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The ACA, Health Care Costs, and Disparities in Employer-Sponsored Health Insurance

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The ACA, Health Care Costs, and

Disparities in Employer-Sponsored

Health Insurance

March 2013

By NaN L. MaxweLL WORKING PAPER 14

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The research was conceived while the author was a Professor of Economics and Director of the HIRE Center at California State University, East Bay, and a Visiting Research Fellow at the Public Policy Institute of California. It benefited greatly from comments and discussions with Jed DeVaro, Catherine McLaughlin, Debbie Reed, Steve Shmanske, and Marian Wrobel and from presentations at Mathematica Policy Research, California State University, East Bay, the W.E. Upjohn Institute for Employment Research, and the Western Economic Association. The research was partially funded by the W.E. Upjohn Institute for Employment Research and the University of California Program on Access to Care. Although numerous individuals made this study possible, the author assumes full responsibility for all errors.

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ABSTRACT

This study examines the potential changes in the disparities in employer-sponsored health

insurance (ESI) between low- and high-wage workers that might accompany the Affordable Care Act (ACA). It uses California Health and Employment Survey (CHES) data to assess ESI offers made prior to active ACA discussions and potential changes in offers after the ACA is

implemented. Our analysis suggests that the potential changes firms might make to

compensation with the ACA could decrease the disparities between low- and high-wage workers in the quality of ESI and increase the disparities in the offer of benefits other than ESI if the legislation does not slow rising health care costs.

Keywords: Affordable Care Act, employer-sponsored health insurance, workforce skills, benefits, disparities, low-wage workers

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The 2010 passage of the Patient Protection and Affordable Care Act (ACA) as amended by the Health Care and Education Reconciliation Act represents a major change for the U.S. health care market while keeping employer-sponsored insurance (ESI) as the cornerstone of coverage for the nonelderly population. Several of its provisions were designed to provide firms with incentives to expand, or at least maintain, ESI coverage and several were designed to increase the quality of coverage offered.

Predictions vary about the ACA’s potential to expand coverage (GAO, 2012).

Microsimulations of the changes in the number of individuals with ESI coverage range from a 2.5 percent decrease to a 2.7 percent increase in near-term coverage, and research on the coverage change using behavioral modeling range from a 6 percent increase to a 2 to 3 percent decrease. Surveys of employers that offer ESI estimate that between 2 and 20 percent are likely to drop coverage in the near term.

Because the intent of the legislation is to increase the quality of coverage and the number of employees covered, discussions have occurred about its potential to increase ESI costs for firms. Several surveys have attempted to assess the potential for cost increases with the ACA. Mercer (2012) surveyed 1,203 employers and found that 60 percent expected some increase in health care costs with the legislation. One-third of those expected an increase of 5 percent or more. Similarly, in a survey of nearly 500 health insurance agents, about three-quarters said, without any prompting, that increasing costs was the most noteworthy change in the individual and small business health insurance market with the ACA (Kaiser Family Foundation, 2012b). Such perceptions might be based on the spike in employers’ spending on health coverage for workers in 2011. The average cost of a family plan rose by 9 percent in 2011, triple the growth

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seen in 2010 (Kaiser Family Foundation, 2011), with about 1.8 percentage points potentially attributable to the ACA (Commonwealth Fund, 2011).

This study focuses the discussion of changes accompanying the ACA on another set of changes that might occur: disparities in the ESI offer between low- and high-wage workers. The examination of such disparities is grounded in an analysis that assesses different changes in the offer by firms employing a disproportionate percentage of low- or high-skilled workers, under the belief firms with a majority of low- (high-) skilled workers employ a high percentage of low- (high-) wage workers.

Our analysis uses the California Health and Employment Survey (CHES), a database of 1,427 randomly selected firms in 27 northern California counties that were interviewed in 2005 and 2006 about their ESI offer. The timing of the survey provides insights into offers prior to active deliberations on the ACA and the Great Recession. Our analysis focuses on three types of potential changes: small firms making offers, characteristics of ESI offers, and offers of other benefits. Our findings suggest that the proportion of small firms offering ESI might remain stable with the ACA, but if ACA does not succeed in slowing the growth of health care costs, the nature of the ESI offer might change in ways that reduce pre-ACA disparities in the ESI offers but exacerbate differences in the offers of other benefits.

Context for Change

Prior to the passage of the ACA, 59 percent of all firms offered ESI (in 2009), although that percentage varied by the size of the firm. About 98 percent of firms with 200 or more employees, 95 percent of those with 50 to 199 workers, and 47 percent of those with 3 to 9 workers offered ESI (Kaiser Family Foundation, 2011). These offers covered about 58.7 percent of individuals under age 65 in March 2010, either as a worker or a dependent (Fronstin, 2011).

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Relatively large disparities existed in the ESI coverage between low- and high-wage workers, however. In 2003, ESI coverage stood 34 percent higher for college-educated workers than for high school-educated workers and their dependents (Gould, 2004), and the percentage of nonelderly workers with ESI was 47 percentage points higher for those earning more than $15 per hour than for those earning less than $10 per hour (Collins et al., 2004).

Such disparities in whether workers are covered by their firm’s ESI can arise for three reasons: not all firms offer ESI, not all workers are eligible for an offer, and not all workers accept (take up) an offer. Whether a firm offers ESI depends on how it perceives the benefits and costs of using it to compensate workers. The primary benefit of replacing wages with an ESI offer arises from a decreased tax burden and an ability to attract workers. Although an employer can deduct both wages and ESI expenses as business expenses from its tax burden, ESI expenses are exempt from the 6.2 percent payroll tax for Social Security (for workers falling below its maximum wage) and the 1.45 percent payroll tax for Medicare. Because ESI is essentially taxed at a lower rate than wages, it becomes cheaper for a firm to compensate a worker with a dollar of ESI than a dollar of wages. Further, most workers want ESI as part of their compensation.

