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The standard treatment of occupational risk in the labour market is conducted in terms of the theory of compensating wage differentials, the basic characteristic of which is that workers can fully estimate actual occupational risks. However, research in cognitive psychology, and recent advances in economic psychology, suggest that individuals consistently underestimate risks associated with accidents. In this paper, we discuss the case when the workers systematically underestimate job risks. After presenting the standard treatment of occupational risks, and of health and safety at work regulation, we then proceed to incorporate the idea of job risk underestimation. The paper discusses the types and impact of regulation on health and safety effort in a simple framework in which workers’ beliefs concerning accident risks also play a role. The paper shows that a particular type of regulatory intervention is necessary for the risk underestimating workers not to suffer a welfare loss.
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WORKERS’ RISK UNDERESTIMATION AND OCCUPATIONAL HEALTH
AND SAFETY REGULATION
By
STAVROS A. DRAKOPOULOS
UNIVERSITY OF ATHENS
IOANNIS THEODOSSIOU
UNIVERSITY OF ABERDEEN
March 2011
Abstract
The standard treatment of occupational risk in the labour market is conducted in terms
of the theory of compensating wage differentials, the basic characteristic of which is
that workers can fully estimate actual occupational risks. However, research in
cognitive psychology, and recent advances in economic psychology, suggest that
individuals consistently underestimate risks associated with accidents. In this paper,
we discuss the case when the workers systematically underestimate job risks. After
presenting the standard treatment of occupational risks, and of health and safety at
work regulation, we then proceed to incorporate the idea of job risk underestimation.
The paper discusses the types and impact of regulation on health and safety effort in a
simple framework in which workers’ beliefs concerning accident risks also play a
role. The paper shows that a particular type of regulatory intervention is necessary for
the risk underestimating workers not to suffer a welfare loss.
2
1. Introduction.
Many studies on individual beliefs concerning risk have shown that people
often underestimate and/or overestimate risks. For instance Kahnemann and Tversky
(2000) suggest that in decision making people consistently underestimate outcomes
that are merely probable in comparison with outcomes that can occur with certainty.
They also argue that individuals are unlikely to perform the operation of subtracting
the cost from the outcomes in deciding whether to buy a gamble. In addition, there is
ample empirical evidence concerning similar behaviour towards risk in the context of
occupational environment. Much specialist scholarship indicate that workers
constantly underestimate their exposure to work risk for work accidents, since
perceptions of risk are influenced by pre-existing, recent or readily available
experiences (Thaler and Sunstein, 2008) or overestimation of personal immunity from
harm (Weinstein, 1989).
This paper studies the repercussions of the above theoretical developments in
the occupational safety and health framework (OSH) when the workers systematically
underestimate job risks. In doing so the paper first briefly reviews the standard debate
relating to the implementation of OSH. Although, it is generally accepted that there is
a need for regulation in the case of job risk underestimation, there is no much work
regarding the type of appropriate regulation. The paper provides a discussion of the
types and impact of regulation on health and safety effort in a simple framework, in
which workers beliefs concerning accident risks at workplace interact with the
behaviour of Health and Safety regulator.
Thus, the following section briefly discusses the evidence of general
systematic risk underestimation. Section 3 examines the implications of workers’ risk
3
underestimation in the context of health and safety at work. Section 4 studies the
behaviour of the health and safety regulator in the case when there is job risk
underestimation by the workers and the interactions between the two. The final
section summarises the main points and provides some conclusions.
2. Systematic risk underestimation
Research in cognitive psychology indicates that individuals consistently
underestimate risks associated with accidents. Kahneman and Tversky, (1979),
Kahneman et al., (1982); Slovic, (2000); Kahneman and Tversky, (2000) show that
people tend to not evaluate appropriate information about the assumed risk. Tversky
and Kahneman, (1974); Gilovich et al., (2002) suggest that individuals employ
simplifying rules of thumb in decision making with respect to assuming risk. These
rules of thumb lead to biases in the assessment of real risk and misplaced subsequent
choices. Research in psychology also shows that the above rules of thumb are driven
by an inbuilt resistance to unwelcome information which results in important
cognitive limitations (Denscombe, 1993). In addition, people make systematic errors
in their perception and predictions as current emotions influence assessments of the
future, and thus they consistently misjudge their future emotions (Gilbert 2006,
p.109). An implication of this is that the individual’s assessment of future risk is
shaped by current circumstances and emotions. Thus, individuals are found to
overestimate the frequency of dramatic or sensational causes of death (homicide,
aviation accidents) and underestimate the frequency of less well-publicised causes
(such as stroke, asthma or a car accident) (Slovic et al 1982). For example, in an
experiment carried out by Tversky (in Bernstein 1996) individuals were asked to
4
estimate the probability of dying from various causes. Their estimates exhibited a
significant discrepancy compared to the actual statistical figures. They consistently
underestimated some risks (e.g. natural causes) and overestimated others (e.g.
unnatural causes).
