No.55

Does Harassment Prevention Law Reduce
Harassment in Workplaces?
Hiroyuki Motegi

Works Discussion Paper No.55
Does Harassment Prevention Law Reduce
Harassment in Workplaces? †Hiroyuki Motegi (Recruit Works Institute)

January 28th, 2022
Abstract
This paper analyzes the impact of harassment prevention laws on harassment in theworkplace using a unique Japanese survey dataset that provides information on
harassment. The harassment prevention laws went into effect only for large companies
in 2020, and I conducted difference-in-difference (DID) analysis using the institutionalchanges by controlling for unobserved macro shocks. The results showed that theharassment prevention law reduced harassment by about 7%.
Keywords Harassment, Harassment prevention law, Bullying, Sexual harassment,
Workplace

All contents and opinions in this discussion paper are the personal views of theauthor and do not represent the views of their organizations or Recruit Works
Institute.

†I would like to thank Ryo Kambayashi and seminar participants at Recruit Works

Institute and Recruit Co., Ltd. The views expressed in this paper are my own and do
not represent the views of organizations with which I am affiliated. Any remaining
errors and omissions are my own.
11

Introduction
Working conditions are detrimental to health and have been shown to increase individual

turnover and the probability of absence from work as shown Ose (2005) and Barnay (2016).1 Furthermore, Bubonya et al. (2017) show deterioration of mental health inﬂuences individual productivity, and also relate job satisfaction. While it has long been understood that poor health places aheavy burden on the aﬀected person and their family, it has now become an inevitable management
issue. Working conditions can be inﬂuenced by a number of factors, such as long working hours anddangerous work (Røed and Fevang, 2007), but one of the most important is bullying, or harassment.
It is not diﬃcult to imagine how harassment can worsen an individual’s health and reduce theirperformance at work. In the context of economics like Eriksen et al. (2016), harassment is also
known to cause a number of problems. The question of how to reduce harassment is an important
one in labour matters.
This paper evaluates the impact of the 2020 harassment prevention law in Japan on the presenceor absence of harassment. The law was prioritised for large companies, so that I apply diﬀerence-indiﬀerence (DID) for identiﬁcation strategy. In 2020, the spread of the coronavirus changed a numberof factors in the work environment. The DID method is suitable because it can eliminate unobserved
macro-shocks. The results show that the Harassment prevention law has reduced harassment byaround 7%. As the law has been in force for only six months at the time of the data collection, thissuggests that its impact is limited, but important. This results are robust against some assumptions
for DID identiﬁcation.
Although many people are aware of the importance of the issue of harassment in the workplace,there is very little research on this in the ﬁeld of economics except Eriksen et al. (2016).2 Theirresults show that gender does not signiﬁcantly explain exposure to bullying and that exposure to
bullying is associated with negative immediate self-reported health for both genders. Furthermore
they also ﬁnd that only bullied females have higher, persistent increases in long-term sickness absence
1

Pouliakas and Theodossiou (2013) summarized this literature.
There is an accumulation of research on harassment in ﬁelds other than economics. In psychology and industrial
psychology, for example, the impact of harassment on health, including mental health, has been studied in Kivimäki
et al. (2000), Kivimäki et al. (2003), and Vartia (2001). In management science, these behaviours have been interpreted
as a type of counter productive work behaviors or abusive leadership problem.
22

and adverse long-term health. Of the few that do exist, only a few papers have analyzed the impactof harassment on any outcomes such as Eriksen et al. (2016). None of the papers consider the
existence of harassment, for example, how it can be reduced. Especially, there is also little researchin the context of developed countries. However, research on harassment in developing countries,
has recently become well known, as global value chains (GVCs) have expanded rapidly since the2000s, and companies from developed countries have moved into developing countries. They has
had a positive impact on employment creation in developing countries (Barrientos et al., 2011),
and improved ﬁrm productivity and performance (Bustos, 2011), but in the process it has also been
criticized for creating unfavourable working conditions.3 For example, long working hours, low wages
and unsafe workplaces. There has been an increase in research on the impact of trade on working
conditions and, in turn, their impact on performance and productivity. Weziak-Bialowolska et al.
(2020), which is one of the few, addressed the prevalence of workplace harassment in the garment
industry in Mexico, Sri Lanka, China and Cambodia and the impacts of workplace harassment on
outcomes related to withdrawal from work (intentions to leave, quitting, and limited abilities toperform usual tasks), work attitudes (work engagement and job satisfaction) and self-reported work
quality. However, the structure of harassment in developing and developed countries is likely to be
diﬀerent and needs to be analyzed in developed countries.
The contribution of this paper is adding empirical results on bullying and harassment at workin the context of developed countries. In particular, it is probably the ﬁrst ever paper of antiharassment legislation in a developed country carefully evaluating causal impacts.
Harassment is also an important labour issue in Japan. Sexual harassment, long working hours
and bullying in the workplace have been the main concerns especially since 2018. Harassment has
become a social problem, with suicides sometimes resulting from it. It is also becoming a social
problem for companies as it is related to the reputation of the company and is seen as part ofmanagement issues. In addition, the number of consultations on labour problems at the Labour
Standards Supervision Oﬃce has more than doubled over the past 10 years, with harassment being
the most common type of consultations, whereas 10 years ago most consultations were on unfair
3
Tanaka (2020) shows that exporting has signiﬁcant positive impacts on working conditions regarding ﬁre safety,
health management, and freedom of negotiation.

