and forecasting which can answer all potential policy questions. therefore, central banks need multiple models for policy advice. some macroeconomic and econometric models which central banks use nowadays include univariate, reduced - form, simultaneous equation, state - space, semi - structural, bayesian methods and dynamic stochastic general equilibrium models ( dsge models ). let me now turn to the evolution of the macroeconomic models at central banks over the years. macroeconomic modeling experienced a paradigm shift after the general acceptance of the lucas critique and the emergence of rational expectations theory. this in effect rendered simultaneous equation models, which were popular until the late seventies, obsolete and unleashed a revolution in the form of real business cycle ( rbc ) theory. lucas posited that as the behavior of economic agents adapts to changes in the economic structure, policy advice based on models becomes increasingly useless. to address the lucas critique, 1 / 3 bis central bankers'speeches macroeconomists came forward with models that contained stronger micro foundations. this class of models dates back to 1982 and is today classified as dsge models. in later incarnations, a wider set of distortions and a host of shocks came to play a larger role in these macroeconomic models. for instance, the incorporation of nominal frictions in rbc theory transformed these models into new keynesian dsge models. the popularity of such models among central banks has grown manifold, mainly due to their ability to explain how nominal shocks can create real impacts in the short - run. over time, these models have become workhorse policy analysis tools, especially for monetary policy advice, scenario analysis and forecasting. alongside standard micro founded dsge models, central bankers also utilize reduced - form versions of dsge models, including forecasting and policy analysis system ( fpas ) and quarterly projection models ( qpm ), for policy advice and forecasting. like dsge, these models also serve as useful tools for shock decomposition and scenario analysis. in terms of the use and advancement of macroeconomic models, the role of central bank researchers has been stellar in recent years. researchers at major central banks have developed in - house dsge models, calibrated on specific characteristics in their economies. today many central banks, both in developed and emerging market economies ( emes ) have developed their own models and central banks in saarc countries are no exception. central banks in some of the saarc countries have invested heavily in human resources and computational tools for

building dsge and fpas models tailored to particular dynamics of their economies. in addition to dsge and fpas models, central banks also make use of various small - scale and special purpose models called satellite models that help bring an independent perspective into policy formulation. due to their ability to outperform dsge models in short - term forecasting, such models can supplement the medium to long - term forecasting process of dsge models. finally, let me touch upon some best practices of central banks with regard to the use of macroeconomic models. central banks usually follow a modular approach in building macroeconomic models. initially, they build smaller models, and then gradually expand them by incorporating sectoral dynamics, rigidities and shocks. these theoretically rich empirical models can later be integrated with core models, if deemed necessary. this modular approach enables economists to understand key transmission channels and policy tradeoffs. another major benefit in constructing such a suite of analytical tools is to minimize forecast uncertainty. in this regard several central bankers utilize bayesian forecast combination and model averaging. from a practical perspective, lack of high frequency data, especially on quarterly national income accounts ( nia ), restricts business cycle analysis. several saarc countries including pakistan do not publish such quarterly data and this severely constrains short - run macroeconomic analysis as well as limits utility of dsge models. to help address this issue, nowcasting information from competing models can be used as external inputs to improve dsge and fpas model forecast performance over a short - term horizon. such high frequency information could include independent forecaster ’ s views on output and inflation developments, expectations of the short - term interest rate and long - run output growth and inflation expectations. ladies and gentlemen, let me end by noting that the development of the macroeconomic models is a continuous process. central bankers continuously tinker and enhance models by incorporating real world macroeconomic events, crises, and new computational techniques. in this context, the challenge that covid - 19 has posed in terms of economic data and modelling has no recent parallel. predicting the trajectory of macroeconomic variables was rarely as difficult as it is today, given their dependence on health factors. recent research proposes integrated 2 / 3 bis central bankers'speeches epidemiological and macroeconomic models to analyze the interplay between the covid - 19 outbreak and macroeconomic activity. 1 these models generally link covid - 19 and labor supply decisions to the current state of the disease progression, allowing for relevant