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Dairy workers' preferences for compensatory benefits: A field choice experiment with US immigrants and students

Dairy workers' preferences for compensatory benefits: A field choice experiment with US... INTRODUCTIONThe US agricultural sector faces severe labor shortages (Fatka, 2019; Hertz & Zahniser, 2013; Taylor et al., 2012). These labor shortages are due in part to fewer immigrants from Mexico, who comprise a sizeable portion of agricultural workers (Charlton & Taylor, 2016; Martin, 2015). The decline in immigrant workers in the United States is due to several factors: the United States–Mexico–Canada Agreement (USMCA) (Zhao et al., 2020); structural transformation in Mexico; and political rhetoric against low‐skilled immigrant workers (Charlton et al., 2021; Christiaensen et al., 2021; Hanson et al., 2017; Taylor et al., 2012). Additionally, many Mexican workers are transitioning to off‐farm work (Charlton & Taylor, 2016).1Off‐farm work includes wage work or self‐employment in manufacturing and services, including commerce. In rural Mexico, this work may entail production of handicrafts or simple construction material such as bricks (Yúnez‐Naude & Taylor, 2001). In the United States, immigrants have shifted from agriculture to construction and retail sectors (Card & Lewis, 2007).While attracting and retaining workers has become difficult across the US agricultural sector, it is particularly challenging in the dairy sector because of the nature of the work and long hours. What's more, the US dairy industry has seen dramatic changes in recent decades, particularly in increased productivity and consolidation. Whereas small dairy farms rely on labor provided by the operator and operator's family, large farms rely on hired labor (MacDonald et al., 2007). Much of this hired labor is comprised of immigrant workers: 51% of dairy workers are immigrants who contribute 79% of the US milk supply (Adcock et al., 2015, p. 2). Dairy workers are needed year‐round, so that most dairy farms are not able to make use of the H‐2A visa program, which provides visas to seasonal immigrant workers as backup labor supply. There have been numerous media accounts of problematic labor shortages in the dairy sector (e.g., ABIC Action, 2022; Dumas, 2022; Hardbarger, 2021; Howard, 2021). In fact, labor is one of the most important drivers of production costs for dairy farms (second only to feed), and hence has an important role in determining profitability for dairy farms (Wittenberg & Wolf, 2014). Though a tight labor supply poses severe challenges for dairy farms, we know little about how farmers might retain and recruit workers in this industry.There is limited scope for further retaining and recruiting dairy workers by raising wages, as US agricultural wages have risen more than 20% since 1990 (Charlton et al., 2019), and dairy workers' earnings have risen even further. According to a national survey of dairy farms in 2014, hourly wages were nearly 20% higher than wages in crop production and wages were higher among dairy farms with hired immigrants. On top of this, the average annual benefit package offered by dairy farms (e.g., paid vacation, housing) increased overall earnings by 56% of wage earnings. When factoring in these benefits and the high number of hours worked per week, annual compensation among dairy workers was 70% higher than compensation in fast food, and 23% higher than compensation in landscaping (Adcock et al., 2015, p. 8).We do not know whether such relatively high earnings may attract workers whose preferences might differ from other agricultural workers. A survey of dairy workers in New York found that workers were primarily interested in maximizing earnings by working as many hours as possible and by learning new skills that would earn them higher wages (Maloney et al., 2016, p. 36–40). But workers in fruit and vegetable production are willing to forego wage earnings for benefits and bonuses (Gabbard & Perloff, 1997; Nolte & Fonseca, 2010). Some farmers believe higher wages will not attract or retain workers, so select US fruit and vegetable producers offer bonuses and low‐cost health care to employees and their families (Martin, 2015).In this article, we elicit dairy workers' preferences for such compensatory benefits with a discrete choice experiment (DCE) (see Louviere et al. [2000] and Hensher et al. [2015]). Our experimental design mirrors real‐world decision‐making for job choice by asking respondents to choose between job profiles described by compensation packages varying in their benefit attributes and attribute levels. Such elicitation methods require respondents to consider trade‐offs, making it possible to rank order preferences for different benefit packages. We assess workers' preferences for three distinct sets of employment attributes: monetary (wage, housing allowance, and incentive‐based pay); nonmonetary (health insurance, retirement plan, on‐site housing, and a meat bonus); and number of hours required to work each week.There have been a few studies using DCEs to estimate workers' preferences for employment contracts in food and agriculture industries. Luckstead et al. (2022) used a DCE to study workers' willingness to work in the US meatpacking industry in light of the COVID‐19 pandemic. Two studies implemented a DCE to identify contractual arrangements that would attract workers to a nascent horticulture exporting industry (Van den Broeck et al., 2016) in Senegal and (Schuster et al., 2017) in Peru. Other DCEs of workers have focused primarily on nonfarm labor.2In nonfarm employment, workers are willing to forego 20% of their wages to maintain control of their work schedules (Mas & Pallais, 2017). Several international studies have used DCEs with medical professionals, a relatively skilled population with different labor regulations. See for example, Ubach (2003), Huicho et al. (2012), Miranda et al. (2012), Rockers et al. (2012), Rao et al. (2013), Rockers et al. (2013), Kunaviktikul et al. (2015), Scott et al. (2015), Song et al. (2015), Efendi et al. (2016), Smitz et al. (2016), Takemura et al. (2016). This differentiation is important as preferences might significantly vary between farm and nonfarm labor, in part because the US Fair Labor Standards Act (FLSA) has a different set of regulations for the agriculture sector. Notably, farm workers are exempt from federal overtime pay requirements (US Department of Labor, 2020a).This article makes several valuable contributions to the literature on worker preferences and the use of DCE to help us understand how best to attract and retain workers in the US dairy sector. First, we have designed a lab‐in‐the‐field experiment tailored to the dairy sector. Second, we focus on a hard‐to‐reach population of immigrant workers who live and work in the United States year‐round, and who are often excluded from surveys of agricultural workers. Finally, to our knowledge, this paper is the first to employ the same methods and survey questionnaires to two distinct populations: immigrant workers and US students interested in working in the same agricultural sector.3We did not restrict our study to US citizens. However, all surveyed students had been born in the United States, with the exception of two exchange students from Ireland. As those two students did not plan to work in the United States, we excluded them from the sample for analysis.Our interest in surveying the two groups was to capture the two possible sets of employees in the industry: the milkers, farmhands, and herdsmen who do much of the labor‐intensive tasks on the farms; and those seeking management or technical positions in the industry. College students studying dairy science and management would be well‐placed to fill positions in high‐tech production. Workers who can manage high‐tech production are increasingly in demand in agriculture, as farms move toward less labor‐intensive and more capital‐intensive production in the face of rising wages and a declining supply of agricultural labor (Charlton et al., 2019).The remainder of this article is structured as follows: we outline the experimental design in Section 2 and econometric methods in Section 3; Section 4 summarizes our first study of immigrant workers (recruitment procedures, sample characteristics, and findings); Section 5 similarly summarizes our second study of students training to work in the dairy sector; and Section 6 concludes with a comparison of the two studies and implications of our findings.EXPERIMENTAL DESIGNWe designed a DCE to elicit dairy workers' preferences among a set of employment options described by different attributes (wage, benefits, bonuses, and number of hours worked). We conducted focus groups with immigrant dairy workers to identify benefits and bonuses that were already being offered, and those not being offered but of interest.4There were three focus groups, each comprised of three to five participants, all of whom indicated they were undocumented workers on local dairy farms. The focus groups were held at the home of a researcher who lived close to many of the targeted dairy farms in St. Johns, MI. The researcher also had prior experience interviewing migrant workers and previously knew a couple of the participants. Recruitment was by word of mouth via these specific participants who knew and trusted the researcher as a member of their local community. He and one of the authors of this paper jointly interviewed all participants in Spanish, the native language of all participants. These focus groups covered a number of topics: demographics, work experience, compensation, financial decisions, health, housing, workplace concerns, and career plans. This input helped us define the attributes and their corresponding levels to be used in the DCE.We identified seven attributes: wage, hours worked, housing, health insurance, retirement plan, a meat allowance bonus, and an incentivized bonus based on milk quality (see Table 1). For wages, we followed prior studies:5See for example, Ubach (2003), Rockers et al. (2013), Kunaviktikul et al. (2015); Scott et al. (2015); Song et al. (2015), and Takemura et al. (2016). one's current wage, a 15% wage increase, and a 15% wage decrease.6Wages reported by respondents were on average considerably higher than the federal minimum wage of $7.25 per hour—$11.49 and $11.20 in the two respective study populations. Thus, even the lower wage on offer in the DCE was on average 31%–35% higher than the federal minimum wage. Hours worked were described by four levels ranging from 48 to 84 h.7The closest attributes to hours worked in the literature were change in hours worked (Scott et al., 2015; Ubach, 2003) and work schedule (Huicho et al., 2012; Miranda et al., 2012). These levels were selected to be above 40 h to avoid conflating the number of hours worked and any potential overtime pay rates.8Though overtime pay in agriculture is not regulated by the FLSA, in our focus groups, some workers received overtime pay. They were also chosen to represent feasible shifts, for example, six 8‐h shifts or seven 12‐h shifts.1TableChoice experiment attributes and levels.AttributesLevelsWage15% less than current wage, Current wage, 15% more than current wageHours (average per week)48/56/70/84Health insurancePresent/AbsentRetirement planPresent/AbsentHousingHousing Allowance/On‐site housing/NoneMeat bonusPresent/AbsentQuality IncentivePresent/AbsentRemaining employment attributes were benefits mentioned in focus groups as either common or highly desired. We included employer provided on‐site housing and a more flexible housing allowance, resulting in three levels: no housing, on‐site housing, and a housing allowance.9Similar housing attributes and levels are frequent