Research suggests that 73 percent of workers said ESI was a very important factor in their decision to take or keep a job (Duchon et al., 2000), 65 percent ranked it as the most important employee benefit, and only 10 percent stated they would prefer a wage increase to health insurance (Salisbury & Ostuw, 2000). Even if a firm offers ESI, a particular worker in the firm might not be covered by it. In 2009, about 80 percent of workers in firms that offered ESI were eligible for the offer and about 80 percent of workers eligible for the offer accepted it (Claxton et al., 2010).

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Differences in both offer and acceptance rates underlie disparities between low- and high-wage workers in ESI coverage. Firms with high-high-wage workers are more likely to offer ESI and high-wage workers are more likely to enroll in a plan if one is offered. The 2010 Kaiser/HRET Survey of Employer-Sponsored Health Benefits shows that 48 percent of firms with at least 35 percent of workers earning $23,000 or less offered ESI compared to 74 percent of firms with fewer than 35 percent at that salary level (Claxton et al., 2010). The 2008 National

Compensation Survey shows that about 50 percent of private sector workers in the lowest 10 percent of wages enrolled in their firm’s ESI plan, compared to 80 percent in the highest 10 percent (U.S. Bureau of Labor Statistics, 2009).

The ACA

The ACA was designed to increase the percentage of individuals with health care

coverage and contain rapidly growing health care costs. It created the state-run American Health Benefit Exchanges (exchanges) as one vehicle by which to implement incentives to achieve these goals. Prior to its implementation, in 2009 through 2010, 18.8 percent of the population younger than age 65 did not have insurance (DeNavas Wait, Proctor, & Smith, 2010) and ESI premiums increased between 3 and 13 percent per year (2000 through 2010), whereas inflation and changes in workers’ earnings were typically 2 to 4 percent (Kaiser Family Foundation, 2012a).

Coverage might expand with the ACA because incentives exist for firms to offer ESI and individuals to accept the offer. Incentives for firms to offer coverage differ by the size of the firm. Large firms—those with at least 50 full-time equivalent employees—will be required to offer ESI to employees that work at least 30 hours per week and more than 120 days during the year within 90 days of their starting employment or potentially face financial penalties. Some small firms will receive a tax credit as an incentive to offer ESI. The full credit is available to

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firms with fewer than 10 employees and with average annual wages less than $25,000. It phases into a partial credit for firms with up to $50,000 in average wages or 25 full-time workers. The credit was worth up to 35 percent of a small firm’s premiums in 2010 and is worth up to 50 percent starting in 2014. Firms can claim the credit for up to six years, the initial four years from 2010 through 2013 and for any two consecutive years thereafter if they buy their insurance through the Small Business Health Options Program (SHOP). Premiums for firms that do not receive a tax credit can still be deducted from taxes. Incentives to accept a firm’s ESI offer arise with the mandate for most individuals to maintain minimum essential health insurance coverage or pay a penalty for noncompliance.1

Arguably, the biggest potential for cost containment lies with the annual reviews of “unreasonable increases in premiums” for non-grandfathered health plans. These reviews will be conducted by the U.S. Department of Health and Human Services in collaboration with state insurance departments. The effectiveness of such reviews has been called into question,

however, because some states do not provide an authority to conduct such reviews; in addition, states that have such an authority have a wide variation in practices for conducting such reviews and have rarely denied premium increases in the past (Kaiser Family Foundation, 2010). Costs might also be contained with competition among insurers and transparency in the sale of insurance policies in the exchanges, risk pool improvements with the individual requirement to carry insurance, rebates if health plans spend less than 85 (large-group market) or 80 percent

1 The ability of the mandate to increase the rate at which workers take a firm’s ESI offer is unknown. Take-up rates

might increase as individuals increasingly accept the offer to comply with the mandate. More than 60 percent of workers declined ESI because they had other coverage (Fronstin, 2007), leaving up to 40 percent of those who declined an offer as susceptible to accepting it with the mandate. Alternatively, they might decrease as some individuals, particularly low-wage workers, replace ESI with lower-priced coverage from expanded Medicaid eligibility or premium subsidies in the exchanges.

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(small-group market) of their premiums on medical care, and reforms to reduce payments for treatments and hospitalizations resulting from errors or poor quality of care.

Cost containment measures may or may not be effective at stemming ESI cost increases for firms because provisions in the legislation might increase a firm’s ESI expenditures by increasing the number of workers covered (discussed above) and increasing its ESI premiums. Several provisions of the ACA might increase premium costs, and unless these premium costs are passed on to the workers, they will increase a firm’s ESI expenditures, otherthings being equal. The ACA restricts plans from imposing lifetime and annual limits on benefits or excluding individuals from coverage for preexisting conditions. Firms must offer a plan that covers dependents and children up to age 26. New health plans must provide a minimum set of services, limit annual out-of-pocket spending, and contain no cost sharing for preventive

services. Health plans sold through the individual and SHOP exchanges must provide a federally determined essential benefit package. In addition, insurers cannot charge higher premiums based on health status and gender, deny coverage to people for any reason, or rescind coverage, except in cases of fraud.

Incentives for Firms to Change Compensation Structure

If the ACA does not succeed in lowering the growth of health care costs for employers, the theory of compensating differentials (Rosen, 1986) suggests that firms that offer ESI will pass the increase to workers by decreasing another component of compensation. Firms might reduce wages or employment (Abraham & Voos, 2008;Baicker & Levy, 2007; Baicker & Chandra, 2006) or cut other benefits offered to workers (Baughman, DiNardi, & Holtz-Eakin, 2003). Firms might also decrease the quality of the health insurance offered (Royalty & Hagens,

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2005) by increasing premium sharing or copayments (for example) even if the ACA limits their ability to decrease the scope of services covered.

