Value to Employers
Personal Financial Wellness May be the Missing Factor in Understanding and Reducing Worker Absenteeism, Personal Finances and Employee Productivity, 1998, Joo & Garman

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The determinants of absenteeism and efficient methods of reducing absenteeism are some of the greatest concerns of employers. This paper examines the relationship between personal financial wellness and absenteeism from the sample of 278 white-collar clerical workers in a mid-eastern state. Financial stressors and personal financial wellness are some of the important factors that explain variance in absenteeism. Based on the relationship, the potential effects of financial education on reducing absenteeism are discussed. Extrapolating the findings to clerical workers throughout the United States show a potential annual net savings from reduced absenteeism through financial behavioral changes by effective workplace financial education of $440 million.

The determinants of absenteeism and efficient methods of reducing absenteeism are of concern to employers. "Employee departures often have veiled effects on a company's top and bottom lines, such as decreases in customer satisfaction, worker morale, and overall company productivity" (Caggiano, 1998). These costs are in addition to the burden on management's time.

Some of the identified determinants of absenteeism are employee satisfaction, employee participation in management systems (e.g., profit-sharing ownership schemes), health status, family factors (e.g., being a mother with small children), job performance, age, organizational tenure, perceptions of interactional justice, and worker perception of the absence norm. Studies also show one of the most significant reasons for absenteeism is stress.

A primary source of stress is personal financial problems (Garman, Leech & Grable, 1996). However, when researchers study the numerous potential determinants of absenteeism, they generally fail to include personal financial problems as one of the independent variables. This is in spite of the fact that personal financial difficulties are one of the greatest personal concerns of workers and that research has demonstrated that these difficulties influence worker productivity, and in particular absenteeism (Garman, Leech, & Grable, 1996; Joo, 1998; Joo & Garman, 1998). Therefore, identifying the relationship between financial wellness and absenteeism can help employers better understand the determinants of employee absenteeism.

Since personal financial wellness is related to job productivity, improving workers' personal financial wellness could be an effective way of reducing absenteeism. Improving the workers' financial wellness could be accomplished relatively efficiently through workplace financial education (Kratzer, Brunson, Garman, Kim, & Joo 1998). In essence, employers can develop financial information and education programs that would result in reducing workers' avoidable absenteeism.

Recent research estimates the potential effects of financial education on productivity (Joo, 1998; Joo & Garman, 1998). According to Joo, if workplace financial education is successful-in that it improves some workers' personal financial wellness-employers could save more than $400 per worker for the first year through improvements in job productivity.

The present research extends those findings. The purpose of this study was to investigate the determinants of absenteeism in a sample of clerical workers, examine the potential effects of financial education on productivity, and estimate the potential monetary value of financial education on reducing absenteeism among clerical workers in the United States.

Related Literature

The following examines the literature on absenteeism, financial wellness, and workplace financial education.

Absenteeism

Research on absenteeism has been conducted in such areas as psychology, human resources, economics, law, and medicine. Research topics include the determinants of absenteeism, causal model development, and relationships among job performance, employee participant policy, job satisfaction, and absenteeism. Factors that have been found to influence absenteeism include demographic characteristics of workers, job satisfaction, stress, job performance, employment environment, job characteristics, commitment to employer, absence norm, and managerial strategies of employers.

Demographic characteristics, such as age, health status, and being a mother with young children, of employees also influence absenteeism. Leigh (1991) found statistically significant predictors of absenteeism using a national sample. In the model, Leigh included four categories of independent variables: demographic variables, health variables, aspects of the job, and economic incentives. The significant determinants included health variables (e.g., being overweight, complaining of insomnia, and hazardous working conditions), job characteristics (e.g., inflexible hours), and personal variables (e.g., being a mother with small children). Among the significant variables, dangerous working conditions had the strongest relationship with absenteeism. In another study, Rogers and Herting (1993) found a negative relationship between education and absenteeism, demonstrating that those who had less education had more absences than those with a higher level of education. They also found no significant relationship between employee tenure and absenteeism.

