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4.4. INTRODUCTION TO THE CALIBRATION METHOD 1254.4 Introduction to the Calibration MethodThe Lucas model plays a central role in asset-pricing research. Chapter6 covers some tests of its predictions using time-series econometricmethods. At this point we introduce an alternative and popularmethodology called calibration. In the calibration method, the researchersimulates the model given ‘reasonable’ values to the underlyingtaste and technology parameters and looks to see whether thesimulated observations match various features of the real-world data.Because there is no capital accumulation or production, the technologyin the Lucas model is a stochastic process governing the evolutionof x t and y t . The reasonably simple mechanics underlying the modelmakes its calibration relatively straightforward. Our work here will setthe stage for the next chapter as real business cycle researchers relyheavily on the calibration method to evaluate the performance of theirmodels.Cooley and Prescott [33] set out the ingredients of the calibrationmethod proceeds as follows.1. Obtain a set of measurements from real-world data that we wantto explain. These are typically a set of sample moments suchas the mean, the standard deviation, and autocorrelations ofa time-series. Special emphasis is often placed on the crosscorrelationsbetween two series which measure the extent of theirco-movements.2. Solve and calibrate a candidate model. That is, assign values tothe deep parameters of tastes (the utility function) and technology(the production function) that make sense or that have beenestimated by others.3. Run (simulate) the model by computer and generate time-seriesof the variables that we want to explain.4. Decide whether the computer generated time-series implied bythe model ‘look like’ the observations that you want to explain. 66 The standard analysis is not based on classical statistical inference, although