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What motivates single women to save? the case of Japan

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Using Japanese panel data, we analyze precautionary savings due to staying single in the presence of income uncertainty. Our panel analysis finds that compared with young women who are likely to get married within 3 years, those who are not plan to have 44 percent more savings for precautionary purposes, and 108 percent more for retirement. These results suggest that in facing higher risk of income fluctuation due to choosing to marry late or remain unmarried, young women intend to have more wealth to mitigate the income risk inherent in single life.

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  1. The other economic reasons for marriage are increasing returns, an imperfect credit market, and the sharing of collective goods (Becker (1973, 1981) and Grossbard-Shechtman (1993).

  2. With respect to same-sex couples’ family formation, Negrusa and Oreffice (2011) analyze their household financial decisions using the 2000 US census data.

  3. We thank the co-editor, F. Woolley, for suggesting the use of this transformation.

  4. Pericoli and Ventura (2011) use whether or not the married couple will be divorced or separated after 2 years as the marital disruption risk when they examine the consequences of family dissolution risk onto consumption and saving.

  5. The data contain 15 waves (1993–2007). In 1993, the survey started with 1,500 women (1,002 married women and 498 single women) between 24 and 34 years of age as of October 1993 (cohort A). In 1997, 500 women between 24 and 27 years of age as of October 1997 (201 married women and 299 single women) were added (cohort B); in 2003, 836 women between 24 and 29 years of age as of October 2003 (351 married women and 485 single women) were added (cohort C).

  6. The drop–off, pick–up method is conducted as follows: First, a census taker visits randomly selected households and leaves a hard copy of the questionnaire. Next, the selected households respond to the questionnaire within a given time period, and then the census takers collect the completed questionnaires by visiting the households again at a convenient time. According to Sakamoto (2006), 42.2% of respondents in cohort A were lost from cumulative attrition from the first to the eleventh wave, which is larger than the first 11-year cumulative attrition rate of the Panel Study of Income Dynamics (32.2%).

  7. The time frame to which the wealth target variables refer is clear only in the ninth and tenth waves since the survey ascertains the timeframe with the question, “In how many years do you expect to reach your wealth target?” From the answer to the question, the unmarried respondents expected to reach their wealth target level in a shorter period of time than the married respondents. The difference in the time frame is the largest for no purpose (6.3 years for unmarried vs. 10.7 years for married).

  8. Some might argue that saving is fungible and that it does not make sense to speak of saving for a specific motive, but we disagree with this argument for the following two reasons: first, household surveys consistently find that respondents are able to allocate their savings and wealth among specific motives (see, for example, Horioka and Watanabe (1997)). Second, in Japan, there are many types of saving accounts for specific motives, such as housing purchase and retirement, and penalties are imposed if the funds are used for a different purpose.

  9. The instrument could be invalid if these five dummy variables on the preferences for marriage have direct effects on wealth target, whereas when we regress wealth target on these five dummy variables on the preferences for marriage, these five dummies have insignificant coefficients.

  10. In Japan, “prefecture” is a general term for 47 local public entities. They include cities, towns, and villages. According to the 2005 census, the most populated prefecture is Tokyo (12.5 million), while the least populated is Tottori (0.6 million).

  11. Single mothers are not excluded by design, but we drop them.

  12. The survey collects information about inheritance. However, more than 99% of the respondents neither received financial or real assets as intervivos and inheritance from their parents in the past nor expected to receive them in the future.

  13. Detailed regression results of Tables 4 and 5 are available from the internet (

  14. We thank the co-editor, F. Woolley, for suggesting the interpretation of dummy coefficients. The same applies to the following dummy coefficients.

  15. The options are as follows: (1) a meeting arranged by relatives and families, (2) a meeting arranged by friends, (3) asked friends and relatives to introduce a male marriage partner, (4) joined a matrimonial agency in the last year, (5) continued to be part of a matrimonial agency over the year, (6) read a bridal magazine, (7) talked about marriage with a boyfriend, (8) got engaged, (9) other, and (10) did nothing.