in the rural medical literature (Efendi et al., 2016; Huicho et al., 2012; Kunaviktikul et al., 2015; Miranda et al., 2012; Rockers et al., 2012, 2013; Smitz et al., 2016; Takemura et al., 2016). Remaining attributes were either included or excluded from each job description, and we described each included benefit and bonus to respondents.10A detailed description of all other attribute levels is reported in Supporting Information: Figure A2. How they were specifically presented to survey participants is included in Supporting Information: Appendix B. The retirement plan reflected a plan mentioned in focus groups. The health insurance plan was similar to plans used in prior studies (Kunaviktikul et al., 2015; Song et al., 2015; Van den Broeck et al., 2016). Two types of bonuses are unique to the dairy industry. A meat allowance bonus is the opportunity to purchase quality beef at reduced market prices. An incentivized bonus based on milk quality is a lump‐sum payment to workers only when milk quality meets certain stated standards. Some producers offered such bonuses, and workers differed in whether they viewed it as either a chance to increase their earnings or introduced too much uncertainty in earnings. As milk quality cannot be attributed to a single milker, this incentivized payment depends on the skills and diligence of the team of workers.Altogether, these seven attributes and their levels resulted in 331,776 = ((24 × 32 × 41)2) possible choice questions. To reduce fatigue effects, we performed a D‐Optimal design (Street & Burgess, 2007), which resulted in 72 choice questions. To further reduce fatigue, these 72 questions were distributed across eight blocks, each containing nine choice questions. Each question was comprised of two experimentally designed employment alternatives and an “opt‐out” option (see an example question in Supporting Information: Figure A1). Participants were randomly assigned to one of eight blocks, and the order of questions in each block was randomized to mitigate order effects.ECONOMETRIC ANALYSISIn designing the DCE, we assumed respondents would have individual preferences over various forms of employment compensation, and that they would select compensation packages that maximize their utility (McFadden, 1974). Utility is comprised of an observable, predictable component, Vnjt, ${{\boldsymbol{V}}}_{njt},$ and some unexplained random component, εnjt ${\varepsilon }_{njt}$ (Train, 2009):1Unjt=Vnjt+εnjt, ${U}_{njt}={{\boldsymbol{V}}}_{njt}+{\varepsilon }_{njt},$where Unjt ${U}_{njt}$ is the utility worker n derives from alternative j in choice question t.We assume εnjt ${\varepsilon }_{{njt}}$ to be independently and identically Gumbel distributed (error term) and estimated a mixed logit model (MXL) for panel data. This model accounts for random taste variation and correlation in unobserved factors over time (see Train [2009, p. 134–150] for the model derivation and Hensher et al. [2015, p. 601–704] for computational details).11For efficiency, we take 1000 Halton draws rather than random draws (Bhat, 2003). Given our experimental setup, we specify Vnjt ${{\boldsymbol{V}}}_{{njt}}$ in Equation (1) as follows:2Vnjt=OptOut+αnWagenjt+βn1Hoursnjt+βn2Healthnjt+βn3Retirenjt+βn4OSHousingnjt+βn5HousingAnjt+βn6Meatnjt+βn7Qualitynjt, ${V}_{{njt}}={\mathrm{OptOut}+\alpha }_{n}{\mathrm{Wage}}_{{njt}}+{\beta }_{n1}{\mathrm{Hours}}_{{njt}}+{\beta }_{n2}{\mathrm{Health}}_{{njt}}+{\beta }_{n3}{\mathrm{Retire}}_{{njt}}+{\beta }_{n4}{\mathrm{OSHousing}}_{{njt}}+{\beta }_{n5}\mathrm{Housing}{A}_{{njt}}+{\beta }_{n6}{\mathrm{Meat}}_{{njt}}+{\beta }_{n7}{\mathrm{Quality}}_{{njt}},$where OptOut was the alternative specific constant indicating the no‐application option, and Wagenjt ${\mathrm{Wage}}_{{njt}}$ is the hourly wage for worker n in alternative j in choice question t.This variable varies by worker because we use the worker's wage at the time of the survey as the base wage.12If the respondent was unemployed at the time of the survey, we use the respondent's wage from the most recent job. If the respondent had never previously held a job, we take the wage to be the federal minimum wage at the time of $7.25. Respondents were similarly instructed. This variable reflects the proposed wage each worker saw for each alternative j in choice question t. If the proposed wage was the same as the worker's wage earned at the time of the survey, then the variable equals this wage. On the other hand, if the proposed wage was 15% lower (higher) than the respondent's wage, we multiply the individual's reported hourly wage by 85% (115%). We estimate the marginal utility (MU) of the wage for individual n by αn ${\alpha }_{n}$, which we assume to be constrained triangular distributed.All other coefficients are assumed normally distributed.13For further details on selecting statistical distributions for random parameters in DCEs, see Hensher et al. (2015) and Caputo and Scarpa (2022). The first attribute, Hoursnjt ${\mathrm{Hours}}_{{njt}}$, is a continuous variable representing the average number of hours worked per week. Remaining variables are dichotomous, equal to one if alternative j in choice task t included the particular benefit or bonus. The marginal utility of the health insurance plan is estimated by βn2 ${\beta }_{n2}$, that of the retirement plan is estimated by βn3 ${\beta }_{n3}$, that of on‐site housing by βn4 ${\beta }_{n4}$, that of the housing allowance by βn5 ${\beta }_{n5}$, that of the meat bonus by βn6 ${\beta }_{n6}$, and that of the milk quality incentive by βn7 ${\beta }_{n7}$. The omitted reference (baseline) category is comprised of the absence of a health plan, retirement plan, housing accommodation, meat bonus, and milk quality incentive bonus payments.While we had expected respondents to receive utility from higher wages and from nonmonetary forms of compensation, it was unclear a priori whether the marginal utility of working more hours than they were already would be positive or negative. In other contexts, employers shifted from 8 to 12‐h shifts at the request of workers wanting to work more hours and increase earnings (Maloney et al., 2016, p. 27). In contrast, immigrant dairy workers already worked 48 h a week on average. To avoid potentially conflating the number of hours required to work per week with whether overtime pay was offered, we provided only choices with the required number of hours to be above the standard 40‐h work week, either 48 h or higher. It is possible that respondents were already maximizing their utility from the number of hours worked, particularly if they viewed more work hours as a negative impact on their leisure time. In this case, marginal utility from additional work hours per week would be negative.Coefficient estimates from the MXL (Supporting Information: Table A2) are used to determine the marginal rate of substitution (MRS) or willingness to pay (WTP) for each k $k$ nonmonetary compensation package, calculated as βk/α ${\beta }_{k}/\alpha $; where β $\beta $ is the coefficient of nonmonetary benefit package k, $k,$ and α $\alpha $ is the monetary (wage) coefficient (or marginal utility of income). We report WTP estimates in terms of one's hourly wage, with standard errors in parentheses and confidence intervals in brackets below each estimate (Tables 3 and 5). These are calculated using the Krinsky and Robb (1986) bootstrapping method. We also report WTP estimates in terms of annual income, calculated by multiplying estimates of the mean WTP per hour × 35 h × 50 weeks per year (median weekly hours worked in the pooled sample was 35 h, and we assume 10 days of paid holidays or leave). In Supporting Information: Table A3, we compare differences between estimated mean WTP in the two samples; we report p‐values from the combinatorial test introduced by Poe et al. (2005).STUDY 1: IMMIGRANT WORKERSRecruitment processParticipants in Study 1 were recruited from Clinton County, Michigan, one of the highest milk‐producing counties in the state. Milk production is the largest agricultural output in Michigan; with over 400,000 cows on nearly 1800 farms, each year producing over 11 billion pounds of milk worth more than $1.6 billion. In contrast to other midwestern states, Michigan dairies were early adopters of large production scale similar to Western states, requiring hired labor, especially immigrant labor (Michigan Department of Agriculture and Rural Development, 2019).We recruited study participants using a variety of approaches, as we focused on recruiting immigrant workers in the dairy sector, a hard‐to‐reach population. Many immigrant workers do not speak English, and some may not have a visa or permit to work in the United States. On top of this, dairy workers work long hours. We worked with agricultural extension agents and trusted leaders from local churches and communities in and around dairy farms. In July through October 2018, we visited dairy farms, Hispanic centers, local churches, and community events such as soccer games. At these community events and at meetings organized with local farmers and community leaders, Spanish‐speaking enumerators approached potential participants to inquire about their eligibility for and interest in the research study. A total of 107 immigrants were included in our survey.14We surveyed a total of 125 respondents through this community outreach. However, 18 respondents were born in the United States. Since the sample of US born respondents recruited via this approach was limited, we chose to drop them from our analysis.The survey took approximately 1 h, and participants were paid $15 for completion of the survey. Participants also received an additional payment from incentivized games used for another study, which averaged around $9 per participant. Participants signed consent forms (available in English and Spanish), following all research guidelines approved by Michigan State University's Institutional Review Board (IRB). We administered face‐to‐face Qualtrics surveys (previously downloaded onto tablets). The survey began with questions on demographics and work history, followed by our choice experiment. It was available in English and Spanish. Respondents could either complete the survey themselves or with the aid of a bilingual survey enumerator (fluent in English and Spanish).Descriptive statisticsWe summarize characteristics of the immigrant sample in Table 2. Most surveyed immigrants were men (63%), and this share of men in our sample was slightly lower than that of the National Agricultural Workers Survey (NAWS) (US Department of Labor, 2020b).15In NAWS, 77% of respondents are men. Immigrants were on average 33.5 years of age. Education levels were quite low among immigrants, with only 15% of immigrants having completed high school. Most immigrants had a least one child (75%) and 45% of them were married when surveyed. In addition, 99% of immigrants self‐identified as Hispanic.2TableDescriptive statistics of immigrant workers (Study 1).MeanStd. Dev.All study 1 respondents (N = 107)Gender (men = 1)0.630.49Age33.5210.50HS degree = 10.150.36Married = 10.460.50Has Children = 10.750.44Hispanic = 10.990.10Has driver's license = 10.290.46Has bank account = 10.440.50Employed when surveyed = 10.850.36Study 1 Respondents employed at the time of survey (N = 91)Works in dairy when surveyed0.650.48Hourly wage11.492.20Avg. hours work per week47.7317.99Employer provides:0.210.41Health insurance0.230.42Retirement plan (self‐paid)0.080.27Retirement plan with employer contribution0.110.31Paid holidays0.590.49Housing or housing allowance0.550.50Food0.180.38Incentive pay0.080.27As it is generally difficult for undocumented immigrants to obtain either a US driver's license or bank account, many of our respondents may have been undocumented. A driver's