to get a toehold in the labor market. It is possible that employers are less stringent about their requirements for hiring for nonstandard positions and, thus, workers may be more likely to receive job offers for positions that are part time or temporary than they would be for full-time, permanent, standard jobs. If job seekers are more likely both to receive job offers from nonstandard positions and to perceive these jobs as beneath their skill level, an important trade-off emerges for job seekers: getting a job versus using their skills.

To date, many of these issues have been largely absent from conversations on nonstandard [End Page 131] employment relationships. This gap in the literature is due in part to data limitations. Addressing these topics requires having detailed information about whether the individual applications submitted by job seekers are for standard or nonstandard jobs. Surveys with information about the applications submitted by individual job seekers are limited and even fewer collect information about the employment relationship that corresponds to the jobs to which the individual applied. We draw on an original data set that contains this information to address these issues.

the job search process and nonstandard work

A significant body of scholarship has pointed to the many changes that have occurred in the U.S. economy over the past decades. Often referred to as the "new economy," researchers note how the economic landscape in the contemporary United States is generally characterized by the relative decline of manufacturing jobs and the rise of service-sector jobs, the increased use of technology in the workplace, the outsourcing of production, the globalization of trade, the polarization of job quality, and the rise and prevalence of nonstandard employment relationships (Autor 2003; Hollister 2011; Kalleberg 2000; Smith 1997; Wright and Dwyer 2003; Clawson and Clawson 1999; Kim and Sakamoto 2008). This final aspect of the "new economy" is our central focus. Despite questions about the extent of the rise of nonstandard work (Bernhardt 2014)—such as part-time and temporary agency employment—we know that millions of workers work in such positions in the United States (Bureau of Labor Statistics 2018a; Katz and Krueger 2016), making our understanding of how these types of positions intersect with job searching important.

Before moving on to the ways that nonstandard employment relationships may shape the job search process, it is useful to define what we mean by nonstandard employment. Throughout this article, we focus on two types of nonstandard work: part-time work and temporary employment.1 Part-time work is the most common type of nonstandard employment and refers to individuals who work fewer than thirty-five hours per week (Kalleberg 2000). Roughly 17 percent of the U.S. labor force is in a part-time position (Bureau of Labor Statistics 2018a). Among those in part-time positions, approximately a quarter are involuntarily working part time, preferring a full-time position. Part-time employment shows some occupation and industry variation. Individuals in service, sales, and office occupations as well as those in the wholesale and retail trade and hospitality and leisure industries are more likely to be in part-time positions (Bureau of Labor Statistics 2018c, 2018d).

By contrast, temporary employment has to do with the time horizon for an individual's employment, rather than the number of hours that they work per week. Thus, temporary employment can be full time or part time. It can also be structured in multiple ways. One common type of temporary work is Temporary Help Agency (THA) employment, when the worker is on the payroll of one company (the temp agency) but performs their daily work at another company. Importantly, the THA is also the legal employer of the temp worker (Autor 2003). Among THA workers, 46 percent would prefer a permanent position, indicating that a significant proportion of THA workers are involuntarily in those positions (Bureau of Labor Statistics 2018b). Not all temporary workers, however, are employed by temp agencies. Companies can hire workers directly on a temporary basis with the mutual understanding that the worker's involvement at the company will be discontinued at some point in the future.

An important feature of some temporary positions—both agency based and those that are directly through companies—is that these positions can sometimes become permanent. According to a study by the American Staffing Association, roughly half of temporary workers perceived temping as a pathway to permanent [End Page 132] employment. They also find that roughly one-third of temporary workers end up receiving an offer for a permanent position from the employer for which they temped (American Staffing Association 2017). In our analysis, we distinguish between temporary positions that are unlikely to become permanent and those that have the potential to become permanent.

It is important to note that our analysis does not cover applications for all types of nonstandard employment. For example, we do not have information about whether applications were submitted for on-call jobs, "gig" work, or independent contracting positions.2 Yet, we are able to examine two key types of nonstandard work: part-time employment and temporary employment. Next, we move on to thinking about how the job search process may be shaped by these positions in the economy. To begin, we discuss how key sociodemographic characteristics of workers may shape the types of jobs to which they apply.

The Sociodemographic Concentration of Nonstandard Work

Research documenting the ways that nonstandard work is unevenly distributed across the population is significant. Women, for example, are much more likely than men to work part time, particularly among prime-age workers. More than 70 percent of part-time workers between the ages of twenty-five and fifty-four in the United States are women (Bureau of Labor Statistics 2018a). Historically, part-time work was largely seen as a way for women to balance paid employment with their disproportionate role in childcare and housework (Kalleberg 2000; Tilly 1992; Epstein et al. 1999). And, although the gender gap in part-time work has declined over time, it remains pronounced. The gender gap for THA employment, by contrast, is limited (Bureau of Labor Statistics 2018b; Katz and Krueger 2016).

In terms of part-time work—particularly involuntary part-time work—there are also racial disparities. Among prime-age workers in part-time positions, black men and black women are more likely than white men and white women, respectively, to involuntarily be working part time (Bureau of Labor Statistics 2018a). Racial disparities are also significant in temporary agency employment, African Americans being three times as likely and Hispanic workers nearly twice as likely as whites to work through a temp agency (Katz and Krueger 2016). Thus, in general, workers of color are more likely to be involuntarily working part time and employed through temporary help agencies.

Age also structures workers' experiences of nonstandard employment. Despite similar overall rates of part-time work for individuals of different ages, differences are significant in terms of whether they are working part time voluntarily or involuntarily. Among part-time workers, prime-age workers (twenty-five to fifty-four-year-olds) are more likely to involuntarily work part time and less likely to voluntarily work part time than both younger and older workers (Bureau of Labor Statistics 2018a). Additionally, workers between twenty and twenty-four are relatively more likely to be working through temporary help agencies (Bureau of Labor Statistics 2018b). However, older workers are only slightly more likely to be in THA positions than mid-career individuals (Bureau of Labor Statistics 2018b).

Estimates also indicate that education matters in determining who labors in nonstandard positions. Insofar as nonstandard positions are less desirable, workers with more education may be able to avoid these types of employment relationships (Kalleberg, Reskin, and Hudson 2000). Indeed, evidence is significant that workers with a bachelor's degree or higher are less likely to be in THA positions (Bureau of Labor Statistics 2018b). Nonetheless, at least for voluntary [End Page 133] part-time work, variation by educational attainment is limited (Dunn 2018). The gender gap in part-time work, however, persists across all levels of education (Dunn 2018).

Some of these patterns are likely stronger among intersections of social positions. For example, women's employment is more likely than men's to "sag" during the transition to marriage and family formation (Goldin and Mitchell 2017). Additionally, women are more likely than men to work part time, due in part to the gendered demands of caretaking and household labor (Kalleberg 2000; Epstein et al. 1999). Married women may therefore be particularly likely to apply for part-time positions. Additionally, race and gender may intersect to produce divergent likelihoods of applying for nonstandard positions (Browne and Misra 2003). Thus, we also examine whether intersectional patterns exist among the applications submitted by job seekers.

Many of these findings are based on surveying job incumbents about their positions. In other words, the estimates are drawn from the workers who actually labor in these positions. Outstanding questions exist, however, about whether workers differentially apply for nonstandard positions along the same sociodemographic axes as they work in those positions. We might imagine that the association between one's demographic group and the types of jobs one applies to would be strongest among workers who voluntarily work in those positions. By contrast, we may expect a weaker correlation between demographic characteristics and application type among groups who are involuntarily in those positions. Regardless, if we see differences between the types of workers who apply for nonstandard positions and the types of workers who are incumbents in nonstandard positions, it may point to processes on the demand side of the labor market that are allocating workers to different types of employment relationships.

