Men – Marketization M - Data, Methods and Descriptives

Excess suicide rate unemployed men 1979-

3. Unemployment, Marketization and Suicide

3.3 Data, Methods and Descriptives

3.4.1 Men – Marketization M

Table 2 examines the relationship between marketization, unemployment growth and the male suicide rate. Model 1 enters the basic control variables (country fixed-effects and year counter). As can be seen, there seem to be no unaccounted time factors that explain variations in the suicide rate across country-years, since the coefficient is small and not statistically significant (b = -.001, p >.10). However, marketization processes do also not account for the suicide rate (b = .001, p >.10), and neither do recent changes in unemployment level (b = .001, p >.10). Therefore, Hypothesis 1 is not

supported for men.

Adding the interaction effect (Model 2) between marketization processes and recent changes in unemployment, the previous conclusions seem to be robust. Moreover, there is no support for an interaction effect: its coefficient is tiny and not statistically significant (b =- .001, p >.10). The data

on males therefore support neither Hypothesis 2, nor 3.

Adding economic control variables (Model 3) does still not alter these results. Interestingly, the GDP level has small but statistically significant relationship with the male suicide rate. The higher the GDP, the lower the male suicide rate (b = -.001, p <.05). GDP growth, by contrast, has no such relationship with suicide rates.

Model 4 adds population variables that may influence the degree of anomie in society as well as the level of development, such as population size, urbanization, divorce rate and educational stock. The main results remain robust against this change. GDP level still retains its small protective effect (b = - .001, p <.05) and population size has, by contrast, a tiny suicide-enhancing effect (b = .001, p <.001). Moreover, the male suicide rate tends to be higher in more urbanized country-years (b = .030, p <.001), and in societies with a higher divorce rate (b = .062, p <.001). Higher social expenditures have a protective effect against higher suicide rates (b -.014, p <.01).

Model 5, in addition, takes the distribution of the unemployed population into account. The general results with regard to the main and interaction effects, as well as for the previous control variables, are robust. However, the distribution of the unemployed population has no apparent influence on the male suicide rate: not youth unemployment, nor the prevalence of tertiary education, or long-term unemployment does.

Model 6 substitutes the unemployment composition variables for two control variables: one indicating the mean suicide rate in leading economies and another indicating the country’s position in the cross- national distribution of suicide rates. The latter is meant to indicate a country’s ‘suicide culture’, as said. Only the latter has an apparent influence on the current suicide rate: the more ‘above-average’ a country tends to be, the higher its present suicide rate (b = .022, p <.001). In this model, the prevalence of tertiary education in the wider population gains a protective, small influence against high suicide rates (b = -.003, p <.05).

Model 7 substitutes the previously added two control variables by another two: a country-years’s transition status (post-soviet, soviet or never have been soviet country) and its welfare regime type. In this model, the prevalence of tertiary education loses statistical significance, but the other previously significant control variables remain robust. Compared to liberal market economies, moreover, transition and Nordic countries tend to have higher suicide rates (b = 1.84 and b = .472 respectively, both at p <.001) and Mediterranean countries tend to have lower rates (b = .253, p >.10), albeit marginally statistically significantly. Conservative countries are not significantly different from their liberal market counterparts.

Model 8, subsequently, substitutes the transition- and regime dummy variables for another control variable: antidepressants consumption. While antidepressants intake has no influence on the suicide rate, adding this variable leaves the main results intact. Note that there were relatively many missing observations on this variable, and that the high imputation-to-observation ratio may have introduced much error in this measure – making it harder to reveal effects.

Model 9, then, substitutes the antidepressants control variable by a dummy variable distinguishing the period in which the valid time series started for some variables (such as two marketization indicators), from the period for which values had to be extrapolated on those variables. This variable had no independent influence on the suicide rates, or on the other results.

Model 10, finally, leaves out the first two decades of the considered time period, to more robustly take account of the influence of extrapolated time series for a number of variables where observations were only available from 1980 on. The model repeats Model 5 for this shorter time period. Approximately 300 units (country-years) were lost by this. This time, the year variable has a statistically significant influence on the suicide rate, with more recent years having lower suicide rates (b = -.007, p <.05).

Note that there is much variance and fluctuation hiding behind this coefficient, as seen in Chapter 1. This time, interestingly, the prevalence of tertiary education among the unemployed has a suicidogenic impact (b = .012, p <.01), while the other composition variables still have no relationship with suicide rates. Moreover, marketization processes and changes in unemployment still have no main influence on the suicide rate, nor are they interacting in their effects.

