Abstract
This paper examines the role of parental transfers on family size. We introduce a simple theoretical model of fertility decision where preferences towards children may differ between female and male spouses. Parental transfers increase both the household income and the bargaining power of the recipient spouse. Therefore, transfers from wife’s and husband’s parents may have dissimilar effects on the number of children. Our empirical result, based on a unique household-level data for Japan, supports this hypothesis. In particular, received transfers from the wife’s parents are negatively associated with the demand for children. In contrast, both received and expected transfers from the husband’s parents are positively associated with the demand for children. These results hold important policy implications.
Acknowledgements
We acknowledge the Osaka University program’s contributors Yoshiro Tsutsui, Fumio Ohtake and Shinsuke Ikeda. We are indebted to Editor Mariapia Mendola, two anonymous referees, Charles Horioka, participants of a seminar held at the American University of Sharjah, the 2018 Royal Economic Society Annual Conference, and the 38th Middle East Economic Association Annual Meeting for their helpful comments and suggestions. All errors are our own.
A Appendix
Descriptive statistics: holding the sample size constant.
Variable | Obs. | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
Number of children | 1,831 | 2.10 | 0.79 | 0 | 5 |
Transfer Rec. | 1,831 | 0.47 | 0.50 | 0 | 1 |
Transfer Exp. | 1,831 | 0.33 | 0.47 | 0 | 1 |
Transfer Rec. (W) | 1,831 | 0.23 | 0.42 | 0 | 1 |
Transfer Rec. (H) | 1,831 | 0.33 | 0.47 | 0 | 1 |
Transfer Exp. (W) | 1,831 | 0.17 | 0.37 | 0 | 1 |
Transfer Exp. (H) | 1,831 | 0.23 | 0.42 | 0 | 1 |
Marriage duration | 1,831 | 34.12 | 8.55 | 1 | 56 |
Net wealth | 1,831 | 34.47 | 37.05 | −31.25 | 200 |
Below high school (W) | 1,831 | 0.13 | 0.34 | 0 | 1 |
High school (W) | 1,831 | 0.57 | 0.50 | 0 | 1 |
Associate (W) | 1,831 | 0.20 | 0.40 | 0 | 1 |
Bach. or higher (W) | 1,831 | 0.10 | 0.31 | 0 | 1 |
Below high sch. (H) | 1,831 | 0.16 | 0.36 | 0 | 1 |
High school (H) | 1,831 | 0.45 | 0.50 | 0 | 1 |
Associate (H) | 1,831 | 0.05 | 0.22 | 0 | 1 |
Bach. or higher (H) | 1,831 | 0.34 | 0.47 | 0 | 1 |
Religiosity | 1,831 | 1.96 | 1.13 | 1 | 5 |
Notes: H stands for husband and W denotes wife. Abbreviations Rec., Exp. and Bach. stand for “received,” “expected” and “bachelor,” respectively.
Poisson regressions: holding the sample size constant.
Variable | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
---|---|---|---|---|---|
Transfer Rec. | −0.006 | ||||
(0.018) | |||||
Transfer Exp. | 0.032 | ||||
(0.021) | |||||
Transfer Rec. (W) | −0.060*** | −0.057*** | −0.051** | ||
(0.021) | (0.022) | (0.022) | |||
Transfer Rec. (H) | 0.034* | 0.031* | 0.036** | ||
(0.018) | (0.018) | (0.018) | |||
Transfer Exp. (W) | −0.012 | −0.003 | −0.002 | ||
(0.026) | (0.027) | (0.027) | |||
Transfer Exp. (H) | 0.049** | 0.043* | 0.044** | ||
(0.022) | (0.022) | (0.022) | |||
Marriage duration | 0.006*** | 0.006*** | 0.006*** | 0.006*** | 0.007*** |
(0.001) | (0.001) | (0.001) | (0.001) | (0.001) | |
Net wealth | −0.001*** | ||||
(0.000) | |||||
High school (W) | 0.063* | 0.069** | 0.064* | 0.068** | 0.073** |
(0.034) | (0.034) | (0.034) | (0.034) | (0.034) | |
Associate (W) | 0.086** | 0.098** | 0.090** | 0.097** | 0.104** |
(0.042) | (0.042) | (0.042) | (0.042) | (0.042) | |
Bach. or higher (W) | 0.094** | 0.111** | 0.096** | 0.107** | 0.121** |
(0.047) | (0.047) | (0.047) | (0.048) | (0.048) | |
High school (H) | −0.017 | −0.018 | −0.019 | −0.020 | −0.015 |
(0.032) | (0.032) | (0.032) | (0.032) | (0.032) | |
Associate (H) | 0.074 | 0.074 | 0.071 | 0.072 | 0.079 |
(0.051) | (0.051) | (0.051) | (0.051) | (0.051) | |
Bach. or higher (H) | −0.017 | −0.013 | −0.020 | −0.020 | −0.007 |
(0.035) | (0.035) | (0.035) | (0.035) | (0.035) | |
Religiosity | 0.017** | 0.017** | 0.018** | 0.017** | 0.016** |
(0.008) | (0.008) | (0.008) | (0.008) | (0.008) | |
Constant | 0.441*** | 0.457*** | 0.442*** | 0.437*** | 0.420*** |
(0.063) | (0.061) | (0.063) | (0.063) | (0.064) | |
N | 1,831 | 1,831 | 1,831 | 1,831 | 1,831 |
Notes: Significance levels: *** is <0.01, ** is <0.05 and * is <0.10. Huber/White robust standard errors are in parentheses. H stands for husband and W denotes wife. Abbreviations Rec., Exp. and Bach. stand for “received,” “expected” and “bachelor,” respectively.