Job Searching in the New Economy

Given the prevalence of nonstandard positions in the economy and the large proportion of workers who are in these positions, workers' job searches necessarily include these types of jobs. To date, however, little research has documented how the job search process is influenced by nonstandard positions. One aim of this article is to document the ways that part-time and temporary positions are involved in shaping the structure of job seekers' application pools as well as the processes by which they find employment.

In terms of the structure of individuals' application pools, two entirely different types of job seekers are possible: those who apply solely for full-time, standard positions and those who apply solely for nonstandard positions. It is easy to imagine a worker who knows that they are looking for a full-time, permanent job and, thus, discards any job postings or job leads that are not for a full-time, permanent position. Similarly, it would not be surprising if a job seeker who was solely looking for part-time jobs to assist with balancing various work and nonwork demand—such as caring for a child or elderly parent—limited their search to part-time positions.

It is also possible, however, that many job seekers' goals and preferences are less clear cut. They may be open to different types of positions—including nonstandard jobs—or they may at least not screen out nonstandard positions if they appear to be a reasonable fit on other dimensions (such as occupation or location). If this is the case, then the structure of job seekers' application pools may be mixed, whereby they submit applications for multiple types of positions—both full-time, standard positions and nonstandard positions—at the same time. As a descriptive exercise, it is interesting to see which type of search most accurately reflects reality.

If, indeed, some individual workers are applying for different types of positions at the same time, this is one important way that nonstandard employment influences the labor market, complicating workers' application pools. The existence of these mixed application pools would also raise questions about whether workers with those mixed pools are different from the workers applying for positions with only one type of employment relationship. Existing theoretical perspectives on job search provide insights about what types of workers may be more likely to apply for mixed application pools. [End Page 134]

Workers face myriad challenges during the job search process. From discrimination to high levels of competition to figuring out a job and organization that is a good fit, job searching can be challenging (Bertrand and Mullainathan 2004; Pager, Western, and Bonikowski 2009; Pedulla 2018; Rivera 2012). Workers who are facing challenges may expand their job search to include additional occupations, company types, or potentially employment relations. Devah Pager and David Pedulla, for example, find that African Americans include a greater range of occupational categories and characteristics in their application pools than observationally similar whites (2015). They also present evidence that concerns about discrimination underlie this racially distinct search behavior. Beyond discrimination, workers who are struggling to find employment, a process that can be filled with feelings of demoralization and self-blame (Sharone 2014), may become less stringent in their search criteria (Krueger and Mueller 2016). As a worker spends more time unemployed, for example, they may loosen their job search criteria and begin to apply for jobs, regardless of whether they are full-time, standard positions or part time or temporary. Thus, there are reasons to think that individuals who face discrimination and other challenges in the labor market may be more likely to have heterogeneous or mixed application pools.

Network-Based Job Search

One of the central concerns in sociological scholarship on job search has been the methods that individuals use to find work. Of particular interest has been the network-based, informal channels through which people find out about jobs (Granovetter 1973; Mouw 2003; for reviews, see Castilla, Lan, and Rissing 2013; Trimble and Kmec 2011). Network-based job search can consist of multiple channels, including friends, family, acquaintances, and co-workers (present or former). Scholars have also drawn the distinction between strong and weak network ties, whereby the latter are likely to be more beneficial for job seekers, in part because they are likely to connect the job seeker with nonredundant information about job leads (Granovetter 1973; Yakubovich 2005). These types of network-based job search methods are contrasted against more formal channels, such as internet-based search. Indeed, network-based search is quite important in understanding the job matching process given that approximately 50 percent of jobs are found through some sort of informal channel (Corcoran, Datcher, and Duncan 1980; Granovetter 1973; Mouw 2003).

Network-based job search may be successful for many reasons (Fernandez, Castilla, and Moore 2000; Kmec 2006). First, it can provide a job seeker with key resources, such as information about the opening. Additional resources may include the network alter—the referrer in the job search context (Smith 2005; Marin 2012)—putting in a good word for the job seeker at the company or putting the job seeker in touch with someone at the company (Castilla, Lan, and Rissing 2013). Second, network-based job search may have a signaling function. When a job seeker is referred by someone for a given job posting, that individual is putting their reputation on the line for the job seeker and, at least in some way, vouching for them. Thus, employers may interpret job seekers with a referral as a positive signal about their ability, status, and potential productivity (Castilla, Lan, and Rissing 2013).

Network-based job search could intersect with nonstandard work in multiple, competing ways. On the one hand, nonstandard types of positions may be less likely to be posted in formal places. It is even possible that many nonstandard positions are not posted at all or are quickly generated for a specific project, particularly in the case of temporary employment. Thus, network-based search may provide valuable information about these types of nonstandard job openings that would not be otherwise available to job seekers. In this case, we could expect that nonstandard job applications would be more likely to have been submitted after hearing about the opening through a network-based channel.

By contrast, it is also possible that workers are not as open with their social networks about looking for part-time work and temporary employment. Thus, the alters in one's network may not share information with a job seeker about positions that are not full time [End Page 135] and permanent. In this case, we may expect to see that job seekers are less likely to apply for nonstandard jobs that they heard about through their network connections and more likely to find these openings through formal mechanisms. Of course, it is also possible that the search methods job seekers use when applying for standard and nonstandard positions will not differ.

Perceptions of Job Quality: Are Nonstandard Jobs Below a Worker's Skill Level?

There are multiple ways to think about and measure job quality. On many key dimensions, scholars have documented that part-time and temporary jobs are of lower quality, on average, than full-time, standard positions. For example, 44.2 percent of men and 35.2 percent of women in temporary help agency positions have low wages, compared with 11.2 percent of men and 16.0 percent women in regular full-time jobs (Kalleberg, Reskin, and Hudson 2000). Similarly, part-time workers are more likely than full-time workers to have low wages. Arne Kalleberg, Barbara Reskin, and Kenneth Hudson also present compelling evidence that access to important benefits—such as health insurance and pensions—is much lower among nonstandard workers (2000). Beyond these material aspects of job quality, qualitative scholarship has probed the lived experiences of workers in nonstandard jobs. For both part-time and temporary employment, research in this area has documented significant stigma and devaluation for the workers who labor in these positions (Henson 1996; Rogers 1995; Smith 1998). Evidence also indicates that temporary employment is correlated with psychological morbidity and, in some cases, more negative workplace attitudes (for a review, see Virtanen et al. 2005; Broschak, Davis-Blake, and Block 2008).3 Yet, variation in job quality is significant within categories of nonstandard employment (Haley-Lock 2009), such as the distinction between retention and secondary part-time work (Tilly 1996).

The material and subjective experiences of workers while they are in nonstandard positions have been examined, but data limitations have made it difficult to explore how workers perceive nonstandard positions to which they might apply before they actually take on those positions. In this article, we examine one such perception: the skill level of the job. Specifically, we examine whether the lower quality of nonstandard jobs found among job incumbents also translates to workers' perceptions of these jobs before they work in them. In other words, do workers' perceptions of a job application's skill level correlate with the employment relationship of the position?

A Toehold in the Labor Market?

