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The Journal of Socio-Economics 40 (2011) 723731

Contents lists available at SciVerse ScienceDirect

The Journal of Socio-Economics

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s o c e c o

Socio-economic determinants of suicide in Japan

Antonio R. Andrs a,b,, Ferda Halicioglu c, Eiji Yamamura d

aAarhus University, Institute of Public Health, Bartholins All 1, 8000 Aarhus C, DenmarkbAssociate researcher, Institute of Economic Analysis & Prospective Studies (IEAPS), Al Akhawayn University, Ifrane, Moroccoc Department of Economics, Yeditepe University, 34755 Istanbul, Turkeyd Seinan Gakuin University, Department of Economics. Fukuokashi Sawaraku Nishijin 6-2-92, 814-8511, Japan

a r t i c l e i n f o

Article history:

Received 12 April 2011

Received in revised form 12 August 2011

Accepted 30 August 2011

JEL classification:

C22

I12

Keywords:

Cointegration

Suicide

Time series

Japan

a b s t r a c t

Japan has the highest suicide rates among the OECD countries and this public health problem seems

to be accelerating in over the recent decades. Investigating and understanding the suicidal behaviour

is of crucial importance to society and health policy makers. Such an investigation could provide with

useful information for those responsible in formulating the national policies on suicide prevention. This

study estimates dynamic econometric models for total, male and female suicides in Japan for the period

of 19572009. Using the ARDL approach to cointegration, we find that the associations of suicide with

sociological factors (divorce and fertility rates) were stronger than those with economic factors (per

capita GDP and unemployment) for females.

2011 Elsevier Inc. All rights reserved.

1. Introduction

Suicide is a very serious public health problem. The World

Health organization (henceforth, WHO) estimates that worldwide

there are approximately one million of deaths from suicide each

year and 20 times this number of people have attempted suicide.

According to many medical professions, suicide is considered to

be the result of depression and other psychiatric disorders ( Mann

et al., 2005). Although Japanese life span is the longest in the world,

it has nevertheless one the world highest suicide rates with nearly

33,000 people killing themselves in 2009. According to statistical

data from the WHO, Japan, in 2004, reports the highest suicide rate

with 24 per 100,000 people among the OECD countries. From 1995

to 2009, the total suicide rate increased from 17 to 25 per 100,000

people.1 Suicide is also associated with substantial economic costs

(with particularly health care costs). In particular, Chen et al.

(2009a) suggested that the costs associated with suicides werearound 197 million USDin 2006 alone even if indirect costs such as

psychological counseling expenditure were not takeninto account.

In comparison, there have been European studies highlighting

Corresponding author.

E-mail address: [email protected] (A.R. Andrs).1 Datasourceis asfollows.Periods 19552004:StatisticsBureau,MinistryofInter-

nalAffairs and Communications(2006).Historical Statisticsof JapanVolume1 (New

Edition). Tokyo: Japan Statistical Association. Periods 20052009: National Police

Agency. http://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.html (accessed

16.06.10).

the enormous costs of completed suicides. For instance in Ireland

(Kennelly et al., 2005), the total cost has beenshownto be 2.04mil-

lion Euros and in Scotland 1.88 million Euros (McDaid et al., 2007).

In some Japanese media, the total costs of suicide and depression

was reported to be about 2.7 trillion Yen in 2009 (available at

http://search.japantimes.co.jp/cgi-bin/nn20100908a2.html). Pre-

vention of suicide has been integral part of the Japanese public

health agenda. The Japanese Government aimed to reduce the

annual incidence of suicide and for this purpose implemented

the Basic Act of Suicide Prevention (jisatsu taisaku kihon hou)

in 2006. In addition, to the role of government, informal social

ties regarded as social capital is also thought to play an important

role in preventing suicide in Japan (Yamamura, 2010). In fact,

community based suicide prevention programs were introduced

in Akita prefecture (see Motohashi et al., 2004). For making the

policy effective, it is important to ascertain how and why suicide

rate of Japan is so high based on empirical analysis.Apart from the interest in describing and explaining suicidal

behaviour, employing rates of suicide as a societal well-being indi-

cator has several advantages. First, suicide rates are a more reliable

and objective indicator of well-being compared to self-reported

well-being measures (such as life satisfaction or self-reported hap-

piness). Second, suicide rates do not have the common problems

associated with survey data on self-reported well-being. Self-

reported measures are often challenged on the basis of reliability

and validity (see for an excellent discussion, see Bertrand and

Mullainathan, 2001). It has been also shown that there is a high

correlation between suicide andsubjective well-being at individual

1053-5357/$ see front matter 2011 Elsevier Inc. All rights reserved.

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http://localhost/var/www/apps/conversion/tmp/scratch_10/dx.doi.org/10.1016/j.socec.2011.08.002http://www.sciencedirect.com/science/journal/10535357http://www.elsevier.com/locate/socecomailto:[email protected]://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.htmlhttp://search.japantimes.co.jp/cgi-bin/nn20100908a2.htmlhttp://localhost/var/www/apps/conversion/tmp/scratch_10/dx.doi.org/10.1016/j.socec.2011.08.002http://localhost/var/www/apps/conversion/tmp/scratch_10/dx.doi.org/10.1016/j.socec.2011.08.002http://search.japantimes.co.jp/cgi-bin/nn20100908a2.htmlhttp://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.htmlmailto:[email protected]://www.elsevier.com/locate/socecohttp://www.sciencedirect.com/science/journal/10535357http://localhost/var/www/apps/conversion/tmp/scratch_10/dx.doi.org/10.1016/j.socec.2011.08.002

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724 A.R. Andrs et al. / The Journal of Socio-Economics 40 (2011) 723731

andaggregate level(for instance,Koivumaa-Honkanen et al.,2001).

Unlike as self-reported measures, suicide data is the kind of data

that is more prone to make cross country comparisons. Using self

reported data comparisons are still difficult because of problems

with interpersonal comparisons of utility. Recently, an American

study concluded that the determinants of well-being are the same

determinants of suicide (Daly and Wilson, 2009).

