Skill Policies for Scotland

In Diane Coyle, Wendy Alexander, and Brian Ashcroft, eds., New Wealth for Old Nations: Scotland’s Economic Prospects, Princeton: Princeton University Press, pp. 119-165. (2005)
Skill Policies for Scotland
James J.Heckman, Dimitriy Masterov
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eBay Authors
Abstract

This paper argues that skill formation is a life-cycle process and develops the implications of this insight for Scottish social policy. Families are major producers of skills, and a successful policy needs to promote effective families and to supplement failing ones. We present evidence that early disadvantages produce severe later disadvantages that are hard to remedy.

We also show that cognitive ability is not the only determinant of education, labor market outcomes and pathological behavior like crime. Abilities differ in their malleability over the life-cycle, with noncognitive skills being more malleable at later ages. This has important implications for the design of policy. The gaps in skills and abilities open up early, and schooling merely widens them.

Additional university tuition subsidies or improvements in school quality are not warranted by Scottish evidence. Company sponsored job training yields a higher return for the most able and so this form of investment will exacerbate the gaps it is intended to close.

For the same reason, public job training is not likely to help adult workers whose skills are rendered obsolete by skill-biased technological change. Targeted early interventions, however, have proven to be very effective in compensating for the effect of neglect.

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Proceedings of the Sixteenth ACM Conference on Economics and Computation (EC '15). ACM, New York, NY, USA (2015)

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Reputation and feedback systems in online marketplaces are often biased, making it difficult to ascertain the quality of sellers. We use post-transaction, buyer-to-seller message traffic to detect signals of unsatisfactory transactions on eBay. We posit that a message sent after the item was paid for serves as a reliable indicator that the buyer may be unhappy with that purchase, particularly when the message included words associated with a negative experience. The fraction of a seller's message traffic that was negative predicts whether a buyer who transacts with this seller will stop purchasing on eBay, implying that platforms can use these messages as an additional signal of seller quality.

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