Compensation changes are likely to be consistent with changes desired by the type of worker a firm wants to retain or attract (Lehrer & Pereira, 2007; Gruber & Lettau, 2004) and to be made at the firm level.2 Firm-wide changes mean that firms must identify the preference for wages and benefits of their typical worker.3 Such identification is complicated because some workers value ESI highly and are willing to trade more than one dollar of wages for one dollar of ESI, whereas others value wages highly and are only willing to trade a dollar of wages for more than one dollar of ESI. Other things being equal, high-wage workers will value ESI more highly than will low-wage workers (Royalty, 2000) because progressive marginal income tax rates increase the tax savings from nonwage compensation for high-wage workers, whereas Medicaid and indigent health care decrease the value of ESI for low-wage workers (Currie & Yelowitz, 2000). Consequently, we might expect firms with a majority of high-wage workers to be wary of adopting a strategy that reduces benefits when ESI costs increase and firms with a majority of low-wage workers to be wary of selecting one that reduces wages.

Our study focuses on three types of changes firms might make with the ACA and

examines how those changes might vary with the skill level of the firm’s workforce. One change is the potential of the ACA to affect, because of tax incentives and continued cost increases, the number of small firms making an ESI offer. We focus on offer changes by small firms because virtually all large firms offered ESI prior to the ACA. The second change is in the nature of the

2 The nondiscrimination rule restricts a firm’s ability to negotiate benefits with individual workers (Carrington,

McCue, & Pierce, 2002).

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Goldstein and Pauly (1976) highlight how firms basing the ESI offer on characteristics of the median worker might weigh it more toward lower-wage workers than firms using average wages because the low-end bound of zero or minimum wage makes median wages lie below average wages. The distinction is less salient in research that models the ESI offer as based on attracting skills and not on wages, as this study does.

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ESI offer, and the third is in the offer of other benefits. Such changes might arise if the ACA is not successful in containing rising health care costs. These changes are examined in a manner that answers three research questions: (1) How might firms respond to continued ESI cost increases? (2) To what extent might the percentage of small firms that offer ESI change with the ACA? (3) What changes in the pre-ACA disparities between low- and high-wage workers might occur with firms’ response to continued ESI cost increases and ACA tax incentives?

RESEARCH DESIGN, DATA, AND ANALYSIS

We focus on disparities by comparing the behaviors of firms with a majority of low-skilled jobs to those with a majority of high-low-skilled jobs. Our use of skills—as opposed to wages—to assess disparities is critical because wages are a key part of the tradeoffs in

components of compensation and are therefore an endogenous part of the disparity.4 Both wages and ESI are critical components of compensation for workers when selecting a firm for

employment (Lehrer & Pereira, 2007), and the direction of their relationship with skills is important. We structure the relationship as one in which the skills a firm needs are exogenously set (through production mode, for example) with the firm using wages and ESI to attract the type of skills that it needs. Firms that need high-skilled workers are likely to have high-wage workers that place a relatively high marginal value on ESI and are likely to attract such workers by building a compensation package that includes health insurance and other benefits. In contrast, firms whose production relies on low-skilled workers, with their relatively lower wages, weigh the compensation package in favor of wages, and do not include as much ESI or other benefits.

4 The use of wages to assess disparities is less problematic in research using individuals as the unit of analysis

because the firms’ benefit offer to an individual is largely exogenous because the nondiscrimination clause limits their ability to individually negotiate an offer of ESI (for example).

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The research questions and study’s design require firm-level data that include

information on how firms might respond to continued ESI cost increases, workforce skills, the different components of compensation firms offer, and firm size. The CHES database is uniquely positioned for this research because it contains all of these components. From July 2005 through September 2006, the CHES randomly selected and surveyed private sector firms with five or more workers and had a 67 percent response rate (Maxwell, 2007). The database contains 1,427 firms5 in 27 northern California counties, 1,245 of which offered ESI. The targeted respondent for the survey was “the person with knowledge about benefits and jobs.” The sampling of firms was structured to approximate the distribution of firms throughout the United States with respect to its rurality and to oversample firms with more than 50 employees. The database contains weights for apportioning its distribution to that of U.S. firms with respect to size and industry.6

A firm’s potential response to ESI cost increases is captured using responses to past cost increases that were collected from firms that offered ESI and reasons for not offering ESI for firms that did not offer it. Information on 21 actions firms offering ESI took in response to rising health care costs in the past was obtained from the question “Because health care costs have risen in the past few years, we are interested in getting your impressions of what your firm has done in the past three to five years about escalating health care costs. We would like you to answer yes to our question if you think the action we mention is one your firm has taken and no if it has not…. In response to rising health care costs, did your firm …?” Table 2 provides a listing of most of the actions. Firms that did not offer ESI were asked to rate the reasons they did not offer it with the question “We are interested in knowing why your firm does not offer health insurance. On a

5 The CHES used establishment as the unit for sampling and excluded multiple establishments in the same firm.

Because only 62 establishments of 706 multi-establishment firms in the CHES (4.3 percent) report setting their own benefits, we discuss the data as if the firm was the unit of analysis.

6 Because California is more urban than the rest of the United States, CHES counties contain a greater percentage of

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scale where one is not at all important and five is very important, please say why your firm does NOT offer health insurance to its workers.”

Workforce skills are captured using the question, asked of all firms, about the percentage of jobs that were low-skilled (required no more than a high school education and one year of work experience at the time of hire), mid-skilled (required some college and three to five years of work experience at the time of hire), and high-skilled (required at least a college education or five years of work experience at the time of hire). We used this information to classify firms as low-skilled (at least half the jobs were low-skilled) and high-skilled (at least half the jobs were high-skilled).

The different components of compensation a firm offers were constructed using the questions asking firms if they offered each of 22 different benefits, including health benefits. If a firm offered health benefits, surveyors asked a series of general questions about them, including the number and kinds of plans offered, how many months and how many hours per week

employees must work before they could enroll in them, and whether they were available to seasonal and temporary workers. Surveyors also asked for specific information about the health care plan most workers selected, including the percentage of the premium the firm paid and cost sharing provisions.