3

dismissal and unpaid wages according to Ministry of Health and Welfare (2020). Of the total
number of consultations, harassment has the largest share, at 25.5% in 2019, compared with 13.9%
in 2010. In contrast, dismissals and unpaid wages have fallen from 35.3% to 20.5% over the same
period. Even in the Japanese context, there is little research on harassment, with the exceptionof Kawaguchi (2019), which analyzed maternity harassment, but the mechanism and other aspects
are diﬀerent from the harassment in other previous research.
The remainder of the paper is organized as follows: section 2 discusses the data and descriptive
statistics, and section 3 explains the institutional setting. Section 4 describes the identiﬁcation
strategy and estimation model, and section 5 discusses the estimation results. Section 6 provides
some additional remarks, and concludes the paper, with suggestions for further research.

2

Data
This paper uses the Japanese Panel Study of Employment Dynamics (JPSED), a panel survey

with a standard set of demographic and labor market variables that has been conducted by the
Recruit Works Institute every year since 2015. JPSED is a nationwide survey that is representativeof all men and women 3 over the ages of 15 years old and is conducted by an internet monitor
registered to Intage Corporation.4 The ﬁrst wave of the survey included 49,131 people, and while
JPSED has contracted and expanded through panel attrition and sample addition, it collects around50,000 observations each year. The surveys, which are conducted each January, ask about the work
situation in the previous month and previous year. For this study, we use the 2020 and 2021 wavesof the survey conducted from January 9-31, 2020, when the outbreak of COVID-19 in China had
been covered by the media but Japan was as yet virtually unaﬀected. The data for 2019 has notbeen aﬀected by COVID-19. This basic analysis sample consists of employed men and women whoseages are 20 years old or above and 70 years old or below because there is sample selection for older
age workers.
The key variable is harassment. The question about harassment for this survey is as follows “We
4

Kawaguchi and Motegi (2021) compared JPSED to the 2015 Census, paying particular attention to the gaps in
types of employment and the distribution of industries of workers. The distributions of these workers’ characteristicsof the 2019 JPSED are broadly similar to the distribution based on the 2015 population census.

4would like to ask you about your work at your workplace over the last year (January-December 2020).
Do any of the following apply at your workplace?” One of the questions was ”I had seen and heardof people in the workplace, including myself, being harassed or sexually harassed.” Respondents
can choose from the following ﬁve options, 1. applicable, 2. if anything, applicable, 3. I cannot sayeither, 4. if anything, not applicable, 5. not applicable. Survey responses are recorded on a 5-point
Likert scale ranging from not applicable to applicable, and we characterized those who responded
either “applicable” or “if anything, applicable” (1 or 2 on the scale) as workers for whom thatspeciﬁc conditions about harassment variable applies. In this survey, the unit of observation is theindividual. This time, the unit of observation is interpreted as the workplace. In other words, thisis an individual response, but this is because the individual captures the situation in the workplace.
According to this deﬁnition, harassment is considered to be subjective. A commonly used
deﬁnition of harassment is the NAQ-R (Negative Acts Questionnaire-Revised), a scale widely usedin workplace bullying literature such as Eriksen et al. (2016). The questionnaire measures various
negative actions (NA) such as ”Being ignored or excluded”. These are objective measures and areoften used in research. However, since there is no such objective information available for this study,
it remains on a subjective level. In other words, since it is a perception of harassment, it is strongly
correlated with individual heterogeneity. In the present analysis, we will use panel data to eliminate
such factors. Robustness check on the measurement of a variable with a deﬁnition using the original
numeric value before conversion to a Likert scale.
The spread of the new coronavirus was observed from 2019 to 2020. In this study, I use panel
data to remove such factors. One of the most important things is remote work. For those who wereable to work more remotely, harassment may have decreased because they did not have to observe
others in the workplace. In particular, according to Kawaguchi and Motegi (2021), there is a resultthat remote work is easier to do in large companies after COVID-19. In other words, there is a highpossibility that the number of harassment cases decreases in large companies, which are potentiallythe treatment group. Therefore, this time I will control remote work in detail. Speciﬁcally I set
two variables about deﬁnitions of remote work. The ﬁrst deﬁnition is those workers who actually
worked remotely in each year, while the second deﬁnition is the state of the remote work system at5

