Discussion Papers In Economics
And Business

Effects of pregnancy and birth on smoking and drinking behaviors:
a comparative study between men and women

Eiji Yamamura
Yoshiro Tsutsui
Discussion Paper 16-26

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANEffects of pregnancy and birth on smoking and drinking behaviors:
a comparative study between men and women

Eiji Yamamura
Yoshiro Tsutsui
Discussion Paper 16-26
November 2016

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANEffects of pregnancy and birth on smoking and drinking behaviors:
a comparative study between men and women
Eiji Yamamura
Seinan Gakuin University

Yoshiro Tsutsui¶
Konan University

Abstract
Using panel data obtained from monthly surveys for 3 years, we examined how the effects oflife events such as marriage, pregnancy, and birth on smoking and drinking behaviors differ
between men and women. Key findings were: (1) marriage did not reduce smoking for men or
women. (2) Both men and women’s consumption of alcohol and cigarettes were lower during
pregnancy and after childbirth than before pregnancy. The degree of the effects of pregnancy for
women was approximately 5–7 times larger than that for men. (3) Giving birth reduced
consumption by roughly 11 cigarettes per day for women and two cigarettes per day for men
compared with before pregnancy. These results indicate that a predicted negative externality to
infants from their parents’ drinking and smoking behaviors gives parents an incentive to avoid
consuming alcohol and tobacco.

Keywords: Externality, Passive smoking, Pregnancy
JEL Classification: I12, D03*Corresponding

author. Department of Economics, Seinan Gakuin University, 6-2-92
Nishijin, Sawara-ku Fukuoka 814-8511, Japan. E-mail address: yamaei@seinan-gu.ac.jp
Tel: +81 92 823 4543; Fax: +81 92 823 2506
¶Faculty of Economics, Konan University, 8-9-1 Okamoto, Higashinadaku, Kobe 6588501 Japan, e-mail tsutsui@center.konan-u.ac.jp1

Highlights

We use panel data obtained from monthly surveys for 3 years.
Effects of pregnancy and birth on smoking and drinking behaviors are examined.
Alcohol and cigarette consumption were lower during pregnancy and after childbirth.
The degree of effects for women was larger than that for men.

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1. Introduction
It is evident that maternal smoking and drinking have detrimental effects on unborn babies and, later, parents’cigarette consumption causes children to be subjected to passive smoking, which hampers children’s health (e.g.,
Abrevaya 2006; Adda and Cornaglia, 2010; Frijters et al., 2011)1. Maternal smoking during pregnancy increases thelikelihood of admission to neonatal intensive care units, which leads to an increase in neonatal costs (Adams 2002). A
number of works indicate that policies such as cigarette taxes and smoking bans are effective to reduce these costs.
This is because such policies reduce the externality of maternal smoking, which has been found to improve the healthstatus of newborn babies (e.g., Evans and Ringel 1999; Colman et al, 2003; Sen and Perard 2011; Lien and Evans 2005;
Bhardwaj et al., 2014). In addition to smoking, parental drinking behavior is thought to hamper the health of newborns(e.g., Russell et al., 1996; Huizink and Mudder, 2006; O’Connor and Whaley 2007) and can lead to fatal deaths (e.g.,
Kline et al., 1980; Barreca and Page 2015). If parents place importance on their children’s health, they will voluntarily
attempt to quit drinking and smoking to reduce the negative externality. Researchers have also investigated how
pregnancy is related to women’s cigarette consumption (e.g., Evans and Ringel 1999; Bradford 2003).

The externality of smoking harms not only children’s health but also that of other family
members. The husband’s smoking is considered to cause a negative externality from the negative
effect of passive smoking on his wife.

Furthermore, the effect during pregnancy on the motherof passive smoking owing to the father’s smoking is detrimental to the birth outcomes of the infant(Goel et al., 2004; Qui et al., 2014). However, the classical work of Wakefield et al. (1998) foundthat men were largely unaware that their own smoking could pose a specific risk to the fetus, thus
they were unlikely to quit smoking. Similarly, Blackburn et al. (2005) did not find that pregnancy
led fathers to quit smoking and argued that improving knowledge levels among fathers about theeffects of passive smoking on infants may encourage more attempts to stop smoking2. Today, more
people appear to have become better informed about the negative effects of passive and parental

