Are Socioeconomic Factors Valid Determinants of Suicide?

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http://ccr.sagepub.com/content/37/3/307The online version of this article can be found at:

DOI: 10.1177/1069397103253708

2003 37: 307Cross-Cultural ResearchEric Neumayer

with Fixed-Effects Estimationre Socioeconomic Factors Valid Determinants of Suicide? Controlling for National Cultures of Su

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10.1177/1069397103253708 ARTICLECross-CulturalResearch / August2003Neumayer/CULTURESOFSUICIDE

Are Socioeconomic FactorsValid Determinants of Suicide?Controlling for NationalCultures of Suicide WithFixed-Effects Estimation

Eric NeumayerLondon School of Economicsand Political Science

National cultures of suicide have found renewed interest in the re-cent literature on variation in suicide rates. Fixed-effects estima-

tion controls more elegantly and comprehensively for such cultures

than other approaches used in the existing literature. This articlesanalysis employs a range of economic and social explanatory vari-ablesbasedoneconomicaswell asDurkheimiansociological theoryin fixed-effects and random-effects estimation of age-standardized

suicide rates in a large panel ofup to 68 countries during the period1980 to 1999. The results suggest that economic and social factors

affect cross-country differences in suicide rates in accordance withtheory. Importantly, the fixed-effects estimation results do not dif-

fer systematically from the random-effects results. This suggeststhat thevast majority of theexisting literature,which typicallyfails

to control for national cultures of suicide and suggests socioeco-

nomic factors as important determinants of suicide, can still be ex-pected to come to valid results.

307

Cross-Cultural Research, Vol. 37 No. 3, August 2003 307-329DOI: 10.1177/1069397103253708

2003 Sage Publications

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Keywords: suicide; national cultures; socioeconomic factors;Durkheim; fixed effects; random effects

In recent contributions to the voluminous literature on cross-national differences in suicide rates, the concept of a national cul-ture of suicidehas received new interest. One can define the con-cept as theextentto which deeplyentrenched culturallysharedat-titudes exist within nation states that are either supportive orrestrictive toward the act of committing suicide. Quite possibly,such attitudes are contingent on the contextual circumstances inwhich individuals take their lives. Such national cultures can beexpected to influence the decision on whether to take ones life by

some individuals and therefore to have an influence on aggregatesuicide rates as well. Whereas Hendin (1964) already addresseddifferences in thenational cultures of suicide among Scandinaviancountries in his case studies,attempts to control for this phenome-non in quantitative research are of a veryrecent nature. One of thereasons for this failure to control for national cultures of suicide inthe vast majority of the existing literature is the lack of quantita-tive data measuring such attitudes.

The main objectives of this article are twofold. First, we willshow that fixed-effects estimation can more elegantly control forthe potential existence of a national culture of suicide than any ofthe other methods employed so far (see Fernquist and Cutright(1998), Cutright and Fernquist (2000, 2001)). Second, we will test

whether controlling for national cultures of suicide changes thesigns and statistical significance of the socioeconomic determi-nants of suicide typically employed in quantitative studies. If thiswas the case, then failure tocontrol for a national culture of suicidewould lead to biased estimates and therefore misleading conclu-sions, which would put doubt on past studies failing to control forsuchcultural differences.Wewill showthat this is not the case andthat cross-national studies of suicide, which fail to control fornational cultures of suicide, can still be expected to arrive at unbi-ased results.

A NATIONAL CULTURE OF SUICIDE?

The strongest evidence in favor ofa fixed national culture of sui-cide that varies across countries stems from the fact that, asKrupinski (1980) observed, countries of a very similar social

308 Cross-Cultural Research / August 2003



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structure have marked differences in suicide rates (p. 262). Forexample,in 1998 Swedenhada total age-standardized suicide rateof 12.73 per 100,000 inhabitants, whereas the rate of Finland wasalmost double at 22.69. The Czech Republic had a rate of 14.63,whereas Hungarys rate was more than double at 29.89 (WHOEurope,2002).Suchstarkdifferences cannotbe explainedwith dif-ferences in social and economic characteristics alone.

Most existing studies simply ignore the issue,and Cutright andFernquist (2000,2001;Fernquist& Cutright,1998) canbe creditedfor trying various approaches to control for a national culture ofsuicide. The obvious one is to try to find proxy variables for a cul-ture of suicide, for example, a control variable for social approval

toward the justifiability of suicide. Cutright and Fernquist (2001)include such a variable,which stemsfrom theWorld Values Survey(Inglehart et al., 2000). The problem with this approach is thatthese data are only available for a very restricted number of coun-tries. Furthermore, it assumes that the culture of suicide can besufficiently well measured by stated approval rates of the general

