ECONOMIC RESEARCH CENTERDISCUSSION PAPER
E-Series
No.E12-3

Determinants of Contraceptive Choice among Japanese
Women: Ten Years after the Pill Approvalby
Sayaka Nakamura

October 2012

ECONOMIC RESEARCH CENTERGRADUATE SCHOOL OF ECONOMICSNAGOYA UNIVERSITY

Determinants of Contraceptive Choice among Japanese Women:
Ten Years after the Pill Approval *Sayaka NakamuraaaSchool of Economics, Nagoya University

Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan
nakamuras@soec.nagoya-u.ac.jp
Phone & Fax: +81-52-789-5961

JEL Codes: J13 (family planning); I18 (government policy; regulation; public health);
D81 (criteria for decision-making under risk and uncertainty)
Key words: contraceptive choice, learning from experience, subjective probability*

I gratefully acknowledge financial support from a Grant-in-Aid for Young Scientists(start-up, No. 20830070) by the Japan Society for Promotion of Science (JSPS). I am
also grateful to Haruko Noguchi, Yoshiro Tsutsui and seminar participants at Nihon
University for their helpful comments.
1

Abstract
The Japanese government approved the use of oral contraception in 1999, butoral contraceptive (OC) users remain a small minority in Japan. Based on an online
survey conducted in 2010, I examine the factors determining Japanese women’s choiceof contraceptive methods by estimating multinomial choice models. The estimation
results indicate that OC use is positively associated with age, willingness to pay (WTP)
for contraceptive effectiveness, frequency of intercourse, and experience with abortion
or emergency contraception. These findings suggest that OC use increases as womenlearn from experience and that the low and declining trend in the frequency ofintercourse in Japan offers one explanation for the slow diffusion of OCs. Additionally,
the prevalent OC use among women with a higher risk of unintended pregnancies
suggests that OC approval may have significantly reduced the incidence of unintended
pregnancies despite the low average prevalence of OC use. Subjective probabilities
regarding each method’s effectiveness and disruption to mood, partner disapproval, side
benefits and minor side effects are important determinants of contraceptive choice.
Somewhat surprisingly, the correlations between subjective probabilities and women's
demographic and socioeconomic characteristics are weak. Overall, the results imply that
increased contraceptive knowledge among both men and women could significantly
increase the use of OCs in Japan. (206 words)

2

“Birth control pills cause a woman’s physiology to malfunction and work by altering
the body’s state from normal to abnormal. I feel that it is rather strange if there are noside effects. … Another thing I am afraid of is the spread of AIDS. … If approval of thepills leads to the reduced use of condoms, then it runs the risk of interfering withmeasures against AIDS.”
Junichiro Koizumi, former minister of health (1996-1998) and former prime minister(2001-2006), excerpt from “Junichiro Koizumi’s Let’s Talk Straight: Pills Approved!
Are They Safe?” Bart, March 24, 1997.
1. Introduction
Previous studies indicate that legal access to OCs had a significant impact on American
society, including increasing women’s enrollment in professional graduate schools,
increasing their ages at their first marriage (Goldin and Katz 2002), decreasing the birthrate (Guldi 2008) and improving the well-being of children (Ananat and Hungerman2012). This raises the following question: What are the effects of the Japanese
government’s approval of OCs? In contrast to other developed countries, physicians inJapan could not legally prescribe low-dosage hormonal pills for family planningpurposes until 1999. 1 The rate of OC use was approximately 1% in Japan in the 1980s
and early 1990s, and researchers expected it to significantly increase after thelegalization of low-dosage OCs (Population Problems Research Council 1990; Oddens
and Lolkema 1998). However, the diffusion of OCs among Japanese women has beenslow. Specifically, according to a report by the United Nations, only 1% of married (orin-union) women aged 15 to 49 use OCs in Japan compared to 16.8% in North America
1Physicians could legally prescribe higher-dosage pills for medical reasons such as

irregular menstrual periods.
3and 45.5% in Western Europe (United Nations 2011). Additionally, based on the
National Fertility Survey conducted in 2005, the percentage of pill users is 1.4% amongsexually active Japanese women aged 18 to 34 who have never been married (Kaneko et
al. 2008). This is in sharp contrast to what occurred in the United States in the 1960s
and 1970s: the diffusion of OCs was rapid once women were able to legally accessthem.
The remarks by Junichiro Koizumi quoted above represent the negative attitudesof Japanese politicians and bureaucrats, as well as the mass-media, toward OCs. In
addition, the Japanese Ministry of Health and Welfare argued that the pill could
encourage promiscuity and lower sexual morality by allowing women to have multiple
sexual partners without the risk of pregnancy (Hollander 2006). While this type of“anti-pill” attitude, which is prevalent in Japan (Matsumoto 2005), could certainly be
related to low OC use, it is unclear how it affects Japanese women’s preferences andperceptions regarding contraceptive methods. Prior studies find that the most common
reason given by Japanese women for not using OCs is concern about side effects.
Specifically, Suga and Kitamura (2009) find that 53% of Japanese women who do notintend to use the pill report concerns about side effects as a reason. Similarly, according
to Matsumoto et al. (2011), 50% of Japanese women who have never used OCs list
concern about side effects as a reason compared to only 25% and 17% of their
American and French counterparts, respectively. Nevertheless, the relative importanceof concerns about side effects in contraceptive choice has not been examined.
This study examines determinants of Japanese women’s choice of contraceptive
methods based on an online survey conducted in 2010, approximately ten years after thelegalization of low-dose OCs in Japan. The Japanese context offers a unique setting in
4which a birth control technology became available after it had been widely adopted inother countries and evidence of its efficacy and safety had been collected. To myknowledge, there are no other studies that estimate a regression model of contraceptive
choice using Japanese data either before or after OC approval. 2 As possible
determinants of contraceptive choice, I examine not only women's demographic andsocioeconomic characteristics but also their subjective beliefs regarding the costs andbenefits of each contraceptive method as explanatory variables, following Delavande(2008).
My empirical analysis (i) uncovers the characteristics of OC-adopters and (ii)examines possible reasons for the slow diffusion of OCs in Japan. With respect to (i),the impact of OC approval depends not only on the prevalence of OC use but also on
the characteristics of new OC users. In particular, if women with a higher risk ofunintended pregnancy use OCs, the impact on abortion and/or unplanned childbirths
could be greater. Similarly, if OC use is more prevalent among women who incur
greater losses in career opportunities due to unintended childbirth, then the legal accessto OCs could have a greater impact on the career choices and participation of women in
the labor market. Regarding (ii), I examine whether hypotheses regarding the reasonsfor low OC use in Japan are consistent with the observed differences between users andnon-users of OCs among Japanese women in my sample.
2