Furnham (1988) and Thaler and Sunstein (2008) show that the individual’s
evaluation of risk is influenced by the immediacy of the event, the framing, the
perception the individual’s ability to control the risks and the anchoring. The
individual’s perception of risk is also affected by an ‘optimism bias’, as individuals
are found to commonly overestimate their personal immunity from harm (Weinstein
1989), always assuming that hazards are more risky for other individuals than for
themselves. Moreover, Rogers et al. (2000) and Lloyd (2001) offer evidence showing
that individuals tend to underestimate the qualitative nature, and severity of outcomes,
in terms of their current and future impact on their health or their functional status.
All in all, the evidence suggest that employees tend to underestimate the level,
nature and severity of risk associated with the execution of job tasks. They
consistently evaluate the likelihood of having an accident at work as being less likely
than the actual risk they face, as predicted on the basis of statistical analysis and
expert opinion.
3. Job Risk Underestimation and Health and Safety
The standard treatment of occupational risk in the labour market is conducted
in terms of the theory of compensating wage differentials (CWD) (Rosen, 1986,
Ehrenberg and Smith, 1997). This theoretical approach suggests that market forces
ensure payment of wage premiums by firms to those employees who are employed in
5
risky job tasks, which premiums persuade workers to accept less attractive jobs that
are associated with higher occupational risk. Hence, the theory predicts that wages
rise with job risk, and that wages will be higher for more risky jobs other things
being equal. The worker is thus able to choose from a menu of wage – job risk
combinations that produces an indifference curve that relate wage levels and the risks
of occupational injury.
Importantly, Purse (2004) criticizes this approach arguing that there are a
number of crucial underlying assumptions of the theory that are problematic. In
particular, the basic assumption for the theoretical validity of the CDW theory is that
of labour mobility. This assumption might not hold in many cases, because of many
market types, and due to institutional obstacles. In addition, workers might not be
informed about workplace risks, and this implies that workers may seriously
underestimate job risks. Finally, Purse (2004) provides a detailed discussion
suggesting that the assumption that individuals are always rational decision makers,
even under conditions of uncertainty and risk, is not consistent with empirical
findings. Furthermore, since safety is a normal good, non-manual workers or those
who enjoy a higher level of human capital can “afford” to select jobs with better
working conditions (Biddle and Zarkin, 1988). Employers also offer superior market
opportunities (both pecuniary and non-pecuniary) to high-skilled workers who have
job-specific training (Viscusi, 1993). This implies that the wage-risk tradeoff is likely
to be an increasing function of wealth, in which case the safer jobs are allocated to the
highest paid individuals.
This has repercussions for the employee’s estimation of level of the risk
premium which they will require in order to compensate them for undertaking a
hazardous job task. In view of the above, it appears that they will consistently accept
6
lower premiums, which in turn offer the opportunity and the incentive to the
employers to provide a less than adequate level of health and safety. In terms of the
standard treatment, Figure 1 shows the worker’s indifference curves and the wage
offer curve by the employer in the case where the worker systematically
underestimates the probability of job injury risk.
(Figure 1 about here)
The worker believes that the job risk is at level r
0
with the corresponding
compensating equilibrium wage at w
0
. This combination lies on the workers’
indifference curve U
0
and the employers wage offer curve is OC. However, if the real
job risk is higher at the level r
1
, then the worker unknowingly is taking “too much”
risk for the given wage level. This means that although the worker believes that
he/she operates at U
0 ,
he/she is effectively at a lower indifference curve U
1
. In order
to remain at U
0
utility level, the worker should receive a higher wage rate equal to w’.
Thus, the difference w’w
0
is the wage loss that the worker suffers due to his/ her job
risk underestimation. Hence, in the context of the standard framework, government
intervention, in the form of the provision of adequate information, the setting of
standards or the imposition of financial penalties or prosecution, might be necessary
to achieve equitable levels of OSH.