Absenteeism is also affected by employee satisfaction. Mowday, Porter, & Steers (1982) found a negative relationship between satisfaction with pay and absenteeism, suggesting that those workers earning lower incomes had more absences than people making higher incomes. Job performance is related to absenteeism, too (Bycio, 1992), as workers with low performance ratings from their supervisors tend to have more absences than other workers. Bycio also found that absenteeism is more likely to follow poor job performance than the reverse situation.

Gellatly (1995) used a sample of 166 nursing and food services employees in a mid-sized hospital to examine whether an employee's level of absenteeism was affected by age, organizational tenure, perceptions of interactional justice, commitment, and the perceived absence norm in the employees' work unit. Gellatly found that age was inversely related to absenteeism, meaning older employees tended to be absent more from work than younger workers. The employees' perception of the absence norm in a work unit has a lagged impact on absenteeism, suggesting that after working in a unit for one year the worker's absenteeism began to reflect the average of other workers.

There also is a strong relationship between job stress and absenteeism. Tang and Hammontree (1992) argued that, "it has been suggested in the literature that over 70% of all job absenteeism has been tied to stress-related illness"(p.493). And their research found a significant relationship between stress and absenteeism.

Absenteeism is further affected by employee participation in the managerial system. Utilizing a linear regression equation using data on 52 engineering and metalworking firms in United Kingdom, Wilson and Peel (1991) found that worker participation schemes had a significant influence on absenteeism. Firms with profit sharing or share ownership schemes had significantly lower absenteeism and quit rates than other firms.

Poor Financial Behaviors

It has been estimated that15% of workers are experiencing stress from their poor financial behaviors to the extent that it reduces their job productivity (Garman & Leech, 1996; Garman, et al., 1996). Poor personal financial behaviors range from regularly spending too much money, writing bad checks, exceeding limits on credit cards, and failing to pay bills to receiving communications from collection agencies to having property repossessed and filing for bankruptcy. At some job sites, the percentage of workers with substantial moneyproblems is much higher, even as high as 40 or 50% (Kratzer et al, 1998; Garman, 1998).

Financial Wellness

Joo (1998) conceptualized financial wellness as "a level of financial health. It includes satisfaction with material and non-material aspects of one's financial situation, perception (or subjective assessment) of financial stability including adequacy of financial resources, and the objective amount of material and non-material financial resources that each individual possesses" (p. 12). Financial wellness can be measured in several ways, including financial behavior scales, perceptions of personal finance, overall satisfaction with financial situation, and objective measures.

The level of one's personal financial wellness is influenced by age, gender, income, marital status, education, ethnicity, financial stressors, employment status, number of financial dependents, and housing tenure (Foster, 1993; Joo, 1998; Livingstone & Lunt, 1992; Mookherjee, 1997; O'Neill, 1995; Porter, 1990; Ross & Huber, 1985). Household income and housing tenure also have positive impacts on personal financial wellness (Foster, 1993; Joo, 1998; Ross & Huber, 1985). Those who have higher household incomes and are homeowners tend to demonstrate a higher level of financial wellness than others (Joo, 1998). The number of financial dependents has negative relationship with financial wellness, as the presence of young children affects financial wellness negatively (Ross & Huber, 1985). The number of financially stressful events experienced by an individual in the past year also affects one's financial wellness (Joo, 1998).

Financial Education

Financial education is believed by many to be the number one solution for poor personal financial behaviors. Wagner (1982) observed that helping workers with problems can bring "incredible success in improving productivity and reducing cost" (p.59). Employer sponsored financial education influences household financial behavior, especially on retirement savings (Bernheim and Garrett, 1996). Bernheim and Garrett found a strong influence of workplace financial education on the amount of one's retirement savings. Workers who participated in a workplace retirement education program saved significantly more toward retirement education than those who did not participate. Companies have experienced an increase of 52% in retirement contributions from workers after conducting workplace financial education (Gorbach, 1997). Besides the increase in retirement savings, workers also to actions and successfully achieved a more appropriate asset allocation because of workplace financial education (DiPaula, 1998; Kratzer, et al, 1998). People also report that they want to obtain financial information at their place of employment (Bernheim & Garrett, 1996; Gorbach, 1997; Kim, Bagwell, & Garman, 1998; Kratzer et al, 1998).