Debate in the literature has been significant about whether nonstandard jobs can serve as stepping stones to future employment opportunities or whether they trap workers, making it difficult for them to advance into better positions down the road (Addison, Cotti, and Surfield 2009; Addison and Surfield 2009; Autor and Houseman 2010; Fuller 2011; Pedulla 2016). Another way to conceptualize this issue, however, is to consider whether it is easier for workers to obtain job offers when applying for nonstandard positions compared to full-time, standard jobs. Rather than asking about the future consequences of nonstandard work—the "stepping stone" versus "dead end" comparison—we could consider whether nonstandard jobs offer a "toehold" in the labor market.

This may be the case for multiple reasons. Employers may be less selective in hiring decisions for nonstandard jobs since the individual will not be a permanent employee or will be working fewer hours per week than if they were full time. Additionally, with some types of nonstandard workers, it is easier to terminate or fire the individual than it is if they are a full-time permanent worker (Autor 2003). Thus, employers and hiring managers may be less stringent in the selection criteria or more likely to take a risk on a worker for a temporary position because they can easily let the worker go if they are not working out. If, indeed, this is the case, [End Page 136] then nonstandard positions may serve as a point of entry for workers into the labor market. If obtaining a job offer for a nonstandard position is easier than obtaining an offer for a full-time, standard job, then these types of positions may enable workers to enter the labor market and gain some experience, which may prove useful down the road. However, insofar as nonstandard positions are of poorer quality or limit workers' future labor market opportunities (Pedulla 2016), an easy entry point into nonstandard positions may not be beneficial for workers' longer-term careers.

data and me thods

To address these issues, we draw on original panel data, which we call the National Longitudinal Study of Job Search (NLSJS). The NLSJS follows a national sample of 2,060 job seekers over eighteen months. The data were collected in collaboration with Gfk (formerly Knowledge Networks). The sampling design for the Gfk panel—referred to as KnowledgePanel—is based on a combination of random-digit dial methods and address-based sampling methods. Their sampling frame covers approximately 97 percent of all U.S. households (Knowledge Networks 2011).

In total, the NLSJS consists of nine survey waves, which were conducted between February 8, 2013, and November 30, 2014. The first seven waves were conducted roughly six weeks apart over approximately eight months. The eighth wave was conducted one year after the baseline. The final survey (wave nine) took place approximately eighteen months after the baseline survey. The target population for the NLSJS was non-institutionalized adults ages eighteen through sixty-four who were residing in the United States and who had looked for work over the previous four weeks. The NLSJS also oversampled African American respondents.4 For our analyses, we limit our sample to job seekers who reported at the baseline survey that they wanted to work at least thirty-five hours per week in the job for which they were searching.5 This sample restriction is important because it removes individuals who would ideally like to work part time. Thus, it is important to remember that the individuals in our analytic sample want to be working full time.

The NLSJS collected detailed information about many aspects of the job seekers' experiences, such as sociodemographic and background characteristics, employment histories and experiences, as well as job search behaviors. Important for our purposes, respondents at each wave were asked to provide information about the five most recent jobs they had applied to in the past four weeks. Then, they were asked a series of questions about each job opening that they listed, including whether the job opening was for a full-time position, a part-time position, a temporary position with the possibility of becoming permanent, or a temporary position that was unlikely to become permanent; and the search method through which the job seeker heard about the opening (family member, friend, online, and so on). Thus we are able to analyze the pools of applications submitted by each job seeker to examine whether application pools are segregated or mixed in terms of employment relations, [End Page 137] how applications for nonstandard jobs are correlated with key demographic characteristics, and what search methods are used to apply for nonstandard jobs.

Variable Construction

For our analyses, one key measure is the employment relationship of the position for each application submitted by a respondent. As noted, for each job application that they listed, survey respondents were asked to select "all that apply" from the following choices: full time, part time, temporary position that is unlikely to become permanent, and temporary position with the possibility of becoming permanent. These categories are not mutually exclusive. Our classification structure for the employment relationship of a given application is as follows. Applications that respondents indicated were both full time and one of the three other categories are classified as mixed positions. This category includes, for example, individual job openings that are temporary full-time positions as well as positions that could be full time or part time. Beyond mixed applications, though, we are interested in whether the pool of applications submitted by a job seeker was mixed. A respondent's application pool is coded as a mixed application pool if an applicant applied to both full-time, permanent positions and any other kind of job during their job search.6 The application pool measure is at the level of the respondent, not the application.

To capture the search methods used for each application, respondents were asked how they found out about each job opening to which they applied. Specifically, they were asked about each application: how did you hear about the position with [employer name]? They were then told to select all options that apply from a list of potential sources (for example, family, friends, online search). In our analyses, we separately compare the four network-based job search methods—family member, friend, acquaintance, and employer or coworker—to formal job search methods. We combine all formal types of job search—newspaper ad, online search, employment agency, help wanted sign, and directly contacting the employer. Given that these job search methods are not mutually exclusive, if a respondent used both a network-based search method (such as friend or family member) and a formal method (such as searching online) in applying to a position, we consider their search method to be whichever network-based method they selected.7

To capture how long individuals have been unemployed, we asked respondents how long they had been unemployed in the twenty-four months prior to the baseline survey. We use this item to capture individuals' unemployment duration (in weeks) leading up to baseline. This variable is coded as 0 for anyone who was employed at baseline (regardless of whether they were unemployed at some point in the twenty-four months before baseline). Some respondents who indicated they were unemployed at the time of the baseline survey did not answer the question about unemployment duration. We coded these respondents as having the mean unemployment duration on this variable and include in our models an indicator variable for whether they were missing on the unemployment duration item.

We also analyze whether nonstandard positions are perceived as requiring lower skills than full-time, standard positions. For each application, respondents were asked which of the following options best describes the position with the employer to which they were applying: a position that is below my level of skill or experience, a position that is appropriate for my level of skill or experience, or a position that is above my level of skill or experience. We used these responses to code whether each position is below the applicant's skill level. The variable [End Page 138] is coded 1 if the respondent selected that the application was for a position below their skill level, and 0 otherwise.

In one set of analyses, we also examine whether nonstandard applications are more likely to result in job offers than applications for full-time, standard positions. Our "job offer" outcome variable is taken from an item that asked respondents at each wave whether they had received an offer from any of the companies—by name—that they had applied to in that wave as well as any of the companies that they had applied to in previous waves. This item is then used to create a variable that captures, for each application, whether the application resulted in a job offer.8

Standard sociodemographic variables were collected by Gfk from their panel members. We use these items to capture respondents' gender, age, race-ethnicity, educational attainment, and marital status.9 These sociodemographic characteristics are included as covariates in the models. The survey also collected information about respondents' occupations in their current or most recent job, which we control for. Specifically, respondents indicated their most recent job title on the survey in an open text format. Then, trained coders at the University of Wisconsin Survey Center classified these open-text responses into three-digit Standard Occupational Classification (SOC) codes for occupation. In our analyses, we use the two-digit SOC codes for major occupational categories. All models control for job seekers' prior occupation.10

Two additional controls are included in our models. First, we control for the intensity of respondents' job search. Specifically, we control for the number of applications that respondents reported submitting over the four weeks prior to each survey wave (logged to adjust for skew). Additionally, we control for the number of waves that a respondent was in the sample. Descriptive information about our sample is presented in table 1.

Results

Our results proceed as follows. First, we examine the application pools of job seekers by looking at sociodemographic differences in who applies for each type of nonstandard position. We then explore whether individuals submit applications to more than one type of job (for example, full time, standard and nonstandard). We then examine the prevalence and predictors of these types of mixed application pools. Next, we examine whether different job search methods are used for nonstandard job applications relative to full-time, standard job applications. Then, we examine the perceived quality of job seekers' applications for nonstandard positions relative to full-time, standard jobs. Finally, we examine whether nonstandard applications are more likely to result in job offers than applications submitted for full-time, standard positions.

