8

Joey Molinaro, MD Hasan, Jason Thoryk

The existence of compensating wage differentials means that there are jobs that are less enticing than others. This is evident in the number of workers in certain roles and industries and the amount of compensation needed to make them consider the job opportunity. Compensating wage differentials are defined as the variation in jobs and the existing wage discrepancy that exist based on the differences in non-wage characteristics. In our analysis, we look at the types of jobs that have compensating wage differentials based on a series of characteristics and then compare them to jobs that do not. In addition to this, the analysis looks at several studies that have looked into compensating wage differentials, what their findings have found, and how it proves that some occupations need extra compensation for workers to accept the job. In our findings, it was found beyond a reasonable doubt that there was evidence of compensating wage differentials.

What are Compensating Wage Differentials?

Compensating wage differentials are the additive pay to take a job where there is risk, unpleasantness, and other attributes that make it more complex than an ordinary 9-5, Monday through Friday job. For a worker to accept a job that contains a negative attribute, the worker’s optimal wage-job risk bundle needs to exceed or meet the market compensation for increased risk (Biddle and Zarkin 661). Many workers are willing to take on additional risk by accepting an occupation that inherently has more risk if their income rises by enough, but not all workers are willing to accept such unfavorable workplace conditions. Safety certainly has a price.

Focusing on the choice of wages and job risk, workers maximize utility by choosing a wage-job risk bundle subject to a hedonic wage equation (Biddle and Zarkin 663). Utility is the amount of satisfaction that workers receive from consumption and leisure. If workers want to consume more, then they need a job that is going to pay more (holding education and experience constant). This means that they will need to accept more risk or other factors to gain an additional increase in wages. Hedonic wage functions reflect the relationship between wages and job characteristics. Essentially, workers need to be paid a certain amount to be compliant with the attributes the job entails and have the motivation to gain an increase in wages. For this to be effective, workers need to have perfect information, perception, and cognition of the job and tasks at hand (Dickens 3). Many workers are aware of the inherent risks of occupations like firefighters and construction, but many are not aware of the risks in more popular jobs such as warehouse and manufacturing. Without all information, present workers are not able to judge the risk present in the occupation and therefore cannot assess the increase in wages needed for them to accept the risk. This usually results in employers winning because they hired a worker at a set wage before they had perfect information about what goes into the job.

Indifference curves show the tradeoffs between the worker’s wages and the probability that they will be injured on the job (Biddle and Zarkin 664). The indifference curve indicates the worker’s reservation price, this is the amount of money it takes for a worker to be indifferent between a safe job or a risky job. An increase in wage results in workers that are more likely to take the risk, but this does not only occur if the employee receives the payment directly. Worker’s compensation also incentivizes workers to take on additional risks since they would receive a compensation package if they ever were injured because of the risk (Arnould and Nichols 333). The basis of indifference curves is that each worker has a preference for the type of work they would like to do, but if their wage or benefits is increased they are more susceptible to do a type of work that is not of preference.

While indifference curves represent an employee’s decision on the type of occupation they want, isoprofit curves show the risk-wage combinations that yield the same profits for the company. If companies spent more money on lowering the risk of the job, then that money would come out of the employee’s pay. Workers would rather have a work environment that has an increased risk and more pay than have an incrementally safer work environment and earn less. This goes to show that employees could have a safer place of work, but many would prefer to be paid for the risk they endure instead of the company taking that money and trying to make it safer. Further discussion of firm-based decisions on this topic will be provided within later sections of the chapter.

There are outside factors that may influence the worker’s decision such as the company itself and how many other factors go into the job. The main focus of our analysis, in terms of compensating wage differentials, is the aspect of injury and how that influences the decision to take a riskier job over a safer job.