Financial wellness is closely related to financial stress (Joo, 1998; Joo & Garman, 1998). Since stress is one of the most significant factors affecting absenteeism, the potential effects of financial wellness on absenteeism could be huge. However, research on absenteeism generally has not investigated the relationship between financial wellness and absenteeism. This implies that the personal financial wellness could be the significant factor that has been missing in understanding absenteeism.

Methodology

A survey research design was undertaken to investigate the determinants of absenteeism, examine the potential effects of financial education on productivity, and estimate the potential monetary value of financial education on reducing absenteeism among clerical workers in the United States. A questionnaire was developed and pre-tested. The instrument inquired about personal financial wellness, absenteeism, financial stressors, and demographic characteristics. A mail survey (N=474) of white collar clerical workers of a large employer in a mid-eastern state was conducted during the spring of 1998. From a random sample of 447 (27 out of the original 474 were undeliverable), 295 questionnaires were returned (65.9%). Seventeen questionnaires were determined unusable resulting in a 62.3% usable return rate (278/447).

Characteristics of the Sample

The majority of the respondents were female (96.4%). The mean age was 43 years old. The largest group (35.8%) were in their 40s, about one-fourth (24.2%) were in their 30s, and more then two-tenths (23.2%) were in their 50s. About one-tenth (11.6%) were in their 20s, and 5.2% were in their 60s. About threequarters (74.7%) had formal education beyond high school (trade, vocational training, associates', some college, bachelors, and graduate).

Almost half (49.3%) had annual household income of less than $50,000. About three-tenths (29.2%) had an annual household income between $50,000 to $80,000, and 5% reported more than $80,000. About two-thirds (64.9%) were married. Over 90% were white, while African American made up most of the remainder (9.7%). The mean age of the 288 respondents and the population of 948 was almost same. The distributions of the length of employment of the respondents and the population were similar. The population had average 11.22 years of employment with the current employer.

As shown in Table 1, compared to national data available on clerical workers, the gender distribution of the respondents was similar to those who hold same job titles. The ethnicity distribution of the respondents was also similar to national data. However, in terms of the education level, the respondents, as a group, were slightly more educated than the general population. Moreover, the three general demographic characteristics shown in Table 1 suggest that the sample may be fairly representative of the broader population of clerical workers.

Analysis

Correlation and regression analysis were used to examine the relationships among personal financial wellness, demographic characteristics, and absenteeism. Demographic characteristics included age, gender, marital status, education, income, housing tenure, number of financial dependents, and length of employment with current employer. Personal financial wellness was measured with four scales: perception of personal financial wellness, behavioral assessment of personal finance, overall satisfaction with personal financial situation, and objective measures. Objective measures included a solvency measure, amount of reserve funds, monthly credit payments, monthly installment loan payments, monthly savings, and monthly supplementary voluntary tax-sheltered retirement contributions. The following regression equation was utilized.

Absenteeism = a + bi Di + b PFW

where, Di = Demographic characteristics which showed significant correlation with absenteeism

PFW = Personal Financial Wellness Measures

Since there were nine measures of personal financial wellness, nine different regression equations were calculated. Among the nine measures of personal financial wellness, only those measures that showed significant correlations with absenteeism were entered into the regression analysis.

Determinants of Absenteeism

As shown in Table 2, among the several demographic characteristics of the respondents and absenteeism, only the factors of financial stressors and absenteeism were significantly correlated. Workers who experienced more financially stressful events in the past year were absent from work more often than the others. No other demographic characteristics-age, gender, number of financial dependents, education, income, housing tenure, and length of employment-were found to be significantly correlated with absenteeism.