Ogawa and Retherford (1991) estimate a binary logit model using data on married

Japanese women, in which the dependent variable is whether a woman intends to use
OC, conditional on government approval. They find that the coefficient of abortion
intention in the case of contraceptive failure is significantly positive and that of theextended family dummy is significantly negative.
5

The remainder of this paper is organized as follows. The next section describes
the data. Section 3 describes the regression model of contraceptive choice on women's
characteristics and presents the estimation results. In section 4, I add subjective
probabilities to the explanatory variables of the regression model. Section 5 discusses
the estimation results obtained in sections 3 and 4, and section 6 concludes.

2. DataWith the collaboration of INTAGE Interactive, Inc., online survey data arecollected from 2,141 young women (18-30 years old) who live in Japan and areregistered as monitors with a web-based survey system (Cue monitors). The survey isconducted in two steps. First, a screening survey is conducted with a random sample of
11,696 young female monitors to select those (1) who had sexual intercourse with amale partner within the last 12 months, (2) who currently do not intend to become
pregnant, and (3) who have not undergone sterilization and whose partner has notundergone sterilization. 3 The 4,820 women who met the criteria of the screening wereinvited to participate in the full survey, and 2,141 of them completed it. Of these
respondents, the 1,873 women who reported that they currently used contraception were3

All of these randomly selected monitors participated in the screening survey.

Regarding (1), 60% report having this experience, 33% deny having this experience,and 6% do not answer. Regarding (2), 21% report a positive intention, 75% report anegative intention, and 4% do not answer. Regarding (3), 87% answer that neither the
respondent nor her partner has undergone sterilization, 2% answer that either the
respondent or her partner have undergone sterilization, and 11% do not answer.
6asked for further details on their choice of contraceptive method.
Women who are in their twenties have the highest number of abortions per
capita in Japan (Baba et al. 2005). In addition, women who are younger than 35 are lesslikely to use sterilization and IUDs compared to their older counterparts (Sato andIwasawa 2006). Thus, limiting the analysis to 18- to 30-year-old women and excluding
women who have undergone sterilization or whose partner has undergone sterilization
allows me to focus on a smaller number of contraceptive methods, therefore simplifying
the analysis. The other selection criteria are intended to limit the sample to those whowill realistically make contraceptive choices.
Table 1 shows the currently used contraceptive methods of all respondents. The
male condom is by far the most commonly used method. Ineffective non-modern
methods (i.e., rhythm and withdrawal) are the second most common. The rate of OC use
is 6.9%, which is much higher than the overall 1-2% prevalence of OC use in Japan
reported by prior studies (Kaneko et al. 2008; United Nations 2011). The reason for this
could be that my sample is restricted to women who do not intend to become pregnant
and have had at least one intercourse experience within the past 12 months. Only 22
women choose contraceptive methods other than these three methods, such as thefemale condom. The male condom will henceforth be referred to as “condom” because
the use of female condoms is rare. When estimating a regression model of contraceptive
choice, I exclude these 22 observations and limit the analysis to the 2,119 women whochoose condoms, OCs, a combination of condoms and OCs, and non-modern methods(the full sample). The respondents were asked about their knowledge of each method
and their subjective risk perceptions regarding each of the methods they know only ifthey reported current use of contraception. Therefore, when analyzing how
7

contraceptive choice is associated with subjective risk perceptions, I further exclude
women who do not use contraception from the analysis. This limits my analysis to the
1,535 women who choose among condoms, OCs, a combination of condoms and OCs,and ineffective methods, and who know about at least two of these methods (thesub-sample).
Definitions of the variables are provided in Table 2. The respondents are asked
which contraceptive method they currently use, and those who report the current use ofcontraception are further asked whether they know each of the three most common
methods: condoms, OCs, and ineffective methods. Following Delavande (2008), WTP isdetermined based on a scenario where only two methods are available: one is 85%
effective (i.e., 15% probability of getting pregnant) and is free of charge, and the otheris 100% effective (i.e., 0% probability of getting pregnant). Respondents are asked
about their WTP for the 100% effective method. Both methods require taking one pill
per week and are completely identical except for the level of contraceptive effectiveness.
The summary statistics of the variables are shown in Table 3. The statistics from the fullsample are presented on the left, and those from the subsample are presented on theright. The use of ineffective methods is less prevalent in the subsample than in the fullsample, which is expected because women who report not using contraception are
excluded from the subsample. The mean values of the explanatory variables are
generally similar between the two samples. The definitions and summary statistics ofthe subjective probability variables are presented and discussed in Section 4.