Sociodemographic Differences in Applying for Nonstandard Work

We begin by examining demographic differences in submitting applications for positions with particular types of employment relationships. For these analyses, each observation captures one of the applications that the job seeker submitted. Each application is nested within a given survey wave and each survey wave is [End Page 139]

Table 1. Summary Statistics of Analytic Sample Source: Authors' calculations. Note: Respondents can report at most five job applications in each survey wave. The maximum possible number of applications for any single respondent is thus forty-five across the nine survey waves. Respondents who sent no applications are excluded from the sample. Four respondents did not indicate their employment status. Of the 452 respondents who reported they were unemployed, twenty-three did not provide an estimate of the duration of unemployment in the baseline survey.
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Table 1.

Summary Statistics of Analytic Sample

Source: Authors' calculations.

Note: Respondents can report at most five job applications in each survey wave. The maximum possible number of applications for any single respondent is thus forty-five across the nine survey waves. Respondents who sent no applications are excluded from the sample. Four respondents did not indicate their employment status. Of the 452 respondents who reported they were unemployed, twenty-three did not provide an estimate of the duration of unemployment in the baseline survey.

nested within a given respondent. We use a multinomial logistic regression model, with standard errors clustered by respondent, to examine the sociodemographic correlates of applying for a nonstandard job. We move through five key sociodemographic groups—gender, race-ethnicity, age, marital status, and education—and then examine potential interactive effects between these different characteristics. In the model, the omitted category for the dependent variable is an application for a full-time, standard position. The findings are presented in table 2.

Gender

In terms of gender, we find that wom en are significantly more likely than men to apply for part-time jobs relative to full-time jobs. However, no gender differences are discernable in applying for temporary-to-permanent nor temporary positions. Women are, however, more likely than men to submit an application for a position that could take on multiple employment relationships (for example, a job that could be either part time or full time, or a position that is temporary, but full time).

Race-ethnicity

The lack of statistically significant differences between the types of applications submitted by non-Hispanic white workers and workers of color is striking. Indeed, black workers are no more or less likely to apply for part-time or temporary-to-permanent positions than white workers are. In addition, they are marginally statistically significantly less likely to apply for temporary positions. This is quite surprising given that African Americans are significantly overrepresented in temporary jobs in the broader economy. Additionally, we see that [End Page 140]

Table 2. Multinomial Logistic Regression Model of Type of Position Applied to Source: Authors' calculations. Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work in a week. +p < .1; *p < .05; **p < .01; ***p < .001
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Table 2.

Multinomial Logistic Regression Model of Type of Position Applied to

Source: Authors' calculations.

Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

[End Page 141] Hispanic workers are marginally significantly more likely than non-Hispanic white workers to apply for part-time positions, but show no differences in applying for temporary positions. In general, it is surprising that the racial and ethnic differences found among incumbents in nonstandard positions in existing scholarship—particularly temporary work—do not appear in the application pools of job seekers.

Age

In terms of age, existing research suggests that non-prime-age workers—individuals younger than twenty-five and older than fifty-four—are more likely to be in nonstandard employment. Therefore, it is likely that both younger and older job seekers will be more likely to apply for nonstandard positions than workers at the peak of their careers. Our data provide general support for this prediction.

Younger workers, between the ages of eighteen and twenty-four, are more likely than workers between thirty-five and forty-four to apply for part-time positions, temporary-to-permanent positions, and mixed positions (all relative to full-time standard positions). For older workers, evidence indicates that workers between fifty-five and sixty-four are more likely to apply for part-time positions and for temporary positions (than for full-time positions) than middle-aged workers, aged thirty-five to forty-four. Thus, in general, non-prime-age workers are more likely to submit applications to nonstandard positions, particularly part-time positions, than workers in the middle of their careers. These findings are generally consistent with the age composition of incumbents in nonstandard positions.

Marital Status

Limited differences emerge in the types of applications submitted by workers with different marital statuses. Although, workers who are married or cohabiting are marginally significantly less likely than never married workers to apply for temp-to-perm positions and significantly less likely to apply for mixed positions.

Education

In terms of education, key differences emerge. We see that having completed college or more—versus having just some college—is associated with being less likely to apply for part-time jobs and positions that offer multiple potential employment relationships and marginally significantly less likely to apply for temporary-to-permanent positions. This suggests that people higher on the educational attainment ladder are more likely to be focused on full-time, standard employment during their job search.

Interactive Effects

We next explore possible interactions between key sociodemographic characteristics. The full models for these analyses are presented in table A1. First, we examine whether the relationship between gender and submitting applications for nonstandard employment is shaped by a worker's marital status.11 Our findings indicate that the relationship between being a woman and applying for a part-time position is stronger among married or cohabiting women than women who have never been married.

Second, we were interested in whether gender intersected with race-ethnicity to shape the likelihood of applying for nonstandard employment. Overall, we see limited evidence of this. In general, the interactions between the gender of the job seeker and the race-ethnicity of the job seeker are not statistically significant. However, the data demonstrate that the relationship between being a woman and applying for a temporary-to-permanent job is weaker among black women than among white women. Thus, instances where gender and race intersect to shape whether applicants apply for nonstandard positions are limited.

Together, these findings provide some evidence that the demographic differences that are found among incumbents in nonstandard [End Page 142] positions are mirrored in the application pools that job seekers submit. One important finding that diverges from this pattern, however, is the relationship between race and ethnicity and nonstandard employment. While black and Hispanic workers tend to be overrepresented in nonstandard positions, particularly temporary employment, they do not appear more likely to apply for these positions.

Mixed Application Pools

Our next set of analyses explore the diversity of application pools by the type of employment relationship within the same individual. Specifically, we ask whether individual applicants submit pools of applications that contain more than one employment relationship. This could mean that an individual, for example, applies for both full-time and part-time positions during their job search. Descriptively, our data indicate that these types of mixed application pools are quite common. Of the respondents in our sample, 55.18 percent have mixed application pools, applying for standard and nonstandard positions alongside one another. Indeed, only about one-third (33.38 percent) applied solely for full-time, standard jobs. Roughly 11 percent applied solely for nonstandard positions. Thus, for more than half of the job seekers in our sample, their application pools consisted of applications for multiple types of positions.

Next, we examine the demographic predictors of whether an individual's application pool contains mixed application types. To do this, we generated a three-category variable for whether a respondent's application pool contained only full-time, standard applications; a mix of full-time, standard and nonstandard positions; or only nonstandard positions. In table 3, we estimate a multinomial logit model where the dependent variable is the three-category variable capturing the employment relationships of respondents' application pools. The omitted category for the dependent variable is having an application pool that is only full-time, standard positions. The full set of controls discussed is also included in the models. For these analyses, there is only one observation per respondent in the data set. Additionally, it is important to remember that the job seekers in our analytic sample indicated that they wanted to work at least thirty-five hours per week and that the unemployment rate during the data collection period was still relatively high (Bureau of Labor Statistics 2018e).

The results from in table 3 reveal that mixed application pools are far from randomly distributed across job seekers. Women, on average, are more likely to have mixed application pools—relative to full-time, standard application pools—than men. Black workers are marginally statistically significantly more likely than white workers to apply for mixed application pools, relative to full-time standard application pools.12 Additionally, both younger workers (eighteen to twenty-four) and older workers (fifty-five to sixty-four) are significantly more likely to have mixed application pools than middle-age workers. Highly educated individuals—those with at least a bachelor's degree—are less likely to apply for more than one job type, compared to individuals with just some college. Finally, workers who have been unemployed for longer durations are more likely to have mixed application pools.