justifiability to the act of committing suicide,where no allowance ismade for the fact that such attitudes might depend on the contex-tual circumstances in which individuals take their lives. Anotherapproach is taken by Cutright and Fernquist (2000), who usederrors of prediction as a proxy for the culture of suicide.The idea isthat positive errors of prediction suggest a culture that is moreacceptingof suicide than the predictions based on the control vari-

ables would suggest, whereas negative errors of prediction wouldsuggest a culture that is more condemning of suicide. This repre-sents a rather cumbersome way of controlling for a culture of sui-cideand faces the problem that the errors ofpredictioncan be vola-tile and actually are somewhat volatile for some countries inCutright and Fernquists (2000) study, whereas the culture of sui-cide by definition is very persistent. For our 20-year period of anal-ysis, one can even justifiably assume it to be constant as a firstapproximation. A third approach is to include regional dummy

variables as also done by Cutright and Fernquist (2000). The prob-lem with this is that countries need to be put together into regionsand it is assumed that the culture of suicide is the same in all coun-tries of the region. Rather than simply assuming this, one wouldprefer to test for it.

Fixed-effects estimation offers a much more elegant way of con-trolling for a fixed national culture of suicide. It allows each

Neumayer / CULTURES OF SUICIDE 309



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country to have its own fixed effect and therefore its own culture ofsuicide. Hence, there is no need to group countries together intoregions with a supposedly shared culture. Formally, the fixed-effects estimator is derived from estimating the following model:

yit = + xit + t + ai + uit

Time is indicated by t, countries are indicated by i, y is the sui-cide rate per100,000 people, is a constant,xcontains theexplan-atory variables, is the corresponding vector of coefficients to beestimated. The variables are T-1 period-specific dummy vari-ables. Their inclusion lets each time period have its own intercept

to allow for aggregate time effects such as a secular change in sui-cide rates that affect all countries. The ai represents individualcountry effects,whicharecaptured by country dummyvariables. Ifnational cultures of suicide are as a first approximation time-invariantwithinthetime span of ouranalysis,thentheir existenceis captured by these dummy variables. Failure to include the fixedeffects leadstobiasedestimatesof ifxis correlated with theai.

1

The fixed-effects estimator has two main advantages for tack-ling the potential incidence and impact of a national culture of sui-cide. First, inclusion of fixed effects ensures that the coefficients oftime-varying variables are free from bias even if they are corre-lated with the fixed effects. Second, to see whether the nationalfixed effects would actually bias our estimations if they were not

controlled for, one can compare the results from the fixed-effectsestimatorwiththosefromtheso-calledrandom-effectsestimator.

The random-effects estimator uses both the cross-sectional(between) and time-series (within) variation of the data. However,it depends on theassumption that thecountry effects arenotcorre-lated with theexplanatory variablesso that theindividual countryeffects ai can beregardedas partofa composite error termvit = (ai +uit ).This random-effects assumption canbe testedwith a so-calledHausman test. This tests whether the coefficients estimated by arandom-effects estimator systematically differ from the coeffi-cients estimated by a fixed-effects estimator for those variablesthat can be estimated with the fixed-effects estimator. If this test

rejects the hypothesis that the coefficients do not systematicallydiffer from each other, then we know that thecountry-specific fixedeffects bias the estimations of the time-varying determinants of

variation in suicide rates in a systematic manner.




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Although fixed-effects estimation represents an elegant way tocontrol for national cultures of suicide, given that these are time-invariantandthereforefixed in first approximation, it suffers froman important drawback. The drawback is that there can be otherfixed effects that have nothing to do with a culture of suicide.Because fixed-effects estimation wipes out all time-invariant vari-ables, these other fixed effects cannotbe estimated either. It wouldtherefore be wrong to attribute all the variation in suicide ratesexplained by the country dummy variables, usually quite a sub-stantial part of overall variation explained, to differences innational cultures of suicide. The random-effects estimator allowsestimation of time-invariant variables, which theory suggests as

further determinantsof suicide other than national cultures of sui-cide. We will therefore employ both fixed-effects and random-effects estimation.

THEORETICAL REFLECTIONS ON

THE DETERMINANTS OF SUICIDE

To see which variables we need to include in our analysis, wereview the sociological and economic literature trying to explaindifferences in suicide rates with differences in social and economic

variables.Most of the modern sociological theory of suicide is basedon Durkheims (1897/2002) groundbreaking study on suicide, inwhich he argues that suicide is a phenomenon with a dominantly

social explanation (p. iv). For him, thekeyto understanding varia-tion in suicide rates lies in the extent towhich individuals are inte-gratedintoa socialgroup aswellasregulated byits norms and con-

ventions. Egoistic suicide occurs when individuals lose touch withsocial groups (family, religious communities, society at large).

Anomic suicide occurs when the social group and their norms andconventions lose control over the individual, but egoistic andanomic suicide are usually merely two different aspects of onesocial state (Durkheim,1897/2002,p.251).2 He develops a numberof testable hypotheses that he subjects to empirical analysis withthe help of descriptive suicide statistics from mainly France andGermany.