3. Case-Specific Conditional Logit Analysis
3.1. Estimation Method8I use a multinomial logistic model to regress contraceptive choice on women’s
individual characteristics. Because all the explanatory variables are individual
characteristics and are thus case-specific (i.e., do not vary by alternative), I use acase-specific conditional logit model. The choice categories are: condom without OC,
OC with or without condom, and no modern methods. 4 When I estimate the modelusing the full sample, the last category includes both no contraception and ineffective
no-modern methods. When I use the subsample, thus limiting my sample to women who
are currently using contraception, the last category only includes the use of ineffective
non-modern methods. The explanatory variables are the intercepts for non-basealternatives and individual characteristics. I use robust standard errors. I conduct a
Hausman-McFadden Test and confirm that the independence of irrelevant alternatives(IIA) assumption holds with both samples because excluding each of the alternatives
does not significantly change the estimates (Hausman and McFadden 1984).

3.2. Results
The estimation results are shown in Table 4, where the estimated coefficientsare presented as marginal effects. The results from the full sample are presented on theleft, and those from the subsample are presented on the right. Both samples yield similar
results, except for the marginal effects of Frequency_0, Single, Emergency,
Frequency_unknown, and Education_unknown. Among women who are not in
4

A specification with an additional choice category of dual condom and OC use is not

feasible because only 27 women choose this category. Case-specific conditional logit
models cannot be identified unless each alternative is chosen by a sufficient number ofindividuals.
9relationship and those who do not experience intercourse frequently, some may answer
that they currently use contraception and report which contraceptive method they would
use if they were to have an intercourse, while others may answer that they do not use
contraception because they do not have intercourse and report no use of modern
methods. Such potential variation in reporting might account for the different estimation
results between the samples regarding Frequency_0 and Single. Additionally, relatively
small variations in Emergency, Frequency_unknown, and Education_unknown mightlead to significant changes in the estimated coefficients when a non-negligible portionof observations are removed from the sample. The marginal effects of most of thewomen's characteristics on the choice probabilities for condoms and OCs are highly
similar across the samples, suggesting that removing women who report not using
contraception does not affect the results regarding the predictors of OC and condom use.
Willingness to pay for contraceptive effectiveness, frequent intercourse,
unmarried marital status, older age, experience with emergency contraception, andexperience with abortion are strong predictors of OC use. Among these factors,
frequency of intercourse and age are negatively associated with condom use. Years ofeducation is positively correlated with condom use, negatively correlated with use ofnon-modern methods and insignificantly associated with OC use. The overall number ofpartners, full-time working status, and smoking status have little predictive power.

4. Alternative-Specific Conditional Logit Analysis: Incorporating Subjective
Probabilities
In this section, I examine the association between subjective risk perceptions
and contraceptive choice by regressing contraceptive choice on both individual women's
10characteristics and the reported subjective probabilities regarding the pros and cons ofeach contraceptive method.
4.1. Subjective Probability Variables
Women who reported currently using contraception are asked about theirsubjective probabilities regarding the pros and cons of each contraceptive method.
Definitions of the subjective probability variables are provided in Table 5. The
respondents were asked about the percent chance of each of the following occurring,conditional on the use of each contraceptive method:

the respondent gets pregnant in the next 12 months, conditional on her use of themethod during this period;the respondent contracts STDs in the next 12 months, conditional on her use of themethod during this period;the respondent's partner disapproves her use of the method;

the respondent's religion or social norms do not align with her use of the method;the method ruins the mood.

In addition, respondents were asked the percent chance that they would experience thefollowing events in the next 12 months, conditional on OC use during this period:

minor (i.e., non-life-threatening) adverse effects such as weight gain, nausea,
headache, bleeding, vaginitis, swelling;

serious (i.e., life-threatening) adverse effects;side benefits (i.e., non-contraceptive benefits).

The construction of these variables largely follows Delavande (2008), though thequestions were slightly modified to better reflect the Japanese context. Because
respondents may use “50%” to avoid reporting precise numbers (Bruine de Bruin et al.
112000), I prohibit answering “50%” and instruct the respondents to choose between 49%
and 51% if their subjective probability is 50%.
Table 6 shows the summary statistics of the subjective probabilities conditionalon each of the four contraceptive methods. On one hand, the reported subjective
probabilities are partly consistent with medical knowledge. Specifically, the meanvalues of the subjective probability that respondents will become pregnant conditionalon the use of each method indicate that the order of perceived contraceptive
effectiveness is, from the strongest to the weakest, dual use of OC and condom, single
use of OC, single use of condom, ineffective methods. Likewise, the mean values of theprobability of contracting STDs indicate that most women know that condoms are
effective in preventing STDs and OCs are not. 5 In addition, the average subjective
probability of the side benefits of OCs is 21.8%, consistent with the medical literaturethat demonstrates significant beneficial effects of OCs on menorrhagia (excessive
bleeding during menstruation), dysmenorrhoea (painful menstruation), and acne (Maiaand Casoy 2008). On the other hand, the average subjective probabilities regarding theside effects of OCs are considerably higher than those indicated by the medical