Parental and maternal cigarette consumption lead to sudden infant death syndrome(DiFranza and Lwe 1995), low birth weight (Olds et al, 1994, Chomiz et al, 1995; Walker
et al., 2009; Yan 2013), extremely small size for gestational age (Fantuzzi et al., 2008), andhinders child neurodevelopment (Wehby et al., 2011).
2 As observed in a study in Sweden during the 1980s, women with low education levels
and who were not living with the father of their infant had increased risk of smoking
before pregnancy and continued smoking in early pregnancy (Cnattingius and Thorslund1990). More recently in Australia, a study found that smoking cessation even during
pregnancy was not a priority for most women, partly because smoking reduced stressand provided opportunities for relaxation (Wood 2008).
1

3

smoking on the fetus. Our paper deals with this issue in modern Japanese society where men’sviews about their role in the family have changed3. A published government report states that"about 80% of men in their 20s to 40s with children are involved in housekeeping, childcare, andfamily care in some way, and their participation rate is higher than the approximately 40% of menof the same generation without children and 55% of all men including other generations" (Gender
Equality Bureau Cabinet Office of Japan 2009, p.15). This indicates that men’s participation inchild rearing is promoted and has become widespread in modern society. Therefore, it is valuable
to explore how the wife’s pregnancy changes smoking behavior in the husband4. In contrast to
smoking, drinking does not have an externality to surrounding people, such as family members,
unless the person who is consuming alcohol behaves in a questionable manner toward them. To
put it in another way, drinking does not automatically and unintentionally harm children’s health;there is no “passive drinking effect” on infants. Differences in the influence of smoking anddrinking seem to affect parents’ quitting behavior during pregnancy and during the period of childcare5.
Pregnancy and infant care are thought to influence drinking and smoking behaviors in both
men and women. However, little is known about how the effects of life events on parental
behaviors differ, according to the types of externality from smoking and drinking, and also
according to their sex.. We used panel data collected using monthly surveys to compare the effects
of life events on drinking and smoking behaviors between man and woman. We found that men’s
and women’s consumption of cigarettes and alcohol were reduced during pregnancy period andafter having a child, compared with before pregnancy. We propose testable hypotheses in Section
2. An overview of the data and empirical method is presented in Section 3. Section 4 presents anddiscusses the major findings. Section 5 concludes the paper.
2. Hypotheses
According to the classical work of Smith (1853, p.321), in reference to men in the family, “themembers of his own family, those who usually live in the same house with him, his parents, hischildren...are naturally the objects of his warmest affections. They are naturally and usually the
The rate of men who support the view that "a husband should go to work, a wife should
stay home and take care of the family" is lower among younger generations (Gender
Equality Bureau Cabinet Office of Japan 2009).
4 An individual’s own current smoking and their partner's past smoking are statisticallyindependent, which indicates positive assortative matching in marriage over smoking in
the marriage market (Clark and Etile, 2006).
5 Smoking and drinking have a complementary relationship in Japan (Yamamura 2011).
Hence, there is a possibility that quitting smoking during pregnancy also reduces alcohol
consumption (Wehby et al., 2013).
3

4

persons upon whose happiness or misery his conduct must have the greatest influence" (1853, p.
321). Naturally, parents’ decision making depends not only on their own desire but also on thehappiness of family members. According to the definition of Becker (1981), "altruistic" meansthat the father’s (or mother’s) utility function positively depends on the well-being of theirchildren.
The framework of Becker can be applied to parents’ drinking and smoking behaviors. Even if
parents enjoy smoking and drinking, externalities from alcohol and tobacco consumption hinder
their children's health. Therefore, we assume that goods K (alcohol or cigarettes) directly increase
parents’ utility, but indirectly decrease their utility through the negative externality on theirchildren’s health. If parents are effectively altruistic, a certain amount of consumption of goods K
decreases parents' utility when the decrease in utility from externality caused by consumption of
goods K outweighs the increase in utility from the consumption of K. If parents adopt asufficiently serious attitude about the externality on their children's well-being, having a childleads parents to reduce the consumption of goods K.
Many studies have reported the negative externalities from women consuming cigarettes (e.g.,
Wehby et al., 2011; Yan 2013) and alcohol (e.g., O’Connor and Whaley 2007; Barreca and Page2015). Men’s smoking during their wife’s pregnancy exerts a negative influence on the birthoutcomes of the infant (Goel et al., 2004; Qui et al., 2014). Accordingly, we proposed thefollowing hypothesis:
Hypothesis 1: Pregnancy reduces not only women’s alcohol and cigarette consumption but also
men’s cigarette consumption.
Parents’ cigarette consumption inevitably leads to their infant being subjected to passive
smoking, which harms the child’s health (e.g., Abrevaya 2006; Adda and Cornaglia, 2010; Frijters
et al., 2011). Hence, we proposed a second hypothesis:
Hypothesis 2:

Compared with the period before pregnancy, the birth of a child reduces not only

women’s cigarette consumption but also that of men.
Although men in Japan are more inclined to participate in infant care than ever before (Gender
Equality Bureau Cabinet Office of Japan 2009), women are likely to be more involved withbringing up children. Especially during the breastfeeding period directly after giving birth,mothers have to breastfeed and care for their infant. Even in a state of only slight intoxication, amother cannot appropriately cope with any incident that may occur with her baby. In short,mothers must keep an eye on their infant at all times, so they cannot afford to drink alcohol. In
other words, the opportunity cost of drinking is very high because a mother's drinking could
possibly cause her baby to be subjected to life-threatening situations while in her care. Thus, if
5there is no negative externality from passive smoking, drinking is avoided by women after giving
birth. Hence, we proposed a third hypothesis.
Hypotheses 3: Compared with the period before being pregnant, giving birth reduces women’s
consumption of alcohol.
If there is no externality from the consuming goods K, the existence of other family members
is unlikely to change one’s consumption behavior. Different from cigarette consumption, afather’s consumption of alcohol does not generate externality on his baby in periods of his
spouse’s pregnancy and infant care. Here, we postulate a fourth hypothesis.
Hypotheses 4: Neither pregnancy nor childbirth change men’s drinking behavior.
3. Data and methods
3.1. Data
We aimed to examine how life events such as marriage, pregnancy, and having a childinfluence consumption behaviors. To this end, the targets of the survey were limited to men andwomen who were married or planned to get married in the future. Men and women who planned
to have a child in the future were included as survey participants Participant ages were between
17 and 51 years. We gathered individual-level panel data from all regions of Japan via internet
surveys. More specifically, we commissioned a market research company, INTAGE
Communications Inc., to conduct the research under the direction of the authors. Monthly surveys
were carried out for 3 years, from March 2012 to March 2015, a total of 37 surveys during thisperiod. A total 1,049 individuals participated in the first survey. However, during the 3-year
survey period, other individuals were included, for a total 1,855 participants during the survey
period. Surveys were conducted monthly; however, some participants failed to respond and others
dropped out of the surveys, giving a response rate of 60.1%. Finally, the sample size was reduced
to 24,418 completed surveys. Questionnaires included items querying individual socioeconomic
characteristics such as age, sex, household income, educational level, and work status. In addition,
every month participants were asked what events had occurred during the previous month suchas marriage, pregnancy (one’s own or a partner’s pregnancy), or birth of a baby. Such events often
occurred frequently during the survey period. The monthly panel surveys allowed us to compare
behaviors before and after these events for the same individual. We also obtained detailed
information about other events, such as experiences of annoyance, during each month. This
enabled us to investigate temporary effects concerning relationships with a partner and in daily
life. The quantities of alcohol and cigarettes consumed within a month were also queried, whichenabled us to explore how life events influenced drinking and smoking behaviors.
Table 1 presents definitions of the variables used in this research and their mean values, based
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on the men and women sampled. The mean value for DRINKING (consumption of alcohol
measured by the number of cans of beer per day) was about 0.77 for men and 0.34 for women,
which suggests that men drank alcohol more frequently than women. The mean value of
SMOKING (cigarette consumption per day) was 4.77 and 1.14 for men and women, respectively.
Hence, men were more inclined to drink and smoke than women. PREG values were 0.10 for men
and 0.11 for women, suggesting that about 10% of the sample had a pregnancy during the survey
period. After the pregnancy period, participants experienced the birth of a baby if miscarriage orabortion did not occur. Values for BABY were 0.37 for men and 0.31 for women, implying thatover 30% of the sample was caring for an infant during the survey period. MARRI values were0.52 for men and 0.48 for women, indicating that around 50% of the sample had a spouse. The
values for the variable ANNOY were slightly larger for women than for men. These values
possibly differed according to each individual, even if they experienced the same type of event;hence, these were subjective values about perceptions of daily life and differences in these values
are thought to reflect, to a certain extent, differences in perception between men and women.
Figures 1 and 2 compare consumption using the variables DRINKING and SMOKING,
respectively, between men and women. Figure 1 shows that around 40% (60%) of male (female)
respondents did not drink and this group accounted for the highest share; this tendency was moreclearly observed for SMOKING. Figure 2 shows that nonsmokers accounted for roughly 70% of
men and 90% of women. Generally, men are more likely to drink and smoke than women,
although quite a few men in our sample hardly drank and smoked.
Based on our sample of men, Table 2 presents the mean values of DRINKING and SMOKING
between the periods of the wife’s pregnancy (PREG=1), the period of having a baby (BABY=1),
and reference periods (PREG=0 and BABY=0). We performed a mean difference test between
the pregnancy and reference periods, and the infant care and reference periods. Consumption of
alcohol and cigarettes were lower during the period of pregnancy than the reference periods. The
difference for alcohol consumption was statistically significant whereas that for cigarette smoking
was not significant. Consumption of alcohol and cigarettes were lower after having a baby thanin the reference periods, and were statistically significant. All in all, pregnancy and child rearing
reduced the consumption of alcohol and cigarettes. The results among our sample of women(Table 3) suggest that consumption of alcohol and cigarettes were lower during pregnancy andwhile caring for a baby than during the reference periods. What is more, these differences were
statistically significant. This is in line with our hypotheses in Section 2. Further, considering
Tables 2 and 3 together indicates that the difference in mean values for women is far larger thanthat for men. This implies that the effect of pregnancy and having a baby on drinking and smoking
behaviors for women is larger than for men. However, Tables 2 and 3 did not control forunobservable individual characteristics and various control variables. To control for these factors,
7