Risk Defined

Before going any further in this chapter, it is important to define what we mean by risk when referring to compensating wage differentials. When referring to risk in the chapter, we are using a broad definition of the word to encapsulate both human decisions and non-human decisions (firms, governments, etc.). The actual definition of risk itself will vary for human decisions and non-human decisions when talking about compensating wage differentials. For humans, risk will involve the likelihood of injury in a job, how unsafe the job is, and how that danger will be reflected with the compensation provided. For non-humans, risk will involve how to incentivize humans to act according to the goals of the entity in question; an example would be offering higher wages to more productive employees.

Sources of Compensating Wage Differentials

Many sources affect compensating wage differentials and justify their existence while others contradict themselves. A later section will describe workplace hazards and how they relate directly to compensating wage differentials while this section will focus on how there are sources of compensating wage differentials that are indirectly related and more deeply connected to compensating wage differentials than the directly related ones. This section serves to provide a broad look into what affects compensating wage differentials on a deeper level of analysis by providing real-world examples and scenarios where the use of these sources of compensating wage differentials will be necessary.

Saving Lives

Bellavance et al. conducted a study in 2006 to determine the value of a statistical life (VSL). Thinking about the monetary value of a life is not something typically associated with compensated wage differentials, but the relation between the two subjects is present. In terms of compensated wage differentials, the VSL represents an additional unit of value with the risk lying on what the actual cost is. From an administrative view, the risk here is how much a single human life would cost and the reward is how much lives can be saved. Making cost-benefit analyses with VSLs is something that public decision-makers have to do to prevent as much risk while also ensuring the safety of their citizens. An illustration of how cost-benefit analyses with VSLs are used will be presented later in this section, but first, we must talk about how compensated wage differentials work with VSLs.

Compensating wage differentials come into play here in the form of administrative decisions. Administrative institutions want to avoid or minimize risk as much as possible to save as many lives as possible. “The unconditional minimization of risk is no more desirable for a particular individual than it is for governments” (Bellavance et al. 2). Compensating wage differentials not only applies to the work but also the payer. When confronted with a risky option (like COVID-19), the option is to pay more to attract attention (an example is how states are currently bidding for medical supplies to gain the needed supplies). However, resources are limited so administrative institutions can not afford the risk associated with banks and other financial institutions. The question of how much a human life is worth is something that any administrative institution needs to take into deep consideration to formulate appropriate procedures in place to prevent costs from exceeding some sort of numerical and monetary threshold. The monetary VSL figures mentioned in the paper ranged from $0.5 million to $50 million in 2000 $US (Bellavance et al. 2). It goes to say that lowering costs to save each life is something any administrative institution would want to endorse. A method in doing so would be promoting exercising, eating healthy foods, not overdrinking alcoholic beverages, quitting smoking, and other such countermeasures to keep the majority of people healthy to help out the people in real need of help. A real-world example as of early 2020 would be the current public health campaign of social distancing to prevent the spread of COVID-19 and prevent hospitals from going beyond capacity. Further discussion about VSLs will be provided within the Pandemics and Compensating Wage Differentials section.

Emotional Demand

Glomb et al. examined how emotional labor demands are related to wages. The study broadens our understanding of compensated wage differentials by researching how emotional demand plays a part in determining pay. While many studies highlight emotional demand in the labor markets with a focus on burnout, stress, and other such cases, Glomb’s study reveals contradictory insights that show that emotional demand does not necessarily correlate with pay. Specifically, the results said that higher levels of emotional demands were not uniformly rewarded with higher wages (Glomb et al. 25). Rather, it was found that the general cognitive ability required by the job with the emotional demand leads to increasing wages in some cases while decreasing wages in other cases. “Results suggest that higher levels of emotional labor demands are associated with lower wage rates for jobs low in cognitive demands and higher wage rates for jobs high in cognitive demands” (Glomb et al. 2). The classical theory of compensating wage differentials would suggest that something is missing to explain what is going on with this discrepancy so more research between cognitive demand with emotional labor needs to be conducted. We would typically expect higher emotional demand to correlate to higher wages, but we are seeing the opposite in the study. More research needs to be performed on this subject to better verify what is going on in this scenario to see if any underlying variables may be taking effect or if we need to readjust the compensating wage differentials model to better adjust for these contradictory results. Overall, not much research has been conducted with emotional labor demands in conjunction with compensating wage differentials so offering a generalization of the subject may not be currently feasible- more research is certainly needed.

