spending as the michigan survey of consumer confidence. and why stop at music? people ’ s tastes in books, tv and radio may also offer a window on their soul. so too might their taste in games. indeed, i am interested in the potential for using gaming techniques, not just to extract data on people ’ s preferences, but as a means of generating data on preferences and actions. existing models, empirical and theoretical, often make strong assumptions about agent behaviour. theoretical models are based on axiomatic assumptions. empirical models are based on historical rotemberg ( 1984 ), for example, discusses the statistical rejection of rational expectations models for consumption and labour demand. tuckett and nyman ( 2017 ), shiller ( 2017 ) and nyman et al ( 2018 ). sabouni ( 2018 ). all speeches are available online at www. bankofengland. co. uk / speeches behaviours. these restrictions may, or may not, be borne out in future behaviour. if they are not, the model will break - down out of sample, as did the ( deductive ) dsge model and the ( inductive ) google flu model. a gaming environment could be used to understand behaviour in a way which placed fewer restrictions. people ’ s behaviour would be observed directly in the act of game - playing which, provided this behaviour was a reasonable reflection of true behaviour, would give us new data. because this is a virtual rather than real world, with shocks controlled and regulated, that could make it easier to address issues of causality and identification in response to shocks, including policy shocks. there are already multi - person games with primitive economies attached to them, which allow goods and monies to change hands between participants. these include eve online and world of warcraft. some economists have begun to use gaming technologies to understand behaviour. for example, steven levitt ( of freakonomics fame ) has used gaming platforms to understand the demand curve for virtual goods. the idea here would be to use a multi - person dynamic game to explore behaviour in a virtual economy. this would include player interactions – for example, the emergence of popular narratives which shape spending or saving. and it could include player reactions to policy intervention – for example, their responses to monetary and regulatory policies. indeed, in the latter role, the game could serve as a test - bed for policy action – a large - scale, dynamic, digital focus group. artificial intelligence experts are creating virtual environments to speed

revolution, portfolio penguin. shiller, r ( 2017 ), ‘ narrative economics ’, american economic review, vol. 104, no. 4, pp. 967 - 1004. sintef ( 2013 ), ‘ big data, for better or worse : 90 % of world ’ s data generated over last two years ’, sciencedaily, 22 may. stiglitz, j ( 2018 ), ‘ where modern macroeconomics went wrong ’, oxford review of economy policy, vol. 34, no. 1 - 2, pp. 70 - 106. tuckett, d and nyman, r ( 2017 ), ‘ the relative sentiment shift series for tracking the economy ’, mimeo. turrell, a, speigner, b, thurgood, j, djumalieva, j and copple, d ( forthcoming ), ‘ using online vacancies to understand the uk labour market from the bottom - up ’, bank of england staff working paper. all speeches are available online at www. bankofengland. co. uk / speeches