5

The mean of the subjective probability that respondents would contract STDs is lower

conditional on the single use of OCs than ineffective methods (i.e., no use of OC or
condom), and lower conditional on the dual use of OCs and condoms than single use of
condoms. This might indicate that some women mistakenly believe that OCs reduce therisk of STDs. Alternatively, this might be due to the differences in risk evaluation
between women who know about OCs and those who do not because the latter do notreport subjective probabilities regarding OCs.
12

literature. Large cohort studies find no harmful effect of OCs on all-cause mortality(Beral et al. 1999; Vessey et al. 2003), and recent placebo-controlled randomized trials
find little evidence that OCs have nonspecific side effects, such as headache, nausea, or
weight gain (Grimes and Schulz 2011).
The mean values of the subjective probabilities that the use of each method
ruins the mood indicate that some women expect the use of condoms and ineffective
methods such as withdrawal to be detrimental in this respect. The average subjective
probabilities regarding religious and social disapproval suggest that few Japanesewomen feel religious or moral concerns regarding the use of condoms and OCs despite
the conservative ideas that link OC use with promiscuity (Hollander 2006). The meanvalues of the subjective probabilities of the partner's disapproval of the use of eachmethod indicate that the order of perceived partner disapproval is, from the strongest to
the weakest, ineffective methods, dual use of OCs and condoms, single use of OCs, andsingle use of condoms. This relatively strong aversion to OCs among Japanese men isconsistent with Suga and Kitamura (2009).

4.2. Estimation Method
In the previous section, I regress contraceptive choice on individual women's
characteristics, and in this section, I add subjective probabilities to the explanatory
variables. Because subjective probability variables vary by alternative, I use analternative-specific conditional logit model instead of the case-specific conditional logit
model used above. I estimate a multinomial logistic model of contraceptive choice inwhich the explanatory variables include subjective probabilities in addition to individual
characteristics. Because subjective probability questions are only asked to the women13

who report currently using contraception, I limit my sample to these women (thesubsample). For this analysis, I assume that women only choose from the four mostcommon categories: condoms without OCs, OCs without condoms, a combination of
condoms and OCs, and ineffective methods. In contrast to the estimation in the previous
section, I distinguish between single use of OCs and dual use of OCs and condoms
because subjective probabilities are reported separately for these methods in the survey.
The effects of women’s characteristics are aggregated for OC use both with and without
condom use because only 27 women choose dual use of condoms and OCs. I use robust
standard errors.
I conduct a Hausman-McFadden Test and confirm that the IIA assumption
holds because excluding each one of the alternatives does not significantly change theestimates (Hausman and McFadden 1984). The only exception is that the coefficients ofintersection terms between individual-specific characteristics and the dummy variablefor OC use (with or without condoms) change significantly when the alternative of
single use of OCs is excluded. Because the vast majority (82%) of OC users does notuse condoms, these coefficients cannot be precisely estimated when the women whochoose single use of OCs are excluded from the sample. I also estimate a mixed-logit
model where the alternative-specific effect for condom use, including single use of
condoms and dual use of condoms and OC, and that for OC use, including single use of
OCs and dual use of condoms and OCs, are normally distributed. The estimatedstandard errors of these alternative-specific effects are statistically insignificant, and thismodification does not cause significant changes to the estimation results. This suggeststhat unobservable similarities between single use of condoms and dual use of OCs andcondoms and those between single use of OCs and dual use of OCs and condoms are14both small, consistent with the IIA assumption.

4.3. Results
Table 7 shows the estimation results, in which the base alternative is single useof condoms, and presents the odds ratios of the estimated coefficients. 6 Model 1 is
identical to the model presented in the previous section, in which the explanatory
variables only include individual characteristics and three alternatives are given:
ineffective methods, condoms without OCs, and OCs with and without condoms. In
Models 2 and 3, four alternatives are given: ineffective methods, condoms without OCs,
OCs without condoms, and dual use of OCs and condoms. Model 2 includes bothsubjective probabilities and individual characteristics as explanatory variables, whereas
Model 3 includes subjective probabilities only.
The estimated coefficients of subjective probabilities are similar between
Models 2 and 3, except that Prob(pregnancy)*WTP is marginally significant in Model 3
but insignificant in Model 2. 7 In both models, the coefficients of Pr(partner's
disapproval), Pr(interruption), and Pr(minor adverse effects) are significantly negative,
and the coefficient of Pr(side benefits) is significantly positive. These results imply thatthe subjective risks of partner disapproval, interruption to the mood, and minor side
effects prevent the use of the method and the subjective chance of side benefits
6

Odds ratios are presented instead of marginal effects because, unlike the case-specificconditional logit analysis presented above, the marginal effects of the coefficientscannot be obtained for an alternative-specific conditional logit analysis.
7

When both Prob(pregnancy) and Prob(pregnancy)*WTP are included as explanatory

variables in Models 2 and 3, neither is significant.
15

increases OC use. Pr(STD), Pr(immoral), and Pr(major side effects) are insignificant inboth Models 2 and 3, indicating that subjective risk perceptions regarding STDs,
religious/social disapproval, and the serious life-threatening side effects of OCs are notsignificantly associated with contraceptive choice. Pr(partner's disapproval)*OC is also
insignificant in both models, implying that the influence of partner disapproval does notdiffer between OC use and the other alternatives.
The estimated coefficients of individual characteristics on the choiceprobabilities are also similar between Models 1 and 2, with a few exceptions: WTP andMarried are significantly associated with OC use relative to condom use in Model 1 but
not in Model 2, and Frequency_0 and Income_married are significantly associated withthe use of ineffective methods relative to condom use in Model 2 but not Model 1. Table
8 presents the estimation results in which the base alternative is the use of ineffective
methods and compares the estimated coefficients of individual characteristics between
Models 1 and 2. 8 Again, these two models yield similar results, except that WTP issignificantly associated with OC use relative to the use of ineffective methods in Model
1 but not Model 2 and that Frequency_0 and Income_married are significantly
associated with the single use of condoms relative to the use of ineffective methods inModel 2 but not Model 1. The differences in the coefficients of the intersection termswith WTP are not surprising because Model 2 includes Pr(pregnancy)*WTP, anotherintersection term with WTP, as an explanatory variable.
Therefore, adding subjective probabilities to the explanatory variables does not
drastically change the estimated coefficients of individual characteristics, as suggested
8