The standard approach to the behaviour of work safety regulator is that the
regulator imposes a maximum level of job risk (Borjas, 2010). The way that the health
and safety regulator imposes this maximum risk is not direct but through an array of
safety measures and penalties (see Viscusi, 1986). Usually, the regulator targets firms
where there is an increase in occupational accidents and imposes stricter health and
safety rules (Bartel and Thomas, 1985; Ruser and Smith, 1991 describe a realistic
approach of the functioning of health and safety regulator).
7
In terms of figure 1, if the maximum level of job risk imposed by the regulator r
max
is
higher than the perceived job risk r
0
but lower than the actual level of job risk at r
1
,
and the wage rate remains the same, then the worker is at a lower indifference curve
than U
0
but higher than U
1
. In order for the worker to remain at the same indifference
level U
0
, he/she should be paid a higher wage than w
0
. In this framework, it is clear
that when the worker underestimates the probability of a work accident, then he/she
suffers a loss either in the form of a lower wage, or of utility. Thus in the presence of
systematic job risk underestimation, workers suffer a loss which can be alleviated
only when the OSH regulator intervenes.
4. Workers’ Risk Perception and the Regulators Safety Effort
The above section offered an overview of the repercussions of job risk
underestimation by the worker and the assumed function of the health and safety
regulator in imposing a maximum acceptable risk. As was mentioned, the way that the
regulator does this is indirect. The standard approach is to assume that the regulator
implicitly sets a maximum level of risk by safety inspections, citations and penalties.
Inspections, backed up by the threat of penalties for non-compliance, may push
employers to comply with standards, or even to improve their overall safety programs.
Firms monitor the regulators’ activity and respond in ways that decrease injury rates
when perceived enforcement risk increases (Mendeloff, 1979; Viscusi, 1986). For
instance, it has been found that in US, a 10% increase in enforcement activity reduced
injuries by about 1% (Scholz and Gray, 1990). By using Canadian data, Lanoie
(1992) reported that a 1% increase in occupational health and safety inspection rates
8
was associated with a 0.2–0.3% decrease in frequency of individual workplace
injuries (see also Mendeloff, 2005 for a discussion of the general OSH impact on job
injuries). However, there seems to be a lack of attention in the literature concerning
the issue of the effect of health and safety regulations combined with workers’ job
risk underestimation, and of the interactions between the two.
One can investigate the above in a simple framework utilising research on risk
perceptions. A discussion of the general case of the difference in beliefs concerning
risk and regulation can be found in Viscusi, (1998); Salanie and Treich, (2009). In the
specific context of safety at work, one can assume that there is a difference
concerning the assessment of a job risk between workers and the work safety
regulator, and that there is agreement between the two parties concerning all other
preferences. Contrary to the standard approach, the health and safety regulator does
not impose a maximum level of job risk but instead he/she adjusts the level of effort
to work safety. Following the standard approach of the relevant literature on risk
perceptions, the representative worker has quasi linear preferences given by:
U(h, e, Pw) = u(h) – (1-e)Pwh – c(e) (1)
Where
h: is the hours of work supplied by the worker with h 0
u(h): is the workers’ gross surplus (arising from hourly wages), assumed increasing
and concave
e: is the level of regulator’s effort to work safety, with 0 e 1
c(e): is the per capita safety provision cost function assumed increasing and convex
Pw: is the probability of suffering a work accident as perceived by the worker with
0 Pw 1
9
In view of relation (1), (1-e)Pwh is the potential worker loss which depends
on the safety effort and the hours worked. Furthermore, the cost of safety effort is
ultimately borne by the worker, through wage loss, as firms implement safety
regulations. Initially assume that h (hours of work supplied) is exogenous. The safety
regulator has different beliefs about job risk, Pr, and he/she is also aware of the
workers beliefs Pw. This simple framework can illustrate how the difference between
Pw and Pr affects the regulator’s safety effort. The regulators’ decision can be viewed
as aiming at the reduction of work accidents.