Despite of its importance, and a growing concern for the factors

driving suicide mortality, suicide in Japan has received little atten-

tion. Althoughthere have been some recent attempts,mainly using

panel data techniques, in this direction (e.g. Chen et al., 2009b;

Yamamura, 2010). Traditional theories of suicide (Durkheim, 1951;

Hamermeshand Soss,1974) havebeen tested using timeseries data

for a large number of countries (e.g. Yang, 1992; Yang and Lester,

1990; Yanget al.,1992; Chuang andHuang,1996; Platt andHawton,

2000; Stack, 2000; Chang et al.,2010). Someresearchers have inves-

tigatedthe socioeconomicdeterminants of suicide usingtime series

data for Japan (Yamasaki et al., 2005, 2008). There are however

few studies which employ causality or cointegration framework

to investigate the causality between suicide and its socioeconomic

determinants. A recentstudyis that ofInagaki (2010) who employs

a Vector Autoregressive (VAR) model. But this methodology has

several shortcomings. First, this methodology requires the set of

variables to be split into exogenous and endogenous variables. Sec-ond, the variables should be integrated of order 1.

This study aims at contributing to the empirical studies of

Japanese suicide by applying a relatively new time series cointe-

gration technique known as the Auto Regressive Distributed Lag

(ARDL) bounds testing procedure. The ARDLapproach to cointegra-

tion is preferable to other conventional cointegration procedures

(Engle and Granger, 1987). One of the reasons for preferring the

ARDL approach to cointegration it is that overcome the problem

of potential endogeneity of some regressors and serial correlation,

which might lead to biased estimates of the cointegrating coef-

ficients. Another reason is that this technique does not require

pre-testing forthe order of integrationof theunderlying timeseries.

Moreover, theresults from this approach to cointegration are more

robust in presence of small samples (such as in this study) thanin other cointegration techniques. Finally, as opposed to multivari-

ate cointegration techniques such as Johansen and Juselius (1990),

it allows the cointegration relationship to be estimated by ordi-

nary least squares (OLS) once the lag order of the model is chosen.

In addition to studying the total suicides, we also analysed male

and female suicides separately, as the underlying determinants of

suicide could differ between the sexes (e.g. Andrs, 2005; Chuang

andHuang, 2007; Yamamura, 2010). Understanding the gender dif-

ferences might be also important in informing appropriate policy

formulations. The remainder of this paper is organized as follows.

The next section presents the socio-economic situation of Japan

relatingto thesuicides.Section3 describes our empiricalmodel and

methodological approach. Section 4 displays our empirical results

along with some discussions. Section 5 is the conclusion.

2. Review of the socio-economic situation of Japan

Total life expectancy at birth of Japanese is 82 years old, which

leads the world in longevity (WHO, 2006; Nakao and Takeuchi,

2006). However, suicide rate is obviously higher than other OECD

countries, which becomes the one of major problem in the modern

Japan society (Chen et al., 2009b). Japans suicide problem is very

different from those of other OECD countries because the impactof

the socioeconomic variables on suicide is greater in Japan than in

other OECD countries (Chen et al., 2009b). To implement appropri-

atesuicide prevention policies, it is importantto ascertainhow and

why suicide rate of Japan is so high based on empirical analysis. In

Fig. 1. Changes of per capita GDP.

what follows, we begin with a simple description of the potential

socio-economic factors affecting suicidal behaviour.

As shown in Fig. 1 illustrating changes of real per capita income,

Japan has experienced the rapid economic growth in the post war

period and became among the most developed countries. Japanese

people enjoyed the rise in income and are thought to be satisfied

with this life style change accompanied with economic growth.

Concerning the growth rate of real per capita GDP, it drops con-stantly andto belowzeroseveraltimesafter 1990s.We canseefrom

Fig.2 that the unemploymentratehas been also lowlevel until mid-

1990s, however,exceeded3% aftermid-1990s. This seemsto reflect

the depression period after 1992 when the prosperity of the bub-

ble economy (from mid 1980 to the beginning of the 1990s) came

to an end in Japan. In this period, number of business bankruptcies

also steeply increased in this period because of macro level eco-

nomic stagnation. In particular, it was difficult for owners of small

and medium size enterprise to run business. Economic recession

lead a lot of people to face the difficulty and suffer distress.

Transition of divorce rate in Fig. 3 shares similarity with unem-

ployment rate in the point that after entering the recession period

divorce rate remarkably increased. The increase in divorce rate can

be in part caused by the economic recession. Marriage leads coupleto be integrated into the new social network, which is expressed

as when you get married, you get married for the people around

you (Brinton, 1993, p. 99). Hence, divorce seems to be more stig-

matized in Japan than in the Western countries because of the

greater importance of extended familyand kinship ties in marriage

(Ono, 2006). That is, people who encounter the economic difficulty

morelikely to experience divorce andso losethe psychological sup-

port from family and kinship ties. During the economic depression

period, not only economic difficulty but also social stigma caused

by divorce lead people to suffer from increase of distress in Japan.

In Japan, over 60%of the individuals committingsuicide were iden-

tified as depressive (Nakao and Takeuchi, 2006).

Fig. 2. Changes of unemployment rate (%).

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A.R. Andrs et al. / The Journal of Socio-Economics 40 (2011) 723731 725

Fig. 3. Changes of divorce rate (%).

Fig. 4 shows that rates of suicide has obviously decreased from

mid 1950s to 1970, and then slightly increased until mid-1990s

for males and females. For example, in Korea with the similar

socio-cultural background, the remarkable increase of suicide rate

from 1997 to 1998 under the economic recession period (Khang

et al., 2005). However, in case of Korea, not only male but also

female suicide rate increased. It is surprising to observe that in

the end of 1990s suicide rate of male has drastically increasedwhereas that of female was stable. According to Fig. 4, there was

a marked rise in female suicide rates from 1997 to 1998 although

its magnitude was smaller than for male suicide rates. Indeed, in

late 1997, Hokkaido Takushoku Bank (one of major commercial

banks) and Yamaichi Securities (one of Major securities) became

bankrupt. Further 1998, The Long Term Credit Bank of Japan and

the Nippon Credit Bank were nationalized, implying the old eco-

nomicregimes failure (Cargill, 2006). Taken together, these results

imply that the problem of committing suicide became remarkably

serious, especially for males. The question arises why is there dif-

ference of suicide rate between male and female?. An imbalance

of increases in suicide appears to come from the different impact

of various factors between males and females. As pointed out by

Nakao and Takeuchi (2006), the most drastic increase has involvedmiddle-aged males partly because most middle-aged males may

be too busy to visit a clinic when they feel mental distress. There-

fore, the case of Japan is suitable for examining how committing

suicide depends upongenderand differences in the impact of socio-

economic factors.

3. Literature review

3.1. International experience

Sociologists have played an important role in providing the

theory of suicide. Durkheim (1951) viewed the suicide as a soci-

Fig. 4. Changes of rate of suicides. Note: Number of total suicides per total popula-

tion (100,000), number of male suicides per male population (100,000), number of

female suicides per female population (100,000).

ological phenomenon. He argues that suicide is related to both

social integration and social regulation. Economists claim that sui-

cide involves rational economic decision making. Hamermesh and

Soss (1974) were the first to provide an economictheory of suicide.