Following Durkheimian analysis, we would expect, forexample,that the (lack of) integration of individuals into the family and theconsequent lack of social regulation represents an importantdeterminant of suicide: Higher marriage and fertility rates should




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be negatively associated with suicide rates and higher divorcerates positively associated.Loweraverage householdsize signals agreater potential for feelings of loneliness and lack of integrationand should be positively associated with suicide.

Similarly with religious communities, those belonging to reli-gious groups that are characterized by greater social cohesionshould be less prone to commit suicide. In his days, Catholics andJews, as opposed to Protestants, represented such groups. Stack(1981) suspected that such confessional differences within Chris-tianity are likely to have shrunk into insignificance. Arguably,however, there remain substantial differences in the extent ofsocial cohesion and integration between, for example, predomi-

nantlyChristianand Muslimsocieties (Simpson & Conklin, 1989).Similarly based on the basic ideas of Durkheim, one could alsoargue that a greater degree of ethnolinguistic heterogeneitywithin a society is likely to lead to less societal integration and istherefore associated with higher suicide rates. More ethnicallyhomogeneous societies tend to be more integrated societies.

Perhaps somewhat surprisingly, Durkheim (1897/2002, pp. 25-29) was rather dismissive of alcohol consumption patterns as anexplanation of suicide, whereas modern scholars have found evi-dence that heavy consumption of alcohol is strongly related tohigher suicide rates, due to both its negative social effects on theindividual and others and the higher risk of committing violentacts in a state of acute intoxication (Brainerd, 2001; Ramstedt,

2001).Thiscould be because Durkheim (1897/2002,p.25) sawalco-holism more as a psychopathic state, to which all the ills of ourcivilization were attributed in his time,rather than as a symptomof a lack of integration of the affected individuals.

Even whereDurkheim didnotdevelop testable hypotheses him-self (perhaps due to the time he was writing in), others have fruit-fully used his basic theory to hypothesize that, for example,increased female labor force participation is associated withhigher suicide rates. Males are challenged in their role as thebreadwinners and are less likely to be comforted in their sorrowsdue to the labor force participation of their female partners, whichis particularly problematic for men, as their female partners areoftentheirmain sourceof emotionalcomfort (Stack,1998).Women,on the other hand, are exposed to the stress of the employed worklife and often face a double burdenof paid outside employment andunpaid housework.




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In addition to these fundamental social determinants, moderntheorists have put more attention on distinctly economic factorsand particularly on the level of income and fluctuations in eco-nomic conditions (for an overview, see Lester & Yang, 1997). Ofcourse, the potential impact of these did not escape Durkheimsattention. For example, he believed that sudden economic change,both in theform ofeconomic crisisandsuddeneconomic prosperity,upsets the social order and thus leads to an increase in anomic sui-cide (Durkheim, 1897/2002, p. 201ff). Others, such as Ginsberg(1966,as cited in Lester & Yang, 1997),have argued that economicgrowthunambiguously raises thesuiciderate,whereas Henry andShort (1954) argued the exact opposite for rather complex reasons.

Ginsbergs hypothesized relationship is supported by modern eco-nomic theory, which suggests that individuals take their life if andonce their expected present-value lifetime utility becomes zero. Aseconomic crises lower the lifetime incomeof individuals and there-fore their consumption level,making living less attractive relativeto committing suicide, economic crises should raise and economicgrowth should lower the social suicide rate (Hamermesh & Soss,1974).

With respect to the level of income, rather than its growth rate,Durkheim (1897/2002, p. 214) noted a remarkable immunity ofpoor countries because poverty protects against suicide becauseit is a restraint in itself. Modern sociological theorists have ques-tioned Durkheims proposition, arguing that poor people are also

confronted with many more personal problems, which are knownto raise the inclinationto commit suicide. It stresses the social andpsychological deprivationspoor peopleareexposed to andtheposi-tive effectof unemploymenton suicide (Stack, 2000).Lester (1996),based on Henry and Short (1954), argued in favor of Durkheim,however,suggestingthathigheraverage income levelsimplyfewerobvious external factors to blame for life failures and misery, thusraising the suicide rate. Unnithan, Huff-Corzine, Corzine, andWhitt (1994, p. 120) also stated as a matter of fact that suicideincreases . . . with economic development. Against this, moderneconomic theory predicts the opposite result to Durkheimshypothesis because higher lifetime incomes raise therelative costsof committing suicide (Hamermesh & Soss, 1974).

Another reason why higher income levels might be associatedwith lower suicide rates is the generally better quality of emer-gency medical services in high-income societies, which should




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lower the success rate of attempted suicides. Ideally, one wouldwant to control for the quality of emergency medical servicesdirectly, but this is rendered impossible due to lack of data.