regression estimations were conducted and the results are reported in the following sections.
3.2. Methods
To assess the effects of pregnancy and giving birth on drinking and smoking behaviors, the estimated function takes
the form:

SMOKING (or DRINKING) it = α0 + α1 PREG it + α2 BABY it + α3 MARRIit + α4 INCOMit+α5ANNOYit +α6AGEit +α7AGESQit +α8NOWORKit +α9PARTWORKit + ei+ m t + u it,
where SMOKING (or DRINKING)it represent the dependent variables for individuals i andsurvey time points t, and α represents the marginal effect of independent variables. As explainedin the previous section, surveys were conducted every month for 3 years and dummy variables
for the survey period were included to control for m, which includes factors that commonly
affected respondents at t6. Further, unobservable individual characteristics, ei, were controlled forby using the panel data analysis. Furthermore, both an upper limit (5 for DRINKING and 41 for
SMOKING) and lower limit (0 for DRINKING and SMOKING) were included. Therefore, thetwo-limit Tobit model was appropriate for estimation, and the random effects Tobit model wasused.
The key independent variables were PREG to capture the period of pregnancy and BABY tocapture the infant care period. Thus, PREG is exclusive to BABY, and the reference period for
PREG and BABY is the period before the pregnancy. Further, subsamples of men and women
were used for estimation, to compare the effects of PREG and BABY between men and women .
For women, from hypothesis 1 proposed in Section 2, negative values for PREG and BABY
would be expected when DRINKING and SMOKING are dependent variables. On the other hand,for men, hypothesis 2 leads us to predict that PREG and BABY would have a negative sign when
SMOKING is the dependent variable.
Apart from PREG and BABY, life events concerning family structure was controlled for by
MARRI. If there is a peer effect from the spouse, the effect would depend on the smoking anddrinking behavior of the respondent’s spouse. However, information about spouses’ smoking anddrinking behavior was not available owing to limited data. If relationships with other people
generate stress, people are likely to drink or smoke. ANNOY is predicted to have a positive signfor estimation of SMOKING and DRINKING. Economic and demographic conditions were
controlled by INCOM and AGE. Drinking and smoking behavior are possibly nonlinear to age
and so the square of age (AGESQ) was included. Work-related stress has been found to increase
Surveys were conducted from March 2012 to March 2015. Hence, there were 37 surveys
so 36 time-period dummy variables were included.
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alcohol and cigarette consumption (Ayyagari and Sindelar 2010; Goel 2014). NOWORK and
PARTWORK were dummy variables for work status.
4. Results and Discussion
Estimation results of the random Tobit model are reported in Table 4. Columns (1) and (2)indicate the results when DRINKING was the dependent variable, whereas columns (3) and (4)show the results when SMOKING was the dependent variable. The sample was divided into men
and women; the results for the men’s sample are presented in columns (1) and (3) and those of
the women’s sample are in columns (2) and (4). In each table, time point dummies are included
but not reported.
As demonstrated in Figures 1 and 2, the percentages for zero consumption of alcohol andtobacco are sufficiently high, which inevitably influences the estimation results. So as to take this
into consideration, the random Tobit model was preferred. As presented in Table 4, left-censoredobservations (at the lower bound, as were zero consumption observations) were 2677, 5843, 8204,
and 10400 in columns (1), (2), (3), and (4), respectively. In comparison, right-censoredobservations, which were at the upper bound, were small but controlled in the estimation. Table
4 shows that the coefficients of PREG and BABY have a negative sign and are statisticallysignificant in all columns. Therefore, pregnancy and infant care give not only women but also
men an incentive to reduce their alcohol and cigarette consumption during pregnancy and overthe course of baby care. As a whole, this supports hypotheses 1 and 2, and 3. On the other hand,both infant care and giving birth served to deter men’s drinking behavior, which is inconsistent
with hypothesis 4. We interpret this to mean that drinking does not allow men to care for theirpregnant wives and increases the burden of housework on wives, which in turn exerts a negative
influence on the fetus. What is more, childbirth generally increases the burden for women owing
to the division of labor within a household. In cases where the husband drinks alcohol, he is lesslikely to help with infant care, which in turn increases the burden on the wife. Consequently, thewoman’s stress from baby rearing leads to marital quarreling or, in extreme cases, infant abuse orneglect. Therefore, men have an incentive to refrain from drinking while their wives are pregnant
and caring for a child.
Regarding the absolute values of coefficients, values for women are generally larger thanthose for men, implying that women have a stronger incentive to avoid drinking and smoking thanmen. Absolute values of PREG for women were roughly six times higher than those for men when
the dependent variable was DRINKING as well as SMOKING. This might reflect that womenare more directly influenced by pregnancy and are more inclined to care for the baby than men.
We examined the results of key variables more closely. For estimation of DRINKING basedon the men’s sample, the absolute value of the coefficient for PREG was 0.15, which is nearly the9same as that for BABY. On the other hand, for the sample of women, the absolute value of thecoefficient for PREG was 0.96, which is 0.17 points larger than that for BABY. That is, the effectof BABY is smaller than that of PREG for women. The reason for these different effects of PREG
and BABY for women might be that a woman’s drinking directly influences her fetus but does
not directly influence her newborn. The effect of men’s drinking on the fetus and infant is also
indirect. However, the coefficient of BABY for women is larger than those of PREG and BABY