Firm size was captured, in categories, by asking firms to estimate the number of workers employed at all locations. We collapsed the information into categories of 5 to 19 workers, 20 to 50 workers, and 51 or more workers to enable analysis by very small (5 to 19), small (20 to 50) and large (more than 50) firms.

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Research Question 1

The first research question investigates responses to past increases, which provides the basis for assessing the changes that might occur if cost increases continue. We used a factor analysis to identify patterns of responses among the 16 responses shown in Table 27 and used those patterns to describe behavior that firms exhibited when health care costs increased in the past. Factor analysis assumes that a system of constructs (that is, patterns) exists in the CHES measures of actions taken that underlie actual behavior. The empirical measures of the constructs estimated from the factor analysis, called factors, account for the correlations8 in CHES

measures. Factors were identified using the factor structure matrix, also known as the factor loading. This matrix of n (the 16 actions) by m (number of retained factors) shows the correlations between the measures of firm actions and the estimated factors and is used to identify common patterns among the actions firms took when health care costs increased. We interpreted the commonalities in the actions using a factor loading of at least 0.5.9

Research Question 2

The second research question addresses the potential for the small business tax credits to induce eligible firms to offer ESI. To answer this question, we undertook two types of analysis. We first aligned the stated reasons small firms gave for not offering ESI in the past against the ACA to assess overlap and then developed a decision tree simulation to estimate the percentage

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Our analysis excluded four behaviors that might reflect changes in the federal tax code (starting a health reimbursement account, flexible spending account, high deductible plan, or health savings account) and one behavior not directly affecting workers (increasing prices or decreasing services).

8 The factor extraction partitions the variance of a measure that is shared with other measures from its unique

variance and error variance to identify the underlying factor structure. Only the shared variance appears in the solution. In contrast, principal components analysis does not discriminate between shared and unique variance and, as a result, can produce inflated values of variance that are accounted for by the components. Osborne and Costello (2005) and Kim and Mueller (1978) provide a straightforward discussion of the differences.

9 We used a variance maximizing (varimax) rotation factor solution, which produces orthogonal (uncorrelated)

extracted factors and identified only factors with eigenvalues exceeding one. We used 0.5 as a criterion for a significant loading, which is more stringent than the 0.30 “rule of thumb,” to cleanly identify unique factors.

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of small firms that will start or continue to offer ESI after the ACA. The simulation was grounded in assumptions from the alignment analysis and used the CHES data to compute the distribution of firms across the following four categories: offered ESI and are eligible for small business tax credit; offered ESI, not eligible; did not offer ESI, eligible; and did not offer ESI, not eligible. The simulated percentage of firms offering ESI after ACA (PCT) was computed as

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where N is the number of firms (using a base of 1,000 firms) in category c, ΔP is the change in ESI price after the ACA, η is the price elasticity associated with offering ESI, and c designates a firm for whom the tax credit might provide an incentive to change its ESI status. We used the Congressional Budget Office’s (Elmendorf, 2009) projected premium decrease of 9.5 percent for price change10 (ΔP) if a firm might receive a tax credit and an increase of 1.5 percent if it does not. We specified several values of elasticity (η) in a sensitivity analysis of our proportion, including -1 (Morrisey, Jensen, & Morlock, 1994), -4 (Feldman et al., 1997), and 0 as a benchmark for an inelastic response (Marquis & Long, 2001; Hadley & Reschovsky, 2002; Helms, Gauthier, & Campion, 1992; Thorpe et al., 1992). We also used two definitions of eligibility for a tax credit as a sensitivity analysis in the proportion of small firms that would receive the credit. We defined the CHES size category of 5 to 19 workers as meeting the size eligibility, akin to the ACA requirement to have fewer than 10 workers to be eligible for the full credit and no more than 25 workers to be eligible for a partial credit, and quantified the annual wage restriction as either (1) being a low-skilled firm or (2) not being a high-skilled firm (that is, having fewer than 50 percent of the workers in high-skilled jobs).

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Research Question 3

The third research question examines disparities and compares the relative changes in benefits compensation between firms with low- and high-skilled workforces. We used the factor-identified strategies developed for research question 1 as dependent variables in multivariate analyses to predict changes in ESI disparities. The multivariate analysis captures the relationship between the strategy a firm (f) adopted when ESI costs increased (HStrat) and workforce skills, while controlling for the firm’s size using the following functional form:11

(2) HStratf = h(sfβ+ xfγ),

where β is two binary measures of workforce skills (low-skilled and high-skilled), and x is two binary measures of firm size (5 to 19 and 20 to 50 workers).12

Our intent in estimating the multivariate model was not to test the determinants of adopting a particular strategy but to establish the correlation between low- and high-skilled firms and responses to rising health care costs. We compared the size and significance (p ≤ 0.05) of the coefficients on workforce skills (β) to assess differences between low- and high-skilled firms in strategies developed to address health care cost increases. If (for example) the estimated coefficient was significant and positive for firms with high-skilled workforces and significant but half the size for firms with low-skilled workforces, we would conclude that the higher costs might have a stronger influence on adopting the strategy in high-skilled than low-skilled firms. We estimated equation (2) with three constructs of HStrat to ensure robustness of results. We used ordinary least squares estimation with the two relatively continuous measures of HStrat (the

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The interest in the estimation lies in how workforce skills are correlated with measures of ESI. The simple correlations from such estimations, without measures of firm characteristics and the like, provide insights into past associations between workforce skills and a dimension of change in ESI, which can be used as a basis for

extrapolating behavior. The associations are not intended to model behavior per se (for example, the net effect of workforce skills on change holding other factors constant.

12 Firms with a majority of mid-skilled jobs or those without a majority of jobs at any skill level are the omitted

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factor score13 from our factor analysis, and the number of actions a firm took in the factor-identified strategy) and a probit estimation with the binary measure (whether the firm took one of the actions in the factor-identified strategy).