In comparison, Durkheim was rather dismissive of potentialexplanations of differences in suicide rates stemming from outsidethe social or economic sphere. He found conditions of the physicalenvironment, such as the climate (Durkheim, 1897/2002, p. 263),both theoretically unconvincing and unsupported by descriptiveempirical evidence (see his Book I on extra-social factors). How-ever, climatic conditions might have an effect on the incidence ofdepression, which is known to be a strong correlate of suicide. Doclimates with low amounts of sunshine render people more

depressed and therefore prone to commit suicide? Does the aver-age temperature have an impact on suicide rates? Robbins,DeWalt, and Pelto (1972) found a positive association between sui-cide and cold climate and Thorson and Kasworm (1984) with lackof sunshine, whereas Lester (1988) finds no such relationship.

In addition, there are other factors that theory would predictdetermine differences in suicide rates. Unfortunately, for many ofthese, no data for a cross-national sample are available. Thisapplies to, for example, the availability of firearms and othermeans of committing suicide (Killias, 1993), the existence of sui-cide prevention centers, access to mental health services, and thelike (Lester, 2000).

RESEARCH DESIGN

THE INDEPENDENT VARIABLES

To control for the variables suggested as important social andeconomic determinants of variation in suicide rates by our review,we include the marriage, divorce, and crude birth rate per 1,000inhabitants as well as the average number of persons living in ahousehold to test for the impact of family integration on suiciderates. Marriage, divorce, and household size data are taken fromEuromonitor International (2002) and complemented by the UN(2001). Data on birth rates and on female labor force participation

measured as a percentage of females aged 15 to 64 are taken fromWorld Bank (2001). We also include pure alcohol consumption inliters per capita. This variable is taken from WHOEurope (2002)andWHO(1999). As a proxy forethnicandracialheterogeneity, we




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take an index from Vanhanen (1999), who codifies data on ethnicheterogeneity based on racial, linguistic,national, tribal, or estab-lished religious divisions. This index refers to the 1990s, is time-invariant,and thereforedropped fromthe fixed-effectsestimation.To our knowledge, no previous study has included a control vari-able for ethnolinguistic heterogeneity.

To test for the influence of religion, we include three furthervariables, all of which are time-invariant and therefore droppedfrom the fixed-effects estimations. The first twoarethepercentageof Muslim and Catholic people taken from La Porta, Lopez-de-Silanes,Shleifer, and Vishne (2000) and Parker (1997). This repre-sents only a rather crude measure of the effect of religious commu-

nity on suicide rates.We therefore include as a further variable forreligious impact the percentage of religious books to all books pub-lished in a country, with data taken from the UN (2000). This vari-able has been used in previous studies (e.g.,Cutright & Fernquist,2001; Fernquist & Cutright, 1998; Stack, 1983). Poor overtimeavailability of this variable prompted us to take the average overthe period of 1980 to 2000, and restricted availability across coun-tries means it is included only in separate model specifications.

To test for the impact of economic factors on suicide rates, weinclude GDP per capita in thousand U.S. dollars of purchasingpower parity, with data generally taken from World Bank (2001).Missing income data were taken from estimations undertaken forWHO (2000). The income data were converted into constant U.S.

dollars (1997) with the help of the United States GDP deflator. It isimportant to use income data in purchasing power parity and notthe conventional income data because the latter often substan-tially underestimate the power of incomes to purchase goods andservices in low-income countries. Becauseof thedivergingviewsonthe effect of income on suicide between economic and sociologicaltheories,as well as among thelatter, we included a squared incometerm to pretest for a nonlinear relationship of income on suiciderates. Where both income terms pretested significantly, both wereincluded in the final estimation results. If the two income termspretested insignificantly, thenthesquared termwasexcludedfromthe final estimations. The economic growth variable is simply thepercentage change in GDP per capita.

To test for the impact of climatic factors on suicide rates, weinclude two variables, which for obvious reasons are time-invariant and thereforedropped in fixed-effects estimation. One istheaverage annualtemperatureof a country, with data taken from




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Mitchell (2001).Theother is theminimum ofmonthly average sun-shine hours per day in the capital city of a country, with data takenfrom Harding (1998). The minimum tested better than the sum ofmonthly average sunshine hours and is also more relevant. This isbecause the long, dark winters should be responsible for highersuicide rates, which is not reflected well by the sum of sunshinehours because many countries with long, dark winters have sum-mer months with very long days such that the sum of sunshinehours does not reflect well the fact of dark, long winters.

THE DEPENDENT VARIABLES

Age-specific numbers of suicide and population data for bothmen and women were taken from WHO (2002) and WHOEurope(2002) and converted into age-standardized rates per 100,000inhabitants using the fictitious European standard population ofthe WHOs Regional Office for Europe as the standard. The choiceof the standard population is essentially arbitrary (Barclay, 1958).The European standard population has been taken as it is the ref-erence point for the published age-standardized suicide rates inthe Health for All database of WHOEurope (2002).