The estimated coefficients of subjective probability variables are omitted in Table 8

because they are independent of the choice of the base alternative.
16

by these similarities between the estimation results of Models 1 and 2. Nor does adding
individual characteristics to the explanatory variables drastically change the estimatedcoefficients of the subjective probabilities, as indicated by the similarities between theestimation results of Models 2 and 3. These findings imply that the individual
characteristics considered in this study offer little explanation for individual
heterogeneity in subjective probabilities and that the variation in contraceptive choiceassociated with individual characteristics cannot be explained by differences insubjective probabilities. In other words, individual characteristics and individual
subjective beliefs significantly and largely independently affect contraceptive choice.

5. Discussion
5.1. Women’s Characteristics
The estimation results indicate that OC use is positively associated with moresexual experience (as measured by age and intercourse frequency), experience ofincidents and near incidents of contraceptive failure (as measured by experience withabortion and emergency contraception), and individual valuation of contraception (asmeasured by WTP for contraceptive effectiveness). However, these factors are notpositively associated with condom use. In contrast, age, intercourse frequency, andexperience with abortion are negatively associated with the probability of condom use,suggesting that women shift from condoms to OCs as they accumulate sexual
experience or experience contraceptive failure.
The positive association between intercourse frequency and OC use suggestthat the low and declining frequency of intercourse in Japan offers one explanation forthe low OC use in Japan. OC use incurs a relatively high fixed cost, including both17

monetary costs and the burden of obtaining prescriptions and taking a pill every day,and zero marginal (i.e., incremental) costs because the cost of OC use does not varywith intercourse frequency. In contrast, the fixed costs of condoms and ineffective
methods are small, if not zero, and these methods could incur nonnegligible marginal
costs such as the psychological burden associated with administration. Thus, it is as
expected that women with higher intercourse frequencies are more likely to use OCs.
OC use is significantly lower in Japan than in other developed countries, as is thefrequency of sexual intercourse. According to Durex (2005), the reported intercourse
frequency in Japan of 45 times per year is the lowest among the 41 surveyed countries,
and less than the half of the average frequency of 103 times per year. Additionally, therate of OC use in Japan realized after its approval is lower than was expected prior toapproval. According to the Population Problems Research Council (1990), in 1990,
approximately 10% of married Japanese women under the age of 50 answered that they
intended to use OCs if they became available. While I could not find any studies that
demonstrate the evolution of intercourse frequency in Japan, the steady decline inpregnancy rates and domestic shipments of condoms in the 2000s implies a declining
trend in intercourse frequency (Sato et al. 2008).
OC use is significantly more prevalent among women with a higher risk ofunintended pregnancy, such as those with higher intercourse frequency and who have
had experience with abortions. According to Goto et al. (2002), 40.1% of women who
have had unintended pregnancies have had more than one unintended pregnancy. Thesefindings imply that OC approval may have significantly reduced unintended
pregnancies and artificial abortions despite the low average prevalence of OC use andthat increased access to OCs could further reduce unintended pregnancies. Similarly, the18

positive association between WTP for effectiveness and OC use implies that OC
approval has reduced the rate of unintended pregnancies, especially among womenwhose perceived cost of pregnancy is high. Provided that WTP for effectiveness reflects
the loss of individual women’s career opportunities due to childbirth, the approval ofOCs may have had a significant impact on the career choices and labor participation of
women despite the low average rate of OC use.
A possible explanation for the negative association between being married andusing OCs is that some married women without pregnancy intentions could havehusbands with pregnancy intentions, whereas this type of disagreement in pregnancy
intention is unlikely among unmarried couples because out of wedlock births are still
considered taboo in Japan. If OC use is difficult for married women who do not havetheir husbands’ consent, then married women whose husbands intend to have children
are unlikely to use OCs. The result that women with higher levels of education are more
likely to choose condoms but are no more likely to choose OCs is difficult to interpret,but one possibility is that the partners of well-educated women proactively use
condoms.
Finally, there is no statistically significant relationship between OC use and awoman’s number of sexual partners, controlling for other factors. This finding does notsupport the claim that OCs encourage promiscuity by allowing women to have multiple
sexual partners without the risk of pregnancy. However, a woman’s number of partners
is weakly associated with a decreased probability of condom use, which raises concerns
regarding STDs.

5.2. Subjective Probabilities
19

The subjective probabilities could reflect important determinants ofcontraceptive choice other than women’s individual characteristics, such as relationshipcharacteristics (Chao 2002; Kusunoki and Upchurch 2011) and social learning (Kohler
1997; Behrman et al. 2002). In particular, subjective beliefs regarding the risk of STDs,
the effectiveness of male-oriented methods (e.g., condoms), and partners’ disapproval ofeach method are likely to be influenced by the relationship context. Similarly,
information communicated by close acquaintances could affect individuals’ risk
perceptions, while the effect of social learning on contraceptive choice might be weakerin information-oriented societies such as contemporary Japan, in contrast to the findingsof Kohler (1997) and Behrman et al. (2002) in the developing world. Local differencesin OC use rates are small in my sample, which does not support the effect of localizedsocial learning on the diffusion of OCs.
The most commonly reported reason for not using OCs among Japanesewomen is concern about side effects (Suga and Kitamura 2009; Matsumoto et al. 2011).
Consistent with this result, the subjective probability that OCs cause minor side effects
is negatively and significantly associated with OC use. However, the subjective
probability that OCs have life-threatening side effects is insignificantly associated with
contraceptive choice. Overall, the estimation results indicate that concerns regarding theminor side effects of OCs are an important but not dominant factor in contraceptive
choice. The finding that OC use is positively and significantly associated with thesubjective probability of the side benefits of OCs is consistent with Suga and Kitamura(2009).
The results show that partner disapproval is a strong predictor not only of theuse of male-oriented methods such as condoms and withdrawal but also of OC use,20