As shown in Table 3, the personal financial wellness level of workers also affected absenteeism. Perception with personal finance, behavioral assessment of personal finance, solvency measure, amount of reserve funds, and monthly installment payments showed significant correlations with absenteeism. Absenteeism was negatively correlationed with perception with personal finance, behavioral assessment of personal finance, solvency measure, and amount of reserve funds. The monthly installment payments showed a positive correlation with absenteeism

These findings mean that those who had lower scores on personal finance perception, behavior, solvency, and reserve funds tended to be absent more from work. In addition, those who had large monthly credit installment payments were absent more from work. In contrast, those who tended to be absent less from work were workers who perceived that they had higher levels of personal financial wellness, good financial behaviors, good financial solvency, and certain amount of reserve funds.

In sum, absenteeism was negatively correlated with personal financial wellness. Those who perceived that they had lower levels of personal financial wellness tended to be absent more from work than those who reported higher levels of personal financial wellness.

As shown in Table 4, regression analysis showed a significant relationship between financial behaviors and absenteeism. Financial stressors and financial behaviors were significant independent variables that explained the variance of absenteeism. Financial stressors were positively related with absenteeism, as those who experienced more financial stressors in the past year were absent more from work than the others, controlling for other variables.

Financial behaviors were negatively related to absenteeism. This finding suggests that if personal financial behaviors of workers improved-their financial wellness changed for the better-workplace absences would decrease. The R square, however, indicates, as would be expected, that there are other factors that explain the variance of absenteeism of workers. As noted earlier, many determinants of absenteeism have been identified. For example, the health conditions of respondents may be one of the significant independent variables. While the small number of independent variables in this research may be one of the reasons for the low R square in the equation, the relationship between absenteeism and personal financial behavior level is statistically significant.

Among other personal financial wellness measures in this research, the amount of monthly installment payments showed a significant relationship with absenteeism. Those who had more monthly credit installment payments tended to be absent more from work. No other personal financial wellness measures showed significant regression coefficients with absenteeism.

Discussion

This study of clerical workers found that absenteeism was not affected by the traditional demographic characteristics of age, education, income, marital status, housing tenure, number of financial dependents, and length of employment. However, absenteeism is affected by the number of financially stressful events in the workers' lives. Examples of financial stressors are major vehicle repair expense, overdue notice from a creditor, major house repair, a family member went to college, a family member died. Employers who employ workers who have a number of financial stressors in their lives can expect frequent absences from that group of workers.

Absenteeism is also related to personal financial wellness. Clerical workers who reported a high level of personal financial satisfaction, who showed healthy personal financial behaviors (e.g., saving regularly, contributing retirement savings, budgeting, financial planning, etc.), who had higher solvency ratio, and who had more reserve funds for emergencies tended to be absent less from work than the others. Further, workers who paid more monthly installment loan payments tended to be absent more from work than the others. These findings show the importance of personal financial wellness as one of the factors explaining absenteeism.

The results of the regression analysis reveal that the slope of annual absenteeism on workers' financial wellness is -0.032 (t = - 2.228, p < .05, two-tailed test) among the sample of clerical workers. In this case, the slope of -0.032 is interpreted as decreases in absenteeism associated with a 1 standard deviation improvement in financial wellness. That is, as financial wellness decreases annual absenteeism-or lost days of work-increases. In essence, as financial wellness decreases absenteeism similarly worsens.

Therefore, if employers can help workers to improve their financial behaviors, it can lead to a reduction in absenteeism. How then can employers help change workers' financial behaviors?

Previous literature has shown the effects of financial education on workers financial behaviors, especially on retirement savings (Bernheim & Garrett, 1996; DiPaula, 1998; Gorbach, 1997). The preceding research suggests that financial education is vital to improving workers' personal financial behaviors. This research illustrates the possible potential effects of financial education on absenteeism through changing workers' financial behaviors in a positive direction.