According to theireconomic model an individual decides to commit

suicide when the discounted expected lifetime utility remaining to

him falls below some threshold level. This model also predicts that

suicide rateswould increase withage, unemploymentand decrease

with income (Hamermesh andSoss, 1974). Recently, Suzuki (2008)

incorporates the concept of income uncertainty within the model

ofHamermesh and Soss (1974). These approaches (sociological and

economics) motivate many of the control variables included in a

variety of econometric studies of macro level determinants of sui-

cide.

According to theHamermesh andSosss model, thehigherfuture

expected income is, the higher is the expected utility; thus, living

is relatively more attractive than committing suicide, and a higher

income should lower suicide rates. However, Durkheim postulates

that higher income levels increase independence (the opposite of

social integration)and might leadto a higher suicide rate.Alongthis

line, Lester (1996) and Unnithan et al. (1994) state that economic

development increases rates of suicide. Both the existing economic

and sociological theories are inconsistent, and they do not permit

a determination of whether income or economic growth may havea positive or negative effect on suicide. Durkheim (1951) suggests

that changes in income are more likely to be relevant for suicide

than the absolute level of income. The empirical evidence for the

effectof income onsuicide is mixed,however. Thoughsomeempir-

ical studies indicate that suicide rates have a positive association

with income (e.g. Hamermesh, 1974; Jungeilges and Kirchgssner,

2002; Viren, 1999), there are many others suggesting the opposite

effect (e.g. Andrs, 2005; Brainerd, 2001; Neumayer, 2003; Chuang

and Huang, 1997, 2007; Minoiu and Rodrguez, 2008; Altinanahtar

and Halicioglu, 2009; Andrs and Halicioglu, 2010). Others have

reported an insignificant effect of income on suicide (Ruhm, 2000;

Cuellar and Markowitz, 2006). The significant negative correlation

effect seems to be stronger for men than for women Qin et al.

(2003).Another economic variable that has received a lot of attention

is the unemployment rate. Unemployment implies less economic

opportunity, lowering an individuals expected income and there-

fore increasing the likelihood of a persons committing suicide.

The unemployment rate is often used as a proxy variable for

economic hardships and lifetime earnings, because measuring an

agents lifetime income is not easy in practice (Koo and Cox, 2008).

But unemployment might be also associated with factors such

as depressive episodes, anxiety, and loss of self-confidence that

might lead directly to suicide. Much of the empirical literature

reports a positive relationship, associating higher unemployment

withhighersuiciderates (forexample,Brainerd,2001;Ruhm, 2000;

Chuang and Huang, 1997, 2007; Lin, 2006; Andrs, 2005; Koo and

Cox, 2008; Minoiu and Rodrguez, 2008). Furthermore, the impactof unemployment might also differ across gender. In particular,

male suicide rates are significantly affected by unemployment, but

female suicide rates are not (Chuang and Huang, 1997).

As mentioned above, Durkheim (1951) indicates that suicide is

influencedby other factors. These factors relateto theway in which

individuals are integrated into a social group that is regulated by

norms and conventions. This sociological approach predicts that

lowerlevels of social integration and regulation are associated with

higher societal suicide rates. From this perspective divorce andfer-

tilityratescan be viewed as indicators of socialintegration. Divorce

can be also a traumatic event for the individuals involved as well

as for other affected parties, and it might lead individuals toward

isolation and reduced poor psychological well-being. Thus, higher

divorce rates might be expected to have a positive correlation with

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suicide rates. Another explanation is that a divorced individual has

lower utility than a married one because marriage has a merce-

nary value (Becker, 1974). Koo and Cox (2008) also suggest that

divorced people have less utility than married people and there-

fore they are more likely to commit suicide. Several studies have

reported a positive association between divorce and suicide (e.g.

Andrs, 2005; Chuangand Huang, 1997, 2007; Kunce andAnderson,

2002; Lester, 1996; Neumayer, 2003). Also, some papers show that

the male suicide rate is more sensitive to divorce than the female

suicide rate (e.g. Koo and Cox, 2008; Andrs, 2005; Yamamura,

2010; Neumayer, 2003). Again, endogeneity concerns are relevant

here, as divorce might be also related to mental healthproblems. It

should be also noted that this variable might capture the influence

of diverse societal problems.Durkheimianarguments of social inte-

gration suggest that increased fertility rates should be associated

with lower levels of suicide, as the presence of children promotes

social and family ties. By increasing social integration, these factors

lower the likelihood of a persons committing suicide. Empirical

research hasdocumented theexistence of a protective effectof fer-

tility against suicide (e.g. Andrs, 2005; Neumayer, 2003; Chuang

and Huang, 2007). However, some studies like Chen et al. (2009b)

and Lester (1995) show that the birth rate has either a positive

impact or no impact on suicide rates. One possible explanation for

the latter result is that childcare may put excessive strain on a par-ent or be too much of an economic burden, thus leading to suicidal

behaviour (Chen et al., 2009b). Endogeneity issues might be rel-

evant here, as better functioning people are more likely to have

children.

Lastly, the gender differences in suicide representa double puz-

zle: Whilst rates of suicide are far higher among males, females

have higher rates of non-fatal attempts. This suggests there maybe

different responses by males and females to the control variables

used in the formalanalysis. In light of thegender differential in sui-

cidal behaviour (e.g. Minoiu and Rodrguez,2008; Altinanahtar and

Halicioglu, 2009; Andrs, 2005; Yamamura,2010), we runseparate

models for males and females. Although the cause of these differ-

ences has not been sufficiently investigated (Yamamura, 2010).

In sum, the formal literature provides ambiguous results on thewayssocioeconomic factors relate to male and female suicide rates.

The existing literature has not come to a firm conclusion about the

correlates of suicide. This is due to different countries employed in

the empirical analysis, more points of the time, and the statistical

techniques employed (time series/cross-section analysis). Never-

theless, of all the variables considered, the results correspondingto

social factors such as divorce and fertility seem to be more robust

than those related to economic factors such as unemployment and

income. Nonetheless, the socio-economic control variables used in

this paper appear to be among the relatively important determi-

nants.