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We are greatly indebted to Charles Yuji Horioka for his kind advice and comments throughout the process of writing this paper. We would also like to thank Setsuya Fukuda, Hidehiko Ichimura, Yukinobu Kitamura, Ayako Kondo, Colin McKenzie, Kei Sakata, Shizuka Sekita, and the participants at the Kansai Labor Economics Seminar, the Horioka seminar, the Empirical Micro Research Seminar at Tokyo University, the seminar at the National Institute of Population and Social Security Research, and the 2011 spring annual meeting of the Japanese Economic Association for their helpful comments and discussion. We are deeply indebted to the editor, S. Grossbard, and co-editor, F. Woolley, as well as to two anonymous referees for their very helpful comments. We also thank the Institute for Research on Household Economics for permitting us to use data from “the Japanese Panel Survey of Consumers (JPSC).” Finally, we are indebted to the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government for the Grant-in-Aid for Scientific Research (#22330094, #24730262 and #22330083) supporting this research.

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Correspondence to Wataru Kureishi.

Appendix: The validity of the instrumental variables

Appendix: The validity of the instrumental variables

We need to check the validity of the five dummy variables for the marriage preferences or intentions and unmarried rate as instruments. First, these variables should not correlate with the error term of our estimation equation (1) in Sect. 2.1—that is, the unobservable determinants of wealth for precautionary purposes. Second, these variables should partially correlate with marriage i, once the impact of the other exogenous variables has been netted out.

1.1 Variables for the marriage preferences or intentions

We discuss whether the five dummy variables for the marriage preferences are valid as an instrument. Since we have already discussed the first condition in Sect. 4.1, we consider the second condition here. We can anticipate that respondents who are very fond of the idea of marriage are more likely to marry. In the survey questionnaire we use, the survey asks, “Did you engage in some activities related to marriage during the last year?”; multiple answers were allowed.Footnote 15 The answers from our 590 respondents indicate that those who have a strong marriage preference are more likely to undertake more than one activity related to marriage. In fact, 81.8 % of those who answered “I am engaged and going to get married” (engaged = 1) undertook more than one activity related to marriage, while 70.5 % of those who answered “I would like to get married soon“(hope to marry soon = 1) and 35.7 % of those who answered “I would like to get married, not soon, but eventually” (hope to marry eventually = 1) did so. These findings imply that those with a strong marriage preference are active with regard to marriage, and such activities provide them with greater chances of meeting a marriage partner and getting married in the future.

1.1.1 Unmarried rate

Next, we examine whether the percentage of unmarried women aged 24–35 by prefecture (unmarried rate) is valid as an instrument. We needed to ascertain that the first condition—that interprefectural variations in the ratio of the unmarried women are unlikely to correlate with unobservable determinants of saving behavior—is reasonable. It is obvious that the ratio of unmarried women by prefecture does not affect individual-level saving behavior.

We consider the second condition—that is, whether or not this ratio correlates with \( \widehat{marriage}_{i} \). It is reasonable that in a prefecture where the ratio of unmarried women is high, it is more likely that the respondents will remain unmarried. This is because of a specific feature of the mobility of women in Japan. That is, there is a gender gap: women leave home for marriage, while men leave home before marriage. Actually, Suzuki (2003), who uses the Fourth National Survey on Household Changes, shows that in Japan the proportions of home leaving associated with marriage are 20.5 % for males and 52.9 % for females, which is in sharp contrast to Western countries. From this immobility of unmarried women in Japan, a higher share of unmarried women in a prefecture implies that there are many marriage competitors, and thus it is difficult to find a marriage partner in the prefecture. Therefore, the percentage of unmarried women by prefecture will be a good indicator of their ability to get married. In addition, this can be understood to mean that in an environment with a large number of unmarried women, being unmarried becomes a norm of sorts, and unmarried women therefore may not feel anxious about being single.

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Kureishi, W., Wakabayashi, M. What motivates single women to save? the case of Japan. Rev Econ Household 11, 681–704 (2013).

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