Poisson regressions: robustness analyses.
Variable | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
---|---|---|---|---|---|
Transfer Rec. (W) | −0.048** | −0.041* | −0.035 | ||
(0.021) | (0.021) | (0.022) | |||
Transfer Rec. (H) | 0.037** | 0.033* | 0.032* | ||
(0.018) | (0.018) | (0.018) | |||
Transfer Exp. (W) | −0.001 | −0.015 | −0.004 | ||
(0.026) | (0.026) | (0.027) | |||
Transfer Exp. (H) | 0.042* | 0.015 | 0.018 | ||
(0.022) | (0.022) | (0.023) | |||
Inter vivos Rec. (W) | −0.060** | −0.055** | |||
(0.028) | (0.028) | ||||
Inter vivos Rec. (H) | 0.069*** | 0.055** | |||
(0.025) | (0.026) | ||||
Inter vivos Exp. (W) | −0.048 | ||||
(0.059) | |||||
Inter vivos Exp. (H) | 0.080* | ||||
(0.045) | |||||
Marriage duration | 0.008*** | 0.022*** | 0.022*** | 0.006*** | 0.007*** |
(0.001) | (0.003) | (0.004) | (0.001) | (0.001) | |
Net wealth | −0.000 | −0.000 | −0.001*** | −0.001*** | |
(0.000) | (0.000) | (0.000) | (0.000) | ||
Wealth index | −0.012*** | ||||
(0.002) | |||||
Age (W) | −0.023*** | −0.026*** | |||
(0.004) | (0.004) | ||||
Age (H) | 0.004 | ||||
(0.004) | |||||
High school (W) | 0.075** | 0.047 | 0.036 | 0.084** | 0.091** |
(0.034) | (0.034) | (0.034) | (0.036) | (0.036) | |
Associate (W) | 0.107** | 0.082* | 0.065 | 0.109** | 0.119*** |
(0.042) | (0.042) | (0.043) | (0.045) | (0.045) | |
Bach. or higher (W) | 0.125*** | 0.105** | 0.090* | 0.136*** | 0.142*** |
(0.047) | (0.048) | (0.049) | (0.051) | (0.051) | |
High school (H) | −0.013 | −0.019 | −0.000 | −0.037 | −0.041 |
(0.031) | (0.032) | (0.032) | (0.032) | (0.032) | |
Associate (H) | 0.087* | 0.077 | 0.074 | 0.081 | 0.068 |
(0.051) | (0.052) | (0.054) | (0.052) | (0.052) | |
Bach. or higher (H) | 0.000 | −0.009 | 0.009 | −0.040 | −0.044 |
(0.035) | (0.035) | (0.036) | (0.036) | (0.036) | |
Religiosity | 0.015* | 0.021*** | 0.023*** | 0.023*** | 0.021** |
(0.008) | (0.008) | (0.008) | (0.009) | (0.009) | |
Constant | 0.407*** | 1.309*** | 1.267*** | 0.453*** | 0.442*** |
(0.064) | (0.133) | (0.159) | (0.065) | (0.066) | |
N | 1,831 | 1,831 | 1,725 | 1,676 | 1,657 |
Notes: Significance levels: *** is <0.01, ** is <0.05 and * is <0.10. Huber/White robust standard errors are in parentheses. H stands for husband and W denotes wife. Abbreviations Rec., Exp. and Bach. stand for “received,” “expected” and “bachelor,” respectively.
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Supplementary Material
The online version of this article offers supplementary material (DOI:https://doi.org/10.1515/bejeap-2018-0118).
Note
This research uses micro-data from the Preference Parameters Study of Osaka University’s twenty-first Century COE Program “Behavioral Macrodynamics Based on Surveys and Experiments” and its Global COE project “Human Behavior and Socioeconomic Dynamics.”
© 2019 Walter de Gruyter GmbH, Berlin/Boston
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Artikel in diesem Heft
- Research Articles
- Public Health Insurance and Prescription Medications for Mental Illness
- Inter-Ethnic Friendship and Hostility between Roma and non-Roma Students in Hungary: The Role of Exposure and Academic Achievement
- The Costs of Firm Exit and Labour Market Policies: New Evidence from Europe
- Parental Transfers, Intra-household Bargaining and Fertility Decision
- Do Firms Supported by Credit Guarantee Schemes Report Better Financial Results 2 Years After the End of Intervention?
- Estimating the Impact of Ride-Hailing App Company Entry on Public Transportation Use in Major US Urban Areas
- Announced or Surprise Inspections and Oligopoly Competition
- Terrorism and Firm Performance: Empirical Evidence from Pakistan
- The Curious Case of Farmer Credit Cards: Evidence from an Indian Policy Reform
- Population Policy, Demographic Change, and Firm Returns: Evidence from China
- Sorting into Contests: Evidence from Production Contracts
- She-E-Os and the Cost of Debt: Do Female CEOs Pay Less for Credit?