license is valuable, as public transportation options are limited in rural Michigan. Immigrants who would have lived in the United States for a while would need a US driver's license. Among those surveyed, 29% had a driver's license and 44% had US bank accounts in their own names.Around 85% of surveyed immigrants were employed at the time of the survey. Among employed respondents, 65% were working in the dairy sector. The average hourly wage was $11.49. Immigrants worked on average 48 h per week. In terms of the benefits that employers provided immigrants, 23% of employed immigrants received health insurance, and only 11% received a retirement plan. In addition, 55% received either housing or a housing allowance, and 18% received food from their employers. Finally, we asked if respondents had received any type of incentive‐based payments, such as the milk quality incentive bonus discussed in focus groups; 8% of employed immigrants received such payments.ResultsIn this section, we discuss estimates of WTP for the Study 1 sample of immigrants. In the first column of Table 3, we report WTP estimates in terms of one's hourly wage, with standard errors in parentheses and confidence intervals in brackets below each estimate. In the second column of Table 3, we report WTP estimates in terms of annual income.3TableMarginal willingness to pay (WTP) estimates for Study 1 sample of immigrants.Hourly wageAnnual salaryRetirement plan$5.01$8768(1.37)[$2.34, $7.69][$4095, $13458]Health insurance$2.67$4673(0.80)[$1.10, $4.25][$1925, $7438]Milk quality incentive$2.15$3763(0.78)[$0.62, $3.68][$1085, $6440]On‐site housing$1.24$2170(0.65)[−$0.03, $2.52][−$0.06, $4410]Housing allowance$0.77$1348(0.66)[−$0.53, $2.07][−$928, $3623]Meat bonus$0.74$1295(0.54)[−$0.03, $1.81][−$53, $3168]Hours−$0.03−$53(0.03)[−$0.08, $0.03][−$140, $53]Note: These estimates are based on Krinsky and Robb (1986) bootstrapping from marginal utility estimates, summarized in Supporting Information: Table A2. Column 1 reports mean WTP estimates as hourly wage. In column 2, we report mean WTP or WTA estimates in terms of one's annual wage income. These values were calculated as 35 h (the median in the pooled sample) × 50 weeks per year × Mean WTP Estimate from column 1. For all estimates, 95% confidence intervals are in brackets.As we might expect, all estimates of WTP are positive, except for the number of required work hours per week. Respondents must be compensated three cents for every additional hour of work required beyond 48 h. The negative coefficient estimates on hours are consistent with prior research (Nolte & Fonseca, 2010), although it runs counter to the commonly held notion in the dairy industry that workers prefer to work more rather than fewer hours (Maloney et al., 2016).Estimates of Equation (2) for this sample indicate the following rank ordering of attributes (from highest to lowest MU): retirement plan, health insurance, incentive bonus based on milk quality, on‐site housing, housing allowance, and a meat allowance bonus.Immigrants are willing to pay $5.01 per hour for a retirement plan, equivalent to roughly 40% of immigrants' wages. Recall that only 11% of employed immigrants received such a plan, despite working full‐time.There are several reasons why immigrants would highly value the retirement plan. Most surveyed immigrants do not have a bank account or any formal means of savings, and they often send money to relatives abroad who save this money on their behalf. But relying on relatives who are themselves in need of money is risky. In addition, the fact that many immigrants are willing to give up a portion of their earnings to be forced to save for the future is consistent with the limited commitment savings literature (Gugerty, 2007).The next most valued benefit is health insurance, and immigrants are willing to pay $2.67 per hour, nearly a quarter of their earnings. Health insurance plans vary greatly, with employers often providing catastrophic insurance, but not preventative care. Most employers do not offer immigrants the type of comprehensive health insurance described in our choice experiment.Immigrants are willing to pay $2.15 per hour for the milk‐quality incentive bonus, nearly 20% of their earnings. This amount is substantial considering that at most, the bonus could amount to $600 per year. Respondents may have misunderstood or not listened clearly to the description of this payment scheme, which may have been quite novel to many of them. They may also have overestimated the potential bonus payment, thinking primarily about their own skills and the possible feeling of worthiness for a payment derived from one's work efforts.16See Kruger and Dunning (1999) for more on the Dunning‐Kruger effect, namely that poor performers overestimate their performance ability. Finally, results could suffer from hypothetical bias.Following the bonus based on milk quality, the next most valued benefit for immigrants is on‐site housing; with a WTP estimate of $1.24 per hour. The description of on‐site housing was consistent with the type of housing immigrant workers often receive from their employers.The next most valued benefit is a monthly housing allowance of $500 a month, or $6000 for the year. On average, respondents are willing to pay $1348 per year. This relatively low valuation might reflect the fact that housing is relatively inexpensive in this region, and that the housing benefit is tied to the specific employer.17For example, the fair market rent for Clinton and Ingham counties, from where participants were recruited, ranged from $328.25‐$690 per person (per bedroom) (see Rentdata.org, 2018).The least valued benefit is the meat bonus, though estimated valuation is much higher than its nominal value. Immigrant respondents are willing to pay 74 cents per hour ($1,295 per year) for the meat bonus. This bonus provides workers the option to purchase freshly slaughtered meat by paying only the processing fee of $0.40 per pound. Workers could request up to one cow's worth of meat for themselves per year, approximately 600 pounds of raw meat. The maximum annual value of this bonus is $240.18From July through December 2018 the average retail price of cuts of beef ranged from $0.99 to $22.99 (US Department of Agriculture: Agricultural Marketing Service).To better understand what might be driving these WTP estimates, we estimate two models using seemingly unrelated regression (SUR), where the dependent variables are the marginal WTP estimates for attributes in the DCE (see Supporting Information: Tables A4 and A5).19We have too small a sample size to estimate SUR for Study 2. Also, students are similar to one another in terms of age and many of the dimensions we explore in the SUR models for Study 1. In the first model, we exclude variables indicating one lives with a spouse or children. In the second model, we include these variables.20We estimate these two models because when we include these family‐related variables, coefficient estimates on whether one has a driver's license or bank account are affected.Respondents who have a driver's license would be less likely to be undocumented workers compared to others, and they would therefore be more likely to receive benefits that require documentation of legal status to work in the United States, such as a pension or health insurance. On average, respondents with a driver's license have a 65% higher WTP (an additional $2.03 with a sample mean WTP of $3.14) for a retirement plan compared to those who do not have a license. When we control for whether one lives with a spouse or children, this estimate declines to $1.62. Respondents with a driver's license are also willing to pay 24%–29% more for health insurance compared to those who do not have a license (mean WTP for health insurance is $1.80).Immigrant workers who have a US bank account in their own names would perhaps have more financial security and savings options than those who do not have an account. Having a bank account lowers WTP by an average of 41%–50% (average WTP for a housing allowance is $3.14); this estimate is statistically significant with p < 0.1 only when we do not also control for indicators related to living with a spouse or children. In addition, having a bank account lowers WTP for a housing allowance by 16% to 20% on average, with p < 0.05 when additional covariates are excluded and p < 0.1 with all covariates in the model.Compared to higher earners, respondents whose annual salaries are below the sample median are willing to forego a greater portion of their wages to work more hours (p < 0.05). The magnitude of the estimate is economically significant—they are willing to forego 4.2 cents in hourly wages to work more hours; whereas on average, participants are willing to accept an additional 3.5 cents in wages to work more hours.Participants with a below median salary have a higher WTP for the milk quality incentive bonus (68 cents or 42% of the average marginal WTP). This estimate is statistically significant with p < 0.1 only for Model 1.Age is a significant predictor of WTP for the retirement plan. We include in the SUR—indicator variables for age ranges (age 25–34, age 35–44, age 44 and up, with ages under 25 as the omitted reference category). Coefficient estimates on the indicator for ages 35–44 are statistically significant (with p < 0.1 in Model 1 and p < 0.05 in Model 2). Magnitudes are economically significant, $2.32 for Model 1 and $2.96 for Model 2. As the mean marginal WTP for the retirement plan is $3.14, on average, respondents ages 35–44 are willing to pay 74%–94% more for the retirement plan than respondents under age 25.Compared to the youngest respondents (under age 25), the oldest respondents (age 44 and up) need to be compensated with considerably higher hourly wages to work more hours. Whereas the average marginal willingness to accept more work hours is 3.5 cents; to work more hours, respondents ages 44 and up need an additional 5.5 cents per hour compared to respondents under age 25. Estimates in both models are statistically significant with p < 0.05.Finally, those who live with a spouse are willing to pay nearly $2 per hour less for the retirement plan, which is 63% of the average marginal WTP for the retirement plan (p < 0.01). Those who live with a spouse also have lower WTP for on‐site housing (22% of the average WTP, p < 0.05), and the meat bonus (47% of the average WTP, p < 0.1). Somewhat puzzlingly, those who live with children have a 23% lower WTP for the housing allowance, with p < 0.05. The amount of the housing allowance may be too small relative to the cost of a home for a family with children.STUDY 2: STUDENT SAMPLERecruitment processIn addition to our efforts to recruit immigrant workers across dairy farm communities in Michigan, we also recruited undergraduate students from Michigan State University's Dairy Club and from the university's Dairy Management Agricultural Technology Certificate program.21For further information on the Dairy club see in the references “Michigan State University Dairy Club.” For further information on the certificate program see “Dairy Management.” The Dairy Club is a student‐run organization for undergraduate students who are interested in working in the dairy industry. This student organization provides opportunities for developing leadership skills for its members.The certificate program is specifically designed for students who plan to work or are already working in the dairy sector. Students do not earn a bachelor's degree, though their coursework could be used toward obtaining a university degree following the certificate program.22In 2018, nearly half of the students continued their education toward a 4‐year college degree. Nearly a third of students returned to their family farms, with remaining students working either on a dairy farm or for an agricultural business supporting dairy farms. These figures were provided by the coordinator of the certificate program, Dr. Joe Domecq. In addition to their coursework, students gain practical experience working on dairy farms who cooperate with the program. The MSU certificate program advertises that their program prepares students for careers in dairy management and farming and nutrition industries.In November 2018, we organized meetings of the Dairy Club for the purposes of our survey. In December 2018, we visited introductory courses required of all students in the Dairy Management Agricultural Technology Certificate program, and with the instructor's permission, we invited students to remain after class to participate in the study.23All of our recruitment efforts and study procedures followed guidelines approved by Michigan State University's Institutional Review Board (IRB). We recruited a total of 53 students, and we excluded from our analyzed sample two exchange students from Ireland—resulting in a sample of 51 students.24We surveyed roughly 80% of the students in these two programs. Each year, there are about 50 members in the Dairy Club. In 2018, 26 students completed or were set to complete the certificate program. Of these 26 students, roughly 16 of them were also members of the Dairy Club. These figures were provided by the coordinator of the certificate program, Dr. Joe Domecq.Descriptive statisticsWe summarize student characteristics in Table 4. Only 29% of surveyed students were men. The average age of students was just under 20, and 65% of students had completed high school. 