At this stage assume two types of regulators: Type 1 maximizes the workers’
welfare taking fully into account the workers’ beliefs concerning job risks. This
behaviour is analogous to respecting consumer sovereignty and is termed ‘populist’ in
the literature (Hird, 1994). Type 2 regulator maximizes the workers’ welfare taking
into account his/her own beliefs or assessment based on objective statistical evidence
concerning job risks. This behaviour is usually termed ‘paternalist’ and it is similar to
that described in the literature on merit goods (Besley, 1988; Sandmo, 1983;
Sunstein, and Thaler, 2003); Thaler and Sunstein, 2008). Type 1 regulator’s problem
is the following
max U(h, e, Pw) = u(h) – (1-e)Pwh – c(e) (2)
e
The solution yields the following expression
Pwh = c’(e) (3)
Expression (3) implies that the marginal benefit, as perceived by this type of
regulator, is equal to the marginal cost of safety effort. It is also clear that in the case
that the worker underestimates job risk, that is Pw < Pr, the regulator under-invests in
10
safety provision and technology compared to the case when Pw = Pr. In the context of
this study, this implies that the maximum risk imposed by type 1 regulator (the level
of the safety effort determines the level of the maximum risk), is lower than the actual
risk. In terms of Figure 1, the level of risk imposed, is lower than the objective r
1
and
as a result, the worker suffers a loss under this regulatory regime.
Type 2 regulator is assumed to have an objective risk assessment of statistical
probabilities of a work accident occurring and thus employs probability Pr. Then
his/her problem is the following
max U(h, e, Pr) = u(h) – (1-e)Prh – c(e) (3)
e
The solution yields the following expression
Prh = c’(e) (4)
Expression (4) implies that the marginal benefit as perceived by Type 2 regulator is
equal to the marginal cost of safety effort. Clearly, in this case, the paternalist policy
ignores the workers’ conceptions of job risk and imposes health and safety effort
which reflect the actual job risk probability r
1
, in Figure 1. Under this approach,
workers do not suffer a loss due to risk underestimation. The important implication
here is that the type of regulatory bahaviour is central in ensuring that workers do not
suffer welfare losses.
In most labour contracts, the hours of work are given. However, there are
cases when the workers can choose the hours of work as in the case of part time work.
This implies that workers may choose the hours worked in line with their perception
concerning job risk and safety effort level, thus h(e, Pw). In this case, for a given
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safety effort e, the worker chooses the hours spent at work h(e, Pw) to maximize
U(h, e, Pw). That is:
max U(h, e, Pw) = u(h(e, Pw)) – (1-e)Pwh – c(e) (5)
h
The solution yields the following expression
u’(h(e,Pw)) = (1-e)Pw (6)
Concavity of u(h) implies that relation (6) indicates that the optimal hours of work
supplied are decreasing in the perceived probability of having a work accident and
increasing in the level of safety effort. Thus, observed absenteeism may also be
influenced by the above factors. Indeed, evidence suggest that the highest absence
rates are observed in secondary sector occupations (Ose, 2005; Michie and Williams,
2003; Bokerman and Illmakunnas, 2008).
It is also interesting to investigate the response of the regulator when h is
endogenous. Type 1 regulator will take into account only the workers beliefs
concerning job risk, thus maximizes U(h(e, Pw), e, Pw) over the safety effort e. The
difference in the behaviour of Type 2 regulator in this case, is that when h is
endogenous, he/she has to take into account the workers’ beliefs about risk. Thus,
Type 2 regulator maximises U(h(e, Pw), e, Pr) taking into account his/her statistical
assessment of job risk but also the workers’ risk perception. If Type 2 regulator does
not consider Pw, thus completely ignoring workers’ beliefs, the regulator’s utility
function would be U(h(e, Pr), e, Pr). It is easy to see that the last policy is inefficient
because it cannot correctly anticipate the workers’ actual reaction and therefore it is a
sub-optimal policy (for an analysis of these issues in a general framework of beliefs
about risk, see Salanie and Treich, 2009).
12
Since the utility of hours of work supplied are linked with the level of
consumption, a specific functional form of quadratic utility for demonstration
purposes can be used. Following Romer, (2001) and Cantor, (1987), this can be:
u(h) = - 1/2(h*-h)
2
(7) and c(e) = 1/2 (e
2
)
(8)
With h* denoting the maximum hours of work. If it is assumed that the workers’
hours are exogenous, then Type 1 regulator maximizes (2) with (7) and (8) in mind.
The solution is
e
t1
= hPw (9)
By the same token, Type 2 regulator maximises (3) with (7) and (8) in mind. The
solution is
e
t2
= hPr (10)
A comparison of (9) and (10) illustrates the previous general conclusion that work
safety effort provided by Type 1 regulator will be lower than the one provided by
Type 2 regulator if workers underestimate job risk and vice versa.
