gdp has averaged less than 5 % in the us. in china, it has averaged around 20 %. in china, the constancy in high household saving rates masks two striking, but broadly offsetting, factors : a 10 percentage point fall in household ’ s income share ; and a 10 percentage point rise in household ’ s saving propensity ( ma and yi ( 2010 ) ). much of the rise in saving propensities appears to be precautionary. facing “ three mountains ” in the future – education, pensions and health care – chinese consumers have taken the high ( saving ) road. in the us, the fall in the household financial balance correlates strongly with the path of household net worth ( mckelvey ( 2010 ), chart 13 ). this correlation emerged strongly during the 1980s, with the simultaneous rise in net wealth and fall in saving. this correlation has remained strong as net worth has reversed recently due to falling house and equity prices. what lies behind these movements? lax monetary policy has been suggested by some ( taylor ( 2007 ) ). financial liberalisation is a second plausible candidate. this had the effect of loosening constraints on the supply of housing credit and thereby boosting housing demand and prices in the us. it also enabled households to mobilise and withdraw the accrued equity in their property to finance spending. estimates of housing equity withdrawal for spending rose from under 2 % of personal disposable income in 2000 to around 4 % at the peak in 2005 ( greenspan and kennedy ( 2007 ), chart 14 ). micro - level data support this story. they show that home equity withdrawal was driven primarily by households with low credit scores and high credit card utilisation rates, who are most likely to have been credit - constrained in the past ( mian and sufi ( 2009 ) ). as these constraints loosened, spending rose and saving fell. liberalisation fed impatience. these patterns are also consistent with an inequality - based explanation for lower saving ( rajan ( 2010 ) ). rising inequality may generate an increased desire to “ keep up with the jones ’ s ”. that, in turn, may have led to higher borrowing, and lower net saving, by the poor. and what applies within countries appears also to apply across them. among advanced countries, there is a significant negative relationship between within - country measures of inequality and the current account position ( chart 15 ). rising inequality, by lowering savings rates among the poor, appears to

have tended to see the ecological threat it poses, data scientists have seen the economic potential. i am caricaturing a little, but only a little. so who is right? and does the era of big data signal an oil - rush or an oil - spill? the truth, as often, probably lies somewhere in between. both deductive and inductive approaches can offer insights into understanding the world. they are better seen as methodological complements than as substitutes. put differently, using one approach in isolation increases the risk of making faulty inferences, and potentially serious mistakes, in understanding and policy. let me give a couple of examples to illustrate. during the global financial crisis, it is now fairly well accepted that the workhorse dynamic stochastic general equilibrium ( dsge ) model of the macro - economy fell at the first fence. it was unable to account for business cycle dynamics, during or after the crisis. while theoretically pure, it proved empirically fragile. that empirical fragility arose, i would suggest, from a methodological over - reliance on deductive methods. or, put differently, from too little focus being placed on real - world data from the past, including on crises. as a counter - example, in 2008 google launched a predictive model of flu outbreaks based on searches for phrases such as “ indications of flu ”. this did a terrific job of tracking flu outbreaks in the us in 2009 - 10. but that model ’ s predictions broke down spectacularly in the following years. that empirical fragility arose, i would suggest, from an over - reliance on empirical regularities and an over - adherence to inductive methods. or, put differently, from too little focus being placed on the deep medical causes of past flu outbreaks. in the first case, empirical fragility arose from too tight a set of axioms and restrictions, from placing too great an emphasis on theory over real - world correlations and historical experience. in the second, empirical haldane ( 2016 ). popper ( 1934 ) and popper ( 1959 ). bacon ( 1620 ). anderson ( 2008 ). for example, stiglitz ( 2018 ). ginsberg et al ( 2009 ). lazer et al ( 2014 ). all speeches are available online at www. bankofengland. co. uk / speeches fragility arose from too loose a set of axioms and restrictions, from observed empirical correlations being given too