for men. In our interpretation, more time is generally spent by women caring for a baby than bymen, so women’s drinking has a larger effect on the baby. As a consequence, women have agreater incentive to reduce their consumption of alcohol. When it comes to men, the absolutevalue of the coefficient for PREG is nearly the same as that for BABY. Men demonstrated
motivation to reduce their alcohol consumption, probably out of concern for their wives who beara larger burden during periods of pregnancy and infant care. Hence, there was not much difference
between PREG and BABY. Consequently, the gender gap in reduction of alcohol consumption
during the pregnancy period became smaller during the infant care period, overall.
Regarding estimation of SMOKING, the absolute value of PREG was 2.07 for men and 11.2
for women, which is interpreted as suggesting that cigarette consumption was reduced by 2.07
cigarettes per day for men and by 11.2 per day for women during the period of pregnancy
compared with before pregnancy. However, the absolute value of BABY increased to 2.85 formen, while it was 11.2 for women, nearly the same as that of PREG. Differences in coefficientvalues between PREG and BABY for men is explained by the direct negative passive smoking
effect on the baby, which is larger than the indirect negative effect on the fetus because it isprotected by the mother’s body. That is, the negative externality from passive smoking strongly
prevented men from smoking so as to care for their baby’s health. On the other hand, women‘ssmoking has a direct negative effect on her fetus during pregnancy and on the baby during theperiod of infant care. Hence, the gap between sexes in the reduction of cigarette consumption
during the child care period was smaller than that during the pregnancy period. Considering theseestimation results together, it became evident that pregnancy has a larger effect on women’s
drinking behavior than does baby care whereas caring for an infant has a larger effect on men’ssmoking behavior than does pregnancy because of the negative externality of passive smoking.
As for control variables, MARRI was not statistically significant for three of four estimation
results. Concerning the exceptional case in column (2), MARRI had a negative sign, which isstatistically significant. We interpret this to mean that women become busy after marriage because
of increased household work, which serves to deter women from drinking. As a whole,
respondents did not consider the externality for their spouse. Accordingly, not only women but
also men put greater importance on their baby’s health than on that of their spouse. This can beinterpreted in various ways. First, from the results of MARRI, we assert that parents adopt
10altruism behavior toward their children but not toward their spouse. Second, the externality fromconsumption on family members varied according to age. That is, the negative effect on adults isthought to be distinctly smaller than that on a fetus or baby, such that getting married is less likely
to influence consuming behaviors. There was a significantly positive sign of ANNOY for womenwhen DRINKING was the dependent variable. However, for men, ANNOY did not yield asignificant sign in any columns. Therefore, compared with men, women are more likely to feelstress from annoyance in their daily lives, which could lead to drinking.
Our observations support our hypotheses 1 and 2, which leads us to assert that men change
their consuming behaviors by attaching importance to the externalities after family life events,
such as pregnancy and the birth of a child. This reflects that men in Japan have come to participate
in child rearing.
Existing studies have not found that pregnancy causes men to quit smoking (Cnattingius andThorslund, 1990; Blackburn et al., 2005). There are two possible reasons for this. First, men do
not take into account the outcomes of their smoking and drinking behaviors. Second, men do nothave sufficient knowledge about the externality on children, although they pay a lot of attention
to their children’s health. In modern Japanese society, fathers tend to take part in child rearing andappear to be informed about the negative externalities of smoking and drinking. Under thiscondition, we were able to test whether fathers reduced their alcohol and cigarette consumption
in an attempt to care for their children’s health.
5. Conclusion
A number of research works have shown that parents’ smoking and drinking have a
detrimental effect on their children’s health. If parents love their children and the children’s healthcondition is related to parents’ utility, parents’ consumption levels of alcohol and cigarettes are
determined by considering the outcome of negative externality from smoking and drinking
behaviors on their children.
We found the effect of passive smoking varied according to the circumstances of the baby.
The effect of smoking on a fetus seems to differ from the effect on a newborn. More precisely,
the degree of the negative externality depends on the period, such as pregnancy or infant careperiods, and on the parent’s sex. Based on our original panel data from respondents surveyed
monthly for 3 years, how pregnancy and childbirth changed alcohol and cigarette consumption
was explored by comparing results between men and women. Using a random Tobit model, we
found that consumption of alcohol and cigarettes was lower among both men and women during
pregnancy and baby rearing periods than before pregnancy. These results indicate that a predicted
negative externality to babies from their parents’ drinking and smoking behavior gives parents an
incentive to control these behaviors. Further, the degree of reduction of men’s cigarette11consumption after having a baby is larger than that during his partner’s pregnancy period. The
findings of this paper have made it evident that not only mothers but also fathers become more
careful about the health of their children and change their behaviors by considering theexternalities of smoking and drinking.
Acknowledgement
This study was supported by the Grant-in-Aid for Scientific Research A (Grant No.23243052) and B(Grant No. 16H03628) from the Japan Society for the Promotion of Science.

