Abstract
The first part of this chapter draws on 12 waves of Japanese household longitudinal data (Keio Household Panel Survey, KHPS) and estimates a conditional fixed effects logit model to investigate the effects of housing equity constraints and income shocks on own-to-own residential moves in Japan by comparing the effects between 2004 to 2008 and 2009 to 2014. By looking at contemporaneous extended Loan-to-Value (ELTV) and extended Debt-to-Income (EDTI) ratios under the recourse-loan system , we examine whether housing equity constraints and negative income shocks have any impact on own-to-own residential moves and whether there is any difference between the two periods. Taking account of the specific nature of the recourse-loan system in Japan, we further investigate whether these effects differ between positive and negative equity households. The estimation results show that housing equity constraints and negative income shocks significantly deter own-to-own residential moves for positive equity households even in recent financial-easing periods. In the latter part of this chapter, we use Japanese prefectural-level data to analyze the relationship between borrowing patterns and house price dynamics under the recourse-loan system. Our principal finding is that, in prefectures where homeowners are highly leveraged (i.e., have high and extended loan-to-value ratios), house prices respond less sensitively than they do in prefectures where lower leveraged homeowners are common. This finding based on the recourse-loan system is quite different from the finding under the non-recourse-loan system , because under the recourse-loan system, the lock-in effect stemming from severe equity constraints is much more severe.
Sect. 2.2 is adapted from Seko et al. (2016), Toyo Keizai Inc. Sect. 2.3 is adapted from Seko et al. (2011a) presented at the International Economic Association 16th World Congress 2011.
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- 1.
Kiyotaki (2010) has suggested that interactions between credit restrictions and corporate and household diversity are important in the analysis of the business cycle.
- 2.
- 3.
The explanation of the theoretical model is based on Seko et al. (2012).
- 4.
The upper age limit of participants in the former KHPS at the time of the initial survey was different, at 69.
- 5.
For these prices for building and land, we used responses to the question to the homeowner, “What would you consider to be the current market price (the price if sold)?”
- 6.
This is equivalent to L in Eq. (2.5).
- 7.
- 8.
- 9.
See Dhrymes (1971), pp. 31–32.
- 10.
See Seko et al. (2011a) 3.3 for details.
- 11.
Lamont and Stein (1999), Table 1.
- 12.
See Table 2.3.
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Seko, M. (2019). House-Price Dynamics and Effects on the Macro Economy. In: Housing Markets and Household Behavior in Japan. Advances in Japanese Business and Economics, vol 19. Springer, Singapore. https://doi.org/10.1007/978-981-13-3369-9_2
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