Together, the findings in table 3 suggest that individuals who belong to groups that may experience less advantage in the labor market—such as women, less educated workers, and workers who have been unemployed for longer periods of time—are more likely to apply for multiple job types, including nonstandard positions alongside their search for full-time, standard jobs. These analyses document two important patterns about how the job search process is shaped by the prevalence of nonstandard employment. First, mixed application pools are common: more than half of the individuals in our sample apply to more than one job type across their set of applications. Second, mixed application pools are not randomly distributed and are correlated with key sociodemographic characteristics. [End Page 143]

Table 3. Multinomial Logistic Regression Model of Whether the Respondent Applied to Both Full-Time and Nonstandard Positions Source: Authors' calculations. Note: Standard errors in parentheses. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table 3.

Multinomial Logistic Regression Model of Whether the Respondent Applied to Both Full-Time and Nonstandard Positions

Source: Authors' calculations.

Note: Standard errors in parentheses. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

[End Page 144]

Table 4. Multinomial Logit Model of Type of Informal Job Search Method Used Source: Authors' calculations. Note: Standard errors in parentheses. All standard errors clustered on applicant. Demographic controls include gender, race-ethnicity, age, marital status, and educational attainment. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table 4.

Multinomial Logit Model of Type of Informal Job Search Method Used

Source: Authors' calculations.

Note: Standard errors in parentheses. All standard errors clustered on applicant. Demographic controls include gender, race-ethnicity, age, marital status, and educational attainment. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

Nonstandard Work and Search Methods

In the next set of analyses, we examine variation in the search methods through which individuals find out about job openings with different employment relationships. It is possible that applications submitted for nonstandard positions—part-time, temporary, temporary-to-permanent jobs—are more likely than full-time job applications to be the result of informal, network-based job search practices, such as hearing about the opening from family, friends, acquaintances, or employers or coworkers. However, it is also possible that the often lower pay and lower status that come with nonstandard positions make it so that individuals use formal channels for these types of positions and reserve network-based search for full-time, standard positions.

Here we examine whether people are more or less likely to hear about nonstandard job openings through their family, friends, acquaintances, and coworkers or employers. Table 4 presents the results of a multinomial logistic regression model, where whether the job opening was heard about through family, friends, acquaintances, or coworkers or employers (relative to through a formal channel) is regressed on the employment relationship of the application and a host of sociodemographic variables and additional controls.13 [End Page 145]

The findings reveal that acquaintances—the quintessential weak ties—play a particularly important role in the job searches of individuals who are applying for nonstandard positions. For part-time, temporary-to permanent, and temporary positions, job seekers are more likely to have heard about the opening from acquaintances than from formal channels. Although family is significantly more likely than formal methods to lead to applications for temporary positions, there is no association between part-time work and hearing about the opening through family. Openings for part-time positions as well as temporary-to-permanent positions are more likely to be heard about from friends than from formal channels. Workers are also more likely to hear about temporary positions from coworkers or employers. Thus there is some variation in the types of positions heard about through network-based channels. Further, acquaintances appear to be particularly useful types of ties through which individual hear about nonstandard job openings. Future scholarship would be well served to further probe the mechanisms driving these different processes.

The Perceived Skill Level of Nonstandard Applications

Our previous analyses examined the job search process: who applies for nonstandard jobs, what do application pools look like, and what types of methods are utilized to apply for those positions. Next, we turn to issues of perceived job quality. Specifically, we examine whether job seekers are more likely to perceive applications for nonstandard positions to be below their skill level relative to positions for full-time, standard jobs.

Table 5 presents estimates from logistic regression models where the dependent variable is whether the job seeker perceives the application to be for a position that is beneath their skill level. The key explanatory variable is the employment relationship of the position. Model 1 is a logistic regression model with the full set of sociodemographic covariates and other controls. A clear pattern emerges: applications to part-time positions, temp-to-perm positions, temporary positions, and mixed status applications (relative to full-time positions) are more likely to be perceived as below the applicant's skill level.

Table 5. Logistic Regression Models of Whether Job Is Perceived to Be Below One's Skill Level Source: Authors' calculations. Note: Standard errors in parentheses. Standard errors in model 1 are clustered on applicant. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Additionally, model 1 includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. Applications where the respondent did provide information about the perceived skill level of the position are excluded from the analysis. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table 5.

Logistic Regression Models of Whether Job Is Perceived to Be Below One's Skill Level

Source: Authors' calculations.

Note: Standard errors in parentheses. Standard errors in model 1 are clustered on applicant. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Additionally, model 1 includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. Applications where the respondent did provide information about the perceived skill level of the position are excluded from the analysis.

+p < .1; *p < .05; **p < .01; ***p < .001

[End Page 147]

Model 2 is also a logistic regression model but includes respondent-specific fixed effects. Including respondent-specific fixed effects enables us to compare perceptions of a job's skill level for applications for standard and nonstandard jobs for the same individual. Thus the model removes concerns about time-invariant unobserved individual heterogeneity. The findings in model 2 closely parallel those in model 1, with nonstandard applications being positively correlated with perceptions of the position being below the applicant's skill level. The findings in table 5 thus provide compelling evidence that applications submitted to nonstandard positions are perceived by job applicants to be beneath their level of skill.

Next, we examined whether these skill perceptions vary by workers' sociodemographic characteristics (the results are presented in table A2). Two key findings emerge from these analyses. First, the association between part-time work and perceiving that a job is below one's skill level is weaker for women than for men. Given that respondents in our analytic sample desire a full-time job, this finding suggests that women are able to find part-time work that is a better match for their skill level. For men, this is more of a challenge. This finding is consistent with the idea that part-time work is more normatively "appropriate" for women than it is for men. Second, we find that black workers are more likely than white workers to perceive the temporary jobs that they apply to as being below their skill level. This in particularly interesting because black workers are no more likely than white workers to apply for temporary jobs. Moreover, they are no more likely to perceive full-time, standard jobs as being below their skill level. Thus, this finding suggests that when black workers apply to temporary positions, they are particularly likely to apply for jobs that are highly at odds with their skill set. Although this could point to the particular challenges the black workers face in the labor market, such as discrimination, future work would be well served to further investigate what may be driving this pattern.

A Foot in the Door? Nonstandard Applications and Job Offers

Our final set of analyses pivot toward a distinct issue: can nonstandard jobs provide a toehold for workers in the labor market? In other words, are applications for nonstandard positions more likely to result in job offers? In table 6, we address this question. For each application submitted over the survey period, we collected information about whether it resulted in a job offer. After a respondent listed an application, we asked at that wave and then in all future waves whether it had led to a job offer. Thus we are able to examine whether applications submitted for nonstandard positions, relative to standard positions, are more likely to result in a job offer.14

Model 1 in table 6 is similar to the previous models we presented—a logistic regression model, with standard errors clustered by respondent, and controls included for a broad set of sociodemographic variables and other covariates. The findings show that applications submitted for any type of nonstandard position (with the exception of mixed applications, which is marginally statistically significant) are more likely to result in a job offer than applications submitted for full-time, standard jobs.15 Also, we find evidence that, net of a broad set of controls, black workers are less likely to receive job offers than their white counterparts.

Given the structure of our data, we are also able to address this question using a within-person comparison approach. In other words, we can look at whether—for the same job seeker—they are more likely to receive job offers [End Page 148]

Table 6. Logistic Regression Models of Whether an Application Resulted in an Offer Source: Authors' calculations. Note: Standard errors in parentheses. Standard errors in model 1 are clustered on applicant. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Model 1 also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table 6.