In Figure 2, we can see the work safety effort provided by Type 1 and Type 2
regulators. It is clear that in the case when Pw < Pr, Type 1 regulator provides lower
safety effort than Type 2. Hence, the maximum job risk imposed by Type 1 regulator
is always lower than the one imposed by Type 2 regulator. Thus, workers suffer a loss
due to their job risk underestimation and the behaviour of Type 1 regulator.
(Figure 2 about here)
The behaviour of the worker and the regulator can be studied under an
endogenous choice of work hours regime. Specifically, given the above, the
13
individual worker’s optimal hours of work supplied are given by the solution of the
problem:
max U(h, e, Pw) = -1/2(h*-h)
2
– (1-e)Pwh - 1/2 (e
2
) (11)
h
which gives
h = h*-(1-e)Pw (12)
Relation (12) illustrates the general conclusion that the optimal work hours supplied
will be increased if the safety effort increases, and will be reduced if the workers’
concerns about job-related accidents increases.
Type 2 regulator maximizes (3) in the specific form given by (7) and (8).
Thus:
max U((h(e, Pw), e, Pr) = u(h) –(1-e)Prh – c(e)
e
s.t.
u(h) = -1/2(h*-h)
2
c(e) = 1/2 (e
2
)
h = h*-(1-e)Pw
The solution gives
h*Pr -2PrPw +Pw
2
e
t2
= ------------------------- Є[0,1] (13)
1-2PrPw +Pw
2
Expression (13) implies that the work safety effort provided by Type 2 regulator is
decreasing and then increasing with the workers’ belief towards job risk (Pw). The
minimum of relation (13) is at identical job risks beliefs when Pw = Pr. In Figure 3
14
we can see that Type 2 regulator’s safety effort is at a minimum only at identical job
risk assessments between the regulator and the workers. After this point, the safety
effort increases as the workers’ beliefs concerning job risk are increasing (for
illustrative purposes, h* has been normalized to unity).
(Figure 3 about here)
In contrast, Type 1 regulator maximizes:
max U((h(e, Pw), e, Pw) = u(h) –(1-e)Pwh – c(e)
e
s.t.
u(h) = -1/2(h*-h)
2
c(e) = 1/2(e
2
)
h = h*-(1-e)Pw
The solution gives:
Pw (Pw- h*)
e
t1
= ----------------- Є [0,1] (14)
Pw
2
- 1
As in the general case, Figure 4 shows that Type 1 regulator’s safety effort is lower
than Type 2 regulator’s effort up to Pw = Pr and increases in accordance with the rise
in workers’ conception of job risk (for illustrative purposes, h* has been normalized
to unity). Again, risk underestimating workers are suffering when Type 1 regulatory
policy is followed. Furthermore, the important implication is that in all cases the
difference in beliefs concerning job risks always calls for more regulatory
intervention even when the regulator follows a Type 2 policy (for a discussion of the
15
general case, see Salanie and Treich, 2009). Furthermore, this is independent of the
worker under-estimating the risk of a work accident.
(Figure 4 about here)
5. Conclusions
Research in psychology shows that individual perception about risk at work is
influenced by pre-existing, recent or readily available experiences. Specifically,
overestimation of personal immunity from harm has been shown to cause people to
often underestimate and/or overestimate risks. This systematic bias in risk of
accidents or illness at work underestimation makes the market solutions to OHS
provision guided by the theoretical constructions of the Compensating Wage
Differentials Theory ineffective in providing adequate OSH provision to those who
are exposed to such risks. This paper studied the repercussions for the implementation
of OSH and provided a discussion of the types and impact of regulation on health and
safety effort. In particular, given that workers are very likely to systematically
underestimate occupational risks, the paper examined the consequences of this
combined with the bahaviour of safety regulators. The discussion indicated that when
the safety regulator follows a policy entirely based on workers beliefs concerning job
risks, will always provide less safety effort than a safety regulator who takes into
account the objective risk probability too. This result holds for exogenous, but also
for endogenous, hours of work. In terms of the standard OSH framework, this
implies that the risk underestimating workers might suffer a loss even when there is
regulatory intervention which follows their beliefs.