RESULTS

In order to speculate about changes in disparities after the ACA, we must first describe the disparities in offers of ESI and other benefits made prior to ACA. Our description highlights the discrepancies between low- and high-skilled firms with respect to the percentage of firms that offered ESI, the characteristics of the offer, and the offer of other benefits (Table 1). The CHES data suggest that, in 2005 and 2006, about 77.6 percent of firms with five or more workers offered ESI,14 with about 67.6 percent of low-skilled firms and 83.8 percent of high-skilled firms making the offer. This difference does not appear to be a result of firm size because the offer rate varied positively with firm size (72 percent of very small firms, 81.7 percent of small firms, and 97.6 percent of large firms offered ESI) and low-skilled firms tend to be large. CHES data also suggest the nature of the offer differed between low- and high-skilled firms and most of the differences suggest a lower quality offer in low-skilled firms. The average copayment for doctor visits was lower ($18.43 vs. $20.13) and the choice in plans was greater (51.0 vs. 36.4 percent offered more than one type of plan) in high-skilled than in low-skilled firms. Receiving an offer appeared to be easier in high-skilled than low-skilled firms that offered ESI: 56.5 percent of high-skilled and 66 percent of low-skilled firms restricted the offer to employees who worked at

13 The factor score measures, in relative terms, the importance of each action in the factor-identified strategy (i.e.,

factor). It is a linear combination of the measured variables (1 = the firm took the action, 0 = not) times a weight derived from the factor loading and measures how much of the strategy the firm took when health care costs rose. Scores are standardized with a mean of zero and about two-thirds of the values lie between +1.0 and -1.0 (and a range of approximately +3.0 to -3.0). A relatively high and positive factor score indicates the firm took most of the actions in the factor-identified strategy.

14 The CHES did not include firms with three or four workers, which increases the estimated percentage of firms

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least 30 hours per week, and 15.8 percent of high-skilled and 26 percent of low-skilled firms made workers wait at least three months before receiving an offer. Finally, offers of other benefits appear to be higher in skilled than low-skilled firms. A greater percentage of high-skilled than low-high-skilled firms offered workers paid vacation, holidays, and sick leave; long-term disability; retiree health insurance; and pensions.

How Might Firms Respond to Continued ESI Cost Increases?

When health care costs increased in the years prior to the 2005 through 2006 CHES survey, 64.5 percent of firms said they adopted one of 16 actions we analyzed from the CHES that directly affected workers (Table 2). We note that only 4.4 percent of firms said they increased product prices without altering wages or employment conditions, an action not

reported in Table 2. The relatively high percentage of firms altering compensation or conditions of employment suggests that these factors might change for many workers if ESI costs continue to increase.

Our factor analysis of these 16 actions identified five strategies that firms adopted in the past when health care costs increased: reducing benefits, reducing employment, increasing the price that a worker pays for ESI, reducing the choice in ESI plans, or restricting access to the ESI offer. Although these five strategies map closely with the three strategies suggested in past research (reducing wages and employment, quality of the ESI offer, or benefits), they represent a more nuanced view of firm behavior. Together, they explain about 56 percent of the variance in the actions firms took when health care costs increased in the past.

The factor analysis suggests that the research-identified strategy of reducing wages or employment has two distinct components: reducing wages and employment and reducing access to the ESI offer. When health care costs rose, about 20 percent of firms took an action that

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directly affected workers’ wages or employment. About 15.9 percent gave fewer raises or reduced wages, about 9.2 percent reduced the size of their workforce, and about 5.6 percent replaced workers eligible for ESI with those who were ineligible. Only about 6.3 percent took an action that reduced workers’ access to ESI. About 4.9 percent increased the minimum hours worked per week needed and about 2.4 increased the months of tenure needed to receive an offer.

The factor analysis also suggests that the research-identified strategy of reducing the quality of ESI has two distinct components: increasing the worker’s price of ESI and reducing the choice of plans. When health care costs rose, about 45 percent of firms took an action that increased the worker’s price for ESI, with about 31.8 percent increasing copayments/coinsurance and about 25 percent increasing the premium workers paid for single and/or family coverage. About 30.5 percent took an action that decreased choice in plans, with about 23.7 percent changing carriers, about 2.4 percent decreasing the variety in the plans offered, and about 7 percent decreasing the number of plans offered.

In addition, the factor analysis confirms the single research-identified strategy of

reducing benefits when health care costs rose. About 13 percent of firms decreased benefits, with about 9.3 percent reducing health care coverage; about 5.8 percent reducing non-health benefits; and fewer than 4 percent (each) reducing dental insurance, vision insurance, or other health-related coverage.

Taken as a whole, the analysis suggests that continued health care cost increases might lower the quality of the ESI offer for a relatively large number of workers. More than half the firms increased the cost workers pay for health care and reduced their choice in plans. Wage compensation and employment might also be affected, although only about half as many firms

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adopted this strategy. Somewhat fewer firms decreased benefits, and relatively few reduced access to benefits.

To What Extent Might the Percentage of Small Firms That Offer ESI Change With the ACA?

The ACA’s ability to increase the number of small firms that offer ESI will depend on how well its incentives align with the reasons small firms do not offer ESI. If, for example, small firms say they did not offer ESI because of its cost, the ACA’s tax credits might stimulate offer rates if the tax credit is large enough to elicit a response. The CHES data afford an opportunity to examine both alignment and potential responsiveness.

When CHES asked firms why they did not offer ESI, most small firms identified

financial reasons and worker preferences (Table 3). About 78.5 percent said the premiums were too high, 67.3 percent said their business could not afford ESI, and 48 percent said revenue was too uncertain to commit to a plan. Tax incentives might ease these financial burdens, albeit for a limited time period.