52% of students had a driver's license and 62% of students had a US bank account in their own names.25In pairwise means comparison tests between students and respondents in Study 1, all but one of the aforementioned descriptives were statistically significantly different across samples, with p < 0.001. Employment rates among students and immigrants were similar (p = 0.46).4TableDescriptive statistics of student sample (Study 2).MeanStd. Dev.All Study 2 respondents (N = 51)Gender (men = 1)0.290.46Age19.571.27HS degree = 10.650.48Married = 1‐‐Has children = 1‐‐Hispanic = 1‐‐Has driver's license = 11.00‐Has bank account = 11.00‐Employed when surveyed = 10.800.40Study 2 Respondents employed at the time of survey (N = 41)Works in dairy when surveyed0.490.51Hourly wage11.205.35Avg. hours work per week21.8818.67Employer provides:0.170.38Health insurance0.100.30Retirement plan (selfpaid)0.100.30Retirement plan with employer contribution0.240.43Paid holidays0.240.43Housing or housing allowance0.240.43Food0.050.22Incentive pay0.170.38Among students employed at the time of our survey, 49% of students were working in the dairy sector.26Among these students, one‐third were working on a family farm. Among the students not employed in the dairy sector at the time of the survey, 55% had previously worked in dairy. The average hourly wage was close to $11.20. On average, students worked about 22 h per week. Only 10% of students received health insurance, and 24% of students received a retirement plan with employer contribution. In addition, 24% of students received either housing or a housing allowance, and just 5% of students received food from their employers. Finally, 17% of students reported receiving some type of incentive‐based payment.ResultsIn this section, we discuss estimates of WTP for the sample of students. In the first column of Table 5, we report WTP estimates in terms of one's hourly wage, with robust standard errors in parentheses and confidence intervals in brackets below each estimate. In the second column, we report WTP estimates in terms of annual income.5TableMarginal willingness to pay (WTP) estimates for Study 2 sample of students.Hourly wageAnnual salaryHealth insurance$1.22$2135(0.28)[$0.66, $1.77][$1155, $3098]Retirement plan$1.19$2,083(0.31)[$0.59, $1.79][$1033,$3133]Housing allowance$1.15$2013(0.35)[0.47, $1.83][$823, $3203]Milk quality incentive$1.14$1995(0.31)[$0.53, $1.75][$928, $3063]Meat bonus$0.78$1365(0.24)[$0.30, $1.26][$525, $2205]On‐site housing$0.33$578(0.31)[−$0.28, $0.94][−$490, $1645]Hours−$0.05−$88(0.01)[−$0.07, −$0.03][−$123, −$53]Note: These estimates are based on Krinsky and Robb (1986) bootstrapping from marginal utility estimates, summarized in Supporting Information: Table A2. Column 1 reports mean WTP estimates as hourly wage. In column 2, we report mean WTP or WTA estimates in terms of one's annual wage income. These values were calculated as 35 h (the median in the pooled sample) × 50 weeks per year × Mean WTP Estimate from column 1. For all estimates, 95% confidence intervals are in brackets.As in Study 1, all estimates of WTP are positive, except for the number of required work hours per week. Students must be compensated 5 cents for every additional hour of work required beyond 48 h. While students worked about 22 h a week on average at the time of the survey, upon graduation or completion of their certificates, students would likely work full‐time, or around 40–50 h per week.Estimates of Equation (2) for the student sample indicate the following rank ordering of attributes (from highest to lowest MU): health insurance, retirement plan, housing allowance, incentive bonus based on milk quality, meat allowance bonus, and on‐site housing.Students are willing to pay about 10% of their earnings for a retirement plan or health plan. Many students do not receive health insurance from their employers, perhaps because they receive health insurance either via the university or parents.Students also similarly value the housing allowance and incentivized bonus determined by milk quality. On average, respondents are willing to pay $2000 per year for each of these benefits. Students are willing to pay 78 cents per hour ($1365 per year) for the meat bonus.Finally, for on‐site housing, students are willing to pay $0.33 per hour. The description of on‐site housing is consistent with housing immigrants often receive from their employers, and this type of living arrangement is likely uncommon for students.DISCUSSION AND CONCLUSIONUsing a discrete choice experiment designed to elicit dairy workers' preferences for compensatory benefits and bonuses, we have shown that to attract and retain workers in the dairy sector, it can be worthwhile for employers to provide retirement and health insurance benefits. Incentivized bonuses are also attractive to workers, as is an average 48‐h work week.These findings are consistent with studies in other industries, which taken together show the importance of offering nonmonetary benefits to attract and retain agricultural workers. In the meatpacking industry, DCE results indicated high valuation of retirement and health benefits (Luckstead et al., 2022). Fruit and vegetable growers were already offering such benefits to retain workers (Martin, 2015).WTP estimates found here could be reasonably provided by employers, with cost sharing between employees and employers. For example, in a review of farm worker union contracts negotiated in 2013 between California employers and the United Farm Workers of America Union (the most prominent union of farm workers in the United States)—the most common health insurance plan offered to UFW employees in California required an average hourly contribution of $2.23 and the most common pension plan offered had an average hourly contribution of $0.13 (Rutledge, 2021). While inflationary pressures may have since increased these values, they are generally higher in California compared to Michigan. Our findings indicate that immigrant workers would be willing to pay a significant share of the health insurance costs, and students would be willing to pay about 55% of the average contribution required for the health plan. Both study populations have a WTP for a retirement plan that is well above this required contribution.We find several notable differences between immigrant workers in the dairy sector and US college students who plan to work in the dairy sector. For health insurance, immigrants are willing to pay more than double students' average WTP. In comparison to students, immigrants are willing to pay five times more for a retirement plan. Immigrants are willing to pay nearly twice as much as students for an incentivized bonus determined by milk quality.Immigrants and students are generally in different stages of their life courses, with different family planning considerations and different expectations regarding healthcare costs; these differences may be particularly relevant in influencing preferences for health insurance or a retirement plan. While students' ages range between 18 and 23 (Study 2), immigrants in Study 1 range in age from 18 to 65 (with the bulk of ages between 23 and 38).27See Supporting Information: Figures A3 and A4 for sample distributions in terms of age. Recall that immigrant respondents ages 35–44 are willing to pay 74%–94% more for the retirement plan than respondents under age 25. Thus, the age differences across the immigrant and student samples may be the main reason for their differences in WTP for the retirement plan.There are a couple of similar valuations between immigrants and students. For respondents in both studies, the least valued benefit is the meat bonus, though estimated valuation is higher than its nominal value. Finally, both immigrants and students prefer to work fewer hours among the employment options on offer.The generalizability of these results is subject to some limitations. The hypothetical nature of the experiments can be prone to hypothetical bias issues. While hypothetical bias may have led to some large estimates, the results do point toward the provision of retirement and health benefits as a potentially viable alternative to raising wages. Future methodological research is needed to improve survey designs and economic experiments with workers as a subject pool. Another limitation of this study is the limited sample size. Extensions could look at a nationally representative sample of workers, perhaps segmented by sub‐fields (dairy, poultry, etc.), and in comparison to other connected fields (processing, distribution, retail, etc.).ACKNOWLEDGMENTSWe are grateful for very helpful feedback and suggestions from Rene Rosenbaum, Mark Skidmore, and Chris Wolf. We are also grateful to Zachariah Rutledge for his help in addressing some comments raised by three anonymous reviewers; as well as the editor and three anonymous reviewers for detailed feedback on previous drafts. The study was also partially funded by Michigan State University Rackham Research Endowment, and the USDA National Institute of Food and Agriculture, Hatch project 1013332.DATA AVAILABILITY STATEMENTThe data that support the findings of this study are available on request from the corresponding author. We will make our data and code available publicly once the manuscript is accepted for publication.REFERENCESABIC Action. 2022. Dairy, Agriculture Groups Call for Lawmakers to Address Farm Labor Shortage. Food Manufacturing. October 7, 2022. https://www.foodmanufacturing.com/labor/news/22485211/dairy-agriculture-groups-call-for-lawmakers-to-address-farm-labor-shortageAdcock, Flynn, David Anderson, and Parr Rosson. 2015. The Economic Impacts of Immigrant Labor on US Dairy Farms. 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Dairy workers' preferences for compensatory benefits: A field choice experiment with US immigrants and students

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© 2023 The Authors. Journal of the Agricultural and Applied Economics Association published by Wiley Periodicals LLC on behalf of the Agricultural & Applied Economics Association.
