Economic and social status, health and subjective well-being. The case of Argentina in 1995 and 2006

Mariana De SantisIgnacio Villagra TorcomianJune 2013

Motivation•Studies that analyze the link between

social variables and inequality and / or health disparities are scarce in Argentina.

•Contribute empirically to the relationship between health and well-being in Argentina.

•Incorporating individual-level social capital as an explanatory variable of health and well-being.

Objectives•Analyze the effect of economic,

demographic and social variables on health and subjective well-being of adult individuals in Argentina during the period 1995-2006.

•Establish the relationship between health and well-being without assuming causality.

Background (health)• Red and Carlson (2006) argue that social capital

has a positive influence on health.• Graham (2008) found that health is positively

correlated with income, although income gains are associated with smaller increases in the improvement of health (Preston curve).

• Borghesi and Vercelli (2008): income inequality is associated with lower levels of good health. Good health is also associated with active social and relational life. Also, they refer to the influence of education as a promoter factor of good health.

Background (health)• Tipper (2010) mentions the negative impact of

low wages, precarious work and instability on the poor health. He also discusses the influence of marital status in adults as a determinant of self-reported health and / or mortality rate.

• Ahnquist et al (2012) conclude that there is a positive relationship between economic capital and social capital to different health indicators and that this effect is enhanced when individuals have both low economic capital as a low capital.

Background (subjective wellbeing)•The literature reveals the positive

relationship between subjective well-being (happiness) and the absolute and relative income, good health and being married.

•Yip et al. (2007) found that cognitive social capital has a positive impact on health and wellbeing.

Background (subjective wellbeing)•Sarracino (2010) concludes that social

capital and happiness are positively associated after controlling for demographic and economic variables.

•Wills-Herrera et al (2011) found evidence that subjective well-being is positively associated with the containment provided by membership in social, cultural or environmental organizations.

Model •The analysis of the relationship between

well-being and health is addressed by estimating a SAH and a SWB functions in a bivariate probit model, which allows to jointly estimate the probability of being happy and the probability of reporting good health under the assumption that the errors of both functions are correlated.

Model

where • and : latent variables.• X1 and X2 are matrices of order (n x k) and (n x j)

respectively, containing demographic, social and economic characteristics of the n individuals in the sample.

• β1 and β2 are vectors of order (kx1) and (jx1) respectively, which represent unknown parameters.

• and are vectors of random errors normally distributed coming from a joint or bivariate normal distribution.

iii

iii

uXy

uXy

222*2

111*1

*1y

*2y

iu1 iu2

Model• The latent variables can not be observed, but it is

possible to observe the dichotomous variables y1 and y2, which assume the following values:

• Where and are the values of each latent variable which define the limits of two categories.

2*2

2*2

2

1*1

1*1

1

0

1

0

1

yyif

yyify

yyif

yyify

1y 2y

Social CapitalLynch and Kaplan (1997) describe social

capital as ‘‘the stock of investments, resources and networks that produce social cohesion, trust and a willingness to engage in community activities’’.

Cognitive dimension: trust

Structural dimension:participation

The data – World Value Survey Argentinawave 1995 wave 2006

n mean Std. Dev. min max n mean Std. Dev. min max

Happy=1 1079 0,817 0,386 0 1 1002 0,857 0,350 0 1

Healthy=1 1079 0,891 0,312 0 1 1002 0,972 0,165 0 1

Confidence Index 681 0,404 0,177 0 1 604 0,363 0,169 0 1

Active member=1 1079 0,342 0,474 0 1 1002 0,321 0,467 0 1

Age 1079 42,734 17,150 17 89 1002 42,548 17,586 18 88

Age_2 1079 2120,041 1604,755 289 7921 1002 2119,373 1658,426 324 7744

Man=1 1079 0,474 0,500 0 1 1002 0,466 0,499 0 1

Married=1 1079 0,598 0,490 0 1 1002 0,552 0,4975 0 1

LowerSES=1 1079 0,050 0,218 0 1 1002 0,087 0,282 0 1

WorkingSES=1 1079 0,400 0,490 0 1 1002 0,457 0,498 0 1

LowerMSES=1 1079 0,392 0,488 0 1 1002 0,296 0,457 0 1

UpperMSES=1 1079 0,124 0,330 0 1 1002 0,113 0,316 0 1

LowerEL=1 1079 0,526 0,499 0 1 1002 0,513 0,500 0 1

MiddleEL=1 1079 0,350 0,477 0 1 1002 0,328 0,470 0 1

UpperEL=1 1079 0,123 0,329 0 1 1002 0,158 0,365 0 1

Number of children 1077 1,937 1,790 0 8 999 1,861 1,810 0 8

Unemployed=1 1079 0,119 0,324 0 1 1002 0,070 0,255 0 1

Results (men and women)Coef. Std. Err. z P>z [95% Conf. Interval]