4. Japanese experience

Although, the epidemiological literature has explored the risk

factors of suicide in Japan (e.g. Yamasaki et al., 2008; Motohashi

et al., 2004), there are a few studies exploring the determinants of

suicide in Japan from an economic perspective (Watanabe et al.,

2006; Koo and Cox, 2008; Akechi et al., 2006; Chen et al., 2009b;

Yamamura, 2010; Inagaki, 2010). Watanabe et al. (2006) using

prefecture level data find that unemployment rate and personal

bankruptcy are positively associated with suicide rates. Koo and

Cox (2008) usingtime series datafind thatthe relationship between

unemployment and suicide is significantly positive for males and

females. Akechi et al. (2006) shows that there is an inverted U

shape between alcohol consumption and suicide employing pre-

fecture level data between 1953 and 1986. Chen et al. (2009b)

employing a panel data approach by using Japanese data and

OECD data analyse to what extent suicide in Japan is different

from suicides in other countries. Inagaki (2010) using time series

focuses on the link between income inequality and suicide. He

finds a positive relationship between income inequality proxied

by the Gini index and suicide rates. Kuroki (2010) is the most

recentpaper using Japanese data at municipality level. He provides

evidence that unemployment has a positive significant effect on

male suicide rates and that this effect differs across age groups,

in particular, the largest effect is found in the 5564 age group.

He also finds a negative effect of unemployment on female sui-

cide rates. That is, higher unemployment is associated with lower

female suicide rates. They conclude that the impact of socioeco-

nomic factors on suicide in Japan is greater than in OECD countries.

Lastly, Yamamura (2010) using panel data at prefectural level

suggests that social capital and divorce have an impact on sui-

cide rates and that these effects are different between males and

females. This leads us to anticipate that sociological factors plays

more critical role on determining on suicide rates than other

countries.

Unlike previous studies of suicide in Japan, this work employs

a new recently methodological approach using time series data to

examine how suicide is related to socio-economic factors in Japan

as in the short as well as in the long run. This approach is morerobust in presence of small samples, and allows us to account for

potential endogeneity of the variables included in the empirical

model. Endogenity issues might lead to misleading results in past

empirical studies.

5. Model and methodology

Following the empirical literature on suicide (for an extensive

reviewof the literature, seeLester andYang, 1997), we form the fol-

lowing long-run relationship between suicide, per capita income,

unemployment rate, divorce rate, and fertility variables in linear

form as:

stj = a0 + a1yt+ a2utj + a3dt+ a4ft+ t (1)

where the subscript tindexes time period with t= 1957, . . ., 2009;

j indexes each suicide with j = 0 (total), 1 (male), and 2 (female);

st is suicide rate; yt is per capita real income; ut is the unemploy-

ment rate; dt is the divorce rate; ft is the fertility rate; and t istheclassical error term. All variables are in their natural logarithms

which allow us interpreting the estimated coefficients as constant

elasticities.

Recent advances in econometric literature dictate that the long-

run relation in Eq. (1) should incorporate the short-run dynamic

adjustment process. It is possible to achieve this aim by expressing

Eq. (1) in an error-correction model, known as the EngleGrangers

(1987) approach.

st,j = b0 +

m1

i=1

b1i,jsti,j +

m2

i=0

b2iyti +

m3

i=0

b3iuti,j

+

m4

i=0

b4idti +

m5

i=0

b5ifti + t1 +t (2)

where represents change, is the speed of adjustment param-eter, and t1 is the lagged error term, which is estimated from

the residuals of Eq. (1). The EngleGranger method requires that

all variables in Eq. (1) are integrated of order one, I(1), and that

the lagged error term is integrated order of zero, I(0), in order to

establish a cointegration relationship. If some variables in Eq. (1)

are non-stationary, we may use a new cointegration method. This

procedure is known as ARDL approach to cointegration of Pesaran

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etal. (2001) thatcombines EngleGranger twosteps procedureinto

one by replacing t1 in Eq. (2) with itsequivalent from Eq. (1). t1is substituted by linear combination of the lagged variables as in

Eq. (3):

st,j = c0 +

n1

i=1

c1i,jsti,j +

n2

i=0

c2iyti +

n3

i=0

c3iuti,j

+

n4

i=0

c4idti +n5

i=0

c5ifti + c6st1,j + c7yt1

+ c8ut1,j + c9dt1 + c10ft1 + vt (3)

To obtain Eq. (3), one has to solve Eq. (1) for t and lag the solu-

tion equation by one period. Then, this solution is substituted fort1 in Eq. (2) to arrive at Eq. (3). Eq. (3) is a representation of theARDL approach to cointegration.

Pesaran et al. (2001) approach to cointegration has some

methodological advantages in comparison to other single cointe-

gration procedures. They are as follows: (i) endogeneity problems

and inability to test hypotheses on the estimated coefficients in

the long-run associated with the EngleGranger (1987) methodare avoided; (ii) the long and short-run parameters of the model

in question are estimated simultaneously; (iii) the ARDL approach

to testing for the existence of a long-run relationship between the

variables in levels is applicable irrespective of whether the under-

lying regressors are purely I(0), purely I(1), or a combination of

the two; (iv) the small sample properties of the bounds testing

approach are far superior to that of multivariate cointegration, as

argued in Narayan (2005).

The bounds-testing procedure is based on the F- or Wald-

statistics, and this is the first stage of the ARDL cointegration

method. Accordingly, a joint significance test that implies no

cointegration hypothesis, (H0: c6 = ...... = c10 = 0), against the

alternative hypothesis, (H1: at least one of c6 to c10 /= 0), should

be performed for Eq. (3). The F-test used for this procedure has anon-standard distribution. Thus, Pesaran et al. compute twosets of

critical values for a given significance level with andwithouta time

trend. One set assumes that all variables are I(0), and the other set

assumes that they are all I(1). If the computed F-statistic exceeds

the upper critical bounds value, then the H0 is rejected. If the F-

statistic falls into the bounds, then the test becomes inconclusive.

Lastly, if the F-statistic is below the lower critical bounds value, it

implies no cointegration.

Once a long-runrelationshiphas been established, Eq. (3) is esti-

mated using an appropriate lag-selection criterion. At the second

stage of the ARDL cointegration procedure, it is also possible to

obtain the ARDL representation of the error-correction (EC) model.

To estimate the speed with which the dependent variable adjusts

to independent variables within the bounds-testing approach, fol-lowing Pesaran et al.(2001), the lagged-level variables in Eq. (3) are

replaced by ECt1 as in Eq. (4):

st,j = 0 +

k1

i=1

1i,jsti,j +

k2

i=0

2iyti +

k3

i=0

3iuti,j

+

k4

i=0

4idti +

k5

i=0

5ifti + ECt1 +t (4)

A negative and statistically significant estimation of not only

represents the speed of adjustment but also provides an alternative

means of supporting cointegration between the variables.

