Work-Family Benefits: Which Ones Maximize Profits? [*].(Brief Article)

Despite the growing attention given to work-family programs in the popular media (e.g., Hammonds, 1996; Lawlor, 1996; Moskowitz and Townsend, 1995), few studies have attempted to measure their financial impact on the firms which provide such benefits (see Lobel and Faught (1996) for difficulties in quantifying the effects of specific programs). This study attempts to fill the gap by determining which work-family programs have a significant effect on the profitability of the firm and measuring the magnitude of that impact. In the process, we are able to pinpoint particular benefits that our sample firms may, from the point of view of maximizing profits, be over-providing or under-providing [1] relative to their optimal level. While we follow standard economic practice and focus on profit-maximization, we are aware that for many firms, profits are not the sole motivating factor as, increasingly, organizations are becoming sensitive to the pressures facing employees endeavoring to balance family and job respons ibilities.

One source of pressure on firms to introduce work-family programs came from the changing needs of a work force increasingly comprised of women with families (Hammonds, 1996). The increased participation of women in the labor force occurred not only for all women (56% in 1996 versus 51% in 1980), but was especially dramatic (a jump from 45% in 1980 to 63% in 1996) for married women with children under the age of six (U.S. Department of Commerce, 1998). Consequently, there was a substantial rise in the number of dual-earner families. For instance, in 1996, in over half of the 53 million married couples both husband and wife worked outside the home. These dual-earner families significantly outnumbered the 10.1 million "traditional" married couple families in which the husband worked for pay and the wife did not (Bureau of Labor Statistics and Bureau of the Census, 1997). These trends contribute to the fact that currently only 16 percent of full-time workers go home to a non-employed spouse (Barker, 1995). The s tress of having another full-time job waiting at home after a full day at the office has both professional and personal effects (Johnson, 1995). These stresses are likely to lower the effectiveness of workers, as indicated by numerous studies (Auerbach, 1988; Axel, 1996; Bailyn, 1993; Ferber and O'Farrell, 1991; Gonyea and Googins, 1992; Magid, 1983; Zigler and Frank, 1988).

With the changing demographics of their work force, many companies began to revamp their work-family programs. Anecdotal evidence suggests that this was done in part to accommodate the needs of a work force increasingly comprised of women with families (Hammonds, 1996). For instance, the rise of dual income families made certain traditional benefits, such as family medical care, redundant. Whereas in 1993, 82 percent of full-time employees in medium and large private establishments were covered by the firms' medical care plans, by 1997 that figure dropped to 77 percent (Bureau of Labor Statistics, 1997a). Concurrently, other new benefits became increasingly relevant for employees such as the ability to take a day off to care for a sick child, a flexible schedule to attend a parent-teacher conference, extended family leave to accommodate long-term family illnesses, child-care subsidies, and onsite daycare. The net effect is that total benefits have mushroomed into a major expense for firms, comprising around 28 percent of the total cost of compensation (Bureau of Labor Statistics, 1997b).

Has the expansion of programs helped worker productivity? To date, studies about work-family programs and productivity have either relied on anecdotal evidence to examine a range of programs or have used statistical analysis to look at only one specific type of work-family program. Focusing first on studies in the former category, surveys indicate that many employers have been experimenting with new or enhanced work-family benefits to increase worker productivity by reducing absenteeism and turnover (Hammonds, 1996). Numerous studies use anecdotal evidence gathered through interviews with managers, workers and CEOs to support the claim that the implementation of work-family programs radically improves productivity (Barker, 1995; Capowski, 1996; Galinsky et al., 1991; Hammonds, 1996; Johnson, 1995; Lawlor, 1996; Osterman, 1995; Soloman, 1994). Other studies use nation-wide, multi-firm surveys to confirm the belief of managers that such programs lead to improved recruitment, morale, public image, absenteeism a nd turnover (Burud et al., 1984; Magid, 1983; Perry, 1982). In addition, there are case studies of particular firms that have implemented such programs; these bring out the disparity between the managers' and the workers' estimates of the effect on productivity (Friedman, 1991). Consistently, the workers' estimate of the effect is greater than that of managers. Furthermore, these case studies point to significant variation in the success of these programs across firms, which suggests that the corporate culture and the structure of the work have a substantial impact on how successful these programs are. For example, the proportion of managers who perceived an increase in productivity from a subsidized onsite child-care center ranged from 32% to 72% depending on the study, while the proportion of employees who perceived such an increase ranged from 47% to 73%.