Using age-standardized suicide rates has the great advantagethat national and, if less relevant,over-time differences in the agestructure are controlled for. This is important as the age structure

varies tremendously across countries (and less so over time),and it

is well known that elder people, for example,have a higher prone-ness to commit suicide than younger ones. Usage of age-standardized suicide rates also implies that one does not need toinclude control variables such as the population share of theelderly in the regressions. In spite of these advantages, it has onlyrecentlybecomecommon tousesuch data in studies of thedetermi-nants of suicide (e.g., Cutright & Fernquist, 2001; Fernquist &Cutright, 1998). The WHO has now decided to publish only age-standardized mortality rates, a practice already adopted before byits Regional Office for Europe.

THE SAMPLE

We analyze variation in national age-standardizedsuicide ratesover the period of 1980 to 1999. 1980 is chosen as the cutoff datebecause many of our variables have poor availability before thatdate.Contrary to Fernquist and Cutright (1998), whorestrict their




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analysis to developedcountries, thesize of thesampleof ouranaly-sis is dictated entirely by the availability of data. No country ortimeperiod is excluded per se. Appendix A lists the countries inthesample. Note that for some of them, data are not available for alltime periods. Clearly, developing countries, other than the Latin

American and Central Asian ones, are underrepresented. Never-theless,thereis substantial variationin all thesocialandeconomicfactors analyzed in our study. Descriptive information of the vari-ables can be found in Appendix B and there is a correlation matrixin Appendix C. Only a few of the bivariate correlations are veryhigh. In addition, variance inflation factors were computed tocheck for multicollinearity. For all regressions, the factors for all

individual variables as well as the mean factor is below 5 (indeed,inmanycases wellbelow 3). There is, therefore,no reasontobecon-cerned about multicollinearity (Kennedy, 1992).

RESULTS

Column 1 of Table 1 presents results from the fixed-effects esti-mationformale suiciderates with both robustandnonrobuststan-dard errors. The nonrobust standard errors are the normal stan-dard errors,whereas the robust ones are robust towards arbitraryheteroskedasticity and serialcorrelation.Column 2 reports resultsfrom therandom-effects estimation.Note that there is no easy way

to compute the random-effects model with robust standard errorsso that the reported results for the random-effects model andtherefore the Hausman test refer to nonrobust standard errors.

What are statistically significant determinants of male suiciderates? Starting with economic factors, income has a nonlineareffect on suicide rates. Higher income levels first lower the suiciderate, but ata decreasing rate, and thenraise the suicide rateafter acertain income level has been reached. The estimated turningpoint can be computed as (a/2b), where a is the coefficient of theincome term and b the coefficient of the squared income term. Theturning point,afterwhichhigher incomelevelsareassociated withhigher suicide rates is estimated to be at around US$30,700. Thisseems to suggest that economic development is associated withhighersuiciderates, as predictedby Durkheimian sociological the-ory, only at very high levels of income, whereas the negative effectpredicted by economic theory holds for the vast majority of coun-tries at lower levels of income. Unemployment also matters with




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318

TABLE 1

Fixed- and Random-Effects Estimation of Male Suicide Rates

I II III

GDP per capita 1.68 (5.85)** [5.35]** 1.78 (6.92)** 1.64 (6.29)**

GDP per capita2 0.027 (3.80)** [3.52]** 0.030 (4.32)** 0.027 (3.89)** Economic growth 0.008 (0.30) [0.21] 0.005 (0.17) 0.005 (0.20) Unemployment rate 0.15 (2.54)* [1.95]* 0.12 (2.08)* 0.13 (2.27)* Female labor force participation 0.32 (2.22)* [2.32]* 0.32 (2.84)* 0.28* (2.32) Birth rate 0.53 (4.07)** [4.15]* 0.56 (5.06)** 0.54 (4.65)** Divorce rate 3.72 (5.93)** [4.48]** 4.28 (7.21)** 3.95 (6.64)** Marriage rate 0.95 (3.85)** [3.61]** 0.92 (3.91)** 0.96 (4.06)** Household size 0.08 (0.09) [0.10] 0.61 (0.74) 0.06 (0.07)

Alcohol consumption 1.28 (7.32)** [5.11]** 1.10 (6.68)** 1.18 (7.20)** Ethnic heterogeneity 0.18 (3.67)** % Muslim 0.01 (0.15) % Catholic 0.05 (0.85)

Average temperature 0.14 (0.47) Minimum sunshine hours 2.90 (2.45)* Share religious book production

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Adjusted R 2 a 0.9296R

2 (within) 0.3063R

2 (overall) 0.4484 0.5755 Hausman test chi-square 38.28 11.56 Hausman test p value 0.1162 0.9984 No. of countries 68 68 68 No. of observations 916 916 916

NOTE: Dependentvariable is age-standardized suiciderate(suicides per 100,000 inhabitants).Absolute t statistics redard errors in parentheses and robust standard errors in brackets. Coefficients of period and country specific dumma. Country dummy variables included.*p = .05. **p = .01.

