The 2013 version of the model can be found here

www.newyorkfed.org/medialibrary...

In contrast to the Bank of England model the New York Fed model has quite an extensive description of how financial conditions can impact lending and the macroeconomy. The New York Fed wants this in the main model instead of being explained by a satelite model.

That means they all have many features and specifications in common. They are also much smaller than the simultaneous equation models we have introduced, with fewer sectors/features.

This model has been around in various editions for decades. The latest version can be found here.

papers.ssrn.com/sol3/papers....

This ability to have a wide range of sectors included is one of the great strengths of simultaneous equation models. If you remember, the fully theory derived DSGE of the bank of England didn't have these. It's that trade-off between theoretical coherence and the ability to match the data.

The model can be found here

www.econstor.eu/bitstream/10...

...too invariant structural features of the economy. These models also haven't been mainstream academic models for decades. As a result, the upkeep and theory of these models is largely maintained within a handful of large institutions like central banks.

This allows the model to explicitly include energy and a financial sector. This allows the model to be used to analyze things like the energy price spike that followed Russia's invasion of Ukraine target than relying on satellite models. The flip side is that the equations aren't directly tied...

For further details see the link

rharrisonmacro.github.io/workingpaper...

This choice can be attractive if explaining 'what if' scenarios and the mechanisms behind them is an important part of the forecasting process.

The small stylized nature of the model means it sacrifices fit for theoretical coherence. Understanding core mechanisms > explaining the data. Other model types we will see make other choices.

It's quite a small model, without a financial sector. This might seem strange for a central bank, but financial issues are analyzed with other satellite models. Because it ignores many real world issues, the model is small and easier to understand.

They are like maps that contain only the most important information for the task at hand. A hiking map is different than a driving map. Different types of models have different strengths and weaknesses, which leads to trade-offs as described nicely by Pagan's report to the Bank of England.

After all, if you are trying to produce forecasts, a model with the correct equations accurately reflecting the relationships between variables will produce the most accurate forecasts. The answer is that models are simplified versions of reality.