16
Thus, this study indicates that a particular type of regulation is necessary for
an economy to attain efficient and equitable levels of OSH. The basis of this type of
regulation is the actual probability of occupational risk. In this sense, the regulatory
activity should take into account the objective probability of accident or illness at
work for the particular occupation, and intervene by setting appropriate health and
safety standards. Monitoring and enforcing these standards (by the imposition of
financial penalties or prosecution to non-compliers) seems to be necessary given the
observed tendency of workers’ job risk underestimation .
17
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20
Figure 1: The worker’s indifference curves and the wage offer curve by the employer
Figure 2: The work safety effort provided by Type 1 and Type 2 regulators when h
is given.
e
Pr
e
t1
e
t2
r
OC
U
1
U
0
w
w
0
r
0
r1
w’
r
max
r
1
Pw
Pw=Pr
21
Figure 3: Type 2 regulator’s safety effort when h is endogenous.
Figure 4: Type 1 regulator’s safety effort when h is endogenous.
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... According to Drakopoulos and Theodossiou (2016), underreporting of workplace occurrences skews employees' perceptions of risk and fosters a false sense of security that reduces attentiveness and safety compliance. Employees minimise workplace risks and participate in risky activities more frequently when they fail to report events. ...
... There are differing theories in the literature about this occurrence. While some researchers blame psychological biases for risk underestimation, others blame it on employer-driven concealment of event disclosures and weak reporting cultures (Drakopoulos & Theodossiou, 2016). By demonstrating how systemic underreporting influences safety awareness, our findings improve theoretical models on risk perception. ...
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Underreporting of workplace incidents is still a major problem in many developing countries, especially in blue-collar industries where safety and risk management deficiencies are still present. By raising safety standards, strengthening risk mitigation techniques, and promoting openness, occupational datasheets provide an organized method of resolving these shortcomings. In order to monitor workplace dangers, evaluate employee capacities, and direct focused actions, this review examines the function of standardized occupational datasheets. It finds important obstacles and chances to use data-driven insights to enhance safety procedures, rehabilitation techniques, and policy creation by examining the body of literature already available on occupational health and safety standards. The findings reveal that while datasheets significantly improve hazard identification and compliance, their adoption is hindered by limited digital infrastructure, lack of training, and resistance to change in traditional industries. Case studies highlight that firms utilizing structured safety documentation experience a measurable decline in workplace accidents and enhanced emergency response preparedness. To bridge the gap between developing countries and international workforce safety norms, the assessment also emphasises how important it is to connect incident reporting systems with best practices from throughout the world.
... Workplace accidents are multifaceted events influenced by various factors that can also predict other outcomes, such as health, job satisfaction, and absenteeism (Drakopoulos & Theodossiou, 2016). These incidents arise from a blend of personal and behavioral elements (Cheung, 2014;Sakina & Omar, 2018), organisational factors (Eskandari et al., 2017;Muchiri et al., 2019;Sawhney & Cigularov, 2018;Thurston & Glendon, 2018), and work or task-related elements (Mullen et al., 2017;Sawhney & Cigularov, 2018;Sheikhalishahi et al., 2017). ...
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... Thus, social contract theories posit that compliance with policies, rules, and regulations is a requisite for maintaining and establishing the secure and safe functioning of organisations and societies, although ensuring and encouraging compliance behaviours is a major challenge in many domains (Button 2008;Drakopoulos and Theodossiou 2016). Policymakers often choose to enforce compliance by punishing individuals for violations, or opt to promote it by providing information or monetary incentives. ...
... [7]. However, this could more likely be an employee's poor assessment or possible underestimation of the risks that such behavior causes in addition to poor assessment of the danger to their health [8]. If there is a risk of occupational disease, its negative consequences create the need to protect the community. ...
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Occupational safety and health is one of the main goals, as well as challenges, for employers, employees and the state. Although this issue is primarily viewed in the context of labor protection of employees, their protection in the field of social security should not be neglected. This aspect of employee protection is analyzed in the scientific and professional literature, but to a much lesser extent than labor law regulations. This paper analyzes the legal framework in Serbia that regulate the social and legal protection of employees against workplace injuries and occupational diseases. In addition to analyzing the existing legal solutions, we provide a critical review and give recommendations for their improvement.
... Social contract theories posit that policies, rules, and regulations are needed to maintain a social order among individuals, while policy compliance is commonly considered to be a requisite for the secure and safe functioning of organizations and societies (Button, 2008;Drakopoulos & Theodossiou, 2016). Therefore, ensuring compliance behaviors is a major challenge across domains, whether related to large-scale global problems, such as climate change and pandemics, or on local scales, such as those related to harassment in working organizations. ...