Logistic Regression Models of Whether an Application Resulted in an Offer

Source: Authors' calculations.

Note: Standard errors in parentheses. Standard errors in model 1 are clustered on applicant. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Model 1 also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

[End Page 149] for applications submitted to nonstandard positions. Given that more than half of the respondents have mixed application pools, this approach provides us with a large group of job seekers to analyze with this approach. Model 2 in table 6, which includes individual-level fixed effects, demonstrates that this within-person analysis produces similar results. The same worker is more likely to receive job offers for nonstandard positions than they are for full-time, standard job openings.

There may be some questions about whether respondents actually end up taking the offers that they receive for nonstandard positions. Our data support the idea that they do. Respondents report that they plan to accept roughly 85 percent of the job offers that they receive. This pattern is similar across the different types of employment relationships. Indeed, a test for differences in proportions of offers that were planned to be accepted indicates that no statistically significant variation across types of applications. The idea of nonstandard positions providing a path to employment that is easier than obtaining a full-time, standard position and providing a toehold for workers therefore has some support. Yet, as the previous analyses demonstrated, these nonstandard positions are also more likely to be perceived to be below a worker's skill level. The quality of these nonstandard jobs may thus be a concern, resulting in a complicated trade-off for workers between obtaining a job and the quality of that job.

discussion and conclusion

The starting point for this article was the observation that millions of workers labor in nonstandard jobs, such as part-time or temporary positions. Yet little is known about how the job search process—a key social and economic process—is shaped by these types of positions. We have drawn on panel data about the job search process to examine the ways that job seekers' application pools are influenced by nonstandard employment relationships, the types of search methods that are used to apply for nonstandard positions, the perceived quality of those jobs, and whether applications for nonstandard positions are more likely to result in job offers than applications for full-time, standard positions.

Our findings shed new light on this important set of issues. First, our findings point to the ways that applications for nonstandard positions are unevenly distributed throughout the population. Women are far more likely than men to apply for part-time positions, even though our sample is limited to individuals indicating that they would like to find a job where they would work at least thirty-five hours per week. This aligns with the pattern that women are much more likely than men to actually labor as incumbents in part-time positions. Additionally, younger workers are more likely to apply for part-time jobs and individuals with higher levels of education are less likely to apply for part-time positions. Interestingly, [End Page 150] though, we generally do not find that workers of color are significantly more likely than white workers to apply for nonstandard positions. This lack of a finding is surprising, given that workers of color are overrepresented in nonstandard positions. Although beyond the scope of our data, it is possible there may be some demand-side process that steers workers of color into nonstandard jobs. This issue—which could be a mechanism driving inequalities between white workers and workers of color—would be valuable for future research to explore.

Second, we find evidence that fully half of the job seekers in our sample submitted mixed application pools—sets of applications that included both full-time, standard positions as well as an application for at least one other type of job, such as part-time or temporary work. We also find that mixed application pools are more common among workers who are disadvantaged on some axis of inequality in the labor market. For example, women, less-educated workers, and people who have been unemployed for longer durations of time are more likely to have mixed application pools. This finding suggests that applying for both full-time, standard jobs and other types of positions simultaneously may be an adaptive strategy deployed by workers who know that they may experience challenges obtaining a new job. Future scholarship would be well served to further explore this issue.

Our findings also reveal that job search methods are intertwined with the type of position that a job seeker applies to. Across the board, job seekers are significantly more likely to hear about nonstandard job openings through weak ties—that is, their acquaintances. It is possible that this finding emerges due to nonstandard positions being less likely to be posted in formal places, making one's networks—particularly one's acquaintances who are likely to have nonredundant information about potential jobs—important in hearing about openings for these types of positions. This finding is intriguing and speaks to the importance of future work that unpacks why these correlations emerge.

Our results also show that workers perceive the quality of nonstandard positions—measured as the position being perceived below the worker's skill level—as worse than standard jobs. This finding holds across different types of nonstandard positions and model specifications, even when we net out time-invariant individual-level characteristics. Yet our findings also indicate that nonstandard employment can serve as a toehold for workers in the labor market. Job seekers are more likely to receive job offers for applications submitted for nonstandard types of positions than for full-time, standard jobs. Workers are also equally likely to accept nonstandard positions and standard, full-time positions. Juxtaposing these findings, a likely conflict emerges for workers. They can apply for nonstandard positions as a way to increase their likelihood of getting a job offer. But, they are then more likely to be in a position that is below their skill level, which can have negative consequences for their future labor market opportunities (Pedulla 2016). And, the evidence on whether nonstandard jobs—particularly temporary positions—can serve as stepping stones to better employment opportunities in the United States is mixed (Autor and Houseman 2010; Addison and Surfield 2009). Existing scholarship suggests that these effects may vary in important ways by the sociodemographic characteristics of the worker (Pedulla 2014, 2016). Thus, trade-offs for workers when deciding whether to apply for and work in nonstandard positions are very real, and these positions have the potential to keep workers stuck in a less desirable segment of the labor market.

Together, our findings provide new insights about job searching in a labor market where nonstandard jobs are a key component of the economic landscape. We uncover a complex set of job search processes, where many workers appear to be hedging their bets on labor market success by applying for both full-time, standard and nonstandard positions simultaneously. This strategy appears to have some payoff because applications for nonstandard positions are more likely to result in job offers than positions for full-time, standard positions. Negative repercussions, however, are also possible, given that these nonstandard positions may not fully utilize workers' skills. Our results also highlight the importance of jointly considering nonstandard [End Page 151] employment relations and job search processes. By bringing these two often separate literatures together we can gain new insights into the nature of nonstandard work as well as the contours of the job search process. As scholarship continues to move forward on both of these issues, additional attention to how the job search process shapes and is shaped by nonstandard employment will advance our understanding of these key aspects of the labor market.

David S. Pedulla

David S. Pedulla is assistant professor in the Department of Sociology at Stanford University.

Katariina Mueller-Gastell

Katariina Mueller-Gastell is a PhD candidate in the Department of Sociology at Stanford University.

Direct correspondence to: David S. Pedulla at dpedulla@stanford.edu, Department of Sociology, Stanford University, Building 120, Room 132, 450 Serra Mall, Stanford, CA 94305.
Table A1. Multinomial Logit Model of Type of Position Applied To Source: Authors' calculations. Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table A1.

Multinomial Logit Model of Type of Position Applied To

Source: Authors' calculations.

Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. The model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. The model also includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

Table A2. Logit Models of Whether an Application Is Perceived as Below Skill, with Interactions Source: Authors' calculations. Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. Each model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Each model includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week. +p &lt; .1; *p &lt; .05; **p &lt; .01; ***p &lt; .001
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Table A2.

Logit Models of Whether an Application Is Perceived as Below Skill, with Interactions

Source: Authors' calculations.

Note: Standard errors in parentheses. All standard errors clustered on applicant. Respondents who did not report their weeks of unemployment in the baseline survey are coded as being unemployed for the mean number of weeks for their baseline employment status. Each model contains a separate indicator variable for whether this information was missing for the respondent. Occupation controls include the twenty-three categories of the SOC system for the previous occupation held by the applicant. Each model includes controls for the number of applications submitted by a respondent, the number of survey waves they participated in, and whether they did not indicate how many hours they would prefer to work for in a week.