Firms’ reasons for not offering ESI also suggest that they do not necessarily believe workers want ESI as compensation. About 52.2 percent said their workers could not afford ESI, 42.3 percent said their workers preferred wages or other benefits to ESI, 42.8 percent said they can recruit and retain good workers without offering ESI, and 20.2 percent said their workers were healthy and did not need health care coverage. It is possible that provisions in the ACA might alter preferences. The individual mandate to have essential health benefits might increase workers’ demand for ESI, although the presence of lower cost alternatives such as expanded

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Medicaid coverage and premium credits in the exchanges might decrease demand, especially among low-wage workers.15

The CHES data allow us to assess the potential of the small business tax credit to change the percentage of small firms that offer ESI. We simulate this potential under the assumption of a premium decrease (9.5 percent) with a tax credit and a premium increase (1.5 percent) without it (Elmendorf, 2009). The simulation suggests that the change in the percentage of small firms offering ESI might be small (Figure 1). If we define low-skilled firms with 5 to 19 workers as being eligible for a tax credit, about 82.9 percent of small firms that offered ESI are not eligible and will face the predicted 1.5 percent premium increase. These firms might change or

discontinue their ESI offer. We estimate that 37.7 percent of the small firms that did not offer ESI might receive a tax credit and face a 9.5 percent premium decrease. If these firms exhibit an elasticity of -4 when responding to ESI price changes, our simulation (equation 1) shows that the percentage of small firms offering ESI would increase from 71.9 to 72.3 percent (Table 4).16 Research suggests that -4 might be an overstated response. The more typical response of -1 would elicit virtually no increase (from 71.9 to 72.0). If we expand the definition of eligibility for the tax credit to include all firms that are not high-skilled and use the -1 elasticity, the increase is still only from 71.9 to 73.5 percent.

What Changes in the Pre-ACA Disparities Between Low- and High-Wage Workers Might Occur with Firms’ Response to Continued ESI Cost Increases and ACA Tax Incentives?

Our analysis thus far suggests that changes in the ESI disparities between low- and high-wage workers might be determined by responses to changes in costs and not by changes in the

15 About one-quarter of firms said that setting up a plan was too time consuming or complicated, which the

exchanges were structured to address. More than 30 percent mentioned worker instability as a reason for not offering ESI, although the ACA did not address this incentive for not offering ESI.

16 The percentage would be understated if worker demand for ESI increased or if the concerns of 25 percent of small

firms that setting up a plan is too complicated and time consuming (Table 3) were not mitigated by the exchanges. The percentage would be overstated if worker demand for ESI falls (see footnote 1).

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percentage of small firms that offer ESI. We therefore used the estimated relationship (equation 2) between workforce skills and response to increased costs (Table 5) to assess how the pre-reform disparities in the ESI offer (Table 1) might change.

Our analysis suggests that the ESI offered to low-wage and high-wage workers might converge but the offer of other benefits might diverge given the strategies firms might adopt if health care costs continue to increase after the ACA. Results are robust to different measures of strategies in responding to increased health care costs. Convergence in the offer is suggested by multivariate estimation results (Table 5) showing that low-skilled firms were less likely to adopt a strategy of increasing the worker’s price of ESI than other firms, with the marginal effect placing them at about 9.7 percent less likely to increase price than other firms. Because low-skilled firms had a lower quality coverage than high-low-skilled firms initially (Table 1), their reluctance to raise its price as compared to other firms will keep quality constant in low-skilled firms but lower it in other firms because the price increases for workers in other firms narrow the differences in the offers. Estimations also suggest that high-skilled firms were 9.3 percent more likely than were other firms to adopt a strategy that would reduce the choice of ESI plans with increasing costs. Because high-skilled firms initially offered greater choice than did low-skilled firms, their actions would narrow the disparities between them in the choice of ESI plans if health care costs increase. Multivariate estimations suggest divergence in the offer of other benefits because high-skilled firms were about 10.2 percent less likely than were other firms to decrease benefits when health care costs increase (Table 5). Because a greater percentage of high-skilled firms offered benefits and were less likely to change them when health care costs increased, increases in ESI costs would increase the initial differences in benefits offered as low-skilled firms cut them.

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SUMMARY AND DISCUSSION

The ACA is likely to change the landscape for firms in offering health care coverage. Large firms will be required to offer coverage to employees who work at least 30 hours per week and have three months’ tenure or potentially face financial penalties. Some small firms will receive tax credits to offset premium costs, and all small firms will be able to participate in the SHOP exchanges that are structured to emulate the economies of scale and risk pooling available in the large-group market. Worker demand for ESI might increase because most individuals will face penalties if they do not have essential health care coverage, or it might decrease among some low-wage workers because they have the opportunity to enroll in an expanded Medicaid program or receive premium subsidies in the exchanges. Most employers believe that their health care costs will increase (Mercer, 2012).

This study used the CHES data to compare the ESI offer made by firms with a majority of low-skilled and a majority of high-skilled workers to predict how the differences might change with the ACA. It examined how firms that offered ESI responded to cost increases in the past, how small firms might respond to the ACA tax incentives to offer ESI, and how the

disparities in ESI offers between low-skilled and high-skilled firms might change with strategies adopted to offset ESI cost increases. Its key assumption is that the cost containment provisions of the legislation do not slow the growth of ESI costs.

The research highlights the disparities in the offer of ESI and other benefits between offers made by low-skilled and high-skilled firms. In 2005 and 2006, low-skilled firms were less likely to offer workers ESI or other benefits and more likely to make a lower quality ESI offer if an offer was made. Our analysis suggests that the percentage of small firms offering ESI might change little after the ACA as the number of small firms that might use the tax credits to offer

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ESI might be offset by the number that might drop coverage if premiums continue to increase. If true, the strategies firms might adopt if ESI premiums increase will be the driver of changes in disparities.