Pay Level vs. Job Satisfaction

A meta-analysis conducted in 2010 indicates that the pay level is only marginally related to satisfaction (Judge et al. 157). In terms of compensating wage differentials, the conclusions of the study further emphasizes the existence of compensating wage differentials. The general thought behind compensating wage differentials is that the riskier the job is the higher the pay will be to compensate it. In that case, the inverse or opposite must also be true; the safer the job the lower the pay. A job considered to be safe will likely be more favorable and satisfactory than a job considered unpleasant or risky. When combining the safety of a certain job with the satisfaction that it provides, the compensating wage differentials model tells us that the pay should be lower for those workers and it is (for the most part). One of our later sections visually illustrates the difference between jobs considered safe and jobs considered dangerous with the use of tables to highlight that pay difference along with the numbers of fatality and injury to highlight the riskiness of those occupations.

From a different viewpoint, this meta-analysis shows how a boss can better improve organizational productivity and conduct through the lens of determining how to pay employees. The general thought is that offering higher pays to workers you want to stay would encourage them to stay and become more satisfied with their jobs; more job satisfaction would lead to less slacking and in turn more productivity for the organization as a whole. The main point brought out in this paper is that offering pays higher than what the market offers does not necessarily improve a worker’s job satisfaction because their co-workers would also be receiving those same benefits (Judge et al. 163). This sort of disparity presents a challenge to bosses as they have to figure out how to make sure their workers are satisfied with their jobs while also making sure that the pay level is satisfactory enough to keep the workers. In the context of compensated wage differentials, the boss is taking the risk to hopefully gain more productive employees to increase overall productivity and in turn make the company more profitable; the risks lie in the employees not potentially being satisfied because their co-workers would be receiving similar wages.

Workplace Hazards

A workplace hazard is any aspect of work that causes health and safety risks and has the potential to harm people in the workplace. Many different types of hazards exist and by examining many different industries and occupations, individuals can assess the possible risks that can cause compensating wage differentials. The different types of hazards that exist in the workplace are:

  1. Physical Hazards: This is the most common hazard seen in the workplace and includes any injuries to the body or death. Some of the jobs that we look at that cover this are truck drivers, firefighters, and agricultural workers. Some injuries that can come from these jobs are broken bones, cuts on the body, and burns. These types of hazards are the most common ones that we will discuss in this paper.
  2. Chemical Hazards: These are hazardous substances that can cause harm to employees. Some jobs that may have this include people who work at a nuclear power plant. Later on, in the paper, we discuss the possible effects of industries that are high in pollution-intensive industries and how they can be associated with compensating wage differentials. Many injuries and deaths from chemical hazards are not instantly noticeable but there could be cancer or other sicknesses that come in the future from working in these industries with chemical hazards.
  3. Biological Hazards: These hazards are less common for what we are looking at but they usually come from bacteria and viruses.
  4. Mental Hazards: These are different types of hazards that exist, which come from mentally difficult jobs. An example of a job that we look at that may experience this is in police officers. They can experience this because of traumatic events that they were a part of on the job. The after-effects of these mentally straining jobs can be extremely detrimental to their future value of life and can affect a person greater than any of the other hazards listed above.

All of these hazards show us the many different kinds of problems that workers may have to endure in the workplace and are all valid reasons for there to be compensating wage differentials. The next section will provide more insight into compensating wage differentials and how they relate to risk.