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rising unemployment being associated with higher suicide rates.Higher birth and marriage rates lower the suicide rate, whereas ahigher divorce rate, a higher female labor force participation rate,and higher alcohol consumption raise it, all in line withexpectation.

Contrary to our expectations, some variables test insignifi-cantly, for example, the economic growth rate. Note that the sameresult prevails if the absolute value of economic change is enteredinstead.3 What this implies is that the rate of economic change issimply insignificant and none of the hypotheses stated above con-cerning the impact of economic change on suicide rates is con-firmed by the estimation results. Similarly insignificant is the

average number of people living in a household.Results are very similar to the fixed-effects estimation in terms

of sign of coefficient and significance for the random-effects esti-mationreported in Column2.Notsurprisingly, then,theHausmantest fails to reject the hypothesis that the difference in the esti-mated coefficients of the two models is simply due to chance. Thissuggests no significant correlation of the fixed effects with theexplanatory variables.

Analogous results are reported for female suicide rates in Col-umns 1 and 2 of Table 2. We find that some of the social and eco-nomic factors determine both male and female suicide rates insimilarways. In particular, theimpactof femalelabor force partici-pation rate and birth and divorce rates on female suicide are simi-

lar to the ones on male suicide. There is evidence for the expectedeffect of alcohol expenditures and income levels on suicide rates,whichassumemarginalsignificanceonly if standard errorsarenotrobust, however. Thereare also someremarkabledifferences. Mostimportant, themarriagerate,whichwas a highlysignificant deter-minant of male suicide rates,is highly insignificant for female sui-cide. The same applies to the unemployment rate.4

Therandom-effects estimations arein line with thefixed-effectsestimations. The only difference is that the alcohol consumptionbecomes marginallyinsignificant. TheHausman test fails to rejectthe hypothesis that the differences between the two models is notsystematic,and a comparison of thecoefficientsofboth modelsalsoshowsthat they differlittlefromeach other in substanceas well.

These results lead us to the important conclusion that theexistence of fixed effects does not imply that our estimates froma random-effects estimation are heavily biased. Note that thisdoes not mean that the fixed effects are not of importance. Indeed,




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321

TABLE 2

Fixed- and Random-Effects Estimation of Female Suicide Rates

I II III

GDP per capita. 0.08 (2.04)* [1.84] 0.09 (2.74)** 0.07 (1.99)* Economic growth 0.02 (1.86) [1.88] 0.01 (1.31) 0.01 (1.58) Unemployment rate 0.02 (1.19) [0.85] 0.01 (0.47) 0.01 (0.63) Female labor force participation 0.20 (4.13)** [3.52]** 0.12 (3.25)** 0.13 (3.49)** Birth rate 0.26 (6.10)** [5.88]** 0.22 (6.15)** 0.24 (6.58)** Divorce rate 0.92 (4.59)** [4.27]** 0.85 (4.52)** 0.80 (4.25)** Marriage rate 0.06 (0.82) [0.62] 0.07 (0.88) 0.08 (1.02) Household size 0.31 (0.99) [1.02] 0.32 (1.19) 0.36 (1.25)

Alcohol consumption 0.12 (2.20)* [1.90] 0.09 (1.75) 0.10 (2.02)* Ethnic heterogeneity 0.05 (3.36)**

% Muslim 0.02 (1.17) % Catholic 0.01 (0.35)

Average temperature 0.22 (2.44)* Minimum sunshine hours 0.95 (2.77)** Share religious book production

Adjusted R2 a 0.9125R

2 (within) 0.3011R

2 (overall) 0.3255 0.4404 Hausman test chi-square 29.42 27.57 Hausman test p value 0.3915 0.4873 No. of countries 68 68 68 No. of observations 907 907 907

NOTE: Dependentvariable is age-standardized suiciderate(suicides per 100,000 inhabitants).Absolute t statistics redard errors in parentheses and robust standard errors in brackets. Coefficients of period- and country-specific dum

a. Country-dummy variables included.*p = .05. **p = .01.

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looking at theR 2values in Column 1 of Tables 1 and 2 shows thatthe majority of the variation in suicide rates explained by ourfixed-effects model needs tobe attributed to thefixed effects.It justmeans that the fixed effects are not systematically correlated withour explanatory variables.

