jetpack domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /mnt/stor08-wc1-ord1/694335/916773/www.tvhe.co.nz/web/content/wp-includes/functions.php on line 6131updraftplus domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /mnt/stor08-wc1-ord1/694335/916773/www.tvhe.co.nz/web/content/wp-includes/functions.php on line 6131avia_framework domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /mnt/stor08-wc1-ord1/694335/916773/www.tvhe.co.nz/web/content/wp-includes/functions.php on line 6131I wouldn’t say that most forecasters are trying to answer the same question per see. Even if we were to say this was the case with “macro” forecasters, the difference is usual due to differing views of exogenous variables – where the dearth of relevant data is endemic and the appropriate way to model them is relatively disagreed upon 😉
In this context I would also note that, contrary to the way we often here macroeconomists argue they do actually provide relatively similar forecasts – I would say that the marginal value a forecaster adds has more to do with their ability to identify what elements will be more important for their client, and help to translate these forecasts into a usable and identifiable way to deal with risk. This makes the narrative component essential not just for helping to create the model – but for helping to create the output that clients value, which in turn explains why forecasters “sound” so different when their numbers are actually quite similar.
]]>Sure, but doesn’t only (2) matter for forecasters at the margin? They’re all trying to answer the same questions using pretty much the same data and models, after all.
]]>There are a few things that prevent that from being the case:
1) The fact that models are generally made to answer specific questions – there is no general model
2) The fact that there is missing data, implying that even if everyone was using the same objective model and data there is room for subjectivity in tying things together.
3) The model informs how you look at the data just as much as the data informs what model to pick.
Without a general model and a perfect information set, I find the idea of a uniquely “right” story disingenuous.
However, for a well specified question, and a given set of defined exogenous variables, we may be able to tie down a uniquely right story – but to me this relies a lot on how we define the question 😉
]]>
I think the difference between your descriptions and the rhetorical approach here is the separation of model and story. I thought you might consider the story a consequence of the model, which might result in one uniquely ‘right’ story.
]]>I’m not sure why you thought I would disagree with this at all – given it is exactly the type of argument I’ve long held onto for economic modeling.
]]>