Table 2: Regression analysis on the male suicide rate with (negative) marketization processes, 1960-2016

Model 1 Model 2 Model 3 Model 4

β SE β SE β SE β SE Constant 3.085 2.838 *** 3.087 0.059 *** 3.185 0.112 *** 0.822 0.112 * Unemployment growth 0 0 0 0 0 0 0 0 Negative marketization 0.001 0.002 0.001 0.002 0.001 0.002 0.001 0.002 Interaction effects 0 0 0 0 0 0 Unemployment growth X Negative marketization

Control variables included

Country fixed- effects X X X X Year counter X X X X GDP X X GDP growth X X Population size X

Percentage tertiary educated X

Urbanization X

Divorce rate X

Social expenditures X

Tertiary educated in total unemployment Young people in total unemployment Long-term unemployment in total unemployment

Average suicide rate leading economies

Suicide culture Welfare regime Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status Not during transition years (ref.) During transition years (1989-1999) Antidepressants consumption Period after 1996 (dummy)

p < .1, * p < .05, ** p < .01, *** p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized coefficients, except the intercept. Control variables were included but not displayed, and can be requested from the author.

Table 2 (continued): Regression analysis on the male suicide rate with (negative) marketization processes, 1960-2016

Model 5 Model 6 Model 7

β SE β SE β SE Constant 0.607 0.35 + 2.323 0.154 *** 0.726 0.371 * Unemployment growth 0 0 0 0 0 0 Negative marketization _0.001 0.002 ₀ 0.003 0.001 0.002 Interaction effects 0 0 0 0 0 0 Unemployment growth X Negative marketization Control variables included

Country fixed-effects X X X Year counter X X X GDP X X X GDP growth X X X Population size X X X

Percentage tertiary educated X X X

Urbanization X X X

Divorce rate X X X

Social expenditures X

Tertiary educated in total unemployment X

Young people in total unemployment X

Long-term unemployment in total unemployment X

Average suicide rate leading economies X

Suicide culture X

Welfare regime X

Liberal market (ref.)

Conservative Mediterranean Transition Nordic

Transition country status

Not during transition years (ref.) During transition years (1989-1999) Antidepressants consumption

Period after 1996 (dummy)

+_{p < .1,}*_{p < .05,}**_{p < .01,}***_{p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized coefficients, except}

Table 2 (continued): Regression analysis on the male suicide rate with (negative) marketization processes, 1960-2016

Model 8 Model 9 Model 10

β SE β SE β SE Constant 0.914 0.373 * 0.828 0.341 * 1.287 0.334 *** Unemployment growth 0 0 0 0 -0.011 0 Negative marketization 0.001 0.002 0.001 0.002 0 0.003 Interaction effects 0 0 0 0 0 0 Unemployment growth X Negative marketization

Control variables included

Country fixed- effects X X X Year counter X X X GDP X X X GDP growth X X X Population size X X X

Percentage tertiary educated X X X

Urbanization X X X

Divorce

rate X X X

Social expenditures X

Tertiary educated in total unemployment X

Young people in total

unemployment X

Long-term unemployment in total

unemployment X

Average suicide rate leading economies

Suicide culture Welfare regime Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status Not during transition years (ref.) During transition years (1989-1999)

Antidepressants consumption X

Period after 1996 (dummy) X

+_{p < .1,}*_{p < .05,}**_{p < .01,}***_{p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized}

coefficients, except the intercept. Control variables were included but not displayed, and can be requested from the author.

3.4.2 Men – Resistance

Table 3’s Model 1, containing the basic control variables of the country fixed-effects and a year counter, shows that the degree of resistance against marketization does not influence the suicide rate (b -.173, p >.10). Neither do recent changes in unemployment level (b = .001, p >.10). If resistance

against marketization is taken as a cultural or attitudinal indicator of marketization, it would mean that Hypothesis 1 is not supported by the data.

Model 2 adds the interaction effect between resistance and recent changes in unemployment. This reveals no support for the presumed interaction effect (b = .001, p >.10). Again, if resistance against

marketization is taken as an attitudinal indicator of marketization, Hypothesis 2 and 3 could not be supported by the data. Unemployment growth is not less or more suicidogenic in societies with a more popular anti-marketized attitudinal framework. Moreover, resistance and

unemployment growth still appear to be unrelated with the male suicide rate.