Table 1

Unit root results.

Variables ADF PP ERS

st,0 2.66 2.21 1.46

st,1 2.85 2.43 1.43

st,2 2.35 1.98 1.78

yt 1.50 1.23 0.31

ut,0 2.58 2.94 1.53

ut,1 2.51 3.05* 1.54

ut.2 2.63 2.62 1.52dt 3.14 2.59 2.56*

ft 1.89 2.28 1.67

st,0 4.07* 6.24* 4.11*

st,1 3.97* 5.96* 3.71*

st,2 4.15* 6.67* 3.81*

yt 2.79 3.08* 2.52*

ut,0 4.33* 5.16* 3.73*

ut,1 4.54* 5.65* 3.66*

ut,2 4.19* 5.12* 4.20*

dt 3.29* 3.98* 2.28

ft 6.64* 12.3* 5.44*

Notes: Sample levels are 19582009 and differences are 19592009. The critical

values for ADF and PP with a constant and without a trend at the 5% level of signifi-

cance are 2.91. The critical value for ERS with a constant and without a trend at the

5% level of significance is 2.29. All test statistics and critical values are expressed in

absolute terms for convenience. Rejection of unit root hypothesis is indicated with

an asterisk. stands for first difference.

6. Results

Annual data over the period 19572009 were used to estimate

Eq. (3) by the ARDLcointegration procedureofPesaran et al. (2001).

Variable definitions and sources of data are provided in Appendix.

To implementthe Pesaran et al.(2001) cointegrationprocedure,

one has to ensure that none of the explanatory variables in Eq.

(1) is above I(1). In the presence of I(2) or higher variables, the

computed statistics provided by Pesaran et al. (2001) are not valid.

Consequently, the implementation of unit root tests in the ARDL

approach is necessary to ensure that none of the variables included

in the model is integrated of order 2 or beyond. Three tests were

used to test unit roots in the variables: Augmented DickeyFuller

(henceforth, ADF) (1979, 1981), PhillipsPerron (henceforth, PP)

(1988), and ElliottRothenbergStock (henceforth, ERS) (1996).

Unit root tests results are displayed in Table 1. The conditions for

applying the ARDL bounds testing approach are satisfied. In other

words, all variables included in the model are either I(0) or I(1).

Table 2

The results ofFand Wtests for cointegration.

95% LB 95% UB 90% LB 90% UB

Panel A: The assumed long-run relationship: F/W(s0

y, u0,d, f )F-statistic

5.30 3.10 4.35 2.60 3.74

W-statistic

26.51 15.52 21.75 13.01 18.70

Panel B: The assumed long-run relationship: F/W(s1

y, u1,d,f )F-statistic

6.54 3.10 4.35 2.60 3.74

W-statistic

32.72 15.52 21.75 13.01 18.70

Panel C: The assumed long-run relationship: F/W(s2

y, u2,d, f )F-statistic

3.46 3.10 4.35 2.60 3.74

W-statistic

17.31 15.52 21.75 13.01 18.70

If theteststatistic lies between thebounds, thetestis inconclusive. If it is above the

upper bound (UB), the null hypothesis of no level effect is rejected. If it is the below

the lower bound (LB), the null hypothesis of no level effect cannot be rejected.

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Table 3

ARDL cointegration results.

Regressor Coefficient Standard error T-ratio

Panel A: Estimated long-run coefficients using the ARDL approach for aggregate suicide model: ARDL (1,1,1,0,1) selected based on the Akaike Information Criterion,

19572009

Dependent variable st,0yt 0.4106* 0.1397 2.9385

ut,0 0.2024 0.1922 1.0533

dt 0.8832* 0.3990 2.2134

ft 0.7003**

0.3352 1.7134Constant 0.3437 1.4435 0.8130

Panel B: Error correction representation results


ut,0 0.0586 0.0095 0.6116

dt 0.3709* 0.1301 2.8501

ft 0.0575 0.1222 0.4712

ECt1 0.4199* 0.1057 3.9714

Diagnostic tests

R2 0.41 F-statistic 8.89* 2SC

(1) 0.06 2FF

(1) 0.73

RSS 0.12 DW-statistic 1.94 2N

(2) 19.26 2H

(1) 2.49

RSS stands for residual sum of squares. T-ratios are in absolute values. 2SC

, 2FF

, 2N

, and 2H

are Lagrange multiplier statistics for tests of residual correlation, functional form

mis-specification, non-normal errors and heteroskedasticity, respectively. These statistics are distributed as chi-squared variates with degrees of freedom in parentheses.

The critical values for 2(1) = 3.84 and 2(2) = 5.99 are at 5% significance level. ***Significance at 10% level.* Significance at 1% level.

**

Significance at 5% level.

Visual inspections of the variables in logarithm show no structural

breaks.

Eq. (3) is estimated in two stages. In the first stage of the ARDL

procedure, the long-run relationship of Eq. (1) was established

in two steps. First, the selection of the lag length on the first-

differenced variables for Eq. (3) was obtained from unrestricted

Vector Autoregression (VAR) by means of Akaike Information cri-

teria (AIC) and the Schwarz Bayesian Criterion (SBC). The results

suggest the optimal lag length as 2, but this stage of the results is

not presented here to conserve space. Second, a bound F-test was

applied to Eq.(3) in order to determinewhetherthe dependentand

independent variables are cointegrated in each model. The resultsof the bounds F-testing are reported in Table 2. From Table 2, it can

bee seen that the computed Fstatistics are above the upper bound

values inthe casesof total andmalesuicidesmodels thus,implying

cointegration relations.

The ARDL cointegration procedure was implemented to esti-

mate the parameters of Eq. (3) with maximum lag-order set to 2,

which is selected on the basis of AIC, SBC and R2 selection criteria.This stage involves estimating the long-run and short-run coeffi-

cients of Eqs. (1) and (2).

