You can get a DGSE model to tell you how a Bank of Canada rate hike is supposed to change the trajectory of inflation versus the path that it will follow if they keep rates steady. But the Bank of Canada's problem is that they do not know why inflation continues to be weaken this late in the expansion cycle, and so they have no idea what the inflation forecast should be for the case where rates are on hold.

A DSGE model will use variables like the output gap. But the main question in the U.S. is - how much slack is in the labour market? Is the fall in the Participation Rate legitimate or not? We do not know how to relate the observed variables (the Unemployment Rate, the Employment Ratio) to the corresponding DSGE model variable (the output gap).

Noah Smith wrote a post I was planning on writing: the most damning critique of Dynamic Stochastic General Equilibrium (DSGE) models is that no-one in the private sector uses them ...The reason I held back on writing the article is that I could not safely state that nobody in the private sector uses them, rather that I am unaware of anyone using them. And although I was in finance for 15 years, I was hardly the most connected person out there. (In fact, Tony Yates states that he was involved with some group that did use the models , so it's safe to say that theresome groups out there attempting to use DSGE models.)To my mind, the most basic reason they are not widely used is that they need to be determined via linearisation, which means that we are modelling the deviations of economic variables from a base case on the basis of some variable changing. (E.g., how much do trajectories move if the Fed hikes rates 50 basis points more than is forecast?)Policy makers have been conditioned to think that this mode of analysis represents best practice - they are focussed what is the impact of moving policy lever. However, reading the entrails of sacrificed animals used to be "best practice" in decision making The problem is simple: if we actually know what the base forecast is, why not use the technique that generated it to determine the new economic trajectory, rather than passing through the linearisation? For people in financial markets, the whole point of economic models is to determine the base forecast. Therefore, a technique that assumes you already know the base forecast is useless.Examples:And from an academic standpoint, the technique appears problematic as it largely cannot be falsified - any prediction errors can be explained by "random unforecastable shocks", parameter changes, or changes to the state around which you are taking the linearisation (which is the big excitement about the "Zero Lower Bound"). As Popper argued, any theory which is non-falsifiable tells us nothing useful.(c) Brian Romanchuk 2014