In contrast to studies relying on anecdotal evidence, Shepard et al. (1996) use statistics to analyze productivity. Their study, however, focuses on the pharmaceutical industry and only considers the effect of one particular benefit flex-time. Using a random effects model, they conclude that the effect of flex-time on productivity was positive and both statistically and economically significant.

Our study departs from earlier work in both scope and methodology. What makes our study unique is that we apply statistical analysis to a broad range of work-family programs across many firms and industries. This enables us to draw policy conclusions based on a careful study of actual data rather than on casual empiricism.

The remainder of this article is as follows. The empirical model which underlies our statistical analysis is developed in the next section. Thereafter, we discuss the data used in the study and present selected descriptive statistics. Our empirical results which follow indicate that programs vary significantly with regard to their impact on firm profitability. Finally, we conclude, give policy recommendations, acknowledge limitations of the study, and suggest avenues for further research.

Empirical Model of Firm Profitability and Work-Family Programs

An important determinant of a firm's profit function is compensation to its employees. In this section we build a simple model of a profit function which seeks to answer the question, "Which work-family programs affect the profitability of the firm and what is the magnitude and direction of this effect?" The theoretical underpinning of our model is the efficiency compensation theory whereby employers pay above-market compensation -- be it in terms of wages, benefits or both -- to increase worker productivity. This productivity boost can come from several sources: by the higher quality of workers that are attracted, by an improvement in efficiency of existing workers, and by a reduction in employee turnover. Workers who are being paid above-market compensation are assumed to be less likely to quit, feel more committed to the firm, and be more industrious. To the extent that this is the case, the firm can also invest more in training and push workers harder, perhaps by asking for longer hours. The combined eff ect will allow the firm to increase profits (Yellen, 1991)

Though the efficiency wage theory implies that higher compensation leads to increased profits through a productivity stimulus, the theory is too general to be used by firms as a practical guideline. To a firm struggling with problems of budget allocation, specific information identifying those benefits yielding highest returns and determining their optimal level is crucial. We seek to provide this information by focusing on a selected subset of benefits.

Assuming that a firm's goal is to maximize profits, the profit function may be expressed as follows:

[pi] = R (p, q) - C (c) (1)

where [pi] is the profit function, R and C are the total revenue and total cost functions, respectively, p is the product price, q is a vector of all factors affecting output (including capital, labor, productivity and demand factors), and c is a vector of factors affecting costs (including wages and benefits).

According to the theory of efficiency compensation, there will be both direct

and indirect effects of benefits on a firm's profits. Higher benefits directly increase a firm's costs. Indirect effects stem from two separate mechanisms as described in the efficiency compensation literature (e.g., Campbell, 1993, Cappelli and Chauvin, 1991). First, productivity goes up, ceteris paribus, as better workers are attracted and existing workers are induced to reduce shirking. Second, turnover costs decrease as relatively higher compensation tends to inhibit potential quitters.

The profit-maximizing firm will choose the level of each work-family benefit it provides by equating the marginal revenue of that benefit with its marginal cost. In other words, the firm will continue to raise the level of the work-family benefit as long as the increased revenue exceeds the additional cost. Assuming that the marginal effect of an increase in a work-family benefit on productivity is positive but diminishing and that the marginal cost does not decrease, the firm can fall into one of three categories, as shown in Figure I. First, a firm can offer exactly the optimal amount of the work-family benefit, in which case the marginal impact on profit of an increase in the benefit is neutral. Second, it could be under-providing the benefit, in which case we should see a positive marginal effect of that benefit on profits. Lastly, it could be over-providing the benefit, in which case we expect to see a negative marginal effect on profits. Thus, the signs of the coefficients in our model are important in interpreting the results of our model, since they provide an indicator of whether each benefit is over- or under-provided in our sample of firms, at least from the point of view of maximizing profits.

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