inverse dependency ratio ), second, the real property price index, and third, total loans in real terms. 2 in japan ( chart 1 ), we have two peaks in the working - age population ratio, accompanied by two peaks in the real property price index, which is the real land price index. of these two, claessens, stijn, m. ayhan kose, and marco e. terrones, ( 2008 ), “ what happens during recessions, crunches and busts? ” imf working paper 08 / 274 ( washington : international monetary fund ) and claessens, stijn, giovanni dell ’ ariccia, deniz igan, and luc laeven, ( 2010 ), “ cross - country experiences and policy implications from the global financial crisis, ” economic policy, volume 25, pp. 267 – 293. the ratios of working - age population to the rest ( inverse dependency ratios ) are taken from the homepage of the united nations. property prices in real terms ( cpi adjusted ) are : japan : total average, urban land nationwide, urban land price index, japan real estate institute, us : us 10 cities, s & p / case - shiller home price indices, standard & poors, and china : zhongfang shanghai residential property index, zhongfang shanghai real estate index office. loans in real terms ( cpi adjusted ) are japan : loans of depository corporations, flow of funds, bank of japan, us : loans and leases in bank credit, all commercial banks, not seasonally adjusted, federal reserve, and china : financial institution loans, people ’ s bank of china. bis central bankers ’ speeches the second peak, around 1991, happened to be a malign bubble which triggered a subsequent long period of stagnation. then, what is the difference between the two? the volume of total loans in real terms may suggest an answer. real loans were increasing at the time of the first peak, but their level was not as high as during the second peak. a remarkably similar picture is found in the united states ( chart 2 ). we have two peaks in the working - age population ratio, though not as pronounced as in japan. and the real property price index, which is the real house price index, seems to have two peaks, roughly coinciding with the demographic change. again, the second peak triggered the financial crisis of 2008, though the first

kiyohiko g nishimura : how to detect and respond to property bubbles – challenges for policy - makers remarks by mr kiyohiko g nishimura, deputy governor of the bank of japan, at the reserve bank of australia - bis research conference “ property markets and financial stability ”, sydney, 21 august 2012. * * * let me begin by commending the impressive achievements of this bis project, as exemplified by the presentations yesterday and this morning. in this regard, i am sure you will join me in applauding the efforts of frank packer and his accomplished colleagues at bis asia & pacific. in spite of this impressive progress, however, i still think that we are only at the starting line : many problems remain to be solved before this project can provide guidelines for policy - making. learned academics may be experts in “ explaining ” the causes and effects of past events that have shaken the world. to put it metaphorically, failures in the last war are always scrutinized thoroughly, and their lessons are presented. in contrast, we policy makers should be looking forward into the future. we should not be fighting the last war when things are changing rapidly, no matter how well we may have learned the lessons of the last war. the two main questions from the policy maker ’ s point of view are : how can we detect malign property bubbles? and, how should we respond to them? 1. how to detect malign bubbles let me start with the first question : how can we detect malign bubbles? here we should be aware that not all property bubbles lead to financial crises, and not all financial crises are preceded by property bubbles. international panel studies have shown that two - thirds of 46 systemic banking crises were preceded by house price boom - bust patterns, while 35 out of 51 house price - bust episodes were followed by a crisis. 1 so there are both malign bubbles and benign ones. then, what leads to a malign bubble? looking back at past experience of malign bubbles, we find another factor which has not been touched upon by the presentations so far : the demographic transition from a “ population dividend ” to the “ burden of an ageing population. ” let us look at the charts comparing the japanese property bubble of the 1990s, the us house price bubble of the 2000s, and the possible chinese property bubble. in these three charts, i juxtapose, first, the ratio of working - age population to the rest ( the