yvar1 (healthy)Active memb=1 0,084 0,139 0,610 0,544 -0,188 0,357C_I 0,622 0,346 1,800 0,072 -0,056 1,300Age -0,019 0,022 -0,850 0,395 -0,063 0,025Age_2 0,000 0,000 0,040 0,970 0,000 0,000Man=1 -0,029 0,123 -0,240 0,814 -0,270 0,212Married=1 0,007 0,134 0,050 0,957 -0,256 0,271WorkingSES=1 0,361 0,186 1,940 0,052 -0,003 0,725LowerMSES=1 0,545 0,197 2,760 0,006 0,158 0,931UpperMSES=1 0,592 0,273 2,170 0,030 0,058 1,126MiddleEL=1 0,210 0,148 1,420 0,155 -0,079 0,500UpperEL=1 0,200 0,217 0,920 0,357 -0,225 0,625Wave_06=1 0,922 0,154 5,980 0,000 0,620 1,224_cons 1,340 0,537 2,500 0,013 0,288 2,392yvar2 (happy)Active memb=1 0,162 0,100 1,620 0,105 -0,034 0,357C_I 1,327 0,261 5,090 0,000 0,816 1,838Age -0,033 0,017 -1,950 0,051 -0,066 0,000Age_2 0,000 0,000 1,490 0,136 0,000 0,001Man=1 0,174 0,090 1,930 0,054 -0,003 0,352Married=1 0,445 0,101 4,420 0,000 0,247 0,642WorkingSES=1 0,382 0,146 2,630 0,009 0,097 0,668LowerMSES=1 0,338 0,151 2,240 0,025 0,042 0,634UpperMSES=1 0,571 0,199 2,870 0,004 0,181 0,962MiddleEL=1 0,003 0,102 0,030 0,979 -0,197 0,203UpperEL=1 0,464 0,163 2,840 0,005 0,143 0,784Wave_06=1 0,287 0,092 3,130 0,002 0,107 0,467Numb. of child -0,068 0,030 -2,260 0,024 -0,127 -0,009Unemployed=1 -0,361 0,138 -2,620 0,009 -0,631 -0,091_cons 0,587 0,376 1,560 0,118 -0,150 1,324/athrho 0,369 0,088 4,180 0,000 0,196 0,542rho 0,353 0,077 0,193 0,495Likelihood-ratio test of rho=0: chi2(1) = 18,517 Prob > chi2 = 0,000

Number of obs. = 1282

Wald chi2(26) = 156.53

Log likelihood = -755.20463 Prob > chi2 = 0.0000

Results (men)Coef. Std. Err. z P>z [95% Conf. Interval]

yvar1 (healthy)Active memb=1 0,150 0,211 0,710 0,477 -0,264 0,564C_I 0,737 0,467 1,580 0,115 -0,179 1,653Age -0,045 0,035 -1,290 0,197 -0,113 0,023Age_2 0,000 0,000 0,740 0,459 0,000 0,001Married=1 -0,244 0,211 -1,150 0,249 -0,658 0,171WorkingSES=1 0,475 0,265 1,790 0,073 -0,044 0,994LowerMSES=1 0,647 0,278 2,330 0,020 0,102 1,192UpperMSES=1 0,437 0,357 1,220 0,221 -0,263 1,137MiddleEL=1 0,139 0,211 0,660 0,509 -0,274 0,552UpperEL=1 0,169 0,311 0,550 0,586 -0,439 0,778Wave_06=1 0,894 0,219 4,080 0,000 0,464 1,323_cons 1,970 0,822 2,400 0,017 0,360 3,581yvar2 (happy)Active memb=1 0,204 0,161 1,270 0,205 -0,112 0,519C_I 1,387 0,378 3,670 0,000 0,647 2,127Age -0,062 0,026 -2,420 0,015 -0,113 -0,012Age_2 0,000 0,000 1,710 0,088 0,000 0,001Married=1 0,490 0,165 2,980 0,003 0,167 0,813WorkingSES=1 0,438 0,224 1,960 0,050 0,000 0,877LowerMSES=1 0,351 0,229 1,530 0,125 -0,097 0,799UpperMSES=1 0,679 0,308 2,200 0,028 0,074 1,283MiddleEL=1 -0,152 0,154 -0,990 0,324 -0,454 0,150UpperEL=1 0,476 0,263 1,810 0,070 -0,039 0,991Wave_06=1 0,414 0,144 2,870 0,004 0,131 0,697Numb. of child 0,001 0,049 0,010 0,990 -0,096 0,097Unemployed=1 -0,379 0,185 -2,050 0,040 -0,741 -0,017_cons 1,428 0,573 2,490 0,013 0,304 2,552/athrho 0,491 0,136 3,620 0,000 0,226 0,757rho 0,455 0,107 0,222 0,639Likelihood-ratio test of rho=0: chi2(1) = 14,480 Prob > chi2 = 0,000