The summary ARDL results with some diagnostic tests for

total suicides, male suicides, and female suicides are presented in

Tables 35, respectively. The overall empirical results appear to be

rather satisfactory. First, income enters negatively in the regres-

sions for overall, male, and female suicides. The long-run elasticity

of suicide with respect to income is highest in the case of male sui-

cides. This is

0.54, suggesting that one per cent increase in percapita income will decrease the number of male suicides by 0.54%

whilst other factors remain constant. The long-run income elastic-

ities with respect to total and female suicides are0.41 and0.36,

respectively. This finding implies that males are more vulnerable

Table 4



Panel A. Estimated long-run coefficients using the ARDL approach for male suicide model: ARDL (1,1,0,0,0) selected based on the Schwarz Bayesian Criterion, 19572009


ut,1 0.0133 0.1755 0.7581

dt 1.1635* 0.4030 2.8870

ft 0.0456 0.1716 0.2661Constant 2.3613** 1.2274 1.9239

Panel B. Error correction representation results


ut,1 0.0560 0.0812 0.6890

dt 0.4896* 0.1382 3.5428

ft 0.0192 0.0712 0.2697

ECt1 0.4208* 0.0944 4.4551

Diagnostic tests


(1) 0.34 2FF

(1) 1.31


(2) 18.10 2H

(1) 2.41


, 2FF

, 2N

, and 2H



The critical values for 2(1) = 3.84 and 2(2) = 5.99 are at 5% significance level. ***Significance at 10% level.* Significance at 1% level.

**

Significance at 5% level.

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Table 5



Panel A. Estimated long-run coefficients using the ARDL approach for female suicide model: ARDL (1,0,0,0,1) selected based on the R-Bar Squared Criterion, 19572009


ut,2 0.0197** 0.3431 1.7628

dt 0.8844 0.6168 0.2570

ft 0.4974* 0.4241 2.0300

Constant 0.6752 2.8321 0.2384

Panel B. Error correction representation results

Dependent variable st,2yt 0.0869*** 0.0565 1.5367

ut,2 0.0046 0.0818 0.0570

dt 0.2091** 0.1127 1.8552

ft 0.1197 0.1251 0.9564

ECt1 0.2364* 0.0899 2.6297

Diagnostic tests


(1) 0.48 2FF

(1) 1.10


(2) 22.41 2H

(1) 0.16


, 2FF

, 2N

, and 2H



The critical values for 2(1) = 3.84 and 2(2) = 5.99 are at 5% significance level.* Significance at 1% level.

** Significance at 5% level.

*** Significance at 10% level.

to income loss than females. However, the magnitude of this effect

is rather minimal. Second, unemployment rates are positively and

significantly associated with female suicides. The long-run partial

elasticity of suicides with respect to unemployment rates is 0.01,

indicating that a 1% rise in unemployment rates will trigger an

increase infemale suicides by about 0.01%.Although there seems to

bethe almostsameimpactexists inthe case ofthe male suicides but

that is not statistically significant. Hence one argues broadly that

the impact of male and female unemployment rates on suicides is

identical. Gender seems to have no special effect on a suicide deci-

sion, whenan individual becomes unemployed. Third, divorce rates

are positively correlated with suicides but are statistically insignif-

icant in the case of female suicides. Male population appears to besuffering more as a result divorce since the long-run elasticity of

divorce rate with respect to male suicides is 1.16, suggesting that

a 1% increase in divorce rates will rise the male suicides by 1.16%

which is the stronger determinant of suicide in the entire analy-

sis. Finally, we find a statistically significant negative association

between fertility rates andsuicides only in the case of the total sui-

cides. Thus, a 1% rise in the total fertility rates will drop the total

number of suicides by 0.70 whilst the other explanatory factors are

constant. The long-run elasticities of suicides in respect to fertil-

ity for male and female suicides appears to be in wrong signs. In

regards to the relative magnitude of the explanatory variables in

this study, the fertility rate seems to be the second most important

factor in explaining suicides, followed by real per capita income

and unemployment rates.Tables 35 also report the coefficients of coefficients of ECt1

the error correction model. All coefficients of ECt1 are statis-

tically significant and have the negative expected sign in all

models. This situation provides further confirmation for cointe-

gration relationships between variables of total and male suicides

models as well as suggesting an alternative means of long-run

relationship in the case of female suicide model. The magnitude

of the speed of equilibrium is relatively low, since their values

are less than 0.5. The lowest error correction coefficient appeared

in the female regression model, which means that about 25% of

disequilibrium is corrected every year. As the suicide is a long-

term phenomenon, the short-run elasticities will have no real

impact in policy designing therefore we are not evaluating them

further.

7. Summary and conclusions

This paper,from a socioeconomic point of view, investigates the

determinants of suicides in Japan for the time span between 1957

and 2009. Unlike earlier studies, this paper employs a relatively

recent econometric procedure, the ARDL approach to cointegra-

tion, which has been utilized to obtain the long-run elasticities of

the suicides with respect to the total, male and female suicides.

To our knowledge, this paper is the first paper to apply an ARDL

approach to examine the determinants of suicide in Japan. This

approach seems to have several potentialadvantages as it needs no

a large number of observations to guarantee the robustness of the

estimators and performance of the statistical tests. Furthermore,the choice of the suicide static model could influence the analysis.

Individuals might respond withsome delayed to changes in socioe-

conomic factors. In this case, suicides are explained by current and

lagged differenced values of realper capita income,unemployment,

and divorce rates.

We show that in the long run, the divorce is the highest suicide

cause and the Japanese men seem to be suffering particularly from

this situation. The second most important determinant of the sui-

cidesin Japan is alsoa sociologicalfactor,fertility rates. As expected,

the female population are more affected with the decreasing level

of fertility rates. Combining these two suicide causes, one may

argue that sociological factors are more dominant than economic

factors in the case of Japanese suicides, which is inconsistent with

Chen et al. (2009b). This might be partly because that Chen et al.(2009b) uses the panel data of OECD countries to make a compari-

sonbetween Japan and other OECD countries. Forrobustness check

of this paper by comparing Japan and other OECD countries, it is

required to use time series data of other OECD countries to conduct

ARDL estimation in the future studies. Furthermore, the economic

determinants of suicides in Japan appear to be moderate in mag-

nitude and similar in both sexes indicating that male and female

participation to work and sharing the burden of economic diffi-

culties are almost the same. Our results support the existence of a

longrun relationship between socio-economicfactorsand suicides,

regardless of gender.

Finally, recommendations for suicide prevention are generally a

combination of strategies targeting high-risk groups and strategies

targeting a whole population. The findings of this study reveal that

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government policies should promote family cohesion and provide

economic incentives to raise birth rates, as these policies will be

effective in lowering suicide rates.

Acknowledgements

The authors are grateful to an anonymous referee for his/her

useful commentsand suggestions on an earlier version of thiswork.

Appendix A. Appendix

Data Definitions and Sources

All data were collected online with the provided internet links

below:

st,j arecrude suicide rates fortotal,male and females per100,000

in logarithm.