Policy Implications

Based upon the research finding that poor and/or low financial wellness is a cause of work absenteeism among clerical workers (Joo, 1998; Joo & Garman, 1998, Garman and Leech, 1997; Garman, Leech & Grable, 1996), it is of interest to determine the substantive significance of the relationship. In this case, the slope of -0.032 is interpreted as the increase in annual lost days of work per person associated with a 1 standard deviation worsening of personal financial wellness.

As noted earlier, it has been recognized that approximately 15% of workers are currently experiencing stress about personal financial matters to the extent that it negatively affects their job productivity (Garman, et al., 1996). This estimate is for white-collar occupations; the figure is probably 20% for blue-collar occupations (Garman, 1998).

How Much Improvement In Financial Wellness Can Be Expected From A Good Workplace Financial Education Program?
The salient question for employers is "How much of an effect on financial wellness can be expected from a good, or even a great, workplace financial education program?" The answer is as follows. A financial education program can be expected to positively impact some, but not all workers. To illustrate, consider an employer of 1,000 workers. A good financial education program might be expected to positively impact at least 50% of workers in varying degrees (Garman, 1998; Milligan, 1998), 500 of the 1,000 workers in this instance. For a number of reasons the other 500 workers may very well not be impacted at all by a good financial education program. While a great financial education program is likely to affect more than 50% of workers (Kratzer et al, 1998), this discussion we will use the conservative estimate of 50%.

Experts say that two-thirds of workers with serious money problems can be turned around within one year given appropriate information, education and counseling (Garman, 1998; Milligan, 1998). Thus, in a population of 1,000 workers, 100 who have serious money problems (2/3 of 150) can be expected to increase their financial behavior 1 standard deviation, or 6.5 points on a 48-point financial behavior scale. Another 200 of 1,000 workers can be expected to increase their financial behavior by 4 points (about 2/3 of 1 standard deviation) and an additional 200 workers can be expected to increase financial wellness by 2 points (about 1/3 of 1 standard deviation).

These anticipated increases, which may result from information, education, and, in some cases, counseling, are less than those empirically determined to result from marital counseling (Hahlweg & Markman, 1988), where the "intervention succeeded in improving marital distress scores by 79% of 1 standard deviation (Forthofer, et. al., 1996, p. 601)." Thus, the illustrated estimates of the effects of workplace financial education shown above are conservative.

The illustrated changes would be equivalent to improving the personal financial wellness of: (1) 100 of those workers with serious money problems (the worst 15%) up closer to the median level of financial wellness to the 25th percentile in the financial wellness distribution, (2) 200 of workers at the median level of financial wellness up to the 73th percentile, and (3) 200 of workers at the median level of financial wellness up to the 81th percentile.

What Effect Would A Good Workplace Financial Education Program Have On Reducing Absenteeism?
The mathematics of these changes demonstrate that the result would be a decrease in the amount of expected absenteeism from work. The expected decrease in absenteeism for the workers who have serious money problems and who increase their financial behavior 1 standard deviation would be five work hours per year (0.032 x 6.5 points behavioral score increase x 3 days x 8 hours work per day). For those who began at the median level of financial wellness and improved their financial behavior by only 4 points, it would be three hours per year (0.032 x 4 points behavioral score increase x 3 days x 8 hours work per day). For those who began at the median level of financial wellness and improved their financial behavior by a marginal, but important, 2 points, it would be one and one-half hours per year (0.032 x 2 points behavioral score increase x 3 days x 8 hours work per day).

Keep in mind, too, that half of the workers in this illustration (500 of the 1,000 workers) are not affected by the workplace financial education for various reasons. The other 500 in a group of 1,000 workers who are positively impacted by the financial education are affected in small, incremental and varying, but important, ways. Overall, these changes add up.

What happens when these changes are applied to data in the sample of clerical workers? Workplace financial education would result in a decrease in the expected number of annual lost days of work per person in the sample from 6.0 days to 5.8 days. The calculations are as follows. The average number of absences of the respondents was 6 days per year. The financial behavioral changes resulting from workplace financial education could be expected to reduce the average annual absenteeism of the sample by 1/5 of one day (the expected average absenteeism change is 5.8 days instead of 6 days).