+p < .1; *p < .05; **p < .01; ***p < .001

references

Addison, John T., Chad Cotti, and Christopher J. Surfield. 2009. "Atypical Work: Who Gets It, and Where Does it Lead? Some U.S. Evidence Using the NLSY79." IZA discussion paper no. 4444. Bonn: Institute of Labor Economics.
Addison, John T., and Christopher J. Surfield. 2009. "Does Atypical Work Help the Jobless? Evidence from a CAEAS/CPS Cohort Analysis." Applied Economics 41(9): 1077–87.
American Staffing Association (ASA). 2017. "ASA Annual Economic Analysis: 2017 Staffing Industry Playbook." Accessed July 23, 2018. www.americanstaffing.net/playbook.
Autor, David. 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing." Journal of Labor Economics 21(1): 1–42.
Autor, David, and Susan Houseman. 2010. "Do Temporary-Help Jobs Improve Labor Market Outcomes for Low-Skilled Workers? Evidence from 'Work First'." Applied Economics 2 (July): 96–128.
Bernhardt, Annette. 2014. "Labor Standard and the Reorganization of Work: Gaps in Data and Research." IRLE working paper no. 100–14. Berkeley: University of California.
Bertrand, Marianne, and Sendhil Mullainathan. 2004. "Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination." American Economic Review 94(4): 991–1013.
Broschak, Joseph P., Alison Davis-Blake, and Emily S. Block. 2008. "Nonstandard, Not Substandard: The Relationship Among Work Arrangements, Work Attitudes, and Job Performance." Work and Occupations 35(1): 3–43.
Browne, Irene, and Joya Misra. 2003. "The Intersection of Gender and Race in the Labor Market." Annual Review of Sociology 29: 487–513.
Bureau of Labor Statistics. 2017. "Women in the Labor Force: A Databook." BLS report no. 1071. Washington: U.S. Department of Labor.
———. 2018a. "Household Data Annual Averages. 8. Employed and Unemployment Full-and Part-Time Workers by Age, Sex, Race, and Hispanic or Latino Ethnicity." Accessed December 12, 2018. http://www.bls.gov/cps/cpsaat08.htm.
———. 2018b. "Contingent and Alternative Employment Arrangements, May 2017." Washington: U.S. Department of Labor. Accessed December 12, 2018. https://www.bls.gov/news.release/conemp.nr0.htm.
———. 2018c. "Household Data Annual Averages. 21. Persons at Work in Nonagricultural Industries by Class of Worker and Usual Full-or Part-time Status." Accessed December 12, 2018. http://www.bls.gov/cps/cpsaat21.htm.
———. 2018d. "Household Data Annual Averages. 23. Persons at Work by Occupation, Sex, and Usual Full-or Part-time Status." December 12, 2018. http://www.bls.gov/cps/cpsaat23.htm.
———. 2018e. "Charting the Labor Market: Data from the Current Population Survey (CPS)." Accessed December 12, 2018: https://www.bls.gov/web/empsit/cps_charts.pdf.
Castilla, Emilio J., George J. Lan, and Ben A. Rissing. 2013. "Social Networks and Employment: Mechanisms (Part 1)." Sociology Compass 7(12): 999–1012.
Clawson, Dan, and Mary Ann Clawson. 1999. "What Has Happened to the U.S. Labor Movement? Union Decline and Renewal." Annual Review of Sociology 25: 95–119.
Corcoran, Mary, Linda Datcher, and Greg Duncan. 1980. "Information and Influence Networks in Labor Markets." In Five Thousand American Families: Patterns of Economic Progress, edited by Greg Duncan and James Morgan. Ann Arbor, Mich.: Institute for Social Research.
Dunn, Megan. 2018. "Who Chooses Part-Time Work and Why?" Monthly Labor Review March: 1–25. Accessed February 15, 2019. https://www.bls.gov/opub/mlr/2018/article/who-chooses-part-time-work-and-why.htm.
Epstein, Cynthia Fuchs, Carroll Seron, Bonnie Oglensky, and Robert Sauté. 1999. The Part-Time Paradox: Time Norms, Professional Life, Family and Gender. New York: Routledge.
Fernandez, Roberto M., Emilio J. Castilla, and Paul Moore. 2000. "Social Capital at Work: Networks and Employment at a Phone Center." American Journal of Sociology 105(5): 1288–356.
Fuller, Sylvia. 2011. "Up and On or Down and Out? Gender, Immigration and the Consequences of Temporary Employment in Canada." Research in Social Stratification and Mobility 29(2): 155–80.
Goldin, Claudia, and Joshua Mitchell. 2017. "The New Life Cycle of Women's Employment: Disappearing Humps, Sagging Middles, Expanding Tops." Journal of Economic Perspectives 31(1): 161–82.
Granovetter, Mark S. 1973. "The Strength of Weak Ties." American Journal of Sociology 78(6): 1360–80.
Haley-Lock, Anna. 2009. "Variation in Part-Time Job Quality Within the Nonprofit Human Service Sector." Nonprofit Management & Leadership 19(4): 421–42.
Henson, Kevin Daniel. 1996. Just a Temp. Philadelphia, Pa.: Temple University Press.
Hollister, Matissa. 2011. "Employment Stability in the U.S. Labor Market: Rhetoric Versus Reality." Annual Review of Sociology 37: 305–24.
Hyman, Louis. 2018. Temp: How American Work, American Business, and the American Dream Became Temporary. New York: Viking.
Kalleberg, Arne L. 2000. "Nonstandard Employment Relations: Part-time, Temporary and Contract Work." Annual Review of Sociology 26: 341–65.
———. 2009. "Precarious Work, Insecure Workers: Employment Relations in Transition." American Sociological Review 74(1): 1–22.
———. 2011. Good Jobs, Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States, 1970s–2000s. New York: Russell Sage Foundation.
Kalleberg, Arne L., Barbara F. Reskin, and Kenneth Hudson. 2000. "Bad Jobs in America: Standard and Nonstandard Employment Relations and Job Quality in the United States." American Sociological Review 65(2): 256–78.
Kalleberg, Arne L., Jeremy Reynolds, and Peter V. Marsden. 2003. "Externalizing Employment: Flexible Staffing Arrangements in US Organizations." Social Science Research 32(4): 525–52.
Katz, Lawrence F., and Alan B. Krueger. 2016. "The Rise and Nature of Alternative Work Arrangements in the United States, 1995–2015." NBER working paper no. w22667. Cambridge, Mass.: National Bureau of Economic Research.
Kim, ChangHwan, and Arthur Sakamoto. 2008. "The Rise of Intra-Occupational Wage Inequality in the United States, 1983–2002." American Sociological Review 73(1): 129–57.
Kmec, Julie A. 2006. "White Hiring Agents' Organizational Practices and Out-Group Hiring." Social Science Research 35(3): 668–801.
Knowledge Networks. 2011. "Knowledge Networks Methodology." Palo Alto, Calif.: Knowledge Networks.
Krueger, Alan B., and Andreas I. Mueller. 2016. "A Contribution to the Empirics of Reservation Wages." American Economic Journal: Economic Policy 8(1): 142–79.
Marin, Alexandra. 2012. "Don't Mention It: Why People Don't Share Job Information, When They Do, and Why It Matters." Social Networks 34(2): 181–92.
Mouw, Ted. 2003. "Social Capital and Finding a Job: Do Contacts Matter?" American Sociological Review 68(6): 868–98.
Pager, Devah, and David S. Pedulla. 2015. "Race, Self-Selection, and the Job Search Process." American Journal of Sociology 120(4): 1005–54.
Pager, Devah, Bruce Western, and Bart Bonikowski. 2009. "Discrimination in a Low-Wage Labor Market: A Field Experiment." American Sociological Review 74(5): 777–99.
Pedulla, David S. 2014. Non-Standard, Contingent, and Precarious Work in the "New Economy." PhD diss., Princeton University.
———. 2016. "Penalized or Protected? Gender and the Consequences of Nonstandard and Mismatched Employment Histories." American Sociological Review 81(2): 262–89.
———. 2018. "How Race and Unemployment Shape Labor Market Opportunities: Additive, Amplified, or Muted Effects?" Social Forces 96(4): 1477–506.
Pedulla, David S., and Devah Pager. 2017. "Race and Networks in the Job Search Process." Working Paper. Stanford, Calif.: Stanford University.
Rivera, Lauren A. 2012. "Hiring as Cultural Matching: The Case of Elite Professional Service Firms." American Sociological Review 77(6): 999–1022.
Rogers, Jackie Krasas. 1995. "Just a Temp: Experience and Structure of Alienation in Temporary Clerical Employment." Work and Occupations 22(2): 137–66.
Sharone, Ofer. 2014. Flawed System, Flawed Self: Job Searching and Unemployment Experiences. Chicago: University of Chicago Press.
Smith, Sandra Susan. 2005. "'Don't Put My Name on It': Social Capital Activation and Job-Finding Assistance Among the Black Urban Poor." American Journal of Sociology 111(1): 1–57.
Smith, Vicki. 1997. "New Forms of Work Organization." Annual Review of Sociology 23: 315–39.
———. 1998. "The Fractured World of the Temporary Worker: Power, Participation, and Fragmentation in the Workplace." Social Problems 45(4): 411–30.
Tilly, Chris. 1992. "Dualism in Part-Time Employment." Industrial Relations 31(2): 330–47.
———. 1996. Half a Job: Bad and Good Part-Time Jobs in a Changing Labor Market. Philadelphia, Pa.: Temple University Press.
Trimble, Lindsey B., and Julie A. Kmec. 2011. "The Role of Social Networks in Getting a Job." Sociology Compass 5(2): 165–78.
Virtanen, Marianna, Mika Kivimäki, Matti Joensuu, Pekka Virtanen, Marko Elovainio, and Jussi Vahtera. 2005. "Temporary Employment and Health: A Review." International Journal of Epidemiology 34(3): 610–22.
Wright, Erik Olin, and Rachel E. Dwyer. 2003. "The Patterns of Job Expansions in the USA: A Comparison of the 1960s and 1990s." Socio-Economic Review 1: 289–325.
Yakubovich, Valery. 2005. "Weak Ties, Information, and Influence: How Workers Find Jobs in a Local Russian Labor Market." American Sociological Review 70(3): 408–21.