Types of Jobs

For many jobs, there is a minimal inherent risk that is evident at the start of the job. For this section, we looked into jobs that had high inherent risk, unpleasantness, and other factors that would lead to compensating wage differentials. We took this information and then compared it to jobs that have low inherent risk and unpleasantness comparatively. The information we compiled comes from the U.S Bureau of Labor Statistics to look at a few main sections which consist of annual mean wages, amount of injuries, amount of fatalities, and the number of people in the occupation. To keep a level of consistency, we chose occupations that require training at most, no higher education past high school. The occupations were broken down into two categories consisting of dangerous and non-dangerous. Each of these has five occupations in them and is comparing the sections listed above.

Dangerous Jobs

In terms of dangerous jobs, we chose five jobs that were well known and have a large number of workers in the occupation.  The occupations that were chosen were Police Officer, Firefighter, Truck Driver, Agricultural Worker, and Maintenance. Each of the occupations had the number of injuries reported, fatalities reported, the number of workers, and the average salary. Police Officer and Firefighter are popular occupations that are known to have inherent risks. Out of the five dangerous occupations, these occupations have the lowest injury rate and fatality rate. These other occupations see tens of thousands of injuries every year with several hundred deaths. These results were surprising because Police Officers and Firefighters have a higher average salary than the rest of the occupations, the next closet being construction. This would appear to go against compensating wage differential, but there is room for growth in both of these occupations and there is more than likely data being withheld from these statistics. In addition to this, not all of these jobs are strictly dealing with an injury. These jobs can be unpleasant in terms of the tasks that need to be accomplished and the time of day that the work shift is. Figure 8.1 shows the differences between occupations and the risk factor that goes into each while displaying the average salary that can be attained.

 

Occupation Total cases of Injury Fatalities Number of Workers in Occupation % Chance of Injury Average Salary
Police Officer 430 111 669,970 0.06% $67,620
Firefighter 260 45 324,620 0.08% $54,650
Truck Driver 78,520 607 3,223,840 2.44% $42,170
Agricultural Workers 13,620 574 415,390 3.28% $29,120
Construction 73,630 1,008 6,194,140 1.19% $54,580
Maintenance 54,400 288 4,429,100 1.23% $31,250

Figure 8.1 (information retrieved from U.S. Bureau of Labor Statistics)

Non-Dangerous Jobs

In terms of non-dangerous jobs, we chose five jobs that were well known and have a large number of workers in the occupation.  The occupations that were chosen were Telemarketers, Food Servers, Administrative Assistants, Cashiers, and Sales Representatives. It was found that the injury and fatality rates were significantly lower than the majority of dangerous jobs. In addition to this, except for Sales Representatives and Administrative Assistants, the other occupations make a lower average salary than the dangerous jobs. These jobs do not have the same risk level or unpleasantness as dangerous jobs and it reflects in the average salary. Figure 8.2 shows a decrease in almost all categories from the dangerous jobs listed above. This shows that there is a compensating wage differential between occupations that have risk and unpleasantness when the education level is held constant.

 

Occupation Total cases of Injury Fatalities Number of Workers in Occupation % Chance of Injury Average Salary
Telemarketer 150 1 134,800 0.11% $29,770
Food Servers 6,780 0 277,580 2.44% $26,080
Administrative Assistant 3,100 0 3,353,950 0.09% $43,410
Cashier 8,220 0 3,617,910 0.23% $24,400
Sales Representative 1,450 0 2,084,000 0.07% $71,660

Figure 8.2  (information retrieved from U.S. Bureau of Labor Statistics)