Number of obs. = 616

Wald chi2(24) = 93.12

Log likelihood = -335.99358 Prob > chi2 = 0.0000

Results (women)Coef. Std. Err. z P>z [95% Conf. Interval]

yvar1 (healthy)Active memb=1 0,068 0,191 0,350 0,723 -0,307 0,443C_I 0,532 0,538 0,990 0,323 -0,522 1,586Age 0,000 0,031 -0,010 0,990 -0,061 0,060Age_2 0,000 0,000 -0,500 0,619 -0,001 0,000Married=1 0,210 0,188 1,120 0,264 -0,159 0,579WorkingSES=1 0,271 0,266 1,020 0,307 -0,249 0,792LowerMSES=1 0,449 0,287 1,570 0,117 -0,113 1,011UpperMSES=1 0,887 0,475 1,870 0,062 -0,045 1,819MiddleEL=1 0,269 0,214 1,260 0,209 -0,151 0,689UpperEL=1 0,280 0,320 0,870 0,383 -0,348 0,907Wave_06=1 0,934 0,221 4,230 0,000 0,501 1,367_cons 0,858 0,738 1,160 0,245 -0,588 2,305yvar2 (happy)Active memb=1 0,135 0,130 1,040 0,298 -0,119 0,389C_I 1,261 0,366 3,440 0,001 0,543 1,979Age -0,022 0,023 -0,950 0,344 -0,067 0,023Age_2 0,000 0,000 0,990 0,322 0,000 0,001Married=1 0,480 0,134 3,580 0,000 0,217 0,743WorkingSES=1 0,361 0,196 1,840 0,066 -0,024 0,745LowerMSES=1 0,353 0,206 1,710 0,086 -0,050 0,756UpperMSES=1 0,527 0,267 1,970 0,049 0,002 1,051MiddleEL=1 0,114 0,140 0,810 0,415 -0,161 0,389UpperEL=1 0,463 0,219 2,110 0,035 0,034 0,892Wave_06=1 0,211 0,122 1,730 0,083 -0,028 0,451Numb. of child -0,109 0,040 -2,760 0,006 -0,187 -0,032Unemployed=1 -0,354 0,211 -1,680 0,094 -0,768 0,060_cons 0,264 0,505 0,520 0,601 -0,726 1,255/athrho 0,292 0,122 2,390 0,017 0,053 0,531rho 0,284 0,112 0,053 0,486Likelihood-ratio test of rho=0: chi2(1) = 5,969 Prob > chi2 = 0,015

Number of obs. = 666

Wald chi2(24) = 75.04

Log likelihood = -406.947 Prob > chi2 = 0.0000

Results (have a good o very good health)• The probability of having good or very good health has a

direct relationship with the trust in institutions and increases with the socioeconomic level.

• The coefficient associated with the dummy for the 2006 wave is also positive and statistically significant. This variable captures the effect of time on the probability of having good or very good health.

• The results indicate that confidence, proxy of cognitive social capital exerts favorable influence on health, unlike the structural capital approximated by active membership.

• Estimates for men and women separately confirm the positive impact of time on the probability of having good or very good health and the favorable effect of belonging to the lower middle and working classes in relation to the low class (baseline).

Results (being happy or very happy)• Positive effect of being married, feel confident with

different institutions, belonging to higher social class and being more educated.

• The probability of being happy or very happy presents an increasing trend during 1995 and 2006.

• Individuals with more children and unemployed have less probability of being happy or very happy in regard with others.

• The probability of being happy decreases as age of individuals increases. In this case, the hypothesis that older people have a lower discrepancy between aspirations and achievements is not satisfied but that gap continues to be relevant even in older adults.

Results (being happy or very happy)• Married people and men are more likely to be

happy.• The probability of being happy or very happy

increases with the social and economic status of people suggesting that in Argentina the association between SWB and income has not become weak during the period considered.