These savings in absenteeism are based on the above calculation that 10% of workers will improve their personal financial behavior score by 6.5 points, 20% will improve their score by 4 points, 20% will improve by 2 points, and the remaining 50% will experience no changes in personal financial behaviors.

What Is The Potential Savings For an Employer Resulting From Less Absenteeism Because Of Improvements In Personal Financial Wellness?
To calculate the potential savings from improving personal financial wellness, begin by figuring the cost as if all of the people in the sample missed a single day of work. Thus, the cost in lost productivity for one day of absence for the 278 workers equals $33,360 per day (multiplying a $15.00 hourly salary for 278 respondents [their actual average hourly rate]). Therefore, the annual loss of productivity for this sample would be $200,160 per year ($33,360 x 6 [average yearly absences]).

Changing absenteeism from 6 days to 5.8 days for this sample of clerical workers can reduced the average yearly loss from $200,160 to $193,488 ($200,160 - $193,488 [$200,160 x 5.8]), resulting in a $6,672 increase in productivity per year. On a per worker basis, the calculations of the potential savings to the sampled employer that result from less absenteeism because of improvements in personal financial wellness are $24 per worker per year ($6,672/278).

The Potential Savings For All Employers Of Clerical Workers Is $440 Million
According to the Statistical Abstract of the United States 1997, there are 18,353,000 administrative support workers nationwide, including clerical workers. The substantive question is how much is the potential savings to the nation's employers of clerical workers if the calculations are extrapolated to all 18,353,000? This again assumes that the workplace financial education program would effect only 50% of them in varying degrees. The savings could amount to $440,472,000 ($24 savings per worker x 18,353,000) per year, assuming an annual average of 6 days lost to absenteeism.

These calculations are conservative. According to data from the Bureau of Labor Statistics, the lost work time rate (hours absent as a percent of hours usually worked) for all clerical workers in 1996 was 2.5. This lost work time rate can be converted to an annual average of absences of 6.25 days (2,000 hours x 0.025 = 50 hours/8 hour workday) for clerical workers.

These calculations show the powerful potential effects of workplace financial education on reducing absenteeism among the nation's clerical workers. These findings suggest that the potential savings for employers who provide workplace financial education to the nation's clerical workers that impacts their personal financial wellness in small, incremental and varying, but important ways is $440 million a year.

Employers should be alert to the potential savings resulting from lower absenteeism because of workplace financial education. Providers of financial information, education, and services need to collaborate with employers to collect empirical evidence on the actual reductions in worker absenteeism as a result of workplace financial education. Comprehensive personal finance employee education that impacts workers' personal financial wellness in a positive manner may very well be the missing factor in understanding and reducing worker absenteeism.

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¹ So-hyun Joo, Ph.D. Visiting Assistant Professor, Department of Merchandising, Environmental Design, and Consumer Economics, Texas Tech University, and Research Affiliate, Virginia Tech, Center for Organizational and Technological Advancement, Personal Finance Employee Education. Texas address: Box 41162, Lubbock, TX 79409-1162. Phone: (806) 742-3050. E-mail: sjoo@hs.ttu.edu
² E. Thomas Garman, P ersonal Finances and Worker Productivit y , Volume 2, Number 2, November 1998 pp. 172- 182. At the time of publication, Garman was Professor and Fellow, Center for Organizational and Technological Advancement, and Director of the National Institute for Personal Finance Employee Education, Virginia Tech, Blacksburg, VA 24061. Garman retired in 2000 as Professor Emeritus at Virginia Tech. E. Thomas Garman, Distinguished Scholar and Director of Educational Services, InCharge Institute of America, 1768 Park Center Drive, Suite 400, Orlando, FL 32835; E-mail: tgarman@incharge.org ; Phone: 407-532-5883; Fax: 407-532-5750; Web: InCharge.org.

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