After reviewing both charts, it becomes noticeable that the injury rate is similar for both food servers and truck drivers. On the contrary, the average salary between both occupations are so different from one another. The difference in pay can be described with compensating wage differentials. As mentioned in a previous section, physical and mental hazards affect the workplace environment as well as the health and safety of its workers. Truck drivers are exposed to both physical and mental hazards. Driving for extended periods (about eight to ten hours daily) can place severe bodily and mental fatigue. Truck drivers may not be able to find the time to exercise or eat healthy meals often so their health will likely diminish due to the characteristics of the job (driving for long hours non-stop). Likewise, truck drivers may also have to deal with long periods isolated from loved ones or close partners- further hindering their mental health. Truck drivers lack social interaction. Unlike truck drivers, food servers do not have to encounter any of the four types of hazards (discussed in earlier sections) frequently. They’re placed in better working conditions and rarely encounter severe physical damage but may encounter slight physical damage like a cut or burn. Physical and mental fatigue is less likely to occur due to food servers constantly performing various tasks (unlike truck drivers only driving) and social interaction is very high. With all these factors in place, food servers have more safety nets in place that promote the health of employees whereas truck drivers have to deal with harsh conditions that could hinder their physical, mental, and social health. In other words, truck drivers are faced with more inherent risk in their job when compared to food servers and are compensated with higher wages to make up for those costs associated with the job.

Pollution Intensive Industries

One of the topics of discussion when talking about compensating wage differentials is employees of companies who are pollution-intensive industries. Do employees in these types of industries receive compensating wage differentials and if so how much? Throughout the industry, when looking at the whole economy, it is noticed that jobs considered dirty receive a wage premium of only a quarter of a percent (Cole et al. 2). When looking at individuals who work in one of the five dirtiest industries there is a wage premium of around 15%. We will dive deeper into why they give these wage premiums and if there is proof that they exist.

Below, we have included a graph with the largest pollution-intensive industries with a breakdown of the percentage of global emissions from 2005.

Industry Percentage
Electricity and Heat 24.9%
Industry 14.7%
Transportation 14.3%
Agriculture 13.8%
Land Use Change 12.2%
Other Fuel Combustion 8.6%
Industrial Processes 4.3%
Fugitive Emissions 4.0%
Waste 3.2%

Table 8.2 (information retrieved from the World Resources Institute)

Over the past number of years, we have seen an increase in how much people care about the environment and especially the possible effects that working in these industries has on a person’s future. Some stats show how much some of these dirty jobs can affect a person’s future health. It is estimated that between 1 and 40% of all lung cancers and 0 to 24% of bladder cancers are related to an exposure that has come from the workplace (Cole et al. 3). Another statistic that showed how many people are affected by their workplace is that in 1992 there were an estimated 50,000 to 70,000 people who died of cancer with direct relation to toxic exposure from work with 200,000 worldwide deaths from the same cause (Cole et al. 3). The definition of a dirty industry is an industrial environment where an employee is potentially exposed to a high level of pollutants that may have a long term effect on somebody’s health. It is clear why workers in this industry do deserve to be compensated with higher wages as they are facing risks with their future health.

In the end, the conclusion that was discovered was that if you are working in a “dirty” industry, then there is a slight wage compensation of about one-quarter of a percent, but if you worked in one of the top five “dirtiest” industries then the wage premium jumps to over 15%. After looking at all of the information, this isn’t very surprising as people must have some incentive to work in an industry that can have negative effects on their future health.

Global Compensating Wage Differentials

The magnitude of compensating wage differentials vary across countries. A study by Thomas J. Kniesner and John D. Leeth found that countries such as the United States, Japan, and Australia each handle compensating wage differentials differently. This section will focus primarily on countries other than the United States to show the contrast between it and the other countries.

Australia has a large number of unions and many workers in these risky jobs are in a union. It has been found that Australian manufacturing workers that are exposed to a mean fatality risk earn 2.5% more than compared to those in a completely safe working industry (Kniesner and Leeth 76). Australian workers know the type of work they do involves risks and that is why they fight for higher wages to be compensated for that.

Japan is very different compared to the United States and Australia. Japan has a different work culture overall so the way they implement compensating wage differentials is distinct. The way they differ is in fact that there is no evidence of compensating wage differentials in Japan. Japanese work culture is about longevity with a firm, not type of job performed. Because employees tend to stay with firms for long durations, employees receive more on the job training which results in employees being more prepared for the tasks at hand. This results in the probability that Japan does not have a wage premium for workplace health hazards because employees are more aware of what is going on. Along with this, Japanese manufacturing firms provide higher pay and safer workplaces (Kniesner and Leeth 80). Because of this, there is little evidence of a positive relationship between wages and the rate of injury. This results in Kniesner and Leeth determining that Japan has a compensating wage differential equivalent to about 0% and Australia has a compensating wage differential equivalent to roughly 2.5% (Kniesner and Leeth 84).