Model 3 adds the economic control variables. The former results remain intact. Interestingly, again, GDP has again a small protective influence against higher male suicide rates: b = -.001, p <.05. The passing of the years now has a small, marginally significant positive relationship with the male suicide rate (b = .004, p <.10).

Model 4 adds the population and development variables. This leaves the previous results intact, except that the passing of the years loses its statistically significant influence. As in Table 2, areas with a larger population have a somewhat larger suicide rate (b = .001, p <.001), and the same goes for more urbanized societies (b = .030, p <.001) with higher divorce rates (b = .059, p <.01). Social expenditures again appear to have a protective influence (b = -.013, p <.01). Again, resistance and unemployment growth are not related to the male suicide rate, and the same goes for their interaction. Model 5 takes into consideration the compositional characteristics of the unemployed population. From these, only the prevalence of tertiary education is related to the suicide rate: societies with a larger stock of tertiary education among their unemployed have a higher suicide rate (b = .007, p <.05). Still, none of the hypothesized relationships are found.

Model 6 substitutes the unemployment composition variables for the mean suicide rate in leading economies and a country’s ‘suicide culture’. Again, only the suicide culture appears to have a statistically significant, but small, relationship with the male suicide rate (b = .022, p <.001). Moreover, the passing of the years again now has a small negative impact on the suicide rate (b = - .004, p <.001). Interestingly, resistance has a suicidogenic impact in this model (b = .347, p <.001).

This would mean a direct contradiction to Hypothesis 1: a more anti-marketization cultural framework would rather lead to lower suicides according to this hypothesis. Still, resistance does

not moderate the relationship between unemployment changes and suicide, nor does unemployment growth itself have an apparent influence here.

Model 7 substitutes the previously added two control variables by another two: a country-years’s transition status and the regime type. In this model, the year variable and resistance both lose statistical significance. Again, being a Nordic country appears to be related to higher average suicide rates (1.03 p <.001), as well as being a transition country (b = .90, p <.001), compared to being a liberal market economy. In this model, Mediterranean countries do not significantly have lower suicide rates than liberal market economies. Transition period for post-soviet countries (soviet country past the collapse of the soviet union until the 2000s) is related to higher suicide rates as well (b = .113, p <.01). Again, none of the hypothesized main or interaction effects is supported in this model.

Model 8 takes account of the antidepressants consumption. This has no influence on suicide rates. Interestingly, however, taking this variable into account reveals a suicidogenic influence of resistance (b = .262, p <.05). Still, resistance does not alter the relationship between unemployment changes and suicide, which relationship stays to be non-supported by the data.

Model 9 accounts for the period for which values had to be extrapolated on variables with more recent time series. This had no influence on the suicide rates, or on the other results, except that the resistance coefficient declines and loses its statistical significance again.

Model 10, finally, leaves out the first two decades of the considered time period, to more robustly take account of the influence of extrapolated time series for a number of variables where observations were only available from 1980 on. Resistance is one of those variables, and it is likely that this model reveals more reliable and valid results here. Again, note that this model repeats Model 5 for this shorter time period. Indeed, resistance turns out to have a protective influence against higher suicide rates (b = -.309, p <.05). This provides some strong support for Hypothesis 1: suicide rates appear

to be lower in countries with a stronger anti-marketization cultural framework. Moreover, the

stock of tertiary education in unemployment becomes a small suicidogenic factor again (b .012, p <.001). Still, however, changes in unemployment is unrelated with male suicide rates, and this relationship is unaffected by resistance.

Table 3: Regression analysis on the male suicide rate with popular resistance, 1960-2016

Model 1 Model 2 Model 3 Model 4

β SE β SE β SE β SE Constant 3.154 0.018 *** 3.155 0.082 *** 3.28 0.084 *** 0.791 0.36 * Unemployment growth 0 0 -0.005 0 -0.016 0 -0.006 0 Resistance -0.173 0.165 -0.164 0.165 -0.244 0.151 0.118 0.141 Interaction effects 0 0 0 0 0 0 Unemployment growth X Resistance

Control variables included

Country fixed- effects X X X X Year counter X X X X GDP X X GDP growth X X Population size X

Percentage tertiary educated X

Urbanization X

Divorce rate X

Social expenditures X

Tertiary educated in total unemployment Young people in total

unemployment

Long-term unemployment in total unemployment

Average suicide rate leading economies

Suicide culture Welfare regime Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status Not during transition years (ref.) During transition years (1989-1999) Antidepressants consumption Period after 1996 (dummy)

p < .1, * p < .05, ** p < .01, *** p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized coefficients, except the intercept. Control variables were included but not displayed, and can be requested from the author.