Source: Period 19552004: Statistics Bureau, Ministry of Inter-

nal Affairs and Communications (2006). Historical Statistics

of Japan Volume 1 (New Edition). Tokyo: Japan Statisti-

cal Association. Period 2005-2009: National Police Agency.

http://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.html

(accessed 16.06.10).

yt is per real capita income in logarithm. Base year is 1990.Source: Period 19552003: Statistics Bureau, Ministry of Inter-

nal Affairs and Communications (2006). Historical Statistics of

Japan Volume 1 (New Edition). Tokyo: Japan Statistical Association.

Period 20042009: Cabinet office of Government of Japan.

http://www.esri.cao.go.jp/jp/sna/qe101-2/gdemenu ja.html

(accessed 16.06.10).

ut,j are unemployment rates for total, male and females in loga-

rithm.

Source: Period 19552009: Statistics Bureau, Ministry of

Internal Affairs and Communications. http://www.stat.go.jp/

data/roudou/longtime/03roudou.htm#hyo 1 (accessed 16.06.10).

dt is divorce rate per 1000 in logarithm.

Source: Period 19552003: Statistics Bureau, Ministry of Inter-

nal Affairs and Communications (2006). Historical Statistics of JapanVolume 1 (NewEdition). Tokyo: JapanStatisticalAssociation.Period

20042009: Ministry of Health, Labour, Welfare.

http://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/

index.html (accessed 16.06.10).

ft is fertility rate per 1000 in logarithm.

Source: Period 19552003: Statistics Bureau, Ministry of

Internal Affairs and Communications (2006). Historical Statis-

tics of Japan Volume 1 (New Edition). Tokyo: Japan Statistical

Association. Period 20042009: Ministry of Health, Labour, Wel-

fare. http://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/

index.html (accessed 16.06.10).

References

Akechi, T., Iwasaki, M., Uchitomi, Y., Tsugane, S., 2006. Alcohol consumption andsuicide among middle aged men in Japan. British Journal of Psychiatry 188,231236.

Altinanahtar, A., Halicioglu, F., 2009. A dynamic econometric model of suicide inTurkey. Journal of Socio-Economics 38, 903907.

Andrs, A.R., 2005. Income inequality, unemployment, and suicide: a panel dataanalysis of 15 European countries. Applied Economics 3, 439451.

Andrs, A.R., Halicioglu, F., 2010. Determinants of suicides in Denmark: evidencefrom time series data. Health Policy 98, 263269.

Becker, G., 1974. A theory of marriage. In: Schultz, T.W. (Ed.), Economics of theFamily. University of Chicago Press, Chicago, pp. 299344.

Bertrand, M., Mullainathan, S., 2001. Do people mean what they say? Implicationsfor subjective survey data. American Economic Review 91, 6772.

Brainerd, E., 2001. Economic reform and mortality in the former Soviet Union:a study of the suicide epidemic in the 1990. European Economic Review 45,10071019.

Brinton,M.C.,1993. Women andthe EconomicMiracle:Genderand Workin Postwar

Japan. University of California Press, Berkley.

Cargill, T.F., 2006. Japans economic and financial stagnation in the 1990 and reluc-tance to change. In: Blomsrom, M., La Croix, S. (Eds.), Institutional Change in

Japan. Routledge, London.Chang, S.S., Sterne, J.A.C., Huang, W.C., Chuang, H.L., Gunnell, D., 2010. Association

of secular trends in unemployment with suicide in Taiwan, 19592007: a timeseries analysis. Public Health 124, 4954.

Chen, J.,Choi,Y.J.,Mori,K., Sawada, Y.,Sugano, S.,2009a. Those whoare left behind:an estimation of the number of family members of suicide victims in Japan.Social Indicators Research 94, 535544.

Chen, J., Choi, Y.J., Sawada, Y., 2009b. How is suicide different in Japan? Japan andthe World Economy 21, 140150.

Chuang, H.L.,Huang,W.C., 1996.A reexaminationof sociological andeconomictheo-ries ofsuicide:a comparison oftheUSA andTaiwan.SocialScienceand Medicine43, 412423.

Chuang, H., Huang, W., 1997. Regional suicide rates: a pooled cross-section andtime-series analysis. Journal of Socio-Economics 26, 277289.

Chuang, H.,Huang, W.,2007.A re-examination of thesuicide ratesin Taiwan. SocialIndicators Research 83, 465481.

Cuellar, A.E., Markowitz, S., 2006. Medicaid Policy Changes in Mental Health Careand Their Effect on Mental Health Outcomes. NBER Working Papers No. 12232.

Daly, M., Wilson, D.J., 2009. Happiness, unhappiness and suicide: an empiricalassessment. Journal of the European Economic Association 7, 539549.

Dickey, D.A., Fuller, W.A., 1981. Likelihood ratio statistics for autoregressive timeseries with a unit root. Econometrica 49, 10571072.

Dickey, D.A., Fuller, W.A., 1979. Distributions of the estimators for autoregressivetime series with a unit root. Journal of the American Statistical Association 74,427431.

Durkheim, E., 1951. Suicide: A Study in Sociology. Free Press, New York.Elliott, G., Rothenberg, T., Stock, J., 1996. Efficient tests for an autoregressive unit

root. Econometrica 64, 813836.

Engle, R.F., Granger, C.W., 1987. Cointegration and error correction: representation,estimation and testing. Econometrica 55, 251276.

Hamermesh, D., 1974. The economics of black suicide. Southern Economic Journal41, 188199.

Hamermesh, D.S.,Soss,N.M.,1974. An economictheoryof suicide.Journalof PoliticalEconomy 82, 8398.

Inagaki, K., 2010. Income inequality and the suicide rate in Japan: evidence fromcointegration and LA-VAR. Journal of Applied Economics 13, 113133.

Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inference oncointegration with application to the demand for money. Oxford Bulletin ofEconomics and Statistics 52, 169210.

Jungeilges, J., Kirchgssner, G., 2002. Economic welfare, civil liberty, and suicide: anempirical investigation. Journal of Socio-Economics 31, 215231.

Kennelly, B., Ennis, J., OShea, E., 2005. Economic cost of suicide and deliberateself harm. In: Reach out National Strategy for Action on Suicide Prevention20052014. Department of Health and Children, Ireland.

Khang, Y.H., Lynch, J.W., Kaplan, G.A., 2005. Impact of economic crisis on cause-specific mortality in South Korea. International Journal of Epidemiology 34,

12911301.Koivumaa-Honkanen, H., Honkanen, R., Viinamki, H., Heikkil, J., Kaprio, J., Kosken-vuo, M., 2001.Life satisfaction and suicide: a 20-year follow-upstudy. American

Journal of Psychiatry 158, 433459.Koo, J., Cox, W.M., 2008. An economic interpretation of suicide cycles in Japan.