Our research highlights the potential of continued ESI premium increases to cause the nature of the ESI offer to low- and high-skilled workers to converge and to enlarge the disparity in the offer of other benefits. The quality of ESI offered might converge as high-skilled firms remove some of the choice in the plans offered to workers and low-skilled firms do not increase the already high price that their workers pay for ESI when health care costs increase. Because quality was lower in low-skilled than in high-skilled firms in 2005 and 2006, these changes would reduce ESI quality differences in the offer and, as a result, converge the nature of the ESI offered to low- and high-wage workers. The convergence in the ESI offer would presumably be reinforced by the ACA requirements that regulate and standardize services contained in health care plans to decrease discrepancies in the quality of ESI offered to low-wage versus high-wage workers, although examining plan differences lies beyond the scope of this research. The offer of other benefits might diverge because high-skilled firms were less likely than other firms to decrease benefits when health care costs increased. Because a greater percentage of high-skilled than low-skilled firms offered workers benefits in 2005 and 2006, differences between low- and high-skilled firms in benefits offered would increase with increased ESI costs.

Of course, using past behavior to predict future change is risky, especially when the environment surrounding the changes is in flux. In that sense, our study’s greatest contribution might lie in its ability to highlight the manner in which the ACA might affect a worker’s

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for the nonelderly population, policymakers might take notice of the potential for changes that affect the level and disparities for workers in all aspects of non-wage compensation.

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Figure 1. Simulation of the Probability Small Firms Will Offer ESI After ACA

Notes: Distributions are based on firms being eligible for a tax credit if they are low-skilled and have 5 to 19 employees. The simulation presented in the figure uses a -4 elasticity. See Table 4 for results of the simulation using different elasticities.

Original Change Simulated

Pre-Reform Distribution Premium Behavior Distribution Offer

Decision ACA 1000 Firms Change Change 1000 Firms Percentage

Tax Credit 123 -9.5 no change 0

Offer 72.3%

71.9% No Tax Credit 596 1.5 fewer offer 36

ESI Offer

Tax Credit 106 -9.5 some offer -40

Not Offer 27.7%

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Table 1. Pre-Reform Behaviors Total Low-Skilled High-Skilled Characteristics Size

Percentage of very small firms (5 to 19 employees) 65.2 55.7 70.5

Percentage of small firms (20 to 50 employees) 20.8 25.8 17.7

Percentage of large firms (at least 51 employees) 13.8 18.5 11.8

Workforce

Percentage of temporary or part-time workers 13.2 17.9 10.2

ESI offer Offer

Percentage of firms that offer ESI 77.6 67.6 83.8

Percentage of firms that are very small and offer ESI 72.0 53.8 78.5

Percentage of firms that are small and offer ESI 81.7 76.1 95.3

Percentage of firms that are large and offer ESI 97.6 97.3 97.3

Percentage of firms that require more than 30 hours to receive benefits 57.1 66.0 56.5 Percentage of firms that require more than 3 months to receive benefits 18.5 26.0 15.8 Quality

Monthly payment for workers for single coverage $374 $396 $407

Average copayment for doctor visit $20.62 $20.13 $18.43

Average percentage payment for coinsurance for doctor visit 12.9 * *

Average copayment for prescription (generic) $13.33 $12.76 $13.69

Average percentage payment for coinsurance for prescription (generic) 14.4 * *

Percentage of firms that offered more than one plan 49.9 44.3 57.9

Percentage of firms that offered more than one type of plan 42.4 36.4 51.0 Benefits Other than Health Insurance

Percentage of firms that offered paid vacation 94.7 90.0 96.2

Percentage of firms that offered paid holidays 92.5 90.0 94.8

Percentage of firms that offered paid sick leave 79.0 71.3 86.9

Percentage of firms that offered dental insurance 65.4 71.1 70.9

Percentage of firms that offered life insurance 42.1 45.0 43.2

Percentage of firms that offered long-term disability (wage replacement) 35.2 32.0 41.3

Percentage of firms that offered vision insurance 36.9 45.0 39.2

Percentage of firms that offered long-term health care 9.9 14.0 13.1

Percentage of firms that offered retiree health 6.9 6.3 7.4

Percentage of firms that offered pensions 64.6 63.7 72.9

N (unweighted) 1245 361 347

Source: CHES (Maxwell 2007). Observations have been weighted such that the distribution of sample firms reflects the proportion of firms in the United States with respect to size and industry.

Notes: Table includes only firms that offered health insurance. Item-specific nonresponse reduced the Ns greatly in the copaymentvariables. A * indicates the cell contains fewer than 20 firms (other cells have at least 35 firms). The percentage of temporary or part-time workers is computed by converting the categorical responses into midpoint percentages and summing across positions the percentage at each skill level times the proportion of workers that work at that skill level. Boldface indicates

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Table 2. Firms’ Response to Rising Health Care Costs Prior to the ACA Percentage reporting Factor Loadings Com-munality Benefits Work-force Worker

price of ESI Choice

Access to benefits

Percentage taking one of the actions below 64.5

Wages and employment

Workforce 20.3

Give fewer raises or reduce wages 15.9 0.045 0.786 0.061 0.102 0.060 0.638

Reduce workforce 9.2 -0.016 0.709 0.026 0.040 0.045 0.507

Increase workers not eligible for benefits 5.6 0.165 0.683 0.211 -0.027 0.178 0.571

Access to benefits 6.3

Increase hours to receive health benefits 4.9 0.039 0.094 0.058 -0.028 0.757 0.588 Increase months to receive benefits 2.4 0.149 0.106 0.039 0.067 0.746 0.596

Quality of ESI offer

Worker price of ESI 45.1

Increase worker payment family coverage 24.2 0.063 0.105 0.855 0.004 0.060 0.749 Increase worker payment single coverage 25.0 0.064 0.013 0.845 0.153 0.121 0.756 Increase copayment or coinsurance 31.8 0.133 0.279 0.534 0.208 -0.072 0.429

Choice 30.5

Change health insurance carriers 23.7 -0.038 -0.052 0.251 0.612 0.005 0.442 Decrease variety of health plans offered 12.4 0.250 0.183 0.041 0.746 -0.036 0.656 Decrease number of health plans offered 7.0 0.181 0.055 0.020 0.775 0.091 0.646

Benefits 13.4

Decrease health insurance coverage 9.3 0.595 0.400 0.175 0.197 -0.108 0.595 Decrease non-health benefits 5.8 0.668 0.150 0.096 0.194 0.026 0.516

Decrease dental insurance 3.6 0.794 0.017 0.039 0.019 0.129 0.650

Decrease vision insurance 3.3 0.812 -0.040 0.034 0.028 0.004 0.664

Decrease other health-related coverage 2.0 0.582 -0.005 0.030 0.139 0.330 0.468

Variance explained by each factor 2.605 1.921 1.891 1.713 1.338 8.874 Percentage variance explained by each factor 16.3 12.0 11.8 10.7 8.4 55.5

N (unweighted) 1223 1104

Source: CHES (Maxwell 2007). Observations have been weighted such that the distribution of sample firms reflects the proportion of firms in the United States with respect to size and industry.