Footnotes

Data collection for the project was conducted jointly with Devah Pager and generous support for this research came from the Russell Sage Foundation (85–13–01) to both Pedulla and Pager as well as the following funding to Pager: NSF (CAREER0547810) and NIH (1K01HD053694). We thank Arne Kalleberg, David Howell, three anonymous reviewers, and participants in the RSF conference on Changing Job Quality: Causes, Consequences, and Challenges for valuable feedback on earlier versions of this manuscript.

1. The rise of part-time employment over the past thirty years has been limited, although rates of involuntary part-time work did increase during the Great Recession (Dunn 2018). And, though Temporary Help Agency (THA) employment has remained relatively stable since the mid-1990s, THA employment increased significantly between the late 1970s and mid-1990s (Autor 2003; Bureau of Labor Statistics 2018b).

2. It is unclear exactly how applications for independent contracting positions would be captured with our data collection strategy, given that an individual who is an independent contractor generally bids to work on a project rather than applying for a job in the sense that we are considering here. Other types of nonstandard employment—such as on-call work—were not included in the item on the survey instrument asking about the employment relationship of the position for which the job seeker applied. The item asked only whether a position was full time, part time, temporary that has the possibility to become permanent, or temporary that is unlikely to become permanent.

3. Joseph Broschak, Alison Davis-Blake, and Emily Block offer insights into the complexity of the workplace attitudes of temporary agency and retention part-time workers (2008). In some cases, workers in these positions do not report more negative workplace attitudes.

4. To recruit participants for the NLSJS, Gfk sampled 19,509 of its KnowledgePanel members and sent email invitations to this group to screen them for eligibility. Of those 19,509 individuals, 11,231 (57.6 percent) completed the screening items. We screened individuals for eligibility on two items. First, the respondent had to provide informed consent. Second, the respondent had to have been looking for work in the four weeks prior to participating in the survey. Of the 11,231 respondents who completed the screening items, 2,092 (18.6 percent) were eligible to participate in the NLSJS. Of those eligible, 2,060 (98.5 percent) completed the survey. Similar descriptions of these data appear in working papers that use these data (see, for example, Pedulla and Pager 2017).

5. Information about desired work hours was gathered through an item that asked, "Assuming you could find suitable work, how many hours per week would you prefer to work on this job?" Individuals with missing data on this item are included in the sample and a dummy variable is included in all models to indicate whether or not the job seeker had missing data on this item. Results are similar when individuals with missing data on this item are excluded. The sign of coefficients for our findings remain consistent, though statistical significance is lost in some instances.

6. As a robustness check, we operationalized mixed application pools as the proportion of applications submitted that were to full-time positions. When we use this variable, all our findings remain equivalent in sign, magnitude, and significance level. In supplemental analyses, we also coded mixed application pools as those that included at least three applications to a full-time position alongside an application to a nonstandard position, while limiting the sample to only those applicants that applied to at least five positions overall. With this threshold, our results remain qualitatively similar, but statistical significance levels change in some instances.

7. We obtain similar results when alternative coding schemes are used for this variable.

8. If a respondent listed a company name that was illegible or something other than a company name (such as the occupation or industry), that application was not presented to respondents when asking them about job offers in future waves because they would be unlikely to be able to identify the application. When we limit our analyses of job offers just to applications where the company name was carried forward to future waves, all findings regarding job offers hold. Additionally, in the survey, we asked respondents at each wave whether they had received a job offer from a company that they had not previously listed. For this set of applications, we did not ask about the employment relationship of the position and, thus, those offers are not included in these analyses.

9. We recode marital status into three categories: never married, married or cohabiting, and divorced, separated, or widowed.

10. The only models where controls for previous occupation are not explicitly entered are those where we include respondent-specific fixed effects.

11. We also examined the interaction between being a woman and having a child twelve years old or younger living in the household. The interaction is not statistically significant in predicting part-time applications, compared to full-time, standard applications. The only case where the interaction term is statistically significant is in predicting applications for temporary-to-permanent positions relative to full-time, standard applications. In this case, the interaction term is negative.

12. In a model where race-ethnicity is the only predictor of application pool type, the coefficient for being black rather than white is large, positive, and statistically significant (p<.001) in predicting having a mixed application pool.

13. For these analyses, we have excluded applications to positions that were heard of through more than one network-based channel (such as through both a friend and a family member).

14. At each wave, we also asked respondents whether they had received a job offer for a position that was not previously listed and then asked a series of questions about each of those positions. Unfortunately, given time limitations in the survey, we were not able to include an item about the type of position (for example, part time, temporary) for the set of job offers received for applications not previously listed. Our analyses of job offers thus do not include all job offers respondents received.

15. We examined whether the association between nonstandard work and job offers was moderated by the search method (for example, family, friends, acquaintances). We did not find supporting evidence.

Additional Information

ISSN
2377-8261
Print ISSN
2377-8253
Pages
130-158
Launched on MUSE
2019-09-19
Open Access
Yes
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