• The rho coefficient is positive and statistically different from zero in the three estimations, confirming there is a positive association between being happy and being healthy.

Marginal effectsMarginal effects of the bivariate probit y = Pr(yvar1=1,yvar2=1) = 0,838

variable dy/dx Std. Err. z P>z [ 95% C.I. ] X

Active memb=1 0,037 0,022 1,710 0,088 -0,005 0,080 0,347

C_I 0,309 0,059 5,220 0,000 0,193 0,425 0,384

Age -0,008 0,004 -2,040 0,041 -0,015 0,000 40,588

Age_2 0,000 0,000 1,370 0,170 0,000 0,000 1913,120

Man=1 0,035 0,021 1,680 0,093 -0,006 0,075 0,480

Married=1 0,097 0,024 3,960 0,000 0,049 0,144 0,578

WorkingSES=1 0,095 0,031 3,060 0,002 0,034 0,156 0,413

LowerMSES=1 0,094 0,031 2,980 0,003 0,032 0,155 0,370

UpperMSES=1 0,117 0,027 4,330 0,000 0,064 0,170 0,125

MiddleEL=1 0,011 0,023 0,480 0,631 -0,035 0,057 0,382

UpperEL=1 0,090 0,026 3,460 0,001 0,039 0,142 0,154

Wave_06=1 0,109 0,021 5,190 0,000 0,068 0,150 0,470

Numb. of child -0,014 0,006 -2,260 0,024 -0,026 -0,002 1,777

Unemployed=1 -0,088 0,038 -2,300 0,021 -0,162 -0,013 0,094

(=1) dy/dx is for discrete change of dummy variable from 0 to 1

Marginal effects• Age presents a negative marginal effect, being no

significant the effect of age squared.• Men and married people have significant and positive

marginal effect.• The marginal effects of the variables associated with

higher socioeconomic class and superior educational level are positive and higher regard to lower class and lower educational level individuals, respectively.

• The dummy variable that captures the year in which the individual was surveyed also has a positive and statistically significant marginal effect indicating that the joint probability of good health and happiness valued at the average increased by 0.109 between 1995 and 2006.

Marginal effects• A greater number of children has a negative

effect on the joint probability of being healthy and happy.

• Being unemployed has a negative and statistically significant effect corroborating the impact of lower incomes, stress and job dissatisfaction.

• Finally, it can be seen that the variables related to social capital, active membership and the confidence index, show positive and significant marginal effects.

Marginal effects of the confidence index for alternative profiles.•The impact of the confidence index on the

joint probability of good health and being happy is analyzed for different profiles of individuals, defined according to the following attributes:Socioeconomic status Working class – Upper middle class

Educative level Middle – Upper

Age Younger than 40 – Over 40

Unemployment Unemployed – Employed

Number of children 2 (was used for all calculations)

Gender Man – Woman

Marginal effects of the confidence index for alternative profiles.

Profiles based on characteristics of individuals

Socioeconomic status

Educative level Age Unemployment

Number of children

GenderCI

(marginal effects)

Younger than 40

Over 40

1 WorkingSES Middle yes no 2 man 0,1952 WorkingSES Middle yes no 2 woman 0,2283 WorkingSES Middle yes no 2 man 0,2434 WorkingSES Middle yes no 2 woman 0,3015 WorkingSES Middle yes yes 2 man 0,3446 WorkingSES Middle yes yes 2 woman 0,3287 WorkingSES Middle yes yes 2 man 0,3948 WorkingSES Middle yes yes 2 woman 0,4319 UpperMSES Upper yes no 2 man 0,07410 UpperMSES Upper yes no 2 woman 0,08711 UpperMSES Upper yes no 2 man 0,10612 UpperMSES Upper yes no 2 woman 0,13813 UpperMSES Upper yes yes 2 man 0,16514 UpperMSES Upper yes yes 2 woman 0,16915 UpperMSES Upper yes yes 2 man 0,20716 UpperMSES Upper yes yes 2 woman 0,276

Final remarks• This result indicates that it is possible to create conditions

for improving the access to equal opportunities and decrease the gap between those healthiest and most happy and the rest by applying lines of social inclusion and reduction of inequality policies.

• The results also suggest that it is possible to affect positively the health and well-being of the less favored by encouraging and promoting the strengthening of social capital.

• The analysis allows saying that the improvement in the confidence about the institutions would have a greater potential effect on women over 40, unemployed, of low socioeconomic class and with a middle educational level, that is, on the most vulnerable groups with fewer labor market opportunities.