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Measuring and explaining productivity change in U.S. manufacturing.

19 Jun 2019 - 5:00 pm - 8:00 pm

In this paper, measures of productivity change are defined as measures of output quantity change divided by measures of input quantity change. Measuring changes in output and input quantities (and therefore productivity) involves assigning numbers to baskets of outputs and inputs. Measurement theory says that so-called index numbers must be assigned in such a way that the relationships between the numbers reflect the relationships between the baskets. For example, if basket A contains exactly twice as much of every output as basket B, then the number assigned to basket A must be exactly twice as big as the number assigned to basket B. Superlative indices, as widely used by economists and statisticians to measure changes in productivity, yield numbers that are not generally consistent with measurement theory. This paper shows how to compute total factor productivity (TFP) index numbers that are consistent with measurement theory. It also shows how textbook stochastic frontier methods can be used decompose so-called proper TFP indices into measures of technical change, environmental change, efficiency change, and changes in statistical noise. In an empirical application, productivity change in U.S. manufacturing is found to be mainly driven by technical change and changes in scale and mix efficiency.


19 Jun 2019
5:00 pm - 8:00 pm
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TUM School of Management
Arcisstraße 21
München, 80333 Germany


Name (Seminar)
Christopher O'Donnell
Link Name (Seminar)
The University of Queensland
Johannes Sauer
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TUM School of Management
Arcisstraße 21
80333 Munich

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