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Figure 1. Distribution of the variable DRINKING

Women

60
40
0

20

Percent

80

100

Men

0

2

4

6

0

4

2

6

drink
Graphs by Gender
Note: As indicated in Table 1, DRINKING is defined as daily consumption of alcohol, which is converted into a number of canned beers consumed (i.e., thenumber of canned beers (350 ml) respondents drank per day 0–5 (or more). For the question about monthly consumption of alcohol, respondents are asked to
select one of five choices: (1) not at all, (2) hardly drink (once or twice a month), (3) sometimes (several times a week), (4) one canned beer a day, (5) three canned
beers a day, (6) over five canned beers a day. We converted respondents’ answers to daily beers consumed.

15

Figure 2. Distribution of the variable SMOKING

Women

60
40
0

20

Percent

80

100

Men

0

10

20

30

40

0

10

20

30

40

smok
Graphsby Gender
Note: As
is indicatedin Table 1, SMOKING is defined as the number of cigarettes respondents smoked per day (0–41 or more). For the question aboutmonthly consumption of cigarettes, respondents were asked to select one of nine choices: (1) not at all, (2) hardly smoke, (3) sometimes smoke, (4) 1–5
cigarettes per day, (5) 6–10 cigarettes per day, (6) 11–20 cigarettes per day, (7) 21–30 cigarettes per day, (8) 31–40 cigarettes per day, (9) 41 or more cigarettes
per day. We converted respondents’ answers to daily cigarette consumption.

