Worst of all, when we feel pumped up with our progress, a tectonic shift can occur, like the Panic of 2008, making it seem as though our long journey has left us disappointingly close to the State of Complete Ignorance whence we began … It often takes years down the Path, but sooner or later, someone articulates the concerns that gnaw away in each of us and asks if the Assumptions are valid … It would be much healthier for all of us if we could accept our fate, recognize that perfect knowledge will be forever beyond our reach and find happiness with what we have … Can we economists agree that it is extremely hard work to squeeze truths from our data sets and what we genuinely understand will remain uncomfortably limited? We need words in our methodological vocabulary to
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Lars Pålsson Syll considers the following as important: Economics
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Many economists regularly pretend to know more than they do. Often this is a conscious strategy to promote their authority in politics and among policy makers. When economists present their models it should be mandatory that the models have warning labels to alert readers to the limited real-world relevance of models building on assumptions known to be absurdly unreal.
Economics may be an informative tool for research. But if its practitioners do not investigate and make an effort of providing a justification for the credibility of the assumptions on which they erect their building, it will not fullfil its task. There is a gap between its aspirations and its accomplishments, and without more supportive evidence to substantiate its claims, critics like yours truly will continue to consider its ultimate arguments as a mixture of rather unhelpful metaphors and metaphysics.
Nowadays it has almost become a self-evident truism among economists that you cannot expect people to take your arguments seriously unless they are based on or backed up by advanced econometric modelling. So legions of mathematical-statistical theorems are proved — and heaps of fiction are being produced, masquerading as science. The rigour of the econometric modelling and the far-reaching assumptions they are built on is frequently simply not supported by data. This is a dire warning of the need to change direction of economics.