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Tag Archives: economic modeling

Brian Romanchuk — Business Sector Is The Main Source Of Modelling Uncertainty

From the perspective of those who work or are interested in finance, it seems obvious that business decisions are a major driver of the business cycle, assuming that policymakers are not doing anything particularly stupid (as in the Euro area in the post-crisis period). The important exception is the housing market, which is dependent upon the willingness of households to borrow insane amounts of money. (However, even this exception is dependent upon the decisions of the financial sector to...

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Jason Smith — Three sigma deviation in the 10-year rate

Now you might wonder how raising interest rates to only about 2% could trigger a recession today in the same way raising interest rates to 14% did in the 80s. I admit I don't have a good answer to this except to say increasing labor force participation in the 80s probably provided a sufficient tailwind that Fed had to do do much more.In any case, this makes for an excellent test of the model. Interest rates should come back down in the near term (about 6 months). A possible mechanism to...

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Brian Romanchuk — Can We Falsify Models With Time-Varying Parameters?

In a previous article, I argued that having unknown fixed parameters within many economic models does not create much in the way of uncertainty: just extend the range of historical data available, and we can pin down the parameter values. This article covers a related case: what if we allow parameters to vary with time? This possibility will make it impossible to make reliable forecasts with the model. However, such models have another defect: they can be fitted to practically any data set,...

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Brian Romanchuk — Why We Should Be Concerned About The Forecastability Of Economic Models

Although it might be possible to find dissenters, the apparent consensus among financial market practitioners is that mathematical economic models provide terrible forecasts. One response is to keep searching through the set of all possible models, hoping to find something that works. The author's suggested response is to accept that forecasting is an inherently impossible task. However, in order to advance beyond nihilism, we need to quantify why mathematical models are terrible. My...

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Brian Romanchuk — Forecastability And Economic Modelling

When most people think about macroeconomics, what they want is the ability to forecast economic outcomes. However, economists' (of all stripes) reputation as forecasters is not particularly high. My view is that this is not too surprising: what we want forecasters to accomplish is probably impossible. (I am hardly the first person to note this, as variants of this idea go back at least to Keynes; I could not hope to offer a history of this idea.) However, I think if we want to approach...

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Peter Cooper — A Simple Framework for Analyzing a Demand-Led Economy

I have been thinking about a simple depiction of a demand-led economy. Mostly it draws on standard Keynesian macro, Kalecki’s work on cycles and growth, and supermultiplier models developed within the surplus approach. The main focus is on the evolution of a demand-led economy through time. The present post simply sketches the basic framework and provides some context. Perhaps in the future certain aspects can be fleshed out.... heteconomistA Simple Framework for Analyzing a Demand-Led...

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Brian Romanchuk — The Theoretical Incoherence Of Full Employment Arguments

One quite often runs into arguments that rely on assuming full employment, and then relating that policy decisions. In my view, such arguments are fundamentally weak; we need to refer to actual model results to discuss policy. In this article, I explain why an attempt to apply a NAIRU argument to a Job Guarantee is misguided. The analysis is unusual: instead of discussing a single model, the behaviour of an entire class of reasonable economic models is analysed. This reflects the attitude...

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Lars P. Syll — Rethinking expectations

The epistemological  and logic problems are not due to either models or their assumptions but rather misinterpreting what a model says about the world realisitically. Models are necessarily simplifications, since their purpose is to encapsulate as well as explain. The probems arise typically in assumptions about the application of models as accounts of real events.  A major issue is over-generalizing by taking a model that illustrates a special cases and extending its scope to other...

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