Contemporary Economic Policy 26, 162174.Kunce, M.,Anderson, A.L.,2002. Theimpact of socioeconomicfactorson statesuicide

rates: a methodological note. Urban Studies 39, 155162.Kuroki, M., 2010. Suicide and unemployment in Japan: evidence from municipal

level suicide rates and age specific suicide rates. Journal of Socio-Economics 39,683691.

Lester, D., 1995. Explaining regional differences in suicide rates. Social Science andMedicine 40, 719721.

Lester, D., 1996. Patterns of Suicide and Homicide in the World. Nova Science Pub-lishers, New York.

Lester, D., Yang, B., 1997. The Economy and Suicide: Economic Perspectives. NovaScience Publishers, New York.

Lin, S.J., 2006. Unemployment and suicide: panel data analyses. Social Science Jour-nal 43, 727732.

McDaid, D.,Halliday,E., McKenzie, M.,MacLean,J., Maxwell, M.,McCollam, A.,Platt,S.,Woodhouse, A., 2007.Issuesin theEconomicEvaluation of Suicide PreventionStrategies: Practical and Methodological Challenges. Personal Social ServicesResearch Unit, LSE, London.

Mann, J.J., Apter, A., Bertolote, J., Beautrais, A., Currier, D., Haas, H., Hegerl, U., Lon-vquist, J., Malone, K., Marusic, A., Mehlum, L., Patto, G., Phillips, M., Rutz, W.,Rihmer, Z., Schmidtke, A., Shaffer, D., Silverman, M., Takahashi, Y., Varnik, A.,Wasserman, D., Yip, P., Hendin, H., 2005. Suicide prevention strategies: a sys-tematic review. Journal of American Medical Association 294, 20642074.

Minoiu, C., Rodrguez, A., 2008. The effect of public spending on suicide: evidencefrom US state data. Journal of Socio-Economics 37, 237261.

Motohashi, Y., Kaneko, Y., Sasaki, H., 2004. Community based suicide preventionprogrammein Japanusing a health promotion approach. Health and PreventiveMedicine 9, 38.

Nakao,M., Takeuchi,T., 2006.The suicide epidemic in Japanand strategiesof depres-sion screening for its prevention. Bulletin of the World Health Organization 84,492493.

Narayan, P.K., 2005. The saving and investment nexus for China: evidence fromcointegration tests. Applied Economics 37, 19791990.
http://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.htmlhttp://www.esri.cao.go.jp/jp/sna/qe101-2/gdemenu_ja.htmlhttp://www.stat.go.jp/data/roudou/longtime/03roudou.htm%23hyo_1http://www.stat.go.jp/data/roudou/longtime/03roudou.htm%23hyo_1http://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.mhlw.go.jp/toukei/saikin/hw/jinkou/suikei09/index.htmlhttp://www.stat.go.jp/data/roudou/longtime/03roudou.htm%23hyo_1http://www.stat.go.jp/data/roudou/longtime/03roudou.htm%23hyo_1http://www.esri.cao.go.jp/jp/sna/qe101-2/gdemenu_ja.htmlhttp://www8.cao.go.jp/jisatsutaisaku/link/keisatsutyo.html

7/27/2019 1-s2.0-S1053535711000904-main

9/9


Neumayer,E., 2003. Socioeconomic factors and suicide ratesat large-unitaggregatelevels: a comment. Urban Studies 40, 27692776.

Ono, H., 2006. Divorce in Japan: why it happens, why it doesnt. In: Blomsrom, M.,La Croix, S. (Eds.), Institutional Change in Japan. Routledge, London.

Pesaran, M.H., Shin, Y., Smith, R., 2001. Bounds testing approach to the analysis oflevel relationships. Journal of Applied Econometrics 16, 289326.

Phillips, P.C.B., Perron, P., 1988. Testing for a unit root in time series regression.Biometrika 75, 335346.

Platt, S.,Hawton,K., 2000.In: Hawton,K., vanHeeringen,K. (Eds.),SuicidalBehaviourand the LabourMarket,in theInternationalHandbookof Suicide and AttemptedSuicide. John Wiley & Sons, Ltd., Chichester, UK, pp. 309384.

Qin, P., Agerbo, E., Mortensen, P.B., 2003. Suicide risk in relation to socioeconomic,demographic, psychiatric, and familial factors: a national register based studyof all suicides in Denmark. American Journal of Psychiatry 160, 765772.

Ruhm,C., 2000.Are recessionsgood foryour health? Quarterly Journal of Economics115, 617650.

Stack, S.,2000. Suicide: a 15-year review of thesociological literature. PartI: culturaland economic factors. Suicide and Life-Threatening Behavior 30, 145162.

Suzuki, T., 2008.Economicmodelingof suicide underincomeuncertainty: forbetterunderstandingof middle-aged suicide.Australian EconomicPapers47, 296310.

Unnithan, N.P., Huff-Corzine, L., Corzine, J., Whitt, H.P., 1994. The Currents of LethalViolence:An Integrated Modelof Suicide and Homicide.State Universityof NewYork Press, Albany.

Viren, M., 1999. Testing the natural rate of suicide hypothesis. International Journalof Social Economics 26, 14281440.

Watanabe, R., Furukawa, M., Nakamura, R., Okura, Y., 2006. Analysis of the Socioe-conomic Difficulties Affecting the Suicide Rate in Japan. KIER Discussion PaperSeries. No. 626.

WHO, 2006. Mortality Country Fact Sheet 2006.Yamamura, E., 2010. The different impacts of socio-economic factors on suicide

between males and females. Applied Economics Letters 17, 10091012.Yamasaki,A., Araki,S., Sakai,R., Yokoyama,K., Voorhees, A.S.,2008.Suicidemortality

of young, middle aged and elderly males and females in Japan for the years,19531996: timeseries analysisfor theeffectsof unemployment, female labour

force, young and aged population, primary industry and population density.Industrial Health 46, 541549.

Yamasaki, A., Sakai, R., Shirakawa, T., 2005. Low income, unemployment, and sui-cide mortality rates for middle-age persons in Japan. Psychological Reports 96,337348.

Yang, B.,1992.Economyandsuicide:a time seriesstudy ofsuicide in USA. AmericanJournal of Economics and Sociology 51, 187199.

Yang, B., Lester, D., 1990. Time series analyses of the American suicide rate. SocialPsychiatry and Psychiatric Epidemiology 25, 274275.

Yang, B., Lester, D., Yang, C.H., 1992. Sociological and economic theories of sui-cide: a comparison of the USA and Taiwan. Social Science and Medicine 34,333334.

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