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Abstract

INTRODUCTIONThe US agricultural sector faces severe labor shortages (Fatka, 2019; Hertz & Zahniser, 2013; Taylor et al., 2012). These labor shortages are due in part to fewer immigrants from Mexico, who comprise a sizeable portion of agricultural workers (Charlton & Taylor, 2016; Martin, 2015). The decline in immigrant workers in the United States is due to several factors: the United States–Mexico–Canada Agreement (USMCA) (Zhao et al., 2020); structural transformation in Mexico; and political rhetoric against low‐skilled immigrant workers (Charlton et al., 2021; Christiaensen et al., 2021; Hanson et al., 2017; Taylor et al., 2012). Additionally, many Mexican workers are transitioning to off‐farm work (Charlton & Taylor, 2016).1Off‐farm work includes wage work or self‐employment in manufacturing and services, including commerce. In rural Mexico, this work may entail production of handicrafts or simple construction material such as bricks (Yúnez‐Naude & Taylor, 2001). In the United States, immigrants have shifted from agriculture to construction and retail sectors (Card & Lewis, 2007).While attracting and retaining workers has become difficult across the US agricultural sector, it is particularly challenging in the dairy sector because of the nature of the work and long hours. What's more, the US dairy industry has seen dramatic changes in recent decades, particularly in increased productivity and consolidation. Whereas small dairy farms rely on labor provided by the operator and operator's family, large farms rely on hired labor (MacDonald et al., 2007). Much of this hired labor is comprised of immigrant workers: 51% of dairy workers are immigrants who contribute 79% of the US milk supply (Adcock et al., 2015, p. 2). Dairy workers are needed year‐round, so that most dairy farms are not able to make use of the H‐2A visa program, which provides visas to seasonal immigrant workers as backup labor supply. There have been numerous media accounts of problematic labor shortages in the dairy sector (e.g., ABIC Action, 2022; Dumas, 2022; Hardbarger, 2021; Howard, 2021). In fact, labor is one of the most important drivers of production costs for dairy farms (second only to feed), and hence has an important role in determining profitability for dairy farms (Wittenberg & Wolf, 2014). Though a tight labor supply poses severe challenges for dairy farms, we know little about how farmers might retain and recruit workers in this industry.There is limited scope for further retaining and recruiting dairy workers by raising wages, as US agricultural wages have risen more than 20% since 1990 (Charlton et al., 2019), and dairy workers' earnings have risen even further. According to a national survey of dairy farms in 2014, hourly wages were nearly 20% higher than wages in crop production and wages were higher among dairy farms with hired immigrants. On top of this, the average annual benefit package offered by dairy farms (e.g., paid vacation, housing) increased overall earnings by 56% of wage earnings. When factoring in these benefits and the high number of hours worked per week, annual compensation among dairy workers was 70% higher than compensation in fast food, and 23% higher than compensation in landscaping (Adcock et al., 2015, p. 8).We do not know whether such relatively high earnings may attract workers whose preferences might differ from other agricultural workers. A survey of dairy workers in New York found that workers were primarily interested in maximizing earnings by working as many hours as possible and by learning new skills that would earn them higher wages (Maloney et al., 2016, p. 36–40). But workers in fruit and vegetable production are willing to forego wage earnings for benefits and bonuses (Gabbard & Perloff, 1997; Nolte & Fonseca, 2010). Some farmers believe higher wages will not attract or retain workers, so select US fruit and vegetable producers offer bonuses and low‐cost health care to employees and their families (Martin, 2015).In this article, we elicit dairy workers' preferences for such compensatory benefits with a discrete choice experiment (DCE) (see Louviere et al. [2000] and Hensher et al. [2015]). Our experimental design mirrors real‐world decision‐making for job choice by asking respondents to choose between job profiles described by compensation packages varying in their benefit attributes and attribute levels. Such elicitation methods require respondents to consider trade‐offs, making it possible to rank order preferences for different benefit packages. We assess workers' preferences for three distinct sets of employment attributes: monetary (wage, housing allowance, and incentive‐based pay); nonmonetary (health insurance, retirement plan, on‐site housing, and a meat bonus); and number of hours required to work each week.There have been a few studies using DCEs to estimate workers' preferences for employment contracts in food and agriculture industries. Luckstead et al. (2022) used a DCE to study workers' willingness to work in the US meatpacking industry in light of the COVID‐19 pandemic. Two studies implemented a DCE to identify contractual arrangements that would attract workers to a nascent horticulture exporting industry (Van den Broeck et al., 2016) in Senegal and (Schuster et al., 2017) in Peru. Other DCEs of workers have focused primarily on nonfarm labor.2In nonfarm employment, workers are willing to forego 20% of their wages to maintain control of their work schedules (Mas & Pallais, 2017). Several international studies have used DCEs with medical professionals, a relatively skilled population with different labor regulations. See for example, Ubach (2003), Huicho et al. (2012), Miranda et al. (2012), Rockers et al. (2012), Rao et al. (2013), Rockers et al. (2013), Kunaviktikul et al. (2015), Scott et al. (2015), Song et al. (2015), Efendi et al. (2016), Smitz et al. (2016), Takemura et al. (2016). This differentiation is important as preferences might significantly vary between farm and nonfarm labor, in part because the US Fair Labor Standards Act (FLSA) has a different set of regulations for the agriculture sector. Notably, farm workers are exempt from federal overtime pay requirements (US Department of Labor, 2020a).This article makes several valuable contributions to the literature on worker preferences and the use of DCE to help us understand how best to attract and retain workers in the US dairy sector. First, we have designed a lab‐in‐the‐field experiment tailored to the dairy sector. Second, we focus on a hard‐to‐reach population of immigrant workers who live and work in the United States year‐round, and who are often excluded from surveys of agricultural workers. Finally, to our knowledge, this paper is the first to employ the same methods and survey questionnaires to two distinct populations: immigrant workers and US students interested in working in the same agricultural sector.3We did not restrict our study to US citizens. However, all surveyed students had been born in the United States, with the exception of two exchange students from Ireland. As those two students did not plan to work in the United States, we excluded them from the sample for analysis.Our interest in surveying the two groups was to capture the two possible sets of employees in the industry: the milkers, farmhands, and herdsmen who do much of the labor‐intensive tasks on the farms; and those seeking management or technical positions in the industry. College students studying dairy science and management would be well‐placed to fill positions in high‐tech production. Workers who can manage high‐tech production are increasingly in demand in agriculture, as farms move toward less labor‐intensive and more capital‐intensive production in the face of rising wages and a declining supply of agricultural labor (Charlton et al., 2019).The remainder of this article is structured as follows: we outline the experimental design in Section 2 and econometric methods in Section 3; Section 4 summarizes our first study of immigrant workers (recruitment procedures, sample characteristics, and findings); Section 5 similarly summarizes our second study of students training to work in the dairy sector; and Section 6 concludes with a comparison of the two studies and implications of our findings.EXPERIMENTAL DESIGNWe designed a DCE to elicit dairy workers' preferences among a set of employment options described by different attributes (wage, benefits, bonuses, and number of hours worked). We conducted focus groups with immigrant dairy workers to identify benefits and bonuses that were already being offered, and those not being offered but of interest.4There were three focus groups, each comprised of three to five participants, all of whom indicated they were undocumented workers on local dairy farms. The focus groups were held at the home of a researcher who lived close to many of the targeted dairy farms in St. Johns, MI. The researcher also had prior experience interviewing migrant workers and previously knew a couple of the participants. Recruitment was by word of mouth via these specific participants who knew and trusted the researcher as a member of their local community. He and one of the authors of this paper jointly interviewed all participants in Spanish, the native language of all participants. These focus groups covered a number of topics: demographics, work experience, compensation, financial decisions, health, housing, workplace concerns, and career plans. This input helped us define the attributes and their corresponding levels to be used in the DCE.We identified seven attributes: wage, hours worked, housing, health insurance, retirement plan, a meat allowance bonus, and an incentivized bonus based on milk quality (see Table 1). For wages, we followed prior studies:5See for example, Ubach (2003), Rockers et al. (2013), Kunaviktikul et al. (2015); Scott et al. (2015); Song et al. (2015), and Takemura et al. (2016). one's current wage, a 15% wage increase, and a 15% wage decrease.6Wages reported by respondents were on average considerably higher than the federal minimum wage of $7.25 per hour—$11.49 and $11.20 in the two respective study populations. Thus, even the lower wage on offer in the DCE was on average 31%–35% higher than the federal minimum wage. Hours worked were described by four levels ranging from 48 to 84 h.7The closest attributes to hours worked in the literature were change in hours worked (Scott et al., 2015; Ubach, 2003) and work schedule (Huicho et al., 2012; Miranda et al., 2012). These levels were selected to be above 40 h to avoid conflating the number of hours worked and any potential overtime pay rates.8Though overtime pay in agriculture is not regulated by the FLSA, in our focus groups, some workers received overtime pay. They were also chosen to represent feasible shifts, for example, six 8‐h shifts or seven 12‐h shifts.1TableChoice experiment attributes and levels.AttributesLevelsWage15% less than current wage, Current wage, 15% more than current wageHours (average per week)48/56/70/84Health insurancePresent/AbsentRetirement planPresent/AbsentHousingHousing Allowance/On‐site housing/NoneMeat bonusPresent/AbsentQuality IncentivePresent/AbsentRemaining employment attributes were benefits mentioned in focus groups as either common or highly desired. We included employer provided on‐site housing and a more flexible housing allowance, resulting in three levels: no housing, on‐site housing, and