It is tempting, but wrong,to simply attribute all the variation insuicide rates explained by the fixed effects to national cultures ofsuicide. This is because of the existence of other time-invariant

variables, which are absorbed in the fixed effects similar tonational cultures of suicide. In our review of the theoretical litera-ture on the determinants of suicide, we have listed ethnolinguisticheterogeneity as well as religious and climatic factors and we will

now test these empirically. Column 3 of Table 1 shows thatethnolinguistic heterogeneity is associated with higher male sui-cide rates.Of the climatic variables, the average temperature pre-

vailing in a country tests insignificantly, but a higher minimum ofdaily sunshine hours is associated with lower suicide rates. As con-cerns thereligiousvariables, neither thepercentage of MuslimnorCatholic people is significant. The same is true for the percentageof religious books production added in Column 4.The sign and sta-tistical significance of the time-varying variables is mainly unaf-fected by the inclusion of these further control variables. Theunemployment rate and female labor force participation becomeinsignificant in the more restricted sample size of Column 4.

Results for female suicide rates are similar in that ethnic heter-

ogeneity is associated with higher suicide rates, whereas the reli-giousvariablesareinsignificant(see Columns 3 and4 ofTable 2).Ahigher minimum number of sunshine hours is associated withlower suicide and higher average temperatures with higher sui-cide. The sign and statistical significance of the time-varying vari-ables are only affected in the more restricted sample of Column 4.There, the income level becomes insignificant, whereas the mar-riage rate and average household size are negatively associatedwith female suicide rates, as expected.

DISCUSSION AND CONCLUSION

As concerns male suicide rates, our results broadly confirm aDurkheimian theory of the determinants of suicide. Lack of socialintegration of individuals as measured by divorce, absence of chil-dren, higher female labor force participation, and higher ethno-




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linguistic heterogeneity raises the suicide rate, whereas a highermarriage rate lowers it. This is in accordance with many previousstudies as listed in Stack (2000, pp. 22-24) and Lester and Yang(1997,pp. 162-166).The average household size does not matter inthe full sample size and only becomes significant in the ratherrestricted sample. This might suggest that it is perhaps not thenumber of individuals living together but the relations amongstthe individuals that matter. Higher alcohol consumption is associ-ated with higher suicide rates, as expected. With respect to eco-nomic factors, unemployment is positively associated with malesuicide as both economic and sociological theory would predict,whereas income is negatively associated with suicide up to a high

threshold of income. The economic growth rate is irrelevant.As concerns female suicide rates, females seem to be somewhat

less sensitive toward economic factors than males. Neither unem-ployment nor the economic growth rate is statistically significantin fixed-effects estimation,andincomeexertsa negativeeffectthatis statistically significant only with nonrobust standard errors.

Absence of children, divorce, female labor force participation, andethnolinguistic heterogeneity have a similar impact on the femaleas well as male suicide rates, but the marital status is significantonly in one model estimation with a more restricted sample size.There is less clearevidence that higheralcohol consumption is pos-itively associated with female suicide rates than was the case withmale suicide rates.

For both sexes, we find no influence of religious variables.Admittedly, our measures of religious integration are rather crude,but the clear failure of our variables to test significantly is ratherstriking. We thus find some tentative evidence corroboratingStacks (2000,p.25) suspicion that inan increasingly secular soci-ety, religious correlates of suicide may not be as strong as secularcorrelates.

We also find evidence that the lack of sunshineis associated withhigher suicide rates in line with expectation. This variablebecomes marginally insignificant in the more restricted sample,however. Average temperatures do not matter for male suiciderates, but somewhat surprisingly, higher average temperaturesare associated with higher female suicide rates.This is contrary toRobbins et al.s (1972) finding that only lookedat bivariatecorrela-tion coefficients, which puts severe doubt on the validity of theirfinding. Also, nonreported results show that theeffect is only signifi-cant ifminimum sunshine hours aresimultaneously controlled for.




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More research seems warranted into the effect of climatic vari-ables on national suicide rates, a topic largely neglected so far.

More important than these results, which are broadly in linewith many previous studies, are two other things, however. First,this article has put forward a methodology that elegantly controlsfor potentially existing national cultures supporting or restrictingsuicide. Second, it has also shown that a failure to control for suchculturesby andlarge does notleadto biasedestimationresults.Thisfollows from a comparison of the fixed-effects with the random-effects estimation results. It is an important result because veryfewstudies of thevoluminous literature on suicidehave attemptedto control for a national culture of suicide. Their findings would be

put into doubt if the socioeconomic time-varying variables theytypically use were correlated with fixed effects.

It would be wrong to attribute the variation in suicideexplained by the fixed effects in the estimation entirely to anational culture of suicide. We have shown that ethnolinguisticheterogeneity and climatic factors are time-invariant and statisti-cally significant yetnotdirectly related to a national culture of sui-cide. Many others could not be tested due to lack of available data.Only more qualitative research and case studies will be able toexplore in more detail the impact of national cultures of suicide.Inthe meantime, our results have demonstrated that we can havefaith in the existing literature that fails to control for national cul-tures of suicide. Our estimations confirm that socioeconomic char-

acteristics are valid determinants of variation in suicide rates.