work and how it applies to respondent.5

3

Harassment prevention law in 2020
Harassment has become an issue in Japan since around 2018. This is partly due to the “MeToo” Movement, which was launched in the United States in 2017. It is also known that there isa close relationship between sexual harassment and workplace bullying. Also, in some companies,
harassment from superiors to subordinates has become an issue, with some subordinates committing
suicide. Harassment in the sports and education ﬁeld has also started to be regarded as a problem
following these news.
With the support of public opinion, the revised Law for Comprehensive Promotion of Labor
Policies (Law for Prevention of Power Harassment) was enacted in May 2019 and promulgated inJune. The Ministry of Health, Labor and Welfare (MHLW) led the implementation of this law. Thislaw deﬁnes harassment as “words or actions that are beyond the necessary and reasonable scope in
the course of work, based on a superior relationship, and that harm the work environment.” Thelaw came into eﬀect in June 2020 for large companies and April 2022 for small and medium-sizedcompanies. For small and medium-sized enterprises, it was made an eﬀort obligation until April
2022. Importantly, the law is a non-legally binding set of rules, a so-called soft law. However,they may play an important role in dealing with ambiguous concepts such as harassment, but theireﬀectiveness is unknown. There are no penalties for violating the law. If the Minister of Health,
Labor and Welfare deems it necessary, they can give advice, guidance, or recommendations toemployers. In other words, employers can damage the reputation of the company if they do notcomply with the law. The speciﬁc examples of harassment are (1) mental aggression, (2) physicalaggression, (3) excessive demands, (4) insuﬃcient demands, (5) disconnection from relationships,and (6) violation of individuality. In response to these trends, strict measures have been taken
against sexual harassment. Harassment can be described as a vague concept, but this law clariﬁes
the deﬁnition.
5

There are four options about company rules about remote work, from 1) the company sets the rule and it applies
to the respondent, 2) the company sets the rule but it does not apply to the respondent, 3) the company does not set
a rule, and 4) do not know.

6This paper will make use of this system change. In other words, large companies are considered
to be the treatment group and small and medium-sized companies are considered to be the control
group, and whether they have been treated before or after 2020 is determined. Figure 1 shows thetransition of harassment between large ﬁrms and small and medium-sized companies, and illustrates
this change to some extent. Figure 1 illustrates this change to a certain extent: between 2019and 2020, harassment has decreased more in large companies than in small medium enterprises.
Importantly, harassment has also decreased for small medium enterprises. There are several reasonsfor this. Firstly, small medium enterprises may be cracking down on harassment in preparation forthe law coming into force in 2022. The second possibility is that in 2020, due to the spread ofteleworking and other measures to combat the COVID-19, harassment will have decreased. In
addition, between 2017 and 2018 harassment increased in both large and small companies. Thismay be due to a change in attitudes. As mentioned above, there was a lot of media coverage ofharassment in 2018. There was also the ”Me Too” movement. In this survey, the question of what
constitutes harassment is subjective. In other words, it is possible that people who did not perceive
harassment as harassment before may have come to perceive it as harassment after 2018.

4

Estimations
This study estimates the eﬀects of harassment prevention law on seeing and hearing harassment

in workplace. The following equation was estimated:yigt = αLEg + γAf tert + βLEg × Af tert + xigt δ + θi + igt