a housing allowance.9Similar housing attributes and levels are frequent in the rural medical literature (Efendi et al., 2016; Huicho et al., 2012; Kunaviktikul et al., 2015; Miranda et al., 2012; Rockers et al., 2012, 2013; Smitz et al., 2016; Takemura et al., 2016). Remaining attributes were either included or excluded from each job description, and we described each included benefit and bonus to respondents.10A detailed description of all other attribute levels is reported in Supporting Information: Figure A2. How they were specifically presented to survey participants is included in Supporting Information: Appendix B. The retirement plan reflected a plan mentioned in focus groups. The health insurance plan was similar to plans used in prior studies (Kunaviktikul et al., 2015; Song et al., 2015; Van den Broeck et al., 2016). Two types of bonuses are unique to the dairy industry. A meat allowance bonus is the opportunity to purchase quality beef at reduced market prices. An incentivized bonus based on milk quality is a lump‐sum payment to workers only when milk quality meets certain stated standards. Some producers offered such bonuses, and workers differed in whether they viewed it as either a chance to increase their earnings or introduced too much uncertainty in earnings. As milk quality cannot be attributed to a single milker, this incentivized payment depends on the skills and diligence of the team of workers.Altogether, these seven attributes and their levels resulted in 331,776 = ((24 × 32 × 41)2) possible choice questions. To reduce fatigue effects, we performed a D‐Optimal design (Street & Burgess, 2007), which resulted in 72 choice questions. To further reduce fatigue, these 72 questions were distributed across eight blocks, each containing nine choice questions. Each question was comprised of two experimentally designed employment alternatives and an “opt‐out” option (see an example question in Supporting Information: Figure A1). Participants were randomly assigned to one of eight blocks, and the order of questions in each block was randomized to mitigate order effects.ECONOMETRIC ANALYSISIn designing the DCE, we assumed respondents would have individual preferences over various forms of employment compensation, and that they would select compensation packages that maximize their utility (McFadden, 1974). Utility is comprised of an observable, predictable component, Vnjt, ${{\boldsymbol{V}}}_{njt},$ and some unexplained random component, εnjt ${\varepsilon }_{njt}$ (Train, 2009):1Unjt=Vnjt+εnjt, ${U}_{njt}={{\boldsymbol{V}}}_{njt}+{\varepsilon }_{njt},$where Unjt ${U}_{njt}$ is the utility worker n derives from alternative j in choice question t.We assume εnjt ${\varepsilon }_{{njt}}$ to be independently and identically Gumbel distributed (error term) and estimated a mixed logit model (MXL) for panel data. This model accounts for random taste variation and correlation in unobserved factors over time (see Train [2009, p. 134–150] for the model derivation and Hensher et al. [2015, p. 601–704] for computational details).11For efficiency, we take 1000 Halton draws rather than random draws (Bhat, 2003). Given our experimental setup, we specify Vnjt ${{\boldsymbol{V}}}_{{njt}}$ in Equation (1) as follows:2Vnjt=OptOut+αnWagenjt+βn1Hoursnjt+βn2Healthnjt+βn3Retirenjt+βn4OSHousingnjt+βn5HousingAnjt+βn6Meatnjt+βn7Qualitynjt, ${V}_{{njt}}={\mathrm{OptOut}+\alpha }_{n}{\mathrm{Wage}}_{{njt}}+{\beta }_{n1}{\mathrm{Hours}}_{{njt}}+{\beta }_{n2}{\mathrm{Health}}_{{njt}}+{\beta }_{n3}{\mathrm{Retire}}_{{njt}}+{\beta }_{n4}{\mathrm{OSHousing}}_{{njt}}+{\beta }_{n5}\mathrm{Housing}{A}_{{njt}}+{\beta }_{n6}{\mathrm{Meat}}_{{njt}}+{\beta }_{n7}{\mathrm{Quality}}_{{njt}},$where OptOut was the alternative specific constant indicating the no‐application option, and Wagenjt ${\mathrm{Wage}}_{{njt}}$ is the hourly wage for worker n in alternative j in choice question t.This variable varies by worker because we use the worker's wage at the time of the survey as the base wage.12If the respondent was unemployed at the time of the survey, we use the respondent's wage from the most recent job. If the respondent had never previously held a job, we take the wage to be the federal minimum wage at the time of $7.25. Respondents were similarly instructed. This variable reflects the proposed wage each worker saw for each alternative j in choice question t. If the proposed wage was the same as the worker's wage earned at the time of the survey, then the variable equals this wage. On the other hand, if the proposed wage was 15% lower (higher) than the respondent's wage, we multiply the individual's reported hourly wage by 85% (115%). We estimate the marginal utility (MU) of the wage for individual n by αn ${\alpha }_{n}$, which we assume to be constrained triangular distributed.All other coefficients are assumed normally distributed.13For further details on selecting statistical distributions for random parameters in DCEs, see Hensher et al. (2015) and Caputo and Scarpa (2022). The first attribute, Hoursnjt ${\mathrm{Hours}}_{{njt}}$, is a continuous variable representing the average number of hours worked per week. Remaining variables are dichotomous, equal to one if alternative j in choice task t included the particular benefit or bonus. The marginal utility of the health insurance plan is estimated by βn2 ${\beta }_{n2}$, that of the retirement plan is estimated by βn3 ${\beta }_{n3}$, that of on‐site housing by βn4 ${\beta }_{n4}$, that of the housing allowance by βn5 ${\beta }_{n5}$, that of the meat bonus by βn6 ${\beta }_{n6}$, and that of the milk quality incentive by βn7 ${\beta }_{n7}$. The omitted reference (baseline) category is comprised of the absence of a health plan, retirement plan, housing accommodation, meat bonus, and milk quality incentive bonus payments.While we had expected respondents to receive utility from higher wages and from nonmonetary forms of compensation, it was unclear a priori whether the marginal utility of working more hours than they were already would be positive or negative. In other contexts, employers shifted from 8 to 12‐h shifts at the request of workers wanting to work more hours and increase earnings (Maloney et al., 2016, p. 27). In contrast, immigrant dairy workers already worked 48 h a week on average. To avoid potentially conflating the number of hours required to work per week with whether overtime pay was offered, we provided only choices with the required number of hours to be above the standard 40‐h work week, either 48 h or higher. It is possible that respondents were already maximizing their utility from the number of hours worked, particularly if they viewed more work hours as a negative impact on their leisure time. In this case, marginal utility from additional work hours per week would be negative.Coefficient estimates from the MXL (Supporting Information: Table A2) are used to determine the marginal rate of substitution (MRS) or willingness to pay (WTP) for each k $k$ nonmonetary compensation package, calculated as βk/α ${\beta }_{k}/\alpha $; where β $\beta $ is the coefficient of nonmonetary benefit package k, $k,$ and α $\alpha $ is the monetary (wage) coefficient (or marginal utility of income). We report WTP estimates in terms of one's hourly wage, with standard errors in parentheses and confidence intervals in brackets below each estimate (Tables 3 and 5). These are calculated using the Krinsky and Robb (1986) bootstrapping method. We also report WTP estimates in terms of annual income, calculated by multiplying estimates of the mean WTP per hour × 35 h × 50 weeks per year (median weekly hours worked in the pooled sample was 35 h, and we assume 10 days of paid holidays or leave). In Supporting Information: Table A3, we compare differences between estimated mean WTP in the two samples; we report p‐values from the combinatorial test introduced by Poe et al. (2005).STUDY 1: IMMIGRANT WORKERSRecruitment processParticipants in Study 1 were recruited from Clinton County, Michigan, one of the highest milk‐producing counties in the state. Milk production is the largest agricultural output in Michigan; with over 400,000 cows on nearly 1800 farms, each year producing over 11 billion pounds of milk worth more than $1.6 billion. In contrast to other midwestern states, Michigan dairies were early adopters of large production scale similar to Western states, requiring hired labor, especially immigrant labor (Michigan Department of Agriculture and Rural Development, 2019).We recruited study participants using a variety of approaches, as we focused on recruiting immigrant workers in the dairy sector, a hard‐to‐reach population. Many immigrant workers do not speak English, and some may not have a visa or permit to work in the United States. On top of this, dairy workers work long hours. We worked with agricultural extension agents and trusted leaders from local churches and communities in and around dairy farms. In July through October 2018, we visited dairy farms, Hispanic centers, local churches, and community events such as soccer games. At these community events and at meetings organized with local farmers and community leaders, Spanish‐speaking enumerators approached potential participants to inquire about their eligibility for and interest in the research study. A total of 107 immigrants were included in our survey.14We surveyed a total of 125 respondents through this community outreach. However, 18 respondents were born in the United States. Since the sample of US born respondents recruited via this approach was limited, we chose to drop them from our analysis.The survey took approximately 1 h, and participants were paid $15 for completion of the survey. Participants also received an additional payment from incentivized games used for another study, which averaged around $9 per participant. Participants signed consent forms (available in English and Spanish), following all research guidelines approved by Michigan State University's Institutional Review Board (IRB). We administered face‐to‐face Qualtrics surveys (previously downloaded onto tablets). The survey began with questions on demographics and work history, followed by our choice experiment. It was available in English and Spanish. Respondents could either complete the survey themselves or with the aid of a bilingual survey enumerator (fluent in English and Spanish).Descriptive statisticsWe summarize characteristics of the immigrant sample in Table 2. Most surveyed immigrants were men (63%), and this share of men in our sample was slightly lower than that of the National Agricultural Workers Survey (NAWS) (US Department of Labor, 2020b).15In NAWS, 77% of respondents are men. Immigrants were on average 33.5 years of age. Education levels were quite low among immigrants, with only 15% of immigrants having completed high school. Most immigrants had a least one child (75%) and 45% of them were married when surveyed. In addition, 99% of immigrants self‐identified as Hispanic.2TableDescriptive statistics of immigrant workers (Study 1).MeanStd. Dev.All study 1 respondents (N = 107)Gender (men = 1)0.630.49Age33.5210.50HS degree = 10.150.36Married = 10.460.50Has Children = 10.750.44Hispanic = 10.990.10Has driver's license = 10.290.46Has bank account = 10.440.50Employed when surveyed = 10.850.36Study 1 Respondents employed at the time of survey (N = 91)Works in dairy when surveyed0.650.48Hourly wage11.492.20Avg. hours work per week47.7317.99Employer provides:0.210.41Health insurance0.230.42Retirement