Appendix ACountries Included in Study

Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Barbados,Belarus, Belgium, Belize, Brazil, Bulgaria, Canada, Chile, Costa Rica,Croatia, Czech Republic, Denmark, Dominican Republic, Ecuador, Esto-nia, Finland, France, Georgia, Germany, Greece, Guatemala, Hungary,Iceland, Israel, Italy, Jamaica, Japan, Kazakhstan, Kuwait, Kyrgyz Re-public, Latvia, Lithuania, Luxembourg, Macedonia (FYR), Mauritius,Mexico, Moldova, Netherlands, New Zealand, Norway, Panama, Poland,

Portugal, Romania, Russian Federation, Singapore, Slovak Republic,Slovenia,SouthKorea,Spain,Sri Lanka,Suriname,Sweden, Switzerland,Trinidad and Tobago, Turkmenistan, Ukraine, United Kingdom, UnitedStates, Uruguay, Uzbekistan, Venezuela.




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Appendix BDescriptive Statistics of Variables

Observations Mean SD Min. Max.

Male suicide rate 916 24.6 17.4 0.1 87.7Female suicide rate 907 7.3 4.7 0.2 26.5GDP per capita 916 13.2 7.2 1.8 33.6Economic growth 916 0.8 7.6 -35.3 65.9Birth rate 916 16.2 6.6 7.6 37.2Female labor force

participation 916 37.6 9.8 11.1 52.7Divorce rate 916 1.9 1.1 0.2 5.5Marriage rate 916 6.7 1.9 3 14.8

Household size 916 3.4 1.0 2.0 9.1Unemployment rate 916 6.2 5.4 0 27.7

Alcohol consumption 916 7.6 3.4 0 17.8Ethnic heterogeneity 916 28.8 27.6 0 177% Muslim 916 7.12 20.5 0 95.1% Catholic 916 20.8 29.9 0 97.8

Average temperature 916 11.6 8.1 -5.4 27.1Minimum sunshine hours 916 2.8 2.1 0 8Religious book production 801 4.1 2.8 0.9 34.0




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Appendix C

Correlation Matrix (n = 916).

Fem. Unem-

GDP Labor ploy- Alcohol House- Ethnic

Per Economic Birth Force Divorce Marriage ment Consump- hold Hetero-

Capita Growth Rate Part. Rate Rate Rate tion Size geneity Mu

Economic growth 0.1815Birth rate 0.4231 0.1065Female labor force

participation 0.2154 0.0153 0.6248Divorce rate 0.2918 0.0751 0.3874 0.6249Marriage rate 0.1728 0.0102 0.2198 0.0081 0.2346Unemployment rate 0.0777 0.0641 0.1246 0.1384 0.2236 0.2273

Alcohol consumption 0.3155 0.1363 0.4116 0.1207 0.0797 0.0842 0.1928Household size 0.5195 0.0805 0.7749 0.6147 0.4805 0.1791 0.0964 0.3856Ethnic heterogeneity 0.3220 0.1013 0.3524 0.2102 0.0197 0.2443 0.0152 0.3921 0.3374% Muslim 0.2571 0.1295 0.4250 0.1556 0.1191 0.2087 0.2485 0.3246 0.5662 0.3289% Catholic 0.4632 0.0407 0.2186 0.4480 0.3926 0.1868 0.0078 0.0166 0.4565 0.1648 0.2

Average temperature 0.3219 0.024 0.5897 0.6706 0.5593 0.0760 0.1961 0.1833 0.6767 0.2262 0.1Minimum sunshine

hours 0.2387 0.0189 0.5850 0.6370 0.5443 0.1127 0.2373 0.0914 0.7103 0.2310 0.2

326

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Notes

1. Note that this is equivalent to an omitted variable bias.2. In principle, Durkheim (1897/2002) distinguished these from yet

another form of suicide, namely, altruistic suicide, which results from asacrificeof individuals for thesake of thesocialgroup.This form of suicideis more relevant for extremely integrated social groups and therefore ofless relevance to modern societies.

3.Detailed results arenotshowndueto space constraints butare avail-able from the author on request.

4.Note that because thesquared term testedsignificantly, thereportedresults refer to the model with this term dropped from the model.

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Eric Neumayer is a senior lecturer at the London School of Economicsand

Political Science (LSE),having received a Ph.D. from the LSE in 1999. His

research in this field focuses on the determinants of violence and conflict

andtheir impacton society. He also hasresearch interests in the allocation

andgovernanceof international flows of tradeand finance aswell as in the

measurement and determinants of environmental performance (http://

www.lse.ac.uk/Depts/geography/Eric1.htm).


Are Socioeconomic Factors Valid Determinants of Suicide?

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