Table 3 (continued): Regression analysis on the male suicide rate with popular resistance, 1960- 2016

Model 5 Model 6 Model 7

β SE β SE β SE Constant 0.681 0.363 + 2.089 0.159 *** 0.694 0.37 + Unemployment growth 0 0 0 0 0 0 Resistance -0.04 0.135 0.347 0.08 *** 0.081 0.141 Interaction effects 0 0 0 0 0 0 Unemployment growth X Resistance

Control variables included

Country fixed-effects X X X Year counter X X X GDP X X X GDP growth X X X Population size X X X

Percentage tertiary educated X X X

Urbanization X X X

Divorce rate X X X

Social expenditures X

Tertiary educated in total unemployment X

Young people in total unemployment X

Long-term unemployment in total unemployment X

Average suicide rate leading economies X

Suicide culture X

Welfare regime X

Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status X

Not during transition years (ref.) During transition years (1989-1999) Antidepressants consumption Period after 1996 (dummy)

p < .1, * p < .05, ** p < .01, *** p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized coefficients, except the intercept. Control variables were included but not displayed, and can be requested from the author.

Table 3 (continued): Regression analysis on the male suicide rate with popular resistance, 1960- 2016

Model 8 Model 9 Model 10

β SE β SE β SE Constant 0.722 0.377 + 0.757 0.344 * 1.67 0.353 *** Unemployment growth 0 0 0 0 0 0 Resistance 0.262 0.132 * 0.162 0.137 -0.309 0.135 * Interaction effects 0 0 0 0 0 0.001 Unemployment growth X Resistance

Control variables included

Country fixed-effects X X X

Year counter X X X

GDP X X X

GDP growth X X X

Population size X X X

Percentage tertiary educated X X X

Urbanization X X X

Divorce rate X X X

Social expenditures X

Tertiary educated in total unemployment X

Young people in total unemployment X

Long-term unemployment in total unemployment X

Average suicide rate leading economies Suicide culture

Welfare regime Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status Not during transition years (ref.) During transition years (1989-1999)

Antidepressants consumption X

Period after 1996 (dummy) X

+_{p < .1,}*_{p < .05,}**_{p < .01,}***_{p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized coefficients, except}

Table 3 (continued): Regression analysis on the male suicide rate with popular resistance, 1960- 2016

Model 8 Model 9 Model 10

Control variables included

Country fixed-effects X X X Year counter X X X GDP X X X GDP growth X X X Population size X X X

Percentage tertiary educated X X X

Urbanization X X X

Divorce rate X X X

Social expenditures X

Tertiary educated in total unemployment X

Young people in total unemployment X

Long-term unemployment in total unemployment X

Average suicide rate leading economies Suicide culture

Welfare regime Liberal market (ref.) Conservative Mediterranean Transition Nordic

Transition country status Not during transition years (ref.) During transition years (1989-1999)

Antidepressants consumption X

Period after 1996 (dummy) X

+_{p < .1,}*_{p < .05,}**_{p < .01,}***_{p < .001. N = 1,360 country-years (1,067 for Model 10). Standardized}

coefficients, except the intercept. Control variables were included but not displayed, and can be requested from the author.

3.4.3 Women – Marketization

Table 4 and 5 turn the focus on female suicide rates. Model 1 contains the basic control variables of the country fixed-effects and a year counter. The year counter coefficient seems to indicate that the female suicide rate, on average, had declined (b = -.007, p < .001). Note again that this broad coefficient conceals much cross-national variance in trends. Female suicide rates do not appear to be related to marketization processes (b = .003, p > .10), nor to recent changes in unemployment (b = .001, p > .10). Thus, also for women, Hypothesis 1 is not supported.

Model 2 adds the interaction effect between resistance and recent changes in unemployment and – given the tiny effect coefficient and the non-significant p-value (b = .001, > .10). Therefore

In document Anomie, Shame, and Resistance. The Impact of the Economy on Suicide (Page 142-154)