plan (self‐paid)0.080.27Retirement plan with employer contribution0.110.31Paid holidays0.590.49Housing or housing allowance0.550.50Food0.180.38Incentive pay0.080.27As it is generally difficult for undocumented immigrants to obtain either a US driver's license or bank account, many of our respondents may have been undocumented. A driver's license is valuable, as public transportation options are limited in rural Michigan. Immigrants who would have lived in the United States for a while would need a US driver's license. Among those surveyed, 29% had a driver's license and 44% had US bank accounts in their own names.Around 85% of surveyed immigrants were employed at the time of the survey. Among employed respondents, 65% were working in the dairy sector. The average hourly wage was $11.49. Immigrants worked on average 48 h per week. In terms of the benefits that employers provided immigrants, 23% of employed immigrants received health insurance, and only 11% received a retirement plan. In addition, 55% received either housing or a housing allowance, and 18% received food from their employers. Finally, we asked if respondents had received any type of incentive‐based payments, such as the milk quality incentive bonus discussed in focus groups; 8% of employed immigrants received such payments.ResultsIn this section, we discuss estimates of WTP for the Study 1 sample of immigrants. In the first column of Table 3, we report WTP estimates in terms of one's hourly wage, with standard errors in parentheses and confidence intervals in brackets below each estimate. In the second column of Table 3, we report WTP estimates in terms of annual income.3TableMarginal willingness to pay (WTP) estimates for Study 1 sample of immigrants.Hourly wageAnnual salaryRetirement plan$5.01$8768(1.37)[$2.34, $7.69][$4095, $13458]Health insurance$2.67$4673(0.80)[$1.10, $4.25][$1925, $7438]Milk quality incentive$2.15$3763(0.78)[$0.62, $3.68][$1085, $6440]On‐site housing$1.24$2170(0.65)[−$0.03, $2.52][−$0.06, $4410]Housing allowance$0.77$1348(0.66)[−$0.53, $2.07][−$928, $3623]Meat bonus$0.74$1295(0.54)[−$0.03, $1.81][−$53, $3168]Hours−$0.03−$53(0.03)[−$0.08, $0.03][−$140, $53]Note: These estimates are based on Krinsky and Robb (1986) bootstrapping from marginal utility estimates, summarized in Supporting Information: Table A2. Column 1 reports mean WTP estimates as hourly wage. In column 2, we report mean WTP or WTA estimates in terms of one's annual wage income. These values were calculated as 35 h (the median in the pooled sample) × 50 weeks per year × Mean WTP Estimate from column 1. For all estimates, 95% confidence intervals are in brackets.As we might expect, all estimates of WTP are positive, except for the number of required work hours per week. Respondents must be compensated three cents for every additional hour of work required beyond 48 h. The negative coefficient estimates on hours are consistent with prior research (Nolte & Fonseca, 2010), although it runs counter to the commonly held notion in the dairy industry that workers prefer to work more rather than fewer hours (Maloney et al., 2016).Estimates of Equation (2) for this sample indicate the following rank ordering of attributes (from highest to lowest MU): retirement plan, health insurance, incentive bonus based on milk quality, on‐site housing, housing allowance, and a meat allowance bonus.Immigrants are willing to pay $5.01 per hour for a retirement plan, equivalent to roughly 40% of immigrants' wages. Recall that only 11% of employed immigrants received such a plan, despite working full‐time.There are several reasons why immigrants would highly value the retirement plan. Most surveyed immigrants do not have a bank account or any formal means of savings, and they often send money to relatives abroad who save this money on their behalf. But relying on relatives who are themselves in need of money is risky. In addition, the fact that many immigrants are willing to give up a portion of their earnings to be forced to save for the future is consistent with the limited commitment savings literature (Gugerty, 2007).The next most valued benefit is health insurance, and immigrants are willing to pay $2.67 per hour, nearly a quarter of their earnings. Health insurance plans vary greatly, with employers often providing catastrophic insurance, but not preventative care. Most employers do not offer immigrants the type of comprehensive health insurance described in our choice experiment.Immigrants are willing to pay $2.15 per hour for the milk‐quality incentive bonus, nearly 20% of their earnings. This amount is substantial considering that at most, the bonus could amount to $600 per year. Respondents may have misunderstood or not listened clearly to the description of this payment scheme, which may have been quite novel to many of them. They may also have overestimated the potential bonus payment, thinking primarily about their own skills and the possible feeling of worthiness for a payment derived from one's work efforts.16See Kruger and Dunning (1999) for more on the Dunning‐Kruger effect, namely that poor performers overestimate their performance ability. Finally, results could suffer from hypothetical bias.Following the bonus based on milk quality, the next most valued benefit for immigrants is on‐site housing; with a WTP estimate of $1.24 per hour. The description of on‐site housing was consistent with the type of housing immigrant workers often receive from their employers.The next most valued benefit is a monthly housing allowance of $500 a month, or $6000 for the year. On average, respondents are willing to pay $1348 per year. This relatively low valuation might reflect the fact that housing is relatively inexpensive in this region, and that the housing benefit is tied to the specific employer.17For example, the fair market rent for Clinton and Ingham counties, from where participants were recruited, ranged from $328.25‐$690 per person (per bedroom) (see Rentdata.org, 2018).The least valued benefit is the meat bonus, though estimated valuation is much higher than its nominal value. Immigrant respondents are willing to pay 74 cents per hour ($1,295 per year) for the meat bonus. This bonus provides workers the option to purchase freshly slaughtered meat by paying only the processing fee of $0.40 per pound. Workers could request up to one cow's worth of meat for themselves per year, approximately 600 pounds of raw meat. The maximum annual value of this bonus is $240.18From July through December 2018 the average retail price of cuts of beef ranged from $0.99 to $22.99 (US Department of Agriculture: Agricultural Marketing Service).To better understand what might be driving these WTP estimates, we estimate two models using seemingly unrelated regression (SUR), where the dependent variables are the marginal WTP estimates for attributes in the DCE (see Supporting Information: Tables A4 and A5).19We have too small a sample size to estimate SUR for Study 2. Also, students are similar to one another in terms of age and many of the dimensions we explore in the SUR models for Study 1. In the first model, we exclude variables indicating one lives with a spouse or children. In the second model, we include these variables.20We estimate these two models because when we include these family‐related variables, coefficient estimates on whether one has a driver's license or bank account are affected.Respondents who have a driver's license would be less likely to be undocumented workers compared to others, and they would therefore be more likely to receive benefits that require documentation of legal status to work in the United States, such as a pension or health insurance. On average, respondents with a driver's license have a 65% higher WTP (an additional $2.03 with a sample mean WTP of $3.14) for a retirement plan compared to those who do not have a license. When we control for whether one lives with a spouse or children, this estimate declines to $1.62. Respondents with a driver's license are also willing to pay 24%–29% more for health insurance compared to those who do not have a license (mean WTP for health insurance is $1.80).Immigrant workers who have a US bank account in their own names would perhaps have more financial security and savings options than those who do not have an account. Having a bank account lowers WTP by an average of 41%–50% (average WTP for a housing allowance is $3.14); this estimate is statistically significant with p < 0.1 only when we do not also control for indicators related to living with a spouse or children. In addition, having a bank account lowers WTP for a housing allowance by 16% to 20% on average, with p < 0.05 when additional covariates are excluded and p < 0.1 with all covariates in the model.Compared to higher earners, respondents whose annual salaries are below the sample median are willing to forego a greater portion of their wages to work more hours (p < 0.05). The magnitude of the estimate is economically significant—they are willing to forego 4.2 cents in hourly wages to work more hours; whereas on average, participants are willing to accept an additional 3.5 cents in wages to work more hours.Participants with a below median salary have a higher WTP for the milk quality incentive bonus (68 cents or 42% of the average marginal WTP). This estimate is statistically significant with p < 0.1 only for Model 1.Age is a significant predictor of WTP for the retirement plan. We include in the SUR—indicator variables for age ranges (age 25–34, age 35–44, age 44 and up, with ages under 25 as the omitted reference category). Coefficient estimates on the indicator for ages 35–44 are statistically significant (with p < 0.1 in Model 1 and p < 0.05 in Model 2). Magnitudes are economically significant, $2.32 for Model 1 and $2.96 for Model 2. As the mean marginal WTP for the retirement plan is $3.14, on average, respondents ages 35–44 are willing to pay 74%–94% more for the retirement plan than respondents under age 25.Compared to the youngest respondents (under age 25), the oldest respondents (age 44 and up) need to be compensated with considerably higher hourly wages to work more hours. Whereas the average marginal willingness to accept more work hours is 3.5 cents; to work more hours, respondents ages 44 and up need an additional 5.5 cents per hour compared to respondents under age 25. Estimates in both models are statistically significant with p < 0.05.Finally, those who live with a spouse are willing to pay nearly $2 per hour less for the retirement plan, which is 63% of the average marginal WTP for the retirement plan (p < 0.01). Those who live with a spouse also have lower WTP for on‐site housing (22% of the average WTP, p < 0.05), and the meat bonus (47% of the average WTP, p < 0.1). Somewhat puzzlingly, those who live with children have a 23% lower WTP for the housing allowance, with p < 0.05. The amount of the housing allowance may be too small relative to the cost of a home for a family with children.STUDY 2: STUDENT SAMPLERecruitment processIn addition to our efforts to recruit immigrant workers across dairy farm communities in Michigan, we also recruited undergraduate students from Michigan State University's Dairy Club and from the university's Dairy Management Agricultural Technology Certificate program.21For further information on the Dairy club see in the references “Michigan State University Dairy Club.” For further information on the certificate program see “Dairy Management.” The Dairy Club is a