Archive for 19 March 2008
Numbers Don’t Lie — Or Do They?
| Peter Klein |
Quantitative analysis leads to superior decision making, says Ian Ayres in Supercrunchers. Enthusiasts for expert systems are skeptical of “intuitive” reasoning. And most contemporary social scientists can’t conceive of a world without econometrics, sociometrics, psychometrics, and fill-in-the-blank-ometrics. Even management scholars are getting into the act. Of course, quantitative analysis is only as good as the assumptions that go into it. And economists such as Knight and Mises maintain that some kinds of human decision-making defy quantification and systematization and are fundamentally qualitative, or verstehende (explaining why some entrepreneurs earn profits while others make losses).
Wharton’s Gavin Cassar studies nascent entrepreneurs (defined here as firm founders) and finds, surprisingly, that those who use common accounting practices such as budgeting, sales forecasting, and financial planning are more likely to overestimate future performance than those who rely on qualitative, intuitive projections. “[T]hose individuals who adopt an inside view to forecasting, through the use of plans and financial projections, will exhibit greater ex-ante bias in their expectations. Consistent with inside view adoption causing over-optimism in expectations, I find that the preparation of projected financial statements results in more overly-optimistic venture sale forecasts.” In other words, quantitative analysis may exacerbate, rather than mitigate, cognitive bias. Worth a read (and see this summary in Knowledge@Wharton).
A New Explanation for Scholarly Productivity
| Peter Klein |
I always suspected it: scholarly productivity is inversely related to — beer. That’s the finding of a new study of Czech ornithologists, as summarized in yesterday’s N.Y. Times (thanks to Brian McCann for the heads-up). The more beer a scientist drinks, the less likely he is to publish or to have his work cited. Apparently this is a cross-sectional result, without fixed effects or instrumental variables, so there is little information on causality. Perhaps unsuccessful Czech scientists tend to drown their sorrows at the local pub (no doubt drinking their copycat Budvar). Personally, I am more likely to grab a brew to celebrate the occasional citation, so I’d expect the correlation (under reverse causality) to run the other way. And what about these rats?
Organizations and Markets 
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