testing hypotheses or investigating the effects of a previous policy change, for example. different users will have different tastes, beliefs and needs and will prefer certain types of models. ” i understand a number of central banks, including the bank of england, have followed this path. i am sure that you will hear more of this later from the expert from the boe himself. such an approach is of course hugely taxing on resources and here in asia, we could perhaps look upon it as a desirable goal to strive for. finally, i also encourage a pragmatic approach. here, i am referring to the practice of supplementing model output with sectoral analyses, survey data, market trends as well as value judgements. modellers need to be aware of the limitations of their models. the complexities of the economy cannot be fully captured by a macroeconometric model, no matter how comprehensive its specifications. in particular, macro models cannot quantify variables such as panic, greed or the herd psychology of investors. as a result, even the predictions of the most sophisticated model have been thrown off by unexpected developments in the environment. this was clearly evidenced during the turmoil in international financial markets in august 1998, when the ltcm crisis unfolded. conclusion the new monetary model of singapore incorporates many of the new features and innovations in macro modelling. in time to come, i hope that it will be further fine - tuned so as to reflect the five qualities that i have just spoken about. in this process, it might be useful to modellers in singapore and even from the region to meet more regularly to exchange ideas and learn from each other ’ s experiences. in the post - asian crisis era, one of the main concerns of regional policymakers is that of monitoring vulnerabilities of the domestic economies to external shocks. there is a need for a formal and reliable monitoring mechanism to help supplement overall surveillance efforts. perhaps macro models could be employed to this end. if workable, this might just be the function that renders models not only relevant but actually indispensable to policymakers. i leave you with this thought and wish you all a day of fruitful deliberations. “ empirical modelling in economics : specification and evaluation ”, the 1998 marshall lectures.

became clear that supply - side factors and the role of expectations also needed to be worked in. thus, today many macro models build in these factors. one example is how most models now work in the impact of the economy ’ s potential output on inflation outcomes. in the us, modellers are faced with growing evidence of an emergent “ new economy ”. the hypothesis is that high rates of growth can be sustained without triggering off inflationary pressures, even at the point of full employment. i understand that staff from the federal reserve constantly update their estimates of key model parameters, such as the nairu2 as well as trend productivity to reflect the features of this new economy. these updated estimates have been used to help shape the fed ’ s forecasts of growth and inflation, thereby ensuring that the policymaking process is an informed one. the second quality i have in mind refers specifically to the model ’ s role in forecasting and policy analysis. a model must have a good track record, in order to serve as a reliable guide to the policymaker. i am not asking for spot - on point forecasts or estimates but, at a minimum, a macro model must be able to provide policymakers with a good feel for the directional effects of various policy options. thirdly, the workings of the model must be transparent. ideally, the structure of the model should correspond to a flowchart of the linkages within the economy. fed governor laurence meyer has said in a recent speech3 that model - based forecasting needs to “ start with a paradigm and end with a story ”. non - accelerating inflation rate of unemployment. to the stern graduate school of business, new york university : “ start with a paradigm, end with a story : the value of model - based forecasting and policy analysis ”. ultimately, when policymakers want to introduce policy changes, they want to know through what channels the effect of this policy will flow and how agents will react to this policy. in other words, policymakers want to know the story going on behind each policy reaction and not just be buried under masses of model output. fourth, macro modelling should adopt a pluralistic approach. policymakers are like consumers while macro modellers are the producers. as the well - known econometrician clive granger4 said, “ it is worth remembering that consumers usually prefer having a choice. it is rare for one model to be superior for all possible purposes : forecasting, policy making, conditional forecasts,