student‐run organization for undergraduate students who are interested in working in the dairy industry. This student organization provides opportunities for developing leadership skills for its members.The certificate program is specifically designed for students who plan to work or are already working in the dairy sector. Students do not earn a bachelor's degree, though their coursework could be used toward obtaining a university degree following the certificate program.22In 2018, nearly half of the students continued their education toward a 4‐year college degree. Nearly a third of students returned to their family farms, with remaining students working either on a dairy farm or for an agricultural business supporting dairy farms. These figures were provided by the coordinator of the certificate program, Dr. Joe Domecq. In addition to their coursework, students gain practical experience working on dairy farms who cooperate with the program. The MSU certificate program advertises that their program prepares students for careers in dairy management and farming and nutrition industries.In November 2018, we organized meetings of the Dairy Club for the purposes of our survey. In December 2018, we visited introductory courses required of all students in the Dairy Management Agricultural Technology Certificate program, and with the instructor's permission, we invited students to remain after class to participate in the study.23All of our recruitment efforts and study procedures followed guidelines approved by Michigan State University's Institutional Review Board (IRB). We recruited a total of 53 students, and we excluded from our analyzed sample two exchange students from Ireland—resulting in a sample of 51 students.24We surveyed roughly 80% of the students in these two programs. Each year, there are about 50 members in the Dairy Club. In 2018, 26 students completed or were set to complete the certificate program. Of these 26 students, roughly 16 of them were also members of the Dairy Club. These figures were provided by the coordinator of the certificate program, Dr. Joe Domecq.Descriptive statisticsWe summarize student characteristics in Table 4. Only 29% of surveyed students were men. The average age of students was just under 20, and 65% of students had completed high school. 52% of students had a driver's license and 62% of students had a US bank account in their own names.25In pairwise means comparison tests between students and respondents in Study 1, all but one of the aforementioned descriptives were statistically significantly different across samples, with p < 0.001. Employment rates among students and immigrants were similar (p = 0.46).4TableDescriptive statistics of student sample (Study 2).MeanStd. Dev.All Study 2 respondents (N = 51)Gender (men = 1)0.290.46Age19.571.27HS degree = 10.650.48Married = 1‐‐Has children = 1‐‐Hispanic = 1‐‐Has driver's license = 11.00‐Has bank account = 11.00‐Employed when surveyed = 10.800.40Study 2 Respondents employed at the time of survey (N = 41)Works in dairy when surveyed0.490.51Hourly wage11.205.35Avg. hours work per week21.8818.67Employer provides:0.170.38Health insurance0.100.30Retirement plan (selfpaid)0.100.30Retirement plan with employer contribution0.240.43Paid holidays0.240.43Housing or housing allowance0.240.43Food0.050.22Incentive pay0.170.38Among students employed at the time of our survey, 49% of students were working in the dairy sector.26Among these students, one‐third were working on a family farm. Among the students not employed in the dairy sector at the time of the survey, 55% had previously worked in dairy. The average hourly wage was close to $11.20. On average, students worked about 22 h per week. Only 10% of students received health insurance, and 24% of students received a retirement plan with employer contribution. In addition, 24% of students received either housing or a housing allowance, and just 5% of students received food from their employers. Finally, 17% of students reported receiving some type of incentive‐based payment.ResultsIn this section, we discuss estimates of WTP for the sample of students. In the first column of Table 5, we report WTP estimates in terms of one's hourly wage, with robust standard errors in parentheses and confidence intervals in brackets below each estimate. In the second column, we report WTP estimates in terms of annual income.5TableMarginal willingness to pay (WTP) estimates for Study 2 sample of students.Hourly wageAnnual salaryHealth insurance$1.22$2135(0.28)[$0.66, $1.77][$1155, $3098]Retirement plan$1.19$2,083(0.31)[$0.59, $1.79][$1033,$3133]Housing allowance$1.15$2013(0.35)[0.47, $1.83][$823, $3203]Milk quality incentive$1.14$1995(0.31)[$0.53, $1.75][$928, $3063]Meat bonus$0.78$1365(0.24)[$0.30, $1.26][$525, $2205]On‐site housing$0.33$578(0.31)[−$0.28, $0.94][−$490, $1645]Hours−$0.05−$88(0.01)[−$0.07, −$0.03][−$123, −$53]Note: These estimates are based on Krinsky and Robb (1986) bootstrapping from marginal utility estimates, summarized in Supporting Information: Table A2. Column 1 reports mean WTP estimates as hourly wage. In column 2, we report mean WTP or WTA estimates in terms of one's annual wage income. These values were calculated as 35 h (the median in the pooled sample) × 50 weeks per year × Mean WTP Estimate from column 1. For all estimates, 95% confidence intervals are in brackets.As in Study 1, all estimates of WTP are positive, except for the number of required work hours per week. Students must be compensated 5 cents for every additional hour of work required beyond 48 h. While students worked about 22 h a week on average at the time of the survey, upon graduation or completion of their certificates, students would likely work full‐time, or around 40–50 h per week.Estimates of Equation (2) for the student sample indicate the following rank ordering of attributes (from highest to lowest MU): health insurance, retirement plan, housing allowance, incentive bonus based on milk quality, meat allowance bonus, and on‐site housing.Students are willing to pay about 10% of their earnings for a retirement plan or health plan. Many students do not receive health insurance from their employers, perhaps because they receive health insurance either via the university or parents.Students also similarly value the housing allowance and incentivized bonus determined by milk quality. On average, respondents are willing to pay $2000 per year for each of these benefits. Students are willing to pay 78 cents per hour ($1365 per year) for the meat bonus.Finally, for on‐site housing, students are willing to pay $0.33 per hour. The description of on‐site housing is consistent with housing immigrants often receive from their employers, and this type of living arrangement is likely uncommon for students.DISCUSSION AND CONCLUSIONUsing a discrete choice experiment designed to elicit dairy workers' preferences for compensatory benefits and bonuses, we have shown that to attract and retain workers in the dairy sector, it can be worthwhile for employers to provide retirement and health insurance benefits. Incentivized bonuses are also attractive to workers, as is an average 48‐h work week.These findings are consistent with studies in other industries, which taken together show the importance of offering nonmonetary benefits to attract and retain agricultural workers. In the meatpacking industry, DCE results indicated high valuation of retirement and health benefits (Luckstead et al., 2022). Fruit and vegetable growers were already offering such benefits to retain workers (Martin, 2015).WTP estimates found here could be reasonably provided by employers, with cost sharing between employees and employers. For example, in a review of farm worker union contracts negotiated in 2013 between California employers and the United Farm Workers of America Union (the most prominent union of farm workers in the United States)—the most common health insurance plan offered to UFW employees in California required an average hourly contribution of $2.23 and the most common pension plan offered had an average hourly contribution of $0.13 (Rutledge, 2021). While inflationary pressures may have since increased these values, they are generally higher in California compared to Michigan. Our findings indicate that immigrant workers would be willing to pay a significant share of the health insurance costs, and students would be willing to pay about 55% of the average contribution required for the health plan. Both study populations have a WTP for a retirement plan that is well above this required contribution.We find several notable differences between immigrant workers in the dairy sector and US college students who plan to work in the dairy sector. For health insurance, immigrants are willing to pay more than double students' average WTP. In comparison to students, immigrants are willing to pay five times more for a retirement plan. Immigrants are willing to pay nearly twice as much as students for an incentivized bonus determined by milk quality.Immigrants and students are generally in different stages of their life courses, with different family planning considerations and different expectations regarding healthcare costs; these differences may be particularly relevant in influencing preferences for health insurance or a retirement plan. While students' ages range between 18 and 23 (Study 2), immigrants in Study 1 range in age from 18 to 65 (with the bulk of ages between 23 and 38).27See Supporting Information: Figures A3 and A4 for sample distributions in terms of age. Recall that immigrant respondents ages 35–44 are willing to pay 74%–94% more for the retirement plan than respondents under age 25. Thus, the age differences across the immigrant and student samples may be the main reason for their differences in WTP for the retirement plan.There are a couple of similar valuations between immigrants and students. For respondents in both studies, the least valued benefit is the meat bonus, though estimated valuation is higher than its nominal value. Finally, both immigrants and students prefer to work fewer hours among the employment options on offer.The generalizability of these results is subject to some limitations. The hypothetical nature of the experiments can be prone to hypothetical bias issues. While hypothetical bias may have led to some large estimates, the results do point toward the provision of retirement and health benefits as a potentially viable alternative to raising wages. Future methodological research is needed to improve survey designs and economic experiments with workers as a subject pool. Another limitation of this study is the limited sample size. Extensions could look at a nationally representative sample of workers, perhaps segmented by sub‐fields (dairy, poultry, etc.), and in comparison to other connected fields (processing, distribution, retail, etc.).ACKNOWLEDGMENTSWe are grateful for very helpful feedback and suggestions from Rene Rosenbaum, Mark Skidmore, and Chris Wolf. We are also grateful to Zachariah Rutledge for his help in addressing some comments raised by three anonymous reviewers; as well as the editor and three anonymous reviewers for detailed feedback on previous drafts. 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Journal

Journal of the Agricultural and Applied Economics AssociationWiley

Published: Jun 1, 2023

Keywords: compensatory benefits; dairy sector; discrete choice experiment; immigrant labor

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