Pandemics & Compensating Wage Differentials

As of early 2020, the coronavirus (COVID-19) outbreak that originated in Wuhan in the Hubei province of mainland China has dealt considerable damage to the global community as well as the economies of every nation. Nations are scrambling to contain the virus to prevent the healthcare systems from becoming overridden. In the US, the social distancing measures along with the quarantine for non-essential workers have damaged the economy severely and the ramifications of the future economy appear to be uncertain at this time. Speculations about a possible depression are starting to emerge. Among all of this chaos, where does compensating wage differentials fit in?

Among this new wave of panic from the COVID-19 pandemic, the existing model of compensating wage differentials may begin to change. If the epidemic persists long enough, healthcare workers and other essential workers will start to see increases in their wages due to the increased amount of risk those occupations are facing right now. In the long-run, the aftereffects of the pandemic measures (social distancing, quarantine, wearing facemasks, etc.) will stay for longer. People may not feel that safe if the economy just opens right back up without any preventative measures taken into place to improve worker safety. More than ever, people are fearing risk because of the potential damage it poses to not only themselves but to the greater community.

Capitalizing on this newfound risk is something firms and governments have to figure out how to address. Worker safety will become a major topic for firms post-pandemic. Governments may increase unemployment benefits to better increase the safety of its citizens. Before the pandemic, people would have preferred a more risky job if it paid appropriately in compensation, but post-pandemic, we might start to see people competing over safer jobs with lower wages. Firms will likely begin to improve worker safety and lower wages to encourage former and new workers to come back to work. Due to the mass unemployment resulting from the pandemic, firms may not have to change operations much, but not changing at all may leave a bad reputation for a firm. If a firm does not improve safety measures, then potential workers and consumers may feel less safe and less likely to go to the firm. The result is that the safety of employees needs to be taken into more consideration regardless of the firm’s decision; focusing on the maximum profitability of a company will no longer be viable. When firms begin to restart operations and begin hiring people again, safety measures will likely be implemented to give a firm a more safe feeling to it. The costs of those newly implemented safety measures may not be possible to be deducted from future employee’s wages, so profits for firms may diminish in the short term.

After this pandemic, short term changes may not be feasible for firms. The risk of being unable to operate due to services being non-essential in another crisis may destroy the company. As a result, firms will have to reexamine their operations and figure out how to make them more essential. In other words, long term changes have to be made for firms so they can continue to remain operational in severe crises. The risks of not doing so are more severe and detrimental than not increasing firm costs to improve worker safety and operability.

For governments, long term changes have to be made to prevent another crisis like this from happening again. While the crisis may have seemed to have been unexpected, preventative measures could have been taken much earlier to prevent human deaths. Permanent safeguard measures need to be established to reduce future risks of similar crises of biological origin. Likewise, the value of statistical lives (VSLs) will have to be re-evaluated and improved upon to lower costs and improve hospital capabilities. The COVID-19 pandemic has revealed significant pitfalls within the healthcare system that have to be addressed (such as the manufacture and logistics of medical supplies) and the use of VSLs will likely play a key role in how services could be improved in the event of a similar crisis occurring again in the future.

The world will look considerably different post-pandemic and individual risk assessments may change following this new change. Firms will have to readjust how they make decisions, people will have to readjust their relationships with and work, and institutions will have to scramble to find resources to better ensure the safety of its citizens along with itself. Institutions may make riskier choices in hopes of faster results for finding a cure to this pandemic while many people may end up becoming risk-averse post-pandemic. Governments need to prevent its citizens from feeling uneasy as that uneased tension may become riskier for the economy and hence more detrimental to the welfare of the nation and its citizens. Overall, a variety of decisions will have to be made to prevent the economy from collapsing in on itself while also maintaining social stability, and compensating wage differentials will play a key role in the process.