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The commonly applied strategies for promoting compliance with public health and safety policies can be inefficient and coercive, posing a need to examine novel motivational strategies to aid in this endeavor. Gamification, which aims to foster engagement and intrinsic motivation towards mundane activities and behaviors, is one of the vanguard design approaches among behavioral change support systems. Despite the increasing interest in gamification, the corpus lacks studies on its effects on policy compliance. Therefore, this study examines the relationships between gamification design types, gameful experience, and policy compliance in the social distancing context (during COVID-19) using a vignette-based online experiment (n=937). Based on the results, gameful experience mediates the positive relationships between achievement and progression-based, competitive, and immersive gamification and policy compliance, while social gamification is not associated with gameful experience. The results provide evidence of gamification's potential as a non-coercive method of helping people follow policies.
... Various sources have shown that workplace safety is a luxury good, that as non-labor income rises, workers choose safer jobs (Biddle and Zarkin 1988). Other relevant work includes Fishback and Kantor (1995), who show that costs of workplace safety are passed through to workers in the form of lower wages, and Drakopoulos and Theodossiou (2016), who show workers often underestimate job-associated risks. Other work has shown that workers prefer jobs with more amenities and lower wages in response to tax increases (Powell and Shan 2012). ...
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Black swan events are statistically rare occurrences that carry extremely high risks. A typical view of defining black swan events is heavily assumed to originate from an unpredictable time-varying environments; however, the community lacks a comprehensive definition of black swan events. To this end, this paper challenges that the standard view is incomplete and claims that high-risk, statistically rare events can also occur in unchanging environments due to human misperception of their value and likelihood, which we call as spatial black swan event. We first carefully categorize black swan events, focusing on spatial black swan events, and mathematically formalize the definition of black swan events. We hope these definitions can pave the way for the development of algorithms to prevent such events by rationally correcting human perception
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Job satisfaction is the result of an employee’s perception of their work and the impact of their actions, attitudes and values on personal and professional life. Potential consequences of job discontentment may include high staff turnover, increased absenteeism, alcohol or drug addiction, and accidents at the workplace. The article aims to develop a methodology for assessing employee job satisfaction to substantiate the cause-and-effect relationship between job satisfaction and the number of workplace accidents. The subject of the study is the Algerian Electricity and Gas Company in Hassi Messaoud, which employs more than 82 thousand employees and has more than 11 million electricity consumers and more than 7 million gas consumers. The study is based on a survey of employees of the operation and human resources departments, for which a random sample was formed, and 84.16% of the questionnaires were valid for analysis. The Cronbach’s Alpha coefficient was used to assess the internal consistency of the questionnaire, which professional experts reviewed. The SPSS statistical package was used to process the data. The study showed that among all dimensions of job satisfaction, the most important for the surveyed respondents were satisfaction with the leadership style and job stability, while less important were workload, satisfaction with the work environment, and remuneration. Future research is needed to examine the factors that will contribute to the reduction of workplace accidents; further efforts are needed to understand the many aspects that affect other sectors of the economy and different industries.
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Chapter
It is generally agreed that knowledge of the causes and consequences of a particular risk influences how people prepare for and respond to it. Ethnographic research in Potosí (Bolivia) shows however a more complex scenario, in which miners simultaneously face a number of physical and socio-economic risks and uncertainties which must be carefully weighed against each other. Miners often have little or no control over most of these risks that affect them, and health and safety risks are only a small group of concerns. Prone to take health risks at work as a strategy to manage other risks that simultaneously affect them, the Potosí's miners are well aware of the potential losses of taking these risks, but also of the potential gains of their decisions.
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Book
Ideally, individual risk‐taking decisions and government risk policies should be based on a rational balancing of risk and cost. Unfortunately, private decisions are subject to a number of biases including overestimation of small probabilities and alarmist responses to ambiguous risks. Hazard warnings can potentially be effective, but are not always ideal, as the people now overestimate the risks of smoking. Labour market estimates of the value of life can provide a rational reference point for benefit‐cost tests of risk regulations. The pressures exerted by irrational public responses to risk often lead to regulations that impose inordinately high costs per life saved. Excessive regulation potentially makes society worse off from a health and safety standpoint as shown by the risk–risk analysis methodology developed in this book. Similarly, liability rules and social insurance systems also should be structured to reflect an efficient balancing of risk and cost.
