Time use of married couples: Bayesian approach

ABSTRACT

The living hours data of individuals' time spent on daily activities are compositional and include many zeros because individuals do not pursue all activities every day. Thus, we should exercise caution in using such data for empirical analyses. The Bayesian method offers several advantages in analyzing compositional data. In this study, we analyze the time allocation of Japanese married couples using the Bayesian model. Based on the Bayes factors, we compare models that consider and do not consider the correlations between married couples' time use data. The model that considers the correlation shows superior performance. We show that the Bayesian method can adequately take into account the correlations of wives' and husbands' living hours, facilitating the calculation of partial effects that their activities' variables have on living hours. The partial effects of the model that considers the correlations between the couples' time use are easily calculated from the posterior results.

KEYWORDS:

• Bayesian statistics
• compositional data
• Markov chain Monte Carlo (MCMC)
• time allocation

JEL CLASSIFICATIONS:

• C11
• J12
• J22

Acknowledgments

The authors appreciate the comments of two anonymous referees, which improve the article greatly. They are grateful to the Institute for Research on Household Economics for providing the micro-data of the Japanese Panel Survey of Consumers (JPSC).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Scale invariance and subcompositional coherence are required in compositional data analysis [[1, p. 418], [12, p. 43]]. However, subcompositional coherence is not ensured in our study, because zeros are included in $Y_1,\dots ,Y_{D-1}$.

Additional information

Funding

The work of the first author was supported in part by a Grant-in-Aid for Scientific Research (No. 16K03589) from the Japan Society for the Promotion of Science (JSPS), while that of the first and second authors was supported in part by a Grant-in-Aid for Scientific Research (No. 17K03668) from the JSPS.