Notes: Firms offering health insurance were asked: (In the past 3 to 5 years) “In response to rising health care costs did your firm….” Numbers in the Percentage Reporting column represent the percentage of firms that said they took an action. Numbers in the Factor Loadings columns show the factor score vectors from a varimax rotated factor analysis. Numbers in the Communality column show the amount of variance an original variable shares with the other variables. The Variance explained by each factor row shows the amount of variance explained by the factor, with the number in the communality column showing the total variance explained by the factor analysis. The Percentage variance explained by each factor shows the percentage of the total variance explained by each factor with the number in the communality column showing the percentage of variance explained by all factors. Boldface indicates a factor score that is greater than 0.5.

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Table 3. Reasons Small Firms Did Not Offer ESI Prior to the ACA Total Workforce Skills Low-skilled High-skilled Price of ESI

Premiums too high 78.5 86.8 61.2

Firm’s scale (revenue)

Business cannot afford it 67.4 81.8 45.7

Firm too small or new 58.6 52.9 59.6

Revenue too uncertain to commit to a plan 48.0 66.6 32.7

Worker preferences

Workers cannot afford it 52.2 56.4 25.5

Don’t need ESI for good workers 42.8 41.7 37.0

Workers prefer wages or other benefits 42.3 49.9 40.7

Workers are healthy and do not need it 20.2 28.7 18.9

Worker instability

Workers are temporary, part-time 34.6 44.2 18.9

Worker turnover too high 31.5 37.2 9.8

Set up costs

Plan set-up too complicated and time consuming 24.9 26.5 16.0

N (unweighted) 160 60 39

Source: CHES (Maxwell 2007). Observations have been weighted such that the distribution of sample firms reflects the proportion of firms in the United States with respect to size and industry.

Notes: Firms NOT offering health insurance were asked to use a scale from 1 to 5 (5 being very important) to rate how important each item was in their decision not to offer it. Numbers represent the percentage of firms that gave a 4 or 5 rating to the item. Boldface indicates a p ≤ 0.05 significant difference and italics indicates a p ≤ 0.10 significant difference between low- and high-skilled as determined by a t-test.

Table 4. Simulated Percentages of Firms Offering ESI: Varying Elasticities and Eligibility Price Elasticity

Definition of Eligibility for Tax Credit 0 -1 -4

Low-skilled firms 71.9 72.0 72.3

Not high-skilled firms 71.9 73.5 78.5

Source: CHES (Maxwell 2007). Observations have been weighted such that the distribution of sample firms reflects the proportion of firms in the United States with respect to size and industry.

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Table 5. Workforce Skills and Response to Rising Health Care Costs Marginal Effect of Low-skilled High-skilled 5–19 workers 20–50 workers N Wages and employment

Workforce

Binary defined change (marginal effect) -0.032 0.008 0.055 0.118 1194 Number actions defined change (standardized coefficient) -0.060 -0.019 0.049 0.185 1194 Factor defined change (standardized coefficient) -0.101 -0.042 0.098 0.193 1102 Access to benefits

Binary defined change (marginal effect) 0.011 -0.020 -0.021 0.210 1214 Number actions defined change (standardized coefficient) 0.002 -0.051 -0.029 0.033 1214 Factor defined change (standardized coefficient) 0.025 -0.020 -0.023 0.007 1102 Quality of ESI offer

Worker price of ESI

Binary defined change (marginal effect) -0.097 -0.009 -0.262 -0.094 1162 Number actions defined change (standardized coefficient) -0.080 -0.068 -0.278 -0.054 1162 Factor defined change (standardized coefficient) -0.039 -0.032 -0.322 -0.100 1102 Choice

Binary defined change (marginal effect) -0.014 0.093 -0.042 0.029 1202 Number actions defined change (standardized coefficient) -0.030 0.064 -0.027 0.000 1202 Factor defined change (standardized coefficient) -0.028 0.045 0.037 -0.015 1102 Benefits

Binary defined change (marginal effect) -0.042 -0.102 0.018 0.054 1192 Number actions defined change (standardized coefficient) -0.048 -0.114 0.024 0.074 1192 Factor defined change (standardized coefficient) -0.034 -0.106 0.032 0.071 1102

Source: CHES (Maxwell 2007). Observations have been weighted such that the distribution of sample firms reflects the proportion of firms in the United States with respect to size and industry.

Notes: Questions were only asked of firms that offered health insurance. See Table 2 for a listing of the actions in each response. Coefficients and marginal effects were estimated using the specification presented in equation (2).

Boldface indicates a coefficient that is significantly different from zero at p ≤ 0.05 and italics indicates a statistical difference at p ≤ 0.10.

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For more information, contact Nan Maxwell, senior researcher, at nmaxwell@mathematica-mpr.com.

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Figure

Figure 1. Simulation of the Probability Small Firms Will Offer ESI After ACA
Table 1. Pre-Reform Behaviors  Total   Low-Skilled   High-Skilled  Characteristics  Size
Table 2. Firms’ Response to Rising Health Care Costs Prior to the ACA  Percentage  reporting  Factor Loadings   Com-munality
Table 3. Reasons Small Firms Did Not Offer ESI Prior to the ACA  Total   Workforce Skills Low-skilled High-skilled  Price of ESI
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