(1)

where subscripts i, g and t indicate workplaces, group (large enterprise or small medium enterprise) and year respectively. The dependent variable yigt is a dummy variable taking one if thereis harassment in the workplace, which means workers see or hear harassment in their workplaces.
Treatment group is LEg in this study, where workplace observed by the workers belongs to large
enterprise. The time after the policy is implemented is deﬁned as Af tert . Covariates are described7

as xigt , which is a set of demographic variables including age and its square, working hours andindicator variables for remote work system. Since long working hours are likely to be closely linked
to harassment, we control for this. As for working hours, we mean individual working hours, but weadopted it as a variable in the sense that there is a certain correlation between individual working
hours and working hours in the workplace. There are two unobserved variables. θi is time invariant
unobserved term such as human resource management styles and corporate structure, also catches
up with individual unobserved factors, a perception of harassment, it is strongly correlated withindividual heterogeneity. In the present analysis, I will use panel data to eliminate such factors. igt
is unobserved error term including measurement error.
The target parameter is β capturing average treatment eﬀect on treated (ATT). Equation (1)is estimated by ﬁxed eﬀects methods. I need two assumptions for identiﬁcation, (1) common trend
assumption and (2) no compositional changes. These will be discussed again in the results section.

5

Results

5.1

Basic results: The eﬀects on harassment

The column (1) of Table 2 shows that there was an eﬀect of the treatment on harassment. The
column (2) shows that the treatment has an eﬀect on harassment, as estimated by the ﬁxed eﬀects.
The coeﬃcients are slightly attenuated. It means that unobservable factors may determine theworkplace where harassment is likely to occur and the characteristics of those who are likely toperceive it as harassment. The column (3) shows the results after carefully controlling for othervariables, such as remote work, and shows that, in any case, the harassment prevention law has
been eﬀective in reducing harassment. The impact was -0.015 percentage points, which is small
but not negligible at 7%, given that 22% of the respondents had no harassment.6 In addition, theHarassment prevention law is not a policy that will change rapidly after its implementation. In
other words, it is possible that the impact of the law will gradually spread from now on. Although
the impact of the law this time was only -0.015 percentage points, it is possible that the impact will
be even greater in a few years’ time.
6

This is calculated by -0.015/0.22.

8

The impact of harassment is also expected to vary by industry. In other words, there are someindustries where harassment is more prevalent than others because of the culture of the workplace.
The type of industry also aﬀects the degree of remote work. For example, Kawaguchi and Motegi(2021) and Dingel and Neiman (2020) prove that the degree of remote work diﬀers depending on
the industry. Therefore, I include industry ﬁxed eﬀects in our estimation. However, in any case,the size of the impact remains unchanged at -0.015. It can be said that the Harassment prevention
law had a certain eﬀect in deterring harassment.

5.2

Another deﬁnition of harassment

Next, as an important robustness check, we change the deﬁnition of harassment. This time,harassment has been converted from a ﬁve-point Likert scale into a binary variable. However,this ﬁve-point scale is a subjective variable and therefore diﬃcult to handle although diﬀerences inperception are removed by ﬁxed eﬀects. In the present study, therefore, we have tried to conduct
the same analysis by treating it as a continuous variable with ﬁve levels, although it is a subjective
scale in any case. The result is shown in clumn (1) in Table 3. There is a negative and signiﬁcant
impact, although the signiﬁcance level is weakened to around 10%. The impact itself cannot beinterpreted exactly, as the diﬀerence between 1 and 2 and between 3 and 4 is diﬀerent for eachvalue, but as it is negative and signiﬁcant, we can say that the Harassment prevention law has beenable to reduce harassment. A further robustness check is carried out in the next section.

5.3

Robustness check

Next, I conduct robustness check speciﬁc to DID estimation The ﬁrst is the common trend
assumption, i.e. the assumption that the treatment and control groups have, on average, the samechange in the period before and after the absence of the policy. Under the common trend assumption
during the periods t = {t , t} where t < t, t indicates a pre-treatment period, t indicates a posttreatment period, and yt indicates the outcome at period t, the following also holds:9

E(y0it − y0it |LEg = 1, xigt ) = E(y0it − y0it |LEg = 0, xigt )(2)This is tested using a placebo test. We check whether the trend in the year before the policy isequal. The results are shown in column (3) in Table 3. As can be seen, the results are not signiﬁcantand the assumption is fulﬁlled. However, it should be noted that this is not the case for time acrosspolicy years.
The next step is to check whether the composition changes between the previous and subsequent
years. First of all, it is unlikely that people will change their group after announcement of this policy.
As it is panel data, it is possible to check whether the workplace has been changed or not. Other
than announcement eﬀects, there will have been an outbreak of the COVID-19 and many people
will have lost their jobs or taken time oﬀ work in 2020. Furthermore, there may also be a selection
problem, as people who are harassed are more likely to leave the labour market in the ﬁrst place.
For this analysis, we exclude those who left or changed jobs in 2020. This will allow us to look atchanges in the same workplace. The results are shown in column (2) in Table 3. The signiﬁcanceof the results is not lost. The coeﬃcient changes by only 0.02. This means that those who left
the company may have seen and heard more harassment, which may have been a threat to theprocess described earlier. The result that the Harassment prevention law has been eﬀective has
been maintained.