which is typically considered to be a female-oriented method because it does not require
men's cooperation. According to Suga and Kitamura (2009), 80.5% of Japanese men areopposed to their partners’ use of OCs, and 55.7% of them report concerns about side
effects as a reason. Therefore, Japanese men’s negative perceptions of OCs could offer
at least a partial explanation for the low OC use in Japan. The subjective probability thata method interferes with the mood is also significantly associated with contraceptive
choice, while religious or social concerns are insignificantly associated with
contraceptive choice.
The subjective risk of STD contraction is insignificantly associated with
contraceptive choice. This might imply that it is difficult to infer the probability that apartner has contracted or will contract an STD rather than women’s lack of concern
regarding STDs. Nevertheless, this result raises concerns and demands further
investigations on STD awareness in Japan. This finding differs from Delavande (2008),
who reports a significant association of the subjective probability of STD contraction
with contraceptive choice, whereas my other findings are generally consistent with hers.
Delavande (2008) collects data via interviews and the majority of respondents are
American college students. Thus, differences in data collection methods and study
subject characteristics might account for the differences in results.

6. Conclusion
This study examines the determinants of Japanese women’s choice ofcontraceptive methods. I conducted a web-based survey in 2010 and estimatedmultinomial models of contraceptive choice using the data from the survey. The
estimation results imply that women’s tendencies to use OCs increase as they learn from21

experience. The estimation results also imply that the low and declining frequency ofintercourse in Japan offers one explanation for the slow diffusion of OCs among
Japanese women. In addition, the finding that OC use is much more prevalent among
women with a higher risk of unintended pregnancy suggests that OC approval may havesignificantly reduced unintended pregnancies despite the low average rate of OC use.
Subjective beliefs regarding each method’s effectiveness, disruption to the mood,partner disapproval, and the side benefits and minor side effects of OCs are also
important determinants of contraceptive choice, whereas the subjective probability thatOCs cause serious, life-threatening side effects is insignificantly associated with
contraceptive choice. Somewhat surprisingly, the correlations between subjective
probabilities and women's demographic and socioeconomic characteristics are weak,
which might imply that the variations in subjective probabilities reflect unsubstantiatedbeliefs rather than actual differences in individual situations.
Overall, the empirical results imply that increased contraceptive knowledge
among both men and women could significantly increase the use of OCs in Japan. First,
the perceived risk of minor side effects among the Japanese women included in thisstudy is negatively and significantly associated with OC use and is significantly higher
compared to the population-based probabilities (Grimes and Schulz 2011). This finding
implies that learning about recent medical findings could reduce Japanese women's
concerns regarding the side effects of OCs and increase their OC use. Second, this study
finds a significant association of male partners' disagreement with the use of bothmale-oriented and female-oriented contraceptive methods, and according to a previous
survey, the majority of Japanese men is opposed to their partners' use of OCs, often
raising concerns regarding side effects (Suga and Kitamura 2009). Thus, increased
22

medical knowledge could reduce men's concerns over side effects and thus reduce theiraversion toward OCs. Third, age, frequent intercourse, and experience with abortion are
positively associated with OC use and are negatively associated with condom use,suggesting that Japanese women become more inclined to use OCs and more averse tocondoms as they accumulate sexual experience or experience contraceptive failure. If
learning population-based statistical information has similar effects on contraceptive
behavior as learning from experience, this type of information could increase OC use
among young and inexperienced women to a rate similar to that of older and moreexperienced women.

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26

Table 1: Current contraceptive choice of surveyed women (N=2141)
Currently used primary method of contraception%

Included in

Included infull sample

sub-sample(N=2119)(N=1535)

12.5%

Y

N

7.6%

Y

Y

Y

Y

No modern methods
No methods (i.e., does not use contraception)
Ineffective methods (e.g., rhythm and withdrawal)
without modern methods
Modern methods (with or without ineffective methods)
Male condom

71.9%

Y

Y

OC without male condom

5.7%

Y

Y

OC & male condom

1.3%

Y

Y

Female condom

0.2%

N

N

Spermicide

0.2%

N

N

Spermicide & male condom

0.1%

N

N

IUD

0.0%

N

N

Other (e.g., pessary)

0.4%

N

N

27

Table 2: Definition of the variables
Variable Name

Definition

Choice_nomodern=1 if does not use any modern method, 0 otherwise

Choice_ineffective=1 if uses ineffective methods only, 0 otherwise

Choice_condom

Choice_OC

Choice_OC&condom=1 if uses male condom, with or without ineffective but with no other modern methods, 0
otherwise=1 if uses OC (excluding emergency OCs), with or without ineffective method but with no othermodern method, 0 otherwise=1 if uses OC (excluding emergency OCs) and male condom, with or without ineffective
method but with no other modern method, 0 otherwise

Know_ineffective=1 if knows any of ineffective methods (e.g., rhythm and withdrawal), 0 otherwise