Chapter
By the mid-nineteenth century, Prussian miners could rely on their own mutual social insurance system in form of the so-called Knappschaft. This institution’s historical as well as economic importance stems from its continuous existence as an instrument of occupational provision against the risks of sickness and invalidity for nearly 750 years, and from its status as an influential precursor of the Bismarckian social insurance system. As part of the Prussian mining reform, the Knappschaft law of 1854 combined mandatory contributions for all miners with the insurance principle and legal claims, thereby creating one of the few occupational social insurance schemes that co-existed with Bismarck’s social insurance later on. The 1854 law just standardized for Prussia what miners had already practised before at different locations and with their own sense of mutuality. The reader will associate Knappschaften with other prominent institutions of the nineteenth century, especially with British Friendly Societies. However, Knappschaften were different in that joining a Knappschaft and thus paying contributions was compulsory for workers in covered activities. Membership in Friendly Societies was strictly voluntary in contrast, implying a different, perhaps stronger, sense of solidarity. This chapter examines a series of arguments concerning the ways in which the size of the Knappschaften affected their ability to satisfy their members’ needs. As we shall see, the societies’ primary functions were to provide different benefits for people experiencing short term illnesses (sickness insurance), long-term or disabling illness (invalidity pensions) or old-age (old-age pensions). It has often been suggested that smaller organizations were more suited to the provision of sickness insurance whereas larger organizations were required to deal with the demands of invalidity pensions and old-age pensions. We intend to explore these questions by testing two different, yet interrelated, hypotheses. The first hypothesis is that moral hazard in the KVs’ health insurance was less a problem for smaller funds, that is, that there was a positive relationship between size and moral hazard, and the second is that actuarial risk was less a problem for larger funds, because of a negative relationship between size and actuarial risk. We use data on Prussian and Bavarian KVs to examine these issues. The chapter includes five sections. In section 1, we begin by discussing the Knappschaften’s medieval origins and their development up to 1854, and the relevant regulatory framework and legal changes between 1854 and 1923. We then go on to examine the argument that the societies were characterized by a fundamental ‘design flaw’ associated with their size. In Section two, we present quantitative data that are central to our discussion of size as part of an overview of the Prussian KVs’ development in general. Section three makes the case for small KVs and moral hazard in health insurance. We first introduce moral hazard theoretically and discuss advantages of small organizations in fighting it. We then present empirical evidence on the relationship between size and moral hazard. The data we use are primarily for Prussia, and to a lesser extent, Bavaria. Section four makes the case for large KVs and actuarial risk. After having introduced the concept and measurement of actuarial risk, we present empirical evidence on the relationship between size and exposure to that risk. This part concentrates on Prussian KVs. Finally, Section five concludes the chapter.
Preprint
The German government introduced compulsory accident insurance for industrial firms in 1884. This insurance scheme was one of the main pillars of Bismarck’s famous social insurance system. The accident-insurance system achieved only one of its intended goals: it successfully compensated workers and their survivors for losses due to accidents. The accident-insurance system was less successful in limiting the growth of work-related accidents, although that goal had been a reason for the system’s creation. We trace the failure to stem the growth of accidents to faulty incentives built into the 1884 legislation. The law created mutual insurance groups that used an experience-rating system that stressed group rather than firm experience, leaving firms with little hope of saving on insurance contributions by improving the safety of their own plants. The government regulator increasingly stressed the imposition of safety rules that would force all firms to adopt certain safety practices. Econometric analysis shows that even the flawed tools available to the insurance groups were powerful, and that more consistent use would have reduced industrial accidents earlier and more extensively.
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This paper provides a systematic review of the economic analysis of health, safety, and environmental regulations. Although the market failures that give rise to a rationale for intervention are well known, not all market failures imply that market risk levels are too great. Hazard warnings policies often can address informational failures. Some market failures may be exacerbated by government policies, particularly those embodying conservative risk assessment practices. Labor market estimates of the value of statistical life provide a useful reference point for the efficient risk tradeoffs for government regulation. Guided by restrictive legislative mandates, regulatory policies often strike a quite different balance with an inordinately high cost per life saved. The risk-risk analysis methodology enables analysts to assess the net safety implications of policy efforts. Inadequate regulatory enforcement and behavioral responses to regulation may limit their effectiveness, while rising societal wealth will continue to generate greater levels of health and safety.