Decisions That Firms Are Faced With

When it comes to safety within the workplace, firms are faced with an important decision. They have to decide if it is more worth investing in their firm to make it safer or compensate for higher pay for their workers. If firms decide to invest more money into safety measures for their company then there is a higher chance that they won’t have to pay as much in wages for their employees as they will feel safer working there and will not need to be convinced to take on the riskiness with high wages. One of the issues that many firms face when deciding this is that even with the upgraded safety measures it is much more difficult to convince people to lower their wages than increase a person’s wages regardless of if they feel safer in their workspace.

Another decision that firms are faced with is in the situation that we described above, during pandemics. Many companies, even those who were deemed essential, had a tough decision to make. They knew they would have to spend more money on safety procedures and most likely pay their employees a wage premium. Workers would expect a wage premium during these times because of the risks they are taking on their life and as we have seen many companies and governments have pledged to pay these employees a wage premium. In these cases firms are faced with the question, should they stay open and provide all these safety measures and wage increases or should they close down and not deal with all the associated costs.

Are Workers Able to Reduce Their Risk Themselves?

Another argument that is not discussed when talking about compensating wage differentials is the idea that many of these so-called “risky” jobs can be much safer with precautions taken by workers in the industry. Now especially we see many companies giving their employees safety incentives like a bonus at the end of the year or extra paid vacation days if they meet a certain safety standard throughout the year. This is another form of compensating wage differentials not usually included in the average salaries of many of these jobs that we are reviewing for this paper. An example of this comes from one of the most dangerous occupations in the United States: Truck driving. Truck drivers make up 25% of occupational fatalities which is an extremely large number. (Bureau of Labor Statistics, 2016, National Public Radio, 2016). What many firms in this industry have done is start to introduce safety incentives that reward drivers for safe driving instead of rewarding them for fast or unsafe driving. This is effective because it makes these truck drivers feel less pressure to deliver their trucks as fast as possible but gives them the incentive to drive safer. There was a survey done of 40 long haul truck companies in Canada where 70% of them said that they had some sort of safety incentive program in place.

Another theory that was looked at in other scholarly papers when talking about compensating wage differentials and how workers reduce risk themselves was how obesity contributes to making a job more dangerous. The articles cited by Guardado and Ziebath related bodyweight to safety-related productivity and found that obesity significantly increases the risk of accidents (Guardado and Ziebarth 135). It was found that becoming obese was associated with a 21% higher chance of having a workplace accident. This part was included in our paper because it is important to view some of the obstacles that may exist when referring to compensating wage differentials and why it may not always be as straight up and easy to calculate if there are compensating wage differentials in certain industries. When looking at different research with one comparing obesity and wages, it was found that there is a direct negative correlation between a person’s body mass index and wages, meaning the higher a person’s body mass the lower their wages are.

Summary & Conclusion

Throughout our research from various studies, economic papers, and statistical data we were able to find several factors that show evidence of compensating wage differentials and the attributes that result in the wage increase. The findings were surprising on the basis that it is not based on only whether the worker is at risk of injury or death, unpleasantness plays a major role in the decision-making process for workers to accept certain occupations. The overall consensus is that simply an increase in pay may not be enough for workers to engage in an occupation where the risk outweighs the additional income. Workers take into consideration how much the unpleasantness or risk will impact them and if they even need the additional income. To add to this, some workers are just more willing to take risks than others. It is hard to classify how much it takes to have a worker take on risk because every worker is different. Based on the many studies and articles, we have found proof of compensating wage differentials and that they are needed for workers to accept jobs that are less appealing than other jobs available with the same education level.

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Why Do Wages Differ? Copyright © by John Kane, editor is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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