Know_condom=1 if knows male condom, 0 otherwise

Know_OC=1 if knows OC (excluding emergency OCs), 0 otherwise

WTP

willingness to pay for hypothetical, perfectly effective contraceptive method

Frequency_0=1 if frequency of intercourse per month is less than 1, 0 otherwise

Frequency_6=1 if frequency of intercourse per month is 6 or more, 0 otherwise

Frequency_unknown=1 if frequency of intercourse is unknown, 0 otherwise

Single=1 if not in relationship, 0 otherwise#Partner_5=1 if ever had 5 or more partners, 0 otherwise

Married=1 if legally married, 0 otherwiseAgerespondent's age

Education

years of non-compulsory education completed

Education_unknown=1 if years of completed non-compulsory education is unknown, 0 otherwise

Income_unmarried=own annual income (in million yen) if unmarried, 0 otherwise

Income_married=annual couple income (in million yen) if married, 0 otherwise

Income_unknown=1 if annual income is unknown, 0 otherwise

Student=1 if student, 0 otherwise

Fulltime=1 if works fulltime, 0 otherwise

Smoking=1 if smokes at least 1 cigarette per day, 0 otherwise

Emergency=1 if ever had emergency contraception, 0 otherwise

Abortion=1 if ever had artificial abortion, 0 otherwise#Children

number of respondent's children28

Table 3: Summary statistics
Subsample: Women using

Full Sample (N=2119)

contraception (N=1535)
Mean

SD

Mean

SD

Choice_nomodern

0.203

0.403

Choice_ineffective

0.104

0.305

Choice_condom

0.727

0.446

Choice_condom

0.805

0.397

Choice_OC

0.057

0.232

Choice_OC

0.074

0.262

Choice_OC&condom

0.013

0.112

Choice_OC&condom

0.018

0.131

Know_ineffective

0.781

0.414

Know_condom

0.996

0.062

Know_OC

0.939

0.239

WTP

2123.62851.1

WTP

2241.93015.8Frequency_0

0.270

0.444

Frequency_0

0.231

0.421

Frequency_6

0.160

0.367

Frequency_6

0.177

0.382

Frequency_unknown

0.051

0.221

Frequency_unknown

0.042

0.200

Single

0.123

0.328

Single

0.094

0.292

#Partner_5

0.344

0.475

#Partner_5

0.361

0.480

Married

0.288

0.453

Married

0.273

0.446

Age

24.9

3.4

Age

24.9

3.4

Education

4.837

2.210

Education

4.880

2.203

Education_unknown

0.016

0.126

Education_unknown

0.017

0.129

Income_unmarried

0.866

1.268

Income_unmarried

0.894

1.264

Income_married

0.887

1.866

Income_married

0.842

1.820

Income_unknown

0.065

0.246

Income_unknown

0.058

0.234

Student

0.277

0.448

Student

0.283

0.451

Fulltime

0.399

0.490

Fulltime

0.414

0.493

Smoking

0.137

0.344

Smoking

0.141

0.349

Emergency

0.088

0.284

Emergency

0.105

0.307

Abortion

0.123

0.328

Abortion

0.130

0.337

#Children

0.336

0.712

#Children

0.311

0.682

29

Table 4: Conditional logit analysis of contraceptive choice(Marginal effects of individual characteristics on the choice probability of each alternative arepresented)
Full Sample(N=2119)

Women using contraception (N=1535)

No modern
Condom
without OC

OC with or

methodwithout(ineffective

condommethods or no

Condom
without OC

OC with orwithout
condomIneffective
methods

contraception)
Marginal Effects
WTP

0.027

0.031 ***

-0.0590.020

0.040 ***

-0.060Frequency_0-0.024-0.0150.040 *

0.044

-0.014-0.030Frequency_6-0.071 **0.050 ***

0.021

-0.085 ***0.066 ***

0.019

Frequency_unknown-0.085 *0.000

0.085 *

-0.0120.020-0.008Single-0.205 ***-0.026 **0.231 ***

0.072 *

-0.031-0.040#Partner_5-0.039 *

0.007

0.032

-0.042 *

0.009

0.033

Married-0.073-0.050 ***0.123 ***

-0.018-0.068 ***

0.085

Age

-0.014 ***0.006 ***

0.008 **

-0.018 ***0.008 ***

0.009 **

Education

0.011 **

0.000

-0.011 **0.013 **

-0.002-0.011 **Education_unknown

0.023

0.040

-0.064

0.042

0.032

-0.074 **Income_unmarried-0.003-0.005

0.008

0.000

-0.0040.004

Income_married-0.007

0.002

0.005

0.006

0.004

-0.010

Income_unknown

0.025-0.013-0.0120.049-0.001-0.048Student

0.044-0.005-0.0400.045-0.011-0.034

Fulltime

0.011

0.007

-0.018

0.001

0.003

-0.004

Smoking-0.023-0.0020.025-0.017-0.005

0.022

Emergency-0.0150.071 ***

-0.057 *-0.064 *0.077 ***

-0.013

Abortion-0.052 *0.054 ***

-0.002-0.062 *0.076 ***

-0.014#Children

0.028-0.016-0.0120.040 *

-0.020-0.020Statistics#maximum alternatives

33

average #alternatives

3

2.7

247.8

133.2

-1437.7-833.72

chi

log likelihood

Notes: *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard
errors are used. Alternative-specific intercepts are included in the estimation but omitted from the table.

