Mankiw on Greenspan and macro-economics:
Better monetary policy, he suggests, is more likely to follow from better data than from better models. Relatively little modern macro has been directed at improving data sources. Perhaps that is a mistake.
Methinks this same sentiment could be said of linguistics. However, I am ambivalent. On the one hand, I am trained in a department long dedicated to descriptive linguistics, so I’m frightened by the lack of good description for most of the world’s languages. I believe in supporting field linguists and old fashioned grammar writing tasks. But I’m equally frightened by the lack of good models of language, particularly of language change and evolution. I’m sympathetic to the recent flood of computationally minded engineers into the field of linguistics who have brought fresh approaches (e.g., statistical). Here’s a representative sample of very smart people bringing mathematical/computational modeling into linguistics:
Sandiway Fong -- U. Arizona
Partha Niyogi -- U. Chicago
Josh Tenenbaum -- MIT
Charles Yang -- U. Penn
2 comments:
Great list of people bringing computational/mathematical models to linguistics. I'm doing a literature review in a class on computational methods being applied to historical linguistics. Any other pointers?
Jason, thanks for the post. Partha Niyogi is spot on for this, but other than him, I'm not sure. I would check Joan Bybee's page to see if she references anything. Hope this helps.
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