16

Table 1. Definitions of variables
Definition
Daily consumption of alcohol, which is converted into number of canned beer.
Number of canned beer (350 ml) respondent drinks per day.
0 -5 (5 or more).
Number of cigarettes respondent smoked per day.
0 (not at all)-41 (equal or more than 41 cigarettes).

Men
0.77

Women
0.34

4.77

1.14

0.10

0.11

BABY

It is 1 when respondent (or respondent’s wife) is pregnant, otherwise 0.
Pregnancy term which was predicted based on respondent child’s born months (9 months before
birth).
It is 1 after respondent’s (or respondent’s wife’s) baby was born, otherwise 0.

0.37

0.31

MARRI

It is 1 if respondent was married, otherwise 0.

0.52

0.48

INCOM

Monthly household income (10 thousands yean)

32

26

ANNOY

Respondent has been annoyed within a month.
0 (not at all)-5 (absolutely annoyed).

3.29

3.37

AGE

Age

35.9

31.9

AGESQ

Square of age

----

----

NOWORK

It is 1 if respondent does not work, otherwise 0.

0.02

0.02

PARTWORK

It is 1 if respondent is part-time worker, otherwise 0.

0.02

0.12

DRINKINGSMOKING
PREG

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Table 2. Mean difference test of drinking and smoking for men
His

partnerpregnant

was

He had a baby

Reference group(BABY=1)(His(PREG=1)

partnert-value]ist-value

notpregnant and he does not(1) vs(3)(2) vs (3)have baby)
(1)

(2)

(3)

DRINKING

0.65

0.74

0.81

4.59 ***

3.40 ***SMOKING

4.95

4.32

5.05

0.36

4.22 ***

Observations

1,192

4,542

6,632

*** indicates significance at the 5% and 1% levels, respectively. PREG=1 indicates that the respondent’s wife was pregnant.

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Table 3. Mean difference test of drinking and smoking for women in the sample
She waspregnant(PREG=1)

She had a baby

Reference group(BABY=1)(His

partnert-value]isnotpregnant and he does not(1)

t-value(1) vs(3)(2) vs (3)have baby)
(2)

(3)

DRINKING

0.07

0.15

0.49

4.44 ***

22.6 ***SMOKING

0.49

0.49

1.62

8.26***

12.7 ***

Observations

1,371

3,709

6,973

*** indicates significance at the 5% and 1% levels, respectively. PREG=1 indicates that the respondent was pregnant.

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Table 4. Random effects Tobit estimation(1)
DRINKING
Men−0.15***(−2.78)(2)
DRINKING
Women−0.96***(−17.8)(3)
SMOKINGMen−2.07***(−2.57)(4)
SMOKING
Women−11.2***(−8.50)BABY−0.14**(−2.47)−0.79***(−13.8)−2.85***(−3.33)−11.0***(−8.14)

MARRI

0.07
(1.62)−0.18***(−4.66)−0.21(−0.34)0.54(0.61)

INCOM

−0.34
(−0.86)

1.09***(2.80)−8.97(−1.57)0.31(0.03)

ANNOY−0.005(−0.59)0.02***(2.83)−0.003(−0.03)−0.02(−0.12)AGE

0.001(0.03)−0.05(−1.34)

1.73***(2.81)

1.34**(2.18)

AGESQ

0.0002(0.38)

0.001(1.65)−0.02***(−2.65)−0.02**(−2.16)NOWORK−0.08(−0.69)−0.08(−0.88)

4.88***(2.87)

1.20(0.58)PARTWORK−0.12(−0.86)−0.20(−0.36)−6.33***(−2.67)−3.21***(−2.66)Waldchi-square

72.5

567.7

84.9

151.8

Number ofgroups

826

1,029

826

1,029

Left-censored obs

2,677

5,843

8,204

10,400

Right-censored
obs

357

86

47

9

Observations

12,365

12,05312,365

12,053

PREG

Note: Numbers in parentheses are z-values. *, ** and *** indicate significance at the 10%, 5% and
1% levels, respectively. Numbers without parentheses are coefficients of each variable. The coefficientof INCOM is multiplied by 1000 for convenience of interpretation. Constant and time of the survey
are included, but their results are not reported.

20