5.4

Discussion

Once again, the Anti-Harassment Act has reduced harassment by 1.5 percentage points, or about
7% of the total. How are these estimates to be interpreted? Firstly, of course, they are the resultof companies cracking down hard on those who would harass them, in order to avoid damage totheir reputation. In particular, the fact that harassment is now prohibited by law is likely to makeit less tolerated by the public. It is also diﬃcult to deﬁne what constitutes harassment in the ﬁrst
place. The Anti-Harassment Act has clariﬁed what constitutes harassment. This has made it easierto reduce harassment.
10

Harassment has also decreased in small medium enterprises. This result can be interpreted
in two ways. The results can be interpreted in two ways: a reduction in workload due to thecoronavirus, or a reduction in social contact in order to maintain social distance. This has led toa decrease in harassment. The second possibility is that small medium enterprises are starting toprepare for the law, which will apply to them from April 2022. The law is not yet in force for small
medium enterprises, but they are obliged to make eﬀorts.

6

Conclusion
This paper analyzes the impact of harassment prevention laws on harassment in the workplaceusing a unique Japanese survey dataset that provides information on harassment. The harassment
prevention laws went into eﬀect only for large companies in 2020, and I conducted diﬀerence-indiﬀerence (DID) analysis using the institutional changes by controlling for unobserved macro shocks.
The results showed that the harassment prevention law reduced harassment by about 7%.
I conclude this paper with some suggestions of future research. The law is also likely to becompulsory in nature, causing companies to change their behavior gradually rather than uniformly.
Dynamic treatment eﬀects should be taken into account. This impact should be additionally veriﬁed
while the survey continues. From April 2022, the law will also apply to small medium enterprises.
New data should be added and validated when the law comes into force for small medium enterprises.
The staggered DID method should then be applied such as Callaway and Sant’Anna (2020) andGoodman-Bacon (2021) because the timing of the treatment is diﬀerent.

11

Table 1: Summary statistics
Small medium enterprise
mean
0.15
0.43
45.63
35.73
0.12
2.95
41831

Harassment
FemaleAgeWork hours
Remote work
Remote work institution
Observations

sd
0.36
0.49
14.76
15.72
0.32
0.65

Large enterprise
mean
0.22
0.40
41.70
37.77
0.14
2.70
31745

sd
0.42
0.49
13.16
13.08
0.35
0.85

Total
mean
0.18
0.41
43.93
36.61
0.13
2.84
73576

.1

Harassment
.15
.2

.25

Figure 1: Transition of seeing and hearing harassment

15

16

17

18

19

Year
Small medium enterprise
lb/ub

12

Large enterprise

20

sd
0.38
0.49
14.22
14.68
0.33
0.76

Table 2: The eﬀects of prevention law on harassment

Treatment

Control
Industry FE
Adjusted R2
Observation(1)
OLS
Harassment=1-0.019∗∗∗(0.006)(2)
FE
Harassment=1-0.015∗∗∗(0.006)(3)
FE
Harassment=1-0.015∗∗(0.006)(4)
FE
Harassment=1-0.015∗∗(0.006)

No

No

Yes

Yes

No
0.01
71,098

No
0.01
71,098No
0.01
70,902Yes
0.01
70,902

1. Standard errors are in parentheses and are heteroskedastic consistent and are robust against individual levels.
2. ∗ p < .10,∗∗ p < .05,∗∗∗ p < .01.
3. Coeﬃcients are average marginal eﬀects for all estimation methods.

Table 3: Robustness check(1)
FE
Harassment=1
Another deﬁnition-0.030∗(0.017)(2)
FE
Harassment=1
Not change job-0.013∗∗(0.006)(3)
FE
Harassment=1
Placebo test
-0.003(0.06)

Control

Yes

Yes

Yes

Industry FE
Adjusted R2
Observation

Yes
0.01
70,902Yes
0.01
58,759Yes
0.00
76,255Treatment

1. Standard errors are in parentheses and are heteroskedastic consistent and are robust against individual levels.
2. ∗ p < .10,∗∗ p < .05,∗∗∗ p < .01.
3. Coeﬃcients are average marginal eﬀects for all estimation methods.

13

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