30

Table 5: Definition of subjective probability variables
Variable Name
Pr(pregnancy)

Pr(STD)

Definition
subjective probability of getting pregnant if respondent uses the method for next 12monthssubjective probability of contracting STD if respondent uses the method for next 12monthsPr(partner's disapproval)

subjective probability that partner disapproves the method

Pr(interruption)subjective probability that the method ruins the moodPr(immoral)

subjective probability that respondent's religion or social norm disapproves the method

Pr(minor adverse effect)

Pr(serious adverse effect)

Pr(side benefit)

subjective probability of having minor adverse effect if respondent uses the method for
one year (e.g., weight gain, nausea, headache, breeding, vaginitis, swelling, etc.)
subjective probability of having serious, life-threatening adverse effect if respondentuses the method for next 12 months
subjective probability of having side benefits (i.e., non-contraceptive benefits) if
respondent uses the method for next 12 months

Table 6: Summary statistics of subjective probabilities (N=1535)
Ineffective

Condom

OC

OC&condom

Mean

SD

Mean

SD

Mean

SD

Mean

SD

Pr(pregnancy)

32.6

32.0

10.3

18.1

5.6

13.0

3.0

9.0

Pr(STD)

20.5

28.0

7.3

14.9

15.8

24.6

4.9

11.7

Pr(partner's disapproval)

20.7

31.9

10.8

21.0

13.1

25.6

15.1

26.6

Pr(interruption)

12.1

22.6

15.4

22.6

2.5

10.3

11.0

20.6

Pr(immoral)

13.5

29.2

1.3

7.5

3.8

14.4

2.6

11.5

Pr(minor adverse effect)

35.0

32.2

35.0

32.2

Pr(serious adverse effect)

14.0

21.1

14.0

21.1

Pr(side benefit)

21.8

29.2

21.8

29.2

31

Table 7: Conditional logit analysis of contraceptive choice: condom without OC as base alternative(N=1535, Odds-ratios of the estimated coefficients are presented)
Model1Model2Model3

Alternative-specific variables
Pr(pregnancy)*WTP

0.993

0.986

Pr(STD)

0.999

0.998

Pr(partner's disapproval)

0.968

Pr(partner's disapproval)*OC

0.995

Pr(interruption)

0.991

Pr(immoral)

1.002

Pr(minor adverse effect)

0.983

Pr(serious adverse effect)

0.997

Pr(side benefit)

1.018

Individual-specific variables

***

0.969

***

0.991

***

0.985

***

1.021
Ineffective

without condom

methods

without condom

methods

Frequency_0

0.781

Frequency_6

2.229

0.579

1.530

0.556

0.714

0.661

0.644

1.305

2.152

Frequency_unknown

1.291

0.945

0.955

0.929

Single

0.550

0.606

0.500

0.513

#Partner_5

1.190

1.388

1.176

1.249

Married

0.333

**

1.940

0.426

1.929

Age

1.142

***

1.108

***

1.160

Education

0.956

0.895

**

Education_unknown

1.355

Income_unmarried

***

***

***

*

1.116

1.110

***

0.927

0.894

**

0.347

1.114

0.286

0.946

1.033

0.888

0.996

Income_married

1.046

0.912

1.003

0.864

Income_unknown

0.931

0.558

0.898

0.529

Student

0.815

0.688

1.026

0.710

Fulltime

1.037

0.969

1.470

0.865

Smoking

0.952

1.227

0.912

1.042

Emergency

2.301

***

0.960

2.378

***

0.902

Abortion

2.298

***

0.948

1.992

**

1.045

#Children

0.729

0.798

0.691

32

***

0.994

OC with or

***

***

0.999

Ineffective

1.671

***

0.994

OC with or

WTP

*

0.739

**

***

Table 7: Conditional logit analysis of contraceptive choice: condom without OC as base alternative(N=1535, Odds-ratios of the estimated coefficients are presented) (continued)
Model1Model2Model3

Statistics#maximum alternatives

3

4

4

average #alternatives

2.7

3.7

3.7

141.0

945.8

994.6

-833.7-762.1-818.8chi

2

log likelihood

Notes: *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard
errors are used. Alternative-specific intercepts are included in the estimation but omitted from the table.

Table 8: Conditional logit analysis of contraceptive choice: ineffective methods as base alternative(N=1535, Odds-ratios of the estimated coefficients are presented)
Model1
Individual-specific variables

Model2

OC with or

OC with orcondom without

without

condom without
without

OCOC

condomWTP

2.890

Frequency_0

1.091

Frequency_6

1.713

Frequency_unknown

condom
**

1.731

2.752

1.799

1.399

1.025

1.552

0.768

1.928

1.355

1.054

1.028

1.077

Single

0.920

1.661

0.976

1.951

#Partner_5

0.856

0.720

0.941

0.801

Married

0.170

0.513

0.221

Age

1.030

0.902

***

1.045

0.901

***

Education

1.070

1.118

**

1.037

1.118

**

Education_unknown

3.908

2.884

3.897

3.498

Income_unmarried

0.914

0.967

0.892

1.004

Income_married

1.148

1.097

1.160

1.158

Income_unknown

1.660

1.788

1.696

1.890

Student

1.177

1.449

1.445

1.408

Fulltime

1.067

1.031

1.699

1.155

Smoking

0.776

0.815

0.876

0.960

Emergency

2.417

**

1.048

2.636

**

1.108

Abortion

2.411

***

1.053

1.907

*

0.957

#Children

0.914

1.253

0.935

*

***

**

**

*

0.896

0.518

**

1.353

Notes: *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard
errors are used. Alternative-specific intercepts are included in the estimation but omitted from the table. The
estimated coefficients of subjective probability variables in Model 2 are also omitted from the table.

33